United States 

Department of 

Agriculture

Forest Service

Pacific Southwest 

Research Station

General Technical 

Report

PSW-GTR-238

April 2012

Proceedings of the Coast Redwood 

Forests in a Changing California: 

A Symposium for Scientists and 

Managers
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Technical Editors

Richard B. Standiford is a Cooperative Extension Forest Management Specialist, University of 

California, Berkeley Center for Forestry 94720. Theodore J. Weller is an ecologist, U.S. 

Department of Agriculture, Forest Service, Pacific Southwest Research Station, 1700 Bayview 

Drive, Arcata, CA 95521. Douglas D. Piirto is a professor and head of the Natural Resources 

Management Department, California Polytechnic State University, 1 Grand Ave., San Luis 

Obispo, CA 93407. John D. Stuart is a professor, Department of Forestry & Wildland 

Resources, Humboldt State University, 1 Harpst St., Arcata, CA 95521

Papers were provided by the authors in camera-ready form for printing. Authors are responsible 

for the content and accuracy. Opinions expressed may not necessarily reflect the position of 

the U.S. Department of Agriculture. 

The use of trade or firm names is for reader information and does not imply endorsement by the 

U.S. Department of Agriculture of any product or service.

Cover Images: Steve Sillett 
i 

Proceedings of the Coast 

Redwood Forests in a Changing 

California: A Symposium for 

Scientists and Managers

Technical Editors

Richard B. Standiford, Theodore J. Weller, Douglas D. Piirto, and John D. 

Stuart

June 21–23, 2011

University of California, Santa Cruz

U.S. Department of Agriculture

Forest Service

Pacific Southwest Research Station

Albany, Calfornia

General Technical Report PSW-GTR-238

April 2012

iii

Proceedings of the Coast Redwood Forests 

in a Changing California: A Symposium for 

Scientists and Managers

Abstract

Standiford, Richard B.; Weller, Theodore J.; Piirto, Douglas D.; Stuart, John D., tech. 

coords. 2012. Proceedings of the coast redwood forests in a changing California: a 

symposium for scientists and managers. Gen. Tech. Rep. PSW-GTR-238. Albany, CA: 

U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station. 

675 p. 

The Coast Redwood Forests in a Changing California Science Symposium was 

held June 21-23, 2011, at UC Santa Cruz with just under 300 registrants in 

attendance. Participants ranged in background from graduate-level students to 

university forestry faculty, land managers, conservation groups, public agencies, 

and land trust members. The symposium was strategically held in Santa Cruz, 

near the southern end of the redwood region. Designed to present the state of our 

knowledge about California’s coast redwood forest ecosystems and sustainable 

management practices, this symposium was built on earlier redwood science 

symposia held in Arcata, CA, in June, 1996 and in Santa Rosa, CA, in

March, 2004. 

The first day of the symposium consisted of two simultaneous field tours, one to 

the North County and one to the South County. The North County tour focused 

on active redwood timber management on corporate ownerships operating under 

the unique policies that dictate decisionmaking on the central coast, and CalPoly’s forest management and research at its Swanton Pacific Ranch. It also 

included a brief tour of the Big Creek Lumber Company sawmill and a visit to 

areas burned in the more than 7,000-acre Lockheed Fire of 2009. The South 

County tour traversed the range of redwood forest conditions from the old growth 

of Henry Cowell State Park and the uncut 120 year old young growth of Nisene 

Marks State Park to uneven-aged young-growth stands established by individual 

tree selection harvesting on nonindustrial forest lands.

Opening remarks started the second day of the symposium and began the 

academic concurrent sessions. Local historian Sandy Lydon spoke about the 

special history of the redwoods in the region, recounting stories from his boyhood 

about roaming through the forests and giving a brief synopsis of the settlement of 

the area. Steve Sillett, Humboldt State University forestry professor, described his 

experiences climbing the redwoods and his discoveries in the redwood forest 

canopy ecosystems, as well as his findings on tree growth from 

dendrochronology measurements. Ruskin Hartley, Executive Director and 
iv

Secretary of Save the Redwoods League, called on the audience to set “audacious 

goals and collaborative actions.” He maintained that nature does not develop 

boundaries and that in moving forward, we should focus on a shared set of goals 

and that public and private land should progress simultaneously. Concluding the 

session, Ron Jarvis, Home Depot’s VP of sustainability talked candidly about the 

role of environmental sustainability practices and policies as part of the home 

improvement retailer’s business model. He noted that when he began in the 

sustainability department, he undertook a 2-year long project to understand where 

every sliver of wood from over 9,000 products originated to ensure sustainable 

wood practices. 

Over 75 concurrent oral presentations were showcased over 2 days, pertaining to 

the topics of: Ecology (15 presentations); Silviculture and Restoration (11 

presentations); Watershed and Physical Processes (22 presentations); Wildlife, 

Fisheries, Aquatic Ecology (10 presentations); Forest Health (10 presentations); 

Economics and Policy (6 presentations); Monitoring (7 presentations). In 

addition, almost 40 posters were displayed during the evening reception, ranging 

in topic from postfire response, to long-term watershed research, and community 

forestry models. Held outside on the warm Santa Cruz evening, participants 

enjoyed a strolling dinner and networking with colleagues, making the reception 

a highlight of the symposium. 

The symposium concluded with closing remarks about the future of research in 

the redwood region from John Helms, UC Berkeley and Mike Liquori, Sound 

Watershed. In addition, a panel including Dan Porter, the Nature Conservancy, 

Lowell Diller, Green Diamond, and Kevin O’Hara, UC Berkeley discussed the 

interface of research, management, and conservation. The overall discussion led 

to the conclusion that academic research and applied research should be made 

available to the field as a whole as findings progress and that more opportunities 

for networking and interactions should be made available to the forestry 

community. 

Overall, the symposium fulfilled its purpose to identify key knowledge gaps, 

bring together multidisciplinary teams, and help identify future opportunities for 

collaboration. Participants were pleased with the presenters and research shown. 

Many noted that a highlight of the symposium was being able to meet and 

interact with others whose works they had previously cited in their own research. 

Of the approximately one half of participants who completed the followup 

survey, 100% hoped to see more events like the 2011 Redwood Symposium. 
v 

Acknowledgments

Program Committee

Richard B. Standiford, UC Berkeley Center for Forestry, 510-643-5428, email:standifo@berkeley.edu 

Douglas D. Piirto, Cal Poly San Luis Obispo, Cal Poly San Luis Obispo, 805-756-

2968, e-mail: diirto@calpoly.edu 

John D. Stuart, Humboldt State University, 707-826-3823, e-mail: 

jds2@humboldt.edu 

Sherry Cooper, UC Ag. And Nat. Res., 530-752-1581, e-mail: slcooper@ucdavis.edu

Theodore J. Weller, Pacific Southwest Research Station, 707-825-2955, e-mail: 

tweller@fs.fed.us

Coordinated by

University of California, Berkeley, Center for Forestry and College of Natural 

Resources

University of California, Division of Agriculture and Natural Resources 

Cal Poly San Luis Obispo, Natural Resources Mgt. Dept. and College of Ag., Food 

and Envir. Sciences 

Humboldt State University. Dept. of Forestry and Wildland Resources and College of 

Natural Resources and Sciences 

Co-sponsors 

Big Creek Lumber 

California Board of Forestry 

California Forestry Association

California Redwood Association 

California State Parks 

ESRI

Green Diamond Resource Company 

Humboldt Redwood Company 

L.W. Schatz Demonstration Tree Farm, Humboldt State University

Mendocino Redwood Company 

The Nature Conservancy

Northern California Society of American Foresters 

Save the Redwoods League 

USDA Forest Service, PSW Research Station

Steering Committee

Leonell Arguello, Redwood National Park 

Pascal Berrill, Humboldt State University 

Sherry Cooper, UC Div. of Ag and Nat. Res. 

Neal Ewald, Green Diamond Resource Company. 

Mike Furniss, PSW Redwood Sciences Lab 

Greg Giusti, UC Cooperative Extension 

Ruskin Hartley, Save-the-Redwoods League 

Russ Henly. California Dept. of Forestry and Fire Protection

Mike Jani, Humboldt Redwood Company, LLC 
GENERAL TECHNICAL REPORT PSW-GTR-238

vi

Janet McCrary Webb, Big Creek Lumber

Brendan O’Neill, California State Parks 

Doug Piirto (co-chair), California Polytechnic State University 

Dan Porter, The Nature Conservancy

Scott Sink, California Polytechnic State University

Richard B. Standiford (co-chair), Univ. of Calif. Center for Forestry 

Steve Staub, RPF 

John Stuart (co-chair), Humboldt State University 

Brad Valentine, Calif. Dept. Fish & Game

Yana Valachovic, UC Cooperative Extension 

Session Chairs

Watershed Processes: Mike Furniss, PSW Redwood Sciences Lab

Ecology: Emily Limm, Save the Redwoods League; Dan Porter, The Nature 

Conservancy 

Forest Health: Kim Camilli, Calfire/Cal Poly San Luis Obispo; Walter Marks, Cal 

Poly San Luis Obispo 

Wildlife, Fisheries, Aquatic Ecology: Brad Valentine, CA Dept. Fish and Game 

Silviculture, Restoration: Scott Sink, Cal Poly San Luis Obispo, Pascal Berrill, 

Humboldt State Univ.

Monitoring: Helge Eng, Calfire

Economics, Policy: Rich Thompson, Cal Poly San Luis Obispo 
vii

Contents

KEYNOTE ADDRESS 1

Redwood Forest Conservation: Where Do We Go From Here? 3

Ruskin K. Hartley 

WATERSHED PROCESSES 11

Road Surface Erosion on the Jackson Demonstration State Forest: 

Results of a Pilot Study 13

Brian Barrett, Rosemary Kosaka, and David Tomberlin 

Total Maximum Daily Loads, Sediment Budgets, and Tracking 

Restoration Progress of the North Coast Watersheds 23

Matthew S. Buffleben 

Logging-Related Increases in Stream Density in a Northern California 

Watershed 33

Matthew S. Buffleben 

Physics-Based Simulations of the Impacts Forest Management Practices 

Have on Hydrologic Response 41

Adrianne Carr and Keith Loague 

Erosion at Decommissioned Road-Stream Crossings: Case Studies from 

Three Northern California Watersheds 53

Sam A. Flanagan, David Fuller, Leonard Job, and Sam Morrison 

Large Woody Debris Budgets in the Caspar Creek Experimental 

Watersheds 61

Sue Hilton 

Sediment Production in a Coastal Watershed: Legacy, Land Use, 

Recovery, and Rehabilitation 69

Elizabeth T. Keppeler 

Declining Sediment Loads from Redwood Creek and the Klamath River, 

North Coastal California 79

Randy D. Klein and Jeffrey K. Anderson 

The VTAC Committee: Developing Guidance for an Alternative 

Regulatory Pathway to the Anadromous Salmonid Protection Rules 89
viii

Michael Liquori, Peter Cafferata, Kevin Boston, Richard Gienger, 

and David Hope 

Assessing Effects of Changing Land Use Practices on Sediment Loads 

in Panther Creek, North Coastal California 101

Mary Ann Madej, Greg Bundros, and Randy Klein 

Fine Sediment Sources in Coastal Watersheds with Uplifted Marine 

Terraces in Northwest Humboldt County, California 111

Stephen Sungnome Madrone and Andrew P. Stubblefield 

Comparison of Estimated and Measured Sediment Yield in the Gualala 

River 121

Matthew O’Connor, Jack Lewis, and Robert Pennington 

Fluorometry as a Bacterial Source Tracking Tool in Coastal Watersheds, 

Trinidad, CA 131

Trever Parker and Andrew Stubblefield 

Use of BasinTemp to Model Summer Stream Temperatures in the South 

Fork of Ten Mile River, CA 141

Rafael Real de Asua, Ethan Bell, Bruce Orr, Peter Baker, and Kevin 

Faucher 

Comparing Hydrologic Responses to Tractor-Yarded Selection and 

Cable-Yarded Clearcut Logging in a Coast Redwood Forest 151

Leslie M. Reid

Landslides After Clearcut Logging in a Coast Redwood Forest 163

Leslie M. Reid and Elizabeth T. Keppeler 

The Impact of Timber Harvest Using an Individual Tree Selection 

Silvicultural System on the Hydrology and Sediment Yield in a Coastal 

California Watershed 173

Arne Skaugset, Christopher G. Surfleet, and Brian Dietterick 

Summer Water Use by Mixed-Age and Young Forest Stands, Mattole 

River, Northern California, U.S.A. 183

Andrew Stubblefield, Max Kaufman1, Greg Blomstrom, and John 

Rogers 

Sediment Yield Response to Sediment Reduction Strategies 

Implemented for 10 Years in Watersheds Managed for Industrial 

Forestry in Northern California 195
ix

Kate Sullivan 

An Approach to Study the Effect of Harvest and Wildfire on Watershed 

Hydrology and Sediment Yield in a Coast Redwood Forest 205

Christopher G. Surfleet, Arne Skaugset, and Brian Dietterick 

Delineation of Preventative Landslide Buffers Along Steep Streamside 

Slopes in Northern California 213

Jason S. Woodward, David W. Lamphear, and Matthew R. House 

ECOLOGY 225

Responses of Redwood Soil Microbial Community Structure and N 

Transformations to Climate Change 227

Damon C. Bradbury and Mary K. Firestone 

Rangewide Genetic Variation in Coast Redwood Populations at a 

Chloroplast Microsatellite Locus 241

Chris Brinegar 

Reference Conditions for Old-Growth Redwood Restoration on Alluvial 

Flats 251

Christa M. Dagley and John-Pascal Berrill

Fog and Soil Weathering as Sources of Nutrients in a California 

Redwood Forest 265

Holly A. Ewing, Kathleen C. Weathers, Amanda M. Lindsey, Pamela 

H. Templer, Todd E. Dawson, Damon C. Bradbury, Mary K. 

Firestone, and Vanessa K.S. Boukili 

Foliar Uptake of Fog in the Coast Redwood Ecosystem: a Novel 

Drought-Alleviation Strategy Shared by Most Redwood Forest Plants 273

Emily Limm, Kevin Simonin, and Todd Dawson 

A Chronosequence of Vegetation Change Following Timber Harvest in 

Naturally Recovering Coast Redwood (Sequoia sempervirens) Forests 283

Kristin K. Hageseth Michels and Will Russell

Accounting for Variation in Root Wood Density and Percent Carbon in 

Belowground Carbon Estimates 293

Brandon H. Namm and John-Pascal Berrill

Response of Montia howellii (Howell’s montia) to Road Management in 

California Coastal Timberlands 303
x 

Maralyn A. Renner, James Regan, and Mark Colosio 

‘Pygmy’ Old-Growth Redwood Characteristics on an Edaphic Ecotone 

in Mendocino County, California 313

Will Russell and Suzie Woolhouse 

Size Distribution of Unharvested Redwood Forests in Mendocino 

County 323

Bradley E. Valentine 

Structure and Dynamics of an Upland Old-Growth Forest at Redwood 

National Park, California 333

Phillip J. van Mantgem and John D. Stuart 

FOREST HEALTH 345

Damage and Mortality Assessment of Redwood and Mixed Conifer 

Forest Types in Santa Cruz County Following Wildfire 347

Steve R. Auten and Nadia Hamey 

Decomposition and N Cycling Changes in Redwood Forests Caused by 

Sudden Oak Death 357

Richard C. Cobb and David M. Rizzo 

Post-fire Response of Coast Redwood One Year After the Mendocino 

Lightning Complex Fires 363

Robert B. Douglas and Tom Bendure 

The Effects of Sudden Oak Death and Wildfire on Forest Composition 

and Dynamics in the Big Sur Ecoregion of Coastal California 373

Margaret R. Metz, Kerri M. Frangioso, Ross K. Meentemeyer, and 

David M. Rizzo 

Regeneration and Tanoak Mortality in Coast Redwood Stands Affected 

by Sudden Oak Death 377

Benjamin S. Ramage, Kevin L. O’Hara, and Alison B. Forrestel

WILDLIFE, FISHERIES, AQUATIC ECOLOGY 387

Sonoma Tree Vole Habitat on Managed Redwood and Douglas-fir 

Forestlands in North Coastal California 389

Sal J. Chinnici, David Bigger, and Eric Johnson 
xi

Two Decades of Research and Monitoring of the Northern Spotted Owl 

on Private Timberlands in the Redwood Region: What do We Know and 

What Challenges Remain? 399

Lowell Diller, Keith Hamm, David Lamphear, and Trent McDonald 

How Do We Know How Many Salmon Returned to Spawn? 

Implementing the California Coastal Salmonid Monitoring Plan in 

Mendocino County, California 409

Sean P. Gallagher and David W. Wright 

Ecology and Management of Martes on Private Timberlands in North 

Coastal California 419

Keith A. Hamm, Lowell V. Diller, David W. Lamphear, and Desiree 

A. Early

A Permeability Study on Salmonid Spawning Areas in Northern 

Humboldt County, California 427

Claire Knopf 

Mesocarnivores as Focal Species for the Restoration of Post-Logging 

Second Growth in the Northern Redwoods 437

Keith M. Slauson 

Northern California Redwood Forests Provide Important Seasonal 

Habitat for Migrant Bats 447

Theodore J. Weller and Craig A. Stricker 

Measurements of Key Life History Metrics of Coho Salmon in Pudding 

Creek, California 459

David W. Wright, Sean P. Gallagher, and Christopher J. Hannon 

SILVICULTURE AND RESTORATION 471

Coast Redwood Live Crown and Sapwood Dynamics 473

John-Pascal Berrill, Jesse L. Jeffress, and Jessica M. Engle 

Influence of Tree Spatial Pattern and Sample Plot Type and Size on 

Inventory Estimates for Leaf Area Index, Stocking, and Tree Size 

Parameters 485

John-Pascal Berrill and Kevin L. O’Hara 

Management Practices Related to the Restoration of Old Forest 

Characteristics in Coast Redwood Forests 499
xii

Gregory A. Giusti 

Carbon Storage in Young Growth Coast Redwood Stands 515

Dryw A. Jones and Kevin L. O’Hara 

Variable-Density Thinning in Coast Redwood: a Comparison of 

Marking Strategies to Attain Stand Variability 525

Kevin L. O’Hara, Lathrop P. Leonard, and Christopher R. Keyes 

The Scotia Plantation: Implications for Multiaged and Even-aged 

Silviculture 527

Kevin L. O’Hara 

Coast Redwood Responses to Pruning 529

Kevin L. O'Hara 

Using FORSEE and Continuous Forest Inventory Information to 

Evaluate Implementation of Uneven-aged Management in Santa Cruz 

County Coast Redwood Forests 539

Douglas D. Piirto, Scott Sink, Dominic Ali, Steve Auten, Christopher 

Hipkin, and Reid Cody 

Using Wood Quality Measures to Evaluate Second-Growth Redwood 553

Stephen L. Quarlesand Yana Valachovic 

Forest Restoration at Redwood National Park: a Case Study of an 

Emerging Program 561

Jason R. Teraoka 

Whiskey Springs Long-Term Coast Redwood Density Management; 

Final Growth, Sprout, and Yield Results 571

Lynn A. Webb, James L. Lindquist, Erik Wahl, and Andrew Hubbs 

ECONOMICS 583

Observations About the Effectiveness of Utilizing Single Tree Selection 

Silviculture in Redwood Forestlands 585

Bob Berlage and the Big Creek Lumber Company Forestry 

Department Staff 

The Watershed TMP: a Proposal to Manage the Redwood Ecosystem 

Under Convergent Environmental, Economic and Social Goals 593

Frederick D. Euphrat 
xiii

Protecting Forests Across Landscapes and Through Generations: the 

Sonoma County Forest Conservation Working Group 603

Frederick D. Euphrat, Steven Swain, Dee Swanhuyser, Jill Butler, 

Amy Chesnut, Kim Batchelder, Caerleon Safford, and Earle 

Cummings 

California’s Coast Redwood in New Zealand 611

Tom Gaman

Subdivide or Silviculture: Choices Facing Family Forest Owners in the 

Redwood Region 617

William Stewart, Shasta Ferranto, Gary Nakamura, Christy Getz, 

Lynn Huntsinger, and Maggi Kelly 

Is it Economical to Manage Jointly for Wood and Carbon Under the 

Climate Action Reserve Protocol? 627

Richard P. Thompson and Steve R. Auten

MONITORING 637

Comparing LiDAR-Generated to Ground-Surveyed Channel CrossSectional Profiles in a Forested Mountain Stream 639

Brian C. Dietterick, Russell White, and Ryan Hilburn 

Tree Height Estimation in Redwood/Douglas-fir Stands in Mendocino 

County 649

Helge Eng

Prioritizing Treatment of Second-Growth Forests Using LiDAR 655

Lathrop P. Leonard and Daryl Van Dyke 

Land Surface Phenology as a Coarse-Filter Indicator of Disturbance and 

Climatic Effects Across the Coast Redwood Range 657

Steven P. Norman and William W. Hargrove 

Use of LiDAR and Multispectral Imagery to Determine Conifer 

Mortality and Burn Severity Following the Lockheed Fire 667

Russell A. White and Brian C. Dietterick 

Keynote Address

3 

Redwood Forest Conservation: Where Do 

We Go From Here?1

Ruskin K. Hartley2

Abstract

One hundred and nine years after the first redwoods were set aside in public ownership, the 

redwood movement has come a long way. For most of the public, “saving redwoods” has 

meant placing threatened giants in parks and reserves—Big Basin State Park (1902), Muir 

Woods National Monument (1908), Humboldt Redwoods State Park (1921), Redwood 

National Park (1968), and the Headwaters Forest Reserve (1999). But after a century when 

more than 95 percent of the ancient redwoods were felled and most of the large groves are 

protected in public parks and reserves, what does it mean to save the redwoods today? If for 

the first 100 years saving meant buying and placing in public ownership, I argue that for the 

next 100 years, saving will mean working together to restore the forest, whether in public or 

private ownership. In a time of rapid climate change, it also means the arbitrary lines we’ve 

drawn on a map to denote public and private ownership become increasingly irrelevant. We’ll 

need a new paradigm to think about building resilience and adaptability to climate change into 

the system to benefit public and private owners. What science is needed to guide these 

efforts? Do practitioners have the tools they need? How can we do this in a way that makes 

economic sense for private companies and the public good? And most importantly, how can 

we engage and gain the support of a skeptical public more used to liquidation lumbering than 

restorative forestry? If we do it right, it can be a model for how forests around the world are 

managed; if we fail we risk losing the redwood forest we all love.

Save the redwoods! 

Save the Redwoods! There’s a lot packed into these three simple, evocative 

words. What has this meant in the past, where has it put us today, and what will it 

mean as we look ahead? For much of the last 150 years, saving the redwoods has 

meant setting land aside in parks and reserves. In fact the earliest acts of preservation 

in the United States were inspired by the coast redwood and its relative, the giant 

sequoia or sierra redwood. 

In 1852 the sierra redwoods of Calaveras County were discovered by Augustus 

T. Dowd. Within a year, the “Discovery Tree” had become “Big Stump.” In large 

measure, it was this act of destruction that inspired the drive to protect the sierra 

redwood of Mariposa Grove and Yosemite Valley in 1864. The five-page report to 

Congress included a full four pages talking about the folly of what occurred at 

Calaveras and how it must be prevented at Mariposa, leaving one page on the need to 

protect the valley. When Abraham Lincoln signed the legislation, it was the first time 

that land had been set aside land for its preservation and the enjoyment of future 

 

1 A keynote address presented at the redwood science symposium: coast redwood forests in a changing 

California, June 21-23, 2011, Santa Cruz, California. 2 Executive Director and Secretary, Save the Redwoods League, 114 Sansome Street, San Francisco, CA 

94104. (rhartley@Savetheredwoods.org).
GENERAL TECHNICAL REPORT PSW-GTR-238

4 

generations, rather than its exploitation today. This far-sighted act was taken at a time 

that the country was engulfed in civil war. 

The term “save the redwoods” was coined in the early 1900s here in the Santa 

Cruz Mountains as the rallying cry for citizens working to protect the California 

Redwood Park, what is now Big Basin. It was driven by a desire to ensure ordinary 

people could come and enjoy these majestic groves that then were all privately 

owned. In 1902 they were successful in persuading the state legislature to purchase 

the groves at what would become the heart of Big Basin Redwoods State Park. 

Save the Redwoods was also the name chosen for my organization, Save the 

Redwoods League. When it was founded in 1918, its goal was clear: to save from 

destruction representative samples of the primeval redwood forest for people’s 

enjoyment, education and inspiration. I think it is no coincidence that while the 

organization was founded by scientists, its early leadership came from marketing 

geniuses such as Stephen Mather. Mather is best known as the National Park 

Service’s first director and the man who created the 20 Mule Team Borax brand—

registered in 1894 and still available today. Newton Drury, was the League’s first 

executive secretary; also a marketing executive who went on to direct both California 

State Parks and the National Park Service. 

They knew that our movement all started with a clear name and purpose. And for 

many years our movement’s name and a simple message—shall it be this (a pristine 

forest), or this (an apocalyptic image of a recently harvested forest)—galvanized a 

nationwide movement that has been remarkably successful in protecting primeval 

forest in public parks. 

But it’s no longer enough to simply purchase land to prevent something bad from 

happening. We’re in the middle of a paradigm shift in redwood protection. The next 

era has to involve protection and restoration. Rather than conflict, it will require 

collaboration. And rather than building legal fences around land, it will require 

thinking and acting across boundaries. 

But I don’t think we should underestimate the challenge ahead when dealing with 

the redwoods. They have always, and will always, stir a deep emotional response. 

Take a recent edition of Parade, read by an estimated 74 million people each Sunday 

over their morning coffee. It recently published a “bucket list” of 32 “essential 

experiences every American should have.” Among “watching a lawnmower race” 

and “admiring the pyramids of Las Vegas,” was “Standing at the base of a really tall 

tree: like one of Northern California’s redwoods or giant sequoias.” But while the 

same list encouraged readers to “Visit a farm” noting that “meeting the men and 

women who grow your food can be fascinating and fun.” There was no mention of 

visiting a “working forest” or acknowledgment that growing wood can be fascinating 

and fun. 

At a recent dinner in DC someone asked me if the last mill in Fort Bragg had 

closed down. When I replied “yes,” much of the table cheered and I found myself 

talking about how forestry was now an important part of the conservation landscape. 

Forestry, I believe, is not well understood in mainstream America. 

Our research shows the average American loves redwoods, and assumes that all 

redwoods are saved—probably in public ownership—unless of course, the last 
Redwood Forest Conservation: Where Do We Go From Here?

5 

redwood was actually cut. And if they think about it at all, they feel guilty at the 

thought of building a deck from redwood. Yet at the same time, they probably don’t 

think twice about the total environmental cost of a composite plastic deck. 

These two emotions—reverence for parks and guilt, or worse yet ignorance, over 

what's happening outside them—have defined the last 100 years of work in the 

redwoods. It’s been easy to juxtapose "parks" as protected and everything else at risk. 

In the meantime, good practices on private land have gone unrecognized. And the 

impact of benign neglect on our parkland—which contrary to popular opinion is not 

and never has been pristine—is poorly understood. 

If we are to succeed in saving the redwoods for the next 100 years, we're going to 

need new thinking, new action, and new leadership. 

But first, where do we stand today? 

We estimate the coast redwood ecosystem covered 2 million acres before 

European settlement of Northern California. Since settlement, 25 percent of the 

redwood forest ecosystem has been lost to land conversion—farming, homes, and 

more recently vineyards. Of the remaining 1.5 million acres, only 117,600 acres are 

old-growth (representing about 5.6 percent of the historical 2 million acres). Most of 

this old-growth is in public ownership (90,700 acres), but public redwood forestlands 

overall are actually 73.5 percent second-growth (251,000 of 341,800 total acres) and 

share many of the same conditions as private redwood forestlands.

In general, the last 100 years has been underpinned by an assumption of stability. 

We have assumed that we can set land aside, “unimpaired... for the enjoyment, 

education, and inspiration of this and future generations,” to quote from the National 

Park Service mission statement. Implicit in this statement is that the land was pristine 

to start with and that the mere act of reserving it will protect it. It is now clear that 

most land has been affected by humans for millennia and that the environmental 

baseline has never been stable, and that today it is changing more rapidly than ever 

before as the Earth warms, population grows, and we mix species up. 

In 1850, the world’s population stood at 1.27 billion, while California had a scant 

92,000. In 2011, the world’s population crossed the 7 billion threshold and California 

stood at 37 million—a ten-fold increase since the establishment of the State Park 

system in 1927. Meanwhile, the concentration of carbon dioxide in the atmosphere 

has increased from an estimated level of 280 parts per million (ppm) in 1850 to over 

394 ppm by May 2011. As the Economist recently noted, we may have already 

moved from the stability of the 10,000 year Holocene, to an era of rapid change 

starting to become known as the “anthropocene.” 

At the same time, the institution that Save the Redwoods League established in 

the 1920s to manage the land we saved—California State Parks—is also suffering. In 

California we’re now having a serious discussion about the wisdom of closing 70 

parks. In fact, a cartoon editorial in a recent Sacramento Bee summed up the sorry 

state of park funding with a picture of an ancient redwood in the park being cut down 

for a deck. 
GENERAL TECHNICAL REPORT PSW-GTR-238

6 

The landscape today 

So what does the forest landscape look like today? Not only are we down to 5 

percent of the original forest uncut, but much of the rest of the forest is near a historic 

low point in terms of its standing inventory. It’s no wonder that so many species that 

depend on intact old-growth forest are teetering on the brink of extirpation here in 

California, marbled murrelet and coho salmon being the most notable examples. 

We stand at a historic turning point in history of the redwood forest. Over the last 

few months I have visited forests from Monterey County in the south to Del Norte 

County in the north, and toured parks and working lands with the people who manage 

them. I find that the issues across the coast redwoods’ range are remarkably similar – 

and while every place has a different history, they all share a common theme. Much 

of the landscape is in various states of recovery from the era of liquidation logging. 

And while the canopy has grown up, the legacy of past management is alive and well 

in the network of roads and stands of dense young forests—coppiced redwoods, 

Douglas-fir thickets and tan oak groves. 

The overarching need is to restore the ecological capacity of these once great 

forests, both for their habitat value and their economic value. And while doing so we 

need to build public support for responsible forest management. 

We’re dealing not only with a long-lived species, but a long collective memory 

of the actions of the past. This image of past management is burned into the 

collective memory of the public. The era of “timber mining” in California—where 

the forest across entire watersheds was slicked off, leaving the naked Earth as a stark 

reminder—may be long gone in reality, but it is alive and well in the public psyche. 

Likewise the misperception that public land is primarily pristine old-growth is just 

wrong. 

Let’s take two members of the public known to many of you: Steve Sillett and 

Mike Jani. I think you’ll agree they’re pretty knowledgeable about redwoods! On a 

recent trip to HRC’s timberland in and around Elk and Freshwater Creek—the center 

of much of the conflict of the past 20 years—Steve Sillett noted he was expecting 

dinky trees and bare earth and was surprised by what he actually saw—a healthy, 

albeit young, forest. And Mike Jani expressed surprise at how much of the park land 

was actually young forest—very similar to the land he’s managing for HRC and 

MRC—rather than the pristine old-growth he imagined. 

Because both our public and private lands have experienced a similar 

management history, it’s not surprising that their conditions are similar today. If you 

take one simple measure, size-class as measured by the CalVeg 2009, you’ll see the 

distribution is remarkably similar across different ownerships. 

What perhaps is a surprise is that the actions being taken today to manage them 

in the near-term are similar, whether you’re on public or private land. Since 1973 and 

the introduction of the Forest Practice Act in California, forest management has 

undergone a sea change and it continues to evolve. We now have a diversity of 

practices across the landscape. In essence, we have a large-scale experiment spanning 

the range of the redwoods. In the last few months I have been in the woods with 

many of you, from Monterey County to Del Norte County, and seen the diversity of 

approaches underway: 
Redwood Forest Conservation: Where Do We Go From Here?

7 

• While even-age management still occurs, managers are leaving structure to 

protect riparian corridors and key landscape features. Give this land another 

decade and it will look very different to the even-age management of the 

past. 

• Selection harvest and thinning is happening across the region — in some 

regions as general practice and in others as an experiment 

• Selection harvest has been practiced here in the Santa Cruz Mountains for a 

generation – with some stands now on their third entry. And in Mendocino 

County, we’ve now had a decade of uneven-age management by Mendocino 

Redwoods Company and we’re starting to see difference it makes on the 

landscape. And conservation groups, such as The Conservation Fund, are 

using similar approaches to manage the forests they own. 

• Land managers as diverse as Redwood National Park, Mendocino Redwood 

Company, and the Land Trust of Santa Cruz County are conducting 

commercial age thinning designed to accelerate growth and grow big trees in 

time. 

• And California State Parks, the Bureau of Land Management and many 

private owners are conducting pre-commercial thinning to accelerate growth 

and affect species composition. 

I have also seen many innovative restoration efforts. 

• Creative work to manage habitat for the northern spotted owl – owls on 

Green Diamond ownership are about to break 2000. 

• Large woody debris installations – moving from engineered log dams, to 

carefully placed free-form structures, to simply dumping wood in the creek 

and allowing it to move at will. 

• Road removals, upgrades, new culverts and new bridges to protect and 

restore habitat for wild salmon and trout. 

Across the range there is a great deal of innovation and experimentation. These 

are happening culvert by culvert, stream by stream, watershed by watershed, 

ownership by ownership. It’s happening on public and private land, on large and 

small ownerships alike. 

I am left wondering which of today’s activities will become tomorrow’s regret—

the equivalent of the often-told tale of coastal stream woody debris removal in the 

1970s and 1980s. We’re putting a lot of faith into single species management for 

northern spotted owls, even as the barred owl moves in. Or into riparian protection on 

class I and II streams, when we know that the water and sediment ultimately flows 

from entire watersheds. And setting a 12-foot diameter limit to thin trees on public 

land when we know it will seriously constrain management options. 
GENERAL TECHNICAL REPORT PSW-GTR-238

8 

What we need is a larger vision for the restoration of the 

redwoods 

What we need is a larger vision to tie all these pieces together—an audacious 

goal and a collective framework for our actions, for our public investments, one to 

help us monitor and learn from our successes and failures. What would it take to: 

• Double the acreage of forest set on a trajectory toward old-growth? 

• Double the land base dedicated to permanent forest uses and protected 

against land use conversion – either as parks or working lands? 

• Double the productive capacity of the redwood region to produce a greater 

volume of high-quality wood products? In other words, sustain a higher level 

of yield from an older and more complex forest? 

And how can we do this in a time of change, where the audacious goal of permanent 

protection—which for the last century has essentially meant freezing the status quo—

needs rethinking for the century ahead? 

Solving this would increase the odds that the redwood forest ecosystem will 

continue to thrive, that the parks will be vibrant places that can adapt to change, that 

high- quality redwood products can reclaim their place in the marketplace, and 

meanwhile the redwood forest would be capturing and storing carbon and helping 

mitigate the impacts of climate change. It would also be a model for other forest 

systems around the world. 

We’re fortunate that in the redwood region today we have a remarkable 

opportunity to be successful. Ironically, the legendary economic value that drove the 

liquidation logging has also driven consolidation of ownership. And today, the land 

tenure pattern is such that we can think, plan, and act at a landscape scale. And at the 

landscape scale, there’s enough space for a diversity of actions from pure ecological 

restoration to sustained production. It’s when we try to meet all our goals on every 

acre that we run into conflict. 

Moving toward this vision will require: 

• New thinking. It starts by thinking holistically about the entire landscape. 

Nature has never respected legal boundaries or been concerned about single 

species. We need to develop a shared set of goals that we can start to lay 

explicitly onto the landscape. 

• New action. We need to create a unity of action among non-traditional 

partners. To get comfortable with ecologically based restoration management 

that may involve selling wood from public lands to offset project costs once 

all ecological goals are met. Or creating incentives for long-term stewardship 

on private land — rather than looking first to the certainty of the regulatory 

stick. It’s time to reward landowners willing to grow their forests longer 

while leaving the big old trees that have survived alone. 

• New leadership. Individuals willing to stand up and partner with their 

traditional adversaries. To talk about the positive benefits of sensitive 
Redwood Forest Conservation: Where Do We Go From Here?

9 

forestry on private land. Or the need to expand parks and connect them 

together so they can adapt to climate change. 

So what role does science have to play in all of this? There is in effect a giant 

experiment underway across the redwoods, whether we acknowledge it or not. 

Everyday we're making decisions on where and how to harvest, how much wood to 

remove in a thinning project, how to approach a road removal project, or install wood 

into streams. In many instances data is being collected to evaluate the effect of that 

treatment. But it's often not shared, or collected in a way that makes comparison 

between sites meaningful. Science can help shape a framework to help us understand 

the impact of our actions.

This grand experiment also lacks a control. Where on the landscape are we 

letting nature run its course so we can really understand the impact of our action? 

Without this control we'll always be left wondering. I don’t mean a small-scale 

project-based control; I mean a watershed-scale control where we’re committed to 

leaving it alone and letting nature reign. Science can help identify these places. 

We lack a clear ecological basis for restoration that can be understood by the 

public and is readily translatable into management actions. What are the ecological 

criteria that should be deployed in developing a restoration treatment and what 

should we measure to monitor progress? There’s a lot of discussion about density 

targets, basically measuring the density of a nearby old-growth stand and using 

thinning to cut down to that level. This simple structural approach to restoration is a 

start, but how can we marry this with a process-based approach in a way that can be 

deployed in the field? 

Scientists and practitioners need more opportunities to work together. As a minor 

example, too often I have spoken to a land manager who simply can’t get access to 

the current literature because the subscription is too costly. This conference is a great 

start, but it needs to be sustained. Ultimately it’s about building trust and 

relationships between academia and practitioners. And while we’re doing all of this, 

we need to acknowledge uncertainty and proceed with humility—essentially adopting 

our own version of the Hippocratic Oath, to do no harm. 

I wanted to return to that bucket list of 32 essential American experiences and the 

vision I have of what saving the redwoods could mean in the future. One of the things 

on my bucket list was to climb Kilimanjaro and see the endless Africa plains. I had 

the chance to do that a number of years ago when I visited Tanzania. On the edge of 

Tarangire National Park we climbed a lookout tower where we could look one way 

into the park, and the other way out to the surrounding plains. The interpretive panels 

discussed the conservation work going on both inside and outside the park. Why do I 

need to go to Africa to see that? 

I imagine climbing up through the old- growth redwoods in Humboldt Redwoods 

State Park to the ridge that divides Bull Creek from Bear Creek. Perhaps to a new 

lookout where to the south you can see the restoration work underway in the park and 

to the north the management underway on the private timberland. And not only 

understanding the role each plays, but feel proud that I am supporting both—through 

my tax dollars supporting the park and through my purchase of redwood timber 

supporting the responsible management of the surrounding landscape. 
GENERAL TECHNICAL REPORT PSW-GTR-238

10

As I described earlier, the redwoods of Yosemite, Santa Cruz and Humboldt 

County have been at the heart of the conservation movement here in California and in 

fact across the United States. We now have a unique opportunity to put them there 

again as we start to work together at a landscape scale. We’ve made significant 

progress toward this since we met in Rohnert Park 5 years ago. I am optimistic that 

by the time we meet again in 5 years time, we’ll be further down this path.
Watershed Processes

13

Road Surface Erosion on the Jackson 

Demonstration State Forest: Results of a 

Pilot Study1

Brian Barrett2, Rosemary Kosaka3, and David Tomberlin4

Abstract

This paper presents results of a 3 year pilot study of surface erosion on forest roads in the 

Jackson Demonstration State Forest in California’s coastal redwood region. Ten road 

segments representing a range of surface, grade, and ditch conditions were selected for the 

study. At each segment, settling basins with tipping buckets were installed to measure coarse 

sediment and total runoff. Laboratory analysis of Total Suspended Solids (TSS) samples from 

the runoff provided estimates of fine sediment production. 

Although the limited scope of our study prevented statistical analysis of site variables, several 

lessons emerged that may be useful to future studies. Total sediment production (fine and 

course) ranged from negligible (0.02 kg/m2

/yr) to more than 4.5 kg/m2/yr, and varied greatly 

from year to year on most sites, in some cases by an order of magnitude. The share of TSS in 

yearly total sediment production also varied greatly from year to year. While site 

characteristics offer partial explanations of the results for each site, we found large variations 

among sites with similar characteristics. Lastly, the study required significant effort but was 

useful in providing site specific results; the variability in site characteristics adds to the 

challenge of understanding sediment production from forest roads. 

Key words: Forest roads, surface erosion, coarse sediment, suspended sediment, runoff

Introduction

This paper describes instrument and study design, data collection, and empirical 

results from a 3 year pilot study of surface erosion associated with forest roads on the 

Jackson Demonstration State Forest (JDSF) in California’s coast redwood region. 

The study was a joint effort by the California Department of Forestry and Fire 

Protection (CAL FIRE) and the National Marine Fisheries Service (NOAA 

Fisheries). Our goals were to assess the method and to collect data over a 

representative range of conditions. 

Increasing our understanding of road surface erosion will help land managers and 

resource agencies improve watershed management. Watershed processes are complex 

and our pilot study is not definitive. While our study is too limited to support strong 

 

1 Results from the first year of this study were presented in Barrett and Tomberlin (2007).

2 CAL FIRE, Jackson Demonstration State Forest, 802 North Main St., Fort Bragg, CA 95437; 707-964-

5674 ext.117. (brian.barrett@fire.ca.gov). 3 NOAA Fisheries, Southwest Fisheries Science Center, 110 Shaffer Rd., Santa Cruz, CA 95060; 831-

420-3988. (rosemary.kosaka@noaa.gov). 4 NOAA Fisheries, Office of Science and Technology, 1315 East-West Hwy., Silver Spring, MD 20911; 

301-713-2328. (david.tomberlin@noaa.gov).
GENERAL TECHNICAL REPORT PSW-GTR-238

14

conclusions, a broader-scale application of the methods described here could provide 

a basis for assessing the predictive power of erosion simulation models and help to 

inform priorities for restoration funding. 

METHODS

Study area and site characteristics

The 10 road segments (sites) in this road surface erosion study are located on the 

JDSF in Mendocino County, California. The study area has a Mediterranean climate, 

with most of the precipitation (annual mean = 1.16 m) occurring as rainfall from 

November through April. The area is mountainous, with elevations ranging from sea 

level to 880 m (2,850 ft). Topography is generally steep and dissected as a result of 

rapid uplift rates. Underlying geologic materials are dominated by coastal belt 

Franciscan sandstone, and soils range from gravelly loam to fine-grained with a high 

clay content.

Study sites were chosen to represent a range of surface, grade, and ditch 

conditions typical of forest roads in the redwood region. Site selection was also 

influenced by operational considerations such as placement on the hillslope, travel 

distances, and risk of vandalism. Individual sites varied in topography, cut-bank 

height, ditch vegetation, overhead canopy, and year of construction or maintenance. 

Road surface conditions were also variable. Some native surface roads contained a 

fraction of native rock, while rocked roads had variations in the condition of applied 

rock. The road segments were selected from the existing network of crowned roads 

with inside ditches and ditch relief culverts, representative of many roads on the 

JDSF and in the region, but different from roads that utilize outsloping and rolling 

dips. This road type provided reasonable hydrologic isolation without re-construction 

or the construction of new roads. Road maintenance consisting of grading to clear 

ditches of soil and debris, smoothing the road surface, and removing brush for 

vehicle clearance, was implemented under normal scheduling on the existing road 

network and not controlled for the study. An example of a study site can be seen in 

fig. 1. Basic information on the sites is presented in table 1. 

Surface flow on each road segment flowed to an inside ditch, from which a 

culvert directed it to devices that measured runoff and sediment production, as 

described below. Thus, the inside ditch was part of the road segment profile, although 

its relative contribution to sediment production is unknown. The catchment area for 

runoff on each site was measured from the base of the cut bank to the estimated 

crown of the road that served as a “water divide.” Sporadic surface flow was 

observed from cut banks at four sites and varied with storm intensity. Because the

actual catchment area for each segment could not be known precisely and likely 

varied to some extent with rainfall intensity, we have explored the sensitivity of our 

results to potential measurement error. However, in this paper we report results based 

on the single catchment area value deemed most probable for each segment. 

Instrument design and calibration

Our method of estimating runoff and sediment production was based on a design 

by Black and Luce (2007). Each site had a settling basin that captured coarse 

sediment generated on the road segment, a tipping bucket with event logger that 

enabled estimation of total runoff, and a splash device that collected a subsample
Road Surface Erosion on the Jackson Demonstration State Forest: Results of a Pilot Study

15

Figure 1—Site 8, December HY07, showing rocked road surface following summer 

grading.

Table 1—Site characteristics for HY05 to HY06. Minor changes in catchment area during the 

study period are not reflected here but were captured in calculation of results. Road 

maintenance did not occur for sites 3, 4, 5, 9, and 10 during the study period. 

Site

(road 

segment)

Surface Winter

traffic

Ditch

(percent 

vegetated)

Grade Area

(m2) 

Road 

maintenance 

(grading)

1 (1000-1) Native Light 10% 6% 1031 Prior to HY05, 

HY07

2 (240-1a) Native None 0% 4% 716 Prior to HY06

3 (90-1) Native None 10% 6% 634

4 (210-2) Native None 10% 6% 778

5 (210-1) Native None 10% 7% 560

6 (240-1) Native None 0% 9% 399 Prior to HY06

7 (600-4) Rocked Light 75% 4% 757 Prior to HY07

8 (620-4) Rocked Light 30% 7% 452 Prior to HY07

9 (640-7) Rocked Light 30% 7% 723

10 (640-1) Rocked Light 20% 4% 573

of the runoff for analysis of suspended solids. A 5 ml subsample (circa 0.05 percent 

of tipping volume) was collected at each tip of the approximately 10 L bucket and 

flowed through a flexible tube into a closed 19 l (5 gal) bucket, which acted as a 

reservoir for composite post-storm sampling. An example can be seen in fig. 2. 

Each tipping bucket was calibrated by providing flow at a known rate, using a 

flow meter, and recording the resulting duration between tips. Repeating this 

procedure with different flow rates enabled estimation of a calibration curve relating 
GENERAL TECHNICAL REPORT PSW-GTR-238

16

flow rate to duration between tips. Durations recorded by the data logger could then 

be used in conjunction with the calibration curves to estimate runoff on each 

segment, generating a hydrograph for each segment throughout the winter season. 

Figure 2—Site 10 in operation with coarse sediment collection tank, tipping bucket, 

and suspended sediment sample bucket with tubing.

Data collection and analysis

Runoff and suspended solids data were collected throughout the rainy season. 

Regular visits, sometimes several per week, to the study sites were necessary to 

download tipping times from the event loggers. When the 19 l buckets containing 

splash samples were nearing capacity, or when a sample had not been taken for 

several weeks, a mechanically agitated composite sample was collected from the 

buckets for analysis of suspended solids at a commercial laboratory using the EPA 

160.2 protocol (1999). We measured total suspended solids (TSS) rather than 

suspended sediment concentration (SSC) due to budget considerations and the 

finding in Gray and others (2000) that these measures differ little when the 

proportion of coarse sediment is small. In our study, because the settling basin 

captured most of the coarse sediment before TSS samples were taken, we did not 

expect TSS and SSC to differ markedly. 

The coarse sediment captured by each settling basin was weighed at the end of 

the hydrologic year with a 2,000 kg (+/- 500 g) electronic dynamometer/crane scale. 

Each settling basin was topped off with water and the tank containing sediment and 

water was weighed and compared to the weight of the tank and water without 
Road Surface Erosion on the Jackson Demonstration State Forest: Results of a Pilot Study

17

sediment. These mass estimates were used to estimate the mass of dry sediment, as in 

Black and Luce (2007). 

Results

Precipitation patterns and changes in site characteristics (largely due to road

maintenance) are keys to interpreting our results. According to data from the U.S. 

Forest Service (USFS) Redwood Sciences Lab, precipitation at the South Fork 

Caspar Creek weir, located on the JDSF, totaled 1.69 m in HY06 (defined as 8/1/05 

to 7/31/06), 0.86 m in HY07, and 1.00 m in HY08. Mean annual rainfall measured at 

the weir during 1963 to 2010 was 1.16 m (L. Keppler and J. Seehafer, USDA Forest 

Service, personal communication, 6/15/11). 

Figure 3 shows total runoff (in kl/m2

) at each study site. Note that runoff data 

from sites 1 and 10 were not collected in HY08 due to constraints on staff time for 

travel to remote locations. 

Figure 3—Total runoff (kl/m2) for each site, HY06 to HY08. Data are normalized by 

area. Runoff was not collected for sites 1 and 10 in HY08. 

Figure 4 shows annual sediment production per square meter on each road 

segment. Total sediment production ranged from negligible (0.02 kg/m2

/yr) to more 

than 4.5 kg/m2

/yr, and varied greatly from year to year on most sites, in some cases 

by an order of magnitude. While the highest-producing road segments were native 

surface segments, one native surface segment (site 4) produced less sediment on 

average than three of the four rocked surface segments. 

Assuming a road surface bulk density of 1,600 kg/m3

 (Coe 2006), the sediment 

production rates given in fig. 4 correspond to surface depth loss rates of 0.03 mm/yr 

to 2.85 mm/yr. The share of suspended solids in total sediment production generally 

ranged from 30 percent to 90 percent, with a mass-weighted mean of 52 percent. 
GENERAL TECHNICAL REPORT PSW-GTR-238

18

Figure 4—Fine and coarse sediment production (kg/m2

) for each site, HY06 to HY08.

Data are normalized by area. Sites 1 through 6 are native surface roads while sites 7 

through 10 are rocked surface roads. Fine sediment was not collected for sites 1 and 

10 for HY08. Dots indicate sites where grading occurred in 1 or 2 previous hydrologic 

years (see table 1). 

Discussion

Our results indicate that both total sediment production rates and the share of 

suspended sediment in total sediment differ greatly among sites and over time. Site 1 

alone produced 45 percent of the total sediment produced on all the sites during the 

study period, despite the fact that fine sediment production data was not collected on 

this site in the final year. Site 4, in contrast, produced less than 1 percent of the total. 

Some of this variation can be attributed to known site characteristics, for example, 

site 1 has the greatest area, receives some light winter traffic, and was the only one 

graded prior to HY05. All four of the highest-producing segments in our study are 

native surface segments, but two native surface segments (sites 4 and 5) produced 

sediment at rates similar to the rocked segments. 

As shown in fig. 4, the four highest annual sediment production totals were on 

road segments that had been recently graded to clear ditches of debris and smooth the 

road surface. This complicates the relationship between rocked and native surface 

roads because grading may have contributed more to sediment production than 

surface type. In the case of site 1, the first grading was prior to HY05 but the effects 

of grading appeared to be evident in HY06. Sediment production at sites without 

grading declined through the 3 year study period, except site 2 which increased 

slightly. Other factors, such as geology, topography, and ditch function, no doubt 

played a role as well, but we did not have sufficient data to support a statistical 

analysis of factors influencing variability in sediment production. Further, more data 

and analysis of erosion rates, rainfall intensities, and grading histories would be 

necessary to assess a cause and effect relationship between erosion and grading. For 

example, a simple conclusion that grading alone causes subsequent erosion does not 
Road Surface Erosion on the Jackson Demonstration State Forest: Results of a Pilot Study

19

consider the possibility that some road segments may have inherent design flaws 

leading to more frequent grading. 

Two points are particularly worth noting in interpreting our results. First, HY06 

was a very wet year (147 percent of average), and accounted for an estimated 70 

percent of total sediment production on our study sites over the three-year period. 

Second, we have not attempted to control for the influence of traffic, since all our 

road segments are either closed in winter or are believed to be used by 10 or fewer 

light-duty vehicles (pickups and sedans) per week. 

Our results are generally comparable to erosion measurements made in other 

forested areas of California. An application of the Water Erosion Prediction Project 

(WEPP) simulation model (Ish and Tomberlin 2007) generated a mean long-term 

surface erosion rate estimate of 4.14 kg/m2

 on native surface roads in our study area, 

which is similar to the higher sediment production rates shown in fig. 4. In studies 

from the interior portions of California, Coe (2006) reported a 16-fold difference in 

median sediment production rates between rocked and native road segments in the 

central Sierra Nevada, while Korte and MacDonald (2007) found that native and 

mixed surface roads (0.7 kg/m2

/yr) produced approximately three times the sediment 

as gravel surfaced roads (0.23 kg/m2

/yr) in the southern Sierra Nevada. 

The results presented here are not definitive, as they represent data from only 

three years, and we have not yet fully explored the sensitivity of the results to 

uncertainties about sediment concentrations, catchment areas, and equipment 

function. A particularly important example of the latter was marked differences in the 

calibration coefficients for some tanks before and after the rainy season. Because we 

cannot know the rate at which the calibration coefficients changed during the season, 

the results reported here are based on a simple linear interpolation over time between 

the pre- and post-season calibration coefficients. Examining the sensitivity of our 

results to other possible patterns of change in the calibration coefficients—for 

example, such that the initial coefficients were operative until the last day of the 

season, or that the final coefficients were operative after the first day of the season—

showed that the results were not very sensitive to this source of uncertainty. 

Additionally, several known technical problems add to the uncertainty in our 

results. Because HY06 was a heavy rain year, 47 of 338 total data downloads (14 

percent) indicated that the data logger had filled, resulting in some lost data. There 

was also some minor equipment damage due to site visitors, for example, on two 

occasions the tubing directing runoff subsamples to a collection reservoirs were 

removed. On site 7, an old buried culvert was found to be directing a significant 

amount of water from the study segment under the road and away from our 

instruments, which may explain the observed increase in runoff during the later, drier 

years of the study. We changed the filter size for TSS analysis from 1.5 to 1.0 

microns after the first year, which increased by an unknown amount the estimated 

fine sediment production levels in HY07 and HY08 relative to what would have been 

captured with a 1.5 micron filter. 

There are important questions related to road surface runoff and erosion that are 

beyond the scope of our study. We have not attempted to develop a statistical 

analysis of the factors contributing to road sediment production nor to assess delivery 

of sediment to the stream network. We did not do a comprehensive assessment of the 

share of organic material in our TSS samples, though in tests on a small (n=12) 
GENERAL TECHNICAL REPORT PSW-GTR-238

20

number of runoff samples the share of organics in TSS was found to be as high as 18 

percent. This suggests that on some sites distinguishing organic from inorganic 

sediment would be important to estimating mineral sediment production. 

The goals of this study were more limited: 1) to examine the feasibility of a 

particular approach to estimating road surface erosion in the redwood region, and 2) 

to generate estimates of sediment production on an existing network of crowned 

roads with inside ditches. The results presented here suggest that the method 

generates useful information, and clearly demonstrate that the application of generic 

rules of thumb to estimate sediment production at a given site may result in gross 

errors. The information, however, comes at a significant cost: instrumentation at each 

site cost approximately $1,800; project initiation and data collection during the first 

year required approximately one staff person per year; and maintenance, data 

collection, and analysis in subsequent years required approximately half of one staff 

person per year. However, it may be possible to lower costs and improve 

measurement accuracy by reducing the tank size on sites anticipated to have lower 

sediment production. 

Conclusion

This pilot study of forest road surface erosion demonstrated remarkable 

variability among sites and years in the production of both fine and coarse sediment. 

Although the methodology was successful in providing site specific data on sediment 

production, the variability of site characteristics and small number of segments limits 

the ability to make conclusions. The results showed rocked road segments produced 

less sediment than most native surface segments, though two native surface segments 

produced amounts comparable to the rocked segments. The native surface roads with 

the highest sediment production had also been graded so it is unknown if the high 

production was the result of the surface type, grading, site characteristics, or a 

combination of factors. The share of fine sediment in total sediment was also highly 

variable, but generally more than 30 percent and in some cases almost 90 percent.

These results, taken cumulatively, offer a cautionary tale about the perils of 

estimating sediment production based on rules of thumb. 

The chief advantage of the method applied here is that it can provide useful, sitespecific estimates of both fine and coarse sediment production. The disadvantages are 

that the method is expensive and labor-intensive, requiring significant staff time for 

data collection, analysis and equipment maintenance. 

Acknowledgments

This project has been funded by the National Marine Fisheries Service (NOAA 

Fisheries) and the California Department of Forestry and Fire Protection (CAL 

FIRE). We thank C. Luce (USFS) for advice on instrument and study design. We also 

thank B. Baxter (CAL FIRE), P. Cafferata (CAL FIRE), J. Griffen (CAL FIRE), L. 

Keppeler (USFS), J. Lewis (USFS), and J. Seehafer (USFS) for helpful discussions 

and suggestions; R. Collins (CAL FIRE), B. Salee (CAL FIRE), J. Bawcom (CAL 

FIRE), R. Hundt (CAL FIRE), B. Perez (CAL FIRE), M. Lombardi (CAL FIRE), and 

A. D’Albert (CAL FIRE) for field work; S. Weir (CAL FIRE) and the Department of 

Corrections inmates at Parlin Fork Conservation Camp for manufacturing the tanks; 
Road Surface Erosion on the Jackson Demonstration State Forest: Results of a Pilot Study

21

the CAL FIRE Fire Crews from Chamberlain Creek Conservation Camp for 

manually weighing the coarse sediment; A. Mamula (NOAA Fisheries), C. Thomson 

(NOAA Fisheries), and two anonymous reviewers for their comments and 

suggestions; and M. Jameson (CAL FIRE) and C. Thomson (NOAA Fisheries) for 

material support and for providing us time to work on this project. 

References

Barrett, B.; and Tomberlin, D. 2007. Sediment production on forest road surfaces in 

California’s redwood region: results for hydrologic year 2005-2006. In: Sustaining 

America’s Forests: Proceedings of the Society of American Foresters 2007 National 

Convention, October 23-27, Portland, OR. Available at: 

http://www.safnet.org/fp/documents/sediment_production_forest_roads_07.pdf

Black, T.A.; Luce, C.H. 2007 (8/15/07 version). Measuring water and sediment discharge 

from a bordered road plot using a settling basin and tipping bucket. Boise, ID: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain Research Station. 37 p. 

http://www.fs.fed.us/GRAIP/downloads/NewRoadPlotv3.pdf. 

Coe, D.B.R. 2006. Sediment production and delivery from forest roads in the Sierra 

Nevada, California. Fort Collins, CO: Colorado State University. M.S. thesis. 110 p.

http://www.fire.ca.gov/cdfbofdb/pdfs/DrewCoe_FinalThesis.pdf. 

Gray, J.R.; Glysson, G.D.; Turcios, L.M.; Schwartz, G.E. 2000. Comparability of 

suspended-sediment concentration and total suspended solids data. WaterResources Investigations Report 00-4191. Reston, VA: U.S. Department of the Interior, 

U.S. Geological Service. http://water.usgs.gov/osw/pubs/WRIR00-4191.pdf. 

Ish, T.; Tomberlin, D. 2007. Simulation of surface erosion on a logging road in the 

Jackson Demonstration State Forest. In: Standiford, R.; et al., editors, Proceedings of 

the redwood science symposium. Gen. Tech. Rep. PSW-GTR-194. Albany, CA: U.S. 

Department of Agriculture, Forest Service, Pacific Southwest Research Station: 457-

463. http://swfsc.noaa.gov/publications/FED/00697.pdf. 

Korte, A.; MacDonald, L.H. 2007. Preliminary summary: sediment production and 

delivery in the southern Sierra Nevada. Unpublished draft (3/1/07 version). Fort 

Collins, CO: Watershed Science Program, Colorado State University. 11 p. 

U.S. EPA. 1999 (revised 11/16/99). Total suspended solids (TSS), EPA method 106.2 

(gravimetric, dried at 103-105 C). Data quality indicator tables. Pacific Southwest, 

Region 9. http://www.epa.gov/region9/qa/datatables.html. 

23

Total Maximum Daily Loads, Sediment 

Budgets, and Tracking Restoration 

Progress of the North Coast Watersheds1

Matthew S. Buffleben2

Abstract

One of the predominate water quality problems for northern coastal California watersheds is 

the impairment of salmonid habitat. Most of the North Coast watersheds are listed as 

“impaired” under section 303(d) of Clean Water Act. The Clean Water Act requires states to 

address impaired waters by developing Total Maximum Daily Loads (TMDLs) or 

implementing another program that will result in the attainment of water quality standards. 

TMDLs are an estimate of the maximum load necessary to meet water quality standards. In a 

general sense, a TMDL and its implementation plan is a water quality attainment strategy and 

provides a framework for assessing the watershed condition, evaluating the sources of 

pollution contributing to the water quality impairment, and developing a water quality 

restoration plan for the watershed.

Sediment budgets are useful tools to evaluate sediment impacts to water quality and channel 

morphology. As part of the TMDL development process, sediment budgets have been 

developed for twenty northern California watersheds. Anthropogenic activities such as 

logging and its associated road building, which commonly occur in this region, have 

dramatically increased sediment loading rates. TMDL studies estimate that is will take several 

decades or more for streams to transport the excess sediment out of the watersheds.

Tracking recovery of the watersheds from sediment impairments over time will be difficult. 

The Regional Water Board will use several tools to verify that progress is being made. These 

tools include sediment budgets, as well as monitoring hillslope and water quality conditions in 

the listed watersheds.

Key words: sediment budgets, targets, TMDLS, trend monitoring

Introduction

Over 40,000 water bodies in the United States do not meet the Clean Water Act 

goals of restoring and maintaining the chemical, physical, and biological integrity of 

the nation’s waters (USEPA 2009). Excessive sediment has impaired the beneficial 

uses of water for nearly 6,500 waterbodies (USEPA 2009). In the North Coast 

Region of the California Regional Water Quality Control Board, several salmonid 

species are listed under the Endangered Species Act. In particular, the Central 

California Coast Coho populations in the southern portion of the range appear to be 

either extinct or nearly so, including those in the Gualala, Garcia, and Russian rivers 

(Good et al. 2005). Although there are several factors involved in the decline of 

 

1 This paper was presented at the redwood science symposium: June 21-23, 2011, Santa Cruz, 

California. 2 California Regional Water Quality Control Board, North Coast Region, Santa Rosa, CA 95403. 

(mbuffleben@waterboards.ca.gov).
GENERAL TECHNICAL REPORT PSW-GTR-238

24

salmonids, the destruction and modification of habitat are the primary reasons for 

decline in the western United States (National Marine Fisheries Service 2007).

Anthropogenic activities such as logging and its associated road building, which 

commonly occur in northern coastal California, can dramatically increase sediment 

loading rates (Gomi et al. 2005, Reid 1993). The increased sediment supply can 

negatively impact salmonid habitat in several ways. Excessive fine sediment can 

prevent adequate water flow through salmon redds, the nest in the stream substrate 

formed by a female salmonid in which eggs are laid, fertilized and incubated. 

Excessive fine sediment in the redd can cause a high level of mortality by limiting the 

oxygen supply to salmon eggs and preventing the removal of metabolic wastes 

(Chapman 1988). Increases in sediment supply can also decrease the pool depth and 

pool size (Lisle and Hilton 1999), which reduces rearing habitat for salmonids. 

Decreases in clarity due to suspended sediment can cause direct effects, such as 

mortality, and indirect effects like decreases in growth rates due to reduced food 

supply (Newcombe 2003). 

Excessive sediment can also impair drinking water supplies, which is another 

concern in some North Coast watersheds. Also, excessive sediment can lead to 

changes in stream channel morphology. Aggradation, the filling in of a stream 

channel by sediment which raises the level of the streambed, may lead to decreased 

channel capacity, which can cause an increase in flooding frequency, magnitude and 

duration (Knighton 1998). This increase in flooding can cause property damage or 

result in nuisance conditions by limiting access for landowners.

Sediment budgets are useful tools to evaluate sediment impacts to water quality 

and channel morphology. A sediment budget is an “accounting of the sources and 

disposition of sediment as it travels from its point of origin to its eventual exit from a 

drainage basin” (Reid and Dunne 1996). A variety of tools and data sources are used 

to create the sediment budget, including monitoring information, aerial photography 

analysis, simple calculations, spreadsheet analysis, and computer models. 

This paper reviews the sediment budgets created for 20 North Coast watersheds. 

The paper then discusses a monitoring strategy that can track watershed recovery and 

will help determine when watersheds have been restored. 

Sediment budgets and total maximum daily loads

Under section 303(d) of the Clean Water Act, states are required to identify all 

water bodies that do not meet water quality standards. For those “impaired” water 

bodies, the states must develop and implement Total Maximum Daily Loads 

(TMDLs) or implement another program that will result in the attainment of water 

quality standards. A TMDL “shall be established at a level necessary to implement 

the applicable water quality standards with seasonal variations and a margin of safety 

which takes into account any lack of knowledge concerning the relationship between 

effluent limitations and water quality” (Clean Water Act, §303(d)(1)(C)). In a general 

sense, a TMDL and its implementation plan is a water quality attainment strategy, 

which provides a framework for assessing the watershed condition, evaluating the 

sources of pollution contributing to the water quality impairment, and developing a 

water quality restoration plan for the watershed. The North Coast Region of the 

California Regional Water Quality Control Board has 61 percent of the region’s area 
Total Maximum Daily Loads, Sediment Budgets, and Tracking Restoration Progress of North Coast 

Watersheds

25

listed for sediment impairment under Clean Water Act Section 303(d) (CRWQCB 

2008). 

A key component of TMDLs is the source assessment. For sediment TMDLs, the 

source assessment typically takes the form of a sediment budget that identifies and 

estimates the hillslope sources of sediment. Due to the significant yearly variation in 

sediment loads in northern coastal California, which can range over several orders of 

magnitude, the sediment budgets rely on long-term estimates of sediment input. 

These estimates are often derived by using sequential aerial photographs to evaluate 

the occurrence of major sediment sources such as landslides. The sequential 

photographs often bracket significant storm events (for example, 1964, 1986, 1997 

and 2003 storms). Therefore, the sediment budgets “average” the estimated sediment 

delivery over the air photo period. 

While calculating the TMDL on a daily basis is a legal requirement, U.S. 

Environmental Protection Agency (USEPA) recognizes that it is impractical for land 

managers to measure sediment loads, or sediment discharges, on a daily basis. 

Therefore, sediment TMDLs are expressed as an average annual load which should 

be evaluated as a long-term (for example, 10 to 15 year) running average (USEPA 

2007a). Furthermore, USEPA expects progress toward the TMDL to be evaluated by 

estimating the total sediment load relative to the natural load (USEPA 2007a), which 

is why the loading capacity is often expressed as a ratio relative to the natural loads, 

in addition to being provided as an absolute load. The underlying assumption is that 

while sediment delivery is very episodic, which makes the determinations of progress 

towards the TMDL very difficult, the ratio of total sediment to natural is not as 

sensitive to episodic events. 

To date, 20 sediment TMDLs have been completed for North Coast Region 

watersheds. The estimated sediment loads and the TMDL, in other words the loading 

capacity, are shown in table 1. Comparisons between the sediment loads from 

TMDLs are difficult because different methods and categories were used to identify 

the sources and volumes of sediment reaching streams. However, some general 

conclusions can be reached. The road system is often the major source of sediment 

averaging 57 percent of the management-related sediment load. Logging sources of 

sediment averaged 24 percent of the management-related sediment load. Agriculture 

and grazing were very minor sources of sediment in these watersheds, while mining 

sources of sediment were important in some watersheds (for example, the Scott River 

watershed).

To provide a better understanding of sediment discharges from the 1970s through 

the 1990s from logging activities, Strauss (2002) reviewed the TMDL sediment 

budgets for several watersheds where the primary land use was logging. Seven 

watersheds were identified for this exercise: Noyo River, Ten Mile River, Albion 

River, and Big River, and portions of the Van Duzen River, South Fork Eel River, 

and Gualala River. The results indicated that 43 percent of the sediment delivered to 

streams was from natural or background sources, 1 percent was from specific sources 

other than silviculture and the remaining 56 percent was associated with timberland 

management. The amount attributed to logging was always substantial, ranging from 

43 to 70 percent, and most of the logging-related sediment was associated with roads, 

but other processes like landslides from logging units were significant.
26

Table 1—Sediment load estimates from northern California TMDLs.

Watershed Size (km2) Natural

(t/km2) 

Management

(t/km2) 

Total

(t/km2) 

Total 

(relative to 

natural)

TMDL

(t/ km2) 

TMDL 

(relative 

natura

Albion River 111 96 152 249 2.58 144 1.5

Big River 469 110 110 220 2.00 138 1.2

Eel River, North Fork 749 291 140 430 1.48 364 1.2

Eel River, Middle Fork 1950 201 29 230 1.14 211 1.0

Eel River, South Fork 1785 378 331 708 1.88 472 1.2

Eel River, Upper Main 1782 109 54 162 1.49 136 1.2

Eel River, Middle Main 1349 181 83 264 1.46 226 1.2

Eel River, Lower Main 774 251 272 523 2.08 315 1.2

Garcia River 295 57 427 483 8.52 193 3.4

Gualala River 774 133 294 427 3.21 166 1.2

Mad River 1243 313 553 867 2.77 376 1.2

Mattole River 767 1016 1786 2802 2.76 1261 1.2

Navarro River 816 410 271 681 1.66 512 1.2

Noyo River 293 130 74 204 1.57 165 1.2

Redwood Creek 738 532 1131 1664 3.13 666 1.2

Scott River 2106 157 105 262 1.67 196 1.2

Ten Mile River 311 109 111 220 2.02 137 1.2

Trinity River 4978 379 197 575 1.52 474 1.2

Trinity River, South 

Fork

2414 239 130 369 1.54 258 1.0

Van Duzen River 1111 596 157 753 1.26 642 1.0

Average 1241 284 320 605 2.29 353 1.3

Median 795 220 155 429 1.77 242 1.2
Total Maximum Daily Loads, Sediment Budgets, and Tracking Restoration Progress of North Coast 

Watersheds

27

For most northern coastal TMDLs, the loading capacity has been set at or near 

1.25 relative to the natural background sediment loads (table 1). Since estimates of 

current sediment loading in these northern coastal watersheds average 2.29 relative to 

natural background, significant reductions in sediment discharges are required to 

meet the TMDLs. On average, it’s estimated that the management-related sediment 

load must be reduced by 69 percent to meet water quality standards. 

These TMDLs and their associated sediment budgets are for large watersheds 

and many of the sediment budgets were the first attempt to analyze sediment source 

information at a watershed scale. It’s expected that further research will increase the 

understanding of sediment sources and sediment loads.

Recent research has identified sediment sources that were not included in most 

TMDL sediment budgets. For example, Reid et al. (2010) found that gullies were a 

significant source of sediment following logging in the Caspar Creek watershed. 

Furthermore, Klein et al. (2011) recently compared turbidity, which is closely related 

to suspended sediment, for 28 watersheds in northern coastal California, some of 

which are on the 303(d) list for sediment. Watersheds with high harvest rates for the 

last fifteen years had turbidity levels approximately eight times greater than nearly 

pristine old-growth watersheds. This study indicates that logging activities continues 

to contribute sediment to impaired water quality conditions and that the impact of 

logging may have been underestimated in previous sediment budgets. 

Tracking watershed recovery

Monitoring can have many different forms based on its objectives. Monitoring 

related to water quality regulation can be classified into the following categories: 

implementation monitoring, upslope effectiveness monitoring, instream effectiveness 

monitoring and compliance and trend monitoring (CRWQCB 2006). This paper is 

focused on compliance and trend monitoring, which describes monitoring that is 

intended to determine if water quality standards are being met. Specifically, this 

paper focuses on the parameters that can be used to determine the water quality 

conditions for cold water fish such as coho and to determine when a waterbody has 

recovered from sediment impacts. When monitoring data indicates that water quality 

standards are being met, the data can then be used for delisting from the 303(d) list.

The 303(d) Listing Policy adopted by the California State Water Resources 

Control Board (2004) establishes a standard methodology for assessing data and 

information for both listing and delisting purposes that utilizes a weight of evidence 

approach. While one of several approaches can be used, sediment delistings will 

likely use a situation-specific weight of evidence approach. This approach requires 

that delisting recommendations are supported by (1) data or information that affords 

a substantial basis in fact from which the decision can be reasonably inferred, (2) data 

and information demonstrates that the water quality standard is attained, and (3) a 

demonstration that the approach used is scientifically defensible and reproducible 

(CSWRCB 2004). Other approaches that can be used to delist waterbodies include 

demonstrating that numeric water quality objectives are not exceeded, nuisance 

conditions no longer exist or adverse biological response is no longer evident. 
GENERAL TECHNICAL REPORT PSW-GTR-238

28

Water quality standards include the designated beneficial uses of water, water 

quality objectives to protect those designated uses, federal and state anti-degradation 

policies, and policies adopted by the State and Regional Water Boards. Water quality 

standards are generally contained in the Water Quality Control Plan for the North 

Coast Region (Basin Plan). The Basin Plan is one regulatory tool used by the 

Regional Water Board staff to implement the federal Clean Water Act and the state 

Porter-Cologne Water Quality Control Act to protect water quality. The cold 

freshwater habitat beneficial use appears to be the most sensitive beneficial use to 

excessive sediment. The water quality objectives related to sediment are narrative.

Regional Water Board staff reviewed the scientific literature related to sediment 

impacts on freshwater salmonid habitat to help interpret the narrative sedimentrelated water quality objectives. The Desired Conditions Report (CRWQCB 2006) 

identifies numeric targets which are directly measurable by known monitoring 

methods. The targets provide a means of assessing attainment, or recovery toward 

attainment, with the narrative water quality objectives for sediment in regards to the

beneficial use of cold water fish, and specifically the freshwater habitat needs for 

salmonids. Non-attainment of these desired conditions, however, is not independently 

enforceable. The desired condition values would only be enforceable if they are 

specifically incorporated into a permit or if they are formally adopted as water quality 

objectives in the Basin Plan.

The desired conditions are intended to be used by the Regional Water Board and 

other agencies, organizations, and interested individuals to assess and monitor 

sediment impacts to water quality. Stakeholders, landowners, and other resource 

agencies are encouraged to monitor instream conditions and compare their data to 

these indices where applicable.

Since the relationship of water quality with sediment cannot be described by a 

single parameter, it is important to track a suite of parameters to assess watershed 

recovery and to determine when water quality standards are being met. There are five 

general categories of data and information needed to track the recovery of sediment 

impaired waterbodies (table 2). The three primary categories are channel substrate, 

channel morphology, and water column. Two other categories, hillslope and 

biological, can provide supporting evidence on watershed recovery. 

The targets for the sediment monitoring parameters primarily come from the 

desired conditions report (CRWQCB 2006). However, other sources are also used for 

establishing appropriate targets, including approved TMDLs (for example, hillslope 

targets from USEPA 1999a) or Recovery Plans (for example, biological targets from 

NMFS 2010). The targets are based on current knowledge and may need to be 

modified depending on further research. Furthermore, some reports identify 

parameters whose targets are “increasing tends” (for example, increasing trend in 

variation along the thalweg elevation (CRWQCB 2006)). Further information on 

monitoring methods can be found in the referenced reports.
Total Maximum Daily Loads, Sediment Budgets, and Tracking Restoration Progress of North Coast 

Watersheds

29

Table 2—Trend monitoring categories and targets. 

Category Parameter Target Reference

Channel 

Substrate

Substrate composition: 

Percent Fines < 0.85 mm

≤ 14 % of substrate is 

small fines

CRWQCB 

2006

Substrate composition: 

Percent Fines < 6.40 mm

≤ 30 % of substrate is 

small fines

CRWQCB 

2006

Embeddedness ≤ 25 % of gravels and 

cobbles are embedded

CRWQCB 

2006

Pool filling with fine 

sediment (V*)

≤ 20 % of the pool 

volume is filled with 

fines

CRWQCB 

2006

Channel 

Morphology

Primary Pools ≥ 40% of reach is 

primary pools

CRWQCB 

2006

Large Woody Debris: small 

streams

> 11 key pieces/ 100 m CRWQCB 

2006

Large Woody Debris: large 

streams

> 4 key pieces/ 100 m CRWQCB 

2006

Water 

Column

Suspended Sediment and 

Turbidity

Water Quality 

Objectives

CRWQCB 

1994

Hillslope Stream crossings with 

diversion potential

≤ 1 % of stream 

crossings have 

diversion potential

USEPA 1999a

Stream crossings with failure 

potential

≤ 1 % of stream 

crossings have failure 

potential

USEPA 1999a

Hydrologic connectivity of 

roads

≤ 1 % of the road 

network is connected to 

streams

USEPA 2003b

Biological Spawning Adults (coho) 20 to 40 per km NMFS 2010

Juvenile Density (coho) 0.5 to 1.0 fish per m2 NMFS 2010

Water column parameters in table 2 already have water quality objectives in the 

Basin Plan. Regional Water Board staff does not propose to revise the standards or 

establish desired conditions, because further research is needed. However, several 

approaches appear promising, including examining turbidity exceedences (Klein et 

al. 2011) or using the Severity Index (Newcombe 2003) to determine water quality 

impacts. Also, it should be noted that suspended sediment and turbidity monitoring is 

helpful for monitoring trends and validating sediment budgets. 

Conclusions

The sediment budgets developed for TMDLs confirm that many streams in the 

north coast region have suffered impacts from large inputs of sediment from 

anthropogenic activities. Much of the management source of sediment comes from 

logging and the roads that are used to access the timber. Substantial effort is needed 

to reduce sediment loads in these watersheds. Establishing trend monitoring 

programs is critical to measuring the progress of watershed recovery in these 

impaired watersheds. Since the relationship of water quality with sediment cannot be 

described by a single parameter, it is important to track a suite of parameters to assess 

watershed recovery and to determine when water quality standards are being met.
GENERAL TECHNICAL REPORT PSW-GTR-238

30

References

Chapman, D.W. 1988. Critical review of variables used to define effects of fines in redds 

of large salmonids. Transactions of the American Fisheries Society 117: 1-21.

California Regional Water Quality Control Board [CRWQCB]. 1994. Water quality control 

plan for the North Coast region. Adopted 9 December 1993. Santa Rosa, CA:

California Regional Water Quality Control Board, North Coast Region. 

CRWQCB. 2005. Staff report for the action plan for the Scott River Watershed sediment 

and temperature total maximum daily loads. Santa Rosa, CA: California Regional 

Water Quality Control Board, North Coast Region.

CRWQCB. 2006. Desired salmonid freshwater habitat conditions for sediment-related 

indices. Santa Rosa, CA: California Regional Water Quality Control Board, North Coast 

Region. 

CRWQCB. 2008. Work plan to control excess sediment in sediment-impaired 

watersheds. Santa Rosa, CA: California Regional Water Quality Control Board, North 

Coast Region. 

California State Water Resources Control Board. 2004. Water quality control policy for 

developing California’s Clean Water Act Section 303(d) List. Resolution No. 2004-

0063. Sacramento, CA.

Gomi, T.; Moore, R.D.; Hassan, M.A. 2005. Suspended sediment dynamics in small forest 

streams of the Pacific Northwest. Journal of the American Water Resources 

Association 41(4): 853-876. 

Good, T.P.; Waples, R.S.; Adams P., editors. 2005. Updated status of federally listed ESUs 

of West Coast salmon and steelhead. Technical Memorandum NMFS-NWFSC-66. 

Seattle, WA: U.S. Department of Commerce, NOAA. 598 p.

Klein, R.D.; Lewis, J.; Buffleben, M.S. 2011. Logging and turbidity in the coastal 

watersheds of northern California. Geomorphology doi:

10.1016/j.geomorph.2011.10.011. 

Knighton, D. 1998. Fluvial forms and processes, a new perspective. London, United 

Kingdom: Arnold 383 p.

National Marine Fisheries Service. 2007. 2007 Federal recovery outline for the distinct 

population segment of Northern California steelhead. Santa Rosa, CA: National 

Marine Fisheries Service, Southwest Regional Office.

National Marine Fisheries Service. 2010. Public draft recovery plan for central California 

coast coho salmon (Oncorhynchus kisutch) evolutionarily significant unit. Santa 

Rosa, CA: National Marine Fisheries Service, Southwest Region.

Newcombe, C.P. 2003. Impact assessment model for clear water fishes exposed to 

excessively cloudy water. Journal of the American Water Resources Association 39(3): 

529-544.

Reid, L.M. 1993. Research and cumulative watershed effects. Gen. Tech. Rep. PSW-GTR141. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest 

Research Station. 118 p.

Reid, L.M.; Dewey, N.J.; Lisle, T.E.; Hilton, S. 2010. The incidence and role of gullies 

after logging in a coastal redwood forest. Geomorphology 117: 155-169.

Strauss, A. 2002 [Letter to Arthur G. Baggett, Jr., State Water Resources Control 

Board]. 2002 July 11. Located at: California Regional Water Quality Control Board, 

North Coast Region, Santa Rosa, California.
Total Maximum Daily Loads, Sediment Budgets, and Tracking Restoration Progress of North Coast 

Watersheds

31

U.S. Environmental Protection Agency [USEPA]. 1998a. Garcia River sediment Total 

Maximum Daily Load. San Francisco, CA: U.S. Environmental Protection Agency, 

Region IX. 

USEPA. 1998b. South Fork Trinity River and Hayfork Creek sediment Total Maximum 

Daily Loads. San Francisco, CA: U.S. Environmental Protection Agency, Region IX.

USEPA. 1998c. Total Maximum Daily Load for sediment Redwood Creek, California.

San Francisco, CA: U.S. Environmental Protection Agency, Region IX.

USEPA. 1999a. Noyo River Total Maximum Daily Load for sediment. San Francisco, 

CA:U.S. Environmental Protection Agency, Region IX. 

USEPA. 1999b. South Fork Eel River Total Maximum Daily Loads for sediment and 

temperature. San Francisco, CA: U.S. Environmental Protection Agency, Region IX. 

USEPA. 1999c. Van Duzen River and Yager Creek Total Maximum Daily Load for 

sediment. San Francisco, CA: U.S. Environmental Protection Agency, Region IX.

USEPA. 2000a. Navarro River Total Maximum Daily Loads for temperature and 

sediment. San Francisco, CA: U.S. Environmental Protection Agency, Region IX. 

USEPA. 2000b. Ten Mile River Total Maximum Daily Load for sediment. San Francisco, 

CA: U.S. Environmental Protection Agency, Region IX.

USEPA. 2001a. Albion River Total Maximum Daily Load for sediment. San Francisco, 

CA: U.S. Environmental Protection Agency, Region IX. 

USEPA. 2001b. Big River Total Maximum Daily Load for sediment. San Francisco, CA: 

U.S. Environmental Protection Agency, Region IX.

USEPA. 2001c. Gualala River Total Maximum Daily Load for sediment. San Francisco, 

CA: U.S. Environmental Protection Agency, Region IX.

USEPA. 2001d. Trinity River Total Maximum Daily Load for sediment. San Francisco, 

CA:U.S. Environmental Protection Agency, Region IX. 

USEPA. 2002. North Fork Eel River Total Maximum Daily Loads for sediment and 

temperature. San Francisco, CA: U.S. Environmental Protection Agency, Region IX. 

USEPA. 2003a. Final Middle Fork Eel River Total Maximum Daily Loads for 

temperature and sediment. San Francisco, CA: U.S. Environmental Protection 

Agency, Region IX.

USEPA. 2003b. Mattole River Total Maximum Daily Loads for sediment and 

temperature. San Francisco, CA: U.S. Environmental Protection Agency, Region IX.

USEPA. 2004. Final Upper Main Eel River and Tributaries (including Tomki Creek, 

Outlet Creek and Lake Pillsbury) Total Maximum Daily Loads for temperature 

and sediment. San Francisco, CA: U.S. Environmental Protection Agency, Region IX. 

USEPA. 2005. Final Middle Main Eel River and tributaries (from Dos Rios to the South 

Fork) Total Maximum Daily Loads for temperature and sediment. San Francisco, 

CA: U.S. Environmental Protection Agency, Region IX. 

USEPA. 2007a. Lower Eel River Total Maximum Daily Loads for temperature and 

sediment. San Francisco, CA: U.S. Environmental Protection Agency, Region IX. 

USEPA. 2007b. Mad River Total Maximum Daily Loads for sediment and turbidity. San 

Francisco, CA: U.S. Environmental Protection Agency, Region IX.

USEPA. 2009. National summary of impaired waters and TMDL information.

http://www.epa.gov/.

33

Logging-Related Increases in Stream 

Density in a Northern California Watershed1

Matthew S. Buffleben2

Abstract

Although many sediment budgets estimate the effects of logging, few have considered the 

potential impact of timber harvesting on stream density. Failure to consider changes in stream 

density could lead to large errors in the sediment budget, particularly between the allocation 

of natural and anthropogenic sources of sediment. 

This study conducted field surveys in randomly selected catchments in two managed and one 

old-growth watershed to determine the location of the channel’s origins in the catchments. 

The drainage areas for identified channel heads were then delineated using a 1 m digital 

elevation model derived from laser altimetry. The two managed watersheds were heavily 

impacted by previous logging activities, particularly by tractor operations used to yard the 

timber out of the watersheds. The channel heads in the managed watersheds had smaller 

drainage areas than channels in a nearby old-growth watershed. The management activities 

led to a tripling of the drainage density in the managed watersheds.

Timber harvesting and the construction of skid trails used to transport timber to the road 

system led to increases in peak flow, ground water interception, soil compaction and drainage 

diversion, which reduced the drainage area necessary to initiate stream channels. Furthermore, 

it appears that recent ground-based yarding operations have further extended stream channels 

upslope, potentially creating additional sources of sediment for downstream receptors. 

Although these results may be unique to these watersheds, the changes in drainage density 

due to management activities found here emphasize the need to compare managed watersheds 

with undisturbed watersheds before using the current drainage network as a base-line for 

estimating chronic sources of sediment like bank erosion. 

Key words: channel incision, drainage density, sediment budget

Introduction

Many watersheds in northern coastal California have been impaired by sediment 

discharges from non-point sources, particularly sediment sources related to logging 

activities. Efforts to assess the sediment impairment often include the construction of 

sediment budgets to create an “accounting of the sources and disposition of sediment 

as it travels from its point of origin to its eventual exit from a drainage basin” (Reid 

and Dunne 1996). Sediment budgets identify sediment sources and provide estimates 

of sediment delivery which can help prioritize erosion control efforts. 

The extent of the stream network, or the drainage density, plays an important role 

in developing sediment budgets. Stream maps are needed to determine if discrete 

 

1 This paper was presented at the redwood science symposium: June 21-23, 2011, Santa Cruz, 

California. 2 California Regional Water Quality Control Board, North Coast Region, Santa Rosa, CA 95403. 

(mbuffleben@waterboards.ca.gov).
GENERAL TECHNICAL REPORT PSW-GTR-238

34

features (for example, landslides) have delivered sediment to the network. The 

drainage density is also important for estimating sediment delivery from diffuse 

sediment-generating processes (for example, bank erosion). Topographic maps do not 

include the majority of headwater streams and is a particular problem in areas under 

forest canopy (Benda et al. 2005). Therefore, field surveys are conducted to 

determine the extent of the stream network in the watershed (Montgomery and 

Foufoula-Georgiou 1993). However, stream lengths may increase due to forest 

management activities, and estimated drainage densities based on only the current 

stream network could overestimate the natural drainage density. If the current stream 

distribution is used to estimate natural chronic sources of sediment and the stream 

network is more extensive than it had been prior to disturbance, the impacts of timber 

harvesting will be underestimated. 

The point of transition from an unchanneled swale, also known as a zero-order 

basin (Dietrich et al. 1987), to a channel is referred to as the “channel head.” The 

channel head is the upstream limit of concentrated water and sediment transport 

between definable banks. Knighton (1998) describes five processes related to channel 

initiation: two by overland flow (Horton overland flow and saturation overland flow) 

and three by subsurface flow (seepage erosion, tunnel scour and shallow landsliding). 

These processes are not mutually exclusive, and all may be present even in a 

relatively homogenous landscape. However, landsliding is likely to predominate in 

steep areas, while overland flow and seepage erosion predominate in lower-gradient 

areas. The location of the channel head is affected by climate, with wetter regions 

needing smaller drainage areas (Montgomery and Dietrich 1988).

Hillslope gradient can also influence channel initiation. Montgomery and 

Dietrich (1988) reported inverse relationship between drainage area and valley 

gradient, especially where landslides initiated channels. Channel heads initiated by 

overland flow may also reflect a relationship between drainage area and gradient 

relationship (Montgomery and Foufoula-Georgiou 1993), as may those of gullied 

channels (Vandekerckhove et al. 2000). However, there are circumstances where 

there is no relationship between drainage area and slope (Jaeger et al. 2007, Wemple 

et al. 1996). Dietrich et al. (1987) noted no systematic drainage area-slope 

relationship at sites in Oregon where channel head locations were thought to be 

controlled by the flow paths through fractured bedrock. 

Since the drainage area needed to initiate channels depends on climatic 

conditions, it seems reasonable to expect that management activities that increase 

runoff may also decrease the drainage area and hence increase the drainage density. 

Roads increase runoff because road surfaces have lower infiltration capacity than 

natural slopes. The drainage area needed to support a channel head is smaller for 

drainages receiving road runoff (Montgomery 1994, Wemple et al. 1996). 

Logging is also likely to have an effect on channel head location. Prosser and 

Soufi (1998) observed gulley initiation during large rainfall events following forest 

clearing. Increases in peak flow due to a reduction in evapotranspiration (Lewis et al. 

2001) likely plays a role in modifying channel head locations. Increases in peak flow 

could exceed the thresholds related to the channel initiation processes and decrease 

the drainage area for channel initiation.

In a comparison between cable-yarded clearcuts and old-growth forest, Pacific 

Watershed Associates (1999) found that valley catchments served as groundwater 
Logging-Related Increases in Stream Density in a Northern California Watershed

35

reservoirs in old-growth areas, with most runoff carried through a network of 

interconnected subsurface pipes. The incised channels or gullied swales within the 

old-growth areas are discontinuous, inactive, and located much farther downstream 

(in other words, have larger drainage areas) than those identified in the clearcut 

drainages of the harvested areas. Pacific Watershed Associates concluded the swales 

in logged areas had experienced gullying in response to first-cycle harvesting. 

This study seeks to determine the effects of logging on stream network by 

comparing the stream density in two logged watersheds with a nearly pristine 

watershed. The field surveys also identified the channel initiation processes and the 

management features associated with channel heads. This information will be used to 

determine if the drainage density can be estimated from drainage area alone or from a 

drainage area-slope relationship. 

Methods

In Elk River watershed, located near Eureka, California, three subwatersheds 

were surveyed to determine the catchment area needed for channel initiation and to 

examine the influence of valley gradient on the location of channel heads. These 

watersheds share similar bedrock, which primarily consists of the sedimentary rocks 

with a sheared and highly folded mudstone exposed in the deeper portions of the 

canyons of the watersheds. The three watersheds have average hillslope gradients of 

23° to 24°. These watersheds experience a Mediterranean climate with dry summers 

and wet winters and with an average annual precipitation of 1650 mm. Forest stands 

in Elk River are dominated by redwood (Sequoia sempervirens) and Douglas-fir 

(Pseudotsuga menziesii) (Buffleben 2009).

The primary difference between the three watersheds is their management 

history. South Branch North Fork Elk River (SBNFER) watershed was first logged in 

the 1970s, though small areas were harvested in the 1940s and 1960s. The western 

portion of the Corrigan Creek (CC) watershed was first logged in the 1950s and the 

eastern portion in the 1970s. These harvests were primarily clear-cut and tractor 

yarded on an extensive skid trail network. Measurements on air photos indicate the 

skid trail density is 32.9 and 31.4 km/km2 in SBNFER and CC respectively. Both of 

these watersheds experience ongoing logging entries beginning in the late 1980s, 

consisting of partial-cut and clear-cut harvests with tractor yarding. The portion of 

the Little South Fork Elk River (LSFER) surveyed in this study is primarily an oldgrowth redwood forest, although a 2.3 km road was constructed in the 1990s and 

decommission in 2003.

Since it is impractical to conduct surveys of the entire watershed for even these 

relatively small watersheds, the watersheds were divided into catchments from which 

a random selection of catchments was surveyed. Catchments within the three 

watersheds were delineated from a 1-m digital elevation map (DEM) derived from 

laser altimetry. 12 to 14 percent of the watersheds were surveyed between October 

2005 and May 2006. Based on a nearby rain gauge located in Eureka, the inspections 

occurred during a wetter than average winter period (148 cm of rainfall, 58 percent 

greater than the average annual precipitation).

Field crews were provided large scale maps (typically 1:4000) of the catchments. 

Typically, field crews would hike up all swales and traverse other areas in the 
GENERAL TECHNICAL REPORT PSW-GTR-238

36

catchments to locate channels heads. Channel heads were defined as the farthest 

upslope location of a channel with well-defined banks (Montgomery and Dietrich 

1988). Since stream channels typically begin as discontinuous segments and access to 

portions of the catchments was difficult due to thick vegetation and old logging 

debris, some subjectivity is introduced in identifying channel heads. The locations of 

the channel heads were recorded using Global Positions System (GPS), although if 

GPS reception was poor, a laser range finder was used to determine the distance to a 

known location (for example, a road or tributary junction). Along with the location, 

other attributes recorded included slope (as measured with a clinometer to a point 

approximately 5 m above the channel head), type (for example, spring, head cut), and 

management activities (for example, presence of roads, skid trails, yarding corridors, 

stand age). The drainage area for a channel head was defined as the upslope area 

draining into that feature as delineated on the 1 m DEM. Further details on the field 

methods and data analysis are included in Buffleben (2009). 

Results

For the managed watersheds, SBNFER and CC, channel heads were found in 

most of the catchments and several catchments in these watersheds had multiple 

channel heads (table 1). Catchments without channel heads in the managed 

watersheds were small and didn’t have a major drainage axis or swale within their 

boundaries. It is likely that the limited drainage area in these catchments prevented 

erosion thresholds from being exceeded. Most channel heads in the managed 

watersheds were associated with some type of management feature, the most 

common of which are skid trails. This result is not unexpected considering the high 

skid trail density in these watersheds. Seepage erosion and saturation overland flow 

are important channel-forming processes along road and skid trail cutbanks. Tunnel 

scour is also commonly associated with skid trails. Landslides appear to be a minor 

process in channel-head formation in these watersheds.

Table 1—Number (and percentage) of catchments with channel heads and number of channel 

heads with identified management associations.

South Branch 

North Fork

Elk River

Corrigan Creek Little South Fork 

Elk River

Catchments with 

channel heads 15 (94%)a 11 (65%) 6 (43%)

Number of channel 

heads 22 17 6 

Road cutbank 2 1 2

Road landslide 1 - -

Landing tunnel scour 1 - -

Skid trail cutbank 5 4 -

Skid trail tunnel scour 8 2 -

Channel heads with 

identified management 

association

17 (77%)b 7 (41%) 2 (33%)

a Percent of catchments with channel heads.

b Percent of channel heads with identified management association.
Logging-Related Increases in Stream Density in a Northern California Watershed

37

The range in drainage area at the channel heads exceeds an order of magnitude 

(fig. 1). The average drainage size in these watersheds is 0.69 ha and 0.98 ha and the 

median is 0.42 and 0.72 ha for SBNFER and CC respectively. Catchments in LSFER 

are separated into two categories depending on whether or not the road passed 

through the catchments. Results for the five catchments that contain portions of the 

road are similar to those from the other managed watersheds. Three small catchments 

(averaging 0.6 ha in size) did not have channel heads. For the two catchments with 

channels, the channel heads were clearly associated with the road and the drainage 

areas for these channel heads reflect the road location in the catchment.

Figure 1—Box plot of drainage area of the channel heads. The number of channel 

heads in each group is shown above its name. The median (50th percentile) is 

marked by the center line within the box and the mean is shown as an X. The 

whiskers extend to the values that fall within 1.5 * IQR (interquartile range). Outliers 

are plotted with asterisks (*) when they fall outside of this range.

Nine catchments within LSFER were not affected by the road construction. Five 

of these catchments had no channels. While three of these catchments were small and 

did not have swales, two catchments were very large with drainage areas of 4.85 and 

5.29 ha. These two large headwater catchments without channel heads exceeded the 

drainage area for the four catchments with identified channel heads, which had 

average and median drainage areas of 3.10 and 3.15 ha respectively. It appears that 

the area of the two large catchments without channel heads is below the erosion 

thresholds necessary to initiate a channel head. If so, it seems appropriate to include 

the area of these two catchments as a minimum value in determining the drainage 

area needed to initiate channels in the undisturbed portions of LSFER. Including 

these two catchment areas raises the average and median drainage area to 3.75 and 

4.22 ha respectively.
GENERAL TECHNICAL REPORT PSW-GTR-238

38

The median drainage areas for channel heads in SBNFER and CC are 

significantly different than that for LSFER (Mann-Whitney test, p = 0.0062 and 

0.0138 respectively). Furthermore, the p-values decrease when the two large 

catchments without channel heads were included in the LSFER. The drainage areas 

for the managed watersheds, SBNFER and CC, were combined and the median 

drainage area was used to construct estimated stream networks for managed 

conditions in the three watersheds. Likewise, the median drainage area for 

undisturbed catchments in LSFER, including the two large catchments where channel 

heads were not present, was used to construct stream networks for old-growth 

forested conditions in the three watersheds. Stream networks for forested and 

managed conditions were then compared to estimate the drainage density resulting 

from the timber management. The drainage density in the managed forests was to 2.7 

to 3.1 times the natural drainage density. 

To test for a relationship between slope and drainage area, regression analysis 

was conducted using the log-transformed drainage areas, since the drainage areas 

were not normally distributed (Anderson-Darling normality test, p = 0.000). Using all 

the channel head data in the regression analysis resulted in a poor, insignificant 

relationship, which indicates that slope is not a dominant factor in determining 

drainage density in these watersheds.

Discussion

Our surveys in the unaltered portions of the old-growth forest indicate that 

subterranean soil pipes play an important role in the transportation of stormflows, 

since infiltration rates are high and overland flow rarely occurs in undisturbed 

forested watersheds. We observed and measured several soil pipes at the channel 

heads (approximately 15 cm in diameter). It appears that soil pipes form a welldeveloped subterranean network and are stable enough to carry stormflows large 

distances downstream. Erosion thresholds are eventually overcome when several 

unchanneled swales merged.Timber management activities appear to have

destabilized the soil pipe network and dramatically reduced the drainage area needed 

for channel initiation, thereby increasing the drainage density. Two aspects of 

management may have been particularly influential: the construction of roads (and 

skid trails) and the removal of vegetation. The increases in drainage density observed 

in these watersheds are greater than those found in previous studies (Montgomery 

1994, Wemple et al. 1996). The large increases identified here may be due in part to 

the extremely high density of skid trails. Although only used briefly during a harvest 

cycle, skid trails have similar impacts as roads in that they intercept ground water, 

increase runoff due to ground compaction, and change drainage patterns. Skid trails 

were observed at many of the channel heads (table 1). Observations suggest that soil 

compaction on skid trails may play a role in tunnel scour and roof collapse in soil 

pipes. 

The reduction in drainage area for the channel heads may have other contributing 

factors other than the presence and impacts of skid trails. Many of the channel heads 

in the logged watersheds were not associated with management features (table 1). 

Vegetation removal is likely to have reduced the drainage areas for channel heads 

through several mechanisms. Vegetation removal increases runoff due to reductions 

in transpiration and interception (Lewis et al. 2001). The increased runoff can 
Logging-Related Increases in Stream Density in a Northern California Watershed

39

destabilize the soil pipes and form gullies (Reid et al. 2010). Another factor that may 

contribute to destabilization of soil pipes is the reduction in root strength, which 

could decrease soil cohesion and resistance to erosion.

This study did not observe an inverse drainage area-slope relationship. One 

possible reason for the lack of this relationship may be the significant scatter in 

drainage area for a particular slope, thereby making it difficult to observe a trend 

(Jaeger et al. 2007). Also, it is possible that the range of slopes was too narrow to 

detect a slope-area relationship. Landslides, typically occurring on steep slopes, are 

present in these watersheds. However, only one channel head in these surveys was 

associated with a landslide. The lack of landsliding may indicate that these 

watersheds lacked significant portions of steep slopes, which would diminish the 

ability to detect a drainage area-slope relationship. However, a trend regarding the 

drainage area-slope relationship was observed. As the drainage areas have been 

reduced by management activities, channel heads have moved closer to ridgelines, 

where swale-axis slopes are steeper. 

The increase in drainage density observed in these watersheds is important to 

consider during construction of sediment budgets. An increase of drainage density 

suggests greater peak flows which could add to channel erosion and sediment yields. 

Furthermore, if a sediment budget used the existing drainage density to estimate the 

sediment delivery from soil creep, it would be overestimate the sediment delivery 

from this natural process. 

Furthermore, it is clear that in the past large amounts of sediment have been 

delivered to the stream network due to the shift in location of the channel head 

(Pacific Watershed Associates 1999). These relatively new channels, caused by 

management activities within the last 100 years, may still be unstable and are 

potentially chronic sediment sources due to continued headcutting and bank erosion 

occurring within the channels (Reid et al. 2010). 

In several catchments in the Corrigan Creek watershed that had recent timber 

harvesting operations, we observed the upslope migration of channel heads. These 

channels appeared to be intercepting groundwater flow from skid trails used in the 

recent logging operations. However, these newer channel heads may only be 

temporary seeps that are due to the increased runoff associated with the harvest. Also, 

since our surveys took place during a wetter than average year, the new channels may 

not become permanently established or become chronic sources of sediment.

Given that water quality is impaired in the Elk River watershed and that it is 

extremely difficult to manage gully erosion once it has initiated, steps to prevent 

upslope migration of channel heads should be considered when developing plans to 

mitigate the impacts of future logging. Tractor operations and construction of new 

skid trails should be minimized along a swale axis. Furthermore, to reduce the 

increases in peak flows and loss of cohesion due to vegetation removal, partial-cuts 

should be considered instead of clear-cutting in well-defined swales.

References

Benda, L.; Hassan, M.A.; Church, M.; May, C.L. 2005. Geomorphology of steepland

headwaters: the transition from hillslopes to channels. Journal of the American 

Water Resources Association 4(4): 853-876.
GENERAL TECHNICAL REPORT PSW-GTR-238

40

Buffleben, M.S. 2009. Assessment of soil creep sediment generation for total maximum 

daily load development in a northern coastal California watershed. Los Angeles, 

CA: University of California Los Angeles. Ph.D thesis. 159 p.

Dietrich, W.E.; Reneau, S.L.; Wilson, C.J. 1987. Overview: "zero-order basins" and 

problems of drainage density, sediment transport and hillslope morphology. In: 

Erosion and sedimentation in the Pacific Rim. Proceedings of the Corvallis symposium, 

August 1987. International Association of Hydrological Sciences: 27-37. 

Jaeger, K.L.; Montgomery, D.R.; Bolton, S.M. 2007. Channel and perennial flow initiation 

in headwater streams: management implications of variability in source-area size.

Environmental Management 40: 775-786.

Knighton, D. 1998. Fluvial forms and processes, a new prespective. London: Arnold. 383 

p.

Lewis, J.; Mori, S.R.; Keppeler, E.T.; Ziemer, R.R. 2001. Impacts of logging on storm peak 

flows, flow volumes and suspended sediment loads in Caspar Creek, California. In: 

Wigmosta, M.S.; Burges, S.J., editors. Land use and watersheds: human influence on 

hydrology and geomorphology in urban and forest areas. Water Science and 

Application, Volume 2. Washington, DC: American Geophysical Union: 85-125. 

Montgomery, D.R. 1994. Road surface drainage, channel initiation, and slope instability.

Water Resources Research 30(6): 1925-1932.

Montgomery, D.R.; Dietrich, W.E. 1988. Where do channels begin? Nature 336: 232-234.

Montgomery, D.R.; Dietrich, W.E. 1992. Channel initiation and the problem of landscape 

scale. Science 255: 826-830. 

Montgomery, D.R.; Foufoula-Georgiou, E. 1993. Channel network source representation 

using digital elevation models. Water Resources Research 29: 3925-3934.

Pacific Watershed Associates. 1999. Sediment source investigation and sediment 

reduction plan for the Freshwater Creek watershed, Humboldt County, California.

Prepared for The Pacific Lumber Company, Arcata, California.

Prosser, I.; Abernethy, B. 1996. Predicting the topographic limits to gully network using a 

digital terrain model and process thresholds. Water Resources Research 32: 2289-

2298.

Prosser, I.; Soufi, M. 1998. Controls on gully formation following forest clearing in a 

humid temperate environment. Water Resources Research 34: 3661-3671.

Reid, L.M.; Dunne, T. 1996, Rapid evaluation of sediment budgets. Reiskirchen, Germany: 

Catena Verlag GMBH. 164 p.

Reid, L.M.; Dewey, N.J.; Lisle, T.E.; Hilton, S. 2010. The incidence and role of gullies 

after logging in a coastal redwood forest. Geomorphology 117: 155-169.

Wemple, B.C.; Jones, J.A.; Grant, G.E. 1996. Channel network extension by logging roads 

in two basins, western Cascades, Oregon. Water Resources Bulletin 32(6):1195-1207.

Vandekerckhove, L.; Poesen, J.; Oostwoud WijDenes, D.; Nachtergaele, J.; Kosmas, D.; 

Roxo, M.J.; De Figueredo, T. 2000. Thresholds for gully initiation and sedimentation 

in Mediterranean Europe. Earth Surface Processes Landforms 25: 1201-1220.
41

Physics-Based Simulations of the Impacts 

Forest Management Practices Have on 

Hydrologic Response 

Adrianne Carr1 and Keith Loague2

Abstract

The impacts of logging on near-surface hydrologic response at the catchment and watershed 

scales were examined quantitatively using numerical simulation. The simulations were 

conducted with the Integrated Hydrology Model (InHM) for the North Fork of Caspar Creek 

Experimental Watershed, located near Fort Bragg, California. InHM is a comprehensive 

physics-based hydrologic-response model. The North Fork watershed (including 11 tributary 

catchments) is the site of an ongoing study monitoring the impacts of forest practices. InHM 

was parameterized and calibrated using existing data and new field measurements of soilhydraulic properties. Continuous long-term simulations were conducted for three wet seasons: 

before logging, after logging, and after a period of regrowth. Simulated increases in flow and 

peak discharges were considerably higher after clearcut harvesting. Concept-development

simulations of cumulative watershed effects (CWEs) examined potential impacts of 

alternative timber harvest levels and methods relative to those that occurred in the North Fork 

watershed. Results from these simulations show that the increases in the simulated discharge 

after clearcutting were significant for the catchment and watershed scales and that relatively 

small changes in soil-hydraulic properties produced substantial changes in hydrologic 

response. The simulations in this study illustrate that timber harvesting can alter the 

streamflow generation mechanisms and patterns within a catchment.

Key words: cumulative watershed effects, forest hydrology, hydrologic-response, InHM

Introduction

The impacts of deforestation on the amount and timing of streamflow has been a 

key environmental concern for centuries (see Andreassian 2004). Removal of 

vegetation in a forested ecosystem decreases evapotranspiration and rainfall 

interception, leading to increased discharge and soil-water content (see reviews by 

Andreassian 2004, Bosch and Hewlet 1982, Brown et al. 2005, Jones and Grant 

1996, Jones and Post 2004, Jones et al. 2001). Decreased interception and 

evapotranspiration caused by timber harvest can lead to higher peak flows, higher 

stormflow discharge depths, and higher subsurface pore pressures which can cause 

greater suspended sediment transport, increased downstream flooding, and greater 

likelihood of landsliding, respectively. 

Paired watershed studies to date have mostly provided empirical analysis of the 

impacts of timber harvest on annual water discharge, peak flows, and sediment 

production. The studies of Andreassian (2004), Bosch and Hewlett (1982), Bowling 

et al. (2000), Brown et al. (2005), Burges (2003), Jones and Grant (1996), Jones et al. 

(2001), and Thomas and Megahan (1998) lead to the following generalizations: (i) 

 

1 Hydrologist, Argonne National Laboratory, Environmental Science Division, Argonne, IL 60439. 

(adrianne@anl.gov). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

42

streamflow responses to deforestation and regrowth are variable and dependent upon 

climate; (ii) smaller catchments have much more variability in response to vegetation 

change; (iii) if the average response is not captured (stationary relationship), then the 

monitored impacts may not be interpreted correctly; and (iv) observed data records 

can be quite poor. The observed changes in watershed response can be examined, but 

only through the limited perspective of the climate that occurs during the monitoring 

periods before and after logging. When the largest storm events are missing from the 

data set, the ability to forecast the impacts from extreme events is compromised. 

Simulation can provide answers to some questions, especially when the observed 

data are poor or site monitoring is limited (Alila and Beckers 2001). For example, 

physics-based simulation conducted in a what-if concept-development mode can 

provide useful insights for land managers concerned with the impact of future timber 

harvest/land management scenarios (Dunne, 2001, Dunne et al. 2001, Loague et al. 

2006, Loague and Ebel in press). 

This study examined the impacts of alternative forest management practices on 

near-surface hydrologic response using comprehensive physics-based simulation. 

The effort reported here employed the Integrated Hydrology Model (InHM) for 

simulations of the North Fork of Caspar Creek Experimental Watershed, located near 

Fort Bragg, California. The Integrated Hydrology Model (InHM) was developed by 

VanderKwaak (1999) in the spirit of the Freeze and Harlan (1969) blueprint. InHM 

was designed to quantitatively estimate in a fully-coupled approach, 3D variably 

saturated flow and solute transport in porous media, 3D variably saturated flow and 

solute transport in macropores /fractures, and 2D flow and solute transport over the 

surface and in open channels. The fundamental and innovative characteristics of the

deterministic-conceptual InHM, including no a priori assumption for a specific 

hydrologic-response mechanism, are discussed by Vanderkwaak (1999) and 

Vanderkwaak and Loague (2001). Several successful applications of InHM have 

been reported in the last decade (for example Ebel et al. 2007, 2008; Heppner and 

Loague, 2008, Heppner et al. 2007, Mirus et al. 2007, Ran et al. 2011, and 

VanderKwaak and Loague 2001). 

The Caspar Creek Experimental Watershed (see fig. 1) is the site of a long-term 

monitoring study of the impacts of timber harvest. In 1962 the California Department 

of Forestry and Fire Protection and the U.S. Department of Agriculture, Forest 

Service Pacific Southwest Research Station, Redwood Sciences Laboratory began a 

paired watershed study using two similarly sized basins within the headwaters of 

Caspar Creek watershed (see Ziemer 1998). The North and South Fork Basins are 

shown in fig. 1. The second phase of the Caspar Creek study, beginning in 1985, was 

a multiple paired-catchment study in the North Fork of Caspar Creek that evaluated 

the impacts of the then state-of-the art timber harvest practices (Lewis 1998). Figure

2 shows a selection of the data collected during the study and the gaging stations on 

the 11 North Fork tributary catchments and on the main channel that monitored 

streamflow discharge from 1986 through 1995. 
Physics-Based Simulations of the Impacts Forest Management Practices Have on Hydrologic 

Response 

43

Figure 1—The Caspar Creek Experimental Watershed located within the Jackson 

State Demonstration Forest in coastal Mendocino County, California (after Ziemer 

1998).

Main-channel boundary

V-notch weir

Gaging station

Gaging station name

 Clearcut cable yarded

N

1

Kilometers

0

 Bu ffer zone

Tractor yarded

Y C

G

I L

K

J

M

H

E

B

D

A

V

F

Channel

Catchment boundary

FLY

ARF

LAN

ARF

Main-stem boundary

Figure 2—Outline of the main-channel boundary-value problem on a map of the 

North Fork of Caspar Creek. Management history, main-stem gaging stations, and 

North Fork catchments are identified.
GENERAL TECHNICAL REPORT PSW-GTR-238 

44

Catchment- and watershed-scale simulations 

Hydrologic-response simulations designed to investigate the impacts of timber 

harvest were conducted with InHM for the 11 North Fork Caspar Creek tributary 

catchments and subsequently for the entire North Fork watershed. Simulations were 

conducted for the wet seasons of 3 water years: (i) before logging – water year 1989 

(WY89), (ii) after logging – water year 1992 (WY92), and (iii) after a period of 

regrowth – water year 1995 (WY95). The long-term hydrologic-response simulations 

were conducted for the 5 to 6 month rainy season that included the majority of the 

rainfall during the water year. The hydrologic response for each of the Caspar Creek 

catchments and the entire watershed was examined before and after logging. Changes 

in hydrologic response relative to forest management (for example, clearcutting) 

were assessed by comparison of the results from different simulation scenarios. 

Boundary value problems 

Thirty-three boundary-value problems (BVPs) were set up for catchment-scale

simulations and three BVPs were set up for the watershed-scale simulations. Each

BVP started with a 3D finite-element mesh for the area of interest. For the watershedscale simulations, a main-channel finite-element mesh included all areas of the North 

Fork watershed not considered by the catchment-scale simulations. The mesh for the 

M catchment BVP is shown in fig. 3; the outline of the surface of the main-channel 

BVP is shown in fig. 2. For each BVP the bottom, upstream, and lateral catchment 

boundaries were impermeable. The surface boundary for each mesh was a specified 

flux (potential evapotranspiration and throughfall). The downstream boundaries for 

each BVP were a local head for the subsurface and a critical depth for the surface. 

The local head boundary condition is described by Heppner et al. (2007). For this 

study, the local head values were chosen to be water levels at downstream gaging 

stations for the catchment-scale simulations and the elevation of the confluence of the 

North Fork with the Middle Fork of Caspar Creek for the watershed-scale 

simulations. The x-y node spacing on the surface varied between 2 to 10 m at the 

channel and 24 to 60 m at the watershed boundaries with an average of 2,157 surface 

nodes. The surface of the main-channel mesh was made with an average x-y node 

spacing of 12 m for the channel and 40 to 55 m for the watershed boundaries, with a 

total of 3,522 surface nodes. For all meshes, the layer spacing in the vertical direction 

was 0.05 m for the near-surface layer, grading to 5 m at the bottom of the mesh.

Soil properties

To parameterize and calibrate InHM for the North Fork BVPs for this study, 

historical information was obtained and new field measurements of soil properties 

were made for the North Fork of the Caspar Creek watershed. The new information 

was needed to specify soil-hydraulic properties within the Caspar Creek flow system. 

The measurements made for this study included saturated hydraulic conductivity, soil 

texture, and soil-water retention. Table 1 presents the range of soil hydraulic 

properties used in the simulations.

Climate and vegetation

The surface boundary conditions for the InHM simulations were estimated with 

BROOK90 (Federer 1995). BROOK90 is a process-based model designed to estimate 

evapotranspiration and soil-water movement in one dimension. BROOK90 solves the 

Shuttleworth and Wallace (1985) version of the Penman-Monteith equation to 
45

Table 1—Soil-hydraulic properties for the catchment boundary-value problems for the Caspar Creek watershed.

Range of values Base case

Saturated 

hydraulic 

Saturated 

hydraulic

van 

Genuchten 

parameters

Depth 

(m)

Nodal 

spacing (m)

conductivity 

(ms-1) 

Porosity

 (-) 

conductivity Ks 

(ms-1) 

Porosity 

(-) 

α 

(m-1) 

n 

(-) 

0 - 0.15 a 0.05 3.5 x 10-2 - 1.1 x 10-1 0.40 - 0.57 1.1 x 10-1 0.55 30.00 1.57

0.15 - 0.3b 0.05 2.2 x 10-5 - 3.0 x 10-4 0.45 - 0.47 2.2 x 10-5 0.45 4.24 1.82

0.3 - 1.5 c 0.05 - 0.10 2.6 x 10-6 - 4.0 x 10-6 0.42 2.6 x 10-6 0.42 8.51 1.58

3.0 - 55.0 d 0.5 - 5.0 2.0 x 10-7 0.10 2.0 x 10-7 0.10 4.30 1.20 a soil layer 1; b soil layer 2; c soil layer 3; d bedrock

Table 2—Vegetation properties for the BROOK90 simulations of the Caspar Creek watershed. 

Vegetation properties Second 

growth 

WY89 

Clearcut 

WY92 

Regrowth 

WY95 

Source

Leaf area index (-) 10 0 1 Reid and Lewis (2006)

Tree height (m) 60 0 1.5 Noss (2000)

Leaf width (m) 0.004 0 0.004 Fedderer (1995)

Maximum leaf conductance (ms-1) 0.0053 0 0.003 Korner et al. (1979), Korner (1994)

Maximum plant conductivity (ms-1) 30 0 5 Fedderer (1995)

Fraction of plant resistance in xylem (%) 25 0 7 Phillips et al. (2003)

Minimum plant leaf water potential (Mpa) -2 0 -0.5 Koch et al. (2004), Woodruff et al. 

(2004)

Albedo (-) 0.14 0.15 0.15 Fedderer (1995)
GENERAL TECHNICAL REPORT PSW -GTR -238 

46

determine the potential evapotranspiration from a single layer canopy and the soil 

surface based on climate and vegetation information from Caspar Creek. BROOK90 

also estimates net throughfall, after rainfall interception and evaporation using a 

simple water balance method. The reader is referred to Federer (1995) for a complete 

description of BROOK90. 

 

A

A'

Impermeable

boundary

Local head boundary Critical depth

Impermeable

boundary

(a)

150

200

250

300

Elevation (m)

3600 3800 4000

Distance (m)

A

A'

Precipitation/Potential evapotranspiration

Local head

boundary

Impermeable

(b)

Figure 3—M catchment boundary-value problem used for simulations of hydrologic 

response and management impacts in the Caspar Creek watershed. (a) 3D mesh 

and boundary conditions. (b) Vertical cross-section taken from A-A’ in (a) showing the 

mesh and boundary conditions with no vertical exaggeration.

The climate forcing data input to BROOK90 measured at Caspar Creek were (i) 

precipitation at five minute intervals, (ii) daily maximum and minimum air 

temperature, and (iii) daily solar radiation. Vapor pressure was approximated with 

BROOK90 using an algorithm developed by Murray (1967). Daily wind speed for 

the Caspar Creek watershed was derived from the NCEP/NCAR Reanalysis Data 

(Kalnay et al. 1996). Monthly average values of air temperature or solar radiation 

(calculated from 1986 to 1996) were substituted for missing measurements. When 

available, the vegetation properties were chosen based on site-specific information 

from Caspar Creek. Table 2 provides the vegetation property values used in the 

BROOK90 simulations. Throughfall and potential evapotranspiration estimates from 

BROOK90, in 5 minute intervals, were used in the InHM simulations. The 
Physics-Based Simulations of the Impacts Forest Management Practices Have on Hydrologic 

Response 

47

interception estimates from BROOK90 were calibrated against measurements from 

Caspar Creek (Reid and Lewis 2007). 

Simulation procedure 

The long-term simulations were conducted for the 5 to 6 month rainy season that 

included the majority of the rainfall during the entire water year. Initial conditions for 

each BVP were estimated (by simulation) before each rainy season. Then there was 

some calibration of InHM before the final hydrologic response simulations for the 

Caspar Creek catchments. For the watershed-scale simulations, the results from the 

long-term catchment-scale simulations were applied as input to the main-channel 

simulations for all 3 water years. The simulated hydrologic response results for the 

Caspar Creek catchments and the entire North Fork watershed were compared with 

observed data to (i) better understand hydrologic response related to the impacts of 

logging and (ii) evaluate the performance of InHM.

Model calibration

The M catchment had the most complete observed discharge record for the water 

years focused on in this study and was, therefore, used to parameterize and calibrate 

InHM. The M catchment simulation was calibrated to observed discharge data. The 

calibration was initially done for the first large storm (event 1) of WY89 and then for 

the entire WY89 simulation period. The InHM-simulated hydrologic response for the 

M catchment reproduced the transient observed discharge record to an acceptable 

level. Therefore, the M catchment calibration was used to parameterize all of the 

other catchments for this study. No calibration was done for the main-channel 

watershed-scale simulation. Further details of the calibration can be found in Carr 

(2006). 

Management impact simulations 

To simulate the impacts of forest harvesting at Caspar Creek, the BROOK90 

vegetation properties were changed to represent clearcutting (WY92) and regrowth 

(WY95). The management impact simulations represented timber harvest patterns 

that occurred in the North Fork of Caspar Creek before WY92 (fig. 1). All of the 

BROOK90 parameter values for the three simulation periods are shown in table 2. 

After clearcutting, the leaf area index was set to zero in the catchments that were 

clearcut and was set to five for the main-channel simulation that was partially cut. As 

a result, there was no interception in the clearcut areas; and all of the rainfall was 

assumed to reach the ground as throughfall. Due to lack of field information, the soil 

properties were unchanged in the InHM BVPs after logging. It should be pointed out, 

however, that the cable yarding method of timber harvest is known to be fairly nonintrusive to soils (Laffan et al. 2001, Swank and Elliot 2001), so the assumption of 

minimal soil disturbance is a valid one.

Results

Model performance

Simulated streamflow was compared with observations for nine of the 11 

catchments and for the watershed-scale results. Streamflow data are available in tenminute intervals for all catchments, providing a good data set to compare to 

simulation results. However, upon close inspection one finds that much of this data 

was interpolated from sparse measurements. In some cases, actual streamflow 
GENERAL TECHNICAL REPORT PSW-GTR-238 

48

measurements were much more infrequent than the ten-minute interval. In the early 

years, the data resolution was acceptable during most large storms but was sparse or 

absent during low-flow periods. The data quality improved in later years. Model 

performance was often poor during periods of poor data resolution. InHM performed 

best during the wetter periods for this study. Specifically, the model performed better 

for big storms and best for large events with high antecedent moisture content. It 

should be noted that WY89, WY92, and WY95 had average, below average, and 

above average annual rainfall. The performance of InHM was best for WY95, the 

wettest year and the year with the most complete observed data. A full discussion of 

model performance for this study can be found in Carr (2006). 

Management impacts on hydrologic response

The increases in throughfall and decreases in potential evapotranspiration caused 

by timber harvesting had significant impacts on the simulated hydrologic response 

for the Caspar Creek watershed. Downstream measurement points captured the 

response in watersheds with a portion of the upstream area clearcut (partial clearcut) 

and the entire area clearcut (full clearcut). There was a large increase in simulated 

discharge depths during WY92 and WY95 after partial and full clearcut harvesting of 

the drainage area. The simulated increases in discharge depth after logging for WY92

and WY95, compared to the second growth response are shown in table 3. The most 

significant factor impacting the discharge of the catchments after logging was the 

increase in throughfall. Increases in throughfall result from reduced interception and 

the loss of evaporation from intercepted water. 

Table 3—Percent increases in simulated discharge depth when compared to the second 

growth response. 

WY92 WY95

Catchment Watershed Catchment Watershed

Partial clearcut 127 121 51 54

Full clearcut 204 NA 105 NA

Cumulative watershed effects simulations

The what-if concept-development simulations performed for this study examined 

the potential impacts of alternate timber harvest levels and methods relative to those 

that occurred between 1989 and 1991 at the North Fork of Caspar Creek watershed. 

Both the catchment- and watershed-scale hydrologic responses to different methods 

and magnitudes of timber harvesting were considered.

The CWEs simulations were carried out in three parts: (i) the hydrologic 

response changes resulting from a clearcut vegetation scenario were examined for the 

unharvested Caspar Creek catchments; (ii) the impacts of 100 percent clearcut timber 

harvest were examined for the entire North Fork watershed; and (iii) the impacts of 

soil compaction due to logging with skidders on seasonal hydrologic response and on 

the hydrologic response to a large rainfall event were examined for the nested 

catchment group K, M, and J. Using the same catchment and the same climate, 

thechanges in hydrologic response as a result of forest clearing and alternate forest 

practices were directly evaluated against the hydrologic response with a second 

growth vegetation scenario. 
Physics-Based Simulations of the Impacts Forest Management Practices Have on Hydrologic 

Response 

49

The simulated peak discharges for the largest storms increased approximately 40 

percent at both the catchment and watershed scales as a result of 100 percent clearcut 

timber harvesting. In addition to the change in the water balance caused by a decrease 

in interception and evapotranspiration after logging, soil compaction directly 

impacted the overall hydrologic response. The simulated peak discharges for the 

largest storm increased an average of 63 percent for the K, M and J catchments (with 

changed soil hydraulic properties), illustrating this impact. The significant increases 

in simulated discharge in this study could cause considerable increases in the 

sediment carrying capacity. 

This research represents a first step towards using comprehensive physics-based 

simulation to investigate the impacts of timber harvest. The work conducted for this 

study sets the stage for unraveling the complex processes that lead to hydrologicallydriven cumulative watershed effects (CWEs) such as flooding, slope-stability, 

sediment transport, and their impacts on, for example, salmon habitat health. Changes 

in watershed function will most certainly accompany logging activities, but 

thresholds for adverse significant changes should, ideally, be decided upon before 

management actions so that adverse impacts can be prevented. By defining 

thresholds of, for example, maximum peak discharges, significant adverse CWEs can 

be avoided by proper management. The simulation-based approach presented here 

could/should be extended and employed to identify strategies for preventing/reducing 

adverse CWEs.

Acknowledgments

We thank the dedicated scientists and land managers at the USDA Forest Service 

Redwood Sciences Lab and California Department of Forestry at the Jackson State 

Demonstration Forest for their help throughout the years. The support of our longterm colleague Joel VanderKwaak is greatly appreciated. Thanks also to Brian Ebel, 

Ben Mirus, Chris Heppner, Laurie Benson, Adam Aables, Ben Kozlowicz, Kirsten 

White, Richard Edward Watts, Jon Sack, and Jennifer Aspittle for being excellent 

field assistants. This effort was supported by a US Environmental Protection Agency 

STAR fellowship, an ARCS of Northern California fellowship, a Stanford Graduate 

Fellowship, the now defunct Center for Earth Science Research (CESIR), and the 

Department of Geological and Environmental Sciences at Stanford University. We 

are grateful to the anonymous reviewers for their thoughtful comments. 

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53

Erosion at Decommissioned Road-Stream 

Crossings: Case Studies from Three 

Northern California Watersheds

Sam A. Flanagan1, David Fuller1, Leonard Job1, and Sam 

Morrison2

Abstract

Post-treatment erosion was observed for 41 decommissioned road stream crossings in three 

northern California watersheds. Sites were purposefully selected in order to characterize the 

nature and range of post-treatment erosional responses. Sites with the highest visible erosion 

were selected in order to better understand the dominant process and incorporate any lessons 

learned into future projects. Sites were also intentionally selected where post-treatment 

erosion appeared to be negligible, or excavation techniques were judged be have been fully 

effective at removing erodible material. In these cases, our objectives and methods remained 

identical, but we wanted to examine the conditions that led to the apparent negligible erosion. 

Results are consistent with other findings in the region. Erosion volumes ranged from 1.5 m3

to 60 m3

, or, 0.1 percent to 4.5 percent of the initial volume excavated during treatment. 

Erosion averaged 11 m3 per site or 0.4 percent of excavated volume in the Headwaters Forest 

Reserve and 21 m3 per site or 2.4 percent of excavated volume in Lacks Creek. Repeat 

monitoring of a sub-set of sites in the Headwaters Forest Reserve over subsequent years, 

indicates that 99 percent of post-treatment erosion occurs in the first year following treatment. 

Channel incision is the dominant process of sediment production from treated sites, 

accounting for 80 percent of observed erosion. In response, woody debris has been 

incorporated into recently excavated crossings with the intent of providing armor and 

roughness elements to reduce channel incision. At those sites where post-treatment erosion is 

apparently minimal, incision remains the dominant process of sediment generation and can 

exceed 20 m3

. In some cases, excavation techniques were judged to be largely effective at 

removing erodible material, however, interstitial material stored between larger, more 

immobile clasts can produce surprisingly large erosion volumes as this material is winnowed 

away during higher flows.

Key words: erosion, road decommissioning, watershed restoration, sediment

Introduction

Removal of logging roads is an established method for reducing ongoing and 

potential sediment delivery to aquatic habitat sensitive to sediment inputs (for 

example, Madej 2001, PWA 2005). Across the redwood region of northern 

California, road removal programs implemented by a variety of landowners have 

resulted in substantial reductions in potential sediment delivery. For example, in the 

Redwood Creek watershed, for the period 1998 to 2000, road treatments have 

reduced the quantities of potentially deliverable road-related sediment by 58 percent 

 

1 Bureau of Land Management, Arcata Field Office, 1695 Heindon Road, Arcata, CA 95521 

(sam_flanaganii@blm.gov). 2 BLM retired.
GENERAL TECHNICAL REPORT PSW-GTR-238 

54

in the lower portion of the watershed on National Park lands, and 18 percent in the 

upper two-thirds of the watershed3

. 

Several efforts in the northern redwood region have documented erosion 

following road decommissioning at road-stream crossings (table 1). Most of these 

studies have shown that channel incision is the dominant form of erosion to occur, 

followed by side slope failures and surface erosion. All of these studies have 

documented post-treatment erosion, with the bulk of the erosion occurring in the first 

winter following treatment (table 1).

The intent of this study is to examine post-treatment erosion at road-stream 

crossings to inform managers, project supervisors and equipment operators on project 

effectiveness. Site selection was intended to develop a series of case studies to 

explore the range of responses experienced at decommissioned crossings. In this 

paper, our specific objectives are to:

1) Describe the principal erosional processes at work.

2) Quantify erosion volumes in the years following treatment. 

3) Assess the temporal distribution of erosion.

4) Quantify erosion quantities at sites where best management practices 

appeared to be met, but erosion was still evident. 

5) Contemplate measures to reduce erosion from future treatment sites.

We compare our findings from BLM-managed lands to studies conducted 

elsewhere in the northern redwood region and offer suggestions for future 

investigative work.

Study sites

The Bureau of Land Management (BLM) manages land in the Redwood Creek, 

Elk River and Salmon Creek watersheds. Redwood Creek and Elk River watersheds 

are listed as sediment impaired under the Clean Water Act 303(d) listing process. The 

areas contain an extensive network of older logging roads. In addition, all three 

watersheds provide habitat for federally listed salmon and steelhead populations. 

Headwaters Forest Reserve

The Headwaters Forest Reserve (Reserve) is located in the headwaters of Salmon 

Creek and the South Fork Elk River, both tributaries to Humboldt Bay in Humboldt 

County, California. The Reserve was established in 1999 (BLM-CDFG 2004) and 

encompasses 30 km2

 of mixed redwood and Douglas fir forest. Approximately 12.5 

km2

 of the Reserve is old growth redwood forest with little road construction. 

Approximately 85 km of roads were constructed throughout the Reserve from the 

1950s through the 1990s. Many of these roads were constructed along streams or 

geologic contacts where a natural bench was present. 

A previous road assessment identified approximately 50 km of road in the South Fork 

Elk River watershed (PWA 2004). The assessment identified nearly 83,000 m3

 of 

potentially deliverable road sediment. Of this, approximately 58,000 m3 was 

identified from 242 stream crossings (PWA 2004). 

 

3 G. Bundros, Geologist, Redwood National and State Parks. June, 2011; personal communication.
Erosion at Decommissioned Road-Stream Crossings: Case Studies from Three Northern California 

Watersheds

55

Table 1—Summary of studies investigating erosion at decommissioned road-stream 

crossings in northwest California. 

Author(s) Location # 

sites

Average 

erosion 

(m3)

% of 

excavated 

volumea

Comments

Klein 

(1987)

Redwood Creek, 

Humboldt County

24 26.6 n/a

Madej 

(2001)

Redwood Creek, 

Humboldt County

207 50 4.8 Incision and 

assoc. bank 

erosion most 

common

Klein 

(2003)

Upper Mattole River, 

Humboldt/Mendocino 

Counties

18 11.9 n/a Channel 

incision 88% 

of observed 

erosion

PWA 

(2005)

Northern California 614 26 5 Incision 

greatest # of 

sites, surface 

erosion 

greatest 

volume

Cook and 

Dresser 

(2007)

Six Rivers National 

Forest

262 21 4.5 40% incision

60% bank 

failure

Keppeler 

and others 

(2007)

Caspar Creek, Mendocino 

County

25 24.6 4 83% of erosion 

after first 

winter

Maurin 

(2008)

Smith River, Del Norte 

County and Redwood 

Creek, Humboldt County

16 6.8 n/a Noted need for 

further work 

on woody 

debris

PWA 

(2008)

Redwood Creek, 

Humboldt County

16 8.8 0.9

Klein 

(2009)

Lost Man Creek, 

Humboldt County

30 14.7 0.4 15% of 

additional 

erosion 

following 

initial winter

Wilson 

(2008)

Headwaters Forest 

Reserve, Humboldt 

County

8 5.4 n/a Incision 98% 

of observed 

erosion a Expressed as total eroded volume as a proportion of excavated volume. See Klein (2003) for discussion 

on various means of displaying erosion results.

Road removal efforts began in the Reserve in 1999, focused on those road 

segments with the greatest potential to deliver sediment. Over the period 1999 

through 2010, 34 km of road have been decommissioned in the Reserve 

encompassing both the Salmon Creek and South Fork Elk River watersheds. 

Lacks Creek

Lacks Creek watershed is a 50 km2 tributary to Redwood Creek in Humboldt 

County, California. The BLM manages approximately 60 percent of the watershed 
GENERAL TECHNICAL REPORT PSW-GTR-238 

56

with the remainder in private ranch lands. Road assessment efforts have identified 

approximately 150 km of roads in the watershed with the potential to deliver 

approximately 150,000 m3 of material (Bundros et al. 2004). Over the period 2007 

through 2010, 13.6 km of road have been decommissioned and 26.3 km have been 

upgraded along the 101 km of road on BLM lands in the watershed. 

Methods

Site selection 

Sites were selected in order to provide a series of “case studies” to inform 

managers, project supervisors and equipment operators on the range of erosional 

conditions experienced following crossing removal. Site selection was based on our 

intent of capturing instances of larger erosional responses in the hopes of avoiding 

such occurrences in the future. Sites were visited following the first winter after 

treatment. In the Reserve, a sub-set of sites were re-occupied to assess erosion in 

subsequent years.

Erosional processes 

We considered three types of erosion during our site visits: channel incision, 

bank failure, and rill/gully erosion along channel sideslopes. In practice, we 

recognized that some bank failures were likely triggered by channel incision. 

Regardless, we recorded these as bank failures. At each site, we recorded eroded 

volume. No attempt was made to quantify what proportion of the eroded volume was 

delivered to the channel network. 

Tapes and marked depth sticks were used to record linear dimensions of eroded 

features. Where erosion patterns were relatively uniform, such as channel incision 

throughout the crossing, we measured width at three to six cross sections through the 

site and depth at three to seven points along each cross section. Values were averaged 

for each cross section and multiplied by the length of the feature. Where numerous or 

complex erosional features were present, we divided the site into two or more 

separate erosional features and calculated erosional volumes. Individual erosion 

features < 0.5 m3 were not recorded. 

Results

Forty two sites were assessed for erosion following treatment (table 2). At the 

Reserve sites, we revisited 19 sites from 2 to 10 years following our initial visit to 

determine the extent of any additional erosion. 

Table 2—Erosional responses from 41 decommissioned crossings on BLM-managed lands.

Location # 

sites

Average 

erosion 

(m3

) 

% 

incision

% 

erosion 

occurring 

first year

% 

excavated 

volumea

Average 

drainage 

area 

(ha)

Average 

channel 

slope 

(%)

Lacks Creek 13 21 89 n/a 2.4 16.5 33.7

Headwaters 

Forest 

Reserve

28 10.8 68 99 0.4 20.7 25.5
Erosion at Decommissioned Road-Stream Crossings: Case Studies from Three Northern California 

Watersheds

57

a Expressed as total eroded volume as a proportion of excavated volume. See Klein (2003) for discussion 

on various means of displaying erosion results.

Discussion

Erosional volumes 

Our results are consistent with others in the region. Average erosion across the 10 

studies reviewed and summarized in table 1 was 19.5 m3 compared with the 21 m3

and 11 m3 observed in Lacks Creek and the Reserve, respectively. Expressed as a 

proportion of excavated volume, values also reflect the greater erosion in Lacks 

Creek. Readers are encouraged to refer to Klein (2003) for a discussion of various 

ways of expressing eroded volumes in context of either the site or watershed-scale 

sediment budgets. In short, we chose to express our erosion volumes in the context of 

excavated volumes due to reporting requirements and a lack of watershed-wide 

sediment budget data which would enable us to report the erosion volumes in the 

context of watershed-wide sediment sources. 

We observed relatively large erosion volumes from sites where all appropriate 

treatment methods had been employed. Finished side slopes, channel slope and width 

through the site were appropriate for the setting. At one site in Lacks Creek, 54 m3

 of 

channel incision occurred. This was the largest site by drainage area (168 ha). The 

channel developed on this terrain flows over boulders in excess of two meters 

diameter. Winnowing of remnant fill material from amongst the boulders and 

consequent incision upstream was the source of the eroded sediment. However, in 

our judgment, further excavation was not possible given the equipment on site. Any 

further reductions in potentially erodible volume would have come with great time 

and expense to dissect the material out from the boulder insterstices.

We also note that a seemingly small incision notch over a long crossing can 

produce eroded volumes on the order of 2 to 6 m3

. While “under excavation” is often 

cited as a reason for channel incision, our findings suggest that some amount of 

channel incision is unavoidable at many sites. 

Temporal distribution of erosion 

In the Reserve, we revisited 19 sites a second time 2 to 5 years after treatment. 

Five of the sites were visited a third time. Only four sites showed evidence of 

subsequent erosion and the erosion observed was <1 m3

. Our results indicate that 99

percent of the post-treatment erosion occurs in the first winter following treatment. 

However, during our site visits in the Reserve, we noted that heavy re-growth in the 

years following treatment may have concealed some instances of subsequent erosion. 

However, we are confident that any larger erosional features (>5 m3

) would likely 

have been detected. This is consistent with others who noted the bulk of erosion 

occurring in the first winter season (table 1).

The role of woody debris in erosion rates 

In response to our findings, we have begun placing woody debris in the channel 

to arrest, or at least minimize channel incision. The effectiveness of wood placement 

on post-treatment erosion has not been systematically studied. Maurin (2008), 

working in Lost Man Creek, concluded that more work was needed on woody debris 
GENERAL TECHNICAL REPORT PSW-GTR-238 

58

placement strategies. His small sample size precluded any conclusions on the 

effectiveness of various placement strategies. Our initial observations suggest that 

wood placement may be least effective on areas of extensively sheared bedrock such 

as occurs in the Incoherent Unit of Coyote Creek. In these areas, channel incision 

leaves the wood ineffectively perched above the channel bed. In other areas, 

however, the placement of logs nearly perpendicular to the channel appears to create 

a series of storage compartments that effectively traps sediment eroded from 

upstream. We agree with Maurin (2008) that more work is needed in this area to 

determine the best strategies for incorporating woody debris into excavated stream 

crossings.

Conclusions

Our observations of erosion following the decommissioning of road-stream 

crossings add to a growing data set of regional observations. Both the volumes and 

style of erosion are consistent with others’ observations in northwest California. Our 

results suggest that post-treatment erosion likely cannot be avoided and that channel 

incision is the dominant erosional response. Areas warranting further examination are 

treatment of crossings in areas of highly sheared bedrock and the best use of woody 

debris in these and other sites. 

References

Bureau of Land Management and California Department of Fish and Game (BLM-CDFG). 

2004. Record of Decision for Headwaters Forest Reserve Resource Management 

Plan. Arcata Field Office. June, 2004. 15 p. 

http://www.blm.gov/ca/st/en/fo/arcata/headwaters_rod.html. 

Bureau of Land Management (BLM). 2008. Lacks Creek Management Area. Preliminary 

Management Plan. Preliminary Environmental Assessment. Arcata Field Office, 

August, 2008. 139 p. http://www.blm.gov/ca/st/en/fo/arcata/lacks_creek_prelim.html. 

Bundros, G.J.; Short, D.; Hare, V.C. 2004. Upper Redwood Creek watershed road 

assessment: updated summary report. Redwood National and State Parks report to 

the Pacific Coast Fish, Wildlife and Wetlands Restoration Association. Unpublished

report. 129 p.

Cook, C.; Dresser, D. 2007. Erosion and channel adjustments following forest road 

decommissioning, Six Rivers National Forest. In: Furniss, M.; Clifton, C.; 

Ronnenberg, K., editors. Advancing the fundamental sciences: proceedings of the Forest 

Service national earth sciences conference, San Diego, CA, 18-22 October 2004. PNWGTR-689, Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station: 297-309.

Keppeler, E.T.; Cafferata, P.H.; Baxter, W.T. 2007. State Forest Road 600: a riparian road 

decommissioning case study in Jackson Demonstration State Forest. California 

Forestry Note No. 120. Sacramento, CA: California Department of Forestry and Fire 

Protection. 22 p.

Klein, R.D. 1987. Stream channel adjustments following logging road removal in 

Redwood National Park. Redwood National Park Technical Report Number 23. 

Arcata, CA: National Park Service, Redwood National Park. 48 p.
Erosion at Decommissioned Road-Stream Crossings: Case Studies from Three Northern California 

Watersheds

59

Klein, R.D. 2003. Erosion and turbidity monitoring report; Sanctuary Forest stream 

crossing excavations in the upper Mattole River Basin, 2002-2003. Prepared for: 

Sanctuary Forest, Inc. Whitethorn, CA. 35 p.

Klein, R.D. 2009. Erosion and turbidity monitoring in Lost Man Creek, Redwood 

National and State Parks, water years 2003-2008. Arcata, CA: Redwood National 

Park. 36 p.

Madej, M.A. 2001. Erosion and sediment delivery following removal of forest roads.

Earth Surface Processes and Landforms 26: 175-190.

Maurin, L.P. 2008. First-year erosion responses following stream channel crossing fill 

removal in Redwood National and State Parks, northwestern California. Arcata, 

CA:. Humboldt State University. M.S. thesis. 85 p.

Pacific Watershed Associates (PWA). 2004. Summary report, 2002-4 South Fork Elk 

River Road assessment and restoration plan, Headwaters Forest Reserve, 

Humboldt County, California. Arcata, CA: Pacific Watershed Associates. 154 p.

Pacific Watershed Associates (PWA). 2005. Evaluation of road decommissioning, CDFG 

fisheries restoration grant program, 1998 to 2003. Final Report submitted to the 

California Department of Fish and Game under Contract #P0210559. Arcata, CA. 81 p.

Pacific Watershed Associates (PWA). 2008. 2006-2008 Upper Redwood Creek Watershed 

improvement project, Humboldt County, CA. PWA Report No. 08077401. 

December, 2008. Arcata, CA. 73 p.

Wilson, S.E. 2008. Post-treatment erosion of decommissioned forest road stream 

crossings. Arcata, CA: Humboldt State University. M.S. thesis. 47 p.

61

Large Woody Debris Budgets in the Caspar 

Creek Experimental Watersheds1

 

Sue Hilton2

Abstract

Monitoring of large woody debris (LWD) in the two mainstem channels of the Caspar Creek 

Experimental Watersheds since 1998, combined with older data from other work in the 

watersheds, gives estimates of channel wood input rates, survival, and outputs in 

intermediate-sized channels in coastal redwood forests. Input rates from standing trees for the 

two reaches over a 15 year period varied from a high of 28 m3

/km/yr in the North Fork (in 

1995) to a low of 0.12 m3

/km/yr in the South Fork (from 2000 to 2002). Rates in the South 

Fork, where a second-growth forest was selectively logged in the 1970s, have consistently 

been lower than those in the North Fork, where partial clearcutting in the 1990s left buffer 

strips along the channel. Since 2004, inputs in both reaches have been between 2 and 8 

m3

/km/yr and are dominated by inputs from snags. More than 90 percent of the volume of 

conifer pieces that entered the channel in 1995 was still present in 2010; alder pieces from 

that period are mostly gone. Wood budgets demonstrate the contrast in wood volumes 

between the two channels and the importance of stored wood in the system.

Key words: in-stream wood, wood budgets, large woody debris, buffer strips 

Introduction

An important aspect of sustainable forest management is maintaining adequate 

levels and types of large woody debris (LWD) in stream channels. Because LWD 

inputs are often episodic and pieces can persist for decades in the channel, an LWD 

budgeting approach can be a useful tool to estimate long-term effects of management 

activities, but such budgets are limited by the reliability of the estimates used for 

inputs, survival, and outputs. In the Caspar Creek Experimental Watersheds, an 

influx of LWD in the North Fork channel in 1995 created an opportunity to monitor 

piece persistence in that channel and to compare input and survival rates between the 

North and South Fork channels, which are adjacent to stands with contrasting forest 

management histories. 

There is a large body of literature on LWD volumes in stream channels, but few 

studies have documented LWD dynamics over time (Wohl et. al. 2010). At Caspar 

Creek, O’Connor and Ziemer (1989) sampled LWD in the North Fork channel, and 

Surfleet and Ziemer (1989) sampled wood in both the North Fork and South Fork 

channels shortly after the North Fork logging. The current study differs from earlier 

Caspar studies by using monitoring of all large pieces within defined reaches to 

understand what causes changes in volume over time. 

 

1 This paper was presented at the redwood science symposium: coast redwood forests in a changing 

California. June 21-23, 2011, University of California, Santa Cruz. 2 Pacific Southwest Research Station, 1700 Bayview, Arcata, CA 95521; (707) 825-2927. 

(shilton@fs.fed.us).
GENERAL TECHNICAL REPORT PSW-GTR-238 

62

Methods

The study area is in the Caspar Creek Experimental Watersheds, Jackson 

Demonstration State Forest, Mendocino County, California. Stream-adjacent stands 

are dominated by coast redwood (Sequoia sempervirens), Douglas-fir (Pseudotsuga 

menziesii), grand fir (Abies grandis), and, in the South Fork, red alder (Alnus rubra). 

Both watersheds were clearcut, with channel clearing, in the 1860s through the early 

1900s. Selective logging (with stream-adjacent roads) in the South Fork in the early 

1970s removed about 2/3 of the standing volume. A series of small clearcuts with 

partially cut buffers along the mainstem channel removed approximately 45 percent 

of the volume in the North Fork watershed upstream of the XYZ tributary between

1989 and 1991 (Henry 1998). Some wood was removed from South Fork channels 

during logging. Buffer strips prevented as much wood from entering the North Fork 

channel during logging as had entered during South Fork logging, and any that did 

enter remained there rather than being yarded out. Some pieces, particularly in the 

North Fork, have been cut to maintain access trails for streamflow studies. 

The North and South Fork watersheds have weir ponds at the downstream ends. 

The study reaches are along the mainstem channels upstream of these ponds, and, in 

the North Fork, upstream of the first major tributary. Reach slopes range from one to 

three percent, and mean bed widths vary from 6 m near the weir ponds to 2 m at the 

upstream ends of the study reaches. Characteristics of the two watersheds include:

Characteristics North Fork South Fork 

Study reach length (m) 1822 1945 

Watershed area, downstream end (ha) 391 393 

Watershed area, upstream end (ha) 163 190 

Field crews tagged and measured existing and new wood pieces in the study 

reaches starting in 1998. For each piece, median (or, for oddly-shaped pieces, 

average) diameter, length within a zone extending 1 m horizontal distance outside of 

the edge of the active channel, species, position, decay class, and distance from a 

benchmark were recorded. Any available evidence of input date, source distance 

from the bank, whether the source tree was a snag, and input mechanism was noted. 

Length in the active channel was estimated in the South Fork. Down live trees 

(leaning more than 45 degrees from vertical) and standing trees or stumps that 

interacted with the stream bed were included. 

The original objective of the study was to monitor survival of pieces contributed 

by a series of windstorms in 1995 (Reid and Hilton 1998), so the 1998 tagging 

included all pieces > 0.1 m3 from trees that entered the channel from 1995 to 1998 

and pre-existing pieces >0.3 m diameter and >2.5 m long or >0.15 m diameter and 

>0.5 m3

. It quickly became obvious, however, that in order to identify new inputs 

(particularly from snags) all pieces larger than some minimum size needed to be 

tagged, so in 1999 all pieces >0.15 m diameter and >2.5 m long in the North Fork, 

and in 2000 in the South Fork all pieces >0.2 m diameter and >1.5 m long were 

tagged. In the North Fork, tagged pieces were mapped on existing channel maps that 

show all pieces >0.15 m diameter and >1 m long. The South Fork channel was 

surveyed in 2001 and wood pieces were mapped beginning in 2004; before that, 

pieces were located by distance upstream from the downstream end of the reach. In 

2002, 2004, 2006, and 2008, existing pieces were checked and new, moved, broken, 

or changed pieces >0.2 m diameter and >2 m long in both channels were tagged and 
Large Woody Debris Budgets in the Caspar Creek Experimental Watersheds

63

measured. In 2010, new hillslope inputs were tagged and the current status of 1995 

inputs in the North Fork and 1995 to 2000 inputs in the South Fork was checked. The 

study is continuing; this paper presents preliminary results as of 2010. 

I calculated channel input rates from standing hillslope trees from 1995 to 2010. 

For inputs from 1998 to 2010, I used new tree data from each year’s survey. For 1995 

inputs I used 1998 survey data and source information. In the North Fork, most trees 

from 1995 were flagged shortly after they fell, and most of those were checked in the 

1998 survey, but because some pieces would have broken up or moved out of the 

channel by 1998 some volume is missing. In the South Fork, 1995 inputs are based 

on trees found in 1998 that appeared (from the condition of the bark, branches and 

twigs, and surrounding vegetation) to have been down for about 3 years. Pieces from 

snags were difficult to identify and age, so snag inputs are likely to be underestimated 

in both forks through 1998. 

Wood volume budgets (inputs, changes, and net gain or loss) were calculated for 

pieces >0.2 m diameter and >2 m long for each survey interval. Because field crews 

did not tag all pieces larger than that size in 1998, I estimated volumes that were 

present in the channel in 1998 but not tagged. Many pieces were later tagged, and I 

used notes from the field crews, existing pool maps, and, in the North Fork, existing 

channel maps, to determine which pieces had been present since 1998. However, 

there were presumably some pieces >0.2 m diameter and >2 m long that were not 

tagged in 1998 and left the channel between 1998 and 2002 (or, in the South Fork, 

2000), when tagging began on all pieces of that size or larger.

In the North Fork, the channel maps provided information needed for an estimate 

of this missing volume. For all pieces marked as “gone” in 1999 or 2002, I measured 

the mapped length within a zone defined by lines drawn 1 m outside of the mapped 

edge of the bank and summed those lengths by mapped diameter class. I calculated 

the diameter distribution within each class for pieces tagged in 1999 that had been 

previously mapped (these pieces were smaller than all pieces tagged in 1999, because 

the larger pieces had been tagged in 1998), and used the percent by diameter within 

each class to calculate a total volume gone for each period. In the South Fork, I 

estimated volumes of untagged pieces that had disappeared by 2000 but were shown 

in pool sketches from a 480 m subreach drawn in 1998 and 1999.That loss estimate 

was adjusted for logs not in pools (92 percent of logs tagged in 1998 in the pool 

subreach were in pools), and scaled back up to the full length of the study reach. Both 

estimates are approximate, and are likely to be accurate to ±50 percent.

Results and discussion

Hillslope input rates

Input rates from standing trees from 1995 to 2010 (table 1) show the combined 

effects of episodic events and stand history. High input rates in the North Fork in 

1995 and 1996 show the effects of the 1995 windstorms, particularly in buffer strips 

adjacent to clearcuts, while those same storms had much less effect in the smaller, 

younger stands in the South Fork. Rates in the North Fork decreased rapidly though 

the late 1990s, then increased as new fir snags began contributing wood. Snag inputs 

also increased in the South Fork, both from fir snags and from riparian alders. By 

2010, input rates were less erratic, and South Fork rates were approaching North Fork 
GENERAL TECHNICAL REPORT PSW-GTR-238 

64

rates. However, inputs to both channels are dominated by short-lived species (grand 

fir in the North Fork and grand fir and alder in the South Fork) and may diminish 

over time as those species disappear from the stands. 

Table 1—Volume of large wood contributed to stream channels from standing trees by year, 

species, and snag status. 1996 inputs entered between January and December 1995; later 

inputs entered between the previous survey and the listed year. Units are m3

/km/yr of pieces 

>2m long and >0.2 m diameter. 

North Fork 1996 1998 1999 2002 2004 2006 2008 2010

Redwood live 2.36 0.38 0.0 0.27 0.49 0.31 0.51 0.19

Redwood snag 0.0a 0.0a 0.0 0.0 0.0 0.0 0.0 0.03

Douglas-fir live 18.96 8.06 2.06 1.30 2.56 0.63 0.0 0.85

Douglas-fir snag 2.48a 3.56a 2.70 2.11 5.93 5.17 4.33 1.96

Grand Fir & otherb

live 3.81 0.97 0.0 0.02 0.06 0.03 0.53 0.0

Grand Fir & 

otherbsnag 0.56a 0.61a 0.0 0.45 1.18 1.11 0.62 4.17

South Fork 1996 1998 2000 2002 2004 2006 2008 2010

Redwood live 0.30 1.64 0.0 0.02 0.53 0.90 0.29 0.24

Redwood snag 0.0a 0.0a 0.0 0.0 0.0 0.0 0.0 0.0

Douglas-fir live 0.72 0.47 0.0 0.0 0.22 0.38 0.0 0.04

Douglas-fir snag 0.01 0.0a 0.12 0.0 0.53 1.63 0.94 1.92

Grand fir & otherb

live 0.08 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Grand fir & otherb

snag 0.0a 0.0a 0.10 0.05 0.15 0.25 0.0 0.93

Alder live 1.98 0.36 0.55 0.0 0.19 1.14 0.64 1.56

Alderc snag 0.0a 0.0a 0.0 0.06 0.30 0.45 0.14 1.30 a Snag inputs are underestimated in 1996 and 1998, particularly in the South Fork. b Includes western hemlock and “fir”—pieces that might be either grand fir or Douglas-fir. c Includes a small amount of tanoak.

Piece survival 

Almost all of the volume of large wood input to the North Fork channel during 

the 1995 windstorms that was present in 1998 was still in the channel in 2010. Table 

2 shows the percent of the 1998 volume that was still in the channel at the time of 

each survey, with survival noted first by species and next by whether it came from a 

standing snag or from a live or recently-live tree. Pieces from snags are slightly less 

stable than those from live trees, but still quite persistent. In the South Fork, most 

alder volume was gone by 2010, but some pieces were still there. Conifer pieces were 

generally stable in that channel also, but the small number of trees makes it difficult 

to determine if they were more or less stable than those in the North Fork. 
Large Woody Debris Budgets in the Caspar Creek Experimental Watersheds

65

Table 2—Persistence of 1995 large wood inputs over time. Values are percent of the 1998 

volume of pieces input in 1995 remaining at the listed time. Numbers in parentheses are the 

number of source trees in each category. Very small categories have been omitted. North 

Fork inputs are grouped by species and by whether the tree was a snag; all 1995 trees in the 

South Fork were identified as “live” or “probably live.” Volume increases are caused by 

pieces moving further into the defined measurement area.

North Fork Percent of 1998 volume remaining

Species 1999 2002 2004 2006 2008 2010

Redwood (15) 95 96 96 108 105 103

Douglas-fir (74) 100 100 97 94 94 92

Grand fir (17) 98 96 96 96 96 97

Status of source tree

Live/probably live (76) 99 98 96 96 96 96

Snag /unknown (33) 100 103 96 90 91 80

South Fork 

Species 2000 2002 2004 2006 2008 2010

Redwood (3) 100 100 100 69 79 86

Douglas-fir (2) 100 100 100 100 95 95

Alder (4) 100 100 63 59 47 33

Part of the reason pieces are so persistent in these reaches is the length of the 

reaches—very few pieces move entirely out of the reach. I evaluated mobility within 

the reaches by comparing pieces that moved more than 5 m downstream between 

2004 and 2006 in the two reaches. The winter of 2005 and 2006 included the highest 

flow during the study. Just under 10 percent of the pieces moved in each channel (16 

of 205 pieces in the South Fork, 73 of 759 in the North Fork), but moved pieces were 

larger in the South Fork, with a mean moved piece volume of 0.53 m3 , compared to 

0.32 m3

 in the North Fork. South Fork pieces also moved, on the average, about 20 m 

further. The percent of total volume moved was also slightly higher, 4.2 percent 

versus 3.8 percent in the North Fork. South Fork pieces appear to be more mobile in 

a given flow year, but it would be useful to compare movement in other high-flow 

years.

Wood budgets 

Wood budgets for all intervals between surveys are summarized in table 3a for 

the North Fork and table 3b for the South Fork. A significant amount of wood 

entering the active channel in some years was previously-down pieces or standing 

stumps that had been outside of the active channel and entered the measurement area 

due to channel migration, or that had been buried in the bed or banks and became 

unburied, or that entered from adjacent hillsides or terraces by being knocked in by 

other trees, by sliding downslope, or by landslides (standing trees that entered from 

landslides are listed as “trees” in the budgets). These pieces are listed as inputs from 

“Off-channel.” Pieces that left the channel in equivalent ways (by burial, changes in 

channel location, or transport onto inactive floodplains) are listed as “Off-channel” 

losses. Budgets start with the tagged volume present at the beginning of the period. 

Volume losses, in addition to “Off-channel,” include pieces that were never found 

(Gone), or broke and became too small (Too small), or were transported downstream 
GENERAL TECHNICAL REPORT PSW-GTR-238 

66

beyond the end of the reach, usually into the weir ponds (Downstream). Volumes 

added include new logs from standing trees, additions from “Off-channel,” 

unidentified transported pieces, and pieces that moved in from upstream. 

Volumes of moved and broken pieces are subtracted from volumes after 

remeasurement to calculate a net change, which can be positive if pieces moved 

closer to the channel and thus had more volume within the measurement area. Trail 

work can also have a positive or negative net effect. Total changes are added to the 

original volume to calculate the volume at the start of the next interval. Budgets for 

1998 to 1999 (or 2000 in the South Fork) and 1999 to 2002 have an additional 

category for untagged pieces >0.2 m diameter and >2 m long that broke or 

disappeared during those periods. These estimated volumes are, as described earlier, 

not very accurate. Since these numbers make up most of the calculated total losses in 

the years to which they apply, losses in those years could range from half to twice the 

listed value. 

Table 3—Wood budgets for the North and South Forks of Caspar Creek, 1998-2008. See text 

for explanation of budget categories. Units are m3

/km over the period listed. Estimated 

numbers are categorized as “untagged.” 

3a. North Fork

1998 to 1999 1999 to 2002 2002 to 2004 2004 to 2006 2006 to 2008

Tagged volume 311.99 314.53 332.98 349.00 357.26

(untagged) 10.4 3.8

Start volume 322.4 318.4 333.0 349.0 357.3

Losses:

Gone -0.42 -1.15 -2.70 -15.64 -5.08

Too small -0.00 -0.00 -1.36 -1.41 -0.47

Off-channel -0.70 -0.33 -1.44 -4.72 -1.74

Downstream -1.68 0.00 0.00 -0.06 -0.12

(untagged ) -6.59 -3.84 0.00 0.00 0.00

Total losses -9.4 -5.3 -5.5 -21.8 -7.4

Moved/broken -19.54 -17.72 -24.77 -57.51 -50.52

Inputs from:

Trees 4.76 12.45 20.45 14.48 11.97

Off-channel 1.40 3.58 5.01 18.13 1.81

Unknown 2.11 2.37 1.82 6.96 0.80

Upstream 0.00 0.11 0.39 0.17 0.00

Total input 8.3 18.5 27.7 39.7 14.6

Moved pieces 16.89 21.16 18.63 47.80 46.73

Net moved -2.6 3.4 -6.1 -9.7 -3.8

Net trail work -0.3 -2.0 0.0 0.1 -1.5

Unchanged 289.37 291.55 301.70 267.31 296.70
Large Woody Debris Budgets in the Caspar Creek Experimental Watersheds

67

3b. South Fork

1998 to 2000 2000 to 2002 2002 to 2004 2004 to 2006 2006 to 2008

Tagged volume 104.62 106.31 105.52 104.16 112.07

(untagged) 3.9

Start volume 108.5 106.3 105.5 104.2 112.1

Losses:

Gone -0.29 -0.97 -3.96 -4.41 -1.70

Too small -0.00 -0.00 -1.00 -0.00 -0.92

Off-channel -0.09 -0.00 -1.44 -0.00 -0.00

Transport out -0.00 -0.00 -0.67 -1.86 -0.00

(untagged ) -3.9

Total losses -4.3 -1.0 -7.1 -6.3 -2.6

Moved/broken -3.49 -5.60 -7.48 -13.63 -16.98

Inputs from:

Trees 1.54 0.25 3.84 9.51 4.02

Off-channel 0.00 0.06 2.38 3.60 0.75

Unknown 0.67 0.27 0.65 1.88 0.87

Upstream 0.00 0.00 0.00 0.07 0.00

Total input 2.2 0.6 6.9 15.1 5.6

Moved pieces 3.35 5.21 6.40 12.74 14.10

Net moved -0.1 -0.4 -1.1 -0.9 -2.9

Unchanged 100.75 99.73 90.88 84.27 92.47

Most wood in both channels was unchanged in any period, and the largest 

amount of change was accounted for by pieces that moved within the reaches, which 

generally did not result in much net volume change. Both reaches showed a net 

accumulation over the period, but net accumulation in the South Fork was much 

lower than in the North Fork and almost entirely a result of high inputs in 2006; it 

may not represent a long-term pattern. The North Fork accumulated volume in every 

interval, with a net accumulation rate over the budget period of 3.3 m3

/km/yr. South 

Fork inputs, outputs, and changes are consistently lower than those in the North Fork. 

Surfleet and Ziemer (1996) noted a strong contrast in volumes between the North and 

South Forks in 1994 (before the 1995 windthrow). They attributed this difference to 

stream clearing in the South Fork between 1967 and 1973. Data from this study 

indicates that the contrast has continued and increased, mainly due to differences in 

input rates to the two channels, exacerbated by differences in piece persistence 

(mainly due to species composition) and possibly by higher relative mobility in the 

South Fork. 

Inputs from “off-channel” were highest in both forks in 2006, following the 

highest peakflow during the study. In the North Fork, these inputs were higher in 

2006 than inputs from standing trees, and much of that volume was large pieces of 

old-growth redwood. Many pieces moving back and forth from “off-channel” are old 

redwood chunks, which persist in the channel for many years. 

Conclusions

Wood inputs, outputs, moved volumes and total volumes are consistently lower 

on the South Fork than the North Fork, in some cases much lower. There are many 

factors that contribute to this difference, including differences in stand age and 

species composition, post-logging channel clearing in the South Fork, and post-
GENERAL TECHNICAL REPORT PSW-GTR-238 

68

logging blowdown in the North Fork. Current input rates in the South Fork are 

approaching those in the North Fork, but much of that input (26 to 48 percent since 

2004) is alder, which does not tend to persist in the channel. Wood is continuing to 

accumulate in the North Fork, partly because more than 90 percent of the volume 

from the 1995 blowdown events is still in the channel. 

Acknowledgments

Jen Feola, Dustin Idler, Elias Stienbuck, Gina Spratt, Sven Rosengreen, Dina 

Ederer, Alejandro Ramirez, Shauna Little, Megan Arnold, Forrest Phifer, Basilia 

Lopez, Ziza Bibic, and Alana Bartoli tagged and searched for and measured logs 

through the years, and many other people in Ft. Bragg and Arcata entered data, 

answered questions, and helped in many ways. Liz Keppeler provided her usual good 

advice and support, and Leslie Reid and Tom Lisle provided inspiration and insight. 

The study was partially funded by the California Department of Forestry and Fire 

protection. 

References

Henry, N. 1998. Overview of the Caspar Creek watershed study. In: Ziemer, R.R., 

technical coordinator. Proceedings of the conference on coastal watersheds: the Caspar 

Creek story. Gen. Tech. Rep. PSW-GTR-168. Albany, CA: U.S. Department of 

Agriculture, Forest Service, Pacific Southwest Research Station: 1-9.

O'Connor, M.D.; Ziemer, R.R. 1989. Coarse woody debris ecology in a second-growth 

Sequoia sempervirens forest stream. In: Abell, D.L., technical coordinator. 

Proceedings of the California riparian systems conference: protection, management, and 

restoration for the 1990s. Gen. Tech. Rep. PSW-110. Berkeley, CA: U.S. Department of 

Agriculture, Forest Service, Pacific Southwest Forest and Range Experiment Station: 

165-171.

Reid, L.M.; Hilton, S. 1998. Buffering the buffer. In: Ziemer, R.R., technical coordinator. 

Proceedings of the conference on coastal watersheds: the Caspar Creek story. Gen. Tech. 

Rep. PSW GTR-168. Albany, CA: U.S. Department of Agriculture, Forest Service,

Pacific Southwest Research Station: 71-80. 

Surfleet, C.G.; Ziemer, R.R. 1996. Effects of forest harvesting on large organic debris in 

coastal streams. In: LeBlanc, J., editor. Conference on coast redwood forest ecology 

and management. Berkeley, CA: University of California: 134-136.

Wohl, E.; Cederelli, D.A; Dwire, K.A.; Ryan-Burkett, S.; Young, M.K.; Fausch, K.D. 2010. 

Large in-stream wood studies: a call for common metrics. Earth Surface Processes 

and Landforms 35: 618-625.
69 

Sediment Production in a Coastal

Watershed: Legacy, Land Use, Recovery, 

and Rehabilitation1 

Elizabeth T. Keppeler2

Abstract

Sediment production has been measured for nearly half a century at the Caspar Creek 

Experimental Watersheds. Examination of this sediment record provides insights into the 

relative magnitudes and durations of sediment production from management practices

including road construction, selection harvest and tractor skidding, and later roaddecommissioning. The 424-ha South Fork was harvested under standards that applied before 

passage of the 1973 Forest Practice Act. Regression analysis of annual suspended sediment 

loads on peak flows indicates that sediment production roughly doubled, with a return to pretreatment levels about 11 years after harvest ended. However, sediment production again 

increased in the 1990s as road crossings deteriorated in response to large storms. Road 

crossings decommissioned in 1998 eroded a volume equivalent to more than half of the total 

yield in 1999 and enlarged another 20 percent over the last decade. Suspended sediment 

yields since decommissioning were reduced only for small storms. Recent assessment of 

1970’s era roads and skid trails found 443 remaining stream and swale crossings. Stream 

crossing have eroded an average volume of 10 m3

. Stream diversions are common, and many 

sites have the potential for future diversion. Diversions along incised roads and skid trails 

contribute to episodic sediment inputs. Mainstem sediment loads are elevated relative to those 

at tributary gages located above the decommissioned riparian haul road, indicating that 

sediment yields at the weir are enhanced along the mainstem itself. Since turbidity monitoring 

began in 1996, South Fork mainstem turbidities have exceeded ecosystem thresholds of 

concern a higher percentage of time than those in the North Fork.

Key words: erosion, legacy, logging, sediment, roads, road decommissioning 

Introduction and site description

Two centuries of logging in the redwood forests of northern California have 

transformed the region. Although the redwoods remain the defining natural 

characteristic of this “other California”, the landscape has been altered in a myriad of 

ways, some obvious and some subtle. Management activities such as timber harvest, 

road construction and use, and site preparation have been shown to deliver sediment, 

nutrients, and other pollutants to streams. Temporal and spatial variability of 

management impacts continues to be a topic of major concern—one that long-term 

research is particularly suited to address (Anderson and Lockaby 2011). The Caspar 

Creek Experimental Watersheds are a source of such data for the region.

 

1 This paper was presented at the redwood science symposium: coast redwood forests in a changing 

California. 21-23 June 2011, Santa Cruz, California. 2 Hydrologist, U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station, 802 

N. Main St., Fort Bragg, CA 95521. (ekeppeler@fs.fed.us).
GENERAL TECHNICAL REPORT PSW-GTR-238 

70

The Caspar Creek research watersheds are within the Jackson Demonstration 

State Forest, 5 km from the Mendocino coast. Streamflow and sediment data are 

collected from weirs constructed in 1962 on the 424 ha South Fork and 473 ha North 

Fork and from tributary gages installed between 1983 and 2001 (fig. 1). Over a 20-

year period of rapidly evolving management practices, the 100-year-old 2nd-growth 

redwood and Douglas-fir forest of this coastal basin was selectively tractor-logged 

(South Fork, 1971 to 1973) and partially cable clear-cut (North Fork, 1985 to 1992). 

New roads were constructed in both watersheds in conjunction with timber harvest. A 

4.7 km mainline riparian road was built in South Fork 4 years prior to harvest and

decommissioned in 1998, 25 years post-harvest. These varied treatments influence 

hydrologic processes, recovery time-frames, and restoration responses.

 

Figure 1—South Fork Caspar Creek watershed. 

Several reports document enhanced sediment production in response to South 

Fork road construction, logging, and tractor-yarding (Lewis 1998, Rice et al. 1979, 

Tilley and Rice 1977). These prior reports rely on North Fork comparisons for 

estimates of South Fork sediment increases. Lewis (1998) found suspended sediment 

in the South Fork increased 335 percent the year after road construction, while yields 

for the next 3 years did not increase significantly. For the 6 years following logging, 

suspended sediment yields increased an average of 212 percent over expected values, 

or 331 percent when North Fork yields were adjusted to remove the effect of a large 

1974 North Fork landslide. Suspended sediment yields recovered to background 

levels by 1979 and remained at background levels until 1985, when logging in the 

North Fork began. This report re-examines South Fork (SFC) suspended sediment 

trends through 2010 using analyses independent of North Fork (NFC) data and 

addresses the analytical problems presented by changing sampling protocols and 

episodic perturbations resulting from large landslides. Results are reviewed in light of 

erosion trends documented during 4 decades of field studies.
Sediment Production in a Coastal Watershed: Legacy, Land Use, Recovery, and Rehabilitation 

71

Methods

Sediment production estimates in the two watersheds are derived from water 

samples collected at the weirs (suspended loads) and annual bathymetric surveys of 

weir pond deposition. Pond deposition consists of approximately 40 percent 

suspended sediments and 60 percent bedload (Lewis 1998). Suspended sediment 

sampling protocols evolved over time. Initially, rising-limb data from fixed-stage 

siphon samplers were supplemented with manual DH-48 sampling during receding 

flows. Pumping samplers have been the primary means of suspended sediment 

sampling since 1976. Sediment concentrations, derived using standard gravimetric 

methods, were used to estimate loads using flow-duration sediment rating curves. 

Instream turbidimeters, deployed in 1996, are currently used in conjunction with 

pumped and DH-75 water samples to refine load estimates according to Turbidity 

Threshold Sampling protocols (Lewis and Eads 2009). Storm events are defined as 

the hydrograph rise to, and the ensuing recession from, a peak discharge exceeding 

1.6 L/s per ha (0.17 yr recurrence interval). 

Annual loads include an estimate of sediment flux between storm events and

have been multiplied by a factor of 0.45 for years 1963 to 1975 to remove bias 

introduced by fixed-stage samplers. Lewis (1998) demonstrated the bias introduced 

by disproportionate sampling of rising hydrographs and the strong correlation 

between annual suspended loads and annual runoff. Using NFC calibration data, 

Lewis (personal communication, 2007) regressed annual loads on annual peaks and 

compared deviations to conclude that estimates prior to the 1976 change in sampling 

protocol are consistently higher than those of the subsequent period by a factor of 

2.22 and proposed this same correction for both NFC and SFC annual loads. 

To allow SFC sediment loads to be analyzed after 1985, when logging began in 

the North Fork control watershed, the present study employs a calibration relation 

between SFC annual suspended sediment loads and SFC annual maximum 

peakflows, using 1963 to 1967 and 1984 to 1992 data. The calibration relation is used 

to estimate expected annual loads under pretreatment (and post-recovery) conditions, 

and observed loads can then be compared with expected loads to calculate deviations 

associated with road construction, harvest, and later road decommissioning. A similar 

approach was taken using storm-based loads and peaks for the 1986 to 2009 data set 

to explore changes associated with road decommissioning.

The potential implications of altered sediment loads are evaluated using the 15 

years of 10-min-interval turbidity now available for NFC and SFC. The number of 

days per year with turbidities exceeding the stream ecosystem stress thresholds 

proposed for Northern California watersheds (Klein and others 2008) were compared 

between sites using a paired t-test.

Erosion features larger than 7.6 m3

 were mapped in 1994, and subsequently after 

peak flows exceeding the 4 year return period (1997, 1998, and 1999). Beginning in 

2000, this inventory was repeated on an annual basis. Slide dimensions and volumes 

were recorded. 

Between 2004 and 2006, an inventory of legacy sediment sources was performed 

in the South Fork watershed based on protocols used for the Sinkyone Wilderness 

State Park Road Rehabilitation Project (Merrill 2003). Untreated roads and skid trails 

were evaluated in the field, using 2-m LiDAR and 1975 air photo imagery to help 
GENERAL TECHNICAL REPORT PSW-GTR-238 

72

locate the features. Stream and swale crossings, roads, landings, gullies, stream 

diversions (existing and potential), and landslide locations were mapped. In addition, 

the field crew attempted to remeasure voids from historic slides. At stream and swale 

crossings, erosion voids were measured to an accuracy of 20 percent, and erosion 

potential, the amount expected to erode over the next 3 decades, was estimated based 

on drainage area, vegetation, and bank condition. 

Erosion measurements along the haul road decommissioned in 1998 (Keppeler 

and others 2007) were repeated in 2011. The field crew evaluated 35 treatment sites 

for “sediment delivery potential” and gully “activity level” (Merrill 2003). At 10 

sites, thalweg profiles and three to five cross-section transects were surveyed using 

control points established in 1999 to estimate erosion in the intervening period. 

Results

Regression results confirmed the strong correlation between annual suspended 

sediment load and peakflow (r

2 = 0.90), allowing prediction of SFC loads 

independently of NFC measurements. SFC suspended sediment loads averaged 44 

t/km2 per year during the 1962 to 1967 calibration period while NFC averaged 56 

t/km2 per year (68 ± 40 (0.95 CI) for 22 pre-treatment years). This revised analysis, 

correcting for sampler bias, resulted in an estimate of excess suspended sediment 

produced post-logging of 928 t/km2

 (116 t/km2 per year) through 1979 (fig. 2). 

A. Deviation

Deviation from expected

suspended sediment

yield (tkm-2yr-1)

0

100

200

300

400

B. Cumulative deviation

1960 1970 1980 1990 2000 2010

Cumulative deviation in

suspended sediment

yield (tkm-2yr-1)

0

500

1000

1500

2000

Annual maximum

peakflow (Ls-1ha-1)

0

20

40

60

pre-treatment

roaded

logged

post-decom

Figure 2—Excess suspended sediment production by year for (A) annual and (B) 

cumulative deviation from predicted load.

Beginning about 10 years after timber harvest, sediment production returned to 

pre-harvest levels, and this pattern persisted for another decade. Elevated sediment 

production was renewed in 1993 and was most evident during years with peak flows 

larger than the 4 year return interval flow (about 12 L/s per ha). Keppeler and Lewis

(2007) detected SFC storm load increases of about 40 percent during 1998 to 2003, 

suggesting an episode of elevated sedimentation spanning the decommissioning 

treatment. Regression analyses of SFC storm loads on storm peaks for 1986 to 1998 

and 2000 to 2009 show no significant difference (p < 0.05) after decommissioning 

for peaks larger than the 0.4 yr recurrence interval, but for smaller peaks, loads were 

significantly reduced (fig. 3). 
Sediment Production in a Coastal Watershed: Legacy, Land Use, Recovery, and Rehabilitation 

73

Storm peakflow (Ls-1ha-1)

1 2 3 5 10 20 30

Storm suspended load (kg/ha)

1

10

100

1000

before 4/1998

after 12/1999

Figure 3—Sediment loads as a function of storm peak before and after 

decommissioning, divided into two peak discharge classes at the 0.4 yr return period.

Since implementation of continuous turbidity monitoring in 1996, SFC turbidities 

have exceeded ecosystem thresholds of concern more commonly than NFC 

turbidities. When turbidity records were tallied by stream ecosystem stress thresholds 

exceeding 25 (moderate), 50 (severe), 100 ntu (extreme) (Klein and others 2008) for 

each hydrologic year, SFC averages exceeded NFC’s by 50, 60, and 120 percent (p < 

0.014), respectively—a fairly consistent pattern even during years when NFC logging 

effects were evident. This result may reflect high inputs of fine sediments from road 

surfaces and bare ground in the South Fork, or may indicate that the physical 

properties of the sediment transported through the two weir ponds differ. The 

difference in ratios of average storm load above and below the two weirs supports the 

latter hypothesis. The weirs trap an estimated 20 to 30 percent of suspended sediment 

and virtually all bedload, thus the rationale for siting sampling stations ARF and 

QUE immediately upstream of the NFC and SFC weir ponds. Based on storm load 

data from 2001 to 2009, NFC transported just 70 percent of the load entering the 

pond, while SFC transported 80 percent. 

Information from field-based sediment source assessments provides a context for 

interpreting the patterns of suspended sediment yield (table 1). The inventory of the 

entire South Fork watershed performed between 2004 and 2006 documented 443 

remaining stream and swale crossings on untreated roads and skid trails. Of these, 

325 had experienced partial failure. Swale crossings numbered 208, including 102 

that had remained stable in the 3 decades since construction and only four that had 

eroded more than 10 m3

. In contrast, only 16 of 235 stream crossing had experienced 

no notable erosion. Eroded volume per stream crossing averaged 10 m3

, but most of 

this erosion did not appear to be recent. Fill material at risk of further erosion 

accounted for 16 percent of the estimated initial crossing fill. Stream crossings 

accounted for 82 percent of the “at risk” projection of erosion potential. Diversions 

onto roads and skid trails were common. Roughly 10 percent of stream crossings 

were active diversions while a similar number were “at risk” because a minor 

blockage could redirect flow onto the road surface. More than 300 m of entrenched 

diversions and active gullies were noted. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

74

Table 1—Field-based sediment source measurements (in-channel erosion from Reid and 

others 2010). 

Type Years m3 m3/yr Method

Logging period

landslides (re-assessed) 1971-76 7944 1324 inventory 2004-2006

Recovery period

untreated crossing erosion 1971-06 2827 79 inventory 2004-2006

gully erosion 1971-06 932 26 inventory 2004-2006

mass-wasting > 7.6 m3 1977-94 1705 95 inventory 1994

mass-wasting > 7.6 m3 1977-06 2897 97 inventory 2004-2006

mass-wasting > 7.6 m3 1995-99 4008 802 inventory, irregular

Post-decommission period

mass-wasting > 7.6 m3 2001-10 553 55 annual inventory

treated crossing erosion 1999 651 651 survey, 1999

treated crossing erosion 2000-01 108 54 survey, 2001-2002

treated crossing erosion 2002-11 150 15 survey, 2011

in-channel erosion 2001-08 na 291 survey, irregular

Landslide voids encountered during the recent inventory included 7944 m3

 (18.7 

m3

/ha) from slides listed in the 1976 data set and 2897 m3 (6.8 m3/ha) in more recent 

features. However, half the slides in the 1976 data set were not relocated.

Soil displacement by mass-wasting for events larger than 7.6 m3 declined since 

the 1970s and again in the most recent decade relative to the 1990s. Through 1994, 

the rate was 95 m3

/yr; from 1995 to 1999, 802 m3/yr; and since 2000, 55 m3/yr. 

Seven of 10 slides in the 1994 inventory were along haul roads and landings, but 

these accounted for less than 20 percent of the total volume. Only two failures along 

the mainline road were attributed to 1993. Between 1993 and 1999, 17 slides 

accounting for 70 percent of the mass-wasting volume occurred along the mainline

road—15 resulted from culvert or fill failures. In the post-decommissioning data set, 

the largest feature was a 255 m3

 slide that originated along an untreated mid-slope 

road routing entrenched flow from a stream diversion to the fill slope. The slide 

traveled down the tributary channel as a debris torrent, depositing debris in the 1998 

restored stream crossing void and continuing on to the South Fork mainstem. 

Keppeler et al. (2007) report that the 1998 road decommissioning, followed by 

the largest peakflow of the 49 year SFC record, profoundly impacted sediment 

production in 1999. Re-evaluation of 35 treated crossings in 2011 indicated that 

erosion is ongoing at 31. Sediment transport potential was rated “high” or “extreme” 

at 12 of 37 sites. The predominant “Activity Class” (Merrill 2003) for the gullied 

crossings was “3” (indicating “good vegetative cover” with less than 50 percent of 

the incised area subject to erosion and transport). However, five were characterized 

as “1” (exhibiting “widespread transport and little or no vegetation”) and five were 

rated as “4” (supporting “good vegetative cover” and having gentle side-slopes). 

The 2011 re-survey of channel cross-sections and profiles established at 10 sites 

in 1999 quantified additional scour and fill since 2001. Incision and widening were 

evident at 60 and 40 percent, respectively, of 42 cross-section transects, while 30 

percent of transects showed neither. Mean profile elevation decreased by 0.09 m. 
Sediment Production in a Coastal Watershed: Legacy, Land Use, Recovery, and Rehabilitation 

75

Headcut retreat was evident along all 10 surveyed profiles. In sum, these 10 sites 

enlarged by 80 m3

, or about 20 percent, since last assessed. Assuming a similar rate 

of erosion from the 25 sites that were not re-surveyed, total enlargement is estimated 

to have been about 150 m3 over the last decade. A foot trail along the former road 

surface receives semi-regular (unsanctioned) bicycle and motorcycle use. The road 

has not fully revegetated and delivers an unknown amount of sediment to the stream.

Discussion

To relate erosion measurements to recent trends in suspended sediment yields at 

the weirs, it is helpful to compare unit-area sediment loads measured immediately 

upstream of the weirs with those measured at upstream tributary gages to identify 

areas contributing disproportionate amounts of sediment. Since 2000, when nine 

tributary gages were installed in the South Fork watershed, NFC event-based storm 

loads averaged 104.3 kg/ha based on contributions from the two gages delivering 

directly to the weir pond. Upstream gages produced similar loads, averaging 99.3 

kg/ha. In contrast, South Fork event-based loads (the sum of mainstem loads 

measured 50 m upstream of the weir pond and the tributary gage load delivered 

directly to the weir pond) averaged 75.8 kg/ha. South Fork tributaries draining 52 

percent of the watershed area produced 54.1 kg/ha per event, on average. Assuming 

the few small ungaged tributaries are not generating disproportionately high amounts 

of sediment, the SFC load is enriched below tributary gages and along the mainstem. 

Three of the tributary gages are sited within 42 m upstream of stream crossings 

restored during the 1998 decommissioning of the mainline road, and paired water 

samples were collected above and below the crossings during water years 2004 and 

2006. These samples indicate suspended sediment concentrations were enriched 

below the decommissioned crossings (p < 0.012), reflecting the net contributions of 

erosion within the restored stream crossings and from the old road surface. 

During the last decade, the volume of fine sediments in pools declined along the 

lower 490 m of mainstem channel above the SFC weir. However, pool depths 

decreased as well. Mainstem cross-sections, measured biennially since 2000 along 

3100 m of channel, scoured 59 m3

 from 2000 to 20103. It is likely that sediment 

inputs from both recent and historic mass-wasting, including materials eroded from 

failed and decommissioned crossings, were re-mobilized during high flows and 

augmented suspended sediment loads generated in upland portions of the South Fork 

watershed. In-channel erosion processes were also active in South Fork tributaries 

and account for a substantial portion of the suspended load at SFC (Reid et al. 2010). 

Conclusions

Measured rates of suspended sediment yield in the South Fork Caspar Creek 

watershed were highest during the first decade after selection harvest and tractoryarding was completed in 1973. A second episode of increased suspended sediment 

yield, coinciding with a notable increase in road-related mass-wasting, commenced 

20 years post-harvest. Since decommissioning of the riparian road in 1998, reduced 

sediment yields have been detected only for small storms, though the incidence and 

 

3 S. Hilton, Hydrologist, U.S. Department of Agriculture, Forest Service, Pacific Southwest Research 

Station, 2011, personal communication.
GENERAL TECHNICAL REPORT PSW-GTR-238 

76

magnitude of mass-wasting was lower during the last decade than in the 1990s.

Mainstem channel measurements and tributary gage data suggest that sediment 

deposited prior to 2000 was mobilized and transported during the last decade. 

Erosion in upland areas, including diversion-induced mass-wasting, incision of 

crossings along untreated roads and skid trails, and in-channel gullying, remains 

active. Potential interactions with persisting legacy effects should be considered 

when modern forest management practices are superimposed on landscapes still 

responding to past disturbances. 

Acknowledgments

This study is part of the cooperative Caspar Creek research program instituted in

1960 by the U.S. Department of Agriculture, Forest Service Pacific Southwest 

Research Station and the California Department of Forestry and Fire Protection. 

Leslie Reid and Jack Lewis provided critical components of this analysis. 

References

Anderson C.J.; Lockaby, B.G. 2011. Research gaps related to forest management and 

stream sediment in the United States. Environmental Management 47: 303-313. 

Keppeler, E.T.; Cafferata, P.H.: Baxter, W.T. 2007. State forest road 600: a riparian road 

decommissioning case study in Jackson Demonstration State Forest. California 

Forestry Note No. 120. 22 p.

Keppeler, E.T.; Lewis, J. 2007. Understanding the hydrologic consequences of timberharvest and roading: four decades of streamflow and sediment results from the 

Caspar Creek Experimental Watersheds. In: Furniss, M.; McCammon, M., editors. 

Advancing the fundamental sciences--a conference for Forest Service physical scientists. 

U.S. Department of Agriculture, Forest Service: 191-196.

Klein, R.; Trush, W.; Buffleben, M. 2008. Watershed condition, turbidity, and 

implications for anadromous salmonids in north coastal California streams. Report 

to the California North Coast Regional Water Quality Board, Santa Rosa, California.

Lewis, J. 1998. Evaluating the impacts of logging on erosion and suspended sediment. In:

Ziemer, R.R., technical coordinator. Proceedings of the conference on coastal 

watersheds: the Caspar Creek story. 1998 May 6, Ukiah, CA. Gen. Tech. Rep. PSWGTR-168. Albany, CA: U.S. Department of Agriculture; Forest Service, Pacific 

Southwest Research Station: 55-70. 

Lewis, J.; Eads, R. 2009. Implementation guide for turbidity threshold sampling: 

principles, procedures, and analysis. Gen. Tech. Rep. PSW-GTR-212. Albany, CA: 

U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station. 87

p.

Merrill, B. 2003. Sinkyone Wilderness State Park road rehabilitation project 

architectural and engineering report. North Coast Redwoods District, California State 

Parks. Appendix B.

Reid, L.M.; Dewey, N.J.; Lisle, T.E.; Hilton, S. 2010. The incidence and role of gullies 

after logging in a coastal redwood forest. Geomorphology 117: 155-169.

Rice, R.M.; Tilley, F.B.; Datzman, P.A. 1979. A watershed's response to logging and 

roads: South Fork of Caspar Creek, California, 1967-1976. Res. Paper PSW-RP-146. 

Berkeley, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Forest 

and Range Experiment Station. 12 p. 
Sediment Production in a Coastal Watershed: Legacy, Land Use, Recovery, and Rehabilitation 

77

Tilley, F.B.; Rice, R.M. 1977. Caspar Creek watershed study—a current status report. 

California Forestry Note No. 66. Sacramento, CA: Department of Forestry.15 p.

79

Declining Sediment Loads from Redwood 

Creek and the Klamath River, North Coastal 

California

Randy D. Klein1 and Jeffrey K. Anderson2

Abstract

River basin sediment loads are affected by several factors, with flood magnitude and 

watershed erosional stability playing dominant and dynamic roles. Long-term average 

sediment loads for northern California river basins have been computed by several researchers 

by several methods. However, characterizing the dynamic nature of climate and watershed 

stability requires computation of annual loads. We computed annual suspended and bedload 

loads for the 1950s through 2009 for both Redwood Creek and the Klamath River. Results 

show high sediment loads coincident with a period of widespread logging by destructive 

practices and large storms in the 1950s through 1970s followed by a dramatic decline in 

sediment loads through the present. Analyses of annual departures from mean and time trend 

tests indicated the decline in loads is not due solely to the lack of very large storms. We infer 

it can also be explained by the partial recovery of watershed erosional stability from the 1980s 

through the present due to reduced logging rate, use of lower impact logging practices, and 

implementation of treatment programs for reducing erosional threats from logging roads.

Key words: bedload, suspended load, watershed recovery, Redwood Creek, Klamath River

Introduction

Sediment yield, or load, consists of the total mass of sediment particles 

transported by streamflow past a location along a stream or river over a given time 

period. Sediment is transported either suspended in the water column (suspended 

load) or along the channel bed (bedload). Quantification of sediment loads can be 

important for a variety of management needs, such as evaluating land use impacts, 

reservoir design, coastal sediment budgets, and others. In oceanographic studies, the 

long term total or average annual sediment yield may suffice for correlation with 

sediment accretion on the continental shelf (Farnsworth and Warrick 2007, Willis 

and Griggs 2003), but for assessing effects of changing watershed conditions, annual 

time series sediment load estimates are required. The objective of this analysis was to 

characterize fluctuations in sediment loads for the period of record for Redwood 

Creek and the Klamath River and to relate changes in annual loads to watershed 

conditions affecting loads. 

 

1 Hydrologist, Redwood National and State Parks, 1655 Heindon Road, Arcata, CA 95521. 707-825-

5111. (Randy_Klein@nps.gov).

2 Engineer, Northern Hydrology and Engineering. PO Box 2515, McKinleyville, CA 95519. 707-839-

2195. (jeff@northernhydrology.com).
GENERAL TECHNICAL REPORT PSW-GTR-238 

80

Study area

The Klamath River and Redwood Creek drain lands in northwestern California, 

with the Klamath basin extending into eastern Oregon (fig. 1). The Redwood Creek 

basin area of 717 km2 lies entirely within the Coast Range of California and is 

underlain by metamorphic and sedimentary rocks of the Franciscan assemblage 

(Nolan et al. 1995), relatively weak rocks subject to high erosion rates. Redwood 

Creek’s Mediterranean climate is dominated by rainstorms rather than snowmelt 

runoff, with most of the average annual rainfall depth of about 150 cm falling during 

winter months (November through March). Occasional intense rainfall events 

produce large stormflow peaks at the basin outlet near Orick, California. Harden 

(1995) reported peak discharges in the 1950s through 1970s ranging from about 1300 

to 1400 m3

s

-1, with recurrence intervals of approximately 25 years.

Figure 1—Location of the Redwood Creek and Klamath River watersheds, northern 

California and southern Oregon. Gaging stations near watershed outlets and location 

of Iron Gate Dam are also shown.

Due to its much larger size (40,720 km2), the Klamath River basin contains 

broader ranges of both climates and lithologies than Redwood Creek. Ayers 

Associates (1999) report that mean annual precipitation ranges from about 280 cm in 

the upper reaches of tributaries near the coast to as little as 25 cm in the upper 

watershed near Tule Lake. Large floods are caused by both intense rainfall and rain 

on snow (Ayers Associates 1999) with several large storms having occurred over the 

past 50+ years. In the simplest terms, the basin can be subdivided geomorphically 

into the upper basin (above the Shasta River) and the lower basin based on bedrock 

geology and potential sediment delivery to streams. Hillslopes of the upper basin 

have generally lower sediment delivery potential due to more competent terrane and 

lower relief than the lower basin. Not far upstream of Cottonwood Creek, Iron Gate 

Dam traps much of the sediment load generated from the upper watershed. The 

Trinity River, the largest Klamath River tributary, is notable for its historically high 

sediment delivery to the lower river due, in part, to the presence of highly weathered 

granitic rocks (US Bureau of Land Management 1995). Elsewhere in the lower basin 
Declining Sediment Loads from Redwood Creek and the Klamath River, North Coastal California

81

the Coast Range geology, similar to that of Redwood Creek, also creates high 

sediment delivery potential and sensitivity to land use disturbances. 

The Redwood Creek watershed has been studied extensively since the 1970s, 

owing in part to the creation of Redwood National Park in 1968 and expansion of the 

park in 1978 due to concerns over erosion and sediment delivery originating on 

adjacent private timberlands (Nolan and Janda 1995). Stream gaging stations were 

established at key locations within the basin where water discharge and, for much of 

the period of record, suspended sediment and bedload transport rates were measured. 

Large increases in sediment yields due to widespread clearcut logging and tractor 

yarding were documented (Nolan and Janda 1995). The Klamath River has also had 

stream gaging stations operated on it for some time, several of which included 

periodic suspended sediment sampling. Together, water discharge and sediment 

transport samples at known discharges provide the information for making sediment 

load computations.

Best (1995) documents the post-World War II acceleration of logging in 

Redwood Creek when few regulations were in place to moderate effects on erosion 

and sediment delivery. Ayers Associates (1999) indicate that acceleration of logging 

began in the Klamath’s lower basin at about the same time as in Redwood Creek.

With passage of the Z’berg-Nejedly Forest Practice Act of 1973 the size of individual 

harvest areas in California was reduced along with other rules to limit damage to 

hillslopes and streams. In Redwood Creek logging rates fell abruptly after park 

expansion in 1978 excluded the downstream one-third of the watershed from 

commercial timber harvest. 

The response to harsh land use and large floods in Northern California’s redwood 

country in the 1960s through the 1970s caused persistent changes to hillslopes and 

channels. Madej and Ozaki (2009) document the export of channel-stored bed 

sediment in Redwood Creek from the 1970s through the present, with channel 

recovery process proceeding in a downstream direction. Recovery rate toward preaggradation channel bed elevations was dramatically slower in the gentler-gradient 

downstream reaches. Payne and Associates (1989) documented tributary delta growth 

in the lower Klamath River, indicative of elevated sediment delivery from these subbasins reaching a maximum in the 1970s and persisting through the time of their 

analysis. Tributaries to the lower Klamath remain heavily aggraded, attesting to a 

high degree of prior land disturbance and persistent channel bed aggradation similar 

to that of Redwood Creek.

Methods

Annual sediment loads were computed for water years (WY) 1954 to 2009 for 

Redwood Creek at Orick (No. 11482500) and for WY1951 to 2009 for the Klamath 

River near Klamath (No. 11530500). The U.S. Geological Survey (USGS) has 

operated these stream gaging stations near the mouths of both rivers since the early 

1950s and collected sediment samples for a portion of that time. Redwood Creek 

sediment data included both suspended sediment and bedload samples, but the 

Klamath dataset included only suspended sediment. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

82

Suspended sediment 

Redwood Creek suspended sediment sampling occurred from 1971 to 2009 

during which 380 samples were collected. Klamath River suspended sediment 

sampling occurred from 1974 to 1995 with a total of 270 samples collected, of which 

158 were used for estimating suspended load. To compute annual suspended 

sediment loads, we used the USGS program “LOADEST” (Runkel et al. 2004), a 

rating curve approach based on a multi-parameter log-linear model that accounts for 

the effects of discharge, time and seasonality on suspended sediment concentration

(SSC). LOADEST contains a number of predefined log-linear models, and the best 

fit model based on the internally calculated Akaike Information Criterion is generally 

recommended. LOADEST automatically adjusts for log-space retransformation bias 

for determining average load estimates (Runkel et al. 2004). Review of log flowadjusted SSC (as described later) showed a nonlinear trend with time for both rivers 

indicating potential SSC rating curve shifts. To overcome the nonlinearity we 

employed multiple log-linear models at obvious shifts. 

Separate log-linear models were used on Redwood Creek for the periods of WY 

1954 to 1970, 1971 to 1977 and 1978 to2009, and on the Klamath River for WY 

1951 to 1964, 1965 to 1977 and 1978 to 2009. Load estimates for periods preceding 

data collection were based on a single-variable log-linear model of discharge using 

all available data. To improve the log-linear rating curves and better constrain 

Klamath River high flow load estimates for the pre-sampling (1951 to 1974) period, 

high flow data between 1957 and 1977 were used from two upstream stations 

composing 94 percent of the basin area draining to the lower Klamath: Klamath 

River at Orleans (No. 11523000) and Trinity River at Hoopa (No. 11530000). Mass 

balanced SSC values for the upstream stations and the corresponding mean daily 

flows for discharges greater than 1,800 m3

 s-1 for the Klamath River near Klamath 

were then used in the Klamath River log-linear rating curves for the two periods. For 

the Klamath River, the selected multi-variable log-linear model was used beyond the 

data sampling period for the 1996 to 2009 load estimates. All selected log-linear 

models showed good fits to the data with coefficient of determination (R2

) values 

ranging from 89 to 99 percent. 

Bedload 

Annual bedload loads were determined for Redwood Creek and Klamath River 

using a recently published bedload transport formula (Recking 2010), which uses 

discharge, active channel width, slope, and surface particle size (D50 and D84) as 

inputs. In general, loads were estimated by first developing log-linear rating curves 

using available streamflow measurement records, slope and surface particle sizes for 

each river with the Recking (2010) bedload formula. The rating curves were applied 

to the mean daily flow record and then summed by WY to produce annual bedload 

loads. We corrected for log-space bias by applying the correction factor exp (s2

/2) 

(Ferguson 1986) to estimated annual loads, where s is the standard error of a loglinear model of sampled bedload and discharge in Redwood Creek (correction factor 

= 1.29). 

For Redwood Creek most of the necessary data were available for most of the 

period of record, with the exception of bed surface particle sizes prior to 2010. The 

USGS sampled bedload (150 samples) in Redwood Creek from 1972 to 2009, which 

included bedload particle size fractions. To estimate surface D50 and D84, a 
Declining Sediment Loads from Redwood Creek and the Klamath River, North Coastal California

83

relationship was developed between measured surface and bedload particle sizes. 

Adequate bedload particle size measurements were available to estimate changes in 

median surface D50 and D84 by decade. Although the ratios may have changed over 

smaller time scales, we felt this was a reasonable method for conditioning bed 

surface grain sizes through time, as suggested by comparison with USGS measured 

daily bedload rates for Redwood Creek: 96 percent of the predicted rates were within 

one order of magnitude of USGS measurements for the overlapping period (1971 to 

1992). 

Recking’s (2010) model was also used to determine bedload annual loads for the 

Klamath River. Unfortunately, no data on bedload samples, channel bed material 

particle sizes or slope were available for the Klamath station, so field data were 

collected for this project in 2010. Particle sizes were determined by performing 

pebble counts (Wolman 1954) on a gravel bar near the gaging station and surveying 

the adjacent water surface slope. Lacking any prior data, we had to use the 2010 

pebble count and slope data to estimate bedload loads for the entire period of record. 

Time trends 

Temporal trends in suspended sediment for the Klamath River and Redwood 

Creek were evaluated by two methods: 1) comparison of departures from period 

means of annual suspended sediment loads and peak flows, and 2) trends in SSC 

using the nonparametric Seasonal Kendall test (Helsel and Hirsh 2002). This test 

adjusts for seasonal variability by combining individual Mann-Kendall trend tests to 

seasonally grouped SSC. To increase the power of the Seasonal Kendall test, SSC 

data were adjusted for streamflow effects (flow-adjusted SSC) using a LOWESS 

smooth curve between SSC and streamflow (Helsel and Hirsh 2002). The residuals 

from the LOWESS curve were then used in the Seasonal Kendall test. Based on 

recommendations in Schertz et al. (1991) and the frequency of available SSC data, 

the Seasonal Kendall test was conducted on six seasons for the Klamath River, and 

three seasons for Redwood Creek. Monotonic trends in SSC are considered 

significant at the alpha < 0.05 probability level (p).

Results

The history of sediment loads delivered to the Pacific Ocean by Redwood Creek 

and the Klamath River is characterized by large inter-annual and decadal variability 

(figs. 2A and 2B). Loads were highest during the largest storms of the 1950s through 

mid-1970s and have declined dramatically since. 

As expected, annual average total suspended sediment loads for the periods were 

vastly different between the two rivers given the differences in watershed area. At 

6,831,000 Mg yr-1, the much larger Klamath River produced about seven times more

suspended sediment over the long term (1950s to 2009) than Redwood Creek, which 

averaged 975,000 Mg yr-1. However, the situation reverses when considered on an 

area-weighted basis: Redwood Creek produced about seven times more suspended 

sediment per unit area than the Klamath River. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

84

Figure 2—Annual suspended and bedload sediment loads for Redwood Creek (A) 

and Klamath River (B), 1951 to 2009. Note the difference in scales for suspended 

loads. 

Unlike suspended loads, differences in bedload sediment loads were relatively 

small between the two rivers: 158,000 Mg yr-1 for Redwood Creek and 116,000 Mg 

yr-1 for the Klamath. Closure of Iron Gate Dam in 1961 on the Klamath River 

approximately 306 km upstream from the mouth (see fig. 1) reduced sediment fluxes 

from the upper one-third of the watershed. However, because area-weighted sediment 

delivery in the basin area upstream of the dam is much lower than that downstream 

(Ayers Associates 1999), reductions in basin yields to the Pacific Ocean would be 

less than the proportion of watershed area truncated by the dam. We note that 

bedload load estimates for the Klamath are based on a very limited data set for model 

inputs 

Figures 3A and 3B show departures in annual maximum instantaneous peak 

discharge and suspended load from their respective period means and trendlines for 

each. Large departures coincided with years of large sediment loads and floods. 

Declining trends since about 1975 characterize both variables for both rivers, but the 

trendline slopes of suspended load are steeper than those of peak discharge for both 

rivers, indicating loads have declined to a greater degree than peak flows. For 

Redwood Creek, the suspended sediment trendline is about three times steeper than 

that for peak discharge, and four times steeper for the Klamath River. For both rivers, 

the largest storms of recent decades (in WY1996 and WY1997 of roughly 10- and 

15-years recurrence intervals, respectively) produced far less sediment than would be 

expected with similar sized stormflows before 1975. 

Results from the Seasonal Kendall test (fig. 4) indicate that SSC significantly 

declined from 1975 to 1995 for the Klamath River (p < 0.0001), and from 1971 to 

2009 for Redwood Creek (p < 0.0001). Trend results indicate a 5.9 mg L-1 yr-1 (0.7 

percent yr-1) decrease in SSC for the Klamath River, and a 3.5 mg L-1 yr-1 (4.4 

percent yr-1) decrease in SSC for Redwood Creek. 

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

1951 1956 1961 1966 1971 1976 1981 1986 1991 1996 2001 2006

Water Year

Suspended Load (Mg )

0

100,000

200,000

300,000

400,000

500,000

Bedload (Mg)

Suspended Load

Bedload

Annual average SSL = 975,000 Mg yr-1

Annual average BL = 158,000 Mg yr-1

A

0

10,000,000

20,000,000

30,000,000

40,000,000

50,000,000

1951 1956 1961 1966 1971 1976 1981 1986 1991 1996 2001 2006

Water Year

Suspended Load (Mg )

0

100,000

200,000

300,000

400,000

500,000

Bedload (Mg)

Suspended Load

Bedload

Annual average SSL = 6,831,000 Mg yr-1

Annual average BL = 116,000 Mg yr-1

B
Declining Sediment Loads from Redwood Creek and the Klamath River, North Coastal California

85

peak discharge trendline slope = -0.0116

suspended trendline load slope = -0.0331

-200%

-100%

0%

100%

200%

300%

400%

500%

1951 1956 1961 1966 1971 1976 1981 1986 1991 1996 2001 2006

Water Year

Departure from Normal (%)

Peak Discharge

Suspended Load

A

peak discharge slope = -0.0067

suspended load slope = -0.0288

-200%

-100%

0%

100%

200%

300%

400%

500%

1951 1956 1961 1966 1971 1976 1981 1986 1991 1996 2001 2006

Water Year

Departure from Normal (%)

Peak Discharge

Suspended Load

B

Figure 3—Suspended sediment load and annual peak discharge departures from 

normal for Redwood Creek (A) and Klamath River (B). Dashed line is trendline for 

suspended sediment load, solid line is trendline for peak discharge.

Figure 4—Suspended sediment concentration (SSC) residuals with flow effects 

removed and Seasonal Kendall test results.

Accompanying the reduction in loads, the proportion of bedload to suspended 

load has shifted in Redwood Creek and the Klamath River. Prior to 1976, the ratio of 

bedload to suspended load for Redwood Creek was 0.12, rising to over twice that 

(0.26) for the later period. The proportion of bedload to suspended load was much 

smaller for the Klamath River: the pre-1976 proportion was 0.012 and rose to 0.029 

for the 1976 to 2009 period, although this should be viewed with caution considering 

that historical Klamath bedload loads were computed using model inputs collected 

only in 2010. This results in lower confidence in computed bedload loads with 

increasing time before present, although we believe this method to be superior to 

bedload computed as an assumed percentage of suspended or total load as others 

have done (e.g., Willis and Griggs 2003).
GENERAL TECHNICAL REPORT PSW-GTR-238 

86

Discussion

Computing historic annual sediment loads necessitated the use of several 

methods and assumptions, however, use of a single sediment rating curve spanning 

decades, as done by other researchers (e.g., Farnsworth and Warrick 2007, 

Wheatcroft and Sommerfield 2005), cannot account for shifting relationships 

between water discharge and sediment transport that occur due to changing 

watershed conditions. Both the departures from normal analysis and the Seasonal 

Kendall trend tests indicated sediment loads are declining independent of lower peak 

flows. These declines highlight the importance of assessing temporal trends in 

sediment loads as opposed to average annual or period total loads. As watersheds 

become erosionally destabilized, sediment loads rise relative to flows, and as 

recovery to more stable conditions proceeds, loads decline relative to flows. 

Accordingly, sediment rating curves can be expected to shift upward or downward 

through time with the watershed disturbance regime. 

Although no definitive causal link has been established, reduction in sediment 

loads since the mid-1970s probably can be attributed to natural watershed recovery 

processes, strengthened land use regulations, and watershed restoration programs. 

Watershed recovery processes such as vegetation re-growth and export of channel 

stored sediment as bedload have occurred throughout our study area even with 

ongoing timber harvest. Timber harvesting regulations that went into effect around 

1980 in California, and have been continually refined since, reduced the allowable 

size of harvest units, elevated road construction standards, and extended riparian 

buffer requirements, all of which tend to reduce erosion and sediment delivery 

relative to earlier, more destructive practices.

In accordance Redwood National Park expansion legislation in 1978, a 

restoration program was initiated on Redwood Creek parklands focusing on the 700 

km of logging roads that existed in 1978. To date, about 480 km (69 percent) of 

logging roads have been decommissioned (obliterated) such that their potential to 

deliver sediment has been greatly reduced. Road decommissioning has also occurred 

elsewhere in Redwood Creek on private timberlands, along with upgrading of 

logging roads to reduce their likelihood of sediment delivery. This type of work is 

also occurring in the lower Klamath River basin, but to a lesser degree than in 

Redwood Creek. 

It remains to be seen how Redwood Creek and the Klamath River will respond to 

the inevitable recurrence of very large floods of magnitudes similar to those of 1950s 

through 1970s. However, our analyses suggest that the changing watershed 

conditions described above have provided the basins with a higher degree of 

resilience than that which led to the highly destructive erosion and sediment delivery 

events of the 1950s to 1970s. 

References 

Ayers Associates. 1999. Geomorphic and sediment evaluation of the Klamath River 

below Iron Gate Dam. Report prepared for U.S. Fish and Wildlife Service. Yreka, CA:

Klamath River Fish and Wildlife Office. 360 p.

Best, D.W. 1995. History of timber harvest in the Redwood Creek basin, northwestern 

California. In: Nolan, K.M.; Kelsey, H.M.; Marron, D.C., editors. Geomorphic 
Declining Sediment Loads from Redwood Creek and the Klamath River, North Coastal California

87

processes and aquatic habitat in the Redwood Creek Basin, northwestern California. 

USGS Professional Paper 1454. Washington, DC: U.S. Geological Survey: C1-C7.

Farnsworth, K.L.; Warrick, J.A. 2007. Sources, dispersal, and fate of fine sediment 

supplied to coastal California. U.S. Geol. Survey Scientific Investigations Report 

2007-5254. 51 p.

Ferguson, R.I. 1986. River loads underestimated by rating curves. Water Resources 

Research 22: 74-76.

Harden, D.R. 1995. A comparison of flood-producing storms and their impacts in 

northwestern California. In: Nolan, K.M.; Kelsey, H.M.; Marron, D.C., editors. 

Geomorphic processes and aquatic habitat in the Redwood Creek Basin, northwestern 

California. USGS Professional Paper 1454. Washington, DC: U.S. Geological Survey: 

D1-D9.

Helsel, D. R.; Hirsch, R. M. 2002. Statistical methods in water resources, U.S. Geological 

Survey techniques of water-resources investigations, Book 4, Hydrologic analysis 

and interpretation. Chap. A3; 524 p. 

Madej, M.A.; Ozaki, V. 2009. Persistence of effects of high sediment loading in a salmonbearing river, northern California. Geological Society of America Special Paper 451: 

43-55.

Nolan, K.M.; Janda, R.J. 1995. Impacts of logging on stream-sediment discharge in the 

Redwood Creek basin, northwestern California. In: Nolan, K.M.; Kelsey, H.M.; 

Marron, D.C., editors. Geomorphic processes and aquatic habitat in the Redwood Creek 

Basin, northwestern California. USGS Professional Paper 1454. Washington, DC: U.S. 

Geological Survey: L1-L8.

Nolan, K.M.; Kelsey, H.M.; Marron, D.C. 1995. Summary of research in the Redwood 

Creek basin, 1973-83. In: Nolan, K.M.; Kelsey, H.M.; Marron, D.C., editors. 

Geomorphic processes and aquatic habitat in the Redwood Creek Basin, northwestern 

California. USGS Professional Paper 1454. Washington, DC: U.S. Geological Survey:

A1-A6.

Payne and Associates, 1989. Lower Klamath River tributary delta study. Report to U.S. 

Department of the Interior, Bureau of Indian Affairs, Redding, CA. 26 p.

Recking, A. 2010. A comparison between flume and field bed load transport data and 

consequences for surface-based bed load transport prediction. Water Resources

Research 46: W03518; doi:10.1029/2009WR008007. 16 p.

Runkel, R.L.; Crawford, C.G.; Cohn, T.A. 2004. Load Estimator (LOADEST) - a 

FORTRAN program for estimating constituent loads in streams and rivers. U.S. 

Geological Survey Techniques and Methods, book 4, chap. A5. 69 p.

Schertz, T.L.; Alexander, R.B.; Ohe, D. 1991. The computer program Estimate Trend 

(ESTREND), a system for the detection of trends in water-quality data. U.S. 

Geological Water-Resources Investigations Report 91-4040. 66 p.

U.S. Bureau of Land Management. 1995. Mainstem Trinity River watershed analysis.

Redding, CA. 56 p.

Wheatcroft, R.A.; Sommerfield, C.K. 2005. River sediment flux and shelf sediment 

accumulation rates on the Pacific Northwest margin. Continental Shelf Research 25: 

311-332.
GENERAL TECHNICAL REPORT PSW-GTR-238 

88

Willis, C.M.; Griggs, G.B. 2003. Reductions in fluvial sediment discharge by coastal dams 

in California and implications for beach sustainability. Journal of Geology 111: 167-

182.

Wolman, M.G. 1954. Method of sampling coarse river bed material. Transactions of the 

American Geophysical Union 35: 951-956.
89

The VTAC Committee: Developing Guidance 

for an Alternative Regulatory Pathway to 

the Anadromous Salmonid Protection 

Rules1

Michael Liquori,

2 Peter Cafferata,3 Kevin Boston,4 Richard 

Gienger,

5 and David Hope6

Abstract

In recent decades, riparian protection standards have been guided by generalized prescriptive 

rules. With the passage of the Anadromous Salmonid Protection rules in 2009, the Board of 

Forestry and Fire Protection (Board) established a regulatory pathway that provides an 

alternative approach for riparian protection based on site-specific criteria (14 CCR § 916.9 

[936.9, 956.9](v)). This new pathway seeks to promote more immediate (short-term) 

responses to active riparian management practices that might not otherwise occur under the 

more prescriptive rule protocols. This approach requires consideration of both watershedscale limiting factors (in other words, context assessment) and site-based factors to lead to a 

modified riparian management design that provides benefits to the aquatic environment. It is 

the Board’s intent that allowing site-specific plans will create an economic incentive for 

landowners to engage in active management and restoration activities in riparian areas. 

The implementation of this new approach is being overseen by the Anadromous Salmonid 

Protection Rule Section V Technical Advisory Committee (VTAC), composed of members 

from academia, the timber industry, professional consulting firms, and the public. The 

California Department of Forestry and Fire Protection (CAL FIRE) appointed this committee 

in October 2010. The VTAC is seeking to establish principles, guidelines, and procedures to 

guide landowners in the use of this new rule section. The VTAC is focusing on: (a) 

broadening incentives, and (b) developing permitting efficiencies that properly balance the 

risks of negative impacts with the potential benefits to listed salmonid species. In short, one 

goal of the VTAC is to reduce the regulatory barriers that might otherwise prevent 

landowners from engaging in active management and restorative actions in riparian areas. 

The VTAC will use multiple pilot projects identified by landowners in both the Coast Ranges 

of California and the interior part of the state to demonstrate active riparian management, with 

potential implementation in 2011. These pilot projects include a range of desired objectives, 

including increasing large wood loading, promoting increased biotic diversity, reducing 

catastrophic wildfire risk, and accelerating conifer tree growth. 

Key words: anadromous, buffer, riparian, restoration, salmonid

 

1 This paper was presented at the redwood science symposium: coast redwood forests in a changing 

California. June 21-23, 2011. Santa Cruz, California. 2 Sound Watershed Consulting, 2201 Melvin Road, Oakland, CA 94602. (mike@soundwatershed.com).

3 California Department of Forestry and Fire Protection, P.O. Box 944246, Sacramento, CA 94244. 

(pete.cafferata@fire.ca.gov).

4 Oregon State University, College of Forestry, Department of Forest Engineering, Resources and 

Management, 204 Peavy Hall, Corvallis, OR 97331. (kevin.boston@oregonstate.edu).

5 Restoration Advocate. P.O Box 283 Whitethorn, CA 95589. (rgrocks@humboldt.net). 6 Watershed Science Consultants, 103 Doane Street, Santa Cruz, CA 95062. 

(salmonsav@sbcglobal.net).
GENERAL TECHNICAL REPORT PSW-GTR-238 

90

Introduction

Over the past 4 decades, there have been several refinements and additions to 

riparian protection rules originally established by the Z'Berg-Nejedly Forest Practice 

Act of 1973. Similar processes have occurred in Oregon, Washington, Alaska, and on 

federal timberlands (Everest and Reeves 2007). Common to most of these riparian 

protection standards is the use of prescriptive rules for longitudinally continuous 

buffer strips. These buffer strips require mandated widths and restricted harvesting 

practices, such as a minimum basal area or canopy cover, to remain following harvest 

for specific classes of stream. Such standards typically result in relatively passive, 

continuous, uniform, one-size-fits-all streamside buffers. 

Recently in California, the California State Board of Forestry and Fire Protection 

(Board) developed Anadromous Salmonid Protection (ASP) rules that seek to protect, 

maintain, and improve riparian habitats for state and federally listed anadromous 

salmonids. The Board adopted an option (14 CCR § 916.9 [936.9, 956.9] Section 

(v)), referenced here as the Section V Rule, that would support more site-specific 

decision making in the design of riparian prescriptions that could be applied during 

the time of adjacent timber harvest. This approach offers an alternative to prescriptive 

uniform buffers and may be more protective of ecological functions (Liquori and 

others 2008) (fig. 1). The intention of this new rule is to promote a more explicit 

riparian design process that addresses specific ecological and geomorphic functions 

and processes specific to the project site. In theory, more site-based riparian 

treatments could better maintain, improve, restore and/or expedite those ecological 

Figure 1—Uniform stream buffer protection measures (A and B) v. spatially variable 

prescriptions (C and D) (image from Liquori et al. (2008) (used with permission).
The VTAC Committee: Developing Guidance for an Alterative Regulatory Pathway to the 

Anadromous Salmonid Protection Rules

91

processes most important to sustaining resilient salmonid habitat conditions 

throughout forested landscapes (Benda et al. in press, Liquori et al. 2008, Ryan and 

Calhoun 2010). 

The Section V Rule allows alternative treatments to the riparian zone with the 

caveat that the effects of the proposed practices on riparian functions must be at least 

equal to those expected from the revised prescriptive standards that were adopted. 

This rule seeks to promote both immediate (short-term) responses to active riparian 

management practices that might not otherwise occur under the more prescriptive 

rule protocols, as well as longer-term habitat improvements (Liquori et al. 2008). 

This approach requires consideration of both watershed-scale limiting factors (in 

other words, context assessment) and site-based factors to lead to a modified riparian 

management design that provides benefits to the aquatic environment. It was also the 

Board’s intent that allowing site-specific plans will create an economic incentive for 

landowners to engage in active management and restoration activities in riparian 

areas. Thus, it will allow for economic incentives to encourage restoration. 

The Section V Technical Advisory Committee (VTAC) was established by the 

Board to develop a guidance document that will allow broad application of the sitespecific approach for riparian management and implementation of at least two pilot 

projects. The VTAC is composed of members from academia, the timber industry, 

professional consulting firms, the public, and includes state and federal agency 

representatives. The VTAC is seeking to establish principles, guidelines, and 

procedures to guide landowners in the use of this new rule section. It is focusing on: 

(a) broadening incentives, and (b) developing permitting efficiencies for measures 

that are necessary for recovery of listed salmonid species. One important goal of the 

VTAC is to reduce the regulatory uncertainty that might otherwise prevent 

landowners from engaging in active management and restorative actions in riparian 

areas. 

VTAC outreach survey genesis and summary 

The VTAC developed an online survey to improve acceptance of the adaptive 

rule described by the ASP Rule 916.9 Section V and to gain a better perspective on 

regulatory requirements that the landowner may face when trying to implement a 

Section V plan. The survey was distributed to landowners, Registered Professional 

Foresters (RPFs), agency personnel, and the public in spring 2011 (see: 

http://calfirevtac.weebly.com). A brief introductory video, as well as background 

information on the rule section, was provided on this website. Information from the 

survey responses is helping the VTAC develop approaches that will be used for the 

guidance document being produced for this new approach to riparian forest 

management. 

The VTAC received 123 responses to the survey. Landowners and land managers 

supplied 39 percent of the sample, while 32 percent were agency staff, 19 percent 

were consultants, 6 percent were from the general public, and 4 percent represented 

advocacy groups. Approximately half of the respondents are California RPFs. 

Roughly 70 percent of respondents had either detailed or moderate knowledge of the 

ASP Section V rule prior to taking the survey and 87 percent of the respondents were 

either very or somewhat knowledgeable of the California Forest Practice Rules.
GENERAL TECHNICAL REPORT PSW-GTR-238 

92

Eighty percent of respondents said they favor more flexible site-based riparian 

protection zone treatments that are professionally designed over a broadly 

prescriptive rule. Seventy-three percent agreed that treatments should be wellgrounded in science. Nearly 80 percent responded that they are likely to support a 

landowner’s ability to apply site-based riparian treatment through Section V rules if it 

is technically justified. 

Respondents informed the VTAC that their primary concern regarding the 

Section V rules is “too much uncertainty/inconsistency in interpretation.” 

Approximately 50 percent felt that well-documented examples of success with regard 

to navigating the various regulatory agencies’ requirements would improve their 

comfort level in the use of Section V projects. Thirty-seven percent of respondents 

said they are highly or moderately likely to submit a Section V project (15 percent 

did not reply to this question). Respondents stated that the primary reason why a 

landowner would be unwilling to submit a Section V project is “too much uncertainty 

in the process.” Approximately 30 percent plan to submit or may submit a Timber 

Harvesting Plan (THP) in the near future with a Section V project. 

The primary take-home messages from the survey are the following: (1) there is 

widespread agreement that site-based riparian management can be used where it is 

justified; (2) an increased level of certainty is required for extensive use of the 

Section V process; and (3) successful pilot projects are needed to demonstrate to 

landowners that this approach can work. 

Potential types of section V site-specific projects

Site-specific riparian management projects that are justified will vary depending 

on current watershed and riparian conditions, geographic location, and geomorphic 

characteristics of the site. Desired objectives for riparian management include 

increasing large wood loading, promoting increased biotic diversity, increasing 

nutrient cycling and biotic qualities of the salmonid food-base, and reducing 

catastrophic wildfire risk. The following sections provide brief descriptions of 

selected references related to these topics, but is not meant to be a comprehensive 

review of the riparian science literature. 

Large wood 

Most of the anadromous fish-bearing watersheds located in the Coast Ranges of 

California are currently deficient in large wood loading due to removal of wood from 

the 1960s through the 1980s (NMFS 2010, Wooster and Hilton 2004) and removal of 

much of the riparian forest in harvests prior to 1973. In smaller coastal streams, large 

wood is usually the dominant structural agent, important in pool formation and a 

critical component for habitat complexity. Generating adequate volumes of large 

wood following removal is a slow process in second-growth coastal stands due to 

lack of adequate material and low levels of mortality in these long-lived species, 

typically requiring 75 to 150 years to reach acceptable levels (Wooster and Hilton 

2004), and was exacerbated by excessive removal of large conifer trees in riparian 

zones in past decades. 

Felling and/or excavating selected large conifer trees from the riparian zone near 

the fish-bearing streams may be appropriate to rapidly create deep pools in channels 
The VTAC Committee: Developing Guidance for an Alterative Regulatory Pathway to the 

Anadromous Salmonid Protection Rules

93

with the appropriate gradient and bankfull width that are currently lacking wood. Past 

monitoring work has shown that large wood placement projects can lead to higher 

densities of juvenile coho and other salmonids (Roni and Quinn 2001, Whiteway et 

al. 2010). Unanchored large wood has the highest likelihood of relative stability in 

smaller streams (for example, third order) when the bole length is at least two times 

bankfull channel width and the rootwad remains attached (Collins 2000, WFPB 

2001). 

Spence et al. (1996) state that for second-growth stands, thinning may be 

appropriate in order to facilitate recovery and protection of key functions, particularly 

in coastal forests. Thinning can accelerate riparian conifer tree growth in areas where 

uniformly young stands exist. In these stands, there are limited large conifers for 

future recruitment to the channel. Additionally, the stream ecosystem is likely to be 

temperature limited and lack large tree habitat characteristics. Very high tree 

densities can preclude the development of large trees for decades in coast redwood 

stands (Thornburgh et al. 2000). Ligon et al. (1999) concluded that to grow and 

maintain larger diameter conifer trees in riparian areas similar to the stand structure 

for those elements found in late-successional stands, “it may be necessary to manage 

these zones through thinnings and selection harvests to promote the growth of the 

larger trees present that have the best opportunity to maximize diameter and height 

growth.” 

In general, thinning has been found to be an effective means of enhancing old 

forest development in coast redwood forests by accelerating tree growth, modifying 

species composition, and increasing stand-level variability (O’Hara et al. 2010). 

Silvicultural approaches to improve tree growth include low thinning (in other words, 

thinning from below), commercial thinning (crown thinning), and variable density 

thinning (VDT) (Teraoka and Keyes 2011). Cafferata et al. (2005) reported that 

thinning from below produced more large trees in a coastal riparian flood prone area 

over a 60-year modeling period than standard single tree selection.7 Low thinning in 

a coast redwood/Douglas fir stand has recently been reported as accelerating conifer 

growth but not promoting redwood dominance. This treatment allowed Douglas-fir to 

remain competitive in the upper canopy (Teraoka 2010, Teraoka and Keyes 2011). 

Biotic diversity and nutrients 

Increased biotic diversity and nutrient input into anadromous salmonid 

watersheds is increasingly being recognized as a key function produced from the 

riparian forests. Past studies have shown that a 30 m buffer with no tree removal 

reduces impacts to a stream that are similar to a no-harvest level (Newbold et al. 

1980). However, completely excluding vegetation management in the buffer strip can 

limit opportunities to increase fish growth rate and biomass (CSBOF 2008). Several 

studies suggest selective thinning of the riparian canopy can result in an increase in 

aquatic macroinvertebrate production, thus raising the food availability for salmonids 

(e.g., Wilzbach et al. 2005). Conifer verses hardwood-dominated riparian stand types 

can produce differing stream temperatures and channel morphology due to 

differences in canopy conditions and root density (Liquori and Jackson 2001 (fig. 2). 

Past research suggests that at appropriate locations, active riparian management that 

promotes an appropriate mixture of conifers and hardwoods can enhance primary 

 

7 Thinning from below was defined as harvesting intermediates and co-dominants only and specifying 

that the quadratic mean diameter (QMD) of the stand must increase after harvest.
GENERAL TECHNICAL REPORT PSW-GTR-238 

94

productivity and produce temperature regimes that promote fish production. The 

riparian stand characteristics most likely to achieve these functions include: (1) a 

sufficient number of nitrogen-fixing deciduous trees distributed at key locations 

within the stream network, and (2) a sufficient number of riparian canopy gaps that 

allow for sunlight to support macroinvertebrate production while balancing effects on 

other riparian functions (CSBOF 2008). 

Fuel hazard reduction 

Research has shown that fuel hazard reduction projects can reduce the risk of 

catastrophic crown wildfire (Martinson and Omi 2003, Omi and Martinson 2004). 

This concept directly applies to riparian zones, where active management can prevent 

dense stands of trees from contributing to rapid fire spread upslope, particularly in 

the interior parts of California with hotter and drier climates. Balancing the potential 

benefits of fuel hazard reduction with the possible risks to habitat recovery, however, 

will be complex and require careful consideration by both the project proponent and 

the reviewing agencies. 

Fire behavior models have been used to show that some parts of the landscape 

Figure 2—Diagram of a unevenaged conifer-dominated riparian stand (above) v. a 

hardwood-shrub riparian stand (below) from the east slope of the Cascade Mountains 

in Washington (image from Liquori and Jackson 2001). Note differences in stream 

shading and channel morphology for each stand type. 
The VTAC Committee: Developing Guidance for an Alterative Regulatory Pathway to the 

Anadromous Salmonid Protection Rules

95

are highly prone to catastrophic wildfire (in other words, a rapidly moving crown 

fire). This information can be used to justify prescriptions to reduce surface fuels, 

intermediate fuels, and co-dominate fuels (in other words, “ladder fuels”) in the 

riparian zone that differ from the standards in the ASP rules. Treatment could occur 

both in the Class I (fish-bearing) watercourse and lake protection zone (WLPZ) core, 

inner, and outer zones, as well on the hillslopes beyond the WLPZ, creating a 

landscape level fire hazard reduction project. Recent modeling work by Van de 

Water and North (in press) shows that Sierra Nevada riparian forests are significantly 

more fire prone under current management regimes with excluded harvest that allow 

for a build-up of fuels when compared to riparian areas that have been exposed to an 

active-fire regime. Additionally, under current conditions, riparian forests were found 

to be significantly more fire prone than upland forests. The 2007 Angora Fire at 

South Lake Tahoe provides an example of this situation. Murphy et al. (2007) 

reported that dense stands of trees in the Angora SEZ (Stream Environment Zone) 

likely contributed to the rapid fire spread to Angora Ridge by supporting crown fire 

runs upslope. 

Framework for riparian design

Site-based riparian design should: (1) identify the relative importance of riparian 

function inputs (wood, heat, sediment, litter/invertebrates) for forming aquatic habitat 

and to affect water quality in the adjacent stream reach, and (2) assess the potential 

connectivity (in other words, transport) of riparian inputs to downstream channels. 

The sensitivity or response of aquatic resource condition to riparian inputs and the 

potential downstream connectivity are indicators of riparian function importance. 

Channel response potential and downstream connectivity are strongly influenced 

by channel geomorphology (gradient, confinement, bed composition), stream 

size/flow, and position in the stream network. Although channel morphology and 

flow vary along the stream network, a stream may be subdivided into reaches with 

distinct channel forms that are reflective of watershed topography and channel 

forming processes (Montgomery and Buffington 1997, Paustian et al. 1992). Such 

geomorphic stream classification provides a qualitative tool for assessing response 

potential to changes in riparian function inputs (WFPB 1997). We adopt this 

approach by apply a typing system that combines stream size (based on channel 

width or regionally calibrated basin areas) with the Montgomery-Buffington 

classification (table 1). More rigorous evaluation of response potential can be 

facilitated by quantitative modeling of channel conditions and watershed processes 

(Benda et al. 2007). 

VTAC guideline document and pilot projects

The VTAC is developing guidance documents that will: (1) identify qualifying 

criteria for suitability of sites for various treatment options, (2) help identify sitebased objectives, (3) outline treatment option alternatives that are consistent with 

those objectives, (4) establish guidance for the data necessary to justify proposed 

actions, and (5) clarify administrative procedures for obtaining agency approvals. In 

preliminary “interim” guidance, the VTAC has established a simplified procedure for 

prioritizing among four objectives: wood loading, thermal regulation, nutrient 
GENERAL TECHNICAL REPORT PSW-GTR-238 

96

cycling, and sediment. 

VTAC pilot projects guidelines documents will allow RPFs to determine if sitespecific riparian management is appropriate for a given location. Both a “default 

design process” using a structured classification system, and a more flexible 

Table 1—Preliminary channel sensitivity/response potential to changes in exchange function 

inputs in relation to stream size and channel type.

Function input (channel response metric)

Channel type

Stream 

size

Large wood

(pool 

formation)

Shade

(temperature)

Sediment

(grain size)

Litter

(retention)

colluvial small M H M H 

bedrock all L H L L 

cascade all L M M L 

step pool all M H M M 

plane bed all H H H L 

pool riffle small H H H H 

pool riffle medium H M H H 

pool riffle large H L H M 

dune ripple small M H L M 

dune ripple medium M M L L 

dune ripple large L L L L 

alluvial fan all H M H H 

“customized design process” requiring more data and expertise are available in the 

draft document. Major steps using the default design process include: (1) evaluating 

existing site conditions, (2) identifying functional objectives, and (3) developing site 

prescriptions. 

While still under development, key concepts to be included in this guidance 

document are: (1) methods for assessing watershed-scale limiting/constraining 

factors, (2) information on how to conduct the assessment at the appropriate spatial 

scale, and (3) riparian stand modeling methodologies for watershed-scale projects 

(for example, the RAIS model for LWD and shade; Welty et al. 2002). 

The initial version of the guidelines will be used for implementing Section V 

pilot projects that are undertaken in the summers of 2011 and 2012. Potential pilot 

project locations range from Santa Cruz County to Humboldt County in the Coast 

Ranges, as well as in the Klamath Mountains and the Sierra Nevada. The list of 

potential pilot projects include the full range of desired objectives, including 

increasing large wood loading, promoting increased biotic diversity, reducing 

catastrophic wildfire risk, and accelerating conifer tree growth. 

The vision for the final document is broad and includes sections on project preconsultation guidance with the state and federal agencies, context assessment at the 

watershed scale, project/site evaluation tools using a refined version of the modified 

Washington watershed analysis approach discussed above, and monitoring guidance. 

The final document will use feedback from the preliminary documents produced by 

the group. 
The VTAC Committee: Developing Guidance for an Alterative Regulatory Pathway to the 

Anadromous Salmonid Protection Rules

97

Conclusions

The VTAC is optimistic that the pilot projects will be successful and demonstrate 

to landowners in California that site-specific riparian management is both 

economically viable and ecologically valuable. It is clear that rapidly accelerated 

habitat improvement for listed anadromous fish species such as coho salmon is 

needed if these species are to recover in this state (NMFS 2010). Hope remains high 

since all surveyed stakeholder groups agree that site-based riparian management is 

appropriate where it is justified and necessary for recovery. Most types of projects 

seem likely to be accepted by the state and federal reviewing agencies in appropriate 

situations. It does appear, however, that riparian management that results in impacts 

only on hillslopes will be initially easier to permit as part of a THP in California than 

those that cause impacts in the stream channel (for example, large wood placement 

projects). These projects may require a federal permit before they can be completed 

and difficulties currently exist with addressing compliance with the Federal 

Endangered Species Act (ESA).

The status of the pilot projects and guidance document that will allow for broad 

application of the site-specific approach for riparian management will be presented to 

the Board in the second half of 2011. The final VTAC report is expected to be 

completed by the summer or early fall of 2012. 

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behavior, suppression effectiveness, and structure ignition on the Angora Fire. Res. 

Paper R5-TP-025. Vallejo, CA: U.S. Department of Agriculture, Forest Service, Pacific 

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and conservation of the coast redwoods. Washington DC: Island Press: 229-261. 

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dynamics for the generation of large woody debris and shade. Forest Ecology and 

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canopy opening and salmon carcass addition on the abundance and growth of 

resident salmonids. Canadian Journal of Fisheries and Aquatic Sciences 62: 58-67.

Wooster, J.; Hilton, S. 2004. Large woody debris volumes and accumulation rates in 

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101

Assessing Effects of Changing Land Use 

Practices on Sediment Loads in Panther 

Creek, North Coastal California1

Mary Ann Madej,2 Greg Bundros,

3 and Randy Klein3

Abstract

Revisions to the California Forest Practice Rules since 1974 were intended to increase 

protection of water quality in streams draining timber harvest areas. The effects of improved 

timber harvesting methods and road designs on sediment loading are assessed for the Panther 

Creek basin, a 15.4 km2 watershed in Humboldt County, north coastal California. We 

compute land use statistics, analyze suspended sediment discharge rating curves, and compare 

sediment yields in Panther Creek to a control (unlogged) stream, Little Lost Man Creek. From 

1978 to 2008, 8.2 km2 (over half the watershed) was clearcut and other timber management 

activities (thinning, selection cuts, and so forth) affected an additional 5.9 km2

. Since 1984, 

40.7 km of streams in harvest units received riparian buffer strip protection. Between 2000 

and 2009, 22 km of roads were upgraded and 9.7 km were decommissioned, reducing 

potential sediment production by an estimated 40,000 m3

. Road density is currently 3.1 

km/km2

. Sediment rating curves from 2005 to 2010 indicate a decrease in suspended sediment 

concentrations when compared to the pre-1996 period, although Panther Creek still has a 

higher sediment yield on a per unit area basis than the control stream.

Key words: suspended sediment rating curves, timber harvest, watershed assessment, 

sediment yield

Introduction

Historically, timber harvest and related road construction have caused accelerated 

hillslope erosion and sediment delivery to streams, impacting salmonid habitat in 

California and the Pacific Northwest (Meehan 1991, Murphy 1995). In recognition of 

these problems, several regulatory efforts have been implemented to ameliorate the 

effects of land use activities on streams. For example, revisions to the modern 

California Forest Practice Rules, implemented beginning in 1974, were intended to 

increase protection of water quality in streams draining timber harvest areas. 

Protective measures included use of improved riparian buffers, where timber harvest 

operations are limited, and improved standards for newly constructed and upgraded 

roads. In July 2000, the California Forest Practice Rules changed watercourse 

crossing sizing requirements for new or reconstructed permanent stream crossings 

from a 50-year storm to a 100-year storm (CDF 2001), thus gradually reducing the 

risks of culvert failure and resultant gullies and landslides as new larger culverts are 

installed. Forest Practice Rule changes in 1983 changed how streams were classified 

and increased tree retention along Class I (fish bearing) and Class II (habitat present 

 

1 This paper was presented at the redwood science symposium: coast redwood forests in a changing 

California. June 21-23, 2011. Santa Cruz, California. 2 U.S. Geological Survey, 1655 Heindon Rd, Arcata CA 95521. (mary_ann_madej@usgs.gov). 3 Redwood National and State Parks, 1655 Heindon Rd, Arcata CA 95521. (gbundros@suddenlink.net; 

randy_klein@nps.gov).
GENERAL TECHNICAL REPORT PSW-GTR-238 

102

for non-fish aquatic species) streams. Class III streams contain no aquatic life and 

receive the least protection. 

In addition, Section 303(d) of the federal Clean Water Act of 1972 requires states 

to identify water bodies that do not meet water quality standards and are not 

supporting their beneficial uses. Redwood Creek in Humboldt County, north coastal 

California, was 303(d) listed as sediment impaired in 1996, and a Total Maximum 

Daily Load (TMDL) was developed for the watershed in 1998 (CRWQCB 1998a, 

1998b). The Redwood Creek Sediment TMDL identified major sediment sources to 

Redwood Creek as streamside landslides, gully erosion, and cutbank and fillslope 

failures on unpaved logging roads. Although state forest practice rules do not require 

long-term road inspection and maintenance, the TMDL included targets for desired 

watershed conditions with respect to road design, location, inspection, and 

maintenance along with timber harvest practices in sensitive streamside areas. In 

recent years landowners in the basin have conducted several erosion control projects 

on their lands to address erosion concerns. Madej et al. (2007) evaluated sediment 

loads in the mainstem of Redwood Creek in the context of the TMDL, but trends in 

sediment yields in tributary basins of Redwood Creek have not yet been analyzed to 

that extent.

In Panther Creek, a tributary of Redwood Creek, timber harvest has been the 

primary land use since the 1930s. Green Diamond Resource Company (GDRCo), the 

current landowner, began implementing an Aquatic Habitat Conservation Plan 

(AHCP) in 2007, which includes the Panther Creek basin. During the past decade, 

GDRCo has completed several road assessments, road upgrades and road 

decommissioning projects in the watershed. Since 1980, the U.S. Geological Survey 

(USGS) and Redwood National Park (RNP) have operated a stream gaging station at 

the mouth of Panther Creek, where stream discharge and suspended sediment are 

measured. Consequently, it is an opportune time to evaluate sediment yields 

measured at the gaging station to determine if sediment reduction goals have been 

met. The objective of this paper is to evaluate possible changes in sediment loading 

in Panther Creek due to improvements in timber harvest methods and road designs 

and maintenance by analyzing shifts in suspended sediment discharge rating curves, 

and comparing sediment yields in Panther Creek to a nearby control (unlogged) 

stream.

Field area

Panther Creek has a drainage area of 15.4 km2 (fig. 1). Total basin relief is 600 

m. The bedrock is a quartz-mica schist of the Franciscan assemblage. Aerial 

photographs taken in 1936 show that about half of the basin was covered with oldgrowth redwood and Douglas-fir forests, but upper hillslopes had been clearcut 

logged and yarded using steam donkeys (steam-powered winches that dragged logs 

across the hillslopes) and railroad equipment. Harvest operations accelerated in the 

1950s with increased demand for timber products following World War II. Beginning 

in the late 1940s and continuing into the 1980s ground based equipment, such as 

crawler tractors, were used for skidding. By the early 1980s nearly all of the oldgrowth forest had been harvested. Second-growth harvest activities began in the 

1980s utilizing commercial thinning and rotational harvests as the timber reached 

commercial size and age. The majority of roads in Panther Creek were constructed 
Assessing Effects of Changing Land Use Practices on Sediment Loads in Panther Creek, North 

Coastal California

103

before implementation of the Z'berg-Nejedly Forest Practice Act beginning in 1974, 

which provided for more stable road designs in subsequent years. In addition, the 

early old-growth harvesting retained very minimal riparian protection along streams. 

Figure 1—Location map.

In 1980 the USGS, in cooperation with Simpson Timber Company (later 

renamed Green Diamond Resource Company), established a gaging station on 

Panther Creek (Station #11482125). In addition, the USGS established a gaging 

station on an unlogged tributary in the lower Redwood Creek basin, Little Lost Man 

Creek (Station #11482468) in 1975 (fig. 1). Little Lost Man Creek (9.1 km2

) is 

underlain by sandstones and mudstones of the Franciscan assemblage. Basin relief, at 

610 m, is similar to Panther Creek, and both basins exhibit similar erosion processes 

(primarily shallow debris slides and debris flows). Continuous streamflow and storm 

flow suspended sediment samples were obtained at both stations. RNP assumed 

operations of the gaging stations in 1993. In 2006 RNP installed turbidity sensors at 

the gaging stations to supplement the suspended sediment sampling program. 

The Panther Creek basin receives an average of about 2,000 mm of precipitation 

annually, most of which falls as rain between October and March. Annual mean flow 

is 0.68 cms. The highest peak flow of the 30-year record, 57 cms, occurred on 

January 1, 1997, although based on records from Redwood Creek, peak flows in the 

1960s and 1970s were probably larger (fig. 2). The storm in January, 1997 initiated 

13 landslides > 400 m2 in area in the Panther Creek basin, which mobilized about 

24,000 m3

 of material. About 80 percent of this volume was generated by landslides 

associated with roads and landings, including a 9,000 m3 debris flow that severely 

scoured the channel (Curren 2007). Several smaller landslides occurred the previous 
GENERAL TECHNICAL REPORT PSW-GTR-238 

104

year as well. Annual rainfall in Little Lost Man Creek basin is 1,700 mm and mean 

annual flow is 0.34 cms. No landslides were detected here on 1:6,000 air photos 

following the 1997 storm. 

Figure 2—Peak flows at Redwood Creek at Orick, CA.

Methods

We used timber harvesting plans approved by California Department of Forestry 

and Fire Protection (CAL FIRE), aerial photographs, and field-based road inventories 

to compile land use statistics for the Panther Creek watershed. Because work 

proposed in a timber harvesting plan may be implemented any time within three 

years of plan approval, exact dates of some timber harvest and road work are not 

known. Attributes included the timing and size of timber harvest, silvicultural and 

yarding methods, and level of streamside protection (RNP, unpublished data). Little 

Lost Man Creek is almost completely unlogged, with no change in land use during 

the study period. 

Gaging stations in Panther Creek and Little Lost Man Creek record water stage at 

10-minute intervals. Stage data are converted to discharge values using individual 

stage-discharge rating curves for each station, based on occasional discharge 

measurements that relate recorded stage to water discharge. Since 2006, electronic 

turbidity sensors mounted on articulating booms have measured turbidity in the water 

column at 10 minute intervals. Before 1992 suspended sediment samples were 

collected manually at high flows, whereas after 1992 an electronic pumping water 

sampler collected samples according to changes in turbidity or stage (Klein 2003). 

Water samples were processed in USGS or RNP laboratories to obtain suspended 

sediment concentrations. Accuracy of suspended sediment load computations most 

likely improved greatly with the addition of automated pumping samplers and 

turbidity-controlled sampling (Lewis 1996). 
Assessing Effects of Changing Land Use Practices on Sediment Loads in Panther Creek, North 

Coastal California

105

We constructed suspended sediment rating curves by plotting sediment 

concentration (SSC, mg/l) against instantaneous discharge (cms) on a logarithmic 

scale for five time periods, based on groupings of water years that were wetter (w) or 

drier (d) than normal (n): pre-1986 (w), 1987 to 1995 (d), 1996 to 1998 (w), 1999 to 

2005 (d), and 2006 to 2010 (n). (A water year (WY) extends from October 1 to 

September 30). We ran an ANCOVA model on the sediment data, using 

log(discharge) as the independent covariate, log(suspended sediment concentration) 

as the dependent variable, and time period as a categorical factor. An interaction 

variable of [time period * log(discharge)] was included to assess possible differences 

in intercepts and slopes of the sediment rating curves. 

Annual suspended sediment loads were available for most years for WY1980 to 

2010 for Panther Creek from either computations by RNP (WY1992 and later) or 

from the USGS (before WY1992). Annual loads also exist for most of this period for 

Little Lost Man Creek, with the exception of two periods (WY1983 to 1984 and 

WY1990 to 1992). Prior to the use of continuous recorded turbidity as a surrogate for 

SSC, the sediment rating curve approach was used for computing loads. 

Results

Based on CAL FIRE-approved harvesting plans, the cutting rate in Panther Creek 

from 1978 to 2008 ranged from 0 to about 7 percent of the watershed annually, and 

averaged about 3 percent per year. Even-aged management (clearcut, rehabilitation, 

and so forth) was applied to more than 60 percent of the watershed. Non-even-aged 

management (thinning, selection, and so forth) was applied to an additional 30 

percent during this period. For the same period, about 60 percent of the harvested 

area was yarded by tractors, 30 percent by cable systems and 10 percent by a 

combination of helicopters and feller-bunchers. In 2006 GDRCo stopped all use of 

tractors for ground-based yarding operations in favor of feller-bunchers, which 

appear to minimize ground disturbance. 

Road density in the Panther Creek basin is currently 3.1 km/km2

, down from 4.2 

km/km2

 in 2000. Since 2000, 24.5 km of road have been upgraded and 15.7 km have 

been decommissioned. The potential sediment savings associated with this work is 

about 40,000 m3 (Bundros and Short 2011). Based upon road assessment data from 

2004, one third of all roads assessed in Panther Creek were being maintained. In 

2009, reassessment showed that three-fourths of the assessed roads were being 

maintained (or were maintenance-free because they have been decommissioned). 

GDRCo’s AHCP contains standards that require road inspections and maintenance of 

mainline roads every year and secondary roads every 3 years for the 50-year life of 

the permit (GDRCo 2006), which are more stringent standards than the state forest 

practice rules. 

Watercourse and Lake Protection Zone (WLPZ) rules were adopted by State 

Board of Forestry and Fire Protection and implemented in 1974, following the 

passage of the Z'berg-Nejedly Forest Practice Act of 1973 by the State Legislature. 

The rules and classification criteria for streams have changed several times, with 

significant changes occurring in 1983 (Berbach 2001). Since 1984, 57.6 km of 

streams have been included in timber harvest plans in the Panther Creek basin, of 

which 7.3 km were classified as Class I. Of the remaining stream length, for the 

period of 1984 to 1993, 44 percent (16.5 km) were classified as Class II, and 9.3 km 
GENERAL TECHNICAL REPORT PSW-GTR-238 

106

classified as Class III. For the period 1994 to 2008, 26.2 km of stream were classified 

as Class II (78 percent) and only 7.6 km classified as Class III. Consequently a higher 

percentage of stream length received increased riparian tree retention and protection 

in recent years.

Sediment rating curves were constructed for five time periods (fig. 3). The 

sediment records exhibit high variability, as is typical of mountainous, forested 

watersheds (Sadeghi et al. 2008). Nevertheless, we can discern some statistically 

significant trends in the results. The results of the ANCOVA analysis show that time 

period is a significant variable in explaining the trends (p < 0.001). The earliest 

period (WY1980 to 1986, #1) had the steepest slope, which can indicate that new 

sediment sources became available when discharge increased (Asselman 2000). 

Figure 3—Sediment rating curves for Panther Creek for five time periods.

However, because of logistic difficulties in manual sampling, this early period 

also had far fewer samples (47) than other periods. The slope of the rating curve 

decreased in the following period (WY1987 to 1995, #2), showing that sediment 

concentrations were lower at high discharges than in the earlier period. The period 

with high landslide activity (WY1996 – 1998, #3) had a significant upward shift in 

the sediment rating curve, with higher sediment concentrations across the range of 

flows. These elevated levels did not persist long, however, and the curve for the 

period WY1999 to 2005 (#4) lowered to the WY1987 to 1995 level (intercepts were 

not significantly different). The most recent period (WY2006 to 2010, #5) has the 

lowest rating curve. Even though the relationship between suspended sediment 

concentration and discharge is weak for this time period (r2 of only 9.3 percent), it is 

still significant at the 95 percent confidence level (p-value of < 0.001). 

Annual suspended sediment loads differed substantially between Panther Creek 

and the control stream, Little Lost Man Creek, during the common years of 

operation. The annual suspended sediment load for Panther Creek ranged from a low 

of 23 Mg to a high of 36,000 Mg. Average sediment load for Panther Creek was 220 
Assessing Effects of Changing Land Use Practices on Sediment Loads in Panther Creek, North 

Coastal California

107

Mg/km2 versus 56 Mg/km2 for Little Lost Man Creek. We compared the ratio of 

sediment loads for each year (Panther load divided by Little Lost Man load, fig. 4). 

The average ratio was 4, with a maximum of 20 during the high flow year of 

WY1997. In WY1981, 1999 and 2001 the normalized sediment load in Panther 

Creek was less than that of Little Lost Man Creek. In WY1999, several inner gorge 

landslides temporarily elevated loads in Little Lost Man Creek, thus reducing the 

ratio for that year. WY2001 had the lowest annual flow and the lowest sediment load 

values in the Panther Creek record, so the small differences between Panther and 

Little Lost Man creeks in low flow years (0.3 Mg/km2

) probably are not meaningful. 

Figure 4—Comparison of annual suspended sediment yields between Panther Creek

(PAN) and a control stream, Little Lost Man Creek (LLM).

Discussion

Sediment supply to rivers in forested mountainous terrain is commonly episodic 

in nature through such processes as mass movement and gullying. Large storms are 

usually needed to trigger severe erosion events, and the landslide-producing storm in 

Panther Creek in 1997 is an example of such an event. In the Redwood Creek basin, 

once material is delivered to steep low-order channels, much of it is routed 

downstream within a few years (Pitlick 1995). In recent years land managers have 

implemented erosion control work on the hillslopes of the Panther Creek basin to 

decrease sediment input to streams and provide more protection to sensitive 

streamside areas. Nevertheless, most of these treatments were implemented post1997 and have not been “tested” by a large storm (20-year return period or greater). 

We would not expect reductions in erosion to be detected at the mouth of Panther 

Creek until such a test occurs. 

Sediment rating curves shifted upward during and immediately after a period of 

high landslide activity in 1996 to 1998. Since then, suspended sediment 

concentrations at moderate to high discharges have decreased. Even so, the sediment 

records exhibit high variability. This variability problem may be addressed by further 

investigations, such as separating data by storms or hydrograph limbs. Sediment 
GENERAL TECHNICAL REPORT PSW-GTR-238 

108

loads are still higher in Panther Creek than in the control stream, but are less than half 

that of the Redwood Creek basin average (600 Mg/km2

 measured at the Redwood 

Creek at Orick gaging station).

Assessing the influence of land use practices and hillslope improvement work on 

sediment loads is complicated by factors such as the lag time between implementing 

erosion control work and sediment transport events, the effect of legacy features from 

past timber harvest, and the occurrence of extreme events. The high volume of 

material mobilized from road-related landslides in the 1997 storm attests to ongoing 

sediment production from remaining legacy roads. On the other hand, current policies 

such as increasing riparian protection, decreasing timber harvest on inner gorge 

slopes, and reducing controllable sediment sources along roads may reduce sediment 

loads in future storms. Continued stream and hillslope monitoring will help elucidate 

such linkages.

Conclusions

The Panther Creek basin is an actively managed watershed with an average 

timber harvest rate of three percent of the watershed per year. Improvements in 

timber harvest techniques, streamside protection, road design and maintenance 

implemented in the Panther Creek basin in recent years appear to have caused a 

downward shift in the sediment rating curve and reduced sediment loads relative to 

those of decades earlier. Results from sediment sampling indicate that sediment loads 

were highest during a period of high landslide activity in 1996 to 1998; most of the 

sediment volume was contributed by landslides associated with roads and landings. 

Consequently, the effect of untreated legacy erosion problems in a basin can obscure 

the beneficial effect of improved erosion control work and improved timber harvest 

practices elsewhere in a watershed. Since 1998 suspended sediment rating curves for 

Panther Creek have shifted downward, indicating a general decrease in sediment 

concentrations. Annual suspended sediment yields remain about four times higher 

than in a control (unlogged) watershed. Hydrologic stresses during a large storm with 

a discharge having greater than a 20-year recurrence interval are needed to test the 

effectiveness of recent erosion control work and improved timber harvest methods on 

the hillslopes and to realize the time-delayed benefits. Adaptive land management 

involves monitoring the effects of management activities, and modifying land 

management approaches and techniques based on what is found to be effective. The 

data set for Panther Creek provides an excellent baseline for future assessments of 

improved management actions. 

Acknowledgments 

We are grateful for the field and technical support from Tom Marquette, and the 

meticulous laboratory analysis of Carrie Jones, both of Redwood National Park. 

Green Diamond Resource Co. provided access to the Panther Creek gaging station. 

Julie Yee and Philip van Mantgem provided statistical guidance, and reviews by 

Darci Short, Matt House, and two anonymous reviewers improved the manuscript.
Assessing Effects of Changing Land Use Practices on Sediment Loads in Panther Creek, North 

Coastal California

109

References

Asselman, N.E.M. 2000. Fitting and interpretation of sediment rating curves. Journal of 

Hydrology 234: 228-248. 

Berbach, M.W. 2001. Biological background for regulatory requirements of WLPZs. In: 

Proceedings of the 22nd Annual Forest Vegetation Management Conference, Redding, 

CA: 83-88. 

Bundros, G.J.; Short, D. 2011. Upper Redwood Creek watershed road assessment: 

updated summary report: Redwood National and State Parks. Report to the Pacific 

Coast Fish, Wetlands and Wildlife Restoration Association. Arcata, CA. 84 p.

California Department of Forestry and Fire Protection. 2001. California forest practice rules 

2001. Title 14, California Code and Regulations Chapters 4 and 4.5. Compiled by the 

California Department of Forestry and Fire Protection Resource Management, Forest 

Practice Program. Sacramento, California. 254 p.

California Department of Forestry and Fire Protection. 2009. Anadromous salmonid 

protection rules, 2009. Modification for OAL approval November 30, 2009. Title 14 of 

the California Code of Regulations (14 CCR). Sacramento, California. 98 p.

California Regional Water Quality Control Board North Coast Region (CRWQCB) 1998a.

Proposed Redwood Creek water quality attainment strategy for sediment (total 

maximum daily loads and implementation plan). Santa Rosa, California. 28 p. 

California Regional Water Quality Control Board North Coast Region. 1998b. Supplemental 

report for the proposed Redwood Creek water quality attainment strategy for 

sediment. Santa Rosa, California. 74 p. 

Curren, T.L. 2007. A landslide study in the Redwood Creek Basin, northwestern 

California: effects of the 1997 storm. Arcata, CA: Humboldt State University. M.S. 

thesis. 107 p.

Green Diamond Resource Company (GDRCo). 2006. Aquatic habitat conservation plan 

and candidate conservation agreement with assurances. Volume 1. Green Diamond 

Resource Company. 552 p.

Klein, R. 2003. Duration of turbidity and suspended sediment transport in salmonidbearing streams, north coastal California. A Report to the U.S. Environmental 

Protection Agency Region IX San Francisco, CA. 29 p. plus appendices. 

Lewis, J. 1996. Turbidity-controlled suspended sediment sampling for runoff-event load 

estimation. Water Resources Research 32(7): 2299-2310.

Madej, M.A.; Klein, R.; Ozaki, V.; Marquette, T. 2007. Analyzing sediment yields in the 

context of TMDL’s. In: Federal interagency sedimentation conference proceedings; 

2006 April, Reno, NV.

Meehan, W.R., editor. 1991. Influences of forest and rangeland management on salmonid 

fishes and their habitats. American Fisheries Society Special Publication 19. Bethesda, 

MD. 751 p. 

Murphy, M.L. 1995. Forestry impacts on freshwater habitat of anadromous salmonids in 

the Pacific Northwest and Alaska--requirements for protection and restoration. 

NOAA Coastal Ocean Program Decision Analysis Series No. 7. NOAA Coastal Ocean 

Office, Silver Spring, MD. 156 p. 

Pitlick, J. 1995. Sediment routing in tributaries of the Redwood Creek Basin, 

northwestern California. Chapter K. In: Nolan, K.M.; Kelsey, H.M.; Marron, D.C., 

editors. Geomorphic processes and aquatic habitat in the Redwood Creek Basin, 

northwestern California. USGS Professional Paper 1454. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

110

Sadeghi, S.H.R.; Mizuyama, T.; Miyata, S.; Gomi, T.; Kosugi, K.; Fukushima, T.; Mizugaki, 

S.; Onda, Y. 2008. Development, evaluation and interpretation of sediment rating 

curves for a Japanese small mountainous reforested watershed. Geoderma 144: 198- 

211.
111

Fine Sediment Sources in Coastal 

Watersheds with Uplifted Marine Terraces in 

Northwest Humboldt County, California 

Stephen Sungnome Madrone1 and Andrew P. Stubblefield1

Abstract

Erosion in the Mill and Luffenholtz Creek watersheds in Humboldt County, California, with 

their extensive clay soils, can lead to high turbidity levels in receiving bodies of water, 

increasing the costs of treating water for domestic water supplies. Detailed road and erosion 

surveys and monitoring of suspended sediment, discharge, and turbidity levels in Mill Creek 

(3.11 km2

) and Luffenholtz Creek (12.95 km2) were completed to determine the sources of 

turbidity. Watershed physiographic and land use characteristics were compared for those 

basin areas upstream from the eight monitoring sites and a statistical analysis was completed 

to determine whether significant differences existed between turbidity levels in the 

watersheds. The Luffenholtz Creek watershed, particularly Grassy and 18 Creeks, and the 

main stem of Luffenholtz, just downstream of the 21 Rock Quarry, were the sub-watershed 

areas with the highest turbidities. They were also the sub-watershed areas with the highest 

density of roads, the most miles of roads adjacent to streams, and the highest concentration of 

identified erosion-prone sites. Although Mill Creek was the watershed with the highest rate of 

timber harvesting during the past 10 years, the steepest stream profile, and a history of more 

extensive fires, its turbidities were nearly always lower than Luffenholtz Creek.

Key words: sediment budget, turbidity, forest road, water quality, coastal California

Introduction

Turbidity in Luffenholtz Creek, north coastal California, has increased treatment 

costs for the City of Trinidad. Excessive turbidity, especially the kind caused by 

erosion of colloidal clay, can be expensive and difficult to treat. Even with effective 

use of filters and chemical alars (which floc the clay particles together allowing 

filtration) there is still the potential for creation of a dangerous by-product, chloro-trihalomethanes that can remain in the treated water. This by-product is a known 

cancer-causing agent 2

. High turbidities can lead to water shortage emergencies and 

can create safety hazards for the community; storage shortages can occur from brief 

firefighting efforts or broken pipes during a freeze. Storage tank recharge can be 

difficult during periods of high turbidity. 

Creeks draining the Trinidad area terraces were considered by Boyd (1978) to be 

possible sources of water quality degradation in the Area of Special Biological 

 

1 Graduate Student and Professor, respectively, Department of Forestry and Wildland Resources, 

Humboldt State University, Arcata, CA 95521. (sungnome@madroneenterprises.com; 

aps14@humboldt.edu).

2 Winzler and Kelly, 2008. Water system options for improvements, to the City of Trinidad, 

Trinidad, California. Preliminary Engineering Report, June, 2008.
GENERAL TECHNICAL REPORT PSW-GTR-238 

112

Significance (ASBS). This ASBS is a specifically designated sensitive coastal area in 

and around Trinidad Bay in the area near where Mill and Luffenholtz Creeks drain 

into the ocean (fig. 1).

Figure 1—Study watersheds.

The objective of this study is to locate and prioritize for treatment the sources of 

fine sediment in these coastal watersheds dominated by uplifted marine terraces. This 

study will help inform the efforts to improve water quality in these streams for 

humans and aquatic species. For this investigation we formed two hypotheses. The 

first is that road density and adjacency have a greater effect on turbidity than other 

physiographic and land use characteristics on these uplifted marine terraces, and that 

because of this Luffenholtz Creek will have higher turbidities than Mill Creek. The 

second hypothesis is that the 0.8 km section of the CR 1000 Road immediately below 

the 21 Rock Quarry is a significant contributor of turbidity to Luffenholtz Creek due 

to its immediate proximity to the stream. 
Fine Sediment Sources in Coastal Watersheds with Uplifted Marine Terraces in Northwest 

Humboldt County, California

113

Study site

Luffenholtz and Mill Creeks were chosen for study because they represent 

unique, and not well studied, topography for this region. They provide habitat for 

endangered species and water supplies for domestic use. Study sites are shown in fig. 

1. Both creeks support populations of anadromous steelhead trout (Oncorhynchus 

mykiss), an Endangered Species Act Listed species, and cutthroat trout 

(Oncorhynchus clarki). The Mill Creek watershed is 404 ha in size, and lies on the 

north side of the city. It was the original water supply and is now the back up or 

alternative water supply. The Luffenholtz Creek watershed is 1527 ha in size and is 

the primary source of water for the citizens of the city of Trinidad, population 311, 

and other watershed residents. As the Mill and Luffenholtz Creek watersheds are 

adjacent and have similar soils, rainfall, and geological formations, they were 

expected to have similar particle characteristics and turbidity levels. 

Comprehensive sediment source assessments have been completed recently for 

most of the watersheds that drain the Trinidad Terraces area, including Mill and 

Luffenholtz Creeks (Allan and Ledwith 2008). Water quality sampling on the two 

creeks was done in spring of 2007 by Cinowalt and Van Matre (unpublished). 

Sampling at the mouths of all the main local creeks, draining this uplifted terrace 

area, was carried out in 2006 through 2009, by Madrone and Allan (unpublished). 

My project builds on these recent studies. The grab samples taken over a 4 year 

period increased from 1 per year in 2006 to 42 samples in Water Year 2009. This 

increased sampling was also focused completely on Mill and Luffenholtz Creeks for 

WY 2009. The results of this sampling were used to compare with watershed 

characteristics and land use variables. These variables included the results from 

detailed on-the ground roads and creek surveys in order to determine what and how 

big the sources of sediment were, whether there was delivery potential, and how they 

affected turbidity. Table 1 provides the detailed watershed characteristics and land 

use variables that make up the different sub-basins of the Luffenholtz and Mill Creek 

watersheds. These details include geology, fire history, drainage area and basin relief, 

road surfacing, densities and lengths, timber harvest history, harvesting types and 

techniques, past and potential soil loss. The following discussion highlights the table 

information. 

The geologic map for the Trinidad area shows that Mill Creek drains 

predominantly Franciscan rocks. Luffenholtz also has significant areas of Franciscan 

geology, mostly in the inner canyon and on slopes between terraces. The remainder 

of both watersheds is underlain by uplifted marine terrace soils. The Franciscan soil 

types have higher clay content (23 to 40 percent) in the A and B horizons than the 

Marine Terrace soil types (13 to 30 percent). Both soil types have high clay contents 

(fig. 2). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

114

Table 1—Site/sub-basin characteristics.

Methods

We used the methods listed below to evaluate sediment sources for two small 

coastal watersheds in northwest California, USA. Seven sources of data are utilized 

in this analysis including road erosion and sedimentation assessments completed in 

2007, by Madrone, D. Allan, and T. Ledwith of the Redwood Community Action 

Agency for all of Mill and Luffenholtz Creeks. This included an aerial photo analysis 

as well as a 100 percent survey of all roads and stream crossing sites. Grab samples 

for turbidity were collected near the mouths of Mill and Luffenholtz Creeks, as well 

as other local creeks that drain into the ASBS area or the bay, in 2006 to 2009 by 

Allan and Madrone. Grab samples for turbidity and SSC were collected in spring 

2007 by Cinnowalt and Van Matre at Site 1 on Luffenholtz Creek and downstream 

0.5 km from Site 2 on Mill Creek. Stream bank and landslide erosion inventories and 

assessments were completed in spring 2008 by Allan and Madrone, for the inner 

canyon areas on Mill and Luffenholtz Creeks. GIS mapping was completed by M. 

Lawler and included 2009 data collected by the author on timber harvest history of 

silvicultural and yarding methods, and rate of harvest, parcel boundaries, soils, 
Fine Sediment Sources in Coastal Watersheds with Uplifted Marine Terraces in Northwest 

Humboldt County, California

115

Figure 2—Road assessment sites, geology, timber harvesting (2000 to 2010). 

geology, fire history, and locations of roads and streams. Grab samples for turbidity 

and flow measurements were collected in WY 2009 by Madrone at Site 1 on 

Luffenholtz Creek, at Site 2 on Mill Creek, and at six tributary sites upstream in Mill 

and Luffenholtz Creeks. Continuous probe sensors for turbidity and stage were 

maintained at Site 1 on Luffenholtz Creek and at Site 2 on Mill Creek in the spring of 

2009. The relationship between turbidity and SSC in these 2007 samples was used to 

generate SSC for the 42 turbidity grab samples taken at Sites 1 and 2 in water year 

(WY) 2009. Suspended sediment loads were computed for three late season storms in 

WY2009 using automated turbidity data as a surrogate for suspended sediment 

concentration (SSC, mg/l) (Lewis and Eads, 2001). The storm dates (5/1 to 5/4/09, 

5/4 to 5/9/09, and 5/13 to 5/17/09) were chosen because these were the only storms 

for which both sites had reliable continuous turbidity data. 

Results

As compared to Luffenholtz Creek, Mill Creek is smaller, steeper, has more 

unstable ground and has burned more completely and more often in the past 100 

years. Mill Creek has had a higher rate of timber harvest in the past 10 years than 

Luffenholtz Creek, but in the harvested areas buffers were left along the creeks and 

the logging was completed on less erodible ground. Mill Creek was also harvested 

with less disturbing shovel-logging excavators with a loader head. Notably, Mill 
GENERAL TECHNICAL REPORT PSW-GTR-238 

116

Creek does have a lower road density and less road adjacency to streams and 

therefore less delivery potential (table 2). Swift (1988) also found that roads and skid 

trails were a major source of sediment from forestry-related activities.

Table 2—Watershed road densities. 

Luffenholtz Creek has a legacy of riparian roads with close proximity and 

thereby delivery, as well as a high road density, due in part to the dendritic nature of 

the channel network. It has also had a high rate of annual timber harvesting over the 

past 40 years, including along its streams and in the inner canyon. Harvest rates in the 

1980s and 90s averaged 4 percent per year including clear cutting with tractor

logging. The watershed with the highest rate of harvest on steep ground and the 

highest density of roads also has the higher turbidities. 

Mill Creek is nearly always less turbid than main stem Luffenholtz Creek (fig. 5).

Suspended sediment load calculations for three storms (5/1 to 5/4, 5/4 to 5/9, and 

5/13 to 5/17) in early May 2009 were 0.02 metric tons (6 x 10-5 t per ha) for Mill 

Creek and 21.29 metric tons (0.16 t per ha) for Luffenholtz Creek (figs. 3 and 4). A 

plot of normalized flows for the two main stems based on the 42 grab samples in WY 

2009 showed that flows are similar (cms per km2

) for Luffenholtz and Mill Creeks 

when normalized, but the North Fork is not similar (fig. 5). Starting with the late 

December 2008 storms, the North Fork normalized discharge regularly exceeded that 

of Luffenholtz and Mill Creeks. 

The rainy season for WY 2009 can be characterized as being 75 percent of 

normal (112.7 cm compared to the 17 year average of 150.9 cm per year at Allan’s 

gage). Rainfall was about 21 percent higher in WY 2009 at the Luffenholtz Gage for 

a total of 143.4 centimeters. There were numerous dry periods between storms, with 

the only significant rainfall events (greater than 5 cm in 24 hours) happening on 

12/28/08, 3/16/09, and 5/4/09. These events match up with the highest turbidities and 

stages recorded. Turbidities at Site 5 upstream of the 21 Rock Quarry were 

substantially lower during the first part of the season (from October 2008 through 

mid December 2008) than at the downstream Site 6 on Luffenholtz Creek. As the 

season progressed and after a large rainfall event (140 mm in 5 days) peaking on 

12/28/08 the difference in turbidities between Site 5 and 6 was decreased. The 

rainfall events of 3/16 and 5/4 did not raise turbidities at Site 6 over Site 5. During 

the rainfall event of 54 mm in 6 hours on May 4, while lower Luffenholtz, the North 

Fork, and Mill Creeks had a jump in turbidities, upper watershed Sites 4 through 8 

showed little increase in turbidity. This suggests that the upper tributary retention 

basins had begun functioning again after a dry period in April. 
Fine Sediment Sources in Coastal Watersheds with Uplifted Marine Terraces in Northwest 

Humboldt County, California

117

Figure 3—Hydrograph and turbidigraph for three storm periods, Luffenholtz Creek, 

Humboldt County, California.

Figure 4—Hydrograph and turbidigraph for three storm periods Mill Creek, Humboldt 

County, California.

Statistical analysis of turbidities from WY 2009 grab samples was completed for 

several of the sites using non-parametric tests because the turbidity data did not pass 

normality. The P-values for all sites were less than 0.05 and because the data did not 

pass normality the median value is the parameter for all tests. The analysis is 

nonparametric in that actual values were not used, just their relative rank, or position 

toward one another. Luffenholtz Creek (Site 1) was found to have significantly 

higher turbidity than Mill Creek (Site 2) and Site 5 upstream of the 21 Quarry had 

significantly higher turbidity than the downstream Site 6. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

118

Figure 5—WY 2009 Grab sample turbidity and discharge data for Main Stem 

Luffenholtz Creek vs. Main Stem Mill Creek vs. North Fork Luffenholtz Crek, 

Humboldt County, California.

Discussion

Joland Creek (South Fork Luffenholtz Creek) had the highest turbidities of all of 

the Luffenholtz Creek tributaries monitored under this study. The North Fork of 

Parker Creek and both forks of Two Creeks also had very high turbidities. These high 

turbidities may be associated with the high road densities of dirt and gravel roads 

coupled with year-round land and home site clearing activities. The results are from

grab samples taken between 2006 and 2009. None of these tributaries flow into 

Luffenholtz Creek or Mill Creek above the city’s water intakes. 

Mill Creek has steeper average slopes and greater basin relief than Luffenholtz 

Creek watershed and it has a greater percentage of its watershed in unstable geology. 

It has a higher rate of harvest during the past 10 years (44 percent for Mill vs. 20

percent for Luffenholtz), and has been burned more severely and more often, and yet 

it has lower turbidities than Luffenholtz Creek. This may be because it has a slightly 

lower density of roads per square kilometer (2.9 km per km2

 for Mill to 3.1 km km2

for Luffenholtz), has fewer total kilometers of roads (9 for Mill and 40.2 for 

Luffenholtz), has fewer kilometers of native surface roads (5.8 to 25.7), and far fewer 

erosion sites (23 to 131) and less actual past soil loss (450 m3 for Mill Creek and 

3680 m3

 for Luffenholtz Creek) (table 1). 

Recent timber yarding in Mill Creek was done with shovels (excavators), cable, 

and helicopters. These operations left substantial wildlife, vegetative, and canopy 

buffers along all perennial streams and have stayed off of the steep less stable 
Fine Sediment Sources in Coastal Watersheds with Uplifted Marine Terraces in Northwest 

Humboldt County, California

119

ground. Riparian buffer strips provide an efficient and widely accepted way to help 

protect aquatic ecosystems and downstream values from the effects of upslope landuse activities (Reid and Hilton 1998). 

Luffenholtz Creek watershed on the other hand is four times the size of Mill 

Creek and 10 times the size of the North Fork of Luffenholtz Creek (fig. 1). It had a 

higher rate of harvest than Mill Creek in the 1980s and 1990s, some of which was 

clear-cutting on steep slopes in the inner canyon and the headwaters areas, and was 

done with crawler tractors. This has left a legacy of stored sediments along floodplain 

areas in the inner canyon. These stored sediments are mobilized at bankfull events, 

which is when elevated turbidities occur. Luffenholtz Creek has several roads 

immediately adjacent to the streams. It also has more overall kilometers of roads, 

more native roads, and more kilometers of high-use rocked roads. Therefore, 

Luffenholtz Creek has much more past erosion (3680 m3

 for Luffenholtz Creek and 

450 m3 for Mill Creek) and potential erosion sites and potential erosion (131 sites for 

Luffenholz Creek and 23 at Mill Creek, and 5270 m3

 for Luffenholz Creek compared 

to 1040 m3 at Mill Creek) (table 1). Rice and Sherbin (1977) noted that when 

considering erosion hazard in northwest California the most important considerations 

probably are the yarding method used, the amount of roads, and the magnitude of 

storms actually experienced following the harvest. 

In conclusion, the data collected and analyzed for this study suggest that higher 

turbidities in Luffenholtz Creek, as compared to Mill Creek, are related to differences 

in timber harvest practices, higher road densities, more erosion-prone sites, and 

greater delivery potential. Data collected showing higher turbidities in the fall at Site 

6 as compared to Site 5 suggest that this is due to the close proximity of the road to 

the creek and that a decrease in the turbidity difference later in winter and spring was 

due to exhaustion of fines from the road. 

Data collected suggest that the lower turbidities in Mill Creek are due to lower 

road densities, low delivery potential for sediment, and improved timber harvesting 

techniques that keep heavy equipment out of riparian areas and retain substantial 

forested buffers for sediment filtering. 

References

Allan, D.; Ledwith, T. 2008. Watershed assessment action plan for the Trinidad terraces.

Redwood Community Action Agency. Eureka, CA. Available from the City of Trinidad 

and the State Water Resources Control Board. 53 p. plus maps. 

Boyd, M. 1978. California marine waters areas of special biological significance 

reconnaissance survey report: kelp beds at Trinidad Head. Water Quality 

Monitoring Report no.79-19. Available from the State Water Resources Control Board. 

35 p.

Lewis, J.; Eads, R. 2001. Turbidity threshold sampling for suspended sediment load 

estimation. In: Proceedings of the 7th Federal Interagency Sedimentation Conference, 

25-29 Mar 2001, Reno, Nevada. Pp. III-110 to III- 117.

Madrone, S. 2011. Fine sediment sources of coastal watershed with uplifted marine 

terraces in northwest Humboldt County, California. Arcata, CA: Humboldt State 

University. MS thesis. 90 p.
GENERAL TECHNICAL REPORT PSW-GTR-238 

120

Reid, L.M.; Hilton, S. 1998. Buffering the buffer. In: Ziemer, R.R., technical coordinator. 

Proceedings of the conference on coastal watersheds: the Caspar Creek story. Gen. Tech. 

Rep. PSW-GTR-168. Albany, CA: U.S. Department of Agriculture, Forest Service, 

Pacific Southwest Research Station: 71-80. 

Rice, R.M.; Sherbin, S.A. 1977. Estimating sedimentation from an erosion-hazard rating.

Research Note PSW-323. Berkeley, CA: U.S. Department of Agriculture, Forest 

Service, Pacific Southwest Forest and Range Experiment Station. 4 p. 
121

Comparison of Estimated and Measured 

Sediment Yield in the Gualala River1

 

Matthew O’Connor2, Jack Lewis3, and Robert Pennington2

Abstract

This study compares quantitative erosion rate estimates developed at different spatial and 

temporal scales. It is motivated by the need to assess potential water quality impacts of a 

proposed vineyard development project in the Gualala River watershed. Previous erosion rate 

estimates were developed using sediment source assessment techniques by the North Coast 

Regional Water Quality Control Board and by the California Geological Survey. Reported in 

this study is the estimated sediment yield under existing conditions in Soda Springs Creek 

(1.5 mi2

) based on similar, but modified, techniques. The modified technique incorporated 

elements of both prior approaches, substituting detailed data for road erosion and adding site 

specific data for landslides not previously available. This study also reports sediment yields 

determined by a suspended sediment monitoring program utilizing Turbidity-Threshold 

Sampling techniques. The monitoring program produced data relating stream turbidity, 

suspended sediment concentration, and stream discharge during Hydrologic Years (HY) 2006 

and 2007. Turbidity and streamflow data collected for HY 2008 to 2011 were used in 

conjunction with the relationship between turbidity and suspended sediment concentration 

from HY 2006 to 07 to estimate sediment yields over an additional 4 year period. Measured 

sediment yields are substantially lower than predicted by sediment source assessment 

techniques. Variation in geomorphic processes over time and space and methodological 

problems of sediment source assessments may be responsible for these apparent 

discrepancies. 

Key words: suspended sediment, erosion, water quality, mass wasting, turbidity threshold 

sampling

Introduction

Water quality in many northern California Coast Range watersheds is designated 

as “impaired” because of excessive sediment loads. Sediment source assessment 

(SSA) techniques customarily used to estimate sediment yield in this region require 

identification of erosion processes and their distribution in the watershed based on 

field observations and remote sensing data. Erosion rate and sediment delivery to 

streams are estimated by measuring soil voids such as eroded gullies and landslide 

scars and by using model algorithms for surface erosion processes and soil creep 

rates into streams. This approach has been used to estimate both current (impaired) 

and natural background erosion rates and provide the basis for determining erosion 

rates expected in a restored watershed. Erosion rates are equated with sediment yield 

on the assumption that over the long-term they should be in equilibrium. However, 

time spans required for such equilibrium are unknown and may be many decades. 

 

1 An abbreviated version of this paper was presented at the redwood science symposium, UC Santa 

Cruz, June 21-23, 2011. 2 O’Connor Environmental, Inc., POB 794, Healdsburg, CA 95448.

3 Hydrologic Statistician, 647 Elizabeth Drive, Arcata, CA 95521.
GENERAL TECHNICAL REPORT PSW-GTR-238 

122

Validation of these estimates can be accomplished by direct measurements of 

sediment yield.

The Gualala River is listed as having sediment-impaired water quality per 

provisions of the Clean Water Act Section 303(d).The Gualala River watershed (fig. 

1) is underlain by Jurassic age sedimentary and meta-sedimentary rocks of the 

Franciscan assemblage. The San Andreas Fault passes through the western edge of 

watershed. A substantial portion of the watershed is mantled by active and dormant 

rock slides and earthflows. The Coast Range is geologically young, and rapid rates of 

uplift are believed to have contributed to high erosion rates. Watershed studies by the 

State of California (Klamt et al. 2002) found that historic landscape disturbance 

caused by logging was severe, and that a trend toward watershed recovery was 

evident. 

Four sub-watersheds located in northwest Sonoma County (fig. 1) have been 

investigated using SSA techniques and the turbidity threshold sampling (TTS) 

program to measure sediment yield (OEI 2008). Findings for Soda Springs Creek are 

representative of the three other sites, which are excluded from this report for brevity. 

Figure 1—Location map. Figure 2—Study area attributes. “Project” 

and “CGS” refer to source for landslide data.

Methods

Prior sediment yield estimates were developed using SSA techniques for 

drainage areas of about 50 mi2 by the North Coast Regional Water Quality Control 

Board (NCRWQCB 2001) in the Gualala River Watershed Technical Support 

Document for Sediment (TSD) and by the California Geological Survey (CGS) for an 

area of 298 mi2 (Fuller and Custis 2002). The TSD provided estimates of sediment 

delivery rates to streams from both natural and anthropogenic sources. The CGS 

study focused on estimating background (“natural”) erosion rates associated with 

accelerated soil creep rates to streams adjacent to large rock slides and earthflows. 

Techniques in this analysis incorporate aspects of the NCRWQCB and CGS methods 

to estimate sediment yield under existing conditions in four small watersheds (1.2 to 

3.1 mi2

, fig.1).We substituted detailed local data on road erosion from field surveys, 
Comparison of Estimated and Measured Sediment Yield in the Gualala River

123

utilized a more detailed map of the stream network developed from field 

observations, and we added site specific data for landslides collected during field 

surveys of the project area.

Suspended sediment monitoring using the TTS system (Eads and Lewis 2002) 

was implemented in late 2005 with assistance from RiverMetrics LLC (Rand Eads, 

formerly of USDA Forest Service Redwood Sciences Lab).This program was 

conducted to validate sediment yield estimates based on sediment source assessment 

techniques and to establish baseline water quality and streamflow conditions. The 

initial analysis of TTS data for HY 2006 to 07 estimated annual suspended sediment 

yield (SSY) based on the regression relationships between turbidity-suspended 

sediment concentration (SSC) data pooled for each year (Eads 2007). A supplemental 

analysis of these data was based on regression relationships between turbidity and 

SSC on a storm-by-storm basis (Lewis 2009). In this study, we utilized a regression 

relationship between turbidity and SSC for pooled data from Soda Springs Creek for 

HY 2006 and 2007 to estimate SSY for HY 2008 through HY 2011 using turbidity 

and discharge data. 

Sediment source assessment 

Sediment sources were classified as background (natural) sources or 

anthropogenic (management-caused) sources. Background sources were comprised 

of three elements: rockslide and earthflow soil creep, bank erosion, and “natural” 

landslides (table 1). Anthropogenic sources were comprised of two elements: roadrelated erosion (including landslides) and erosion from skid-trails and log landings.

Rock slide and earthflow soil creep rates were estimated based on interpretation 

of literature data (Fuller and Custis 2002). They presented low- and high-range creep 

rate estimates. These soil creep rates to stream channels were differentiated based on 

the style of mass wasting and the activity class of the mass wasting feature (table 2). 

Additional data regarding the location and type of landslides (Kleinfelder 2008)

supplemented existing data (Fuller and Custis 2002). Sediment delivery from soil 

creep was calculated as the product of two (representing two stream banks), average 

bank height of 3.3 ft (consistent with field observations), and stream length 

intersecting active and dormant mass wasting features (table 2) as determined from a 

GIS database. 

Considering uncertainty of methods and assumptions, presenting erosion rate 

estimates as a range of values maintains an additional measure of caution with 

respect to interpretation and use of the estimates. In this study, we present sediment 
GENERAL TECHNICAL REPORT PSW-GTR-238 

124

yield estimates as a range of values where possible. Low- and high-range rates were 

calculated for landslide soil creep per table 2. 

Methods for estimating road erosion rates used by Pacific Watershed Associates 

(PWA) for the project area and for TSD field sites were similar. However, project 

area data are based on direct field observations of 37 miles of project area roads 

(PWA 2005a, 2005b), whereas the TSD estimates are based on a smaller sample of 

field plots supplemented by aerial photo interpretation. The mean historic road 

erosion rate estimated for the project area over the past 30 years was 85 t/mi/yr. The 

estimated sediment yield from existing roads in Soda Springs Creek is the product of 

historic erosion rate and road length (fig. 2).The TSD estimate is comprised of mass 

wasting (landslides), stream crossing failures, gullying and surface erosion, and is 

estimated to be 920 t/mi2

/yr. TSD-estimated sediment delivery from roads for Soda 

Springs Creek is a function of watershed area. Low-range rates of road-related 

erosion were those estimated from field surveys in the study area; high-range rates of 

road erosion were those estimated in the TSD.

Sediment yield measurement by TTS 

Hydrologic data used to estimate sediment loads were collected through use of 

the TTS system developed at the Redwood Sciences Laboratory (RSL), a field office 

of the USDA Forest Service, Pacific Southwest Research Station (Eads and Lewis 

2002). “TTS was designed to permit accurate determination of suspended sediment 

loads by establishing a relation between SSC and turbidity for each sampling period 

with significant sediment transport. It does so by collecting pumped suspended 

sediment samples when pre-selected turbidity conditions, or thresholds, are satisfied. 

During analysis the relations are applied to the nearly continuous turbidity data for 

the respective sampling periods to produce a continuous record of estimated SSC. 

The product of discharge and estimated SSC is then integrated to obtain accurate 

suspended sediment yields.” 

Data collection began in mid-December 2005 at Soda Springs Creek. Full 

implementation of TTS with SSC sampling continued through May of 2007.The 

number of samples processed was 285 in HY 2006 and 161 in HY 2007.Continuous 

stage and turbidity are still being measured using the TTS program as of June 2011, 

however SSC sampling was discontinued after HY 2007. 
Comparison of Estimated and Measured Sediment Yield in the Gualala River

125

Data processing and sediment load estimation procedures 

Sediment loads for Soda Springs Creek have been estimated for HY 2006 to HY 

2011 using TTS analysis procedures (Lewis and Eads 2009).Raw stage and turbidity 

data were compiled and adjusted using the TTS Adjuster software developed by the 

USDA Forest Service Redwood Sciences Laboratory4

. Adjusted stage values were 

used to estimate instantaneous discharge, and adjusted turbidity was used as a 

surrogate for SSC. Discharge is multiplied by SSC to compute sediment yield for 

each data interval (10 minutes) and summed to estimate the sediment yield for any 

given period. For HY 2006 to HY 2010 turbidity was the only SSC surrogate used. 

During HY 2011 there were some periods with questionable turbidity data related to 

fouling of the turbidity sensor. For these periods, flow was used as a surrogate for 

SSC. Stage-discharge relationships (rating curves) for HY 2006 and 2007 are the 

same equations used by Lewis (2009).The rating curve for HY 2008 to HY 2011 

represents the most up to date stage discharge relationship as of June 2011. 

Annual sediment loads were calculated with R software according to TTS 

procedures (Lewis and Eads 2009). Sediment loads were estimated using four 

different regression relationships of SSC on turbidity: 1) simple linear regression: y = 

ax + b, 2) simple linear regression on the natural logarithms of both variables5

: log 

(y) = a + b log (x), 3) power function: y = axb, 4) loess (non-parametric locallyweighted) regression (Cleveland and Devlin. 1988). Each of these models was fitted 

to three different data sets: HY 2006 only, HY 2007 only, and HY 2006-2007 pooled. 

The resulting 12 sediment load estimates for each year provide an indication of the 

uncertainty associated with model selection and interannual sampling variability. 

Results

Sediment source assessment 

Sediment yield estimates for Soda Springs Creek (sub-watershed of Buckeye 

Creek) from this analysis (Project) are compared with sediment yield estimates from 

CGS and the TSD (table 3). CGS estimates only the natural background rate 

associated with soil creep. Nevertheless, the CGS upper range estimate (3,019 

t/mi2

/yr) is about twice the TSD and Project (upper range) estimates of 1,400 t/mi2/yr 

and 1,688 t/mi2

/yr, respectively. The CGS low-range estimate (994 t/mi2/yr) is 71 

percent of the TSD estimate and 59 percent of the low range estimate for the Project 

(1,168 t/mi2

/yr). 

Comparison between estimates from the TSD and the Project are more relevant 

given the comprehensive scope and spatial scale of erosion processes considered. The 

Project estimate is based on some of the same rate estimates used in the TSD. The 

TSD natural mass wasting rate (170 t/mi2

/yr) is added to rock slide/earthflow creep 

calculated for the Project. The high range road estimate and the skid trail/timber rate 

for the Project are from the TSD estimates for Buckeye Creek.

 

4 http://www.fs.fed.us/psw/topics/water/tts/adjuster/AdjusterManual.html. 5 In this analysis, all logarithms are natural logarithms (base e = 2.718282).The bias of retransformation, 

i.e., that introduced when transforming log(y) to y, was corrected using the minimum variance unbiased 

estimator (Cohn et al 1989).
GENERAL TECHNICAL REPORT PSW-GTR-238 

126

The Project low-range and high-range estimates are 83 and 121 percent of the 

Buckeye Creek estimates, respectively. The range of natural background sediment 

yield estimated for the Project is greater than that estimated by the TSD, 454 to 648 

t/mi2

/yr versus 360 t/mi2/yr. The range of natural background sediment yield for the 

Project (Soda Springs Creek) is 126 to 180 percent of that estimated by the TSD for 

Buckeye Creek.

Measured sediment yield

Turbidity and SSC data were closely correlated and least-squares fits to the data 

(e.g., fig. 3) were strikingly similar in HY 2006 and 2007.The coefficient of 

determination (r2) for all models and all data sets is relatively high, ranging from 

0.88 to 0.96.For models fitted to the pooled data, r2 ranged from 0.90 to 0.92. 

While an unknown error is introduced in using HY 2006-2007 data to estimate 

sediment yields for HY 2008 to 2011, the likely magnitude of that error appears to be 

small. The HY 2006 relationship produced mean annual sediment yield ranging from 

186 to 218 t/mi2

/yr, while the HY 2007 relationship produced only slightly higher 

mean annual sediment yields ranging from 192 to 219 t/mi2

/yr. The loess model (r2 = 

0.92) produced the lowest estimates and the power model (r2 = 0.91) the highest. The 

model based on the relationship for pooled data gave mean annual sediment yield 

ranging from 194 to 216 t/mi2

/yr.
Comparison of Estimated and Measured Sediment Yield in the Gualala River

127

Sediment yield (fig. 4) measured in HY 2006 is by far the greatest during the 

period of record, ranging from about 620 to 710 t/mi2

/yr. The lowest sediment yield, 

about 30 t/mi2

/yr, was measured in HY 2009. 

Figure 4—Sediment yield estimates based on HY 2006-07 pooled data regressions.

Discussion

SSA yield estimates substantially exceed measured SSY for Soda Springs Creek. 

In HY 2006, measured sediment yield (about 620 to 710 t/mi2

/yr) represents about 

one-half that estimated by the TSD6

. The HY 2006 measured sediment yield is 37 to 

61 percent of estimated yield from the Project SSA (table 3). In subsequent years, 

measured yield is about ten percent of yields predicted by SSA. The difference 

between SSA-predicted yield and measured SSY is considerably less than the 

magnitude of uncertainty in measured SSY attributable to sampling and modeling 

error hypothesized above.

Part of the discrepancy between predicted and observed sediment yield is 

attributable to unmeasured bedload sediment transport. Bedload (typically sand and 

gravel) is transported infrequently and over short distances relative to suspended 

sediment load. The TTS method does not account for bedload sediment. The 

magnitude of bedload sediment yield can be estimated using regional ratios of 

bedload to suspended load. Bedload and SSY have been estimated for North Fork 

Caspar Creek (1.8 mi2

), a watershed with geologic and hydrologic characteristics 

similar to Soda Springs Creek. Estimates of the ratio of bedload to suspended load 

range from 15:85 (Napolitano 1996) to 30:70 (Cafferata and Spittler 1998). Based on 

these ratios, total sediment yield would be about 18 to 43 percent greater than SSY. 

Total sediment yield for HY 2006 would range from about 730 to 1,020 t/mi2

/yr, a 

rate that approaches the low-range prediction for Soda Springs Creek (table 3). 

Adjusted for unmeasured bedload transport, mean annual sediment yield for HY 

2006 to 2011 ranges from 229 to 308 t/mi2

/yr. Unmeasured bedload does not appear 

 

6

A portion of HY 2006 (October, November and early December 2005) was unmeasured as monitoring 

stations were being installed, hence the sediment yield measured for HY 2006 is an underestimate.

However, the unmeasured flows represent less than ten percent of flow recorded in that year based on 

comparison with other regional data.

 
GENERAL TECHNICAL REPORT PSW-GTR-238 

128

to be great enough to account for the discrepancy between measured yields and those 

estimated by sediment source methods.

SSA methods rely on numerous assumptions to develop quantitative estimates of 

erosion and sediment delivery rates. Field measurements of landslide scarps and 

gullies can be made with reasonable accuracy, however, the timing of erosion and the 

proportion of soil delivered to a stream from a source is difficult to determine. Soil 

creep rates estimated from literature values may represent average conditions, but 

variability related to geologic conditions and climate is complex. Eroded sediment 

may be temporarily deposited on hillslopes, in stream channels, and on alluvial fans, 

awaiting geomorphic events capable of remobilizing it. Erosion processes are 

episodic, with periods of quiescence punctuated by extreme events associated with 

large storms and floods in the California Coast Range. Hence it is not surprising that 

estimates of sediment yield from source assessment methods could diverge from 

measured sediment yields.

Conclusion

Sediment source assessment methods that estimate mean annual sediment yield 

do not always provide accurate estimates of actual sediment yields, nor do they 

account for inter-annual variability related to climate conditions. Measurement of 

sediment yield using TTS methods allows for validation of sediment source 

assessments and provides an alternative means of evaluating watershed sediment 

yield. Field studies involving more direct measurement of erosion and sediment 

transport processes appear to be required to validate sediment source assessments.

References

Cafferata, P.; Spittler, T. 1998. Logging impacts of the 1970's vs. the 1990's in the Caspar 

Creek watershed. In: Ziemer, R., technical coordinator. Proceedings of the conference 

on coastal watersheds: the Caspar Creek story. Gen. Tech. Rep. PSW-GTR-168. Albany, 

CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research 

Station: 103-116. 

Cleveland, W.S.; Devlin, S.J. 1988. Locally-weighted regression: an approach to 

regression analysis by local fitting. Journal of the American Statistical Association 83: 

596-610.

Eads, R. 2007. Preservation Ranch suspended sediment load analysis for Buckeye, 

Franchini, Soda, and South Fork Fuller Creek-Hydrologic years 2006-2007. 

RiverMetrics LLC. Prepared for O'Connor Environmental, Inc., Healdsburg, CA. 41 p. 

Eads, R.; Lewis, J. 2002. Continuous turbidity monitoring in streams of northwestern 

California. In: Glysson, G.; Gray, J., editors. Proceedings of the federal interagency 

workshop on turbidity and other sediment surrogates. Reno, NV: U.S. Geological 

Survey. 3 p.

Fuller, M.;Custis, K. 2002. Geology and geomorphology for Gualala River watershed 

assessment. Department of Conservation, California Geological Survey. CD2002-08.

Klamt, R.R.; LeDoux-Bloom, C.; et al. 2002. Gualala River watershed assessment report. 

Sacramento, CA: North Coast Watershed Assessment Program. California Resources 

Agency and California Environmental Protection Agency. 367 p.
Comparison of Estimated and Measured Sediment Yield in the Gualala River

129

Kleinfelder, Inc. 2008. Landslide hazard evaluation, Preservation Ranch, northwest 

Sonoma County, California. Report prepared for Preservation Ranch.18 p. . 

Lewis, J. 2009. Evaluation of baseline data for Preservation Ranch conversion project: 

storm suspended sediment, peak flow, flow volume, and turbidity-hydrologic years 

2006-2007. Prepared for O’Connor Environmental Inc. Healdsburg, CA. 61 p.

Lewis, J.L.; Eads, R.D. 2009. Implementation guide for turbidity threshold sampling: 

principles, procedures, and analysis. Gen. Tech. Rep. PSW-GTR-212. Arcata, CA: 

U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station. 87 

p.

Napolitano, M.B. 1996. Sediment transport and storage in North Fork Caspar Creek, 

Mendocino County, California: water years 1980-1988. Arcata, CA: Humboldt State 

University. M.S. thesis. 148 p. 

NCRWQCB. 2001. Gualala River watershed technical support document for sediment. 

North Coast Regional Water Quality Contrrol Board, Santa Rosa, CA. 138 p. 

O'Connor Environmental, Inc. 2008. Preservation ranch sediment source assessment and 

evaluation of project effects. Prepared in association with Kleinfelder. 71 p.

Pacific Watershed Associates (PWA). 2005a. Draft summary report, phase 1 mainline 

road inventory and upgrading plan, Preservation Ranch, Gualala River 

Watershed. Prepared for Winzler & Kelly Consulting Engineers, Eureka, CA. 56 p.

Pacific Watershed Associates (PWA). 2005b. Phase 2 road inventory and upgrading plan, 

Presevation Ranch, Gualala River Watershed. Prepared for Winzler & Kelly 

Consulting Engineers, Eureka, CA. 106 p. 

Parrett, C.; Hunrichs, R. 2006. Storms and flooding in California in December 2005 and 

January 2006--a preliminary assessment. US Geological Survey. Open File Report 

2006-1182: 8.

131

Fluorometry as a Bacterial Source Tracking 

Tool in Coastal Watersheds, Trinidad, CA1

Trever Parker2 and Andrew Stubblefield3

Abstract 

Bacterial counts have long been used as indicators of water pollution that may affect public 

health. By themselves, bacteria are indicators only and can not be used to identify the source

of the pollutant for remediation efforts. Methods of microbial source tracking are generally 

time consuming, labor intensive and expensive. As an alternative, a fluorometer can be used 

to measure fluorescence in natural creeks as an indicator of concentrations of optical 

brighteners found in laundry detergent. In this way, fluorescence can be used as a tool for 

identifying failing or malfunctioning onsite wastewater treatment systems. Fluorometry was 

used in watersheds draining into northern California’s Trinidad Bay in Humboldt County, in 

conjunction with bacterial sampling and measurement of rainfall and turbidity for correlation 

and comparison. Results showed that optical brighteners, when coupled with rainfall and 

turbidity data, can accurately predict whether bacterial standards will be exceeded within 

individual watersheds. Fluorescence of optical brighteners was also shown to be a useful tool 

for discerning the most impacted watersheds and tributaries for more detailed investigation of 

individual bacterial pollution sources. 

Key words: bacteria, fluorometer, optical brighteners, septic, source tracking, wastewater

Introduction

Four types of bacteria are routinely used to assess and regulate water quality in 

terms of human health: total coliforms, fecal coliforms (a subgroup of coliforms), 

Escherichia coli (a specific fecal coliform) and Enterococcus. These bacteria types 

are found in fecal matter, in the presence of enteric pathogens, they have good 

survivability in the environment, and are relatively easy to isolate and identify 

(McCorquodale et al. 1996). Current methods of bacterial testing take 24 to 48 hours 

to resolve, which is problematic for posting and removing public health warnings in a 

timely manner (Ely 2006). It is also impossible to determine the source of pollution 

using just the Most Probable Number (MPN) of the indicator bacteria that most tests 

provide. Human fecal contamination poses the greatest threat to public health 

because the associated pathogens are more transmittable. Because the indicators are 

found in the environment and in the feces of other warm blooded animals, the human 

health threat is not known even when their numbers are high. 

In order to implement actions to improve water quality, the specific source (e.g. 

pets, livestock, septic systems) and its location, need to be identified. Source tracking 

is the term for a process used to identify the origin of fecal contamination in water. 

Unfortunately, most methods currently in use tend to be time consuming, expensive 

 

1 This article has been adapted from the thesis of the same title by T.A. Parker, presented May 2011, 

Humboldt State University, Arcata, CA 95521. 2 Streamline Planning Consultants, Arcata, CA 95521. 3 Dept. of Forestry, Humboldt State University, Arcata, CA 95521. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

132

and / or unreliable and are not practical for small government jurisdictions or 

volunteer groups to use (Stoeckle 2005). Optical brighteners (OBs) are an emerging 

chemical method of source tracking human bacterial pollution from septic systems. 

These organic compounds are added to laundry detergents and other products where 

they absorb UV light and re-emit that energy in the visible blue spectrum. When 

added to white textiles, or paper, it makes the objects appear less yellow and more 

blue, giving them a ‘whiter’ appearance (Hagedorn et al. 2005). OBs are added to 97 

percent of detergents sold in the U.S. Because OBs are readily adsorbed to particles, 

including soil, a properly functioning onsite wastewater treatment system (OWTS), 

or septic system, should remove nearly 100 percent of any OBs discharged to the 

system (Dates 1999). In addition, OBs do not readily biodegrade in the environment, 

unless they are exposed to sunlight (Hagedorn et al. 2005). Recent studies (e.g. 

Hagedorn et al. 2003, Hartel et al. 2007) show that monitoring OBs with a 

fluorometer holds promise as a relatively inexpensive source tracking method for 

suspected bacterial pollution of septic origin (Hartel et al. 2008). 

The first goal of this study was to test the viability of using a fluorometer to 

detect the presence of OBs to confirm and track OWTS pollution in the greater 

Trinidad area; consideration was given to both spatial and temporal patterns. The 

fluorometer was used as a source tracking tool both to confirm anthropogenic sources 

of bacterial pollution and to identify and prioritize areas contributing the greatest 

amount of bacteria. The second goal of this study was to evaluate the effectiveness of 

this relatively new, cheap and quick method of identifying and locating human 

sources of bacterial pollution that can be used by even small municipalities and 

volunteer monitoring groups and to provide recommendations for its use. 

Study area

This study took place in and around the City of Trinidad in Humboldt County, 

California (fig. 1). The study area consists of a pre-defined project area related to 

water quality and watershed management / planning grants received by the City of 

Trinidad. The entire area consists of seven watersheds, four of which were utilized in 

this study – Mill, Parker, Luffenholtz and Joland Creeks – as well as beach and seep 

samples. The entire planning area contains a total of 6,498 acres and 32.7 miles of 

stream. This area is characterized by heavily wooded, steep slopes, particularly near 

stream channels and ocean bluffs, interspersed with flatter plateaus. Baseline water 

quality monitoring efforts have shown periodic, widespread bacterial contamination 

as high as 60 times, or 6000 percent of the State’s contact recreational standards4

. 

The major land uses in the study area are timber production and rural residential. 

Much of the lower watersheds consist of residential development with small pockets 

of commercial and public land, and the upper watersheds are all commercial 

timberland. The residential development is concentrated around the communities of 

Trinidad and Westhaven. All residences in the study area utilize onsite wastewater 

treatment systems (OWTS), including septic systems, to dispose of wastewater (fig. 

 

4 Parker, T. 2008. Trinidad-Westhaven coastal watershed program: preliminary watershed 

assessment. Unpublished report, prepared as part of the requirements for a Proposition 50 Watershed 

Planning Grant from the State Water Resources Control Board to the city of Trinidad. City of Trinidad, 

Trinidad, CA. 
Fluorometry as a Bacterial Source Tracking Tool in Coastal Watersheds, Trinidad, CA

133

Figure 1—Project location and vicinity.

Figure 2—Permit data gathered from the Humboldt County Division of Environmental 

Health showing age of OWTS or lack of permit data, Trinidad, CA.
GENERAL TECHNICAL REPORT PSW-GTR-238 

134

2). There are approximately 1,000 developed parcels in the study area. Many are less 

than 1⁄4 acre in size, much smaller than current regulations require for use of an 

OWTS. Most of these parcels were created and developed prior to current regulatory 

standards (fig. 3), and therefore the OWTS are often unpermitted (built prior to 

permit requirements) or otherwise do not meet current requirements (City of Trinidad 

2010). 

Figure 3—Percentages of OWTS by age in (from left to right, top to bottom) Mill, 

Parker, Luffenholtz and Joland Creeks watersheds. ‘Unknown’ indicates there is no 

file information for those parcels, which means they were installed prior to 1970 or 

without permits.

Materials and methods

For this study we used an AquafluorTM handheld fluorometer and turbidimeter 

(Turner Designs, Sunnyvale, CA). The UV-445 wavelength filter was chosen based 

on the recommendation that it is the most ideal setting (available) for detecting OBs 

while eliminating other sources of fluorescence such as hydrocarbons and organic 

matter (Hartel et al. 2007, Turner Designs 2007). 

Samples were taken from five different watersheds: beach/seeps, Mill Creek, 

Parker Creek, Luffenholtz Creek and Joland Creek, on 18 different dates starting on 

September 17, 2008 and ending April 15, 2010 (fig. 4). Samples were taken at 

various times and locations with varying weather, seasons and conditions in an 

attempt to get a broad view of data patterns. Field crews started at the mouth of the 

creeks, or another easily identifiable starting point such as a culvert. Samples were 

taken approximately every 100 feet upstream, and also at tributaries and other inlets. 

Bacterial tests included total coliform, E. coli and Enterococcus. Daily rainfall was 

collected from records at the city’s water plant. 
Fluorometry as a Bacterial Source Tracking Tool in Coastal Watersheds, Trinidad, CA

135

Figure 4—Sampling locations and transects in this study, Trinidad, CA.

All calibrations, sampling, testing and data management occurred according to a 

quality assurance project plan prepared in accordance with State Water Quality 

Control Board guidelines. The fluorometer was calibrated with Tide liquid detergent 

and distilled water. Samples were taken in accordance with Standard Operating 

Procedures. Measurements for OBs were taken in the field according to the 

manufacturer’s instructions. Turbidity readings were taken immediately following the 

fluorescence reading for most samples. Bacteria samples were also taken at the same 

time and delivered to the Humboldt County Public Health Lab. 

Data recorded were as follows: sample point identification, watershed, date, OB 

first reading, OB second reading, total coliform, E. coli, Enterococcus, turbidity, 

rainfall in the past 24 hours, rainfall in the past 3 days (72 hours), rainfall in the past 

2 to 3 days (24 to 72 hours) and rainfall in the past week. In addition to the directly 

sampled data, several derived data categories were utilized. This included the 

difference between the first and a second OB reading (called ‘difference’) and

whether the bacterial results were in exceedance of the state contact recreational 

standards. 

Results

The results showed consistent patterns between sampling events and watersheds 

with each watershed having a consistent raking for each of the water quality 

parameters tested (table 1). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

136

Table 1—Median values of variables and their ranks of all data sampled between September 

17, 2008 and April 15, 2010 from five watersheds, Trinidad, CA. 

WatershedOptical 

Brighteners

Total

Coliform E. coli

Enterococcus Turbidity

Med. Rank Med. Rank Med. Rank Med. Rank Med. Rank

Beach 1.1 5 31 5 1 5 1 5

Mill 8.0 4 424 4 10 3 6 4

Parker 17.0 1 1935 1 31 1 121 1 50.8 1

Luffenholtz 12.6 2 504 3 20 2 41 2 23.6 2

Joland 8.6 3 697 2 10 3 20 3 20.5 3

The most promising statistical results were obtained using logistic regressions to 

predict if bacterial counts would exceed state standards for contact recreation using 

OBs, rainfall and turbidity as the independent variables (table 2). The bacterial 

standards are as follows: total coliform 10,000 MPN/100 ml; E. coli 400 MPN/100 

ml; and Enterococcus 104 MPN/100 ml. These regressions were run with all the data 

together, starting with the following independent variables – OBs, difference, 

turbidity, rain 1-day and rain 2-3 days. Total coliform and E. coli could not be 

analyzed, because there were too few bacterial exceedances. For the same reason, 

logistic regression could not be used on the data for each individual watershed. 

Table 2—Result of logistic regression analysis for the aggregated data from five watersheds 

in Trinidad, CA sampled between September 17, 2008 and April 15, 2010. 

Independent 

Variables

Exceedances 

Correctly 

Classified

Nonexceedances 

Correctly 

Classified Model

OB 1sta, 

Difference, 

Turbidity, Rain 1-

day, Rain 2-3 days 82.4% 96.1%

0.860 - 0.237*Diff + 0.219*OB_1st -

2.14*Rain_1_day + 

1.22*Rain_2_3_days - 

0.0536*Turbidity

OB 1st, Turbidity, 

Rain 1-day, Rain 

2-3 days 82.4% 96.1%

0.917 + 0.215*OB_1st -

2.13*Rain_1_day + 

1.23*Rain_2_3_days - 

0.0536*Turbidity

OB 1st, Turbidity, 

Rain 1-day 76.5% 96.1%

1.73 + 0.194*OB_1st -

2.03*Rain_1_day - 0.0508*Turbidity

Turbidity, Rain 1-

day 61.8% 98.0%

3.33 - 0.831*Rain_1_day -

0.0486*Turbidity

Turbidity 58.8% 98.0% 2.92 - 0.0494*Turbidity

OB 1st 38.6% 83.6% 2.80 - 0.170*OB_1st a OB 1st refers to the first optical brightener or fluorescence reading.

Linear regressions between OBs and the three different bacteria measurements 

essentially showed no direct relationship. Multiple regression was more successful. 

Based on the results of variable selection routines performed, three of the variables 

were consistently the best predictors of bacteria, are easy to collect, and provide good 

power for the multiple regression models: OBs, turbidity and rain 1-day (24 hours). 

We used these three variables as independent variables in multiple regressions 

against each of the three bacterial variables for each watershed with good predictive 

results (table 3). We did not run this analysis for the beach / seep dataset due to the 

lack of both turbidity readings and rainfall. For Mill Creek we used only OBs and 
Fluorometry as a Bacterial Source Tracking Tool in Coastal Watersheds, Trinidad, CA

137

rain 1-day since there were no turbidity samples taken.

Table 3—Results of multiple regression analysis from four watersheds in Trinidad, CA 

sampled between September 17, 2008 and April 15, 2010.

Mill Creek Model r

2

Total coliform 104.5+ 40.5*OB_1sta+ 28,681.6*Rain_1_day 0.83

E. coli 0.33+ 0.67*OB_1st+ 345.6*Rain_1_day 0.77

Enterococcus -53.5+ 6.83*OB_1st+ 2,493.2*Rain_1_day 0.80

Parker Creek

Total coliform

1,393.9-56.6*OB_1st+ 527.1*Rain_1_day+ 

9.87*Turbidity 0.48

E. coli -39.4+ 1.28*OB_1st+ 41.8*Rain_1_day+ 0.78*Turbidity 0.78

Enterococcus 1.41-0.30*OB_1st+ 116.5*Rain_1_day+ 0.82*Turbidity 0.71

Luffenholtz Creek

Total coliform NA

E. coli 12.9-6.74*OB_1st+ 66.5*Rain_1_day+ 2.41*Turbidity 0.59

Enterococcus 46.2-25.2*OB_1st+ 220.6*Rain_1_day+ 7.62*Turbidity 0.68

Joland Creek

Total coliform

4,687.9-773.1*OB_1st+ 5,109.6*Rain_1_day+ 

106.9*Turbidity 0.84

E. coli

-184.6+ 27.1*OB_1st+ 648.3*Rain_1_day2.89*Turbidity 0.91

Enterococcus

-92.2+ 7.57*OB_1st+ 836.1*Rain_1_day+ 

0.27*Turbidity 0.88 a Refers to the first reading of optical brighteners / fluorescence

We graphed the sample results from the longitudinal stream profiles to provide 

visual clues as to pollution sources within the watersheds. The following chart (fig. 5) 

is one selected example (out of a total of 10 transects). Regardless of the statistical 

relationships between the variables, these transects may provide a more reliable 

analog for what is actually happening in the environment. They remove the influence 

of rainfall, because each transect was taken on a single day under the same 

conditions. Anomalous points can be looked up in the field notebook for clues as to 

what is causing the 

differences.
GENERAL TECHNICAL REPORT PSW-GTR-238 

138

1

10

100

1000

10000

100000

2500 2600 2700 2800 2900 3000 3100 3200 3300 3400

Distance Upstream from Mouth (ft)

Bacteria (MPN/100ml)

0

5

10

15

20

25

30

35

Fluorescence (ppm)

Total coliform

E. coli

Enterococcus

Fluorescence

 

Figure 5—Upstream transect on Mill Creek showing longitudinal trends. These 

samples were taken on 11/17/08 with 0.0 in of rainfall in the previous three days. 

Note that points without lines indicate seeps or tributaries draining into the main 

channel.

Discussion

When OBs were included with rainfall and turbidity as independent variables in 

multiple or logistic regressions with the bacteria indicators the results showed strong 

predictive value. The logistic regression analysis showed that these variables can be 

used to predict exceedances of bacteriological standards (table 2). Multiple 

regression was improved when the data was analyzed separately for each watershed 

(table 3). These results could be used to protect public health by allowing warnings 

on beaches to be posted immediately after rainfall.

Patterns of OBs and bacteria were consistent with expected priority areas based 

on land use and watershed characteristics. The results of this study showed that each 

creek had consistent rankings when considering the median values of each variable 

(table 1). These rankings can be explained by the land use characteristics of each 

watershed. For example, of the four creeks, Mill had the lowest medians. The upper 

and lower portions of the Mill Creek watershed are mostly undeveloped timber and 

park land. It also has a high percentage of undeveloped and open space land, large 

residential lot sizes and, maybe most importantly, the lowest percentage of old and 

unpermitted onsite OWTS (fig. 3). Similarly, Parker Creek had by far the highest 

median values and also has the greatest percentage of old and unpermitted OWTS 

(fig. 3). Parker Creek is also densely developed with a high percentage of impervious 

surfaces and the greatest diversity of land uses. These correlations are strong 

indicators that the pollution is in fact coming from failing or poorly functioning 

OWTS. Similar to this study, Hartel et al. (2007) consistently showed high 

fluorescence and high bacteria when the source was human/residential.

Based on past water sampling results, it was known that higher bacteria counts 

occur after rain, particularly if there was some prior dry weather. This study 

confirmed that both bacteria and OBs were influenced by rainfall. Rainfall in the 
Fluorometry as a Bacterial Source Tracking Tool in Coastal Watersheds, Trinidad, CA

139

previous day (24 hours) was the best predictor of bacteria counts. Rainfall in the 

previous 2 to 3 days (24 to 72 hours) was also a useful predictor as was turbidity. 

However, rainfall also increases the amount of turbidity and organic matter in the 

water. Since organic matter fluoresces and can interfere with OB readings (Hartel et 

al. 2007) it may be beneficial to conduct fluorometry based source tracking during 

summer low-flow periods. Unfortunately, our study found that there was a lack of 

variability in bacteria counts during low-flow periods, possibly because the samples 

were diluted at a ratio of one to ten in order to pick up the higher bacteria counts, 

which are of greatest concern and interest. 

The longitudinal creek profiles may provide the best information for source 

tracking individual failing OWTS or at least the worst contributing neighborhoods or 

subwatershed. Figures 5 and 6 show points that form peaks or valleys for one or 

more constituents. The points can be identified in the graphing program, and then 

looked up in the field notebook for further information and / or investigated in more 

detail in the field. Some generalizations can be made when looking at the 

longitudinal profile data. Points with high levels of bacteria and OBs should be 

considered priority areas for further investigation of OWTS failures. High bacterial 

readings with low OBs could either indicate animal sources of bacteria, or an OWTS 

source that lacks laundry capabilities. High OBs with low bacteria likely indicate a 

greywater source, or a high concentration of organic matter.

The Mill Creek transect (fig. 5) shows sharp spikes of both bacteria and 

fluorescence in tributaries at 2700 and 3300 ft. The high point at 2700 ft was 

associated with a seep draining into the creek from an area occupied by an illegal 

settlement of trailers. Since the time these samples were taken, the County Division 

of Environmental Health investigated and condemned the site partially based on 

inadequate sewage disposal. The high point at 3300 ft was taken from a small 

tributary draining into the main channel at that location. This tributary drains a small 

residential neighborhood that would be a good candidate for further investigation. 

This study helped confirm that OWTS are the cause of bacterial contamination in 

the study area creeks. This study also showed that a fluorometer was a viable tool in 

an easy to use form over a wide variety of conditions that is applicable to other 

government jurisdictions and non-profit organizations that are involved in water 

quality monitoring, but that do not have the funds for traditional bacterial source 

tracking. One of the important things this study showed was that the results are much 

more accurate when considered within a single watershed rather than the entire study 

area. OBs can provide a quick, cheap and easy method to help characterize different 

watersheds and to prioritize areas for further investigation and remediation that are 

contributing the most pollution. Other variables do have to be considered, including

the natural variability of the system, seasonality and rainfall.

References

City of Trinidad. 2010. City of Trinidad geographic information systems files. Maintained 

by Streamline Planning Consultants, 1062 G Street, Suite I, Arcata, CA 95521.

Dates, G. 1999. Monitoring optical brighteners detergent ingredient helps track bacteria 

sources. The Volunteer Monitor, the National Newsletter of Volunteer Water Quality 

Monitoring 11(2): 63-69.
GENERAL TECHNICAL REPORT PSW-GTR-238 

140

Ely, E. 2006. Bacteria methods for recreational waters, a short history and guide. The 

Volunteer Monitor, the National Newsletter of Volunteer Water Quality Monitoring 

18(1): 8-12.

Hagedorn, C.; Saluta, M.; Hassall, A.; Dickerson, J. 2005. Fluorometric detection of optical 

brighteners as an indicator of human sources of water pollution. Part I: 

Description and detection of optical brighteners; and Part II: Development as a 

source tracking methodology in open waters. Crop and Soil Environmental News, 

November 2005. http://www.ext.vt.edu/news/periodicals/cses/2005-11/part1.html, and 

http://www.ext.vt.edu/news/periodicals/cses/2005-11/part2.html. 

Hagedorn, C.; Reneau, R.B.; Saluta, M.; Chapman, A. 2003. Impact of onsite wastewater 

systems on water quality in coastal regions. Virginia Coastal Resources Management 

Program grant report 50312-01-13-PT. Dept. of Crop and Soil Environmental Sciences, 

Virginia Polytechnic Institute and State Univ., Blacksburg, Virginia.

Hartel, P.G.; Rogers, K.; Moody, G.L.; Hemmings, S.N.J.; Fisher, J.A.; McDonald, J.L. 2008. 

Combining targeted sampling and fluorometry to identify human fecal 

contamination in a freshwater creek. Journal of Water Health 6: 105-116.

Hartel, P.G.; Hagedorn, C.; McDonald, J.L.; Fisher, J.A.; Saluta, M.A.; Dickerson, J.W. Jr.; 

Gentit, L.C.; Smith, S.L.; Mantipragada, N.S.; Ritter, K.J.; Belcher, C.N. 2007. 

Exposing water samples to ultraviolet light improves fluorometry for detecting 

human fecal contamination. Water Resources Journal 41: 3629-3642.

McCorquodale, D.: Burney, C.; Row, M. 1996. Indicators for determining the sources and 

extent of fecal contamination in coastal waters: an annotated bibliography.

Technical Report 96-06, Fort Lauderdale, FL: Broward County Dept. of Natural 

Resource Protection.

Stoeckel, D.M. 2005. Selection and application of microbial source tracking tools for 

water quality investigations. Book 2, Section A, Chapter 3. In: various authors.

Techniques and methods reports. Reston, VA: United States Geological Survey. 

Turner Designs. 2007. Product webpage and associated links. 

http://www.turnerdesigns.com/t2/instruments/aquafluor.html. 
141

Use of BasinTemp to Model Summer Stream 

Temperatures in the South Fork of Ten Mile 

River, CA

Rafael Real de Asua,1 Ethan Bell,2 Bruce Orr,2 Peter Baker,2 and 

Kevin Faucher3

Abstract

We used BasinTemp to predict summer stream temperatures in South Fork Ten Mile River

(SFTMR), Mendocino County. BasinTemp is a temperature model that attempts to quantify 

the basin-wide effects of high summer stream temperatures in basins where the data inputs are 

scarce. It assumes that direct solar radiation is the chief mechanism behind stream summer 

heating in mid latitudes. We applied it in the SFTMR basin to understand the dynamics of 

summer stream temperatures, the influence of timber management and the effects of climate 

change on water temperatures, and its implications for coho salmon habitat. Three vegetation 

scenarios (current vegetation conditions, reference vegetation conditions and topography only 

conditions) and their effects on the Maximum Weekly Average Temperatures (MWATs) 

throughout the basin were analyzed for 3 different years. We predicted a significant increase 

in water temperature related to the decrease in shade as vegetation conditions shift from 

reference to current and to topographic conditions under timber management. We also found 

that current vegetation conditions account for significant amounts of shade that reduce solar 

radiation and stream temperatures and that discharge has a growing effect in water 

temperatures as the basin approaches topographic conditions. 

Key words: BasinTemp, riparian shade, stream temperature, model, watershed management

Introduction

The effect of high water temperatures on fish populations is well documented and 

substantial (Berman 1998). Potential effects of water temperatures may become more 

pronounced if summer temperatures continue rising as climate change models predict

(Kiparsky and Gleick 2003). There is considerable interest in understanding and 

quantifying the interactions between summer stream heating dynamics, aquatic 

habitat quality and quantity, and the influence of land management activities on water 

temperature and its effects on fish populations. Theory supported by considerable 

empirical research indicates that in mid-latitude regions, direct solar radiation is the 

most important mechanism driving summer stream heating (Bartholow 2000, Beschta 

et al. 1987, Brown 1969, Ice 2001), comprising more than 80 percent of the heat 

budget (Monteith and Unsworth 1990). In these locations riparian shade and 

topography are the most important controls on the amount of direct solar radiation 

reaching the water surface (Ice 2001). 

 

1 Stillwater Sciences, 2855 Telegraph Avenue, Suite 400 Berkeley, CA 94705. (raf@stillwatersci.com). 

2 Stillwater Sciences, 2855 Telegraph Avenue, Suite 400 Berkeley, CA 94705. 

3 Campbell Timberland Management, 90 W. Redwood Ave, Fort Bragg, CA 95437.
GENERAL TECHNICAL REPORT PSW-GTR-238 

142

Shading supplied by topography and riparian vegetation during the summer 

months is considered to be essential for moderating high stream temperatures

(Bartholow 2000, Beschta et al. 1987, Brown 1969, Ice 2001, Johnson and Jones 

2000, Rutherford et al. 1997); particularly in small, low-order streams that are highly 

sensitive to changes in the thermal environment due to the relatively low heat 

carrying capacity of these streams. 

BasinTemp, developed by Allen and Baker in 1999, addressed the need to find a 

simple way to predict high summer stream temperatures at a watershed scale. Since 

BasinTemp model was presented at the 2004 Redwood Region forest science 

symposium and its methods were discussed in a paper by Allen et al. 2007 in the 

symposium’s proceedings, we will only refer to them briefly here. BasinTemp is a 

mechanistically based model which assumes that direct shortwave radiation drives 

stream summertime temperatures, emphasizing the role of the riparian vegetation in 

the control of insolation and water temperatures. It is composed of several modules

including (1) a GIS Pre-processor that assembles a channel network, elevations and 

vegetation heights; (2) a radiation model that generates daily-averaged, spatially 

explicit shortwave radiation predictions (W/m2

/day) from the above data; (3) a simple 

hydrology model that assumes that groundwater accretion is a linear function of 

drainage area and estimates low wetted widths from empirical values; (4) a simple 

1D heat balance model which uses solar radiation, discharge, groundwater accretion 

and hydraulic geometry values to predict MWAT values for the whole basin; (5) an 

optimization routine which improves model predictions using field measured 

temperature data derived from a number of thermistors deployed in the watershed.

BasinTemp was applied to the South Fork Ten Mile River (SFTMR) Basin to 

confirm the effectiveness of BasinTemp in a current vegetation conditions scenario, 

to assess and quantify spatially explicit summer stream temperatures in the basin and 

more explicitly to study the influence of topography, vegetation patterns, climate 

change and the effect of land management on these and on stream temperatures. The 

study attempts to answer the following questions: (1) What is the role of shading by 

riparian vegetation in controlling summer stream temperatures? (2) How does the 

importance of riparian shade vary across the basin, and if so? (3) How do different 

riparian vegetation conditions affect stream temperatures locally and downstream? 

(4) How might changes in regional climate patterns affect stream temperatures in the 

South Fork Ten Mile River Basin?

Study Area

The SFTMR is a small sub-watershed (100 km2) in the Ten Mile River Basin, 13 

km north of Fort Bragg, CA (fig. 1), with elevations that range between 6 m and 950 

m. It has four main tributaries, three of them coming in from the right (Smith, 

Campbell and Redwood creeks) and one from the left (Churchman Creek).The 

climate in the SFTMR basin is characterized by two distinct seasons: a hot, dry 

summer and a cool, wet winter. This is modified by the effect of the coastal fog 

which towards the ocean, moderates summer temperatures (Albin and Law 2006). 

Temperatures range between 12°C at the coast to 30°C inland. 

We subdivided the watershed into three main zones depending on the reach and 

influence of the fog layer: (1) a coastal or fog zone, extending approximately 4 km 

inland, where August average maximum daily air temperatures are below 20°C; (2) a 
Use of BasinTemp to Model Summer Stream Temperatures in the South Fork of Ten Mile River, CA

143

transition zone, extending from 4 km to 9 to 10 km from the coast, where 

temperatures increase from 20 to 26°C; (3) an inland zone, extending farther than 9 to 

10 km from the coast, where temperatures are predominantly over 26°C. Results 

from the fog zone were discarded in the optimization and in the validation of this 

study because the model is inappropriate for conditions where incoming shortwave 

radiation is no longer the dominant heat energy flux (Allen 2007). 

The geology is comprised of homogeneous Franciscan Coastal Belt composed of 

greywacke sandstone, shales, siltstones and conglomerates and has relatively small 

influence in the model output due to its homogeneity. Redwood (Sequoia 

sempervirens) in the coast and Douglas-fir (Pseudotsuga menziesii) inland are the 

dominant tree species in the basin. 

Figure 1—Study area. 

Currently all of the SFTMR basin is privately owned. Over 90 percent is owned 

by Campbell Timber Management. The watershed was heavily logged between 1910 

and 1940 and has been recovering by natural means since 1930, although in 1945 a 

wildfire burnt most of the inland part of the watershed to the south of Smith Ridge to 

the north and to the west of Sherwood Ridge delaying its recovery substantially 

(Ambrose et al. 1995). This can be seen today as late seral stages dominate the 

western half of the basin while early seral stage stages dominate the eastern half. 

Native fish species include Chinook salmon (Oncorhynchus tshawytscha), steelhead 

(O. mykiss), coho salmon (O. kisutch), and sculpin species (Cottus spp.). This study 

focuses on the effects on the temperature sensitive juvenile life-stage of coho salmon, 

which are listed as endangered by both the federal government and the State of 

California. The input data used in the study are shown in table 1. The basic stream 

channel network was provided by Campbell Timberland Management (CTM). It was 

expanded to include headwater swales and split into 30 m segments which constitute 
GENERAL TECHNICAL REPORT PSW-GTR-238 

144

the minimum unit for which MWATs, solar radiation, discharge and wetted widths 

are modeled. 

Three scenarios were tested: (1) topographic conditions, representing the worst 

case scenario assuming no vegetation anywhere and topography derived shade only; 

(2) current vegetation conditions representing shade derived from topography plus 

vegetation heights as of 2006; and (3) reference vegetation conditions representing 

shade from undisturbed riparian conditions and assigning late seral tree heights to the 

riparian vegetation. 

Table 1—Data types used for BasinTemp in the SFTMR basin. 

Data type Data used for SFTMR

Stream network Modified USGS 1:24,000 DLG hydrography

Topography USGS 10m DEM

Tree heights Landsat TM imagery classified according to the California Wildlife 

Habitat Relations (CWHR) system (Fox et al. 1997)

Channel geometry Power-law relationship between drainage area and field measured 

low-flow widths throughout the SFTMR basin

Low flow discharge

7-day mean daily discharge data from pressure transducers set 

throughout the basin by CTM and from the Noyo River USGS gage 

near Fort Bragg

Observed stream 

temperature data 2006, 2007 and 2010 thermograph data compiled by CTM

Absolute tree heights are obtained from combined topographic data and 

estimated tree heights derived from vegetation information (Allen 2007). 

Topographic elevations were extracted from a USGS 10 m DEM and were used with 

no modification in the topographic conditions scenario. Estimated vegetation tree 

heights were added to the 10 m DEM elevations for the current and reference 

vegetation condition scenarios.

For current vegetation conditions tree heights were generated using vegetation 

data from 1994 Landsat Thematic Mapper (TM) imagery classified according to a 

modified California Wildlife Habitat Relationships (CWHR) classification scheme 

(Fox et al. 1997) where DBH-height relationships were established for current and 

reference condition vegetation as shown in table 2. These height were validated by 

2005 CTM stand data summarized into average tree heights and if within 90 m of any 

streams, updated with 2005 1 m National Agricultural Imagery Program (NAIP) 

color orthophotography resampled in several steps to 30 m. 

Water temperature data was provided by CTM for 2006, 2007, and 2010. 

Thermostats were evenly distributed throughout the basin and located upstream and 

downstream of major confluences. Of these 3 years, 2007 was the most typical of hot 

and dry conditions while 2006 was an abnormally hot, useful for estimating 

temperature increases that might result from climate change. The year 2010 was the 

most representative of average temperature and discharge conditions (fig. 2). As 

mentioned above, to calibrate the model, sites in the fog zone (Zone 1, fig. 1) were 

removed from the analysis. HoboTM data loggers were used to measure actual stream 

temperatures throughout the basin for 3 years. Thirty two sites were studied in 2010, 
Use of BasinTemp to Model Summer Stream Temperatures in the South Fork of Ten Mile River, CA

145

twenty two in 2007 and twenty in 2006. They recorded temperatures at 15 minute 

intervals which were combined into daily averages. These were calculated into 7 day 

moving averages or average weekly average temperatures (AWATs). The maximum 

AWAT in the year (MWAT) was extracted for each station and the most common 

MWAT value for each station was defined for every year: July 27th for 2006 and 

2007 and July 21st for 2010. Wetted widths were measured in August of 2006 and 

2007 and extrapolated to 2010 due to the lack of measurement. July monthly average 

maximum air temperatures, 21°C for 2006 and 2007 and 15.8°C for 2010, were 

derived from 4 km Oregon State University PRISM grids. A single basin-wide 

average was used as an input parameter in the heat transfer model. 

Table 2—Diameter at breast height (DBH) to tree height relationships for CWHR vegetation 

assemblages.

DBH 

range Tree height (m)

(inches)

Mixed 

Hardwood

Mixed 

Pine Mixed Fir

Mixed 

Conifer 

and 

Hardwood

Mixed Oak 

Woodland

Mixed 

Hardwood 

and 

Conifer

Mixed 

Conifer

6-Jan 10 7 7.5 7.5 5 10 10

11-Jun 15 10 15 15 10 15 15

24-Nov 20 17.5 20 22.5 15 20 25

> 24 25 25 30 30 20 27.5 35

> 36a - - - - - - 45 a Only applies to the Mixed Conifer class.

Figure 2—Long-term water temperature (MWAT), air temperature (average 

maximum daily air temperature from PRISM) at SFT5, and estimated discharge for 

site SFT19 in the South Fork Ten Mile basin, 1993 to 2010. 

In 2006 and 2007 discharge values at SFT19, the lowest station in the watershed, 

were 3.7 m3

/s and 2.7 m3/s respectively, some of the lowest values since 1993 (fig. 2). 

The calculated 2006 and 2007 accretion rates were 0.000414 and 0.00030571 m3

/km 

respectively. With no 2010 discharge data in the SFTMR basin, we estimated the 

10

12

14

16

18

20

22

24

26

28

30

19921993199419951996199719981999200020012002200320042005200620072008200920102011

Year

Temperature °C

0

2

4

6

8

10

12

14

16

18

20

Discharge (cfs)

Observed MWAT -SFT5

Avg-Maximum Daily Air Temperature July -SFT5

Predicted discharge -SFT19
GENERAL TECHNICAL REPORT PSW-GTR-238 

146

discharge at SFT19 based on values from the USGS gage in the Noyo River near 

Forth Bragg and in their high correlation with SFT19 discharge in other years. 

Discharge for 2010 at SFT19 was estimated to be 4.5 m3

/s and the accretion rate 

0.000504 m3

/km. 

Results

A high correlation between observed and modeled results was observed in 2010 

(average water year) with a root mean square error (RMSE) = 0.3°C and a R2 = 

0.89). 2007 (dry water year) had a RMSE of 0.59°C and an R2 of 0.67. Model 

parameters derived from these best-fit relationships were later applied for subsequent 

temperature prediction scenarios (reference vegetation conditions, and topographic 

shade-only). We assume the higher correlation and lower RMSE in the 2010 data to 

be a result of a lower temperature range in the observed temperatures in 2010 (2.9°C) 

than in 2007 (3.1°C). The better placement of the thermistors after several years of 

field surveys is possibly another reason for the better fit.

The spatial distribution of predicted MWATs closely tracks the observed MWAT 

temperatures. Warmest predicted MWATs relative to drainage area are generally 

observed in the eastern portion of the basin in upper Redwood Creek and the Upper 

South Fork Ten Mile River near the confluence with North Fork Redwood Creek (fig. 

3). Downstream of that confluence, temperatures warm up to 17°C, over the preferred 

range for coho salmon, during the dry water year and remain at 17°C until the river 

reaches the fog zone. Temperatures for the average water year (2010) warm up in the 

mainstems of Redwood Creek and South Fork Ten Mile River in the inland zone but 

at 15°C stay within the preferred range for coho and remain at close to 15°C until the 

waters reach the fog zone where the water cools down. This warming is apparently 

due to the combined influence of warm July air temperatures and reduced shading 

provided by early seral-stage vegetation. A net water loss of the reach (personal 

observation) may be another cause of the warmer temperatures in the reach. Overall, 

less than 1 km of stream length has temperatures higher than the preferred range for 

coho salmon in the dry water year, while all predicted temperatures are below 15.5°C 

in the average water year. 

Upstream of Churchman Creek (drainage area 10.3 km2

 (fig. 3), tributaries 

draining into the mainstem South Fork Ten Mile below its confluence with Redwood 

Creek are all small and hence have relatively small thermal dilution effects. Water 

temperatures cool downstream of the Churchman Creek confluence, where 

temperatures less than 13 or 15°C (for average or dry water year types, respectively) 

empty into the mainstem South Fork Ten Mile River. 

MWAT temperature predictions for shade provided by topography only were 

generated for average and dry water year data. Under current vegetation conditions, 

the average water temperatures are 0.9°C and 1.3°C (average and dry water years, 

respectively) cooler than under topographic-shade-only conditions. Water 

temperatures in the headwaters start out cool at less than 13°C due to cold 

groundwater temperatures, but due to the lack of vegetative shading heat loading is 

high, resulting in temperatures predicted to exceed 18°C in the mainstem South Fork 

Ten Mile River for all of Zone 2 and much of Zone 3 in 2007. In 2010 there is less 

heating in the mainstem. Temperatures reach 17°C below the confluence of South 
Use of BasinTemp to Model Summer Stream Temperatures in the South Fork of Ten Mile River, CA

147

Figure 3—2010 MWAT predictions for SFTMR for (A) reference vegetation, (B) 

current vegetation and (C) topographic conditions. 

Fork Ten Mile and Redwood Creeks, increasing until 18°C below the confluence 

with Churchman Creek to cool down when we enter the fog zone. Although the 

difference with temperatures observed under current conditions is smaller that in the 

dry water year, observed temperatures are still higher. 

The year 2006 was considered to be a climate change scenario. Current climate 

change models for northern California (Cayan et al. 2006) predict a trend of 

increasing summer air temperatures. Total annual precipitation is predicted to remain 

similar to current conditions, with most rainfall continuing to occur during a 

relatively short winter season. Summer air temperature predictions range from 

increases of about 2 to 5°C over the next 50 to 100 years depending on the scenario. 

To predict water temperatures based on climate change models, we modeled shade 

under current and reference conditions based on data collected during a recordbreaking heat wave event that was experienced between July 16 – 26, 2006. The 

water temperature dynamics during summer 2006 were very similar to what is 

predicted for northern California climate change. This scenario predicted that over 27 

km of stream channel would have temperatures greater than 17°C under current 

vegetation conditions, and over 7 km under reference vegetation conditions. Based on 

our results, if these climate models are accurate, we predict a trend of increasing 

MWATs in the South Fork Ten Mile River, regardless of land management actions.

Under these conditions, more of the mainstem South Fork Ten Mile River will 

become too warm for coho salmon, and cooler tributaries, such as Churchman and 

Smith creeks, and areas located downstream within the cooler coastal fog zone, will 

likely play a heightened role in overall salmon productivity. Precisely how 

exceptional this period was and how it affected water temperatures in the South Fork 

Ten Mile Basin can be seen by comparing MWATs recorded in 2006 compared with 
GENERAL TECHNICAL REPORT PSW-GTR-238 

148

average MWATs recorded at the same gages between 1993 to 2004 (fig. 2). Observed 

MWATs for 2006 gages were all warmer than MWATs in previous years, some 

significantly so. 

Discussion

The study shows an expected rise in average basin wide MWATs with an 

increase in air temperatures (See table 3 and fig. 2 to compare the 3 year’s average air 

temperatures). Predicted MWATs also increases regardless of the scenario, 2.3 °C 

under current and reference vegetation conditions and 2.0 °C under topographic 

conditions. We found that MWATs increased 0.4°C from reference to current 

conditions in 2006 and 2010 and 0.8°C in 2007 and 0.6°C, 0.9°C and 1.3°C between 

current vegetation conditions and topographic conditions in 2006, 2010 and 2007 

respectively. Even though 2006 was an extremely hot year (fig. 2), the difference in 

predicted MWAT values is smaller than in 2007, a cooler year but with higher 

discharge. 

Table 3 shows the percentage of the stream network outside the fog zone with 

MWATs under 15°C. Over 90 percent of the stream channel network is within the 

preferred range of coho salmon (15°C MWAT) for reference vegetation conditions in 

2007 and 2010, and 74 percent in 2006. The decrease in the percentage of channel 

network under 15°C as we depart from the reference conditions is 16 percent in 2006 

(the climate change scenario) and 8 percent in 2010 (the average water year). 

MWATs under current vegetation conditions are closer to MWATs under reference 

vegetation conditions (best case scenario) than to topographic conditions (worst case 

scenario), indicating the positive effects of current land management conditions in 

maintaining low stream temperatures. 

Table 3—Average predicted MWATs (°C ), percentage of total stream length and percentage 

of Class I stream length with MWATs under 15°C in zones 2 and 3 for topographic, current 

and reference vegetation conditions in years 2010, 2007 and 2006.

Year Topographic 

Conditions

Current Vegetation 

Conditions

Reference Vegetation 

Conditions

2010 14.2°C / 92% / 68% 13.3°C / 100% / 99% 12.9°C / 100% / 100%

2007 15.7°C / 73% / 5% 14.4°C / 83% / 35% 13.6°C / 90% / 62%

2006 16.2°C / 58% / 1% 15.6°C / 68% / 20% 15.2°C / 74% / 23%

Table 3 also shows the percentage of the stream network outside the fog zone 

with MWATs under 15°C, but this time constrained to the mainstem SFTMR and 

main tributaries as defined by STREAM CLASS = 1 (fig. 1). This query extracts the 

main channels from the boundary of the fog zone to the upper extent of the fish 

bearing streams allowing us to see the impact of tree shade on the channel network’s 

aquatic reaches. The reduction of channel length under 15°C is concentrated in the 

main channels rather than in the headwater channels and it is more pronounced as the 

air temperature increases. We find that 68 percent of the main channels outside of the 

fog zone have MWATs less than 15°C in an average water year (2010) even in 

topographic conditions while only 1 percent have in the climate change scenario 

reinforcing the importance of vegetation shade in the climate change scenario.
Use of BasinTemp to Model Summer Stream Temperatures in the South Fork of Ten Mile River, CA

149

The effects of vegetation shading on the main channels are reduced substantially 

with higher air temperatures. In the climate change scenario (2006) only 1 percent of 

the channels are under the 15°C threshold in the climate change scenario under

topographic conditions and 23 percent under reference conditions. But a small 

decrease in air temperature or increase in discharge (2007) results in a significant 

increase in the length of main channel under the 15°C MWAT to 35 percent in 

current conditions and 62 percent in reference conditions. As the air temperature 

increases the importance of the role of the vegetation in the reduction of the 

temperatures also increases. It is interesting to observe how current land management 

practices maintain main channel MWATs closer to reference conditions than 

topography conditions. 

BasinTemp has been used as a tool in this study to predict basin-wide 

temperatures in the SFTMR with a few, simple parameters and with a limited field 

effort. We consider the model to be a valid tool to get a good first estimate of a 

basin’s temperature and complementary to reach-based temperature models. RMSE’s 

for the 3 years studied ranged between 0.3 and 0.6°C. 

We found land management in the SFTMR basin to keep the riparian vegetation 

in conditions that are closer to reference heights than bare ground conditions thus 

helping current MWATs to stay below 15°C in an average water year (2010) and in 

most reaches in a dry water year (2006). In the 3 years shown here, current 

temperatures are closer to reference than to topographic conditions. 

With regard to the main four questions stated in the introduction we found that: 

(1) Riparian shading in the SFTMR reduced summer stream temperatures in all 3 

years studied. This reduction of predicted MWATs in the whole basin was greatest in 

2007 and 2006 and we found that riparian shading effects were reduced in 2010 due 

to higher discharge and lower air temperatures (table 3 and fig. 2); (2) Riparian shade 

is important throughout the basin. Shaded lower order streams feed colder water to 

higher order tributaries reducing water temperatures in these reaches. Riparian shade 

has greater effect in reducing MWATs in Class I streams as it lowers stream 

temperatures and their propagation downstream (table 3, fig. 3); (3) Reference 

vegetation conditions help keep stream temperatures low in upper stream reaches 

feeding colder into larger tributaries and reducing the propagation of high 

temperatures downstream in Class I streams reducing temperature impact on 

salmonids. Current land management practices help maintain riparian shade effects 

closer to reference vegetation conditions than topographic conditions keeping most of 

the channels under 17°C; and (4) Predicted climate change scenarios leading to 

higher air temperatures and reduced flows are expected to reduce the influence of 

vegetation shade in the control of stream temperatures increasing stream 

temperatures. 

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Rutherford, J.C.; Blackett, S; Blackett, C.; Saito, L.; Davies-Colley, R.J. 1997. Predicting the 

effects of shade on water temperature in small streams. New Zealand Journal of

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Campbell Timber Management.
151

Comparing Hydrologic Responses to 

Tractor-Yarded Selection and Cable-Yarded 

Clearcut Logging in a Coast Redwood 

Forest1

Leslie M. Reid2

Abstract 

Initial increases in dry-season flow after selective logging of second-growth coast redwoods 

(Sequoia sempervirens) in the 424 ha South Fork Caspar Creek watershed disappeared by 7 

years after logging ended, and low flows then dropped to below expected values for the next 

20 years. During the 16 years after clearcut logging in the 473 ha North Fork watershed, latesummer flows increased to nearly twice those expected and then declined to pre-treatment 

levels on a trajectory that suggests further decline is likely. This contrast in dry-season flow 

responses is consistent with expected differences in post-logging recovery rates for 

transpiration after selective and clearcut logging. The South Fork showed a delayed peakflow 

response relative to that in the North Fork, and a maximum 3 year increase (per unit area of 

clearcut equivalent) about 40 percent lower. South Fork peaks remained slightly elevated for 

more than 20 years after logging ended, and North Fork peaks remained elevated for at least 

12 years after logging.

Keywords: cumulative watershed effects, logging, low flow, peakflow, recovery

Introduction and study site

Studies at different sites often provide conflicting information about the 

hydrologic effects of logging (e.g., Moore and Wondzell 2005), indicating that 

different settings, forest types, or silvicultural strategies may produce different 

outcomes. Silvicultural preferences shift through time, and the extent to which past 

experimental results apply to new management strategies is often unknown. Unevenage management is again being used in some coast redwood (Sequoia sempervirens) 

forests instead of clearcutting, so it would be useful to know how hydrologic 

responses to selective logging and clearcutting compare. This study evaluates low 

flow and peakflow responses to these silvicultural strategies during two watershed 

experiments. 

The Caspar Creek Experimental Watersheds (N39°21 ́ W123°44 ́; fig. 1) are 

underlain by sandstone and shale of the Coastal Belt of the Franciscan Complex. 

Rainfall averages 1170 mm/yr and about half reappears as streamflow. Snow is 

uncommon. October through May account for 95 percent of the rainfall, and annual 

minimum flows generally occur in early October. By 1962, the old-growth forests 

logged in 1865 to 1905 had regrown into mature stands dominated by coast redwood 

 

1 This paper was presented at the redwood science symposium: coast redwood forests in a changing 

California. 21-23 June 2011, Santa Cruz, California. 2 Research geologist, U.S. Department of Agriculture, Forest Service, Pacific Southwest Research 

Station, 1700 Bayview Dr., Arcata, CA 95521. (lreid@fs.fed.us). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

152

and Douglas-fir (Pseudotsuga menziesii). The 424 ha South Fork Caspar Creek 

watershed was selectively logged during the first of the two experiments, and the 473 

ha North Fork watershed was partially clearcut during the second. Similar forest 

types at similar sites were thus subject to different silvicultural strategies, allowing 

comparison of their hydrologic responses.

However, the two studies used different experimental designs, produced different 

kinds of data, and weathered different storms. Because the control watershed for the 

first experiment became the treatment watershed for the next, post-logging results for 

the first study spanned only 12 years. Previous reports (described by Ziemer 1998) 

presented short-term North and South Fork results. To compare responses over a 

longer period, the current analysis required development of methods to permit 

tracking of South Fork responses after logging began in the North Fork. 

Figure 1—North and South Fork Caspar Creek watersheds.

Methods

The South Fork experiment began in 1962 with 4 years of monitoring to calibrate 

relations between measurements at the North and South Fork gaging weirs. More 

than 4 km of mainline road were constructed along the South Fork riparian zone in 

1967, and the watershed was then selectively logged from 1971 to 1973 using 

tractors, with about 2/3 of the timber volume removed. Treatment effects were 

evaluated until 1985, when logging began in the control watershed. 

Thirteen new stream gages were installed in the North Fork watershed in 1984 

and 1985, with three gaged subwatersheds selected to be left unlogged as controls. 

XYZ tributary enters the head of the North Fork weir pond and was not a part of the 

second study; 60 ha of XYZ were clearcut in 1985 and 1986. Hydrologic recovery 

could not be assured by then at the South Fork, so neither weir record could be 

compared to that from a calibrated control after 1985. The second experiment instead 

compared records from 10 of the new stations to those of the control tributaries 

(HEN, IVE, and MUN). Calibrations were established from 1985 to 1989, then 37 

percent of the watershed was clearcut in 1989 to 1992, with selectively logged buffer 
Comparing Hydrologic Responses to Tractor-Yarded Selection and Cable-Yarded Clearcut Logging 

in a Coast Redwood Forest

153

strips left along channels draining more than about 10 ha. Cut logs generally were 

cable-yarded to ridge-top roads. About 20 percent of the watershed was burned after 

logging, and most units were pre-commercially thinned a decade later. 

Rainfall has been monitored near the South Fork weir since 1963 using a series 

of weighing and tipping-bucket gages, but dry-season data were not collected 

consistently until 1972. The National Weather Service recorded rainfall for most of 

this period 12 km north in Fort Bragg. Summer storm totals of >0.6 mm at the Fort 

Bragg and South Fork (S620) gages are strongly correlated for 1989 to 1999 (RainS620

= 1.03 RainFtBragg + 0.73 mm, r

2

 = 0.89), but smaller events often reflect coastal fog 

and are less common at S620. This study combines the daily rainfall measured at 

S620 for October through May (accounting for 98 percent of the annual rainfall) with 

Fort Bragg data for daily rainfalls >0.6 mm in June through September to construct a 

continuous rainfall record from September 1962 through August 2008. 

The North and South Fork gaging structures are concrete sharp-crested 

compound weirs. Weir pond stages have been measured since 1962 in stilling wells, 

first using strip-chart recorders and then data-logged pressure transducers, and flow is 

calculated from pond stage using standard equations. Flows are monitored in Parshall 

flumes or rated sections at each upstream or tributary station by using data loggers to 

record stage at 10-minute intervals. Most tributaries run dry by late June, so dryseason flow analyses are based on data from the North and South Fork weirs.

Keppeler (1998) evaluated changes in low flow after North and South Fork 

logging, and her data suggest that South Fork flows may have dropped below pretreatment levels by the late 1980s. However, results were complicated by the lack of 

a control record after the onset of North Fork logging. Because summer rainfall is 

minimal, late-summer flows are sustained primarily by moisture stored from winter 

storms. The current study thus uses relations between runoff and antecedent 

precipitation indices (APIs) to calculate expected flows directly from rainfall, 

allowing flow deviations to be estimated after the control record ends. 

Periods in August and September were identified that had no rain in the 

preceding 3 days and <9 mm in the preceding 30 days. Mean daily flow was 

tabulated for 3 to 5 such days each year, with dates selected to be at least 6 days apart 

and to have records for both the North and South Forks, if possible. Records were not 

used during periods when weir ponds were drained to remove sediment. APIs were 

calculated for each selected date using a range of coefficients (0.99 to 0.60). The 

selected North Fork flows between 1963 and 1984 were regressed against each of the 

API sets, and a recession coefficient of 0.977 was found to best predict flows: 

LN = 0.0272 API977 + 0.0366 r

2

 = 0.87 n = 46 (1) 

where API977 (mm) is calculated as 0.977 times its value on the previous day plus the 

current day’s rainfall, and LN (L km-2s

-1) is the mean discharge for the day at the 

North Fork weir (fig. 2A). The same approach was used to develop a predictor for 

expected South Fork flows (LS1, L km-2s

-1) based on data from 1963 to 1970 (fig. 2B), 

with API985 calculated using a coefficient of 0.985: 

LS1 = 0.0143 API985 - 0.0320 r

2

 = 0.94 n = 22 (2) 
GENERAL TECHNICAL REPORT PSW-GTR-238 

154

An equation was also developed to predict South Fork flows from those observed 

at the North Fork (LNO, fig. 2C):

LS2 = 1.52 LNO + 0.0706 r

2

 = 0.91 n = 22 (3) 

An analogous regression using expected North Fork flows produced a relation not 

significantly different from equation 3, allowing expected South Fork flows to be 

calculated from either observed or expected North Fork flows. 

August and September South Fork flows expected in the absence of logging can 

now be estimated using either equation 2 or equation 3, and results can be compared 

to observed values to evaluate long-term patterns of deviation after selective logging. 

Similarly, North Fork deviations can be calculated by comparing measured values 

with those predicted from rainfall records using equation 1. 

Figure 2—Calibrations between A. North Fork late-summer flows and API977; B. 

South Fork late-summer flows and API985; C. South Fork late-summer flows and 

those observed at the North Fork; D. South Fork and North Fork peakflows; E. ARF 

peakflows and the average of those at HEN, IVE, and MUN; and F. North Fork 

peakflows and the average of those at HEN and IVE.

Past analyses of South Fork peakflows compared pre-logging correlations to 

North Fork peaks with those from between the onset of logging and either 1 (Ziemer 

1981) or 2 years (Wright et al. 1990) after logging ended, thus including 3 years of 

logging. No significant increase was found for moderate to large peaks. However, 

results of the North Fork study later showed that effects of logging may not appear 

until the following wet season (Lewis et al. 2001), so inclusion of data collected 

during logging may increase variance enough to hinder detection of responses. 

The present peakflow analysis incorporates all peaks higher than 0.16 m3

s

-1km-2

in the North or South Fork. Pre-logging South Fork peaks were first regressed against 

observed North Fork peaks (PNO, m3

s

-1km-2) from 1963 through 1971 (fig. 2D):

PS = 1.130 PNO

0.876

r

2

 = 0.88 n = 61 (4) 
Comparing Hydrologic Responses to Tractor-Yarded Selection and Cable-Yarded Clearcut Logging 

in a Coast Redwood Forest

155

allowing expected peakflows in the South Fork (PS) to be estimated from observed or 

expected North Fork peakflows. 

Between 1985 and 1989, only the new North Fork control tributaries are assured 

to provide stable records. Two methods provide estimates of expected North Fork 

peaks. First, the ARF gage (384 ha) is upstream of the XYZ confluence, so ARF 

peaks were unaffected by XYZ logging and can be calibrated against the average of 

peaks at control catchments HEN, IVE, and MUN (PHIM, m3

km-2s

-1) for 1986 to 1989 

(fig. 2E), providing a predictor for expected ARF flows (PA) from 1985 to 1995: 

PA = 0.775 PHIM

0.943

r

2

 = 0.91 n = 21 (5) 

Second, because only 13 percent of the North Fork watershed was logged in 1985 

and 1986, North Fork peakflows are likely to have changed little over this period. If 

the North Fork record is assumed to be stable for the period, calibration of weir peaks 

to the mean of peakflows at controls HEN and IVE (PHI, m3

km-2s

-1; fig. 2F) provides 

a predictor for expected North Fork weir peakflows (PN) for 1985 to 2004: 

PN = 1.06 PHI

0.854

r

2

 = 0.93 n = 23 (6) 

If North Fork peakflows had increased during the calibration period due to XYZ 

logging, use of equation 6 would provide lower estimates of change per percent 

forest removed than would an analysis based on equation 5. The validity of the 

assumption of stability can thus be tested. 

Results and discussion

Application of equation 2 to the rainfall record provides estimates of expected 

late-summer North Fork flows for the selected dates in August and September from 

1963 to 2007. Observed and expected flows agree relatively closely until 1985 (fig. 

3A), when variance increases and several flows exceed expected values by >50 

percent. Flows again increased after completion of most logging in 1991, and 

between 1996 and 2000 the mean of sampled flows is 1.7 times that expected. An 

unusual 50 mm/day storm in June 2001 produced a higher summer API than 

baseflows reflect, so expected flows are anomalously high in 2001. Flows begin to 

decrease after 2003, and by 2007 the mean again equals the expected value, but the 

slope of the recovery curve suggests that flows will continue to decrease. Values 

since 2001 reflect effects of both clearcutting and pre-commercial thinning. Overall, 

dry-season flow remained higher than expected for at least 15 years after North Fork 

clearcutting ended. 

Low-flow deviations show a different pattern in the South Fork. Analyses based 

on equations 2 and 3 show similar results (fig. 3B, C): dry-season flow was enhanced 

for at least 4 years after South Fork logging began and reattained pre-logging values 

by 10 years. By 15 years after the onset of logging, flow had consistently dropped 

below expected levels, reaching a minimum at 21 years. Flows neared pre-treatment 

levels once again about 30 years after selective logging began. More data are needed 

to determine whether the apparent renewed downturn at 36 years represents the start 

of a new trend or simply reflects a short-term aberration.
GENERAL TECHNICAL REPORT PSW-GTR-238 

156

Late summer flows began to show an effect during the first year of logging in the 

South Fork (fig. 3D), while North Fork responses to the major period of logging were 

not evident until the third year. The downstream portion of the South Fork was 

logged the first year, so hydrologic changes would have occurred first near the gage. 

North Fork logging progressed in the opposite direction, so riparian vegetation along 

the entire channel length could utilize increased flow before it reached the gage. At 

each site, the response became evident soon after areas near the gage were logged. 

Figure 3—Ratio of observed to expected late summer flows at A. the North Fork 

weir; B. at the South Fork weir calculated from rainfall; C. at the South Fork weir 

calculated from North Fork flows; and D. at both weirs (calculated from rainfall) as a 

function of years after logging began. Post-logging curves are fitted using loess 

regression and exclude data from 2001. 

Once the response is under way, the contrast in response trajectories is consistent 

with the differing silvicultural strategies used. South Fork selective logging left a 

third of the stand well distributed across the watershed. Because summers are dry, 

potential transpiration exceeds actual transpiration after May, and trees must compete 

for a limited water supply. When competition is reduced by selective logging, the 

remaining trees can quickly begin to use moisture that in the past would have 

sustained neighboring trees, and soil moisture reserves are again depleted by the end 

of the dry season. Such a response would be particularly rapid in stands containing 

coast redwoods because most second-growth redwoods originate as stump-sprouts, so 

neighboring trees often share root networks. In contrast, trees left uncut after 

clearcutting are not within reach of most the surplus moisture, and hydrologic 
Comparing Hydrologic Responses to Tractor-Yarded Selection and Cable-Yarded Clearcut Logging 

in a Coast Redwood Forest

157

recovery must rely on establishment of new vegetation on the clearcut surface. In

addition, North Fork burned units were treated with herbicides in the mid-1990s, and 

most units were pre-commercially thinned in 2001, further prolonging the effects. 

Reduced interception and transpiration appear to largely explain hydrologic 

changes after North Fork logging (Reid and Lewis 2007), with altered interception 

dominating wet-season changes. If summer rain is minimal, dry-season transpiration 

and residual moisture storage from the wet season are major influences on latesummer flow, so both transpiration and interception may be influential. Comparison 

of sampled late summer flows with those from 60 days earlier (with <20 mm of rain 

between the dates) shows that a given early summer flow leads to higher than 

expected late summer flow in the immediate post-logging period at both sites (fig. 4) 

and to lower than expected flow during the later period of flow depression after 

South Fork logging. A major causal mechanism thus is active during the summer, 

suggesting that altered summer transpiration is an important influence. The North 

Fork record is not yet long enough to test for depressed flows. 

Figure 4—Comparison of early and late dry-season flows before and after logging at 

the A. South Fork and B. North Fork Caspar Creek weirs.

South Fork logging may have contributed to low-flow depression in several 

ways. First, selective logging promotes growth of young trees among the residuals. 

Water competition may thus be more intense than in the original stand, in which 

mortality during drought years likely achieved a long-term balance between stand 

density and water availability. Second, the lack of buffer strips increased light in 

riparian zones, increasing growth at sites where plants may disproportionately affect 

summer flow by removing water directly from the hyporheic zone. Third, regrowth 

along the South Fork included many red alders (Alnus rubra), which tend to use more 

water than conifers (Hicks et al. 1991). Fourth, a young, dense, rapidly growing age 

cohort may simply use more water than a mature stand (Moore et al. 2004). Lowflow depression has also been observed in other young stands in the Pacific 

Northwest (Perry 2007). 

Peakflow deviations at the ARF gage after North Fork logging show increased 

peaks after 1990 (fig. 5A), a pattern also shown by deviations calculated using the 

assumption that weir peakflows did not change after XYZ logging (fig. 5b). For 1992 

to 1994, the North Fork at ARF and at the weir both show a mean dischargeweighted peakflow increase of 0.62 percent per percent of forest logged in the 

catchment upstream, where percent logged at the weir includes only the portion 

logged between 1989 and 1992. This agreement suggests that North Fork peakflows 

were not strongly affected by XYZ logging. The weir record indicates that pre-
GENERAL TECHNICAL REPORT PSW-GTR-238 

158

commercial thinning in 2001 may have renewed the effect, and pre-treatment levels 

had not been reattained by 12 years after logging ended. The temporal pattern shown 

by figure 5B is similar to that identified for the 27-ha CAR sub-watershed (fig. 5C), 

which was 96 percent clearcut in 1991 (fig. 1). 

Figure 5—Ratios between observed and expected peakflows at A. ARF from 

average of peaks at HEN, IVE, and MUN; B. the North Fork weir from average at 

HEN and IVE; and C. clearcut sub-watershed CAR from average at HEN and IVE. 

Symbol areas are proportional to unit area discharges, and post-logging curves are 

fitted using loess regression for B and C, and linear regression for A.

Comparison of observed South Fork peakflows with those expected on the basis 

of correlations to observed or expected North Fork peaks shows that most South Fork 

peakflows were higher than expected 3 to 11 years after logging began (fig. 6A), and 

that they appear to remain slightly elevated until about 1995. If expected North Fork 

peaks are overestimated due to increased flow from XYZ logging during the 

calibration period, South Fork deviations after 1986 would be larger than shown. 

Overall, South Fork peaks showed a maximum 3-yr discharge-weighted mean 

increase of 0.36 percent per percent of forest logged in the catchment, about 60% of 

that seen in the North Fork. The South Fork response also appears to be delayed 

relative to that in the North Fork (fig. 6B, C). 

Most peakflows at Caspar Creek are more strongly influenced by interception 

than transpiration (Reid and Lewis 2007), and recovery trajectories for interception 

and transpiration differ. Interception may be influenced both by a stand’s canopy and 

by the volume of absorbent bark present. Leaf area can recover relatively quickly 

while bark storage cannot, so interception-controlled peaks may remain slightly 

elevated long after either clearcutting or selective logging ends, as appears to be the 

case at Caspar Creek. 

Wet- and dry-season hydrologic responses appear to be decoupled in the South 

Fork, with peakflows remaining slightly elevated during the period of summer flow 

depression. Such decoupling is consistent with the presence of multiple mechanisms 

of hydrologic change, each with its own recovery trajectory and distinctive effects. 
Comparing Hydrologic Responses to Tractor-Yarded Selection and Cable-Yarded Clearcut Logging 

in a Coast Redwood Forest

159

Figure 6—A. Deviations from expected peakflows at South Fork calculated from 

North Fork peakflows, B. comparison of recovery trajectories for North and South 

Fork peakflows by time after logging, and C. cumulative deviations. Symbol areas are 

proportional to discharges, and post-logging curves are fitted using loess regression.

Conclusions

Long-term flow records are rare for watersheds the size of the North and South 

Forks of Caspar Creek. For those that do exist, the questions the original monitoring 

studies were designed to address have often been superseded by new issues that had 

not yet been recognized when monitoring began. The Caspar Creek data stream, 

initiated a half-century ago, has provided the information needed to address two 

generations’ controversies and concerns. Many of the watershed-related issues that 

have arisen since Caspar Creek monitoring began could not be resolved without longterm hydrologic data, and among these is the current need to understand mechanisms 

for long-term cumulative watershed effects associated with forest management. 

Cumulative effects can accrue if changes resulting from a management activity 

are superimposed on changes induced by other contemporary or past activities. First 

steps in understanding the potential for cumulative hydrologic effects are to 

determine the length of time required for hydrologic recovery from a particular 

activity and to understand the factors that may affect the recovery rate. After 

selective logging of second-growth redwoods at Caspar Creek, it has taken at least 30 

years for dry-season flows to reattain pre-treatment levels, and additional data are 

required before recovery can be assured to be complete. Long-term monitoring 

results also demonstrate that clearcut logging produced a very different recovery 

trajectory than selective logging, with the post-logging period of enhanced dryseason flow lasting about twice as long. Peakflow changes also show evidence of 

long-term persistence and differences between silvicultural treatments. Where 
GENERAL TECHNICAL REPORT PSW-GTR-238 

160

hydrologic change is an issue of concern in a watershed, it may be useful to plan 

management to ensure maintenance of a diversity of stand ages and silvicultural 

strategies in order to desynchronize post-logging hydrologic changes. 

Acknowledgments

This study is part of the cooperative Caspar Creek research program conducted 

since 1960 by the U.S. Department of Agriculture, Forest Service, Pacific Southwest 

Research Station and the California Department of Forestry and Fire Protection. John 

Griffen, Peter Cafferata, and an anonymous reviewer provided very helpful reviews. 

References

Hicks, B.J.; Beschta, R.L.; Harr, R.D. 1991. Long-term changes in streamflow following 

logging in western Oregon and associated fisheries implications. Water Resources 

Bulletin 27: 217-226.

Keppeler, E.T. 1998. The summer flow and water yield response to timber harvest. In: 

Ziemer, R.R., technical coordinator. Proceedings of the conference on coastal 

watersheds: the Caspar Creek story. Gen. Tech. Rep. PSW-GTR-168. Albany, CA: U.S. 

Department of Agriculture, Forest Service, Pacific Southwest Research Station: 35-43.

Lewis, J.; Mori, S.R.; Keppeler, E.T.; Ziemer, R.R. 2001. Impacts of logging on storm peak 

flows, flow volumes and suspended sediment loads in Caspar Creek, California. In: 

Wigmosta, M.S.; Burges, S.J., editors. Land use and watersheds: human influence on 

hydrology and geomorphology in urban and forest areas. Water Science and Application 

Volume 2. Washington, DC: American Geophysical Union: 85-125.

Moore, G.W.; Bond, B.J.; Jones, J.A.; Phillips, N.; Meinzer, F.C. 2004. Structural and 

compositional controls on transpiration in 40- and 450-year-old riparian forests in 

western Oregon, USA. Tree Physiology 24: 481-491.

Moore, R.D.; Wondzell, S.M. 2005. Physical hydrology and the effects of forest harvesting 

in the Pacific Northwest: a review. Journal of American Water Resources Association 

41: 764-784.

Perry, T.D. 2007. Do vigorous young forests reduce streamflow? Results from up to 54 

years of streamflow records in eight paired-watershed experiments in the H.J. 

Andrews and South Umpqua Experimental Forests. Corvallis, OR: Oregon State 

University. Master’s thesis.135 pp.

Reid, L.M.; Lewis, J. 2007. Rates and implications of rainfall interception in a coastal 

redwood forest. In: Standiford, R.B.; Giusti, G.A.; Valachovic, Y.; Zielinski, W.J.; 

Furniss, M.J., technical editors. Proceedings of the redwood region forest science 

symposium: what does the future hold? Gen. Tech Rep. PSW-GTR-194, Albany, CA: 

U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station: 

107-117.

Wright, K.A.; Sendek, K.H.; Rice, R.M.; Thomas, R.B. 1990. Logging effects on 

streamflow: storm runoff at Caspar Creek in northwestern California. Water 

Resources Research 26(7): 1657-1667.

Ziemer, R.R.1981. Stormflow response to roadbuilding and partial cutting in small 

streams of northern California. Water Resources Research 17(4): 907-917.

Ziemer, R.R., technical coordinator. 1998. Proceedings of the conference on coastal 

watersheds: the Caspar Creek story. Gen. Tech. Rep. PSW-GTR-168. Albany, CA: 
Comparing Hydrologic Responses to Tractor-Yarded Selection and Cable-Yarded Clearcut Logging 

in a Coast Redwood Forest

161

U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station.149 

p.

163

Landslides After Clearcut Logging in a 

Coast Redwood Forest1

Leslie M. Reid2 and Elizabeth T. Keppeler2 

Abstract

Landslides have been mapped at least annually in the 473 ha North Fork Caspar Creek 

watershed since 1985, allowing evaluation of landslide distribution, characteristics, and rates 

associated with second-entry partial clearcut logging of 1989 to 1992. Comparison of sliding 

rates in logged and forested areas shows no appreciable difference for streamside slides (size 

range: 7.6 to 380 m3

). However, the incidence of large landslides, including both streamside 

and upslope slides of 98 to 4900 m3

, varied by treatment. Such slides displaced 12 m3/yr per 

km2 of unlogged forest but showed rates one and two orders of magnitude higher in logged 

areas and along roads, respectively. Moreover, the volume rate of sliding from roads in logged 

areas was more than three times that from forested roads. The largest slides occurred 9 to 14 

years after logging, when root cohesion is expected to be near its minimum value; and within 

a few years of pre-commercial thinning, when hydrologic changes are again evident. Large 

slides may strongly influence suspended sediment yields both by increasing yields for several 

years after the slide and by emplacing temporarily stable channel and floodplain deposits, 

which then provide a sediment source for future gully and bank erosion. 

Key words: cumulative effects, erosion, landslides, logging, roads, sediment budget 

Introduction and site description

Associations between logging and increased landslide incidence have long been 

recognized, and many studies attribute the effect largely to reduced root cohesion (for 

example, Wu et al. 1979). However, because second-growth coast redwoods

(Sequoia sempervirens) usually survive logging, altered root cohesion is rarely 

considered important after redwood logging. Recent studies have identified another 

influence that may be more relevant in redwood forests: reduced rainfall interception 

during major storms after logging could increase pore pressures on marginally stable 

slopes, contributing to their destabilization (Keim and Skaugset 2003, Reid and 

Lewis 2009). We here evaluate landslide distribution in the 473 ha North Fork 

Caspar Creek Experimental Watershed (N39°21 ́ W123°44 ́), near Fort Bragg, 

California, to 1) quantify the influence of roads and logging on landsliding in the 

area; 2) assess interactions between the effects of roads and logging on landslide 

generation; 3) evaluate storm characteristics associated with landsliding; and 4) 

assess the contribution of landsliding to the watershed’s suspended sediment yield. 

This study uses a longer record to build on analyses by Cafferata and Spittler (1998). 

The North Fork Caspar Creek watershed is underlain by marine sandstones and 

siltstones of the Coastal Belt of the Franciscan Complex. Soils on ridge-top marine 

 

1 This paper was presented at the redwood science symposium: coast redwood forests in a changing 

California. 21-23 June 2011, Santa Cruz, California. 2 Research geologist and hydrologist, respectively, U.S. Department of Agriculture, Forest Service, 

Pacific Southwest Research Station, 1700 Bayview Dr., Arcata, CA 95521. (lreid@fs.fed.us; 

ekeppeler@fs.fed.us).
GENERAL TECHNICAL REPORT PSW-GTR-238 

164

terrace deposits are deep, sandy loams, while those lower on the slopes are shallower 

with higher clay and gravel contents. Many 3rd and 4th order channel segments flow 

through inner gorges, and drainage density is 4 to 5 km per km2

. Annual precipitation 

averages 1170 mm and falls mostly as rain; about half runs off as streamflow. The 

watershed’s old-growth redwood forest was logged between 1860 and 1904. Secondgrowth stands had matured by 1960, when the Caspar Creek watersheds were 

selected as a location for watershed-scale experiments. 

Figure 1—North Fork Caspar Creek watershed. 

Stream gaging began in 1962 at the newly constructed North Fork weir (fig. 1), 

and the North Fork watershed remained forested as a control for the next 23 years. 

Thirteen new gaging stations were installed in 1984 for a study of scale-related 

hydrologic effects of clearcutting in a second-growth redwood forest. The ungaged 

XYZ tributary, which enters the head of the weir pond at the basin mouth, was not 

included in the experiment and was about 64 percent clearcut in 1985 and 1986. 

Catchments above five gaging stations were then 90 to 100 percent clearcut in 1989 

to 1992, while those above three others were left forested; five downstream gages 

provided information for partially clearcut watersheds of increasing size. Overall, 13 

percent of the watershed was logged in 1985 and 1986 and another 37 percent 

between 1989 and 1992. Logged units were mostly cable-yarded from ridge-top 

landings. About 18 km of road are present and are located primarily on or near ridgetops, with 45 percent of the road length constructed immediately prior to logging at 

each unit. Selectively logged buffer strips were left within 40 to 60 m of channels 

draining more than about 10 ha. 

Methods

Landslide data available for the watershed were grouped into two partially 

overlapping data sets. First, “streamside slides” consist of landslide events larger than 

7.6 m3 that were observed within 15 m of a gaged tributary channel. These features 

have been mapped annually since 1985 along 72 percent of the length of 2nd- and 

higher-order channels in the watershed; observations are also made after major 

storms. Slide dimensions, associations with treethrow and roads, and the volume of 

debris still present are noted for each feature. Mapped events in some cases represent 
Landslides After Clearcut Logging in a Coast Redwood Forest

165

progressive enlargements of previously mapped landslides, so the number of 

landsliding “events” is larger than the number of independent landslides mapped. The 

second data set consists of “large slides”: those observed anywhere in the North Fork 

watershed that are 98 m3 or larger. Many of these were initially observed during the 

channel-based surveys, but most are located >15 m from a mapped channel. For both 

data sets, we estimate that volumes are accurate to better than ±25 percent. 

Management effects were evaluated separately for each data set using post-1991 

data; all land-use categories thus had experienced the same storms. Because buffer 

zones were selectively logged, they are either evaluated separately or grouped with 

logged slopes, depending on the analysis. For “streamside slide” data, the inventoried 

area includes the 15 m strip on either side of each gaged channel, while the entire 

watershed area above the weir is represented by the “large slide” data set. 

A slide is assumed to be associated with a road if it is adjacent to the road or is 

immediately downslope of a drainage outlet. Areal sliding rates from roads are 

calculated per unit area of road surface, where road areas are estimated by applying 

an average width for each road type (mainline or spur road) to the length of that road 

type present. Only half the road width along North Fork boundary ridges is included 

because half the drainage from such roads is expected to enter other watersheds. To 

compare sliding rates on roads in different vegetation types, we calculated rates of 

volume displacement per unit length of road, and the total “road-km-yr” represented 

by a road segment in a particular land class is calculated by multiplying the 

segment’s length by the time it spent in that class. Roads traversing level terrain 

(gradient <10 percent) are disregarded for this portion of the analysis. These lowgradient surfaces were delineated using aerial photographs and generally correspond 

to the ridge-top marine terraces. Spur roads on steep ridges often abut a logged slope 

on one side and a forested slope on the other; in such cases, half the segment length is 

assigned to each class. 

Cafferata and Spittler (1998) identified threshold rainfalls associated with large 

North Fork slides between 1962 and 1998, and we reevaluate thresholds to account 

for rainfall interception and transpiration. Rainfall has been monitored since 1962 at 

the SFC620 gage, located about 3 km downstream of the North Fork weir. Storms are 

identified as consecutive rain days bounded by days with <2 mm of rain and having a 

total rainfall >25 mm. The maximum 24-hr rainfall is identified for each storm using 

consecutive 1 hr rainfalls. The 2nd-growth forest at Caspar Creek intercepts and 

reevaporates 21 percent of the above-canopy rainfall (Reid and Lewis 2009), so 

subcanopy rainfall is calculated as 79 percent of the gage rainfall, while that in 

clearcuts is represented by the gage rainfall. A long-term antecedent precipitation 

index (API) is assessed for the day preceding each storm by applying a recession 

coefficient of 0.97 to calendar-day rainfalls. APIs for forested conditions are 

calculated using subcanopy rainfall, and estimated daily transpiration (Reid and 

Lewis 2009) is also subtracted. APIs of less than 0 are assigned a value of 0. 

Because gaging stations are visited at least daily during storms, failure timing is 

often known to within days. Most other slides can be attributed to particular 

sequences of storms occurring over a 2- to 3-week period, and we assume that such 

landslides occurred during the most severe storm of the sequence. 

Suspended sediment loads have been monitored at the North Fork weir since 

1962 and at the sub-watershed gages during water years 1986 through 1995; 
GENERAL TECHNICAL REPORT PSW-GTR-238 

166

measurements continue at six of these gages. Loads were originally estimated using 

sediment rating curves constructed from gravimetrically determined sediment 

concentrations. Since 1995, load estimates are refined using turbidity readings logged 

at 10 minute intervals. The potential relative importance of landsliding as a sediment 

source is evaluated by comparing rates of sediment displacement by landslides with 

annual suspended sediment loads. An estimated 50 to 75 percent of the sediment 

displaced by landslides is expected to be of small enough grain size to be carried in 

suspension, and an additional component would break down to suspendible sizes 

during transport. 

Results and discussion

Between 1985 and 2006, 91 events larger than 7.6 m3 were observed in the North 

Fork watershed, and 83 of these occurred after 1991. Of the 65 post-1991 events that 

were mapped within 15 m of gaged channels (table 1), 14 were reactivations of 

previously mapped slides, so 51 independent slides of 7.6 to 380 m3 are represented 

in the streamside slide data set, displacing 2280 m3 of sediment. “Legacy” slides that 

originated at an old splash dam or along skid roads built during old-growth logging 

of the 1800s account for 29 percent of the streamside slide volume. 

Table 1—Landslides in the North Fork Caspar Creek watershed, 1992-2006. 

Legacy Forest Buffer Logged Road Total

Streamside slides > 7.6 m3

bank km-yr 140 70.2 34.6 244.8

number of events 7 30 19 9 0 65

volume m3 670 880 520 210 0 2280

m3/km-yr 6.3 7.4 6.1 0 9.3

All slides ≥ 98 m3

km2-yr present 34.1 2.9 32.3 1.6 70.9

number of slides 2 3 1 3 4 13

volume m3 600 420 140 3620 7170 11950

m3/km2-yr 12 48 112 4480 169

Between 1992 and 2006, differences in streamside landsliding rates were 

inconsequential among treatments, with forested, buffered, and clearcut reaches 

producing averages of 6.3, 7.4 and 6.1 m3

/yr per km of channel bank, respectively 

(table 1). These results may be complicated by influences of logging on adjacent and 

downstream sites. Two forested slides were associated with blowdown along clearcut 

margins, for example, and failures along one forested reach began when increased 

runoff from upstream logging appears to have accelerated headcut retreat at the site, 

undermining adjacent banks. Events that may have been influenced by nearby 

logging account for 21 percent of the post-1991 sediment displacement from forested 

streamside slides. On average, 55 percent of the displaced sediment remained within 

the landslide scars.

Although rates of sediment displacement from streamside slides are similar 

among treatment types, associations between streamside events and potential 

destabilizing features show several differences. In forested areas, 86 percent of the 

streamside slides are associated with treefalls or undercut banks, while only 70 

percent of buffer strip slides and 33 percent of those in clearcuts show such 

associations. All streamside events at logged sites show evidence of hydrologic 
Landslides After Clearcut Logging in a Coast Redwood Forest

167

influence, either through their association with tunnel erosion or bank erosion, or, in 

one case, by mobilization of landslide debris into a short debris flow. 

Fifteen slides larger than 98 m3 (including seven also tabulated as streamside 

slides and three progressive failures) displaced about 13,500 m3 of sediment in the 

watershed between 1985 and 2006 (fig. 1); 13 of these occurred after 1991 (table 1). 

Debris flows triggered during two events accounted for 2500 m3

 through channel 

scour and undercutting of banks. In contrast to the smaller streamside slides, the post1991 rate of sediment displacement from large slides in forested areas (12 m3

/yr per 

km2

 of unlogged forest) was appreciably less than in treated areas (48 and 112 

m3

km-2yr-1 in buffer strips and on clearcut slopes, respectively). The four slides 

associated with roads after 1991 produced about 4500 m3

yr-1km-2 of road surface. For 

large slides, an average of 21 percent of the displaced volume remained on the scars.

Two large slides occurred along forested roads, contributing 16 m3

km-1yr-1 for 

the 97 road-km-yr of forest-lined road present between 1985 and 2006. Both slides 

occurred before 1992. The four large slides along road segments within logged areas 

all occurred after 1994 and together displaced an average of 53 m3

km-1yr-1 for the 

135 road-km-yr of logged road present between 1985 and 2006. The period during 

which all road types were exposed to the same storms, 1992 through 2006, showed 

no displacement for the 60 road-km-yr of forested roads present and 61 m3

km-1yr-1

for the 118 road-km-yr of logged roads. 

Logging roads in steep terrain have long been recognized to be relatively 

unstable features (for example, Swanson and Dyrness 1975), and Bawcom (2007) 

notes the prevalence of road-related slides in and near the Caspar Creek watershed. 

The distribution of slides found by the current study to be associated with North Fork 

Caspar Creek roads suggests that influences of roading and logging may interact. 

Piezometric data from North Fork hillslopes (Keppeler and Brown 1998) indicate that 

such interactions could result from hydrologic change. Measurements in a swale 

upslope and downslope of a road corridor showed little change during the winter after 

road construction, though downslope readings showed brief pore pressure spikes that 

had not been observed previously during similar storms. Piezometers above the road 

remained dry both before and after roading. However, after the swale was clearcut 

the following year, positive pressure heads developed upslope of the road and 

increased as the wet season progressed. The road prism may thus have been retarding 

subsurface drainage, but changes became apparent only after reduced transpiration 

and interception increased water inputs to subsurface storage. 

The temporal distribution of landslides in the North Fork watershed reflects a 

strong hydrologic influence. Each of the four storms that generated a total slide 

volume greater than 100 m3 in forested areas had a sub-canopy API of >180 mm, a 

sub-canopy storm rainfall >115 mm, and a maximum 24 hr sub-canopy rainfall >75 

mm (table 2). These were four of only five storms between 1985 and 2006 that 

shared these characteristics, and the fifth (December 2005) generated the largest 

landslide observed in the North Fork watershed between 1985 and 2010. 

If these subcanopy rainfall thresholds are applied to the gage record, thus 

removing the influence of rainfall interception, five additional storms surpass the 

thresholds, and three of these generated significant landsliding in logged, roaded, or 

buffered areas. A fourth predated most logging, and the fifth closely followed another 

slide-generating storm. Three other notable slide-generating storms occurred between 
GENERAL TECHNICAL REPORT PSW-GTR-238 

168

1985 and 2006 (table 2), including a major windstorm (December 1995), in which all 

slides were associated with treefalls, and two storms that strongly exceeded two of 

the three thresholds. On average, a storm surpassed all thresholds for notable sliding 

in forests once in 4 years and twice as often for notable sliding on treated slopes. 

Table 2—Storms generating numerous or particularly large landslides, 1985 to 2006. 

Storm Number Slide volume (m3) Rainfall (mm) Effective API (mm)

of slides forest treated storm 24-hr forest treated

Feb 1986 2 8 1262 310 64 149 212

Jan 1993 8 112 79 146 127 255 345

Jan 1995 9 62 1932 387 107 88 130

Mar 1995 8 67 667 267 97 120 180

Dec 1995 4 55 55 148 69 46 70

Dec 1996 7 154 28 302 104 181 249

Jan 1998 6 37 191 338 85 157 221

Mar 1998 1 103 0 189 124 242 338

Mar 1999 3 0 119 122 95 194 277

Dec 2002 5 102 2035 155 100 230 307

Dec 2005 2 0 4009 266 122 218 291

Landslide risk is likely to be affected by three prominent trends after logging. 

First, transpiration and interception rates increase once again as regrowth progresses, 

reducing the likelihood of attaining excessive pore pressures. Second, even though 

most redwood stumps quickly resprout, a proportion of the original roots die and 

begin to decay, eventually to be replaced by new roots sustained by the recovering 

foliage. The minimum root cohesion is expected about 10 to 15 years after logging (J. 

Lewis, personal communication, March 2011). Third, exposure of trees along 

clearcut margins initially increases their risk of blowdown, but early post-logging 

wind storms cull the least stable trees, and regrowth eventually reduces the margins’ 

exposure. Slides associated with blowdown along clearcut margins might thus show 

reduced frequency with time since logging.

The observed timing of failure events after logging may reflect such trends. All 

non-road-related slides at either forested or buffer strip sites after 1985 were smaller 

than 200 m3

. Plots of cumulative landslide volume against years since logging for 

slides >200 m3

 show slightly different patterns for clearcuts and buffer strips: both 

show high rates until about 8 years after logging, but slide activity resumes on 

clearcut slopes at about 13 years, while it does not do so in buffer strips (fig. 2). In 

contrast, all slides larger than 200 m3 at logged sites occurred 9 to 14 years after 

logging, when root cohesion on the logged slopes is near its minimum value but 

regrowing vegetation would ordinarily have ameliorated much of the initial 

hydrologic change. However, about 70 to 90 percent of the crown area was removed 

at these sites by pre-commercial thinning 9 to 11 years after logging, and peakflows 

had again increased to well above those expected for unlogged conditions (Lewis and 

Keppeler 2007). The largest slides thus occurred at a time when influences of both 

altered root cohesion and hydrologic change were strong. 

The association of landsliding with storms having high 24 hr and storm rainfalls 

and high APIs demonstrates the dependence of sliding on hydrologic triggers, as does 

the increased slide frequency for smaller storms after logging. However, the delay in 

occurrence of the largest slides suggests that while hydrologic influences affect the 
Landslides After Clearcut Logging in a Coast Redwood Forest

169

frequency of sliding, reduced root cohesion may provide an important influence on 

the size of the slides triggered. 

Figure 2—Cumulative landslide volume on treated sites as a function of time after 

logging. 

Annual suspended sediment yield is not significantly correlated with the volume 

of landslide sediment displaced along gaged channels between 1986 and 1995, the 

period during which all gages were operating (Reid et al. 2010). All slides that 

occurred in these sub-watersheds during the period analyzed were < 280 m3

. 

Although the average sediment displacement rate for streamside slides of 6 to 7 

m3

/km of channel bank for 2nd-order and larger channels (table 1) would amount to 

about 20 m3

km2yr-1, more than half of the sediment remains in storage on or near the 

slide scars and does not consistently contribute to the suspended sediment load. 

The largest slides, in contrast, can strongly influence short-term suspended 

sediment yields. The “Z” slide occurred in 1995 in the ungaged XYZ tributary on a 

slope logged in 1986 and thinned in 1994. Debris from the 1750 m3 failure flowed 

200 m downstream, scouring sediment from channel banks and triggering streamside 

failures to mobilize an additional 1000 m3

. Because only XYZ tributary enters the 

North Fork between the ARF gage and the North Fork weir, excess XYZ inputs can 

be estimated by comparing measured suspended sediment loads at the weir with 

those predicted using pre-slide correlations between loads at ARF and at the weir. 

Results show that the weir station recorded 1300 kg/ha (610 t) more than expected 

during 1995 to 2000 (fig. 3), and that loads had once again stabilized by 2000. The 

excess suspended sediment accounted for about 14 percent of the sediment displaced 

by the slide and debris flow, and 55 percent of the slide debris was redeposited near 

the slide scar, so about 30 percent of the displaced sediment remained within the 

channel and weir pond. The annual pre-treatment suspended sediment load averaged 

68 ± 39 t km-2yr-1 at the weir between 1963 and 1985 (incorporating a bias correction 

suggested by J. Lewis, personal communication, 2007, to adjust for the pre-1976 

sediment sampling protocol), so the slide produced the equivalent of about 2 years of 

suspended sediment yield for the 4.7 km2 watershed above the weir. 

During the 23 years that North Fork sediment loads had been monitored before 

logging began, only a 3300 m3 landslide was large enough to increase sediment 

markedly at the North Fork gage. The 1974 failure occurred on a forested inner-gorge 

slope about 2 km upstream of the weir (Rice and others 1979). Considering now only 

the extremely large slides (>2500 m3

) expected to be recognizable from suspended 

sediment records at the weir, those in the 40 km2

yr of logged area present between 
GENERAL TECHNICAL REPORT PSW-GTR-238 

170

1963 and 2006 displaced an average of 190 m3km-2yr-1, while that in the 173 km2yr of 

forest displaced 19 m3

km-2yr-1. About 25 to 50 percent of the displaced material is 

expected to be too coarse to be carried in suspension. 

Figure 3—Cumulative deviation in storm suspended sediment yields from expected 

values at the North Fork weir. The Z slide occurred in January 1995.

The mean pre-logging suspended sediment load of 68 t km-2yr-1 at the North Fork 

weir is equivalent to a volume rate of 52 m3

km-2yr-1 if a bulk density of 1.3 g cm-3 is 

assumed. The single extreme slide on undisturbed land thus could have increased the 

long-term mean suspended yield from forest lands by as much as 20 percent if 75 

percent of the displaced sediment eventually becomes suspended load. If the same 

assumptions are made for extreme landslides associated with disturbed sites, these 

slides could increase the long-term suspended sediment yield for logged areas by a 

factor of about 3.1 relative to that expected for pre-treatment conditions. In either 

case, much of the displaced sediment would be stored along downstream channels 

and become susceptible to later remobilization by bank erosion and gullying. 

Conclusions

Clearcut logging appears to have influenced landsliding in the North Fork 

watershed primarily through the increased incidence of large landslides and by 

destabilization of logged slopes adjacent to roads. Clearcutting also appears to have 

reduced the storm magnitudes required to generate landsliding. 

Logging can affect landslide incidence by decreasing transpiration and rainfall 

interception and by reducing root strength. Hydrologic conditions appear to be the 

primary influence on the generation of small to medium landslides at Caspar Creek, 

while root strength may be an important influence on landslide size. Notably, all 

slides >200 m3

 that occurred between 1986 and 2006 were associated either with 

roads, buffer strips, or clearcut slopes, and all slides >200 m3

 on logged lands 

occurred 9 to 14 years after clearcutting and within 5 years of pre-commercial 

thinning. Three destabilizing conditions were present at that time: 1) root cohesion 

would have been near its minimum value after logging as roots killed by clearcutting 

had decayed while regrowing roots were not fully developed, 2) new roots killed by 

thinning would have begun to decay, further reducing root cohesion, and 3) thinning 

would have again reduced interception and transpiration, again increasing the 

hydrologic response to storms. At sites where slope stability is of particular concern, 

it may be useful to delay thinning to a time when root cohesion has recovered more 
Landslides After Clearcut Logging in a Coast Redwood Forest

171

fully from logging so that the ensuing increase in hydrologic response does not 

coincide with the period of minimum root cohesion. 

An interaction between the topographically destabilizing presence of roads and 

hydrologic changes induced by clearcutting may be responsible for the higher 

frequency of road-related landsliding in clearcuts than in forest. In many areas, rates 

of landsliding along roads have been contrasted to rates on logged slopes, producing 

the conclusion that logging has a relatively insignificant influence on sliding. 

However, in areas where road-related instability is expressed primarily after adjacent 

slopes are logged, the distinction between “logging-related” and “road-related” 

landslides may not be particularly useful: the cumulative effect of roads and logging 

may be synergistic rather than additive. The number of slides associated with roads 

was relatively small in the North Fork Caspar Creek watershed, however, and it 

would be useful to test for interactions of roads and logging at additional sites. 

Comparison of landslide incidence with suspended sediment yields in North Fork 

Caspar Creek tributaries demonstrates that small to medium landslides have little 

short-term effect on suspended sediment yields (Reid et al. 2010), while a few 

extremely large slides can strongly influence the suspended sediment yield for the 

entire watershed. Much of the sediment generated by landsliding remains stored in 

and adjacent to channels, making it susceptible to later entrainment through bank 

erosion and gullying. Sediment inputs during small to moderate storms might thus be 

influenced by the history of past landsliding. 

Acknowledgments

This study is part of the cooperative Caspar Creek research program established 

in 1960 by the U.S. Department of Agriculture, Forest Service, Pacific Southwest 

Research Station and the California Department of Forestry and Fire Protection. We 

thank Lynn Webb, Peter Cafferata, and two anonymous reviewers for their comments 

and suggestions.

References

Bawcom, J.A. 2007. Even-aged management and landslide inventory, Jackson 

Demonstration State Forest, Mendocino County, California. In: Standiford, R.B.; 

Giusti, G.A.; Valachovic, Y.; Zielinski, W.J.; Furniss, M.J., technical editors. 

Proceedings of the redwood region forest science symposium: what does the future 

hold? Gen. Tech Rep. PSW-GTR-194. Albany, CA: U.S. Department of Agriculture, 

Forest Service, Pacific Southwest Research Station: 323-333.

Cafferata, P.H.; Spittler, T.E. 1998. Logging impacts of the 1970’s vs. the 1990’s in the 

Caspar Creek watershed. In: Ziemer, R.R., technical coordinator. Proceedings of the 

conference on coastal watersheds: the Caspar Creek story; 1998 May 6; Ukiah, CA. 

Gen. Tech. Rep. PSW-GTR-168. Albany, CA: U.S. Department of Agriculture, Forest 

Service, Pacific Southwest Research Station: 103-115. 

Keim, R.F.; Skaugset, A.E. 2003. Modelling effects of forest canopies on slope stability. 

Hydrological Processes 17: 1457-1467. 

Keppeler, E.T.; Brown, D. 1998. Subsurface drainage processes and management 

impacts. In: Ziemer, R.R., technical coordinator. Proceedings of the conference on 

coastal watersheds: the Caspar Creek story; 1998 May 6; Ukiah, CA. Gen. Tech. Rep. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

172

PSW-GTR-168. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific 

Southwest Research Station: 25-34.

Lewis, J.; Keppeler, E.T. 2007. Trends in streamflow and suspended sediment after logging, 

North Fork Caspar Creek. In: Standiford, R.B.; Giusti, G.A.; Valachovic, Y.; Zielinski, 

W.J.; Furniss, M.J., technical editors. Proceedings of the redwood region forest science 

symposium: what does the future hold? Gen. Tech Rep. PSW-GTR-194. Albany, CA: 

U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station; 95-

105. 

Reid, L.M.; Dewey, N.J.; Lisle, T.E.; Hilton, S. 2010. The incidence and role of gullies 

after logging in a coastal redwood forest. Geomorphology 117: 155-169.

Reid, L.M.; Lewis, J. 2009. Rates, timing, and mechanisms of rainfall interception loss in 

a coastal redwood forest. Journal of Hydrology 375: 459-470.

Rice, R.M.; Tilley, F.B.; Datzman, P.A. 1979. A watershed's response to logging and 

roads: South Fork of Caspar Creek, California, 1967-1976. Res. Paper PSW-RP-146. 

Berkeley, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Forest 

and Range Experiment Station. 12 p. 

Swanson, F.J.; Dyrness, C.T. 1975. Impact of clear-cutting and road construction on soil 

erosion by landslides in the western Cascade Range. Geology 3: 393-396.

Wu, T.H.; McKinnel, W.P.; Swanston, D.N. 1979. Strength of tree roots and landslides on 

Prince of Wales Island, Alaska. Canadian Geotechnical Journal 16: 19-33.
173

The Impact of Timber Harvest Using an 

Individual Tree Selection Silvicultural 

System on the Hydrology and Sediment 

Yield in a Coastal California Watershed

Arne Skaugset1, Christopher G. Surfleet2, and Brian Dietterick3

Abstract

There is still widespread concern regarding the environmental impact of timber harvest. This 

is certainly true for timber harvest activities that occur on the Swanton Pacific Ranch, the 

school forest for the California Polytechnic State University, located in Santa Cruz County, 

California. A paired watershed study was carried out to help determine the impact of 

contemporary forest practices on the hydrology and sediment yield of the Little Creek 

watershed in the Swanton Ranch. Discharge and suspended sediment were measured at two 

gauging stations, the North Fork and South Fork of Little Creek, from 2002 to 2009. The 

calibration period extended from 2002 to 2008. Timber harvest occurred in the summer of 

2008 and three storms occurred during the winter after timber harvest. During the summer of 

2009, the Lockheed Fire occurred and significant portions of both watersheds were burned, 

thus the South Fork lost its value as a control watershed. Hourly peak flows, total storm 

quickflow volume, and total storm sediment yield were analyzed for 35 storms during the 

calibration period and for the three storms that occurred during the post-harvest winter. There 

was no evidence that the timber harvest had any impact on the hydrology or sediment yield of 

the Little Creek watershed.

Key words: hydrology, sediment yield, individual tree selection

Introduction

The impact of timber harvest on the hydrology and sediment yield of forested 

watersheds is a topic of ongoing concern and study. Research results from seminal 

paired watershed studies in the Pacific Northwest (PNW) show that timber harvest 

activities do affect annual water yield (Harris 1973, Rothacher 1970, Wright et al. 

1990), peak flows (Harr et al. 1975, Jones and Grant 1996, Rothacher 1973, Ziemer 

1981), and sediment yield (Brown and Krygier 1971, Fredriksen 1970, Lewis 1998). 

These results, for the most part, chronicle the environmental impact associated with a 

bygone era. In that era the trees to be harvested were very large, roads were 

constructed commiserate with the harvest, the logging machinery was large and had a 

significant environmental footprint, and finally, there were no Best Management 

Practices (BMPs) applied. In the ensuing 3 to 4 decades forest practices have 

changed drastically. Contemporary managed forests are made up of smaller, more 

uniform, harvest-regenerated stands, the road systems exist, the logging machinery is 

smaller and has a smaller environmental footprint, most importantly, timber harvest 

 

1 Associate Professor, Oregon State University, Corvallis, OR (541)737-4952. 

(Arne.Skaugset@oregonstate.edu). 2 Research Associate, Oregon State University. 3 Director, Swanton Pacific Ranch, Cal Poly State Univ., San Luis Obispo, CA.
GENERAL TECHNICAL REPORT PSW-GTR-238 

174

activities are highly regulated and BMPs are used. This is certainly the case for the 

Swanton Ranch in Santa Cruz County, California (Piirto et al. 1999). Nonetheless, 

there is still ongoing concern regarding the environmental impact of timber harvest 

activities. The objective of this project was to investigate the impact of timber harvest 

activities in harvest-regenerated redwood stands with an individual tree selection 

silvicultural system on the hydrology and sediment yield of the Little Creek 

watershed.

Methods

Study area 

This paired watershed study was carried out in the Little Creek watershed located 

on the Swanton Pacific Ranch, which is the school forest for the California 

Polytechnic State University in San Luis Obispo. Swanton Ranch is located 18 km 

northeast of Santa Cruz near Davenport, California. The two watersheds that made up 

this study are the South Fork Little Creek (SF), which has an area of 106 ha and was 

the control watershed, and the North Fork Little Creek (NF), which has an area of 

106 ha, was the control watershed (fig. 1). 

The elevation of the study watersheds ranges from 100 to 580 m and average 

annual precipitation ranges from approximately 450 to 1400 mm from the outlet to 

the higher elevations (Gaedeke 2006). For the period of study, 2002 to 2010, the 

average annual precipitation was 875 mm at the outlet of the study watersheds to 

1060 mm on the ridgelines. The soils in the study watershed are deep to moderately 

deep, well drained to somewhat excessively drained, and have a surface layer of 

loam, sandy loam, or stony sandy loam (Bowman and Estrado 1976). The forest on 

the Swanton Ranch in lower Little Creek is a harvest-regenerated stand of redwood 

(Sequoia sempervirens) and Douglas-fir (Psuedotsuga menziesii). The stand is, 

nominally, 100 years old and before harvest has 280 ft2 of basal area, 45 mbf/ac, and 

an incremental growth of 500 bf/ac/yr. The stands are comprised of 60 percent 

redwood, 25 percent Douglas fir, and 15 percent tanoak (Lithocarpus densiflora) 

(Piirto et al. 1999). 

Timber harvest treatment

During the summer of 2008, timber harvest took place on 116 ac (47 ha) of the 

Swanton Ranch property above the gauging station on the NF Little Creek. The 

silvicultural system used was an individual tree selection system in compliance with 

the Santa Cruz County Rules of the California Forest Practice Regulations. The 

timber harvest removed 728 trees that accounted for 3,882 ft2 of basal area and 824 

mbf (gross scale) of volume. Timber harvest removed, on average, six trees per ac 

that accounted for 33 ft2 of basal area and 7,103 bf per ac. Those values represent 23 

percent of the basal area and volume in unmanaged redwood stand in lower Little 

Creek. The harvest was carried out with ground based systems, tractors, and aerial 

systems, slackline skyline. Approximately 62 percent of the volume was harvested 

with tractor systems and 38 percent was harvested with cable systems. Harvest 

operations took place, for the most part, off of existing roads. 
The Impact of Timber Harvest Using an Individual Tree Selection Silvicultural System on the 

Hydrology and Sediment Yield in a Coastal California Watershed

175

Data collection 

Precipitation was measured with four tipping bucket rain gauges located in the 

Little Creek study watersheds (fig. 1). Streamflow, turbidity, and suspended sediment 

concentration (SSC) were measured at two gauging stations located at the outlets of 

the NF and SF Little Creek for the study period (fig. 1). Pressure transducers were 

used to measure stage that was stored on data loggers and converted to discharge 

with empirical stage vs discharge relationships. Turbidity was measured with realtime, instream turbidity probes. Automatic pump samplers were used to collect water 

samples during storms that were later analyzed for suspended sediment 

concentration. Streamflow was measured year round but values of turbidity and water 

samples for SSC were taken hourly just during storms. 

Figure 1—Little Creek study watersheds, California.
GENERAL TECHNICAL REPORT PSW-GTR-238 

176

Data analysis

Three parameters were selected to use for analysis of the streamflow and 

sediment yield data; peak flow, total storm quickflow volume, total storm sediment 

yield. Gaedeke (2006) described how storms were selected from the time series 

streamflow data. Subsequent analysis of the streamflow data used his approach. Once 

a storm was defined, the peak flow is the maximum hourly flow in the storm 

hydrograph and is reported in l/s/ha. A standard hydrograph separation (Hewlett and 

Hibbert 1967) was performed to determine the total storm quickflow volume and this 

value is reported in mm. Finally, turbidity vs SSC relationships were developed so 

SSC values could be estimated. SSC in mg/l were multiplied by hourly discharge in 

l/s to give an hourly sediment discharge, which were summed to give the mass of 

sediment for the storm, expressed in kg. Unique relationships between turbidity and 

SSC were storm and watershed specific. Examples of these relationships and how 

they were developed is presented in Gaedeke (2006). 

For the calibration time period, 2002 to 2008, pairs of values from the control 

(SF) and the treatment (NF) watershed for peak flow, total storm quickflow volume, 

and total storm sediment yield were plotted. These data were not homoscedastic, thus 

a log transform was performed on the variable values to satisfy that assumption. A 

linear regression was performed on the transformed data and plotted with the data. 

Then values of the 95 percent prediction limit were calculated and added to the 

graphs. Log transform values for peak flow, total storm quickflow volume, and total 

storm sediment yield for the three storms that occurred during the post-harvest water 

year were added to the plots. The location of the post-treatment data points relative to 

the 95 percent confidence limits were used to evaluate if a statistically significant, 

post treatment effect occurred the first winter after timber harvest.

During the summer of 2009 the Lockheed Fire occurred. Significant portions of 

the NF and SF of Little Creek were involved in that fire. The SF Little Creek no 

longer had value as a control watershed for the study. Thus, no further post-harvest 

data are available.

Results

The data set that was analyzed for this study consisted of 38 storms that occurred 

between December 2002 and March 2009. Of these 38 storms, 35 occurred during the 

calibration period between December 2002 and February 2008. Three storms 

occurred during WY 2009 after timber harvest was carried out. 

For the calibration period for the SF Little Creek, the control watershed, the 

average peak flow was 1.08 l/s/ha and the values ranged from 3.46 to 0.13 l/s/ha. The 

three peak flows for the post logging period were 0.39, 1.34, and 1.02 l/s/ha for an 

average of 0.92 l/s/ha. For the calibration period for the NF Little Creek, the 

treatment watershed, the average peak flow was 1.28 l/s/ha and the values ranged 

from 4.79 to 0.14 l/s/ha. The three peak flows for the post logging period were 0.49, 

1.53, and 0.86 l/s/ha for an average of 0.96 l/s/ha. All three of the peak flows that 

occurred after logging during WY 2009 were within the variability exhibited by the 

population of calibration peak flows (fig. 2a). There was no observed impact of the 

timber harvest on peak flows.
The Impact of Timber Harvest Using an Individual Tree Selection Silvicultural System on the 

Hydrology and Sediment Yield in a Coastal California Watershed

177

For stormflow volumes the control watershed, the SF Little Creek, for the 

calibration period had an average of 16.2 mm and the values ranged from 67.5 to 0.2 

mm. The three storms for the post logging period had quickflow volumes of 0.6, 

11.8, and 9.9 mm for an average of 7.4 mm. For the treatment watershed, the NF 

Little Creek, for the calibration period storm quickflow averaged 11.1 mm and the 

values ranged from 51.4 to 0.4 mm. The three storms in the post logging period had 

quickflow volumes of 0.2, 14.5, and 10.5 mm for an average of 8.3 mm. Once again, 

the values of storm quickflow for the three post logging storms fell within the 

variability exhibited by the calibration data (fig. 2b). There was no observed impact 

of timber harvest on storm quickflow volumes. 

For total storm sediment yield the SF Little Creek, the control watershed, for the 

calibration period had and average of 31.8 kg/ha and a range from 396 to 0.1 kg/ha. 

The three storms for the post logging period had total storm sediment yields of 4.9, 

64.9 and 9.5 kg/ha for an average of 26.4 kg/ha. For the treatment watershed, the NF 

Little Creek, for the calibration period the total storm sediment yield averaged 35.9 

kg/ha and ranged from 331 to 0.1 kg/ha. The three storms during the post logging 

period had total storm sediment yields of 0.3, 5.2, and 1.5 kg/ha for an average of 2.3 

kg/ha. The total storm sediment yield from the post logging period fits well within 

the variability exhibited by the calibration data (fig. 2c). There was no observed 

impact of timber harvest on total storm sediment yield.

Discussion

It should not be surprising that there is no detectable impact of the timber harvest 

that occurred in the NF Little Creek in 2008 on the hydrology and sediment yield of 

the NF the first winter after logging. The reasons for this are the scale and intensity of 

the timber harvest operations in the NF Little Creek watershed. In published results 

from the seminal watershed studies the size of the treatment watersheds were often 

very small, 70 to 101 ha, compared to the size of the NF Little Creek watershed, 291 

ha (Brown and Krygier 1971, Rothacher 1970). The Caspar Creek study watersheds 

had comparable sizes, 508 and 425 ha (Lewis 1998). 

But more important than the scale of the timber harvest activities is the intensity. 

In all of the seminal paired watershed studies the silvicultural system was clearcut 

and the percent area affected ranged from 30 to 100 percent (Brown and Krygier 

1971, Fredriksen 1971). The exception, again, is the Caspar Creek study where the 

South Fork was harvested with an individual selection system but 100 percent of the 

area supported operations and 59 percent of the volume was removed (Lewis 1998). 

The silvicultural system for the NF Little Creek was individual tree selection, harvest 

operations were conducted on only 20 percent of the area above the gauging station 

and only three percent of the volume and basal area of the forest above the gauging 

station was removed.

Bosch and Hewlett (1982) report that it takes removal of forest canopy on at least 

20 percent of the area of a watershed to detect an impact on annual water yield. 

While this analysis did not investigate annual water yield, the 3 percent volume and 

basal area removed is well below the published threshold of 20 percent. The scale 

and intensity of the harvest operations essentially precluded a significant effect on 

hydrology. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

178

a 

b 

c 

Figure 2—Three graphs showing data for the control (SF) vs the treatment (NF) 

watersheds for the pre-treatment and post-treatment data for a) hourly peak flows, b) 

total storm quickflow, and c) total storm sediment yield.
The Impact of Timber Harvest Using an Individual Tree Selection Silvicultural System on the 

Hydrology and Sediment Yield in a Coastal California Watershed

179

There is a concern that given the paucity of post-harvest data this study may not 

give a true test of the impact of the forest practices used in the NF Little Creek on the 

hydrology and sediment yield of the watershed. This is not the case. While there are 

differing opinions regarding the impact the timber harvest on peak flows, those 

differing opinion are usually with regard to large peak flows (Grant et al. 2008). 

There is widespread agreement that timber harvest can and does affect small peak 

flows (Ziemer 1981) or the peak flows that may occur many times a year, the first 

winter after timber harvest occurs. The mean annual flood (MAF) for the NF Little 

Creek during the period of record, was 1.94 l/s/ha and the three post harvest peak 

flows, 0.49, 1.53, and 0.86 l/s/ha, were all below the value of the MAF. These are the 

size flows that could and should be affected by timber harvest the first winter after 

logging occurs. These flows represent an excellent opportunity to evaluate the impact 

of timber harvest on the hydrology of a watershed. 

While the scale and intensity of the harvest combined with the size of the postharvest peak flows may help explain the lack of an impact to the hydrology of the NF 

Little Creek, it doesn’t necessarily explain away the lack of significance in the 

sediment yield data. It does explain part of the lack of significance in the sediment 

yield data because sediment yield and streamflow are very tightly correlated. In all of 

the seminal paired watershed studies an increase in sediment yield was always 

accompanied by an increase in water yield and storm flow. However, the degree that 

the increased sediment yields are a function of increased stream power versus an 

increase in the erosion rate of the watershed has never been fully investigated. 

Nonetheless, the two harvest entries for the Caspar Creek Watershed Study did 

conclusively exhibit the importance of contemporary Best Management Practices in 

mitigating increases in sediment yield associated with timber harvest. Accelerated 

erosion associated with timber harvest was reduced by roughly an order of magnitude 

when contemporary BMPs were used in the 1990s compared with the practices used 

in the 1960s and 1970s. A compelling hypothesis to put forward is that the 

combination of the reduced scale and intensity of timber harvest activities in 

conjunction with the use of contemporary BMP’s resulted in levels of accelerated 

erosion, which must occur, that remained within background variability.

Conclusion

Hourly peak flows, total storm quickflow volume, and total storm sediment yield 

were analyzed for 35 storms that occurred prior to timber harvest activities and three 

storms that occurred during the winter after timber harvest occurred. There is no 

evidence in any of the results that the timber harvest activities had any impact on the 

hydrology or sediment yield of the NF Little Creek watershed. This finding should 

not be surprising given the scale and intensity of the timber harvest activities. Timber 

harvest removed only about two percent of the basal area in the NF Little Creek 

watershed above the gauging station effectively negating a discernable impact on the 

hydrology. It is hypothesized that in the absence of a significant impact on the 

hydrology, the forest practice regulations and BMP’s were effective in keeping the 

accelerated erosion, which must occur, within background variability. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

180

Acknowledgments

This research was supported by a grant from the California State University 

Agricultural Research Institute. Data from Little Creek was provided by the students 

of California Polytechnic State University San Luis Obispo, Swanton Pacific Ranch; 

specifically we thank Drew Loganbill, Drew Perkins, and Michael Gaedeke. We 

would also like to thank Steve Auten for information regarding the 2008 timber 

harvest in Little Creek.

References 

Bosch, J.M.; Hewlett, J.D. 1982. A review of catchment experiments to determine the 

effect of vegetation changes on water yield and evapotranspiration. Journal of 

Hydrology 55: 3-23.

Brown, G.W; Krygier, J.T. 1971. Clear-cut logging and sediment production in the 

Oregon Coast Range. Water Resources Research 7: 1189-1198.

Fredriksen, R.L. 1970. Erosion and sedimentation following road construction and timber 

harvest on unstable soils in three small western Oregon watersheds. Res. Pap.PNW104. Corvallis, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest 

Forest and Range Experiment Station. 15 p.

Gaedeke, M.C. 2006. Preharvest calibration of the Little Creek watershed a paired and 

nested watershed analysis. San Luis Obispo, CA: California Polytechnic State 

University. M. S. thesis. 116 p.

Grant, G.E.; Lewis, S.L.; Swanson, F.J.; Cissel, J.H.; McDonnell, J.J. 2008. Effects of forest

practices on peak flows and consequent channel response: a state-of-science report 

for western Oregon and Washington. Gen. Tech. Rep. PNW-GTR-760. Corvallis, OR: 

U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 74 

p.

Harr, R.D., Harper, W.C.; Krygier, J.T.; Hsieh, F.S. 1975. Changes in storm hydrographs 

after road building and clear-cutting in the Oregon Coast Range. Water Resources 

Research 11: 436-444.

Harris, D. D. 1973. Hydrologic changes after clear-cut logging in a small Oregon coastal 

watershed. U. S. Geological Survey Journal of Research 1: 487-491.

Hewlett, J.D.; Hibbert, A.R. 1967. Factors affecting the response of small watersheds to 

precipitation in humid areas. In: Sopper, W.E.; Lul, H.W., editors. International 

symposium on forest hydrology. Oxford: Pergamon Press: 275-290.

Jones, J.A.; Grant, G.E. 1996. Peak flow responses to clearcutting and roads in small and 

large basins, western Cascades, Oregon. Water Resources Research 32: 959-974.

Lewis, J. 1998. Evaluating the impacts of logging activities on erosion and suspended 

sediment transport in the Caspar Creek watersheds. In: Ziemer, R.R., technical 

coordinator. Proceedings of the conference on coastal watersheds: the Caspar Creek 

story. Gen. Tech. Rep. PSW-GTR-168. Albany, CA: U.S. Department of Agriculture, 

Forest Service, Pacific Southwest Research Station: 55-69.

Piirto, D.D.; Thompson, R.P.; Piper, K.L. 1999. Implementing uneven-aged redwood 

management at Cal Poly’s school forest, an update.

http://www.spranch.org/files/piiroetal/1999.pdf.
The Impact of Timber Harvest Using an Individual Tree Selection Silvicultural System on the 

Hydrology and Sediment Yield in a Coastal California Watershed

181

Rothacher, J. 1970. Increases in water yield following clear-cut logging in the Pacific 

Northwest. Water Resources Research 6: 653-568.

Rothacher, J. 1973. Does harvest in west slope Douglas-fir increase peak flow in small 

forest streams? Res. Pap. PNW-163. Portland, OR: U.S. Department of Agriculture,

Forest Service, Pacific Northwest Forest and Range Experiment Station. 13 p.

Wright, K.A.; Sendek, K.H.; Rice, R.R.; Thomas, R.B. 1990. Soil logging effects on 

streamflow: storm runoff at Caspar Creek in northwestern California. Water 

Resources Research 26: 1657-1667.

Ziemer, R.R. 1981. Storm flow response to road building and partial cutting in small 

streams of northern California. Water Resources Research 17: 907-917.

183

Summer Water Use by Mixed-Age and 

Young Forest Stands, Mattole River, 

Northern California, U.S.A. 

Andrew Stubblefield1, Max Kaufman1, Greg Blomstrom2, and John 

Rogers3

Abstract

Resource managers have noted a decline in summer flow levels in the last decade in the 

Mattole River watershed, Humboldt County, California. Reduced river flows pose a threat to 

endangered coho and chinook salmon in the watershed, as stream heating is inversely 

proportional to discharge. While the cause of the reduced flow is unclear, several factors have 

been cited: increased groundwater pumping from residential development in the area, regional 

climate shifts tied to global warming, and the recovery of forest cover after widespread 

deforestation in the 1950s and 1960s. The goal of this project was to gain insight into the 

effect of stand age and composition on forest water consumption. Quantitative information on 

tree and stand level transpiration was collected in order to inform comprehensive hydrologic 

budgets being developed for the Mattole River watershed under existing conditions and 

resulting from prospective forest management activities. Granier thermal dissipation probes 

were inserted into 18 Douglas-fir (Pseudotsuga menziesii) trees in mixed and even-aged 

stands in order to record water use over the course of the 2008 summer dry season. Trees 

ranged in size from 10 to 91 cm diameter at breast height (DBH). A tight relationship was 

found between sapwood area (cm2

) and water use (liters/season, y = 7.68x – 638.6, r2 = .86). 

Strong positive relationships were also found between DBH (cm) and water use (y = 92.40x – 

1068.4, r2 = .90), and for basal area (cm2

) and water use (y = 1.261x + 241.57, r2 = .94). The 

relationship between basal area and water use was much steeper for the youngest trees (y = 

3.42x – 233.15. r2 = .76), indicating a steep increase in water use with increasing tree size at 

the lower end of the size range. This information was used to model stand level water use 

with the current composition and under future scenarios using Forest Vegetation Simulator. 

Results indicate that the water use of Mattole River forests will decline in coming decades as 

the high numbers of young (< 5 cm DBH) trees decline from canopy closure and stem 

suppression.

Key words: sapflow, transpiration, Pseudotsuga menziesii, forest management, water balance, 

coastal California, Forest Vegetation Simulator.

Introduction

Resource managers have noted a decline in summer flow levels in the last decade 

in the Mattole River watershed, northern California, U.S.A. (fig. 1). While the cause 

of the reduced flow is unclear, several factors have been suggested: increased 

groundwater pumping from residential development in the area, regional climate 

shifts tied to global climatic disruption and the recovery of forest cover after 

 

1 Professor and Graduate Student, respectively, Department of Forestry and Wildland Resources, 

Humboldt State University, Arcata, CA 95521. (aps14@humboldt.edu; jedi717@gmail.com). 2 Consulting Forester, Baldwin, Blomstrom, Wilkinson and Associates, Arcata, CA 95521.

3 Director, Institute for Sustainable Forestry, Redway, CA 95560.
GENERAL TECHNICAL REPORT PSW-GTR-238 

184

widespread deforestation in the 1950s and 

1960s. Reduced flows pose threats to 

aquatic conditions as the amount of stream 

heating is inversely proportional to 

discharge. Tributary drainages have gone 

completely dry in recent summers, or been 

limited to isolated pools. Mattole River 

salmonid populations are declining for 

three threatened species under the U.S. 

Endangered Species Act: coho salmon 

(Oncorhynchus kisutch), chinook salmon 

(O. tshawytscha), and steelhead trout (O. 

mykiss). 

The goal of this research is to gain 

insight into the effect of stand age and 

composition on forest water consumption. By collecting quantitative information on 

tree and stand level transpiration we hope to inform comprehensive hydrologic 

budgets being developed for the Mattole River watershed under existing conditions 

and resulting from prospective forest management activities.

To examine water use for trees of different size and stands of different 

composition we instrumented 11 trees in a young stand and seven trees in an adjacent 

mature stand with thermal dissipation probes. We then used relationships between 

tree size and water use in conjunction with outputs from the forest growth model 

Forest Vegetation Simulator (Dixon 2002) to estimate changes in stand water use as 

the trees mature, canopy closure and stem exclusion processes take place. Given the 

tight relationship between leaf area index and sapwood area observed by other 

researchers (Waring et al. 1982) we hypothesized that larger dominant trees found in 

the mature stand would show greater maximum transpiration rates, daily and seasonal 

water consumption levels than younger trees and suppressed, understory trees, but 

that on a stand basis, water use would be reduced in mature stands because of lower 

numbers of stems per acre. 

Study area

The study was conducted at two adjacent sites near Ettersberg, California in the 

Mattole Watershed, Humboldt County (40°9′ Ν, 123°59′ W, elevation ~300 m).

Dominant tree species were Douglas-fir (Pseudotsuga menziesii), tanoak 

(Lithocarpus densiflora), and pacific madrone (Arbutus menziesii). Stands were 

located midslope, with SE aspect. Southern Humboldt County has a Mediterranean 

climate with cool rainy winters and hot dry summers. Average annual precipitation is 

110 cm. 

The first site was a mature stand composed of large Douglas-fir (61 to 91 cm 

Diameter at Breast Height (DBH)) with a mid story of tanoak in the larger size 

classes (30 to 46 cm DBH), and an understory of smaller tanoak and suppressed 

Douglas-fir. The stand was closed except to the east, which was bordered by a dirt 

road. The second site was a densely stocked with small Douglas-fir (10 to 25 cm 

DBH) with occasional larger black oak and pacific madrone, and a small component 

of tanoak. This stand was estimated to be 20 years old. The canopy was closed. 

Figure 1—Study site location, Mattole 

River watershed, California.
Summer Water Use by Mixed-Age and Young Forest Stands, Mattole River, Northern California, 

U.S.A.

185

Materials and methods

The technique used for this study was measurement of individual tree water use 

with thermal dissipation probes (Granier 1985). In this method pairs of probes are 

inserted in predrilled holes in the xylem of the tree bole. The probes are linked to 

dataloggers which continually record temperature. The upper probe of each pair is 

heated. The lower probe serves as a reference. The rate of sap flowing through the 

hydroactive xylem is determined by the amount of cooling of the heated probe 

relative to the reference probe. 

The method has been validated by comparison with other techniques such as heat 

pulse methods (Swanson 1994), gravimetric measurements of pot-grown saplings 

(McCulloh et al. 2007), and micrometeorological flux measurements (Kostner et al.

1998). Thermal dissipation probes have been used in a numerous applications since 

their development. Examples include evaluating sapflow in Douglas-fir stands 

(Moore et al. 2004) and scots pine and spruce stands (Granier et al. 1996). 

TDP-80 probes (Dynamax, Inc., Houston, Texas) were used at the mature stand. 

Instrumented trees are described in table 1.The probes consist of 80 mm hypodermic 

needles fitted with copper-constantan thermocouples. They are inserted into 

predrilled holes in the sapwood in pairs with an upper probe 40 mm above a lower 

probe. The upper probe has a constantan heating wire in addition to the thermocouple 

wire. The lower probe acts as a reference probe, giving the temperature of the 

sapwood without heating. The temperature difference between the needles is at its 

greatest when sap flow velocity is minimal and as flow increases the upper needle 

cools and the difference in temperature decreases. This temperature difference is 

recorded with Campbell Scientific 1000x Dataloggers (Campbell Scientific Inc, 

Logan, Utah). The TDP-80 probes have two thermocouples mounted in each probe, 

allowing for measurement of temperature changes at two depths within the sapwood.

TDP-30 and TDP-50 probes were used at the young stand. These probes are a more 

appropriate length for smaller trees with thinner sapwood (30 mm and 50 mm needles 

respectively) and have only one thermocouple per needle. 

 Average sap flow velocity V (cm/s) is calculated from the expression: 

 V = 0.0119*K^1.231 

where the dimensionless parameter K is:

 K = (∆Tm – ∆T)/∆T

∆T is the measured difference in temperature between the heated probe and the 

reference probe. ∆Tm is the maximum value of ∆T when there is no sap flow. 

(Grenier 1987).

 Detailed observations have indicated that when a portion of the probe is inserted 

into inactive xylem, heat is attenuated more slowly, introducing a bias into probe 

readings (Clearwater et al. 1999). To adjust for this bias, a correction factor was used 

when the probe lengths were longer than the measured sapwood depth. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

186

The recommended correction factor (Clearwater and others 1999) is: 

∆Tsw = (∆T – b∆Tm) / a 

where ∆Tsw is the change in temperature of the sapwood, ∆T is the recorded change 

in temperature of the probe relative to the reference probe, ∆Tm is as defined above, 

a is the proportion of the probe in active xylem, and b is the proportion of the probe 

in inactive xylem.

The correction factor was not applied for the 80 mm probes as they have two sensors 

within the probe, one at 15 mm and one at 70 mm. Sap velocity (cm/s) is converted to 

sap flow rate (cm3

/s) by multiplying by the sapwood area of the tree, determined by 

coring techniques. The flow rate is then converted to volumes by summation of rates 

over the time period of interest. 

Thermal shielding was installed to insulate the probes from direct sunlight. Two 

48 hr power-down tests were conducted in which the heating elements were turned 

off to verify that the probes were properly insulated, with minimal heating from solar 

radiation. Probe readings were taken every 60s with the mean value recorded every 

Table 1—Characteristics of trees instrumented with sapflow 

sensors, Mattole River watershed, California, 2008.

Species*

Dia. at 

breast ht 

(cm)

Sapwood 

cross 

section 

(cm2

) 

Basal 

area 

(cm2

) 

Probe length#

(cm)

Douglas-fir 9 52 66 5

Douglas-fir 12 67 107 5

Douglas-fir 12 78 117 3

Douglas-fir 14 95 148 8

Douglas-fir 16 139 195 3

Douglas-fir 18 166 241 5

Douglas-fir 19 190 277 5

Douglas-fir 19 227 293 5

Douglas-fir 20 207 324 5

Douglas-fir 27 401 569 5

Douglas-fir 37 270 1051 8

Douglas-fir 42 397 1413 8

Douglas-fir 55 685 2364 8

Douglas-fir 76 771 4591 8

Douglas-fir 90 1023 6422 8

tanoak 38 865 1110 8

tanoak 52 1490 2088 8

*Douglas-fir (Pseudotsuga menziesii), tanoak (Lithocarpus densiflorus).

#Trees with 3 and 5 cm probes had one sensor per probe and one probe 

was placed in each tree. Trees with 8 cm probes had two sensors per probe, 

and two probes per tree. 
Summer Water Use by Mixed-Age and Young Forest Stands, Mattole River, Northern California, 

U.S.A.

187

30m on dataloggers equipped with 32-channel multiplexers (CR1000, Campbell 

Scientific, Inc., Logan, UT). 

Sapwood area was determined for each tree by the following procedure. Tree 

DBH was measured with a tape. The thickness of the bark was subtracted from the 

DBH. The thickness of the sapwood was determined by radial increment boring. 

Water conducting vascular tissue was identified by semi-translucent properties. Once 

the radius of the tree and the radius of the sapwood were measured, the radius of the 

heartwood could be estimated and the following equation applied: 

SA = π (RT

2

 – RH

2

) 

where SA is sapwood area, RT is radius of tree (without bark) and RH is radius of 

heartwood. 

Basal area (BA) was calculated for all plots using tree diameter and the plot 

expansion factor for a 1⁄2 ha (1/5th ac) circular plot to get total BA/ac (cm2

). All trees 

were tallied within the plot. Species, diameter, and crown ratio were collected on 

every tree. 

Continuous data was collected at 30 min intervals from July 6 to October 8, 

2008. Data was summed into 24 hr daily totals. Daily totals were summed to create 

growing season totals for the period. Regression equations were developed between 

growing season water use and tree diameter, sapwood diameter and basal area. Sap 

flux density was calculated by converting liters to kg water, then dividing by 

sapwood basal area (m2

).

The next step was to generate estimates of seasonal water use for representative 

stands of the Mattole River watershed moving forward through time. A 

representative stand was created for a year 2005 starting point using an average 

created from four Forest Inventory Analysis plots (FIA). FIA is the U.S. Department 

of Agriculture’s national forest inventory program (Woudenberg et al, 2010). The 

stand composition was then modeled through time using the U.S. Department of 

Agriculture, Forest Service Forest Vegetation Simulator (FVS, Dixon 2010). Output 

was generated for 20 size classes (0 to 101 cm) of DBH at 5 year increments for the 

period 2005 to 2055. Output used for this study included average DBH within each 

size class, trees/ha, and basal area/ha. FVS output was then used to estimate total 

growing season water use for each age class at each 5 year increment using the 

regression equation developed for basal area. 

Results
GENERAL TECHNICAL REPORT PSW-GTR-238 

188

Sapflow was observed to rise 

and fall with solar radiation 

levels. Representative samples 

of the daily continuous and 

weekly data for individual trees 

are shown in fig. 2 and 3

respectively. A steady decline in 

transpiration was observed over 

the course of the season as soil 

moisture declined. This matches 

a drawdown in discharge in the 

Mattole River (fig. 3). The first 

rainstorm of the fall (Oct 2, 

2008) caused a spike in

transpiration readings. Total 

water use for each tree over the growing season is shown in table 2. A tight 

relationship was found between Douglas-fir sapwood area and water use (y = 

7.6861x – 638.59, r2

 = .86). Strong positive relationships were also found between 

Douglas-fir diameter at breast height (DBH, cm) and water use (y = 92.397x - 

1068.4.4, r2

 = .90), and for basal area (cm2) and water use (y = 1.2611x +241.57, r2 = 

.94). Regressions were also strong when the smaller trees in the young stand were 

analyzed separately. The relationship between basal area and water use was steeper 

for the young stand than for the larger trees (y = 3.423x – 233.15, r2 = .76) indicating 

a steep increase in water use with increasing tree size at the lower end of the size 

range. To compare water use by tree size, seasonal water use for each tree was 

divided by the basal area of the tree. A higher range of water use was found for the 

smaller trees, as compared to the higher end of the size range. Trees below 30 cm 

DBH had an average water use/ unit basal area of 2.2 (± 1.2) l per cm2

, while trees 

larger than 30 cm DBH averaged 1.2 (± 0.5) l per cm2

. Mean sap flux density ranged 

from 123 to 976 kg per m2

 per day. A linear trend was not observed between 

sapwood area and mean sap flux density. 

Figure 3—Sapflow in mature Douglas-fir over the 2008 

growing season and Mattole River discharge. M1 to M4 refer to 

individual trees.

Figure 2—Daily sapflux, June 6 to17, 2008, 

Mattole River watershed.
Summer Water Use by Mixed-Age and Young Forest Stands, Mattole River, Northern California, 

U.S.A.

189

Table 2—Water use in instrumented trees, Mattole River watershed, June 25 to 

October 8, 2008.

Basal area

(cm2) 

Season water use

(liters)

Water use per unit

basal area

(liter cm-2)

Sap flux density

(kg m-2 d-1) 

Douglas-fir (Pseudotsuga menziesii)

66 150 2.3 307

107 291 2.7 462

117 122 1.0 166

148 133 0.9 149

195 415 2.1 318

241 458 1.9 294

277 219 0.8 123

293 1415 4.8 663

324 711 2.2 365

569 1786 3.1 474

1051 2476 2.4 976

1413 2343 1.7 628

2364 2038 0.9 317

4591 5383 1.2 743

6422 8948 1.4 931

Tanoak (Lithocarpus densiflorus)

1110 1817 1.6 223

2088 5849 2.8 418

There were not sufficient instrumented tanoak trees to create independent 

regressions. The data from the two tanoak trees appears to follow the general linear 

relationship of the Douglas-fir. Adding the two data points to the Douglas-fir data 

changes the regression equation only minimally (y = 1.312x + 355.52, r2 = 0.87). 

The initial forest species composition for 2005, determined from FIA plots, 

indicates a dominance by small Douglas-fir and tanoak trees (10 to 30 cm DBH), 

with a few larger pacific madrone (20 stems per ha). Figure 4 shows basal area. 

Forest Vegetation Simulator runs indicated a rapid attainment of canopy closure 

and stem suppression with a steep drop off in individual tree numbers over time. For 

example in the smallest size class (0 to 5.1 cm DBH), Douglas-fir drops from 525 to 

95 trees per ha by 2055, and tanoak drops from 1929 to 887 trees per ha by 2035. As 

would be expected, a gradual increase in basal area is observed for surviving trees. 

These trends are reflected in estimates of stand water use over time generated 

from applying water use data from this study to the Forest Vegetation Simulator 

output for future stand conditions. A drop in overall water use was shown for 

Douglas-fir species (489 to 385 m3

 per ha, table 3). This decrease resulted directly 

from the greatly reduced numbers of young trees. While mid and larger sized trees 

increased their water use over the time period, they were a much smaller proportion 

of total water use, so their impact was minimal. For example, summing the water use 

of the smallest four size classes (0 to 15 cm, DBH) we find a decrease over 50 years 

from 127 to 23 m3 per ha, while the largest four size classes (86 to 102 cm, DBH) 

increased from 65 to 101 m3

 per ha. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

190

Similar results were found for the tanoak and Douglas-fir. While water use of 

larger trees increases, its effect is eclipsed by the decrease in water use from stem 

suppression of younger trees. Overall water use drops from 2188 to 1506 m3

 per ha 

over the season. The largest trees increase water use from 46 to 170 m3

 per ha, while 

the smallest trees decrease from 813 to 23 m3

 per ha. 

Discussion

Thermal dissipation probes were successfully used to quantify individual tree 

water use over the growing season, June to October, 2008. The October spike in 

water use resulting from a rainstorm indicates the sensitivity of tree growth to soil 

moisture and indicates the sensitivity of the method to fluctuations in tree growth. 

This was also observed by correlation of solar radiation measurements to measured 

sapflow: it decreased during cloudy days. Mean sap flux density values closely match 

values measured by Moore et al. (2004) for similar-aged Douglas-fir in western 

Oregon. 

A tight relationship was found between measures of tree size: basal area, DBH, 

sapwood area, and tree water use. Previous research (Kostner et al. 1998) indicates 

that the number of trees measured were sufficient to characterize stand variability for 

Douglas-fir but not for tanoak. The high r2 values of the regressions are evidence that 

the variability of individual tree water use was sufficiently captured by the size of the 

sample.

Figure 4—Mattole River watershed forest composition, basal area by DBH size class.
Summer Water Use by Mixed-Age and Young Forest Stands, Mattole River, Northern California, 

U.S.A.

191

Individual tree water use was then combined with forest growth model 

predictions to estimate water use under future conditions. The predicted changes in 

forest vegetation should be accurate and representative of the Mattole as the input 

conditions were from four standard Forest Inventory Analysis plots surveyed in the 

watershed, the FVS model has been widely applied and validated, and was run by 

experienced practitioners. 

The model assumes a stable climate, no thinning or harvest activity, and lack of 

major disturbance such as fire, windstorm or severe disease outbreak. If we make 

these assumptions for the purposes of isolating the impact of forest vegetation on 

water yield, the model output points to two strong and competing trends in forest 

composition that would stand drive water use. The first is the growth of the stand. We 

have shown a linear increase in water use with tree size. As the stands age over the 

next fifty years they will be composed of larger trees and might thus be expected to 

use more water. The second trend is stem suppression. As the trees grow the canopy 

Table 3—Growing season water use in Douglas-fir 

estimated from sapflow measurements and Forest 

Vegetation Simulator output, Mattole River watershed, 

2005 to 2055.

Size 

Class 

(cm)

2005 2015 2025 2035 2045 2055

0.0 127 97 69 34 28 23

5.1 47 29 22 33 26 20

10.2 83 76 54 8 5 1

15.2 37 30 43 76 36 15

20.3 28 34 25 23 53 47

25.4 12 30 27 24 13 31

30.5 17 11 24 22 20 16

35.6 26 16 11 20 27 15

40.6 14 31 27 17 15 31

45.7 9 10 24 25 21 16

50.8 0 16 14 23 25 2

55.9 0 0 11 24 26 2

61.0 3 0 8 4 23 40

66.0 6 3 0 8 5 15

71.1 3 4 4 5 10 3

76.2 8 6 2 2 6 15

81.3 4 10 6 3 1 5

86.4 14 4 10 7 4 2

91.4 5 15 13 12 7 4

96.5 0 4 12 16 15 0

101.6 46 48 51 62 79 95

TOTAL 489 474 456 448 445 395
GENERAL TECHNICAL REPORT PSW-GTR-238 

192

closes and the trees begin to compete for available light. Suppressed trees eventually 

die out. The current composition of high numbers of very small (<5 cm DBH) trees 

indicates that the total number of trees will drop substantially in coming decades. 

Our results strongly support the conclusion that stem suppression will be the 

dominant trend affecting water use in the Douglas-fir dominated portions of the 

Mattole river watershed. Water use will be expected to decline in a steady fashion as 

the number of trees declines. A further implication of this finding is that clearcut 

harvesting of existing stands would not be beneficial for water yield in the basin 

beyond the initial regeneration period. It would result in a new crop of dense small 

trees, and delay the stem exclusion stage that much longer. Selective harvest of small 

and mid size trees might be expected to increase water yields without producing a 

thicket of young trees if remnant trees were able to quickly grow into the light gaps. 

The results are less conclusive regarding tanoak which is the more dominant 

species in the Mattole River watershed because only two trees were instrumented. 

The two trees had similar mean sap flux density values as the Douglas-fir. The water 

use predictions made using the basal area regression that included tanoak would 

indicate that stem suppression is also the dominant process affecting water yield for 

this species over the next fifty years. The numbers of small tanoak in the watershed 

are quite high. 

One way to assess the robustness of this conclusion is to test the sensitivity of the 

conclusion to input assumptions. To perform this sensitivity test we increased the 

water yield slope by 50 percent for tanoak (from 1.3123x + 355.52 to 1.968x + 

355.52) and then looked at resulting water use predictions for the whole stand over 

the period 2005 to 2055. The water yield continued to show a decrease over this time 

period (1927 to 1439 m3

 per ha) as compared to the original (1699 to 1111 m3 per 

ha). 

Previous research supports our finding of diminished water use with stand age. A 

sapflow study in western Oregon (Moore et al. 2004) determined that young mature 

Douglas-fir stands (40 yr) had 3.27 times higher water use than old growth Douglasfir (450 yr) stands for a similar time period (June to October, 2000). They attributed 

this difference to greater sapwood area per unit basal area and greater sap flux 

density in the younger stand, as well as greater numbers of mesic angiosperms. 

Phillips et al. (2002) found reduced hydraulic conductance in older Douglas-fir 

stands as compared to young and mature trees. 

Conclusions

Sapflow measurements in the Mattole River watershed show strong relationships 

between total seasonal tree water use and basal area, DBH and sapwood basal area 

for Douglas-fir. Water use measurements combined with stand growth modeling 

indicate that the water use of Mattole River forests will decline in coming decades as 

the high numbers of young (< 5 cm DBH) trees decline from canopy closure and 

stem suppression. Decreased water use is expected to have beneficial effects on 

aquatic ecosystems. 

References
Summer Water Use by Mixed-Age and Young Forest Stands, Mattole River, Northern California, 

U.S.A.

193

Clearwater, M.J.; Meinzer, F.C.; Andrade, J.L.; Goldstein, G.; Holbrook, N.M. 1999. 

Potential errors in measurements of nonuniform sap flow using heat dissipation 

probes. Tree Physiology 19: 681-687.

Dixon, G.E., compiler. 2002. Essential FVS: a user's guide to the forest vegetation 

simulator. Internal Report. Fort Collins, CO: US Department of Agriculture, Forest 

Service, Forest Management Service Center. 193 p.

Granier, A. 1985. Une nouvelle methode pour la mesure du flux de seve brute dans le 

tronc des arbres. Annales des Sciences Forestiers 42:81-88.

Granier, A.; Biron, P.; Breda, N.; Pontailler, J.Y.; Saugier, B. 1996. Transpiration of trees 

and forest stands: short and long term monitoring using sapflow methods. Global 

Change Biology 2: 265-274.

Kostner, B.; Granier, A.; Cermak, J. 1998. Sapflow measurements in forest stands: 

methods and uncertainties. Annales des Sciences Forestiers 55: 13-27.

McCulloh, K.A.; Winter, K.; Meinzer, F.C.; Garcia, J.A.; Lachenbruch, B. 2007. A 

comparison of daily water use estimates derived from constant-heat sap-flow probe 

values and gravimetric measurements in pot-grown saplings. Tree physiology 27: 

1355-1360.

Moore, G.W.; Bond, B.J.; Jones, J.A.; Phillips, N., Meinzer, F.C. 2004. Structural and 

compositional controls on transpiration in 40- and 450-yr-old riparian forests in 

western Oregon, USA. Tree physiology 24: 481-491.

Phillips, N.; Bond, B.; McDowell, N.; Ryan, M.G. 2002. Canopy and hydraulic 

conductance in young, mature, and old Douglas-fir trees. Tree Physiology 22:205-

211.

Swanson, R.H. 1994. Significant historical developments in thermal methods for 

measuring sap flow in trees. Agricultural and Forest Meteorology 72:113-132.

Waring, R.H.; Schroeder, P.E.; Oren, R. 1982. Application of pipe model theory to predict 

canopy leaf area. Canadian Journal of Forest Research 12: 556-560.

Woudenberg, S.W.; Conkling, B.L.; O'Connell, B.M.; LaPoint, E.B.; Turner, J.A.; Waddell, 

K. L. 2010. The Forest inventory and analysis database: database description and 

users manual version 4.0 for Phase 2. Gen. Tech. Rep. RMRS-GTR-245. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 

336 p.

195

Sediment Yield Response to Sediment 

Reduction Strategies Implemented for 10 

Years in Watersheds Managed for Industrial 

Forestry in Northern California1

 

Kate Sullivan2

Abstract

For the past decade, the productive forestlands now owned and operated by the Humboldt 

Redwood Company have been managed with low impact practices designed to reduce 

sediment delivery according to voluntary agreements and regulatory requirements of state and 

federal agencies. These timberlands located in the erosive sedimentary terrain of the northern 

coast of California have been extensively roaded and several generations of redwood 

dominated forests have been clear-cut logged since the 1860s. Intensive watershed and 

property-wide studies of sediment processes within the past 50 years when information is 

most reliable have created watershed sediment budgets and documented significant sediment 

impacts from past management activities. Forest operations now include geologic hazard 

avoidance and an extensive road upgrading and removal program to minimize the dominant 

sediment sources. Over the past 10 years, suspended sediment and streamflow have been 

continuously monitored at a number of locations in the mainstems and major tributaries of 

Freshwater Creek and Elk River. In this paper we explore the extent of sediment reduction in 

the watersheds and effects on water quality that may be evident in the relatively short 

monitoring record.

Key words: sediment yield, suspended sediment, water quality monitoring, logging effects

Introduction

Long-term research on logging effects in coastal California watersheds has found 

that sediment can be expected to increase concurrent with clearcut timber harvest for 

some duration, with effects diminishing with time (Lewis 1998, Ziemer 1998). Initial 

response levels vary with the type of erosion processes that are disturbed and the type 

of management practices applied (Lewis 1998). However, past effects may be 

persistent and contribute to sediment yield for decades (Klein et al. 2008, Lewis and 

Keppler 2007, Ziemer 1998). 

The majority of timberlands in Elk River and Freshwater Creek were acquired by 

the Humboldt Redwood Company (HRC) after financial reorganization of the Pacific 

Lumber Company in 2008. The watersheds have been actively logged since the 

1860s using clear-cut harvest as the primary logging method over the past several 

decades and has a road system built to various construction standards over the last 50 

years. Since 1999, The Pacific Lumber Company and now HRC has been steadily 

 

1 This paper was presented at the redwood science symposium: coast redwood forests in a changing 

California. Jun 21-23, 2011, Santa Cruz, California. 2 Physical Sciences Manager, Humboldt Redwood Company, LLC, 125 Main St., Scotia, CA 95547. 

(707)764-4492. (ksullivan@hrcllc.com).
GENERAL TECHNICAL REPORT PSW-GTR-238 

196

working to reduce sediment with a combination of state-of-the-art road construction 

practices, a commitment to reconstruction and removal of older roads, and wet 

weather use limitations that prevent damage to roads and prevent sediment delivery 

to streams. Harvest related sediment is controlled through geologic hazard 

identification and geologist field investigation during timber harvest plan layout, rate 

of harvest limitations in these two watersheds, and practice of uneven-aged 

silviculture. Should we realistically expect sediment decline and has any occurred 

over the past decade? 

Study area

Freshwater Creek and Elk River are adjacent watersheds that respectively drain 

to the north and south ends of Humboldt Bay on the coast of northern California 

(40o

44’ N, 124o2’ W) (fig.1). The watershed area of Freshwater Creek is 80 km2 and 

Elk River is 111 km2

. The region has warm to hot dry summers and mild wet winters 

with moderate storm intensities. The watersheds are predominantly forested with 

second-growth stands of various ages comprised of redwood (Sequoia sempervirens) 

and Douglas-fir (Pseudotsuga menziesii). 

Figure 1—Overview of study watersheds in Humboldt County with the location of 

hydrologic monitoring stations. 

Unlike the controlled experiment at Caspar Creek, this water quality monitoring 

project can only be described as a messy experiment. There was no pre-measurement 

period—the experiment was joined in progress along with whatever past impacts and 

possible recovery may have occurred from high sedimentation documented in the 

sediment budget from a significant storm that occurred in 1997. Management is 

ongoing throughout the study period and multiple activities that could either increase 
Sediment Yield Response to Sediment Reduction Strategies Implemented for 10 Years in 

Watersheds Managed for Industrial Forestry in Northern California

197

or decrease sediment happen simultaneously. Most of the tributary basins have 

experienced both harvest and road construction or deconstruction during the 8 year 

monitoring period, often in the same year. As the experiment proceeds, timber 

management objectives dictate where, when and what activities occur. All of the 

current management activities are designed to prevent and minimize new sediment 

input while restoration activities remove existing sources. Is the net effect of the 

system as a whole leading to a reduction in the sediment yield? An extensive water 

quality monitoring project was initiated in 2002 to answer these questions. 

Watershed sediment budgets

Sediment sources have been extensively studied in Watershed Analysis projects 

sponsored by the Pacific Lumber Company (PWA 1998, 1999) and in support of 

TMDL related projects (Manka 2005, NCRWQCB 2011; PWA 2006, 2008). The 

erosion studies have characterized past and current sediment discharges and compiled 

sediment budgets (Reid and Dunne 1996) using remote sensing and aerial 

photography, extensive field surveys, and empirical physical modeling. Although the 

details within the sediment budgets vary somewhat among the various studies, and 

remain a topic of debate (NCRWQCB 2011), the general level of sediment as shown 

in figure 2 is similar among the studies. HRC updates the budgets based on ongoing 

landslide inventories and other adjustments with monitoring projects and restoration 

work. The current estimated budget is also shown in figure 2 along with the average 

sediment yield described in the next section. There has been reduction in sediment 

sources in each watershed over the decade, largely due to significantly reduced 

landslide rates and road improvements.

0

100

200

300

400

500

600

N. Fork Elk River Freshwater Creek

Sediment Yield (Mg km-2Yr-1)

Sed Budget 1988-1997

Sed Budget 2003-2010

Sediment Yield

Figure 2—Sediment budget estimates for the period prior to (1988 to 1997) and 

following adoption of new management practices in the watersheds (2003 to 2010). 

Sediment budgets have been a helpful tool that adds insight into expected 

sediment sediment yield and management effects, especially when available at the 

level of detailed study performed in these watersheds. Current sediment budgets 

match observed average sediment yield adjusted for bedload fairly well (fig. 2). The 

study has benefited from a wide range of rainfall during the short 8-year study period 

that has produced a representative average. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

198

Stream sediment measurement methods

An extensive water quality monitoring program was installed by The Pacific 

Lumber Company in Elk River and Freshwater Creek in October 2002 and sites are 

currently operated by HRC. Sites are located in a number of subwatersheds and in the 

mainstems (fig. 1). Sediment and streamflow are measured at nine sites in the 

Freshwater and 11 sites in the Elk River watersheds. Contributing basin areas range 

from 0.13 to 112 km2

. The project includes the basin containing the Headwaters 

Forest Reserve in the Little South Fork Elk River (534). This watershed has an 

undisturbed old growth forest with only a very minor management impact. This site 

was initially installed by Humboldt State University (HSU) on Bureau of Land 

Management Property (Manka 2005) and has been maintained by HRC since 2007. 

All sites are run of the river installations. Streams are equipped with continuous 

measuring turbidimeters and depth recorders that sample every 15 minutes from 

October to June. Physical sediment samples are collected and streamflow is 

measured. This combination of measures allows the continuously recorded turbidity 

and depth to be translated to streamflow (m3

s

-1) and sediment load. These are 

summed to produce annual sediment load, expressed in metric tons (Mg), or sediment 

yield per unit watershed area expressed as Mg km-2. 

Results

A comprehensive presentation of results for all stations and parameters of interest 

is beyond the scope of this paper. The focus is trends of annual sediment yield within 

the 8-year period from 2003 to 2010. There is a wide and typical range in sediment 

yield among sites as illustrated for an average rainfall year (hydrologic year 2010) in 

figure 3A. The old growth watershed in the headwaters of Elk River (534) had 

sediment yield of 5.9 Mg km-2. Sediment yield is similar among the Freshwater sites, 

averaging about 50 Mg km-2. This is about 10 times greater than the export from the 

old growth watershed. Sediment yield is more variable in Elk River reflecting a 

variety of factors. The old growth site has no management influence, subwatershed 

519 has substantial bank erosion and streamside landslides from legacy channel 

filling (PWA 2008), and stations 510 and 511 are the mouths of the large river basins 

(drainage areas 50 and 57 km2

, respectively). The relationship between sediment 

yield and watershed size is shown in figure 3B. Site 533 is found in the westernmost 

portion of the watershed within the Hookton geology, a spatially minor but 

particularly erosive formation with considerable soil disturbance from past logging. 

Data from four sites is used to illustrate the annual pattern of sediment yield for 

the period from 2003 to 2010 widely observed among most of the sub watersheds in 

the study (fig. 4). 
Sediment Yield Response to Sediment Reduction Strategies Implemented for 10 Years in 

Watersheds Managed for Industrial Forestry in Northern California

199

0

100

200

300

400

500527526505

506504528502523534522

519550517533188183532510511509

Annual Sedimmt Yield Mg km2)

HRC Station Number

Hydrologic Year 2010

Freshwater Elk River

ESL ESC ENS 

A. 

1

10

100

1000

0 50 100 150

Annual Sedimetn Yield (Mg m-2)

Watershed Area (km2)

Freshwater

Elk River

B. 

Figure 3—A) Sediment yield in hydrologic year 2010 (Oct 2009-Sept 2010) at each 

of the hydrologic stations. Original HSU labels for three sites discussed in Manka 

2005 are indicated. B) Sediment yield as a function of basin area. 

Adj = 330.42e-0.166x

R2 = 0.42

y = 710.15e-0.319x

R2 = 0.57

0

100

200

300

400

500

600

700

800

900

2003200420052006

2007

200820092010

Sediment Yield (Mg km2)

North Fork Elk River 511

Adjusted Yield Sediment Yield

Adj = 17.316e-0.096x

R2 = 0.11

Measured = 38.941e-0.241x

R2 = 0.3448

0

10

20

30

40

50

60

70

80

90

20032004200520062007200820092010

Sediment Yield (Mg km2)

Little South Fork Elk --534 (Headwaters)

Adjusted Yield Sediment Yield

Adj= 213.78e-0.187x

R2 = 0.78

Measured = 409.61e-0.358x

R2 = 0.66

0

100

200

300

400

500

600

700

20032004200520062007200820092010

Sediment Yield (Mg km2)

Cloney Gulch 504

Adjusted Yield Sediment Yield

Adj = 262.48e-0.17x

R2 = 0.42

Measured = 507.82e-0.343x

R2 = 0.54

0

100

200

300

400

500

600

700

800

2003

20042005200620072008

20092010

Sediment Yield (Mg km2)

Graham Gulch 505

Adjusted Yield Sediment Yield

Figure 4—Annual sediment yield at four stations in the study area. A value for site 

534 for 2003 has been estimated. The adjusted sediment yield has been normalized 

for annual climate characteristics using the erosivity index. 

The four sites were selected to include a large river (511), the old growth 

unmanaged site (534), and two moderate sized subwatersheds, each of which had 
GENERAL TECHNICAL REPORT PSW-GTR-238 

200

timber harvest and road reconstruction work during the interval (504 and 505). Other 

stations not shown follow a similar pattern evident at these four.

There is a clear decreasing trend in sediment yield during the measurement 

period. This largely follows the rainfall and storm pattern experienced during the 

period. The study period began in hydrologic year 2003. A storm in December 2002 

set a number of rainfall records for the 122-yr record at the National Weather Service 

site in Eureka, including maximum daily rainfall, and caused an estimated 60-yr 

return interval flood in the study area (Dhakal and Sullivan 2005). Hydrologic year 

2009 was a dry year with rainfall at 75 percent of normal and no large storms. Note 

that site 534 was not yet operative in 2003 and a value for that year has been 

estimated for illustrative purposes in this figure only. 

Beginning the monitoring project coincident with the large storm assures a 

decreasing trend in sediment yield and related turbidity measures within the record. 

Hydrologic analysis of water quality trends often requires some method for removing 

the influence of climate (Helsel and Hirsch 2002). This paper introduces a climate 

detrending parameter that can be simply calculated with standard reported rainfall 

data to represent the climate influence, referred to here as the erosivity index. It is 

calculated as:

Erosivity Index = Annual Rainfall (in.) x Maximum Daily Rainfall (in.) 

The index is very efficient at explaining sediment yields in the study area as 

shown for one representative site in figure 5. Sediment yield is highly correlated with 

the annual maximum peak flow (fig. 5A). This storm typically carries between 40 and 

80 percent of the annual load each year. Although only rainfall is used in the 

calculation of this index, it is highly correlated with the annual peak flow (fig 5B.) 

Thus the index shares the same high correlation with sediment yield as the annual 

peak flow (fig. 5C). It is clear from fig. 5 that one could also use the annual peak flow 

to index storm effects on sediment yield. One could also fine tune the short-term 

rainfall metric if the weather records are available. For comparing many stations, the 

erosion index has the advantage of applying commonly to all sites and it is 

surprisingly effective at capturing the elements of rainfall that lead to the observed 

sediment load. 

This method based on rainfall was conceived with the goal to meaningfully 

characterize storm conditions that explain the erosiveness of storms with one simple 

parameter. The method helps create historical perspective on the relative sediment 

generating capacity of past storms based on climate records that may exist when 

long-term flow records may not. This is a question that arises often when 

constructing sediment budgets backwards in time or even in creating context for 

modern storms. The historical erosion index reflecting the 125-year rainfall record at 

the nearby Eureka NWS weather station is shown in fig. 5D. The record setting 

conditions of 2003 were equaled only in 1890. This storm generated at least a 60-year 

flood event at the hydrology stations in the study area. The period from 1997 to 1999 

was a period of significantly higher than average erosivity. With the exception of 

2003, the index has been at or below the long-term average during the monitoring 

period. This index would not effectively represent rain-on-snow events, but these 

type of events are rare in these watersheds due to low elevation and coastal proximity 

and have not occurred in the recent monitoring period. 
Sediment Yield Response to Sediment Reduction Strategies Implemented for 10 Years in 

Watersheds Managed for Industrial Forestry in Northern California

201

y = 183.23x2 - 136.06x + 37.261

R2 = 0.94

0

100

200

300

400

500

600

700

800

0.0 1.0 2.0 3.0

Sediment Yield (Mg km2)

Annual Peak Flow ( m3 km-2 s-1 )

A. Graham Gulch 505

y = 22.038e1.1665x

R2 = 0.90

0

50

100

150

200

250

300

350

400

0.0 1.0 2.0 3.0

Erosivity Index 

Annual Peak Flow ( m3km-2 s-1 )

B. Graham Gulch 505

y = 336.01ln(x) - 1329.5

R2 = 0.98

0

100

200

300

400

500

600

700

800

0 100 200 300 400

Sediment Yield (Mg km-2)

Erosivity Index 

C. Graham Gulch 505

0

50

100

150

200

250

300

350

400

Erosivity Index 

D. NWS Site, Eureka, CA

Figure 5—Erosivity index as a detrending variable. Relationships between A). annual 

peak flow and sediment yield, B) erosivity index and annual peak flow, C) erosivity 

index and sediment yield. D). Annual erosivity index of Eureka rainfall. Five-year 

moving average is also traced. 

Correlation and multiple regression analysis was applied to the annual sediment 

yield to determine whether trends exist and whether there are effects of ongoing 

management activities. Figure 6 shows the correlation (Pearson’s) between various 

factors and annual sediment yield at individual sites and for all sites combined. The 

erosivity index as a surrogate for weather factors explains 89 to 99 percent of the 

variation in sediment yield and turbidity parameters during the study period and is 

highly significant at each individual site and for all sites combined. The correlation of 

the other factors was computed controlling for the erosivity index. There is a negative 

correlation between sediment yield and year at all sites. The correlation is strong but 

is statistically significant only at site 504 and when all sites are combined (p< .05). 

The trend is weak at site 502. This result suggests a generally decreasing trend in 

sediment yield with time independent of the climate but varying by watershed. 

The correlation of sediment yield with several management related parameters is 

also shown in fig. 6 for seven sites. These sites were selected because all data was 

available for the full monitoring period and to represent the range of watershed size 

and activity. For these variables, the correlation was controlled for both erosivity 

index and year. The correlation of annual harvest rate with sediment yield is quite 

mixed. At several sites the correlation is positive and at others it is negative. Overall, 

the annual harvest rate is not highly correlated with sediment yield. Klein et al. 

(2008) used the annual average harvest rate of the previous 10 or 15 years as an index 
GENERAL TECHNICAL REPORT PSW-GTR-238 

202

of harvest effects. This parameter tends to have a negative correlation with sediment 

yield in most watersheds but is positive in several. The correlation is not statistically 

significant. Finally, the annual sediment removal is the sum of sediment saved at 

each road sediment source site in each watershed and it is used here as a measure of 

the amount of disturbance from road construction and deconstruction conducted in 

the preceding summer. This work potentially generates sediment with post 

construction site adjustment. This management activity generally has an increasing 

influence on sediment yield, and was statistically significant for all sites combined. 

A multivariate linear regression on the combined data for all the parameters 

discussed was highly statistically significant and a backward stepping algorithm 

selected the same 3 significant variables for the combined group as the correlation 

analysis shown in fig. 6 (F = 158.65, p< .000). The variables are erosivity index, year, 

and sediment removal. 

Figure 6—Correlations between annual sediment yield and various weather, time 

trend and management factors. Management factor correlations were computed by 

controlling for the erosivity index and year. 

Comparison of the sediment yield from the managed sub-basins with the old 

growth basin (534) confirms that there has been a decreasing trend in sediment yield 

with time. One of the relationships between a managed basin and 534 is illustrated in 

fig. 7A. This relationship was computed for all sites and the residuals from this 

regression at each site are plotted in relation to time in fig. 7B. This analysis includes 

2004 to 2010 when the old growth site (534) was operative. A check of the one high 

value evident in figure 7A did not appear to exert leverage on the results.
Sediment Yield Response to Sediment Reduction Strategies Implemented for 10 Years in 

Watersheds Managed for Industrial Forestry in Northern California

203

y = 7.172x + 20.839

R2 = 0.81

0

100

200

300

400

500

600

700

800

0 20 40 60 80 100

Annual Yield at 505 (Mg km-2)

Annual Yield at 534 (Mg km-2)

A.

y = -0.2926x + 587.3

R2 = 0.45

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

2003 2005 2007 2009 2011

Standardized Residuals 

B.

Figure 7—A. Relationship between annual yield in a managed watershed (505) with 

the old growth watershed (534). B. Residuals of the same comparison with eight 

managed watersheds as a function of year. 

To visually see the effect of climate normalization, climate adjusted sediment 

yield is shown at the four sites in figure 4. This is computed by dividing the observed 

annual yield by the normalized erosivity index relative to the long-term median 

value. For example, in 2003 the erosivity index was 4.3 times the long-term median 

and the sediment yield was adjusted downward accordingly. Years with below 

median yield are adjusted upward. A negative exponential curve fit to the adjusted 

yield at the old growth site shows a decline of about 10 percent per year. The decline 

in slope averages about 18 to 20 percent for many of the managed watersheds but is 

higher in some. The difference in slope between the control and managed sites 

suggests that the sediment yields in many of the subwatersheds have declined at least 

10 percent and perhaps as high as 18 percent per year during the 8 year study period. 

Discussion and conclusions

There has been a small but persistent decline in sediment yield in most of the 

subwatersheds independent of climate and management factors from 2003 to 2010. 

The effect of ongoing management activities on annual sediment yield vary with 

subwatershed. Most have negative correlation suggesting that effects are not large 

enough to prevent observable recovery. Sediment yield in a few basins is positively 

correlated with ongoing activities. None are statistically significant. 

It is questionable whether this rate of decline can continue. The sediment budgets 

indicate that roads and landslides were a large part of the sediment sources in the 

past. A large part of the road system has now been upgraded and landslides have 

been rare for a number of years. The forest on the landscape continues to mature, 

especially in steep streamside higher hazard areas that are now off limits to logging. 

The sediment budgets indicate that legacy sediment sources are now an increasing 

portion of the annual sediment load. These include such features as old skid trail 

crossings which are abundant in the two watersheds and eroding banks left from the 

initial logging (PWA 1999), both of which continue to contribute sediment on an 

annual basis. Finding solutions for these sources will be challenging. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

204

References

Dhakal, A.; Sullivan, K. 2005. Analysis of rainfall characteristics of the December 2002 

storm at Eureka, California. Unpublished report prepared for The Pacific Lumber 

Company, Scotia, California. 

Helsel, D.R.; Hirsch, R.M. 2002. Statistical methods in water resources. Techniques of 

water-resources investigations of the United States Geological Survey. Book 4, 

Hydrologic analysis and interpretation Chapter A3. U.S. Department of Interior. 510 p. 

Klein, R; Trush, W.; Buffleben, M. 2008. Watershed condition, turbidity, and implications 

for anadromous salmonids in north coastal California streams. Unpublished report 

prepared for the North Coast Regional Water Quality Control Board, Santa Rosa, 

California. 104 p. 

Lewis, J. 1998. Evaluating the impacts of logging activities on erosion and suspended 

sediment transport in the Caspar Creek watersheds. Gen. Tech. Rep. PSW-GTR168. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest 

Research Station–Web. 26 p. 

Lewis, J; Keppeler. E.T. 2007. Trends in streamflow and suspended sediment after 

logging, North Fork Caspar Creek. Gen. Tech. Rep. PSW-GTR-194. Albany, CA: 

U.S. Department of Agriculture, Forest Service. Pacific Southwest Research Station: 95-

105. 

Manka, P. 2005. Suspended sediment yields in tributaries of Elk River, Humboldt 

County, California. Unpublished report prepared for the North Coast Regional Water 

Resources Control Board, Santa Rosa, California. 91 p. 

North Coast Regional Water Quality Control Board (NCRWQCB). 2011. Elk River TMDL 

Sediment Source Analysis. Draft staff report. Santa Rosa, California. 115 p. 

Pacific Watershed Associates (PWA). 1998. Sediment source investigation and sediment 

reduction plan for the North Fork Elk River watershed, Humboldt County, 

California. Unpublished report prepared for The Pacific Lumber Company, Scotia 

California. 

Pacific Watershed Associates (PWA). 1999. Sediment source investigation and sediment 

reduction plan for the Freshwater Creek watershed, Humboldt County, California.

Unpublished report prepared for the Pacific Lumber Company, Scotia California. 

Pacific Watershed Associates, 2008. Elk River bank erosion void assessment and bank 

erosion-related wood inventory Humboldt County, California. Unpublished report 

prepared for the North Coast Regional Water Quality Control Board, Santa Rosa, 

California. 40 p.

Reid, L.M.; Dunne, T. 1996. Rapid evaluation of sediment budgets. Reiskirchen, Germany: 

Catena Verlag GMHB. 164 p. 

Ziemer, R.R., technical editor. 1998. Proceedings of the conference on coastal watersheds: 

the Caspar Creek story. Gen. Tech Rep. PSW-GTR-168. Albany, CA: U.S. 

Department of Agriculture, Forest Service, Pacific Southwest Research Station. 149 p.
205

An Approach to Study the Effect of Harvest 

and Wildfire on Watershed Hydrology and 

Sediment Yield in a Coast Redwood Forest

Christopher G. Surfleet1, Arne Skaugset2, and Brian Dietterick3

Abstract

The Little Creek watershed, within California State Polytechnic University’s Swanton Pacific 

Ranch, is the location of a paired and nested watershed study to investigate the watershed 

effects of coast redwood forest management. Streamflow, suspended sediment, and stream 

turbidity have been collected during storms at two locations on the North Fork Little Creek 

and at the outlet of South Fork Little Creek from 2002 until present. In 2008, the watershed 

area between the two monitoring stations on the North Fork Little Creek watershed was 

harvested with an individual tree selection silvicultural system within the Santa Cruz County 

Rules of the California Forest Practice Rules. The South Fork Little Creek was left 

unharvested to serve as a control. In 2009, the Little Creek watershed was burned by a 

wildfire. The wildfire eliminated our control watersheds for the proposed Before After 

Control Intervention (BACI) study design. We present an alternative approach at detecting 

harvest and fire effects that uses rainfall/runoff models, soil erosion models, and sediment 

runoff relations to simulate runoff and sediment yield from the watersheds. The models and 

sediment runoff relationships will be developed within the framework of an uncertainty 

assessment to simulate pre-harvest and pre-fire conditions for the North and South Forks of 

Little Creek. The modeled results will be used as the control for the study which had been 

eliminated due to the wildfire in 2009. We use the HBV hydrologic model and sediment 

runoff relations to demonstrate our approach. An example of post-harvest and post-fire runoff 

and sediment changes within the uncertainty of the approach are demonstrated.

Key words: streamflow, suspended sediment, stream turbidity, harvesting, modeling

Introduction

The Little Creek watershed, near Santa Cruz, California has been the location of 

a paired watershed study investigating the watershed effects of coast redwood forest 

management. The classic method for evaluating forest watershed effects has relied on 

paired watershed studies (e.g., Bates 1921; Hewlett 1971; Rice et al. 1979) using 

statistical analysis within a Before After Control Intervention (BACI) study design. 

In 2009 a fire burned both the treatment and control watersheds of Little Creek. With 

the loss of a true control watershed following the 2009 Lockheed fire we propose an 

alternative approach using hydrology and sediment models to discern forest harvest 

and fire effects on watershed hydrology and sediment yield. A modeling approach to 

discern treatment effects on watershed hydrology in paired watershed studies has 

been used in other studies (e.g., Lørup et al. 1998, Seibert and McDonnell 2010, 

Zegre et al. 2010). The modeling approach offers the benefit of eliminating the need 

 

1 Research Associate, Oregon State University, Corvallis, OR. 541-737-4952. 2 Associate Professor, Oregon State University.

3 Director, Swanton Pacific Ranch, Cal Poly State Univ., San Luis Obispo, CA. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

206

for control watersheds, allows testing of alternative treatments, or the ability to 

evaluate long time durations not easily achieved in field experiments. However, the 

use of models represents additional uncertainty depending on model capabilities to 

represent the physical processes or the accuracy or availability of input data to the 

model. Therefore watershed study using models cannot be used in all situations and 

results need to be interpreted within the uncertainties associated with model use.

Methods

Study area 

The Little Creek study watersheds are located on the Swanton Pacific Ranch, 

owned and operated by California Polytechnic State University, San Luis Obispo, 

approximately 18 km northeast of Santa Cruz, California (fig. 1). The study portion 

of the watershed is divided into the 281 ha North Fork Little Creek (NF), the 106 ha 

South Fork Little Creek (SF), and 191 ha Upper North Fork Little Creek (UNF) subbasins. Elevations at the study watersheds range from 100 to 580 m. Mean annual 

precipitation ranged from 875 mm near the outlet of the study watersheds to 1060 

mm on the ridgeline during the study period 2002 to 2010. The overstory vegetation 

is primarily second-growth redwood (Sequoia sempervirens) and Douglas-fir 

(Pseudotsuga menziesii), with redwood comprising the majority of the vegetation 

cover. The soils in the study watershed are deep or moderately deep and well drained 

or somewhat excessively drained. They have a surface layer of loam, sandy loam, or 

stony sandy loam (Bowman and Estrado 1976). 

Data measurement

Three monitoring stations (NF, SF, and UNF) were used to measure streamflow, 

turbidity, and suspended sediment (fig. 1) for the entire study time period. Electronic 

stage monitoring equipment, instream turbidity probes, and automated pump 

samplers were deployed at each site. The portion of the North Fork below the Upper 

North Fork monitoring station was intended as the treatment area, where logging 

occurred in 2008, while the South Fork and Upper North Fork were intended as the 

control watersheds. 

Streamflow was measured year round; suspended sediment and turbidity were 

measured during storm events. Relationships between Turbidity and SSC 

measurements were developed by storm. The total mass or load of sediment for each 

storm was calculated by multiplying the hourly streamflow volume by the SSC then 

summing the hourly loads for the storm. Precipitation was measured with tipping 

bucket gauges at four locations within the Little Creek study watersheds for the study 

time period (fig. 1). Air temperature measurements were from the California 

Department of Forestry and Fire Protection Ben Lomond climate station (CDEC 

2011) approximately 6 km from Little Creek. 
An Approach to Study the Effect of Harvest and Wildfire on Watershed Hydrology and Sediment 

Yield in a Coast Redwood Forest

207

Figure 1—Little Creek study watersheds, California.

Approach to change detection study 

A modeling approach will be used to determine if there was change in runoff and 

storm sediment loads due to disturbances of forest harvest and wildfire. The approach 

will use the measured runoff and sediment from the pre-treatment time period of 

2002 to 2008 water years (WY) for the NF and 2002 to 2009 WY for the SF and 

UNF to fit hydrologic and erosion models. The differential evolution adaptive 

metropolis approach (DREAM) (Vrugt et al. 2009) or the Generalized Likelihood 

Uncertainty Evaluation (GLUE) (Beven and Binley 1992) will be used to address 

parameter and forcing data (precipitation and meteorological data input to models) 

uncertainty in the model simulations. The output from each model following the 

uncertainty analysis will be a range of acceptable answers from the models; this 

range represents the uncertainty in model use. The model uncertainty in our 
GENERAL TECHNICAL REPORT PSW-GTR-238 

208

evaluations will be represented by using the median, 2.5 percentile, and 97.5 

percentile model results for each model time step. 

Our data analysis approach will be similar to what has been previously used in 

paired watershed studies. In paired watershed studies statistical models (commonly 

linear regression) are fit to pre-disturbance measurements for the control and treated 

watershed. Post-disturbance statistical models between the control and disturbed 

watershed measurements are compared to pre-disturbance for detection of change. 

Because our control watershed was disturbed by wildfire we will fit hydrologic and 

erosion models to the pre-disturbance time period for each station. We will develop 

regression models between the simulated response (from models) and the measured 

response. We will use the hydrologic and erosion models fit to the pre-disturbance 

measurements to model the post-disturbance time period. We then develop postdisturbance regression models between the simulated response, as if harvest or fire 

had not occurred, with the measured response from harvest and fire disturbance. 

Prediction intervals will be developed for each of the regression relationships. 

Change from pre-disturbance will be determined by whether the post- disturbance 

regression model and model innovations (individual events) are outside the predisturbance prediction intervals. This will be replicated for the median, 2.5 percentile, 

and 97.5 percentile relationships to provide a measure of range of detectability under 

model uncertainty (Zegre et al. 2010). 

We will use four models for our change detection analysis, two hydrologic 

models and two watershed erosion models. The hydrologic models to be used are 

HBV-EC, a conceptual hydrologic model (Canadian Hydraulic Centre 2010), and the 

Distributed Hydrology Soil Vegetation Model (DHSVM) (Wigmosta et al. 1994) a 

physically-based distributed model. The watershed erosion models will be the 

process based model, DHSVM-Sediment (Dooten et al. 2006), and the surface 

erosion model Water Erosion Prediction Project (WEPP) (Flanagan et al. 1995). 

Change detection will be analyzed for the storm runoff volume, daily streamflow, 

monthly streamflow, and storm sediment load. Simple linear regression can be used 

for evaluating storm runoff volume and sediment load because storm events satisfy 

the independence requirements of regression analysis. When evaluating daily and 

monthly streamflow serial auto correlation will be present and will have to be 

accounted for and used within a generalized linear regression analysis. 

Two approaches will be utilized to simulate storm sediment load. The first 

approach will use the relationship between HBV-EC and DHSVM simulated storm 

runoff and measured storm sediment load. In the first approach storm sediment load 

will be calculated by two different methods. The first method simulated storm runoff 

will be used for linear regression relationships with measured storm sediment load. In 

the second method simulated storm sediment load calculated from simulated runoff 

will be used for linear regressions relationships with measured storm sediment load. 

The second approach to storm sediment load change detection will use two different 

watershed erosion models to estimate storm sediment load. The second approach to 

storm sediment load change detection will use two different watershed erosion 

models to estimate storm sediment load. DHSVM-Sediment and WEPP will be used 

to estimate storm sediment loads. Simulated storm sediment load calculated from the 

erosion models will be used for linear regressions relationships with measured storm 

sediment load. Additionally we will make adjustments to the vegetation, hydrology, 

and ground cover in DHSVM-Sediment and WEPP to represent both the forest 
An Approach to Study the Effect of Harvest and Wildfire on Watershed Hydrology and Sediment 

Yield in a Coast Redwood Forest

209

harvest (2009 water year for the NF) and the wildfire (2010). These manipulated 

models will be run for the post-disturbance time periods for comparison to measured 

response.

In paired watershed studies the control-treatment watersheds are located as close 

as possible to eliminate climate variations between the watershed pairs. In our 

modeling approach we compare pre-and post-disturbance which are independent time 

frames. The unaccounted variations in climate make possible a rejection or 

acceptance of the null hypothesis when it should not be, Type I or II errors 

respectively. To test if climate variation differs in the post-disturbance time period 

from pre-disturbance total precipitation and mean temperature for storm events for 

the pre-disturbance (2002 to 2008) and post-disturbance time periods of forest 

harvest (2008) and wildfire (2009 to 2010) will be tested for difference using a 

Wilcoxon Rank Sum test. 

Example of modeling approach for storm sediment load and 

runoff using HBV-EC

The HBV-EC hydrology model was applied to NF and SF at an hourly time 

interval to demonstrate change detection of storm runoff and one method of storm 

sediment load analysis. Comparison of measured and HBV-EC simulated storm 

runoff volume for the two watersheds in Little Creek, NF and SF indicates that no 

change is detectable between the pre-harvest relations and the one post-harvest water 

year for NF (2009) and one post-fire water year for both NF and SF (2010) (fig. 2). 

All innovations of post- disturbance storm runoff volume were found within the 95 

percent prediction interval of the pre-harvest regression model, with the exception of 

one storm from the post- harvest year of the NF, which was lower than pre-harvest 

values. This was true for the entire range of HBV-EC simulated runoff (median, 2.5 

percentile, and 97.5 percentile values). 

0

50000

100000

150000

0 50000 100000 150000

Measured Storm Volume (m3)

Simulated Storm Volume (m3)

Pre- harvest median

Pre- harvest 2.5 percentile

Pre- harvest 97.5 percentile

2009 Post- harvest

2010 Post-fire

0

20000

40000

60000

80000

0 20000 40000 60000

Measured Storm Volume (m3)

Simulated Storm Volume (m3)

A) NF B) SF 

Figure 2—Storm runoff comparison pre- and post-disturbance for A) North Fork Little 

Creek, and B) South Fork Little Creek. Grey shaded area represents range of linear 

regression relationships between simulated 2.5 and 97.5 percentiles and measured 

storm volume, thick dashed line is regression line post-fire, thin dashed lines are 95

percent prediction intervals for median regression line.
GENERAL TECHNICAL REPORT PSW-GTR-238 

210

Similarly, comparison of the natural log of measured sediment load and HBV-EC 

modeled storm runoff volume for the two watersheds in Little Creek, NF and SF, 

indicates that no change is detectable between the pre-harvest relations and the one 

post- harvest water year for NF (2009) and one post-fire water year (2010) for both 

NF and SF (fig. 3). All innovations of post-disturbance storm runoff volume were 

found within the 95 percent prediction interval of the pre-harvest regression model. 

This was true for the entire range of HBV-EC simulated runoff (median, 2.5 

percentile, and 97.5 percentile). 

0

5

10

15

0 50000 100000 150000

Ln Sediment Load (kg)

Simulated Storm Volume (m3)

Pre- harvest median

Pre- harvest 2.5 percentile

Pre- harvest 97.5 percentile

2009 Post- harvest

2010 Post-fire 0

5

10

15

0 20000 40000 60000

Ln Storm Sediment Load (kg)

Simulated Storm Volume (m3)

A) NF B) SF

Figure 3—Storm sediment load comparison pre- and post-disturbance for A) North 

Fork Little Creek, and B) South Fork Little Creek. Grey shaded area represents range 

of linear regression relationships between simulated 2.5 and 97.5 percentiles and 

measured storm volume, thick dashed line is regression line post-fire, thin dashed 

lines are 95 percent prediction intervals for median regression line.

The demonstration of the modeling approach, using the hydrology model HBVEC, for evaluating harvest and fire hydrologic and sediment effects in Little Creek 

did not find detectable changes. However, only one year of post-harvest and post-fire 

events were used. In both these years no large storm events occurred and the number 

of storm events was low. When you look at the data using only the smaller storm 

events (< 1 year recurrence), events of similar size for both the pre- and postdisturbance time periods a potential effect from the fire is observed (fig. 4). However, 

we emphasize we do not have evidence this effect occurs for larger events. 

Future years of measurement will make the post-disturbance data set more robust 

and provide more complete results. The analysis does suffer from the results of using 

one hydrology model. The HBV-EC model is a simple model and did not always 

quantify the hydrology of Little Creek accurately; see the comparison of pre-harvest 

measured and modeled storm runoff volumes (fig. 2). HBV-EC poorly predicts a few 

of the storm events creating an artificial variability to the pre-harvest data set.

Additional effort at model parameterization would improve the model. Integrating

other models into our analysis will allow contrast of the different results and 

strengths and weaknesses of each model providing improved interpretations of the 

watershed response.
An Approach to Study the Effect of Harvest and Wildfire on Watershed Hydrology and Sediment 

Yield in a Coast Redwood Forest

211

0

5000

10000

15000

20000

0 5000 10000 15000 20000

Measured Storm Volume (m3)

Simulated Storm Volume (m3)

Pre- harvest median

Pre- harvest 2.5 percentile

Pre- harvest 97.5 percentile

2010 Post-fire

Figure 4—Small storm runoff (< 1 year event) comparison pre- and post-fire for 

South Fork Little Creek. Grey shaded area represents range of linear regression 

relationships between simulated 2.5 and 97.5 percentiles and measured storm 

volume, thick dashed line is regression line post-fire, thin dashed lines are 95 percent

prediction intervals for median regression line.

Acknowledgments

This research was supported by a grant from the California State University 

Agricultural Research Institute. Data from Little Creek was provided by the students 

of California Polytechnic State University San Luis Obispo, Swanton Pacific Ranch; 

specifically we thank Drew Loganbill, Drew Perkins, and Michael Gaedeke. 

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213

Delineation of Preventative Landslide 

Buffers Along Steep Streamside Slopes in 

Northern California1

Jason S. Woodward2, David W. Lamphear3, and Matthew R. 

House4

Abstract

Green Diamond Resource Co (GDRCo) applies tree retention buffers to steep slopes along 

fish bearing (Class I) and non-fish bearing (Class II) streams that are in addition to the 

standard riparian management zones associated with timber harvest plans. These Steep 

Streamside Slope (SSS) buffers were designed to reduce the amount of sediment delivering to 

watercourses as a result of landslides generated by forest management related operations. 

Initial default buffers were developed through a landslide study during the planning stages of 

GDRCo’s Aquatic Habitat Conservation Plan (AHCP). The continued evaluation of 

streamside landslides across the property is one of the AHCP’s long term research projects, 

which is aimed at re-defining the SSS “default” prescriptions using a spatially distributed 

probability based sampling design. Through continued research, our goal is to refine the 

minimum slope gradients and maximum slope distances associated with the Steep Streamside 

Slope criteria for each of the 11 Hydrographic Planning Areas (HPA) identified in GDRCo’s 

AHCP.

The HPA to be re-evaluated was the Coastal Klamath HPA, which is a grouping of several 

watersheds near the mouth of the Klamath River in Humboldt and Del Norte Counties. 

Sampling consisted of 93 half-mile long stream segments that represent roughly ten percent of 

the lineal distances of Class I streams and five percent of the lineal distances of Class II 

streams within this HPA. The sampling method used insured both random selection and 

spatial distribution of the half mile segments within the study area. The study focused on 

those landslides that were non road-related, active to historically active, and had observably 

delivered sediment to a watercourse. The landslide data collected included causal factors, 

slope characteristics, cross sections, and dimensions of the source and debris, of more than 

400 landslides in this region.

Using a topographic ruggedness model on a 50 m LiDAR-based DEM and field-based 

geologic mapping of the area, we divided the area into distinct morphologic units. The results 

from the analysis of the landslide data provide new slope gradient and distance thresholds for 

the SSS default prescriptions. These new SSS prescriptions are unique to each of these 

morphologic units and provide site specific protections to areas prone to streamside 

landsliding within the Coastal Klamath HPA. A similar approach will be used for the 

remaining 10 HPAs.

Key words: shallow landslides, steep streamside slope buffers, LiDAR, topographic 

ruggedness model, Klamath River

 

1 This paper was presented at the 2011 Coast redwood forests in a changing California: a symposium. 2 PG, Green Diamond Resource Co, P.O. Box 68, Korbel, CA 95550. 

(jwoodward@greendiamond.com). 

3 Research Analyst, Green Diamond Resource Co. (dlamphear@greendimond.com). 

4 Aquatic Biologist, Green Diamond Resource Co. (mhouse@greendimond.com).
GENERAL TECHNICAL REPORT PSW-GTR-238 

214

Introduction

The Steep Streamside Slope Delineation Study is the analysis of streamside 

landslides across the portions of GDRCo ownership that are bound by the AHCP. 

The results of this analysis determine the new SSS default protection measures. The 

primary goal of the initial landslide study, which led to the development of the AHCP 

SSS “default” prescriptions, was to attempt to reduce the amount of sediment 

delivering to watercourses as a result of streamside landslides generated by forest 

management related operations. The AHCP objective of the SSS prescription is to 

achieve a 70 percent reduction of delivered streamside landslide volumes in 

comparison to historic management related streamside landslides. The initial study 

took into account slope distances from the main scarp of observed landslides to the 

affected watercourse transition line and slope gradients associated with the observed 

landslides. In addition, the initial study was intentionally biased towards areas that 

exhibited high concentrations of landslides due to the limited scope and compressed 

time frame to conduct the study. In order to more accurately define these protection 

measures and achieve the AHCP objectives directed at streamside landslides, the SSS 

Delineation Study expands upon the initial landslide evaluation effort. This report 

presents the findings of the initial phase of the SSS Delineation Study, which was 

directed at the eighty-thousand acre Coastal Klamath HPA.

Purpose and scope

The purpose of this study is to refine the minimum slope gradients and maximum 

slope distances associated with the Steep Streamside Slope prescriptions for the 

Coastal Klamath HPA.

The scope of work for this study is based on the initial “inner-gorge” study that 

was aimed at delineating an expanded protection zone adjacent to watercourses that 

would reduce the amount of streamside landslides related to timber harvesting. The 

study focuses on shallow streamside landslides that were not caused by roads or 

historic skid trails, were active to historically active, and have observably delivered 

sediment to a Class 1 or Class 2 watercourse.

Methods

Development of sample reaches

Our sample area involves hillsides adjacent to Class 1, Class 2-2 and Class 2-1 

watercourses within the Coastal Klamath HPA. As defined in GDRCo’s AHCP Class 

1 watercourses are current or historic fish bearing streams and domestic water 

supplies, Class 2 watercourses contain no fish but support or provide habitat for 

aquatic vertebrates. Class 2 watercourses are further broken into 1st and 2nd order 

streams. A Class 2-1 (1st order) watercourse is defined as the first 1,000 ft of a Class 

2 stream. Beyond the first 1,000 ft of a Class 2 stream the watercourse becomes a 

second order Class 2 which we define as a Class 2-2. In addition a Class 2-2 may be 

formed when two Class 2-1 streams converge. From the point of convergence of the 

two Class 2-1 watercourses, the watercourse is considered a Class 2-2. 

In order to sample random hillside areas within the Coastal Klamath HPA we 

broke the mapped Class 1 and Class 2 watercourses into half-mile survey reaches 

throughout the HPA. At the time, the Class 2 watercourses within our hydrography 
Delineation of Preventative Landslide Buffers Along Steep Streamside Slopes in Northern 

California

215

Figure 1—Coastal Klamath HPA 

sample reaches.

layer had not been broken up into the Class 2-2 and Class 2-1 designations. Therefore 

we sampled the Class 2 watercourses as a whole and visually checked for a 

reasonable distribution of Class 2-2 and Class 2-1 watercourses. Once our LiDAR 

derived hydrography was developed we assessed the actual distribution of the Class 

2-2 and Class 2-1 watercourses, which is discussed later under Results. 

At the time of development, there were 191 miles of mapped Class 1 and 619 

miles of mapped Class 2 watercourses within the Coastal Klamath HPA. Our goal 

was to survey roughly ten percent of the lineal distance of Class 1 streams (19 miles) 

and five percent of the lineal distance of Class 2 streams (31 miles) within this HPA.

The geographically distributed systematic random sampling method used, insured 

both random selection and spatial distribution of the half-mile segments within the 

study area. This method involved 

delineating whole streams, from the 

confluence to the upstream end of a 

Class 2, breaking these streams into 

approximate half mile sample 

reaches, sorting them tabularly 

according to the confluence 

coordinates and position within the 

individual stream, and then 

systematically selecting reaches to 

gain the appropriate sample 

percentage. In addition, we stratified 

the Class 1 watercourses to ensure an 

even distribution of sample reaches 

from the lower, middle, and upper 

portions of these streams. Due to their 

abundance this was not necessary for 

the Class 2 watercourses. In all, there 

were 93 half-mile long stream reaches 

along Class 1 and Class 2 

watercourses. The sample reaches are 

shown on fig. 1. 

Review of existing documents 

Our review of existing documents included a review of published geologic 

mapping in the area and a comprehensive landslide inventory using aerial 

photographs from the 1954, 1958, 1969, 1975, 1984, 1997, 2001, and 2004 sets and 

was focused on the areas within the vicinity of our sample reaches. As is common 

practice we mapped only landslides that were visible at the scale of the photographs 

which is 1:12,000 for each of the photo sets. We found that this typically equates to a 

landslide roughly 50 ft wide by 100 ft long or 5,000 square ft. These landslides were 

transferred into our GIS landslide layer with associated tabular data that included; 

photo year and label, land use and stand age at the time of failure, road and/or skid 

trail association, landslide type, slope curvature, geomorphic association, watercourse 

association, feature certainty and delivery. Landslide types are based on definitions 

modified from Cruden and Varnes (1996). 

Review of the aerial photographs indicates that the areas west of the Klamath 

River from Saugep Creek south to Tectah Creek were clearcut beginning in the 1950s 
GENERAL TECHNICAL REPORT PSW-GTR-238 

216

and slowed down by the late 1970s. The primary harvest method was ground-based

tractor-yarding likely due to the more subdued topography in this region. There are 

however several areas in this region that are much steeper and were subject to cable 

yarding in the late 1960s and 1970s such as portions of Ah Pah Creek and the lower 

portion of Tectah Creek. Along the Klamath River we observed early harvesting in 

the 1950s and 1960s that consisted of ground-based tractor clear cutting. East of the 

Klamath River from Mynot Creek south to Bear Creek, timber harvesting began in 

the mid to late 1960s and continued through the 1980s and slowing down in the 

1990s. Mainly clearcut with few selections were observed in these areas with groundbased tractor yarding as the main harvest methods. Cable-yarding however was the 

primary yarding method being utilized in the steeper terrain within the Hunter and 

Terwer Creek drainages.

Throughout the Costal Klamath HPA, lay-out construction was also common 

practice. Lay-outs were mounds of earth constructed in the direction of felling that 

softened the landing of old-growth timber and helped reduce breakage from the 

landing. This resulted in a significant amount of ground disturbance throughout the 

area. Road construction also resulted in significant ground disturbance throughout the 

area. Until the early 1980s side-cast construction was the common practice. This was 

a practice where earth materials from road construction were simply pushed off the 

downhill side of the road rather than being hauled to a stable location. Due to the 

dense skid road network involved with this initial entry and poor road-building 

practices, such as side-cast construction, road-related failures were very common 

throughout the region. 

Published mapping in the area includes mapping from Aalto and Harper 1982, 

Aalto and Kelsey 1981, Dell’Osso et al. 2002, and Ristau 1979a, 1979b. This 

mapping indicates the majority of the Coastal Klamath is underlain by the broken 

formation of the Franciscan Complex. Aalto and Harper describe the broken 

formation as tectonically fragmented interbedded graywacke, shale, and 

conglomerate. In general the topography in the area becomes more incised and 

rugged to the east where bedrock is less fragmented. In the western portion of the 

area topography is more subdued, bedrock is more fragmented, and ridges are 

frequently capped with alluvial deposits.

Field work, measurements, and calculations 

Field work involved surveying the hillsides adjacent to the sample reaches for 

shallow streamside landslides. Our study focused on those landslides that were non 

road and non skid-trail related, active to historically active, and had observably 

delivered sediment to a watercourse. Only landslides greater than 10 ft by 20 ft were 

included in the survey. The data collected for each landslide included a fielddeveloped cross section using a tape measure and clinometer, causal factors, slope 

characteristics, dimensions of the source area and slide debris, a field estimate of the 

delivery volume, distance from the crown of the slide to the watercourse transition 

line, and the average slope gradient of the hillside. 

Cross sections show the main scarp, projected failure surface, the estimated 

original surface, extent of slide debris and the associated watercourse. Cross sections 

were utilized to determine the length of the rupture area, length of debris, estimated 

thickness of the failure, estimated thickness of the remaining slide debris, and an 

estimated slope gradient of the hillside.
Delineation of Preventative Landslide Buffers Along Steep Streamside Slopes in Northern 

California

217

As mentioned above landslides that were thought to have been caused by roads 

or skid trails were not included in the analysis. Determining whether or not a slide 

has been caused by a road is a difficult task; especially if the failure is not a recent 

one. There are inferences that must be made in attributing a causal mechanism such 

as roads to the failure of a landslide. As a result we attempted to attribute road caused 

only to failures that appeared to have a reasonable or obvious negative association 

with a road or skid trail. Our determination of road caused failures took into account 

several factors. Fill slope related failures had to truncate a portion of the running 

surface of the road in order to be considered. In general it is difficult to determine if a 

failure emanating from the fill slope was caused by the road as most of these failures 

are older. Therefore we focused on slides that had observably offset at least a portion 

of the road. Cut bank related failures are typically easier to determine as most slides 

will take out a cut slope and fail onto or over the road prism or may take out a portion 

of the road as well. These types of cut bank failures were considered road caused.

Skid trails, although no longer being constructed on GDRCo timberlands, were 

commonly cut across steep terrain adjacent to watercourses and regularly used sidecast construction. In such areas skid-trail related slides were common and fairly easy 

to distinguish and were considered road-caused. Patterns of failure can typically be 

captured in aerial photographs. For instance, we observed that road related and skid 

trail failures were common in the early harvest entries where side-cast construction 

was the common practice and in areas with dense skid road networks or tall cut 

banks. Thusly, aerial photographs were also used to assist in the determination of 

road caused failures. 

Volume estimates were derived from a calculation based on the length, width, 

and depth of both the rupture area and the remaining slide debris observed in the 

field. The calculation treats the slide rupture area and debris as a half of an ellipse 

and was obtained from published work by Cruden and Varnes 1996. 

Development of morphologic units 

The initial default SSS prescriptions were applied uniformly across the Coastal 

Klamath HPA regardless of morphology or bedrock type, both of which can vary

dramatically across the region. Looking at the hillshade model from a 1 meter 

LiDAR DEM we determined that the morphologic complexity of the region could be 

separated into at least three discreet units. By doing so we could develop multiple 

SSS buffers within the HPA that would be more accurately applied to specific areas 

based on their morphology. In order to help define these areas we chose to use a 

topographic ruggedness model developed by Riley et al. 1999, using a 50 m 

resampled LiDAR DEM. The topographic ruggedness model computes the Terrain 

Ruggedness Index (TRI); the average change in elevation (meters) within a three by 

three kernel (150 m by 150 m area) at each 50 m cell within the region. The resulting 

TRI’s were classified into three groups (0 to 38 m, 38 to 63 m, and 63 to 170 m) 

using Jenks natural breaks (Jenks 1967). Jenks natural breaks, developed by 

cartographer George Jenks, are a data classification method that minimizes variance 

within groups of data and maximizes variance between groups of data. We 

characterized the resulting three TRI values as subdued, moderately subdued to 

slightly rugged, and rugged terrain, noting that this characterization is specific only to 

this HPA and portions of its surrounding areas. Next, we manually divided the HPA 

into large morphologic blocks based on our observations of the morphology observed 
GENERAL TECHNICAL REPORT PSW-GTR-238 

218

in the LiDAR DEM, our observations in the variation of the local bedrock, and the 

TRI’s. These larger blocks have been termed “Steep Streamside Slope Morphologic 

Units” (SSSMU). 

Once the SSSMU’s had been delineated we overlaid them with the landslide 

data. At that time we noticed that we did not have enough landslide data in each of 

the SSSMU’s to define the SSS buffers and slope thresholds. This is not to say that 

we did not have enough sample area, we simply found very few landslides in certain 

areas. In one of the SSSMU’s there were only 14 landslides to characterize the Class 

2-1 streams and only 28 landslides to characterize the Class 2-2 streams. As a result 

SSSMU 1 and SSSMU 2 were grouped together. For the final grouping SSSMU 1 

and SSSMU 2 were combined and renamed SSSMU 1 with TRI values of 0 to 63 and 

SSSMU 3 was renamed SSSMU 2 with TRI values of 63 to 170. The final SSSMU’s 

are shown on figure 2. 

Figure 2— Coastal Klamath HPA.

Cumulative volume 

This study included 423 landslides to characterize landslide patterns and develop 

the SSS buffers for the Coastal Klamath HPA alone. We found that of the 423 

landslides, 42 (or 10 percent) of the slides fall in the cumulative volume distribution 

above the 60 percent threshold. Of those 42 landslides, 33 percent were observed on 

1978 photos or earlier, 74 percent of them were observed on the 1997 photos or 

earlier and 12 percent were not observed in the photo record. Each of the slides 

observed on the 1997 or earlier photos occurred in areas that were clearcut prior to 

the retention of riparian buffers of any kind. Although primarily intended for riparian 

habitat, these buffers also help reduce the potential for streamside landslides. The 

slides observed on the 1997 and earlier photographs failed under management 

conditions that have not existed since the mid-1990s and certainly not under current 
Delineation of Preventative Landslide Buffers Along Steep Streamside Slopes in Northern 

California

219

management practices (i.e., those within the last 15 years that have been afforded 

various protection measures including riparian and geologic). Under current 

management practices these areas would have been, all or in part, protected by 

various retention buffers and likely received some level of geologic oversight at the 

THP level. These data suggest that these larger landslides are rare and may be 

attributed to historic logging practices. Based on these observations it is our judgment 

that using the 60 percent cumulative volume threshold will be adequate to derive the 

SSS distance buffers and be able to achieve the SSS objective of a 70 percent 

reduction in sediment delivery from management related streamside landslides in the 

Coast Klamath HPA. It should also be noted that the effectiveness of these new 

buffers will be evaluated during the AHCP’s SSS Assessment project which will take 

place over the next 11 years.

With the exception of the Coastal Klamath HPA group and Smith River HPA, a 

cumulative sediment delivery volume of 80 percent was used to determine initial 

default SSS gradients. In these areas the data from the initial SSS study suggested 

slope gradient thresholds of 85 percent and 70 percent, respectively. It was assumed 

that the initial data were biased towards steeper slopes that would not accurately 

characterize these areas as a whole. The actual slope gradients assigned to the initial 

SSS default buffers for these areas were reduced to 70 percent and 65 percent 

respectively. Like what was done for the maximum distance threshold, this was a 

conservative approach based on limited data to ensure that the SSS buffers would be 

able to meet the overall sediment objectives from the streamside slopes until a more 

robust analysis was conducted. Based on the observations described above, it is our 

judgment that using a cumulative volume threshold of 80 percent will be adequate to 

derive the SSS minimum gradient thresholds and be able to achieve the SSS 

effectiveness objectives. 

Results

Our sample reaches were mapped in the field and end points marked using a 

Garmin 60Cx GPS. After transferring these endpoints into the GIS and onto the 

LiDAR corrected hydrography layer we found that the spatially upgraded sample 

came very close to our target. Our surveys captured 13 percent of the mapped lineal 

distance of Class 1 watercourses (target of 10 percent) and 5 percent of the mapped 

lineal distance of the Class 2 watercourses (target of 5 percent) with a fairly even 

distribution between the Class 2-1 and Class 2-2 watercourses capturing 4 percent of 

the Class 2-1 and 6 percent of the Class 2-2 mapped watercourses.

As noted above we used a cumulative volume of 60 percent to determine the new 

SSS slope distances. There were a total of 423 landslides included in our analysis of 

the Coastal Klamath HPA. The distribution of landslides by watercourse and SSSMU 

are shown in table 1. 

The majority of these landslides occurred along the Class 1 and Class 2-2 

watercourses. Few landslides were found along the Class 2-1 watercourses, in fact 

there were 70 slides observed along the selected sample reaches with a near even

split of 34 slides in SSSMU 1 and 36 slides in SSSMU 2. After reviewing the Class 

2-1 landslide data within the individual SSSMU’s we noticed a high variability 

within the measured SSS criteria. It became apparent that this would be an

insufficient amount of data to delineate buffers for each of the SSSMU’s. Therefore
GENERAL TECHNICAL REPORT PSW-GTR-238 

220

Table 1—Distribution of landslides by watercourse and SSSMU.

Watercourse 

Class SSSMU Number of Slides

I 2 67

I 1 68

2-2 2 133

2-2 1 85

2-1 1&2 70

we combined the data for Class 2-1 watercourses and came up with prescriptions for 

the HPA as a whole for this watercourse class. The remaining landslides provided a 

sufficient distribution to characterize the SSS buffers in both of the SSSMU’s. 

Review of the Class 2-2 and 2-1 watercourses and their adjacent slope gradients 

using the LiDAR indicates that average slopes adjacent to Class 2-1 and Class 2-2 

watercourses are essentially the same. However, when we looked at the average 

maximum slope gradient adjacent to these watercourses we found that Class 2-2 

watercourses are located in proximity to much steeper slopes, by up to 22 degrees. 

This suggests that there may be fewer steeper slopes adjacent to Class 2-1 

watercourses and may explain why there were fewer landslides observed in these 

areas. However at this point this is simply a correlation and requires more 

investigation which we may be able to address at a later date. 

The revised SSS slope distances have been calculated. The distribution of 

cumulative volume of delivered sediment versus landslide distances from crown to

watercourse is shown on figure 3 and a summary table of these results is shown in 

table 2. 

Figure 3—Cumulative volume of delivered sediment versus landslide distances from 

crown of slide to watercourse transition line for Class I, Class 2-1 and Class 2-2 

watercourses.
Delineation of Preventative Landslide Buffers Along Steep Streamside Slopes in Northern 

California

221

Table 2—New SSS thresholds & a comparison of the revised Coastal Klamath SSS buffers 

with initial default buffers.

Slope Gradient thresholds were based on a cumulative volume of delivered 

sediment of 80 percent. With a significantly larger data set than the initial study, it 

was our judgment that we had sufficient data to characterize the SSS gradient 

thresholds by watercourse type as well as SSSMU. As was the case for the SSS slope 

distances we combined the data for the Class 2-1 watercourses to come up with an 

HPA wide slope threshold for this watercourse class. The distribution of cumulative 

volume of sediment delivered versus landslide slope gradients are shown on figure 4

and a summary table of the slope gradient thresholds is shown in table 2. 

Figure 4—Cumulative volume of sediment delivered versus average slope gradient 

from SSSMU 1& 2 for Class I, Class 2-1 and Class 2-2 watercourses.

Discussion

Looking at the different slope distances and slope gradient thresholds we can see 

justification for the rationale behind the development of the SSSMUs. Table 2 also 

outlines a comparison of the Initial Default SSS distance and slope thresholds as well 

as the new slope distances and associated slope thresholds.

Both slope distances and slope gradient thresholds vary significantly between 

SSSMUs. Within SSSMU 2 we can see the effects of the more competent sandstone 

Coastal Klamath SSS Maximum Slope Distances (feet) & Minimum Slope Gradient

(%) Thresholds

SSSMU Class I Class 2-2 Class 2-1

1 240' & 65% 110' & 70% 135' & 75% 2 425' & 75% 195' & 85%

Initial Default Buffers 475' & 70% 200' & 70% 100' & 70%
GENERAL TECHNICAL REPORT PSW-GTR-238 

222

and shale of the broken formation of the Franciscan complex. In these areas, we 

observed landslides occurring on steeper slopes with longer slide run out distances. In 

contrast within SSSMU 1 we observed more fragmented earth materials of the 

broken formation of the Franciscan complex as well as uplifted alluvial sediments, 

which resulted in slacker slopes and shorter run out distances with the associated 

landslides. In the future, our observations from this study coupled with more detailed 

mapping of the local bedrock may lead to differentiation of multiple bedrock units 

within the broken formation of the Franciscan complex. In the meantime, these 

varying buffer criteria offer more site specific protection measures where they are 

warranted.

Conclusions

Our analysis of landslides in the Coastal Klamath HPA has resulted in changes to 

both the slope distance and slope gradient criteria associated with the default SSS 

prescriptions. These new criteria offer specific protection to morphologically discrete 

areas within the Coastal Klamath HPA which we termed SSSMUs. Our sampling 

methods reduced bias and spatially distributed the samples about the HPA such that 

we were able to produce a robust data set that more accurately characterizes the 

geomorphic conditions of the region as they pertain to streamside landsliding. The 

goal of the SSS buffers was to achieve a 70 percent reduction in management-related 

sediment delivery from landslides compared to delivery volumes from landslides in 

appropriate historical clearcut reference areas. It is our judgment that these new 

default buffers will allow GDRCo to meet this goal set forth in the AHCP. 

Acknowledgments

We would like to thank our field crew; Scott Matheson, Scott Kirkman, Evan 

Saint-Pierre, Nick Graehl, Daniel Hadley, William Troxler, and Esther Stokes for 

producing quality field data through inclement weather and the steep and challenging 

terrain of the interior Klamath River region.

References

Aalto, K.R.; Harper, G.D. 1982. Geology of the Coast Ranges in the Klamath and Ship 

Mountain quadrangles, Del Norte County, California. California Division of Mines 

and Geology Open File Map QFR 82-16-SF, scale 1:62,500.

Aalto, K.R.; Kelsey, H.M. 1981. Geologic map of the Tectah Creek 15-minute 

quadrangle, northern California. Unpublished. California Division of Mines and 

Geology, scale 1:62,500. 

Cruden, D.M.; Varnes, D.J. 1996. Landslide types and processes. In: Turner, K.A.; 

Schuster, R.L., editors. Landslides - investigation and mitigation. Special Report 247. 

Washington, DC: National Research Council Transportation Research Board. National 

Academy Press: 36-75. 

Dell’Osso, D.R.: Falls, J.N.; McGuire D.J. 2002. Geologic and geomorphic features related 

to landsliding Redwood Creek watershed (north, central, and southern portions), 

Humboldt County, California. California Geological Survey, watershed mapping 

series, map set 6, Plate 1, 3 sheets.
Delineation of Preventative Landslide Buffers Along Steep Streamside Slopes in Northern 

California

223

Falls, J.N.; McGuire, D.J.; Dell’Osso, D.R. 2000. Geology and geomorphology for the 

Redwood Creek watershed assessment, Humboldt County, California. California 

Geological Survey.

Jenks, G.F. 1967. The data model concept in statistical mapping. International Yearbook of 

Cartography 7: 186-190.

Riley, S.J.; DeGloria, S.D.; Elliot, R. 1999. A terrain ruggedness index that quantifies 

topographic heterogeneity. Intermountain Journal of Sciences 5, No.1-4.

Ristau, D. 1979a. Geologic map of the Klamath 15 minute quadrangle, California.

Department of Forestry Title II Geologic Data Compilation Project, scale 1:62,500.

Ristau, D. 1979b. Geologic map of the Ship Mountain 15 minute quadrangle, California.

Department of Forestry Title II Geologic Data Compilation Project, scale 1:62,500.

Ecology

227

Responses of Redwood Soil Microbial 

Community Structure and N 

Transformations to Climate Change

Damon C. Bradbury1 and Mary K. Firestone1

Abstract

Soil microorganisms perform critical ecosystem functions, including decomposition, nitrogen 

(N) mineralization and nitrification. Soil temperature and water availability can be critical 

determinants of the rates of these processes as well as microbial community composition and 

structure. This research examined how changes in climate affect bacterial and fungal 

community structures and rates of N mineralization and nitrification in coast redwood forest 

soils. Soils were reciprocally transplanted between three redwood sites located across a 

latitudinal climate gradient, from near the southern extent of redwoods to near their northern 

extent and collected one year later at the end of the summer. A molecular community 

fingerprinting technique was used to examine changes in fungal and bacterial community 

structures, and 15N-isotope pool dilution was used to measure gross rates of N mineralization 

and nitrification. After one year, soil fungal and bacterial community structures in 

transplanted soils had changed to become more similar, but not identical, to those native to 

their new destination sites. Both climatic and edaphic variables were correlated with the 

variability in microbial community structure. While there were few significant differences in 

gross N mineralization rates between soil-climate combinations, gross nitrification rates were 

influenced by a change in climate. Rates of gross nitrification were highest in soils when 

located in the wetter, most northern site. While rates of gross nitrification varied widely in 

soils with water potentials above -0.05 MPa, rates were low in soils below -0.05 MPa. 

Changes in redwood climate, fog frequency and summer water availability will likely alter 

soil microbial community structure and rates of gross nitrification. Greater magnitude changes 

in climate or more than one year of exposure may be necessary to cause alterations in rates of 

gross N mineralization. 

Key words: bacteria, climate change, fungi, microbial community structure, nitrogen, redwood

Introduction

Global climate models predict alterations in regional patterns of precipitation and 

temperature (IPCC 2007). An understanding of how soil microbes respond to 

alterations in climate is important because these organisms determine many aspects 

of ecosystem structure, function and services. While patterns have been proposed for 

the manner in which macrobiota can respond to shifts in climate (e.g., shifts in 

species range with latitude or altitude; Colwell et al. 2008, Parmesan and Yohe 

2003), we have limited knowledge of microbial responses to climate change. 

Due to the influence of temperature and moisture on microbial activity, changes 

in gross nitrogen (N) mineralization and nitrification are likely to occur in response to 

climate change. Soil moisture, in particular, has been suggested to be one of the main 

 

1 Department of Environmental Science, Policy and Management, University of California, Berkeley, 

CA 94720-3114. (bradbury@berkeley.edu; mkfstone@berkeley.edu).
GENERAL TECHNICAL REPORT PSW-GTR-238 

228

factors that will influence rates of soil N mineralization and nitrification in response 

to changes in climate, especially in seasonally dry ecosystems (Gomez-Rey et al. 

2010, Jamieson et al. 1999). It is possible that N mineralization may not be as readily 

affected by changes in moisture as gross nitrification because N mineralization 

reactions are carried out by a wide variety of prokaryotic organisms and fungi while 

nitrification is carried out by only a limited number of archaeal and bacterial groups 

(Gleeson et al. 2010, Paul and Clark 1996). 

This study examined the impact of climate change on rates of gross N 

mineralization, gross nitrification and soil fungal and bacterial community structures 

in coast redwood forests. Soils were transplanted across the latitudinal range of coast 

redwood forests in northern California to examine how interactions among native soil 

characteristics and changes in climatic exposure affect gross rates of N mineralization 

and nitrification and bacterial and fungal community structures. Soils were sampled 

at the end of the dry, Mediterranean-climate summer, a time of year when the 

presence of fog is a defining characteristic of coast redwood forests (Azevedo and 

Morgan 1974) and differences in fog frequency result in the most dramatic 

differences in temperature and soil water availability north to south. The results 

elucidate the potential of climate change to alter rates of these communities and 

important N-cycling processes, while also considering how soil characteristics can 

modulate the impacts of climate change.

Methods

Study sites 

The three study sites were located in old-growth coast redwood forests in Prairie 

Creek State Park, CA (Humboldt County), the Grove of the Old Trees, Occidental, 

CA (Sonoma County) and Big Basin State Park, CA (Santa Cruz County), referred to 

as the North, Middle and South sites, respectively. The mean annual average 

precipitation increases with latitude and temperature decreases with latitude (table 1). 

The aboveground biomass is much greater in the North site and the rates of primary 

productivity and decomposition are higher there as well. Soil characteristics (e.g., soil 

C and N, pH, percent silt and sand, and water retention curves) also differ between 

the sites (table 1). 

Experimental design: three-way reciprocal transplant 

In August 2004, two types of intact soil cores (either 10 cm diameter x 15 cm 

deep, solid schedule 40 PVC cylinders or flexible 2 mm mesh shade cloth sown into 

cylinders of the same dimensions with nylon thread) were transplanted between the 

three sites in a full factorial design (soil from each site transplanted into every site).

Five (3 m x 3 m) plots located from 30 to 400 m apart were established at each site. 

Plot pairs between sites were chosen randomly, and cores were randomly located 

within a plot. Soil cores that were returned to their plots of origin served as controls. 

Ninety transplanted cores were harvested after one year in early September 2005 (45 

mesh and 45 PVC; five of each from three sites of origin x three transplant sites), as 

well as 15 previously undisturbed cores (five cores x three sites).
Responses of Redwood Soil Microbial Community Structure and N Transformations to Climate 

Change

229

Table 1—Site characteristics. See text for weather station locations for mean annual rainfall 

and temperature data (1970 to2000). All soil variables were measured for 0 to 15 cm, except 

percent C and percent N were measured for 0 to 10 cm and soil temperature was measured at 

7.5 cm. 

North Middle South

Location Prairie Creek S.P., 

Orick, CA

Grove of the Old 

Trees, Occidental, 

CA

Big Basin S.P., 

Boulder Creek, CA

Latitude 41° 41' N 38° 24' N 37° 10' N

Distance to coast, 

elevation

6.8 km, 54 m.a.s.l. 6.5 km, 148 m.a.s.l. 6.4 km, 128 m.a.s.l.

Mean annual rainfall 1,677 mm 1,419 mm 1,211 mm

Air temperature, 

mean (range)

11 °C (2 °C – 21 °C) 14 °C (4 °C – 29 °C) 15 °C (2 °C – 30 °C)

Soil texture Sandy Loam Sandy Loam Sandy Loam

Soil pH (mean +/-

s.e., n=5)

4.9 +/- 0.1 5.3 +/- 0.2 5.7 +/- 0.2

Soil %C (mean +/-

s.e., n=5)

10.7 +/- 0.9 4.6 +/- 0.4 4.5 +/- 0.5

Soil %N (mean +/-

s.e., n=5)

0.58 +/- 0.04 0.27 +/- 0.07 0.25 +/- 0.03

Microbial community analyses 

Bulk soil DNA was extracted from 500 mg of soil using the Bio101 Fast DNA 

Spin Kit for Soils (Q Biogene, Carlsbad, CA) according to the manufacturer's 

instructions. The DNA extracts were then diluted (7.5X or 10X) to approximately 40 

ng / μl. The PCR primers (from Sigma-Genosys, The Woodlands, TX) used for 

bacteria were 27F and 1492R (Giovanni 1991), and the ITS1F and ITS4 primers, 

targeting the internal transcribed spacer (ITS) region of the rDNA gene, were used 

for fungi (Gardes and Bruns 1993). The forward primers were labeled with 6-FAM 

for PCR for terminal restriction fragment length polymorphism (T-RFLP; Liu et al. 

1997). Three PCR reactions of each sample were bulked together before PCR clean 

up and digestion. All of the PCR products were purified using the MoBio UltraPure 

Clean Up Kit and eluted in 50 μl of elution buffer. All 10 replicates of transplanted 

samples and controls and five replicates of fresh undisturbed samples were analyzed 

by T-RFLP with bacterial primers, and four replicates (two mesh and two PVC cores 

for each origin-transplant combination) were analyzed for fungal T-RFLP. After PCR 

clean up, approximately 400 ng of bacterial 16S rDNA PCR product was digested 

with MspI. For fungi, 100 ng of fungal ITS PCR product was digested with HhaI. 

The tubes were incubated at 37 °C for 18 hours and then ethanol precipitated and 

washed twice before resuspension in 10 μl of fresh formamide. The abundance of 

different terminal restriction fragments (TRFs) was measured using an ABI 3100 

capillary sequencer (Applied Biosystems, Foster City, CA) run in the GeneScan 

mode. Each TRF was converted into its relative abundance (percent abundance) by 

dividing each individual TRF peak height by the total sum of peak heights for all of 

the TRFs found in a sample and multiplying by 100. 

Rates of gross N mineralization and nitrification 

Gross rates of N mineralization and nitrification were measured by 15N-isotope 

pool dilution (Herman et al. 1995). Soils were labeled with 15N as either (15NH4)2SO4
GENERAL TECHNICAL REPORT PSW-GTR-238 

230

for gross N mineralization or K15NO3 for gross nitrification; 1 ml of labeled solution 

was added to 50 g of soil to increase the appropriate pool to approximately 50 or 25 

atom percent 15N, respectively. Initial samples were taken after approximately 2 

hours and final samples 16 hours later. Concentrations of nitrate (NO3) and 

ammonium (NH4) were determined after a one-hour extraction in 1 M KCl. Atom 

percent15N was determined using an automated N and C analyzer coupled to an 

isotope-ratio mass spectrometer (ANCA-IRMS; PDZ Europa Limited, Crewe, UK) 

after diffusing out the NH4 or NO3 onto filter disks (Herman et. al. 1995). Gross rates 

of N mineralization and nitrification were calculated according to Kirkham and 

Bartholomew (1954). Soils were stored at 12 °C rates were measured at 12 °C to 

determine rates that were reasonably representative of field conditions (14 to 16 °C). 

Climate and soil characteristics 

Monthly precipitation data was obtained from NOAA National Climatic Data 

Center records for weather stations near each site; the stations near the North and 

Middle sites, respectively, were Orick Prairie Creek Park (Station 046498, 41° 22′ N 

and 124° 01′ W) and Occidental (Station 046370, 38° 23′ N and 122° 58′ W), and for 

the South, the average of Ben Lomond #4 and Felton (Station 040673, 37° 05′ N and 

122° 05′ W; Station 043004, 37° 03′ N and 122° 05′ W) was used. Soil temperatures 

were recorded at the time of sampling and in February, May and November as well 

as to determine the annual ranges in soil temperature. Gravimetric water content 

(GWC) was determined for soils collected at the same times. Determinations of bulk 

density, soil particle size distributions (sand, silt, clay; Sheldrick and Wang 1993), 

water retention curves (Klute 1986), pH (1:1 soil:0.01M CaCl2), and concentrations 

of soluble organic C and N (extracted in 0.05M K2SO4) and microbial biomass C and 

N (Brookes et al. 1985, Cabrera and Beare 1993) were made using standard methods. 

Bulk density and water retention curves were used to transform GWC into volumetric 

water content (VWC) and soil water potential, respectively. 

Statistical analyses 

To examine changes in community structure, non-metric multidimensional 

scaling (NMDS) was used to visualize the (dis)similarity in community structure 

between samples (McCune and Grace 2002). In NMDS ordinations, the farther apart 

samples are in space, the more they differ in structure. Permutational multivariate 

analysis of variance (PERMANOVA) was performed to determine if the differences 

in structure between soil-climate groups were significant (Anderson 2001, 2005). 

Pair-wise differences between groups were determined a posteriori. The Bray Curtis 

distance was used, and the tests were done using the distance ranks. The results from 

the NMDS ordinations and PERMANOVA tests were compared to hypothesized 

general response scenarios (fig. 1) to determine if the transplanted redwood microbial 

communities had exhibited a strong response, intermediate response or no response 

to the change in climate. Transplanted samples were always compared to the control 

samples of both the site of origin and the new transplant destination. 
Responses of Redwood Soil Microbial Community Structure and N Transformations to Climate 

Change

231

Figure 1—Hypothetical responses of soil microbial communities to climate change 

shown in theoretical NMDS ordinations. The distance between samples is indicative 

of the magnitude of their dissimilarity in community composition. Different letters 

indicate significant differences, as determined by PERMANOVA. The theoretical 

communities from the North and Middle controls are labeled and that of the North soil 

transplanted into the Middle climate is shown as a gray triangle. 

The variability in fungal and bacterial community structure was correlated with 

environmental variables by performing Mantel tests. The Bray-Curtis distance was 

used for the taxa abundance matrix and the Euclidean distance for the environmental 

variable matrix. The standardized Mantel statistic (r) is equivalent to the Pearson's 

correlation (r) statistic. Mantel tests were performed to examine correlations between 

fungal and bacterial community structures and several climatic and edaphic variables, 

including: gravimetric water content, volumetric water content, water-filled pore 

space, water potential, total annual rainfall, spring rainfall (MJ), summer rainfall 

(JA), temperature, maximum mean monthly temperature, soluble organic carbon, 

total soluble nitrogen, microbial biomass carbon, microbial biomass nitrogen, pH, 

percent sand, percent silt and percent clay and pH. 

Two-way analysis of variance was performed to determine if there were 

differences in gross rates of N mineralization and nitrification between sites of origin, 

transplant sites, or the interaction between the two (using R version 2.10.0). Because 

the results for the two types of cores (PVC and mesh) did not differ significantly, 

they were analyzed together. The N mineralization and nitrification results are 

presented as the averages by either the soil origins or the sites of 

transplantation/incubation because the interaction terms were not significant for 

either process rate.

Results

Effect of transplant on soil microbial community structure 

In general, after 1 year, the fungal and bacterial community structures of the 

transplanted samples shifted to more closely resemble those of the control soils 
GENERAL TECHNICAL REPORT PSW-GTR-238 

232

native to the new transplant site (climate), but they did not become indistinguishable 

from them. All fungal community responses were classified as "intermediate" by the 

NMDS ordinations and PERMANOVA results (table 2). For the bacteria, five of the 

six transplanted soils changed in structure but still differed from the control samples 

of the new site (table 2). One transplant scenario did not cause a bacterial community 

response, North soil into the South climate.

Table 2—Summary of changes in fungal (F) bacterial (B) and community structures in 

response to transplanting. Responses were determined from NMDS ordinations and 

PERMANOVA results, as shown in fig. 1.

Transplant Strong response Intermediate response No response

North into South - F B

North into Middle - F , B -

Middle into North - F , B -

Middle into South - F , B -

South into North - F , B -

South into Middle - F , B -

Correlations between community structures and 

environmental variables 

Fungal community structure was significantly correlated with temperature, 

precipitation, pH and soil texture values. The strongest correlations were found with 

the maximum mean daily temperature (r = 0.62), the mean annual temperature (r = 

0.56), the amount of summer rainfall (r = 0.56) and the total annual rainfall of the 

previous year (r = 0.37; table 3). When examining the correlations between bacterial 

community structure and environmental variables, measures of precipitation and soil 

water availability had weaker correlations (r = 0.15 to 0.20). Measures of soil texture 

and soil pH had correlations between 0.28 and 0.39, and total dissolved nitrogen (r = 

0.18), microbial biomass nitrogen (r = 0.20) and microbial biomass carbon (r = 0.23) 

all had lower but significant correlations with bacterial T-RFLP community structure. 

Table 3—Significant standardized Mantel correlations (Mantel r) between fungal and 

bacterial community structures and environmental variables. Only significant correlations 

are shown, p < 0.01 for all.

Environmental variable Fungi Mantel r Bacteria Mantel r

Max. temperature 0.62 -

Temperature 0.56 -

Summer rain 0.56 -

Annual rainfall 0.37 0.20

Late spring rain 0.32 0.15

pH 0.20 0.39

% sand, % silt, % clay 0.12 – 0.14 all 0.28

Total dissolved N - 0.18

Gravimetric water content - 0.10

Gross N mineralization and nitrification: soil and climate 

controls 

Rates of gross N mineralization did not differ significantly by transplant site (p = 

0.15) or the interaction of transplant site and origin (p = 0.10), but they did differ by 

site of origin (p = 0.02). The rates in soils with a South origin (4.8 ± 0.6 μg N g soil-1
Responses of Redwood Soil Microbial Community Structure and N Transformations to Climate 

Change

233

day-1) were significantly greater than in soils of Middle origin (2.6 ± 0.5 μg N g soil-1

day-1), and soils of North origin were intermediate (3.1 ± 0.7 μg N g soil-1 day-1).

Among all soil-climate combinations, rates of gross N mineralization ranged from 

(1.5 ± 0.4 to 6.4 ± 1.2 μg N g soil-1 day-1). Rates of gross nitrification differed 

significantly among soils harvested from different sites (of transplantation), but not 

among soils from different origins or the interaction of transplant site and origin (fig. 

2). Gross nitrification rates were higher when transplanted soils had been located in 

the North site compared to the other two sites (fig. 2A). In terms of soil origin, rates 

tended to increase from the South to the Middle to the North, but the differences were 

not significant (fig. 2B). There appeared to be a minimum soil water potential below 

which nitrification was seriously impaired (fig. 3). Below -0.05 MPa, rates of gross 

nitrification were always below 0.8 μg N g soil-1 day-1. Above this water potential, 

rates varied widely, ranging between 0.0 and 9.5 μg N g soil-1 day-1. 

Figure 2—Gross nitrification graphed by (A) site of transplantation (incubation) and 

(B) site of origin for samples collected one year after transplanting. ANOVA p-values 

are in the upper left-hand corner and significant differences are denoted by 

lowercase letters. The interaction (not shown) was not significant (p = 0.32); thus, 

only the results averaged by site of transplantation and site of origin are shown to 

display the significant effect of transplantation.

Discussion

Response of bacterial and fungal community structure to a 

change in climate 

Climate change resulting from transplanting soil cores across a 500-km 

latitudinal gradient in climate caused detectable changes in soil bacterial and fungal 

community structures within one year. Under all of the transplant scenarios, except 

one, the community structures of transplanted soils shifted to more closely resemble 

those of the sites into which they were transplanted. However, the community 

structures of the transplanted samples were still distinguishable from those native to 

their new sites. Given more time, the structure of a microbial community may 
GENERAL TECHNICAL REPORT PSW-GTR-238 

234

Figure 3—Rates of gross nitrification graphed against soil water potential for 

transplanted samples collected after 1 year. 

continue to change, but it may also never fully resemble that native to the new site. 

While climate is clearly an important determinant of microbial community structure, 

it is certainly not the only significant controller. 

The varying impacts of climate change on microbial community composition and 

structure that have been found across studies could be related to the strength of the 

change in climate to which soils are exposed. For example, in California, Waldrop 

and Firestone (2006) also found that soil microbial community structure changed 

when soils were transplanted from beneath oak canopies into an open grassland 

environment, but the reverse was not true (grassland soil microbial community 

structure did not change when transplanted beneath an oak canopy). They suggested 

that the exposure of communities to climatic conditions outside of their recently 

experienced range in historical climate caused a rapid change in community 

structure. In contrast, bacterial community composition differed little in response to 

increased rainfall after five years of rainfall manipulations in a coastal California 

grassland (Cruz-Martinez et al. 2009). However, in that study, all of the communities 

had experienced the same historical range in climate, one that likely encompassed the 

conditions experienced under the imposed rainfall manipulations. Additionally, 

Castro et al. (2010) observed changes in fungal and bacterial abundances and 

community structure after three years in response to manipulations of climatic drivers 

(temperature, precipitation and CO2 concentration) in old-field ecosystems. They 

found that precipitation had the largest impact on community structure. 

The climatic conditions of our three redwood forest sites overlap. The mean 

values for temperature and precipitation at all sites are within the ranges historically 

experienced by the indigenous communities. However, the extremes in precipitation 

and temperature (maxima and minima) occurring in the "new" sites posttransplanting may have provided additional stimulation for a change in community 

structure to occur. The warmest summer temperatures and driest soil conditions of 

the South site are outside of the range experienced in the North site, and the coolest 

winter temperatures in the North are slightly cooler than those experienced in the 

South. The relative importance of mean temperature and rainfall values compared to 

maxima and minima (and their duration) in determining differences in community 

composition and structure is an important but largely unexplored question. 
Responses of Redwood Soil Microbial Community Structure and N Transformations to Climate 

Change

235

While climate clearly influences community structure in this study, it is not the 

sole determinant. The predominance of intermediate changes in microbial community 

structure suggests that edaphic and/or biological factors also influence the trajectory 

and magnitude of the community response to climate. The structure of some 

communities may be slowly changing toward that of the new site, but in other 

instances, the structure of a transplanted community may never closely approach that 

of the new site's native community. Native soil characteristics can buffer against the 

effects of climate; in addition, biological interactions or environmental stochasticity 

could also cause the change in community structure to take a different trajectory. In 

this study of coast redwood soils, the strongest correlations between environmental 

variables and fungal community structure were found with temperature and rainfall, 

while bacterial community structure correlated most strongly with pH. The 

association of fungi with temperature and rainfall could indicate the importance of 

climate as a regulator of fungal decomposition, while soil pH has been found to be a 

strong environmental driver of bacterial community composition and structure (Chu 

et al. 2010, Fierer and Jackson 2006). 

Impact of a change in climate on gross rates of N 

mineralization and nitrification 

The responses of gross N mineralization and gross nitrification to imposed 

changes in climate differed. While rates of gross N mineralization differed somewhat 

among soils with different sites of origin, rates of gross nitrification differed 

significantly among transplant sites, that is, the sites at which the soil cores spent the 

preceding year (regardless of origin). Consequently, rates of gross nitrification were 

not correlated with rates of gross N mineralization. Instead, the impact of 

transplanting on gross nitrification seems to be due to the relationship between gross 

nitrification and water availability. 

Rates of gross nitrification in coast redwood forests are clearly affected by soil 

water availability at the end of the summer, when north-south differences in fog 

frequency can cause substantial differences in climate between sites. The impacts of 

soil water availability on nitrification result from two primary factors: the effects of 

soil water content on the diffusion of NH4 to ammonia oxidizers and the 

physiological impacts of the energetic availability of water (Stark and Firestone 

1995). In this field study, there was a striking relationship between gross nitrification 

and soil water potential. Rates of nitrification were always low (< 0.8 μg N g soil-1

day-1) below a water potential of -0.05 MPa. This water potential, however, is much 

greater (wetter) than the -0.6 MPa at which Stark and Firestone (1995) found 

physiological stress to become more important than diffusion in terms of limiting 

nitrification. Thus, the lower rates of nitrification below -0.05 MPa could be due to 

diffusional limitation of ammonium, or the ammonia oxidizers in these soils could be 

more sensitive to water stress since they are from a moister summer environment

than the grassland soils studied by Stark and Firestone (1995). Ammonia-oxidizing 

bacteria are known to be able to carry out ammonia oxidation down to below -1.0 

MPa in soils (Chen et al. 2011, Paul and Clark 1996), but little is known about the 

physiology of archaeal nitrifiers because few have been cultured (de la Torre et al. 

2008, Konneke et al. 2005, Tourna et al. 2011). Soils in coast redwood forests are 

well suited to maintain relatively high water availability throughout the summer. The 

lowest water potential in this study was -0.5 MPa. The high organic matter contents 

(and associated high water holding capacity) and the presence of fog (which reduces 
GENERAL TECHNICAL REPORT PSW-GTR-238 

236

evapotranspiration) can both contribute to this characteristic. Decreases in fog water 

inputs could, however, lead to drier soils (Ewing et al. 2009) 

In contrast to gross nitrification, rates of gross N mineralization in coast redwood 

forests were relatively insensitive to any variable measured, edaphic or climatic. 

Other studies have reported a direct relationship between gross N mineralization and 

substrate availability (Booth et al. 2005), and a significant relationship between gross 

N mineralization and concentrations of soluble organic nitrogen was previously 

found for two northern redwood sites (Bradbury 2011). However, that study was 

conducted during a very wet time of year in late winter, March 2003, while this 

transplant study concentrated on a drier time of year at the end of summer. At the end 

of the dry summer period, it may be impossible to separate substrate and water 

controls of gross N mineralization. Mean rates of gross N mineralization varied 

between ~2 and ~6 μg N g soil-1 day-1 among the different origin-transplant site 

combinations in this study, but there was no consistent pattern in the variation of 

gross N mineralization among groups. Other studies conducted in pasture and 

grassland soils have found significant decreases in gross N mineralization at water 

potentials lower than those measured in these coast redwood soils (-1.5 MPa in 

Murphy et al. 1997 and -1.5 MPa in Jamieson et al. 1998), but a decrease in water 

potential from -0.1 MPa to -1.0 MPa did not cause a substantial decrease in gross N 

mineralization in the EA horizon of an acid coniferous forest soil (Chen et al. 2011). 

Thus, rates of gross N mineralization in forest mineral soils may not be highly 

influenced by decreases in soil water availability down to at least -1.0 MPa. Hence, 

greater magnitude changes in climate than those experienced in this study, or more 

than one year of exposure to a new climate, may be necessary to cause alterations in 

rates of gross N mineralization. 

Implications for climate change in redwoods 

Changes in summer fog frequency could have important effects on coast 

redwood forests. The importance of fog to coast redwood ecosystems in terms of 

supplying water and reducing transpiration during the otherwise dry summer has 

been demonstrated for coast redwood trees and their understory species (Dawson 

1998, Limm et al. 2009). In this study, a regional-scale transplant-induced change in 

climate caused changes in fungal and bacterial community structure within one year. 

These changes occurred within the framework of the native soil characteristics, 

possibly as a result of the exposure of indigenous soil microbial communities to 

conditions outside of their historical range in climate. The relative importance of 

climate maxima and minima compared to climatic means requires further 

exploration. By examining the impact of differences in climate on gross N 

mineralization and nitrification, this study has helped to elucidate the importance of 

water availability for N-cycling processes that can control plant N availability at this 

critical time of year. While rates of gross N mineralization seem to be relatively 

insensitive to differences in summer climate across coast redwood forests, rates of 

gross nitrification are significantly affected by differences in summer climate and 

water availability. Therefore, continued reductions in fog frequency or amount, as 

have been observed over the last 100 years (Johnstone and Dawson 2010), may affect 

populations of ammonia-oxidizing bacteria and archaea and cause significant 

reductions in rates of gross nitrification and nitrate availability to redwoods and their 

understory species.
Responses of Redwood Soil Microbial Community Structure and N Transformations to Climate 

Change

237

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241

Rangewide Genetic Variation in Coast 

Redwood Populations at a Chloroplast 

Microsatellite Locus1

Chris Brinegar2

Abstract

Old growth and second growth populations of coast redwood (Sequoia sempervirens) were 

sampled at 10 locations throughout its range and analyzed at a highly variable chloroplast 

microsatellite locus. Very low FST values indicated that there was no significant genetic 

differentiation between adjacent old growth and second growth populations at each location. 

Genetic diversity was moderate to high in populations north of the San Francisco Bay but low 

to very low in more southerly populations. Phylogenetic analysis produced a neighbor-joining 

tree with one clade composed of all populations north of San Francisco Bay and the other 

composed of the remaining southern populations. Differentiation of these two groups is 

consistent with the loss of rare alleles in the smaller, more fragmented southern populations 

by genetic drift. 

Key words: chloroplast microsatellite, coast redwood, genetic drift, Sequoia sempervirens

Introduction

Ancestors of the modern coast redwood (Sequoia sempervirens) were once 

dominant forest species of the temperate northern latitudes. Glaciation ultimately 

forced the ancient redwood forests to retreat into the coastal fog belts of Oregon and 

California where they reached their extreme southern range limit near Santa Barbara 

in the late Pleistocene (Sawyer and others 2000). Genetic analysis of extant 

populations throughout the current 450 mile range could provide insights into the 

nature of historical expansions and contractions of redwood forests while shedding 

light on the evolutionary forces that will shape the composition of redwood forests in 

the future. 

Three rangewide studies have provided data on the diversity and genetic structure

of coast redwood populations. Hall and Langenheim (1987) detected a statistically 

significant geographic variation in leaf monoterpene composition. Cluster analysis 

revealed three major groups with the more divergent southern group separated from 

the more related central and northern groups by the San Francisco Bay. Growth 

performance differences in common garden experiments (Anekonda 1992) also 

supported a division between redwoods north and south of the San Francisco Bay. 

Douhovnikoff and Dodd (2011) detected a weak divergence between redwood 

lineages near the Sonoma/Mendocino border using nuclear microsatellite markers. 

 

1 This paper was presented at coast redwood forests in a changing California, June 21-23, 2011, 

University of California, Santa Cruz.

2 Division of Natural Sciences, University of Maine Farmington, Farmington, ME 04961. 

(chris.brinegar@maine.edu). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

242

Molecular markers in haploid genomes have smaller effective population sizes 

compared to nuclear markers (Weising et al. 2005). Therefore, chloroplast 

microsatellites are typically more sensitive in detecting founder effects, bottlenecks, 

and differentiation by genetic drift (Provan et al. 2001). Among a set of coast 

redwood microsatellite markers developed by Bruno and Brinegar (2004) was the 

chloroplast Seq21E5 locus, a highly variable tetranucleotide repeat. Preliminary data 

from the Seq21E5 locus suggested a greater genetic diversity in northern coast 

redwood populations compared to populations in Santa Cruz County (Brinegar et al.

2007). However, the northern and southern populations were sampled from old 

growth and second growth forests, respectively. Whether the observed differences 

represented a north-south divergence or were due to regeneration artifacts could not 

be determined in that limited study. 

The major goal of the current study was to determine whether a chloroplast 

microsatellite analysis at the Seq21E5 locus could provide independent confirmation 

of a north-south split in the genetic structure of coast redwood populations. A 

secondary objective was to ascertain if, in fact, there are detectable differences in 

genetic composition between old growth and second growth populations. 

Methods

Sampling sites are shown in figure 1. At most sites, old growth and second 

growth populations were sampled in different areas within the boundaries of the same 

park or reserve. Exceptions were in the old growth/second growth collections at 

Armstrong Redwoods State Reserve/Austin Creek State Recreation Area, Big Basin 

Redwoods State Park/Castle Rock State Park, and Miller Creek/Lime Kiln State Park. 

In all cases, paired old growth/second growth populations were within five miles of 

each other. Redwood branchlets were collected from 40 trees spaced at least 10 m 

apart along transects. Tissue was dried in desiccant and stored at room temperature. 

DNA extraction and PCR conditions were performed as described by Bruno and 

Brinegar (2004). PCR products were separated on 6.5 percent polyacrylamide gels 

(29:1 acrylamide:bisacrylamide, 40 mM Tris-acetate [pH 8.3], 1 mM EDTA) 

supplemented with 1X Spreadex Polymer NAB (Elchrom Scientific, Cham, 

Switzerland). Samples were electrophoresed for 3 h at 200 V and stained with 0.5 

mg/L ethidium bromide. PCR product sizes were estimated using M3 markers 

(Elchrom Scientific). Seq21E5 size variants are referred to in this study as “alleles.”

Allele frequencies and Wright’s FST values, which represent the variance of allele 

frequencies among populations (Avise 2004), were calculated using HAPLOTYPE 

ANALYSIS (Eliades and Eliades 2009). Shannon diversity indices were calculated 

for populations from the formula: S = –∑pi log2 pi (Allnut and others 1999) where pi

is the frequency of the ith allele. Standardized Shannon indices where calculated by 

dividing S by its maximum value for a given sample size. A neighbor-joining tree 

was constructed in POPTREE2 (Takezaki and others 2010) using Nei’s DA distance 

(Nei et al. 1983). 
Rangewide Genetic Variation in Coast Redwood Populations at a Chloroplast Microsatellite Locus 

243

Figure 1—Map of coast redwood distribution in California with sampling locations.

Results

Comparison of old growth and second growth populations 

The numbers of individuals with a given allele in the paired old growth and second 

growth populations are shown in table 1. Histograms of allele distributions based 

either on old growth or second growth allele frequencies are compared in fig. 2. 

Figure 2—Allele frequencies in combined old growth populations and combined 

second growth populations.
244 

 Table 1—Allele distributions (number of individuals) in paired old growth and second growth redwood populations.a 

 Allele size (bp)

Populationb 96 100 104 108 112 116 120 124 128 132 136 140 144 148 152 

JS-OG 4 0 6 7 11 1 3 1 2 1 0 3 1 0 0 

JS-SG 1 0 6 4 19 1 2 0 4 0 0 3 0 0 0 

PC-OG 1 1 8 4 15 0 5 1 2 0 3 0 0 0 0 

PC-SG 1 0 7 1 14 0 8 1 5 1 0 1 0 1 0 

HU-OG 1 0 1 2 28 0 1 1 2 0 0 1 1 1 1 

HU-SG 0 2 6 6 18 1 3 1 2 0 0 1 0 0 0 

MW-OG 0 1 6 6 11 2 5 1 3 1 1 0 0 0 0 

MW-SG 2 2 5 5 8 1 8 2 1 1 0 3 2 0 0 

AR-OG 2 1 6 4 16 0 7 0 2 0 1 0 1 0 0 

AC-SG 0 3 5 3 17 1 6 0 3 0 2 0 0 0 0 

MT-OG 0 2 6 0 26 0 1 1 2 0 0 1 1 0 0 

MT-SG 0 3 2 4 21 0 1 3 6 0 0 0 0 0 0 

BB-OG 0 0 15 0 22 0 0 0 0 0 2 0 1 0 0 

CR-SG 0 0 8 0 29 0 2 0 1 0 0 0 0 0 0 

HC-OG 0 0 12 0 28 0 0 0 0 0 0 0 0 0 0 

HC-2G 0 0 10 2 26 0 2 0 0 0 0 0 0 0 0 

BS-OG 0 0 5 0 35 0 0 0 0 0 0 0 0 0 0 

BS-SG 0 0 4 0 36 0 0 0 0 0 0 0 0 0 0 

MC-OG 0 0 1 0 39 0 0 0 0 0 0 0 0 0 0 

LK-SG 0 0 2 0 37 1 0 0 0 0 0 0 0 0 0 

 a n = 40 for each population. b Population abbreviations are defined in figure 1. OG = old growth; SG = second growth.
Rangewide Genetic Variation in Coast Redwood Populations at a Chloroplast Microsatellite Locus 

245

The two distributions, each based on data from 400 individuals, are extremely similar 

and include alleles ranging from 96 to 164 bp (corresponding to 4 to 21 repeat units). 

Allele number and FST comparisons between paired old growth and second 

growth populations are displayed in table 2. Allele number ranged from two in some 

of the southernmost populations to 12 in the MW populations. In general, allele 

numbers in old growth populations are mirrored in their second growth counterparts. 

When differences in allele numbers occur, they are due to rare alleles. 

Table 2—Allele number and FST comparisons of paired old growth and second growth 

redwood populations. 

Populationa

JS PC HU MW AR/

AC

MT BB/

CR

HC BS MC/

LK

OGb alleles 

SG alleles

11

8 

9

10

11

9 

12

12

9

8 

8

7 

4

4 

2

4 

2

2 

2

3 

Normalized 

percent FST 0.7 0.3 1.6 0.4 0.1 0.8 1.3 0.2 0.0 0.2 a Population abbreviations are from fig. 1. b OG = old growth; SG = second growth.

Wright’s FST, when normalized to the maximum value possible, can be expressed 

as the percent of genetic diversity due to allele frequency differences among 

populations. Pairwise FST values for each old growth/second growth pair (table 2) are 

all extremely low (0.0 to 1.6 percent) indicating that there is negligible genetic 

differentiation between adjacent old growth and second growth populations 

throughout the coast redwood range. Therefore, for subsequent analyses, allele 

frequency data from the adjacent old growth and second growth populations at each 

location were combined in order to provide a larger population sample size (n = 80).

Rangewide variation in genetic diversity 

The standardized Shannon diversity index is a measure of genetic diversity that 

takes both allele number and frequency into account. Values of 0 and 1 indicate no 

genetic diversity and maximum genetic diversity, respectively, within populations. 

Figure 3 shows how genetic diversity at the ten sampling sites (combined old growth 

and second growth data) varies with distance from the northern range limit of coast 

redwood (approximately eight miles north of the Oregon/California border). 

Populations north of the San Francisco Bay have standardized Shannon indices 

of 0.51 to 0.81 with the MW population being the most diverse. North of MW, 

diversity drops at the HU population owing to its high frequency of the 112 bp allele 

relative to the other populations in Mendocino, Humboldt and Del Norte Counties. 

Genetic diversity decreases almost linearly with distance in populations south of 

MW, falling to 0.08 in the southernmost population (MC/LK) where the 112 bp allele 

is nearly fixed (95 percent). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

246

Figure 3—Standardized Shannon diversity index of combined old growth and second 

growth populations at each sampling location (indicated on map inset) vs. distance 

from the northern range limit.

Interpopulation genetic structure 

Using the allele frequency data from combined old growth/second growth paired 

populations, an unrooted neighbor-joining tree based on Nei’s DA distances was 

constructed (fig. 4). The populations segregated into two clades: one containing the 

six populations north of the San Francisco Bay and one containing the four 

southernmost populations. Resampling of data by bootstrapping (Felsenstein 1985) is 

typically performed in order to determine the degree of support for the topography of 

phylogenetic trees. Unfortunately, bootstrapping values cannot be assigned to this 

tree which is based on data from a single locus. 

Trees were also constructed using data from the old growth and second growth 

populations separately (not shown). The tree from second growth population data 

was essentially the same as the combined population tree. The tree from old growth 

population data differed only in the placement of the MT population which appeared 

on an interior branch of the southern clade. This suggests that the allele composition 

of the MT population, in Marin County, is teetering on the “borderline” between the 

northern and southern clades, indicating that it, too, may be succumbing to the effects 

of genetic drift. 
Rangewide Genetic Variation in Coast Redwood Populations at a Chloroplast Microsatellite Locus 

247

Figure 4—Neighbor-joining tree based on Nei’s DA distances calculated from 

combined old growth and second growth populations at each sampling location. 

Discussion

In all 10 locations sampled throughout the range, second growth populations 

were not significantly different in their allelic compositions from adjacent old growth 

populations. Apparently, neither the decreased rate of stump sprouting in redwoods 

over the age of 400 years (Powers and Wiant 1970) nor the higher ratio of ramets per 

genet in second growth forests (Douhovnikoff et al. 2004) altered the genetic 

architecture of naturally regenerated forests to any significant extent. 

Genetic diversity of coast redwood populations at the Seq21E5 locus varied 

considerably, with higher diversity levels in the northern populations and lower 

levels in the southern populations. The MW population, the most genetically diverse, 

is centrally located in the large tract of continuous coast redwood forest ranging from 

central Sonoma County to just north of the Mendocino County-Humboldt County 

border. It is likely that long distance gene flow via pollen would be substantial in this 

region, leading to higher diversity levels than would be present in smaller, more 

fragmented forests. An alternative explanation for the high diversity in the MW 

population is that this region could be closer to the center of expansion of the modern 

range’s founding population and, being older, would be more diverse.

The two southernmost populations along the Monterey County coast, BS and 

MC/LK, are the least genetically diverse and are classic examples of how fragmented 

populations are susceptible to fixation through genetic drift. These and other 

populations along the Big Sur coastline are separated from each other by a severe 

canyon topography and therefore have little or no exchange of pollen with each other 

or with the more diverse populations to the north. Furthermore, Viers (1996) 
GENERAL TECHNICAL REPORT PSW-GTR-238 

248

proposed that the warmer and drier conditions in the southern part of the range would 

cause greater difficulty in seedling establishment resulting in even higher rates of 

clonal reproduction than observed in northern forests. The high incidence of wildfires 

along the Big Sur coast would also lower diversity by promoting clonal over sexual 

reproduction. One can assume that the same evolutionary forces are at work on 

nuclear loci as well, although fixation will occur more slowly in a polyploid genome. 

Although the Santa Cruz County populations (BB/CR and HC) had lower genetic 

diversity values and allele numbers compared to the northern populations, a larger 

sample study (n = 530) in Big Basin Redwoods State Park (Glavas 2006) detected 10 

Seq21E5 alleles compared to six in this study’s combined BB/CR population (n = 

80). Between the two studies, 11 total alleles were observed in this general location. 

Although many of these alleles were found in only one or a few individuals, their 

presence raises the possibility that this region may have once harbored a forest as 

diverse as its neighbors to the north but has since become less diverse through a 

reduction in rare allele frequency through genetic drift. 

The division of populations in the neighbor-joining tree (fig. 4) into northern and 

southern clades with a boundary at or near the San Francisco Bay is in keeping with 

results from previous biochemical, physiological and genetic studies (Anekonda 

1992, Douhovnikoff and Dodd 2011, Hall and Langenheim 1987). Certainly, there is 

no substitute for using multiple loci in phylogenetic studies, but the large population 

sample sizes used in this study, the high variability of the Seq21E5 locus, and the low 

effective population size of the chloroplast genome all contributed to the detection of 

a north-south genetic division despite the use of only one locus. 

While the major genetic transition zone between the northern and southern 

redwood populations has been identified by this and previous studies, the 

evolutionary relationships between redwood populations north of the San Francisco 

Bay remain unclear. The characterization and use of more chloroplast microsatellite 

loci would allow for a much more powerful phylogenetic analysis of that very 

important part of the redwood range. 

Acknowledgments

I would like to thank the USDA Forest Service, the National Park Service, and 

the California Department of Parks and Recreation for issuing collecting permits; 

Rueben Bolton, Greg Brinegar, Michele Conrad and Steve Glavas for collecting 

assistance; Dr. Robert Fowler (San Jose State University) for the use of his laboratory 

for DNA extractions; and Bonnie Brinegar for generous financial support. 

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251

Reference Conditions for Old-Growth 

Redwood Restoration on Alluvial Flats

Christa M. Dagley1 and John-Pascal Berrill1 

Abstract 

We quantified structural attributes in three alluvial flat old-growth coast redwood stands. Tree 

size parameters and occurrences of distinctive features (e.g., burls, goose pens) were similar 

between stands. Occurrence of distinctive features was greater among larger trees. Tree sizefrequency distributions conformed to a reverse-J diameter distribution. The range of tree sizes 

was similar between study sites. Redwood density ranged from 118 to 148 trees ha-1 and 

upper canopy tree density ranged from 45 to 74 trees ha-1. Crown ratio was similar across 

study sites with an overall mean of 64.3 percent, except that crown ratio of the largest trees 

was lower at the site with the highest growing space occupancy. The percentage of plot area 

in canopy gaps ranged from 17 to 25 percent. Seedling regeneration was no more frequent 

beneath canopy gaps. These and other results describe structure in old-growth redwood forests 

and can serve as reference conditions for old forest restoration on alluvial flats. 

Key words: canopy gaps, regeneration, Sequoia sempervirens, stand structure

Introduction

Old-growth redwood (Sequoia sempervirens) forests are structurally diverse, 

having been shaped over centuries by a wide range of forces (Lorimer et al.2009). 

Trees with diameters of 2 to 4 m and heights of 60 to 100 m are common. The desire 

to restore some of these features in managed forests has prompted application of 

various silvicultural practices, yet to date, little attention has been directed at 

developing a detailed description of structural parameters and distinctive features 

found in old-growth redwood forests that describe the historic condition and could 

serve as reference conditions for restoration. 

Quantification of old-growth forest structure supports restoration efforts by 

providing reference conditions that could serve as targets for management activities 

(Harrod et al. 1999, SERISPWG 2004). The objective of this study was to identify 

structural parameters and distinctive features that were characteristic of alluvial flat 

old-growth redwood stands and may thus serve as targets for restoration of old forest 

structures. We hypothesized that: (1) multivariate analysis would not successfully 

discriminate between study sites on the basis of tree size and crown parameters; (2) 

seedling regeneration was no more frequent directly beneath canopy gaps than 

beneath tree crowns; and (3) the occurrence of distinctive features (e.g., epicormic 

sprouting) on live trees differed between sites, and was greater among larger trees. To 

test these hypotheses, calculate canopy gap areas and canopy volume, and summarize 

total live stem biomass, coarse woody debris, and regeneration data, we made 

detailed measurements of various tree size and crown size parameters, mapped tree 

locations, and recorded instances of distinctive features on individual redwood trees. 

 

1 Research Associate and Assistant Professor, respectively, Department of Forestry and Wildland 

Resources, Humboldt State University, Arcata, CA 95521 (cd104@humboldt.edu). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

252

Methods 

Three study sites were selected—from the few larger remaining old growth 

groves on alluvial flats in northern California—to each represent different conditions 

and locations. Two of the study sites, named Children’s and Rockefeller, were 

located at Humboldt Redwoods State Park in the southern part of Humboldt County 

(N 40°18.5’, W 123°54.4’). The study site at Children’s Forest in HRSP was located 

along the south fork of the Eel River adjacent to Myers Flat. Children’s differed from 

the other two study sites in that a wildfire occurred there 1.5 years prior to study 

installation. The Rockefeller site in HRSP was approximately 14 km NW of the 

Children’s site and located along the small perennial Bull Creek. Mean annual 

temperature for the HRSP area is 12.6 °C and mean annual precipitation is 123 cm. 

The third study site, named Armstrong, was located alongside a seasonally dry creek 

at Armstrong Redwoods State Preserve (ARSP) in the Russian River region of 

Sonoma County (N 38°53’, W 123°0.6’). Mean annual temperature for ARSP is 13.9 

°C and mean annual precipitation totals 104 cm. 

Plants common to these redwood-dominated sites included redwood sorrel 

(Oxalis oregano) and western sword fern (Polystichum munitum). Hardwoods such as 

tanoak (Notholithocarpus densiflorus), bigleaf maple (Acer macrophyllum), and 

California bay (Umbellularia californica) were found in small numbers in openings 

or near streams. 

At each site, a 1 ha sample plot (100 m x 100 m) was established with the 

objective of quantifying the horizontal and vertical structure. All trees ≥ 15 cm 

diameter at 1.37 m breast height (dbh) were mapped using a survey laser mounted on 

a tripod. Species, dbh, and location (e.g., azimuth and horizontal distance to the 

middle of each tree from reference points) were recorded. To assure mapping was 

accurate, the angle and distance from plot center to each reference point was recorded 

and cross-checked with tree locations taken from both plot center and the respective 

reference point. Additionally, all trees ≥ 15 cm dbh were measured for total height,

live crown base height, and crown radius. Live crown base height was defined as the 

height of the lowest major branch that formed part of the main canopy. The number 

of crown radius measurements varied with complexity of crown shape. A minimum 

of four crown radius measurements were taken, each in a cardinal direction, for small 

trees with circular crowns. A maximum of eight measurements were taken for large 

trees with irregular crowns. Crown class, crown shape, and crown fullness estimates 

were recorded for each tree. The three-dimensional shape of individual tree crowns 

was most often described as a parabola; however, some were described as a cone, 

cylinder, or diamond. Crown fullness was an ocular estimation of the percentage of 

the live crown occupied by branches and foliage (e.g., 50, 66, 75 percent). Because 

older trees often have discontinuous crowns, incorporating the “fullness” variable 

into the crown volume equation provided a more accurate estimate of actual space 

occupied by live tree crowns. 

For each redwood tree, we noted presence or absence of the following distinctive 

features: burls, epicormic sprouting, goose pens, and reiterations. A goose pen was 

defined as a large fire-created basal hollow greater than 30 or 60 cm tall for trees less 

than or greater than 1 m dbh, respectively. A reiteration was defined as an erect 

sprout or branch found on an existing tree but supporting its own network of 

horizontally oriented branches. Three 100 m north-south transects were established in 
Reference Conditions for Old-Growth Redwood Restoration on Alluvial Flats 

253

each 1 ha plot with the objective of quantifying regeneration, understory vegetation, 

and groundcover. Height, location, species, and regeneration source (i.e., sprout 

versus seedling) were recorded for all trees < 15 cm dbh in a continuous 4 m wide 

belt centered on each transect line. Percent ground cover values were obtained by 

dividing the entire length of each transect line into one centimeter sections and 

recording species of shrubs, herbaceous vegetation, bareground, and litter covering 

ground directly below the transect line. Down logs ≥ 30 cm diameter and ≥ 2 m 

length were mapped and measured to determine the volume, mass, and percent cover 

of large down wood at Children’s and Rockefeller. Diameter at the midpoint of each 

length of down log, log length, and location were recorded. Only the portions of logs 

falling inside the plot were measured. Down logs at Armstrong were not measured 

due to a history of removal of down wood from the site. Standing dead trees (snags) 

≥ 15 cm dbh were mapped and measured for dbh at the three study sites. 

Data for live trees with dbh ≥ 15 cm were summarized to give per-hectare stem 

density, basal area, and stem volume, stand density index (Reineke 1933), and 

maximum tree height for each species at the three study sites. Stem volume (V) was 

calculated using a simple conic shape: V=π(0.5 dbh)

2

h/3 where dbh = dbh in m and h

= total tree height in m. Stand density index (SDI) was calculated as a summation of 

individual tree values because the dbh data were not normally distributed: 

SDI=∑(0.04dbhi)

a where dbhi = dbh in cm of the ith tree in the plot, and a = 1.605 

(Long and Daniel 1990, Shaw 2000). Trees were grouped into 30 cm dbh size classes 

to give size-frequency distributions for each site. Individual tree size parameters of 

dbh, height, crown radius, crown volume, and crown ratio (ratio of crown length to 

total tree height) were analyzed using canonical discriminant analysis. The objective 

was to identify individual parameters or groups of parameters that differed least 

between sites, assuming these ‘commonalities’ would be more useful targets for 

restoration than parameters that differed between sites. Prior to analysis, a 

logarithmic transformation of dbh was applied to achieve normality of the residual 

variances.

After arc-sine transformation, average crown ratio was calculated for redwood 

trees in each 30 cm dbh size class. Average crown ratios for each size class were 

subjected to an ANOVA to test for significant differences (α = 0.05) between study 

sites. The length of clear bole was defined as the portion of the tree stem not 

occupied by the canopy (equivalent to live crown base height). Clear bole length was 

summarized by 30 cm dbh size classes to further describe the vertical structure of 

standing trees at each site. Crown volume for each tree was calculated using crown 

length, radius, shape, and fullness. Summing crown volume data for all trees in the 1-

ha plots allowed for a site-by-site comparison of total canopy volume. To determine 

the vertical distribution of crowns and crown volume at each site, individual tree 

crown volume was separated into layers at 10-m height intervals and summed for 

each 10 m layer. 

ArcGIS ArcMap (ESRI) was used to delineate and calculate plot area not covered 

by the downward projection of tree crowns. Crown canopy maps of each site were 

created using stem locations and crown radius measurements. Spatial coordinates of 

crown extent were created for each crown radius measurement and then connected 

for each tree to create polygons representing tree crown extent. Polygon boundaries 

were smoothed using a t-spline. To obtain an accurate estimate of gap area within the 

1 ha plots, portions of the crown of trees surrounding the plot that extended inside 
GENERAL TECHNICAL REPORT PSW-GTR-238 

254

plot boundaries were included in the crown canopy maps. This necessitated mapping 

and measurement of crown radii for trees with crowns encroaching on the plot area. 

Crown canopy maps were used to examine the relationship between canopy gaps and 

regeneration.

Location coordinate data for regeneration in each 4-m wide belt transect were 

imported into the crown canopy maps for each site. Each record of regeneration (all 

trees <15 cm dbh) was coded as occurring directly beneath a canopy gap or beneath 

an opening in the canopy. Binomial proportions tests were used to test for differences 

in occurrence of regeneration beneath tree crowns versus regeneration under canopy 

gaps, by species type (i.e., redwood or hardwood) and source of regeneration (i.e., 

sprout or seedling). Count data for regeneration under canopy gaps or tree crowns 

were each divided by the proportions of transect area either under canopy gaps or 

beneath tree crowns, respectively, making count data comparable when different 

proportions of transect area were located directly beneath the canopy and under 

canopy gaps. 

Logistic models were developed to predict probability of occurrence of burls, 

epicormic sprouting, goose pens, and reiterations on individual redwood trees as a 

function of tree-size parameters. Dummy variables for study site were also included 

to test for significant differences in presence-absence of these distinctive features 

between the three study sites. Model goodness-of-fit in terms of -2 Log Likelihood 

was compared between models to identify the tree size parameter (i.e., dbh, height, 

live crown base height, crown length, crown radius) most strongly associated with 

probability of occurrence of distinctive features on redwood trees. Data were 

analyzed using SAS statistical analysis software (SAS Institute 2004).

Results 

Redwood density ranged from 118 to 148 trees ha-1 and density of all live stems 

ranged from 118 to 183 trees ha-1 for the three study sites (table 1). The two sites at 

Humboldt Redwoods State Park (Children’s and Rockefeller) were almost 

completely comprised of redwood. In contrast, the site at Armstrong Redwood State 

Park (Armstrong) contained a mix of hardwoods. Hardwood crowns had not attained 

upper canopy status. The distribution of stems by 30 cm dbh class indicated that 

Armstrong’s higher stem density was mostly in the small size classes and because of 

the hardwood presence. The frequency distribution of redwood tree diameters was a 

reverse-J shape at the three study sites. The two northern sites (Children’s and 

Rockefeller) contained larger diameter trees while a narrower distribution of 

diameters at Armstrong was observed (fig. 1). Mean dbh was similar at Armstrong 

and Children’s (1.10 and 1.08 m, respectively). Mean dbh at Rockefeller was 1.45 m. 
Reference Conditions for Old-Growth Redwood Restoration on Alluvial Flats 

255

Table 1—Species composition and stem density per hectare by crown class for all live trees ≥ 

15 cm dbh in the 1-ha plot at the three alluvial flat old-growth redwood study sites.

Site Species Dominant Codom. Intermediate Suppressed Total

Armstrong S. sempervirens 47 27 27 47 148

A. macrophyllum -- -- 4 2 6

N. densiflorus -- -- 5 2 7

U. californica -- -- 19 3 22

Total 56 27 46 54 183

Children’s S. sempervirens 13 33 45 37 128

U. californica -- -- 2 1 3

Total 14 33 46 38 131

Rockefeller S. sempervirens 29 16 44 29 118

Figure 1—Diameter distribution of live trees ≥ 15 cm dbh for 1-ha plots at the 

three alluvial flat old-growth redwood study sites.

Structural attributes of redwood basal area, canopy volume, and total standing 

stem volume tended to be similar at Children’s and Armstrong study sites, and 

highest at Rockefeller (table 2). Among these structural attributes, total standing stem 

volume differed most between study sites. Basal area and total standing stem volume 

at Rockefeller were at least 30 and 37 percent greater, respectively, than at Children’s 

and Armstrong. Similarly, redwood SDI was greater at Rockefeller than at Children’s 

and Armstrong (metric SDI: 2529, 1884, 2057, respectively). Maximum height was 

similar at the two northern sites and taller compared to Armstrong. Total canopy 

volume for the three sites was similar in overall value but was distributed differently 

along the vertical profile (table 2, fig. 2). Peak canopy volume values differed 

between the three study sites; Armstrong peaked at a lower height (40 m) than the 

two northern sites, Children’s peaked at 50 m, and Rockefeller had the most crown 

volume at 60 m above ground. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

256

Table 2—Basal area (BA), canopy volume, total standing stem volume, and height of the 

tallest tree (Max. Ht.) for live trees ≥ 15 cm dbh in the 1-ha plot at the three alluvial flat oldgrowth redwood study sites. 

Site Species BA

(m2 ha-1) 

Canopy volume 

(m3 ha-1) 

Stem volume 

(m3 ha-1) 

Max. Ht. 

(m)

Armstrong S. sempervirens 228.3 168,281 5,542 95

A. macrophyllum 0.3 838 1.7 24

N. densiflorus 0.3 588 1.3 18

U. californica 4.8 15,363 60.2 49

Total 233.7 185,070 5,605 --

Children’s S. sempervirens 225.1 171,806 6,732 105

U. californica 0.8 1,186 15.9 59

Total 225.9 172,992 6,748 --

Rockefeller S. sempervirens 307.8 174,588 9,272 107

Canonical discriminant analysis revealed significant structural differences 

between the three sites. Armstrong and Children’s sites were found to be the most 

different (P < 0.0001) while the two northern sites, Children’s and Rockefeller, were 

found to be the least different (P = 0.007). The analysis discriminated between the 

sites predominantly on the basis of dbh and height, suggesting that height to diameter 

ratio was the most important structural difference between sites. The analysis also 

revealed different tree diameter – crown volume relations between sites. However, 

modest allocation rates (42 to 57 percent) indicated that the sites could not be 

separated easily by tree size parameters. 

Figure 2— Canopy volume distribution by 10-m height interval along vertical 

profile for each alluvial flat old-growth redwood study site, based on tree crown 

volume estimates for redwood stems ≥ 15 cm dbh.

Long crowns were a common feature at the three study sites (table 3). The 

overall mean crown ratio for the three study sites was 64.6 percent. An F-test failed 

to detect significant differences in mean crown ratio for each 30-cm dbh size class 

between the three study sites (P = 0.14). However, differences in crown ratio 
Reference Conditions for Old-Growth Redwood Restoration on Alluvial Flats 

257

between sites were detected in an F-test of tree crown ratio data for large trees (i.e., 

trees > 1.5 m dbh; P = 0.001). Further analysis of data for large trees detected no 

significant difference in crown ratio between Children’s and Armstrong sites (P = 

0.92), whereas crown ratios at these two sites differed significantly from the 

Rockefeller site (P ≤ 0.005) where the larger trees had longer clear boles and shorter 

crowns (table 3). 

Table 3—Average crown ratio (CR) and length of clear bole (CB) by 30 cm dbh size class for 

all redwood trees ≥ 15 cm dbh at the three alluvial flat old-growth redwood study sites. 

Dbh class Armstrong Children’s Rockefeller

midpoint (cm) n CR CB (m) n CR CB (m) n CR CB (m)

30 45 .61 6 51 .62 8 31 .68 6

60 24 .71 9 18 .70 13 11 .76 9

90 12 .69 16 8 .69 21 11 .69 17

120 14 .65 22 15 .66 24 7 .67 23

150 11 .64 24 8 .66 27 12 .69 22

180 7 .74 21 8 .61 34 11 .58 34

210 15 .67 23 2 .74 22 6 .64 32

240 11 .55 35 3 .68 30 5 .50 44

270 6 .61 32 3 .64 34 5 .59 40

300 3 .65 30 2 .65 35 6 .58 41

330 0 -- -- 1 .47 47 6 .50 47

360 0 -- -- 5 .61 39 3 .50 47

390 0 -- -- 3 .73 27 2 .62 38

420 0 -- -- 1 .84 15 2 .54 46

Mean -- .65 -- -- .65 -- -- .64 --

The sum of canopy gap areas as a percentage of total plot area was similar at the 

three sites, ranging from 17 to 25 percent. Gap shape and size were variable (fig. 3). 

For gaps contained within plot boundaries there was an approximate reverse-J 

distribution in gap sizes. Rockefeller had one large gap (>1272 m2

) which extended 

beyond the plot boundary and accounted for 50 percent of the total gap area within 

the plot. 

Figure 3—Canopy map of tree crown projections in 1-ha plots at (a) Armstrong; (b) 

Children’s; and (c) Rockefeller alluvial flat old-growth redwood study sites. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

258

Regeneration density and species composition differed between study sites (table 

4). Hardwood trees < 15 cm dbh were found at Armstrong and Rockefeller. 

Armstrong contained a mix of hardwoods including tanoak, California bay, and red 

alder (Alnus rubra). In contrast, Rockefeller contained only one hardwood species, 

tanoak. Redwood sprouts and seedlings were present at all three sites. Binomial 

proportions tests did not detect differences between the occurrence of redwood 

sprouts or seedlings occurring in canopy gaps and redwood regeneration beneath the 

canopy (P ≥ 0.31), nor between hardwood sprouts or individuals occurring in gaps or 

beneath the canopy (P ≥ 0.12). Most redwood regeneration found along transects was 

in the form of basal sprouts associated with an existing root system.

Table 4—Regeneration density per hectare for all trees < 15 cm dbh in three 400 m2 belt 

transects at each alluvial flat old-growth redwood study site. 

Site Species Sprouts Seedlings Total

Armstrong Sequoia sempervirens 1125 48 1173

Hardwoods 404 538 942

Children’s Sequoia sempervirens 1538 25 1563

Rockefeller Sequoia sempervirens 158 150 308

Hardwoods 483 517 1000

The main constituents of the forest floor were similar among sites, with redwood 

sorrel, sword fern, and litter most prevalent. However, the proportions of these 

elements differed between sites. Rockefeller contained almost an even mix of litter, 

redwood sorrel, and sword fern (35, 21, and 32 percent, respectively). Children’s 

groundcover was almost a complete blanket of redwood sorrel (76 percent), probably 

as a result of the fire. Armstrong’s ground cover was dominated by litter (54 percent) 

followed by redwood sorrel (30 percent), and sword fern (6 percent). Consistent with 

the higher tree species diversity found at Armstrong, the understory was also most 

diverse and included fragrant bedstraw (Galium triflorum), trail marker 

(Adenocaulon bicolor), fairybell (Disporum hookeri), and wood rose (Rosa 

gymnocarpa). 

Epicormic sprouting was the most common distinctive feature at each site. Burls, 

epicormic sprouting, goose pens, and reiterations were more common among larger 

redwood trees (fig. 4). Most redwood trees had one type of distinctive feature and 

very few trees had all of these features. The natural logarithm of tree dbh was a 

stronger predictor of the probability of occurrence of distinctive features than either 

tree height, live crown base height, crown length, or crown radius. The probability of 

occurrence of epicormic sprouting was greater at Children’s and lower at Armstrong 

when compared with incidence of epicormic sprouting for any given tree size at 

Rockefeller. Logistic model coefficients indicated that redwood trees at Children’s 

were less likely to have a goose pen than trees of equivalent dbh at either Armstrong 

or Rockefeller (table 5). 
Reference Conditions for Old-Growth Redwood Restoration on Alluvial Flats 

259

Figure 4—Percentage frequency distribution of redwood trees having a distinctive 

feature by 30 cm dbh class, based on pooled data from the three alluvial flat oldgrowth redwood study sites. 

Table 5—Coefficients and fit statistics for logistic model of the presence of burls, epicormic 

sprouts, goose pens, and reiterations as a function of the natural logarithm of dbh for alluvial 

flat old-growth redwood trees ≥15 cm dbh (n=394). Dummy variables for study sites were

included when differences detected between sites (α=0.05). 

Distinctive Feature Parameter Coefficient s.e.a Wald’s χ2 Pr > χ2

Burls Intercept 1.0617 0.15 52.70 <0.0001

(Model -2LL = 346.5) Ln dbh -1.7086 0.20 76.08 <0.0001

Epicormic sprouts Intercept -1.0899 0.13 70.94 <0.0001

(Model -2LL = 438.9) Ln dbh -0.3871 0.13 9.43 0.0021

 Armstrong -0.7871 0.16 25.48 <0.0001

 Children’s 0.7660 0.19 16.47 <0.0001

 Rockefeller 0.0000 -- -- --

Goose pens Intercept 2.4330 0.23 107.86 <0.0001

(Model -2LL = 225.8) Ln dbh -1.7091 0.28 36.91 <0.0001

 Armstrong 0.2623 0.25 1.12 0.2894

 Children’s -0.8022 0.24 11.31 0.0008

 Rockefeller 0.0000 -- -- --

Reiterations Intercept 1.6237 0.15 123.64 <0.0001

(Model -2LL = 327.1) Ln dbh -0.8489 0.17 24.51 <0.0001

-2LL = -2 Log Likelihood, measure of goodness of fit. a s.e. = standard error for coefficient.

The number of large fallen logs was similar at Children’s and Rockefeller study 

sites. Logs at Rockefeller were slightly longer and larger in diameter which resulted 

in almost twice the amount of volume and area covered by logs at Rockefeller (table 

6). There appeared to be no trend in the direction of tree fall and most of the logs 

were found to be scattered widely across each site. One exception occurred at 

Rockefeller. The eastern side of the plot contained a large gap which was created by 

three large fallen trees that fell in the easterly direction. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

260

Table 6—Coarse woody debris characteristics for Children’s and Rockefeller alluvial flat 

old-growth redwood study sites. Minimum dimensions of logs sampled were 2 m length and 

30 cm midpoint diameter. Standard error for mean log diameter shown in parentheses. 

Site Density 

(logs ha-1)

Mean diameter 

(m)

Volume 

(m3 ha-1)

Cover a

(%)

Mass b

(tons ha-1)

Children’s 14 1.09 (0.12) 570 3.7 114

Rockefeller 19 1.25 (0.17) 1072 6.8 214 a Cover represents percent ground area covered by downward projection of logs. b Mass estimated as volume by an averaged wood density from Bingham and Sawyer (1988). 

Standing dead trees (snags) ≥ 15 cm dbh appeared to be exclusively redwood at 

the three sites. The two snags within the plot at Armstrong were 1.5 and 1.6 m dbh. 

The two snags at Rockefeller were 0.7 and 3.5 m dbh. The eight snags at Children’s 

included four small dead-standing redwood trees (dbh < 40 cm) that appeared to have 

sustained severe fire damage and died recently. The other four snags at Children’s 

ranged from 0.9 to 2.2 m dbh. 

Discussion 

Our work provides an important description of structural characteristics in 

alluvial flat old-growth redwood forests. Density, diameter distribution, crown ratio, 

and total canopy gap area were most similar among study sites. As such, they may 

serve as key reference conditions for future restoration treatments (table 7). 

Table 7—Reference conditions for alluvial flat old-growth redwood forests. 

Condition Description 

Stand densitya Redwood 118-148 trees ha-1

Upper canopy tree densityb 45-74 trees ha-1; mean dbh 2.1 m; range 0.55-4.27 m dbh

Crown ratio Trees > 1.5 m dbh: 0.56-0.64; trees ≤ 1.5 m dbh: 0.65 

Canopy gap area 17-25% total area in gaps

Coarse woody debrisc Density 14-19 logs ha-1; mean midpoint diameter 1.2 m; mean 

length 26.6 m; cover 3.7-6.8%; mass 114-214 tons ha-1 

Snags 2-4 dead standing trees ha-1; range 0.9-3.5 m dbh

Spatial pattern Random pattern for redwood > 1.5m dbh (Dagley 2008) a Trees ≥ 15 cm dbh.

b Dominant and codominant trees. 

c Logs ≥ 30 cm midpoint diameter and 2 m length. 

Similarities between our data and published density data suggest both overall 

redwood density and upper canopy density can be useful reference points in old 

forest restoration efforts. Van Pelt and Franklin (2000) reported a main canopy 

density of 46 trees ha-1. Sugihara (1992) reported an overall redwood density of 182 

trees ha-1 for trees > 10 cm dbh and a density of 67 trees ha-1 for redwood trees > 1.5 

m dbh. A redwood density of 107 trees ha-1 for trees > 10 cm dbh was reported for a 

stand located in Prairie Creek Redwoods State Park (Sawyer and others 2000). 

Fujimori (1977) reported 66 trees ha-1 for trees > 1 m dbh. 

Stand density index (SDI) is a measure of growing space occupancy, and is 

useful for quantifying relative density across a wide variety of stand conditions (Long 

and Daniel 1990). Reineke (1933) reported that the maximum SDI for redwood is 
Reference Conditions for Old-Growth Redwood Restoration on Alluvial Flats 

261

approximately 2500 (equivalent to an SDI of 1000 in English units) based on data 

from even-aged second growth stands. The SDI was highest at Rockefeller, and 

slightly exceeded the maximum reported by Reineke (1933). This could explain the 

lower crown ratios among larger trees (table 3) and lower regeneration density (table 

4) at Rockefeller. 

Old-growth redwood tree crowns occupy an immense amount of space. Van Pelt 

and Franklin (2000) reported a canopy volume of 230,100 m3

 ha-1 with the maximum 

occurring at a height of 50 m for a stand on the alluvial flats in Humboldt Redwoods 

State Park. This value exceeded our estimates (172,992 to 185,070 m3

 ha-1; table 2) 

but was based on a conic representation of tree crown volume. We generated more 

realistic estimates by describing the shape and fullness of individual tree crowns. 

Crown shape impacts volume estimation and placement of crown volume in the 

vertical profile (fig. 2). For example, the volume of a parabola is 50 percent greater 

than that of a cone. When compared with crown volume estimates obtained using a 

cone shape, canopy volume estimates from this study were 10 m higher in the vertical 

profile when shape was taken into account. The shape was most often described as a 

parabola and the average crown fullness was 60 percent. 

Total canopy gap area ranged from 17 to 25 percent between sites. These values 

closely resembled reported values from other old-growth stands ranging from 18 to 

20 percent (Busing and Fujimori 2002, Sugihara 1992, Van Pelt and Franklin 2000). 

Gap size and shape were variable, suggesting that treefall events involved individual 

trees or groups of trees. 

A preference to establish under canopy gaps was not detected among redwood 

regeneration. Hunter (1995) found the influence of canopy gaps to only account for 

4.6 percent of the variation in understory light levels in a mixed evergreen forest 

(containing redwood) in Northern California. He proposed that several factors limit 

the effects of canopy gaps on the understory: temperate latitude placing the sun at 

lower angles, a dry summer season restricting growth when light is at its highest 

angle in the sky, a tall canopy, and small gap diameters. Van Pelt and Franklin (2000) 

found no relationship between understory tree location and canopy gaps. 

Exposure to wind and windstorm events likely affects stem form. Results from 

the multivariate discrimant analysis revealed differences in tree height-diameter 

relations between study sites. Our use of a simple conic shape to estimate stem 

volume is repeatable, but highlights need for reliable predictive volume and taper 

equations. Existing equations predict merchantable volume above a tall stump to 

large top diameters, not total stem volume. Differences in stem taper and incidences 

of top breakage and reiteration will complicate the task of modeling stem volume and 

whole-tree biomass: a priority for future research. 

Our characterization of coarse woody debris highlighted differences between 

sites (table 6). These differences may in part be due to stand history. Over time, 

down logs may have been removed for use or aesthetics. Yet, the lowest published 

estimates remain two to five times greater than those reported for most other 

temperate or tropical forests (Franklin and Waring 1980). Our estimates of 114 and 

214 metric tons ha-1 for Children’s and Rockefeller, respectively, fall within the range 

of values reported for alluvial flats (Busing and Fujimori 2005, Sugihara 1992). 

The study sites at Armstrong, Children’s, and Rockefeller were selected to 
GENERAL TECHNICAL REPORT PSW-GTR-238 

262

represent alluvial flat old-growth redwood forests with different site characteristics 

and/or recent disturbance histories. Our data and analyses revealed that each stand 

had unique attributes, but also shared features with the other study sites, suggesting 

that these commonalities could represent general reference conditions or “targets” for 

future restoration efforts (table 7). For example, managers seeking to accelerate 

development of old-growth characteristics in a young stand might begin by 

identifying approximately 50 to 80 overstory trees ha-1 in a random spatial 

arrangement, and releasing these trees from competition. Retaining more trees would 

allow for artificial creation of 2 to 4 snags ha

-1 in the absence of natural mortality. 

Concurrently identifying one or more open areas to serve as large canopy gaps 

between overstory tree crowns might preclude future conflict between overstory tree 

density and canopy gap area requirements. Less regard, at least initially, might be 

paid to structural parameters or distinctive characteristics that differed between the 

three reference sites or that correlated with tree size. When combined with 

descriptions of the spatial pattern of tree locations within stands (Dagley 2008), this 

work represents a detailed quantitative description of the three dimensional structure 

and complexity found in old-growth redwood forests on alluvial flats. 

Acknowledgments

The project was funded by Save-the-Redwoods League and The Center for 

Forest Disturbance Science, Southern Research Station, USDA Forest Service. 

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265

Fog and Soil Weathering as Sources of 

Nutrients in a California Redwood Forest 

Holly A. Ewing,

1 Kathleen C. Weathers,2 Amanda M. Lindsey,2

Pamela H. Templer,

3 Todd E. Dawson,4 Damon C. Bradbury,4 Mary 

K. Firestone,4 and Vanessa K.S. Boukili5

Abstract 

Fog water deposition is thought to influence the ecological function of many coastal 

ecosystems, including coast redwood forests. We examined cation and anion inputs from fog 

and rain, as well as the fate of these inputs, within a Sonoma County, California, coast 

redwood forest to elucidate the availability of these ions and some of the biotic and abiotic 

processes that may influence their relative abundance. At this site, the patterns of water and 

chemical inputs via fog and rain and their movement through the soil-plant ecosystem differed 

between the summer fog and winter rain seasons. Most (98 percent) of the annual water and 

more than three quarters of the total ionic load was delivered to the forest during the rain 

season. Soil water patterns followed those of throughfall. Water for plant use was most 

available in the rain season; however, after large fog events (fog season) plant-available soil 

water was also present at the forest edge. Differences between soil water and throughfall 

chemistry were a function of the mobility of each ion, whether or not an ion was a soil 

weathering product, and the likely biological demand for the ion. The impact of redwoods as 

fog catchers, transformers, and redistributors of both water and nutrients may extend all the 

way into the soil profile: in our plots, organic-rich soil horizons were thicker at the forest edge 

than in the forest interior. Our data show that, although total fog water inputs were small 

compared to inputs from rain, fog carried a large proportion of the total aqueous ionic 

inputs—inputs that, presumably, continued to be biologically available until their loss during 

the rain season. Cross-seasonal, functional coupling of aboveground (canopy) and 

belowground (soil) processes are likely to be prevalent in this redwood and other foginundated forests.

Key words: canopy, fog, input-output, rain, redwoods, soil

Introduction

Fog water deposition is thought to influence the ecological function—from plant 

physiology (Burgess and Dawson 2004, Limm et al. 2009, Simonin et al. 2009, 

Williams et al. 2008) to ecosystem function (Ewing et al. 2009, Weathers et al. 

2000)—of many coastal forests, including coast redwood forests. Within California, 

redwoods inhabit a narrow strip of land from approximately 42 to 35.8 degrees N 

latitude and a zone fewer than 40 km from the ocean, a region known for its summer 

fog and winter rain (Noss 2000). Research on soil water and understory plants 

(Dawson 1998, Limm and Dawson 2010, Limm et al. 2009) and trees (Ambrose et al. 

2009, Burgess and Dawson 2004, Ewing et al. 2009, Ingraham and Matthews 1995, 

 

1 Bates College. (hewing@bates.edu). 2 Cary Institute of Ecosystem Studies. (weathersk@caryinstitute.org; lindseya@caryinstitute.org). 3 Boston University. (ptempler@bu.edu). 4 University of California, Berkeley. (tdawson@berkeley.edu; bradbury@nature.berkeley.edu; 

mkfstone@nature.berkeley.edu) 5 University of Connecticut. (vanessa.boukili@huskymail.uconn.edu). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

266

Limm et al. 2009, Simonin et al. 2009) has shown that fog water is taken up directly 

into plant leaves within fog-enshrouded coastal California forests. 

Much less is known about the influence of fog on biogeochemical processes, 

especially in regard to the influence of fog chemistry on ecological function. 

Nutrients and chemicals are consistently more concentrated in fog than rain (Collett 

et al. 2002, Weathers et al. 1986, Weathers et al. 1988, Weathers et al. 2000), 

suggesting that fog could be an important vector of nutrients and pollutants even 

when it contributes a relatively small fraction of the total water input (Azevedo and 

Morgan 1974, Ewing et al. 2009, Weathers 1999, Weathers and Likens 1997, 

Weathers et al. 1988, Weathers et al. 2000). In the redwood forests of California 

where fog drip is high in the summer, fog brings a fifth (21 percent) of the total 

nitrogen delivered via atmospheric deposition and below-canopy drip to the forest 

floor even though it delivers as little as six percent of the water to the same location 

(Ewing, et al. 2009). Fog in California, like other coastal and inland regions, can 

carry substantial amounts of calcium, magnesium, potassium, and sodium (Ca+2, 

Mg+2, K+

, and Na+; for example, Weathers et al. 1986), and it has been proposed that 

these elements might influence nutrient cycling, soil fertility, and understory plant 

growth (Azevedo and Morgan 1974, Weathers 1999, Weathers et al. 1986) by 

enhancing the availability of essential major or minor nutrients. However, no studies 

have examined delivery of these nutrients to redwood forests via fog and rain within 

the same forest nor their abundance in soil water. 

We examined fog and rain inputs, as well as the fate of these inputs, within a 

Sonoma County, California, coast redwood stand to elucidate the potential role of fog 

in the cycling of major mineral cations and anions. Our objectives were (1) to 

elucidate the importance of fog as a vector for the delivery of major mineral cations 

and anions to a redwood forest, and (2) to trace the movement of these ions through 

soil water to better understand the interplay between inputs, transformations, and 

translocations within the atmosphere-plant-soil water system.

Methods

Our research was conducted at a coast redwood forest site in Occidental, Sonoma 

County, California (see Ewing, et al. 2009 for a more complete description). About 

96 percent of the annual precipitation falls between October and May (hereafter rain 

season); the warm summer season (hereafter fog season) is a time of little rain.

Intensive measurements of fog, bulk precipitation, throughfall (TF), and soil 

water were made at the Sonoma site from 2003 to 2007 (see Ewing et al. 2009 for 

full details). Briefly, TF collectors were arrayed from the forest edge to interior in a 

five-band stratified random design. Two additional (bulk) collectors were placed in 

open grassy areas outside the forest to the southwest of the forest stand. Fog water 

was collected outside the forest using a passive fog collector with a plastic mesh 

collection surface (after Azevedo and Morgan 1974). Soil water was collected using 

two tension lysimeters (TL; Soil Moisture 1900 series), installed at a depth of 12 cm 

and set to -50 kPa, and two zero-tension lysimeters (ZTL; PVC trough installed in a 

soil pit face draining into a collection bottle) at a depth of 70 cm in each of the five 

bands inside the forest and the clearing. Soil profile descriptions were done in each 

band in the forest as well as in the field outside the forest at the time of lysimeter 

installation.
Fog and Soil Weathering as Sources of Nutrients in a California Redwood Forest 

267

Aqueous TF, bulk, fog, and soil water samples were collected every week during 

the fog season and every two weeks during the rain season between July 2003 and 

April 2006. Sampling handling, including nitrogen analysis, is detailed in Ewing et 

al. (2009). Samples were analyzed at the Cary Institute (IES) for bromide, chloride, 

phosphate, and sulfate (Br-

, Cl-, PO4

3-, SO42-) on a Dionex DX-500 IonChromatograph and for Ca2+, Mg2+, K+

, and Na+ on a Perkin-Elmer P400 inductively 

coupled plasma emission spectrometer, after Weathers et al. (2001). Samples with 

concentrations below the method detection limits were set at half the detection limit 

for data handling. 

Seasonal mean, median, minimum, maximum, and first and third quartile ion 

concentrations for fog, bulk, TF, TL, and ZTL samples were calculated over all 

sampling periods for each season; TF and bulk ion concentrations were volumeweighted before statistical analysis. Season delineation follows Ewing et al. (2009). 

Results

Nutrients and other chemicals were more concentrated in fog than rain, and fog 

delivered a substantial proportion of the ionic load to the forest floor even though fog 

constituted only two percent of the total water delivered via TF (Ewing et al. 2009). 

On average, ions in fog water collected outside the forest were about 10-fold (range 

three- to 46-fold) more concentrated than in rain water for all elements, and ions were 

likewise more concentrated in TF in the fog season (seven- to 22-fold) than in the 

rain season (fig. 1). However, the large amount of precipitation in the rain season 

meant that the highest per-day inputs of both water and ions were in the rain season 

rather than the fog season. However, the flux of ions to the forest floor via TF (on a 

per day basis, charge delivered per unit area; eq/ha) from fog was, on average, 

approximately 20 percent that of rain (data not shown; Ewing, et al. 2009). The 

dominant ions were similar for fog, rain, and TF. In all collections, Na+

, K+, Mg2+, 

and Ca2+ made up the majority of cations, while Cl- and SO4

2- dominated the anions. 

Bromide, PO4

3-, NO3-

, and NH4

+

 made up a relatively small proportion of the total 

ionic load (fig. 1). Nitrate was the only ion that was consistently less concentrated in 

TF relative to fog. Most other ions had more variable concentrations in TF than in 

bulk collections, and the non-acid cations in particular were more often more 

concentrated in TF than in collections outside the forest (fig. 1). 

Nearly all ions delivered to the soil via TF were also found in lysimeters, but 

their concentrations differed as a function of lysimeter position within the soil and 

were variable across fog and rain seasons. As reported in Ewing et al. (2009), soil 

water was collected throughout the rain season in the near-surface soil (12 cm, TL), 

but it took approximately a month of rain before water began to drain freely and be 

collected in the ZTL at 70 cm. Only rain season data are reported here. The non-acid 

cations Ca2+, Mg2+, Na+

, and K+ and the anions SO4

2- and NO3-

 occurred in higher 

concentrations in TL than in TF in the rain season (fig. 2). Chloride and Br- appeared 

in roughly the same concentration in soil water as in TF. Sodium was slightly greater 

in ZTL than TL samples (median concentration) while Ca2+ and K+ were lower in 

ZTL than TL (fig. 2). 

 
GENERAL TECHNICAL REPORT PSW-GTR-238 

268

Figure 1—Ionic concentration (μeq/L) of (A) fog water and fog season throughfall, 

and (B) rain water and rain season throughfall collected in a redwood forest in 

Sonoma County, California. Values for collections at edge and interior sites were 

averaged before plotting; plots show variability among collections within a season. 

Note different concentration scales in (A) and (B).
Fog and Soil Weathering as Sources of Nutrients in a California Redwood Forest 

269

 

Figure 2—Concentration of ions (μeq/L) in throughfall, tension lysimeters and zerotension lysimeters during the rain season, Sonoma County, CA. Values for 

collections at edge and interior sites were averaged before plotting; plots show 

variability among collections within a season.

Discussion

Fog is an important input vector for both water and nutrients for coast redwood 

forests; many cation and anion fluxes are influenced by fog despite small fog water 

fluxes. While water flux outside the forest in the fog season is less than one percent 

of the rain season flux, high redwood tree surface area results in TF flux at the forest 

edge that is more than five times greater than in the open, although almost no TF 

occurred in the forest interior (Ewing et al. 2009). Both the more concentrated nature 

of fog relative to rain and the change in concentration of water—usually an increase 

in concentration—as fog passed through the canopy supported observations made in 

previous studies (for example, Collett et al. 2002, Draaijers et al. 1997, Edmonds et 

al. 1991, Ewing et al. 2009, Weathers et al. 1988).

Where TF deposition via fog drip is high, fog may deliver a significant amount of 

ions to soil. Further, through root uptake of water and microbial processing, fog 

water input has implications for primary production and soil genesis. Root uptake 

would be possible most of the fog season at the edge of the forest where plantavailable water, as evidenced by water found in TLs, was collected from surface soil 

throughout the fog season. Even in more leeward positions in the forest where fog 
GENERAL TECHNICAL REPORT PSW-GTR-238 

270

inputs were less, trees could have access to these ions for the first quarter of the fog 

season when soil water potentials were high (Ewing et al. 2009). Nevertheless, tree 

moisture stress was lower at the windward edge of this forest (Ewing et al. 2009), and 

higher litterfall rates here compared to the interior of the forest indicate that primary 

production may be greater at the more fog-inundated windward edge of the forest 

(Ewing et al. 2009). These differences in inputs and tree production are reflected in 

soil characteristics insofar as soil organic matter concentrations and root densities 

remain higher deeper into the soil profile at the forest edge (data not shown).

Even in places where fog drip does not occur, fog interception by the canopy can 

still supply trees with a wide variety of cations and anions; trees have been shown to

take in fog water through their needles (Burgess and Dawson 2004, Ewing et al. 

2009, Limm et al. 2009, Simonin et al. 2009); they almost certainly are taking in ions 

in these highly concentrated solutions. Early work predicted that canopy interception 

of atmospherically-derived nutrients could be a significant source of plant nutrition in 

some crops (Breazeale et al. 1950, Ingham 1950). While no studies of redwood 

nutrition as a function of fog exist, our data suggest that redwoods have access to fog 

water with high concentrations of many nutrient ions. 

As indicated by increasing concentrations of some ions as they pass through the 

soil system, some elements are clearly made available through soil weathering or 

mineralization in addition to deposition (Ca2+, Mg2+, Na+

, K+), but their fate may 

depend upon their relative importance as limiting elements for plant growth and their 

mobility in soils. Of these, Na+

, which appears in greatest concentration in ZTL 

solutions (70 cm depth), is not needed for plant growth and may be in high 

concentration in the soil either as function of soil weathering or sea salt accumulation 

(Edmonds et al. 1991). Potassium and Ca2+, on the other hand, appear in high 

concentration in TL (plant-available), but lower concentrations in the ZTL, 

suggesting that plant or microbial uptake is important. Sulfate and NO3

-

, like the nonacid cations, appear in higher concentrations in the soil solution than in TF 

suggesting a soil source for them as well. Since the parent material at our study site 

was primarily sandstone (Bradbury 2011), the most likely source for sulfur is 

mineralization of S from organic matter (Bailey et al. 2004). For NO3

-

, high 

concentrations in TL are also likely a result of organic matter decomposition and 

subsequent nitrification of NH4

+

. Since NO3

- is an important nutrient for plants and 

microbes, it is unsurprising that nitrate is in much lower concentration in ZTL, 

suggesting strong conservation within the forest, as with Ca2+ and K+

. 

Implications

Both fog water and the chemical constituents within fog are likely to influence 

biogeochemical cycling in fog- and cloud-dominated forests. Any environmental 

change that affects the frequency, chemistry, and height and depth of fog layers is

likely to impact canopy, soil, and soil water biogeochemical transformation and 

fluxes (Cavelier and Goldstein 1989, Ingraham and Matthews 1995, Johnstone and 

Dawson 2010, Ponette-González et al. 2010). Microbial community structure and 

activity (Bradbury 2011) can also be directly and indirectly affected by fog inputs. 
Fog and Soil Weathering as Sources of Nutrients in a California Redwood Forest 

271

Acknowledgments

Authorship: We make no distinction in effort and contribution between the first 

and second authors. Co-authors are listed in order of relative contributions to this 

paper. S. Simkin assisted with study design, field set-up, and initial sampling; D. 

Herman contributed to field sampling. Funds were provided by a grant from the A.W. 

Mellon Foundation. 

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273

Foliar Uptake of Fog in the Coast Redwood 

Ecosystem: a Novel Drought-Alleviation 

Strategy Shared by Most Redwood Forest 

Plants

Emily Limm1, Kevin Simonin2, and Todd Dawson3 

Key words: fog, understory, Polystichum munitum, leaf wetness, foliar uptake, drought, 

climate

Introduction

Fog inundates the coast redwood forests of northern California frequently during 

the summer months (May to September) when rainfall is largely absent (Azevedo and 

Morgan 1974, Byers 1953, Oberlander 1956). This maritime fog modifies otherwise 

warm and dry summer climate by increasing humidity, decreasing the air 

temperature, reducing solar radiation, and contributing water to the ecosystem 

through leaf wetness and fog drip (Fischer et al. 2008, Grubb and Whitmore 1966, 

Hutley et al. 1997, Williams et al. 2008). Fog water provides an important water 

subsidy for redwood forest plants that face high demand for water during the spring 

growing season and throughout the summer as soil moisture levels decrease (Dawson 

1998, Ewing et al. 2009). In this study, we investigated how effectively fog water 

alleviates redwood forest plant drought stress during the summer and identified foliar 

uptake as a key mechanism promoting plant hydration following exposure to fog.

Foliar uptake is the absorption of water into plant crowns by leaves and stems 

(Rundel 1982). It occurs in diverse taxa around the world directly through the leaf 

cuticle (Gouvra and Gammaikopoulos 2003, Slatyer 1960, Suarez and Gloser 1982, 

Vaadia and Waidel 1963, Yates and Huxley 1995), specialized water-absorbing 

trichomes (Benzing et al. 1978, Franke 1967), or hydathode channels in the leaf 

epidermis (Martin and von Willert 2000). Fog, light rain, and dew may contribute 

little or no water to the soil profile, but may wet leaves for hours at a time (Boucher 

et al. 1995, Breshears et al. 2008, Ewing et al. 2009). Plants with foliar uptake 

capacity can absorb this water whenever their crowns are wet. In this way, foliar 

uptake provides an efficient mechanism to hydrate photosynthetic tissue when water 

is available aboveground because the water does not need to be absorbed from the 

soil first and transported from the roots to the plant crown second (Simonin et al. 

2009). 

Given the frequent occurrence of fog in the coast redwood forest during the 

summer and the known contribution of fog to the annual water budget of redwood 

forest plants (Dawson 1998), we hypothesized that foliar uptake was a common water 

acquisition strategy alleviating drought in the coast redwood ecosystem. Through a 

 

1 Save the Redwoods League, 114 Sansome Street, Suite 1200, San Francisco, CA 94104, 415-820-

5808. (elimm@savetheredwoods.org).

2

 University of Sydney, Australia. 3 Department of Integrative Biology, University of California, Berkeley, CA. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

274

combination of glasshouse experiments using artificial fog chambers and field 

measurements, we studied (1) how many species in the redwood forest absorb fog 

water directly by foliar uptake, (2) geographical variation in the foliar uptake 

capacity of the dominant understory fern, Polystichum munitum, along the redwood 

forest range, (3) how foliar uptake influences the water status of P. munitum, and (4) 

how fog influences the seasonal timing and intensity of drought stress for understory 

plants. 

Methods

Foliar uptake 

To determine if foliar uptake is a shared mechanism for fog water absorption by 

redwood forest plants, we measured changes in leaf water content gravimetrically on 

cut leaves submerged in water for 3 hours to standardize water availability on the leaf 

surface. Single leaves were sampled from potted plants (n=7 per species) of two ferns 

species, P. munitum and Polypodium californicum; two shrub species, Gaultheria 

shallon and Vaccinium ovatum; five tree species, Sequoia sempervirens, Pseudotsuga 

menziesii, Arbutus menziesii, Notholithocarpus densiflora, and Umbellularia 

californica; and one herbaceous species, Oxalis oregano. Changes in leaf water 

content (LWC) were calculated as:

Equation 1 

 

LWC = 100% × [((Mass2-(Mass4-Mass3)-Massdry))/((Mass1-Massdry))-1] 

Where, Mass1 is the leaf fresh mass before submergence, Mass2 is the towel-dried 

leaf fresh mass after 3 hours of submergence, Mass3 is the leaf fresh mass after brief 

air-drying and before a method-control resubmergence, Mass4 is the towel-dried leaf 

fresh mass after a brief resubmergence, and Massdry is the oven-dried mass of each 

leaf. We used one-sample t-test to calculate if LWC increased significantly (α=0.05) 

after leaf wetting. Please see Limm et al. (2009) for further method detail. 

To determine if the dominant redwood forest understory fern P. munitum exhibits 

intraspecific variation in foliar uptake capacity along the redwood forest range, in 

mid-summer we randomly sampled fronds from ten P. munitum crowns in Prairie 

Creek Redwoods State Park, Humboldt Redwoods State Park, the Angelo Coast 

Range Reserve, Hendy Woods State Park, the Grove of Old Trees, Roy’s Redwood 

Preserve, and Big Basin State Park. Foliar uptake capacity was measured on the frond 

samples by calculating the change in LWC gravimetrically after the fronds were 

exposed to water misted on the adaxial leaf surface for ten hours overnight. LWC 

was calculated using equation 1, where the leaves were misted with water droplets 

instead of submerged. We used a linear regression to determine the relationship 

between LWC increase and foliar uptake among sampled redwood forest sites. Please 

see Limm and Dawson (2010) for further method detail. 

Fog effects on plant water status 

To determine if nocturnal fog exposure provides enough hydration to eliminate 

plant water deficit even when soil moisture availability is low, we exposed potted 
Foliar Uptake of Fog in the Coast Redwood Ecosystem: a Novel Drought-Alleviation Strategy 

Shared by Most Redwood Forest Plants

275

plants of P. munitum to four consecutive nights of artificial fog in glasshouse fog 

chambers and measured changes in plant water status. To isolate the effect of leaf 

wetting, we constrained fog exposure to the fern crowns by preventing fog drip into 

the soil and measured soil moisture volumetrically using sensors transecting 20 cm of 

the rooting zone. Over the course of the experiment, we did not add any water to the 

soil to allow the soil moisture to decline. We evaluated maximum plant water status

at predawn after the fogging treatments ended by measuring the leaf water potential 

using a Scholander Pressure Chamber (PMS Instruments, Corvallis, OR) and 

compared fog-exposed fern hydration to control (no-fog exposure) fern hydration 

levels. We used non-linear regression to evaluate the relationship between leaf water 

potential and soil volumetric water content. Please see Limm (2009) for further 

method detail. 

To determine if and when fog alleviates redwood forest plant drought stress, we 

measured seasonal trends in water status for three dominant understory species at the 

Grove of Old Trees, a central forest in the coast redwood ecosystem range. From 

2007 to 2009, we measured the predawn leaf water potential of randomly selected 

plants of S. sempervirens, U. californica, and P. munitum distributed throughout the 

forest (n=15 per species). At each forest location where we measured plant water 

status, we quantified fog drip to the forest floor using throughfall collectors as 

described by Ewing et al. (2009). Please see Limm (2009) for further method detail. 

Results

Foliar uptake 

We found that 80 percent of the redwood forest species we studied exhibit 

capacity for foliar uptake. Only U. californica (a broadleaf tree) and O. 

oregano (a herbaceous understory plant) exhibited no measurable capacity for 

foliar uptake. We observed that LWC increased most (11 percent) in the 

dominant understory fern, P. munitum (fig. 1). Throughout the redwood forest 

ecosystem, the magnitude of P. munitum LWC increase following overnight 

leaf wetting varied significantly (fig. 2) among sites. While an 11 percent 

LWC increase for P. munitum was observed in one site (the Grove of Old 

Trees), P. munitum from most sites averaged LWC increases of approximately 

5 percent. Polystichum munitum from one of the seven sites (Big Basin State 

Park) exhibited no measureable foliar uptake capacity.
GENERAL TECHNICAL REPORT PSW-GTR-238 

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Figure 1—Foliar uptake significantly increased (*) mean (±SE) leaf water content 

(LWC) in the leaves of eight of the ten species studied following three hours of foliar 

submergence in water. This figure is modified from Limm et al. (2009).

 

Figure 2—Among redwood forest sites, the mean (±SE) leaf water content (LWC) of 

Polystichum munitum increased with overnight foliar uptake of water misted on the 

frond adaxial surface. This figure is modified from Limm and Dawson (2010).
Foliar Uptake of Fog in the Coast Redwood Ecosystem: a Novel Drought-Alleviation Strategy 

Shared by Most Redwood Forest Plants

277

Fog effects on plant water status 

In the glasshouse, both fog-exposed and control P. munitum plants maintained 

high predawn water potential (greater than -0.75 MPa) when the soil volumetric 

water content (VWC) was above 5 percent (fig. 3). The water potential of ferns 

exposed to four consecutive nights of leaf-wetting by artificial fog remained high 

even when their soil VWC dropped below 5 percent. In contrast, the water status of 

ferns that received no leaf wetting and only ambient, control conditions for four 

consecutive nights decreased sharply as the soil dried out. Without fog exposure, soil 

VWC below 5 percent resulted in P. munitum predawn water potentials decreasing to 

less than -2 MPa.

Figure 3—Predawn water potential decreased markedly in control ferns (- Fog; 

closed circles) that received no fog exposure during the experiment when the soil 

volumetric water content (VWC) dropped below 5 percent. In contrast, the predawn 

water potential stayed high in the fogged ferns (+ Fog; open circles) that received 

overnight fog exposure regardless of declining soil VWC.

At the Grove of Old Trees, the predawn water potential of all three species 

studied varied significantly, both seasonally and between years (fig. 4). In general, S. 

sempervirens maintained the highest water status in comparison to U. californica and 

P. munitum unless the measurements occurred during a fog event. When foggy, P. 

munitum hydration increased significantly, resulting in higher predawn water 

potentials than observed in either tree species. When not foggy, P. munitum predawn 

water potential was lowest. We measured significantly more water input to the forest 

floor as measured by the throughfall collectors during the rainy season (October to 

April) than during the fog season (May to September). In each year, the hydration 

levels of all three species increased at least once during the summer fog season when 

no rain fell. For all three species, the positive hydration response to fog occurred 

despite the disproportionately low volume of water delivered by fog drip. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

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 Figure 4—The predawn maximum water potentials of S. sempervirens, U. 

californica, and P. munitum changed throughout the summer fog season in (a) 2007, 

(b) 2008, and (c) 2009 at the Grove of Old Trees in Sonoma County. The understory 

received less water input during the rainless summer fog season relative to the winter 

rainy season in (d) 2007, (e) 2008, and (f) 2009. On foggy mornings (*), the hydration 

status of P. munitum was higher than the other species.

Discussion

Foliar uptake is a water acquisition strategy shared by most plants of the coast 

redwood forest (Burgess and Dawson 2004, Limm et al. 2009). While a common 

phenomenon among this taxonomically and morphologically diverse plant 

assemblage, the magnitude of potential hydration by foliar uptake varies significantly 

both between species and even within species. The species with foliar uptake 

capacity possess a wide range of leaf types, from evergreen broadleaves to fern 

fronds to coniferous needles and no one leaf form appears more adapted for foliar 

uptake than another. Polystichum munitum demonstrated double the capacity to 

increase its leaf water content following leaf wetting relative to all other species 

studied, but even this plant exhibits a range of foliar uptake capacity in the field. The 

mechanistic pathway for foliar uptake is unknown in P. munitum and the other 

redwood forest species, but we hypothesize that the leaf cuticle is the most likely 

pathway for water absorption as in most other species known to do foliar uptake 

(Limm and Dawson 2010). If the cuticle does facilitate water absorption in redwood 

forest plants, variation in chemical composition and architecture of the cuticle 

between species and populations in the ecosystem may explain the range of foliar 

uptake capacities we observed (Kersteins 1996, Riederer and Schreiber 2001, 

Shepherd and Griffiths 2006). Specifically for P. munitum, the greatest foliar uptake 

capacity was observed at the Grove of Old Trees, the windiest and foggiest site 

studied. Both wind and fog abrade the cuticle (Baker and Hunt 1986, Hoad et al. 

1992, Pitcairn et al. 1986) and may have resulted in greater capacity of P. munitum to 

absorb water directly through its fronds in this forest. 
Foliar Uptake of Fog in the Coast Redwood Ecosystem: a Novel Drought-Alleviation Strategy 

Shared by Most Redwood Forest Plants

279

Foliar uptake is physiologically important for coast redwood forest plants 

because it provides opportunities for hydration after the rainy season ends and soil 

water availability declines. Many fog events contribute little or no fog drip into the 

soil profile where plant roots access water (Ewing et al. 2009), but leaf wetting 

associated with short-duration or low-intensity fog events provides a subsidy that 

foliage can access. In the glasshouse, we observed that overnight fog exposure 

maintains a high P. munitum hydration status despite extremely low soil moisture.

Simonin et al. (2009) also observed that water absorption by S. sempervirens crowns 

can decouple plants from soil water deficit. When foliar uptake readily occurs as 

observed in P. munitum and S. sempervirens, the potential for soil water deficit to 

cause plant drought stress diminishes significantly. If plants stay hydrated throughout 

the summer because of fog water subsidies as we observed at the Grove of Old Trees, 

plants can maintain higher photosynthetic rates and extend the length of their 

growing season. 

Seasonal water deficit may increase in the coast redwood region as climate 

changes over the next decades (Hayhoe et al. 2004, Loarie et al. 2008). This will 

increase plant demand for water and dependence on fog water subsidies. Fog 

frequency is declining along the coast of California (Johnstone and Dawson 2010), 

reducing the number of days when redwood forest plants receive drought alleviation 

by fog exposure. The future availability of fog remains uncertain, but continued fog 

presence in the coast redwood forest would likely lessen the redwood forest drought 

stress imposed by climate change.

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283

A Chronosequence of Vegetation Change 

Following Timber Harvest in Naturally 

Recovering Coast Redwood (Sequoia 

sempervirens) Forests

Kristin K. Hageseth Michels1 and Will Russell1 

Abstract

The management of second-growth coast redwood (Sequoia sempervirens) forests for the 

purpose of restoration and ecological conservation is a growing trend. However, little is 

known about the long-term regenerative potential of this forest type in the absence of postharvest management techniques such as thinning and planting. Data were collected on a 

chronosequence of second-growth sites (18 to 127 years) and three old-growth reference sites 

in order to characterize changes in stand structure and composition over time. A total of 360 

plots on 18 sites with minimal post-harvest treatment were sampled in the central range of the 

coast redwood forest in California in order to compare stand conditions between post-harvest 

age groups.

One-way ANOVA with Bonferroni post-hoc analyses indicated that stand density, canopy 

cover, and species richness approached old-growth conditions within 40 to 80 years. Total 

basal area and the mean maximum diameter of S. sempervirens stems continued to increase up 

to 127 years. Cover of non-native species declined with stand age to the extent that no nonnative species were recorded in stands older than 60 years. The cover of old-growth 

associated understory species was highest on the oldest second-growth stands and in some 

cases reached levels statistically equivalent to the old-growth references sites between 40 and 

100 years. Results suggest that coast redwood forests are highly resilient to human 

disturbance and will recover naturally over time in the absence of post harvest management. 

Key words: chronosequence, coast redwood, natural recovery, second-growth, Sequoia

sempervirens

Introduction

Timber harvest practices have significant impacts on forest communities. The 

removal of canopy species exposes the forest floor to increased levels of solar 

radiation (Rivas-Ederer and Kjeldsen 1998, Russell and Jones 2001), facilitating the 

recruitment of opportunistic and exotic species (Rivas-Ederer and Kjeldsen 1998). 

Logging practices also alter soil conditions through compaction (Corns 1988, Stone 

and Wallace 1998), and reduce nitrogen levels in previous logged stands (Jussy et al.

2004), particularly near skid roads (Ebrecht and Schmidt 2003). Forest clear-cutting 

has been categorized as a major forest disturbance (Oliver 1981).

Oliver (1981) provides a framework for describing the recovery processes of 

overstory and understory species following stand level disturbance. Post-disturbance 

development involves four stages: stand initiation, the invasion of new stems on 

 

1 Department of Environmental Studies, 1 Washington Square, San Jose State University, San Jose, CA, 

USA 95192-0115. (kkh.michels@gmail.com; russell_sjsu@yahoo.com). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

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released sites; stem exclusion, the vertical stratification and competition among 

existing and new stems; understory reinitiation, the development of favorable 

conditions for understory species; and old-growth development, the increase in 

canopy variability and understory development (Oliver 1981). These processes have 

rarely been studied in naturally recovering understory and overstory vegetative 

communities in coast redwood (Sequoia sempervirens (D. Don) Endl.) forests after 

clear-cut harvest. The purpose of this study was to determine how coast redwood 

communities respond to this major disturbance over time.

Methods

This study was conducted in the central range of the coast redwood forest. Study 

sites were primarily located in the Big River watershed, consisting of more than 

2,968 ha of regenerating coast redwood forest (California Department of Parks and 

Recreation 2006) in Mendocino County, California. Much of the Big River watershed 

was managed as industrial timberland prior to its purchase by the Mendocino Land 

Trust in 2002, and was subsequently transferred to the California State Park system

as the Big River Unit of Mendocino Headlands State Park (fig. 1). The Big River 

watershed was an ideal location for this study due to the presence of recovering 

redwood stands between 15 and 127 years old that had received minimal post-harvest 

manipulation. Three unharvested old-growth reference sites, the only sizable 

remaining old growth stands in Mendocino County, were also included in this study: 

the 49 ha Russell Unit (the largest remaining old-growth redwood stand on the 

Mendocino coast), Montgomery Woods State Natural Reserve (462 ha), and Hendy 

Woods State Park (342 ha). 

Within the three study sites selected in each of the five post-harvest age classes 

(0 to 20, 21 to 40, 41 to 60, 81 to 100, and 101 to 130 years) and the three 

unharvested old-growth reference sites, 60 plots were sampled in each site (360 plots 

total). Sites were selected using detailed timber harvest and land management history 

data on a GIS platform (Rutland 2002). Site selection criteria included stands that 

were dominated by S. sempervirens, previously clear-cut, large enough for adequate 

sampling without edge effects (Russell and Jones 2001), and received no post-harvest 

management such as seeding, thinning, or planting. The post-harvest age class of 61 

to 80 years was not sampled as no sites in that age range existed that met these

criteria. Physical variation between sites was minimized to the extent possible.

Twenty, 20 m diameter (0.031 ha), circular sample plots were randomly selected 

within each of the 18 study sites using ArcGISTM, and located using a handheld GPS 

receiver. Each sample plot was located a minimum of 20 m from adjacent plots, 10 m 

from special habitats such as riparian areas and rock outcroppings, and 200 m from 

adjacent age class boundaries and main access roads. Plot size and sampling intensity 

were determined through a pilot study using the species-area curve method (Cain 

1938). Data were collected on each plot to describe the composition and structure of 

the existing stand as well as physical characteristics of the site. Slope, aspect,

dominant canopy species, and percent canopy cover (measured with a spherical 

crown densiometer) were recorded at the center of each plot. The occurrence and 

abundance of each tree species was recorded within each 20 m diameter sample plot, 

as well as the diameter at breast height (dbh) of all individuals greater than 1 m in 

height. Percent cover was determined for all understory species using ocular 
A Chronosequence of Vegetation Change Following Timber Harvest in Naturally Recovering Coast 

Redwood (Sequoia sempervirens) Forests

285

estimates. All tree species and understory species were identified following 

nomenclature from the Jepson Manual (Hickman 1993). 

Statistical analyses were conducted in AabelTM. One-Way ANOVA were used to 

test differences between recovering stands and old-growth sites. Data were tested for 

normality using a skewness test and transformed using the natural log (loge) 

transformation if skewed. Additional post-hoc analyses were conducted using the 

Bonferroni test for pair-wise differences between groups. 

Results

Tree species development

Stand structure and composition varied significantly between age-classes. OneWay ANOVA indicated that tree density (F(5, 360)=27.599, p<0.001) (fig. 1a) and 

richness of tree species (F(5, 360)=17.121, p<0.001) (fig. 1b) declined significantly 

from younger to older stands, but did not statistically differ from old growth stands 

(hereafter referred to as ‘old-growth equivalence’) at 41 to 60 years after disturbance. 

Approaching levels of old-growth density and richness within 41 to 60 years suggests 

stands of this age class have successfully reached the stem exclusion phase of stand 

recovery as described by Oliver (1981). 

Canopy cover exhibited an inverse pattern than that of tree density and tree 

richness, as percent canopy cover increased across age classes (F(5, 360)=8.470, 

p<0.001) (fig. 1c). Canopy cover did not reach old-growth equivalence until stands 

were 81 to 100 years old. Although there was a significant increase over time, 

percent canopy cover exhibited minimal variation between age classes, ranging from 

approximately 76 percent in the youngest age class to approximately 86 percent in 

the old-growth stands. These results illustrate a dominant canopy is present 

throughout all stages of post-disturbance development in this ecosystem.

Figure 1—One-Way ANOVA between 

(a) tree density (stems per hectare), 

(b) tree richness, (c) canopy cover, 

and age class with Bonferroni post hoc 

analyses in recovering and 

old-growth stands.

 a b

 c
GENERAL TECHNICAL REPORT PSW-GTR-238 

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Similar to canopy cover, the combined basal area of all tree species (F(5, 

360)=167.158, p<0.001) and the basal area of the most dominant tree species, S. 

sempervirens (F(5, 360)=81.207, p<0.001), increased significantly with stand age 

(fig. 2a). Old-growth stands encompassed the highest combined basal area than any 

other age group. In contrast to canopy cover, however, total basal area and S. 

sempervirens basal area did not resemble areas typical of old-growth stands within 

the chronosequence of stands sampled. Observation of this pattern of development is 

limited by the ages of recovering stands sampled in the chronosequence (15 and 127 

years) compared to the old-growth stands (>1,500 years). Although total basal area 

and S. sempervirens basal area did not statistically reach old-growth stands, basal 

area consistently increased throughout recovering stands and illustrated initial 

movement towards old-growth levels at 81 to 100 years. Basal area development, 

also indicated movement through the stem exclusion phase of recovery. 

The variability in dominance among the three most predominant tree species, 

Notholithocarpus densiflorus (Hook. & Arn.) Rehder, Pseudotsuga menziesii (Mirb.) 

Franco var. menziesii, and S. sempervirens, fluctuated throughout the chronosequence 

and compared to old-growth stands (fig. 2b). Both N. densiflorus and P. menziesii

var. menziesii were dominant in the younger sites, however after stands reached 41 to 

60 years, this variability in dominance decreased, favoring S. sempervirens in the 

older age classes. Due to the regenerative capability and growth pattern of S. 

sempervirens, the older sites and old-growth stands exhibited higher levels of 

dominance by this critical old-growth species and less variability in canopy 

dominance. 

Figure 2—(a) One-Way ANOVA between total dominance and age class in 

recovering and old-growth forests and Sequoia sempervirens dominance and age 

class in recovering and old-growth forests and (b) number of plots dominated by the 

three most dominant tree species, Notholithocarpus densiflorus, Pseudotsuga 

menziesii, and Sequoia sempervirens, with Bonferroni post hoc analyses in each 

recovering age class and old-growth forests.

Understory species development 

The understory community also significantly varied with stand age. Percent

cover of understory species initially decreased immediately after harvest, reaching 

the lowest cover within 41 to 60 years, followed by a slight increase (F(5, 

360)=52.140, p<0.001), illustrating a moderate bimodal pattern of development (fig. 

3a). Understory dominance was closest to old-growth levels immediately after 

harvest, likely due to non-native species that easily colonize recently disturbed 

habitats. Understory percent cover did not achieve old-growth equivalence in the 

recovering stands. However, a subsequent increase of understory cover did occur in 

 a b
A Chronosequence of Vegetation Change Following Timber Harvest in Naturally Recovering Coast 

Redwood (Sequoia sempervirens) Forests

287

the 81 to 100 year age group, suggesting the understory reinitiation phase may be 

suitable after at least 80 years of recovery. 

In contrast, the richness of understory species declined to old-growth levels after 

only a few decades of post-harvest recovery (F(5, 360)=4.261, p<0.001) (fig. 3b). As 

soon as 21 to 40 years after harvest, total understory species richness reached levels

equivalent to old-growth stands. Compared to tree species richness, recovery of 

understory species richness progressed much quicker. Understory species richness 

achieved old-growth equivalence after at least 21 years of development, supporting 

the understory reinitiation that arises in subsequent age classes. 

Figure 3—One-Way ANOVA between (a) understory species percent cover, (b) 

understory species richness, and age class with Bonferroni post hoc analyses in 

recovering and old-growth forests.

The recovery of individual associated understory species varied. The most 

dominant species in all age classes including old-growth, Oxalis oregana Nutt., 

steadily increased in second-growth stands, exhibiting the highest value within the 

recovering stands in the 101-130 age group, but did not statistically reach old-growth 

values (F(5, 360)=11.937, p<0.001) (fig. 4a). Although O. oregana did not 

statistically indicate full recovery during the chronosequence, maximum cover values 

approached old-growth within 101 to 130 years (fig. 4b). 

Figure 4—(a) One-Way ANOVA between Oxalis oregana percent cover and age 

class in recovering and old-growth forests and (b) maximum, minimum, and median 

values for O. oregana percent cover with Bonferroni post hoc analyses in each

recovering age class and old-growth forests.

Trillium ovatum Pursh increased significantly from the youngest to the oldest 

age-classes (F(5, 360)=16.247, p<0.001) (fig. 5a). T. ovatum achieved old-growth 

 a 

b

 a b
GENERAL TECHNICAL REPORT PSW-GTR-238 

288

equivalence during the 81 to 100 age class. Although a decrease subsequently 

occurred, this may in part be due to an increase in O. oregana dominance. 

Non-native species cover was significantly higher in younger recovering stands 

compared to older age classes (F(5, 360)=16.328, p<0.001) (fig. 5b) and achieved 

old-growth equivalence in 81 to 100 years. Although exotic species were present in 

early age groups following harvest, non-native species were completely absent in 

second-growth stands older than 60 years and old-growth stands. 

Figure 5—One-Way ANOVA between (a) Trillium ovatum percent cover, (b) exotic 

species percent cover, and age class with Bonferroni post hoc analyses in recovering

and old-growth forests. 

Discussion

Results from the unmanaged stands sampled may be described utilizing the 

Oliver (1981) recovery model following major stand-scale disturbances. Stand

characteristics including tree species density, tree species richness, S. sempervirens 

basal area, and total combined basal area of all tree species indicate the stem 

exclusion phase was reached within 41 to 80 years, supporting understory species 

richness to approach old-growth status shortly after disturbance. Development during 

this phase allowed for further understory reinitiation within 81 to 130 years as 

illustrated by the increased cover of native redwood associate species, including 

Trillium ovatum and Oxalis oregana, and die out of non-native species. Understory 

development continued in the oldest age class demonstrated by the marked increase 

in cover and dominance of O. oregana, the most prevalent understory species in all 

age classes. 

In this study, indicators of stand heterogeneity, such as tree species richness, 

were highest immediately after harvest, but declined in subsequent age groups, most 

likely due to the increased availability of resources immediately after harvest, such as 

greater soil fertility, solar radiation, and habitable landscapes (Fraterrigo et al. 2006, 

Tilman 1985). Fritz (1945) found that total tree density decreased after harvest within 

a permanently established naturally-recovering one-acre sample plot. Busing and 

Fujimori (2002, 2005) also illustrated high levels of S. sempervirens dominance in 

old-growth forests, which resulted in a decrease of tree species richness and diversity 

in stands. This research illustrates that tree species density and tree species richness 

are capable of stem exclusion, successfully reaching old-growth levels, without any 

active management of stands. 

b a 
A Chronosequence of Vegetation Change Following Timber Harvest in Naturally Recovering Coast 

Redwood (Sequoia sempervirens) Forests

289

Increased basal area is characteristic of old-growth forests (Busing and Fujimori 

2002, 2005) and can be attributed to the dramatic growth of the dominant species, S. 

sempervirens (Fritz 1945). As has been found in previous research, S. sempervirens 

in old-growth stands had the highest basal area (Busing and Fujimori 2002, 2005; 

Fujimori 1977, Russell and Jones 2001). In this study, basal area development of S. 

sempervirens contributed to the stem exclusion of other dominant tree species. Due to 

the regenerative capability, growth pattern, and longevity of S. sempervirens, 

additional time may be necessary for basal area to fully resemble old-growth levels in 

naturally recovering redwood communities. However, the older sites and old-growth 

stands exhibited higher levels of dominance by principal old-growth species, 

resulting in the understory initiation phase described by Oliver (1981). 

Old-growth forests exhibited the highest levels of canopy cover, but remained 

isolated to patches, due to an increase in canopy complexity and insularity (Loya and

Jules 2007). Although younger stands were highest in tree density, the intermediate 

stages illustrated old-growth levels of canopy cover. This suggests that canopy cover 

began to move toward old-growth levels in the intermediate stages of recovery, 

allowing for understory development to take place. These developing stages 

produced similar levels of understory species as old-growth forests. As with density, 

the cover of these naturally recovering stands approached that of old-growth stands 

without active management. Future research should consider the effect of actively

removing canopy species within these redwood communities and the subsequent 

effect on the development of native plant communities. 

Loya and Jules (2007) also found understory cover was highest in early stages of 

development following clearcut harvest, although the stem exclusion patterns 

occurring within the 41 to 80 year range in this study resulted in understory 

reinitiation and subsequent patch dominance of old-growth associate species, such as 

Oxalis oregana, in the 81 to 130 year stands. In addition, an important old-growth 

associate species, Trillium ovatum did reach old-growth equivalence during this 

understory reinitiation phase. Heavy soil compaction resulting from clear-cut harvest 

may not have allowed for adequate recovery of other understory species on the 

chronosequence sampled. Additional research, including soil analyses, is likely 

required to fully evaluate recovery patterns of understory species approaching oldgrowth levels. Although understory species richness was low in old-growth forests in 

this study and in previous research (Busing and Fujimori 2002, Loya and Jules 2007), 

richness reached old-growth equivalence within a relatively short time frame 

following disturbance. Richness of understory species was therefore also capable of 

recovery in second-growth stands without active management. 

In the unmanaged, naturally recovering redwood forest communities sampled, 

non-native species may establish in younger second-growth stands, but could 

eventually give way to native species over time. This supports previous research by 

Loya and Jules (2007) that also found few exotic species in old-growth stands. 

However, the year of introduction, life history, distribution, and physiology of exotic 

species must also be considered (Russell and Hageseth Michels 2010). Nonetheless, 

the most dominant exotic species within the study area, Cortaderia selloana (Schult. 

& Schult. f.) Asch. & Graebn. (pampas grass), was first introduced into California in 

1848 (Lambrinos 2001), before the initial harvest of the oldest stands sampled. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

290

Recommendations

The results of this study illustrate that a variety of community parameters and 

individual species followed Oliver’s (1981) model of natural forest recovery without 

active management. Even though sites were highly fragmented due to various harvest 

time frames and land use histories, older sites were relatively undisturbed, even from 

trail use or recreation activities, and existed in fairly remote areas distant from local 

populations. In addition, the Russell Unit is the least disturbed remaining old-growth 

stand on the Mendocino coast and is the most representative of old-growth 

communities of this region. These recovering stands have the potential to eventually 

resemble old-growth forests and retain developing old-growth characteristics. 

While the results from this study indicate that second-growth coast redwood 

stands are capable of natural recovery, some small-scale actions could enhance these 

stands. Continued presence or use of prominent logging roads would likely increase 

erosion, negatively affect edaphic health, and damage adjacent aquatic habitats. 

Major roads should be further decommissioned to a natural setting to mitigate 

potential negative effects. Due to the sensitivity of these stands, any recovery 

activities should take place with minimal impact. 

Limitations of this study could be clarified through additional research. This 

study focused on the vegetative change in redwood plant communities following 

clear-cut harvest on a chronosequence, although several other factors beyond the 

scope of this study likely contributed to the development of these forest communities. 

Future research on the stands sampled in this study could include assessing variables 

related to soil conditions, fungal associations, fauna biodiversity, or long-term 

vegetative monitoring. The recovering redwood stands of Mendocino County should 

continue as a focal point for forest ecologists. 

A detailed understanding of community development is necessary to manage 

recovering coast redwood forests. A management paradigm that focuses on specific 

tree species does not adequately assess timber harvest effects on the entire redwood 

community, which may hinder recovery. The remaining redwood forests are largely 

fragmented, increasing the importance of the overall continuity of the redwood range. 

If allowed sufficient time to recover after harvest, developing second-growth coast 

redwood communities could increasingly resemble old-growth redwood stands. 

References 

Busing, R.T.; Fujimori, T. 2002. Dynamics of composition and structure in an old Sequoia 

sempervirens forest. Vegetation Science 13: 785-792.

Busing, R.T.; Fujimori, T. 2005. Biomass, production and woody detritus in an old coast 

redwood (Sequoia sempervirens) forest. Plant Ecology 177: 177-188.

Cain, S.A. 1938. The species-area curve. American Midland Naturalist 19(3): 573- 581.

California Department of Parks and Recreation. 2006. Draft initial study/mitigated negative 

declaration. Big River Watershed restoration, Mendocino Headlands State Park. 

Mendocino, CA. Department of Parks and Recreation, State of California.

Cole, D.W. 1983. Redwood sprout growth three decades after thinning. Journal of 

Forestry 81: 148-157.
A Chronosequence of Vegetation Change Following Timber Harvest in Naturally Recovering Coast 

Redwood (Sequoia sempervirens) Forests

291

Corns, I.G.W. 1988. Compaction by forestry equipment and effects on coniferous 

seedling growth on four soils in the Alberta foothills. Canadian Journal of Forest 

Research 18: 75-84.

Ebrecht, L.; Schmidt, W. 2003. Nitrogen mineralization and vegetation along skidding 

tracks. Annals of Forest Science 60: 733-740.

Fritz, E. 1945. Twenty years’ growth on a redwood sample plot. Journal of Forestry 43: 

30-36.

Hickman, J.C., editor. 1993. The Jepson Manual of higher plants of California. Berkeley, 

CA: University of California Press.

Jussy, J.-H.; Ranger, J.; Bienaime, S.; Dambrine, E. 2004. Effects of a clear-cut on the in 

situ nitrogen mineralisation and the nitrogen cycle in a 67-year-old Douglas-fir 

(Pseudotsuga menziesii (Mirb.) Franco) plantation. Annals of Forest Science 61: 397-

405.

Lambrinos, J.G. 2001. The expansion history of a sexual and asexual species of Cortaderia

in California, USA. Ecology 89(1): 88-98.

Lindquist, J.L. 2004a. Precommercial stocking control of coast redwood: a seventeen year 

status report (1981-1998). California Forestry Report 2. Sacramento, CA: California 

Department of Forestry and Fire Protection. 25 p. 

Lindquist, J.L. 2004b. Growth and yield report for the whiskey springs redwood 

commercial thinning study: a twenty-nine year status report (1970-1999). California 

Forestry Report 3. Sacramento, CA: California Department of Forestry and Fire 

Protection. 25 p. 

Loya, D.T.; Jules, E.S. 2007. Use of species richness estimators improves evaluation of 

understory plant response to logging: a study of redwood forests. Plant Ecology 

194(2): 179-194.

Oliver, C.D. 1981. Forest development in North America following major disturbances.

Forest Ecology Management 3: 153-168.

Oliver, W.W.; Lindquist, J.L.; Strothmann, R.O. 1994. Young-growth redwood stands 

respond well to various thinning intensities. Western Journal of Applied Forestry 

9(4): 106-112.

Raven, P.H. 1988. The California flora. In: Barbour, M.G.; Major, J., editors. Terrestrial 

vegetation of California. 2nd ed. Sacramento, CA: California Plant Society Press: 109-

137. 

Rivas-Ederer, D.L.; Kjeldsen, C.K. 1998. Seral vascular plant communities on clearcut 

sites in Jackson Demonstration State Forest, Mendocino County, California. 

Sonoma State University, Rohnert Park, CA: California Department of Forestry and Fire 

Protection. 

Russell, W.H.; Hageseth Michels, K. 2010. Stand development on a 127-yr 

chronosequence of naturally regenerating Sequoia sempervirens (Taxodiaceae) 

forests. Madrono 57(4): 229-241.

Russell, W.H.; Jones, C. 2001. The effects of timber harvesting on the structure and 

composition of adjacent old-growth coast redwood forest, California, USA.

Landscape Ecology 16: 731-741.

Rutland, R. 2002. Big River land use history, 1852-2001. Santa Rosa, CA: CalFire. 

Sawyer, J.O.; Sillett, S.C.; Popenoe, J.H.; LaBanca, A.; Sholars, T.; Largent, D.L., et al. 2000. 

Characteristics of redwood forests. In: Noss, R.F., editor. The redwood forest: history, 

ecology, and conservation of the coast redwoods. Washington DC: Island Press: 39-79.
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292

Stone, M.K.; Wallace, J. B. 1998. Long-term recovery of a mountain stream from clearcut logging: the effects of forest succession on benthic invertebrate community 

structure. Freshwater Biology 39: 151-169. 
293

Accounting for Variation in Root Wood 

Density and Percent Carbon in

Belowground Carbon Estimates

Brandon H. Namm1 and John-Pascal Berrill1 

Abstract

Little is known about belowground biomass and carbon in tanoak. Although tanoaks rarely 

provide merchantable wood, an assessment of belowground carbon loss due to tanoak 

removal and Sudden Oak Death will inform conservation and management decisions in

redwood-tanoak ecosystems. 

The carbon content of woody biomass is a function of density and the proportion of carbon in 

dry biomass. Whole-tree basic wood density or specific gravity estimates are often available 

to facilitate calculation of forest biomass, and contemporary carbon analyses generally 

assume that carbon comprises 50 percent of the dry biomass for the whole tree. Less is known 

about root wood density and carbon, or variations within root systems. Quantifying root wood 

density and carbon content changes along the length of a root will enable more accurate 

estimation of belowground carbon, and support development of equations predicting carbon 

from easily measurable aboveground variables, such as dbh.

To analyze root density and carbon content at different locations within root systems, tanoak 

trees were first removed using an excavator. Root wood samples were taken from four 

locations within the root system: within the stump (aboveground), within the lignotuber, at the 

start of the root (adjacent to the lignotuber) and at the end of the root (near tip). 

We did not detect significant differences in root wood density between samples collected at 

different distances from the stem or between different sizes of roots. Percent carbon was 

highest at the sample farthest from the lignotuber, while samples from the other locations 

were not statistically different. Root carbon also varied among root systems sampled. 

Key words: belowground, biomass, carbon, lignotuber, Notholithocarpus densiflorus, roots, 

tanoak, wood density

Introduction

Due to challenges in sampling and measurement of tree roots, little is known 

about root system biomass and carbon (C) content (Böhm 1979). The C content of 

roots is a function of root biomass and the proportion of carbon in dry root biomass. 

Accurate estimates of root biomass are difficult to obtain. Any variability in root 

wood density and C content within and between root systems will introduce 

uncertainty into estimates of belowground C. An understanding of patterns of 

belowground density and C within root systems is needed to guide belowground 

sampling methods and support calculations or predictions of belowground C. 

 

1 Graduate Student and Assistant Professor, respectively, Department of Forestry and Wildland 

Resources, Humboldt State University, 1 Harpst St, Arcata, CA 95521. (bhn4@humboldt.edu; 

pberrill@humboldt.edu). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

294

One method of sampling roots (Achat et al. 2008) involves digging a trench next 

to the root system of interest and mounting a grid frame on the trench wall to count or 

map roots. This method reveals gradients in root distribution with depth, but ignores 

root length. Extracting entire roots gives root volume and biomass, but requires care 

further from the stem where roots narrow, weaken, and become intertwined with 

roots from neighboring trees. Root volume equations can be fitted to diameter and 

length data. Volume estimates can be converted to biomass and carbon estimates 

once patterns of root density and carbon content have been described. 

Aboveground biomass and C allocation patterns have been described for many 

species. Variations in light interception as well as interspecific differences in wood 

density are major factors determining variations in growth among trees (King et al.

2005). Wood density is positively correlated with crown area and depth and can be a 

reasonable predictor of light demand of some species (Aiba and Nakashizuka 2009, 

Nock et al. 2009). Wood density also generally decreases along the length of the stem 

(Correia et al. 2010, Espinoza et al. 2004, Park et al. 2009, Paul et al. 2008). 

Radial patterns of growth (growth from pith to bark) are different in stems 

branches and roots, supporting the hypothesis that wood in different positions in a 

tree has different physiological or mechanical roles (Peterson et al. 2007). Tracheid 

length, which is correlated with wood density, in roots is relatively constant from pith 

to bark, while tracheid length varies within boles and branches (Peterson et al. 2007). 

Although branch specific gravity is not affected by its distance from the bole 

(Woodcock and Shier 2003), the pattern of root wood compression strength 

decreasing with distance from the stem (Stokes and Mattheck 1996) may also hold 

for root wood density. 

Roots are subject to different conditions and stresses than tree stems and 

branches, and therefore may exhibit different trends in wood density and C content. 

The C content of woody biomass has been shown to range from approximately 47 to 

59 percent (Arola 1976, Fryling 1966, Hollinger et al. 1993, Pingrey 1979, Ragland 

1991, Tillman 1981), but is generally assumed to equal 50 percent for both wood and 

bark (Cooper 1983, Dewar and Cannell 1992, Hollinger et al. 1993, Matthews 1993, 

Sedjo 1989, Thuille et al. 2000, Wenzl 1970). However, bark typically contains less 

carbon than wood relative to its density (Quilho and Pereira 2001). 

Accurate wood density estimates depend on accurate volume measurements. For 

branches, volume can be estimated from path distances between set diameter 

intervals and summed for each branch (Sillett et al. 2010). The same method can be 

applied to roots, giving root taper information. The alternative volume estimation 

method of displacement (immersion in liquid) does not provide root dimension and 

taper information, which can be used to develop root volume and taper equations. 

These models would allow for subsampling during excavation and prediction of the 

biomass in missing/broken roots from diameter at the point of breakage.

The objective of this study was to quantify wood density and percent C at 

different locations within tanoak (Notholithocarpus densiflorus (Hook. and Arn.) 

Manos, Cannon and S.H. Oh) root systems. In addition to measuring the percent C, 

accounting for wood density gradients is likely to improve the accuracy of 

belowground biomass and C estimates (Nock et al. 2009). We hypothesized that (1) 

roots of larger diameter have both denser wood and a greater proportion of C and (2) 

wood within the lignotuber is most dense and holds proportionally the most C while 
Accounting for Variation in Root Wood Density and Percent Carbon in Belowground Carbon 

Estimates

295

roots decrease in wood density and proportion of C with increasing distance from the 

lignotuber. Root bark volume and C content were also examined. Results will support 

efforts to quantify belowground C storage and sequestration in the redwood region. 

Methods

Site description 

Root systems were excavated at the L.W. Schatz Demonstration Tree Farm, near 

Maple Creek, Humboldt County, California. The 148 ha tree farm is located 40 km 

inland and extends from N40o46’49” to 40o45’56” and W123o52’21” to 123°51’32”. 

Average annual precipitation is approximately 120 cm with the majority falling as 

rain between the months of November and March. 

Before clearcutting in the 1950s, the site was occupied predominantly by oldgrowth Douglas-fir (Pseudotsuga menziesii) forest with tanoak and California bay 

(Umbellularia californica). Species composition on the property now consists 

primarily of Douglas-fir, grand fir (Abies grandis), and tanoak mixtures, and pure 

stands of Alnus rubra (West 2007). 

Excavation and measurements 

Three second-growth tanoak trees were selected for sampling. Tree height, live 

crown base height, diameter at breast height (dbh), and diameter at the base of the 

tree were measured. An excavator was used to create a 30 cm wide trench at a 

distance of 1 m surrounding each tanoak to the depth where roots were no longer

visible (approximately 1 m) severing the lateral roots traversing the trench. A rope 

was attached 5 to 10 m up the bole and each tree was pulled over using either a 4WD 

vehicle or a hand winch. We measured the diameter of the severed root ends and their 

distances from the lignotuber to allow for future prediction of mass lost during 

excavation (Niiyama et al. 2008).

Root samples were extracted at four locations within the root systems. Two pithto bark wood cores were collected from each stump and lignotuber. Lateral roots 

oriented in the four cardinal directions around the three sample trees were excavated 

by hand for density and C analysis. Two short sections of root were cut from each 

lateral root: one adjacent to the excavated trench approximately 100 to150 cm from 

the stem, and a section of the same root at the narrow end farthest from the stem (fig. 

1). 

The green volume of these samples was estimated by measuring their diameter 

and length, and assuming the volume of each section was best represented by a 

truncated cone. Samples were dried at 65 °C and weighed to obtain dry mass. Much 

of the water was removed by drying biomass at 65 °C but drying at 100 °C was 

required to remove water bound within the cell walls (Wiemann and Williamson 

2010). Different portions of the same roots used for C analysis were dried at 65 °C 

and weighed, and then dried further at 100 °C and re-weighed for comparison. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

296

Figure 1—Locations and quantities of C samples within each of the three individual 

tanoaks excavated at the L.W. Schatz Demonstration Tree Farm. 

Root bark samples collected throughout the three root systems were displaced in 

water to obtain estimates of bark volume. The estimates of volume and dried bark 

weight gave estimates of bark density. A subsample of root bark with known mass 

was removed and analyzed for percent C. A caliper was used to measure the outside 

diameter of roots including the bark and the diameter inside bark of roots with 

varying diameters giving estimates of the cross sectional area and volume of bark in 

lateral roots.

Carbon/nitrogen analysis

Percent C in each stump, lignotuber, root and bark sample was determined using 

a dynamic flash combustion system coupled with thermal conductivity/ IR detection 

(Thermo-Finnigan Flash EA 1112). Samples were oxidized by flash combustion 

which converted all organic and inorganic substances into combustion gases (N2, 

NOx, CO2, and H2O). The method has a detection limit of approximately 0.1 percent 

for C (http://anlab.ucdavis.edu/analyses/plant/sop5222

, AOAC Official Method 

927.43).

Statistical analysis

We constructed a nested model to test for differences in wood density and 

percent C at the different locations within the root system across all sample trees. 

Tukey-Kramer’s multiple comparison test was used to identify differences among the 

sample locations and the acceptable level of error was adjusted for multiple 

comparisons (α = 0.008). One-way ANOVA was used to identify differences in root 

wood density and percent C within and between trees. Additionally, density and

percent C were regressed against the sample locations’ path lengths from the 

lignotuber using Minitab 16 Statistical Software (Minitab 2010). 

 

2 Total nitrogen and carbon – combustion method. University of California, Davis, analytical lab.
Accounting for Variation in Root Wood Density and Percent Carbon in Belowground Carbon 

Estimates

297

Results 

The sample trees were similar in height, but had different stem diameters and 

crown ratios and occupied different positions within the canopy (table 1).

Table 1—Aboveground sample tree data for tanoak at L.W. Schatz Tree Farm.

Tree Height

(m)

Live crown

ratio

Dbh 

(cm)

Diameter at

base (cm)

Crown position

1 21.1 0.81 33.5 39.6 open grown/dominant

2 18.3 0.27 34.8 42.1 codominant

3 20.7 0.59 52.4 60.1 codominant

Mean wood density for belowground components (lignotuber, lateral roots) was 

590.3 kg/m3

 and varied between 565 and 621 kg/m3 (table 2). The nested model with 

trees as random factors indicated that no significant difference in root wood density 

among trees (p = 0.508), or among sample locations (p = 0.334) was detected (fig. 

2A). Wood density did not change when regressed against root diameter (F = 1.16, p 

= 0.260) nor path distance from the lignotuber (F = 0.04, p = 0.852) but was highly 

variable among trees (coefficient of variation = 0.139). 

The grand mean of the C samples across the three trees was 49.5 percent. The 

nested model indicated that no significant differences in percent C among trees were 

detected (p = 0.097), but percent C differed among sample locations (p < 0.0001). 

Kramer-Tukey multiple comparison tests indicated that sections of roots farthest 

from the lignotuber had a significantly greater C content than the other sample 

locations while the aboveground stump, lignotuber and the samples nearest the 

lignotuber were not significantly different in percent C (fig. 2B). Mean percent C 

ranged from 48.6 to 50.6 percent (table 2).

Percent C did not change when regressed against diameter (p = 0.703). A nested

model of belowground percent C (stump C not included) with individual trees as a 

random effect indicated that percent C increased with path distance from the 

lignotuber (p = 0.003) (fig. 3). The model explained 45 percent of the variation in 

belowground percent C which varied within and between sample trees (coefficient of 

variation among trees = 0.02). 

Mean root mass decreased 5.5 percent when the drying temperature increased 

from 65 °C to 100 °C. The proportion of root volume comprised of bark was 

consistent for all root diameters (mean proportion bark volume = 22.1 percent) and 

bark consisted of 48.6 percent C. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

298

Figure 2—Box plot of (A) wood density and (B) percent C at the different sample 

locations in the root system. Different letters indicate significant differences in percent 

C and wood density. Lines connected by location means.

Table 2—Root wood density and percent C for the three sample trees. Differences in location 

means detected by Tukey-Kramer multiple comparison tests indicated by different letters. 

Acceptable levels of error adjusted for multiple comparisons (α = 0.008).

 Wood Density (kg/m3)

Tree stump lignotuber near far

1 635.7 628.3 648.7 507.8

2 529.5 590.8 614.2 526.5

3 592.3 585.7 564.9 662.9

mean 585.9a 601.6a 621.2a 565.7a

st. dev. 52.4 30.7 87.0 105.5

max 664.9 659.7 749.4 696.5

min 528.4 575.6 471.2 370.0

 Total C (%)

Tree stump lignotuber near far

1 49.0 49.0 50.6 51.3

2 48.7 48.3 49.1 50.2

3 48.5 48.4 48.0 50.3

mean 48.7a 48.6a 49.2a 50.6b

st. dev. 0.2 1.4 1.2 1.1

max 47.3 51.1 51.8 51.4

min 48.5 47.3 47.2 48.5
Accounting for Variation in Root Wood Density and Percent Carbon in Belowground Carbon 

Estimates

299

Figure 3—Change in C with increasing path length from the lignotuber. Lignotuber 

included as zero distance.

Discussion

The grand mean root wood density of 589.58 kg/m3 was almost equal to the 

value of 580 kg/m3

 reported in the Global Wood Density Database for tanoak in 

North America (http://datadryad.org/handle/10255/dryad.235, Alden 1995) even 

though latitude, temperature and precipitation (Wiemann and Williamson 2002), 

successional stage (Henry et al. 2010, Wiemann and Williamson 1988, Woodcock 

and Shier 2002), stocking levels (Persson et al. 1995), and diameter distribution 

(Ruiz-Jaen and Potvin 2010) typically contribute to variation in wood density across 

forests. The differences in root wood density and percent C between trees was not 

surprising considering individuals of the same species often exhibit large withinstand variation due to genetic variation (Fries and Ericsson 2009, Wang et al. 2000, 

Zhang and Morgenstern 1995) and canopy position (Aiba and Nakashizuka 2009, 

King and et al. 2005). The variations in root wood density between different sample 

sections within each sample tree was a concern, and suggests that great care must be 

taken when measuring green root dimensions for volume estimates. The large 

differences in root wood density between different sample trees indicated that a large 

sample size is needed to obtain precise estimates of belowground biomass in tanoak 

at the stand level (table 2).

The increase in C and absence of detectable change in wood density with 

distance from the lignotuber is contrary to aboveground findings that wood density 

decreases with increasing stem height (Correia et al. 2010, Park et al. 2009, Paul et 

al. 2008). Larger diameter roots containing more biomass did not have greater wood 

density or percent C (table 2), suggesting that root systems allocate C differently than 

aboveground stems. Our finding that wood density does not increase with larger 

diameter roots also suggests that tanoak roots may not develop juvenile wood. 

Peterson et al. (2007) reported that juvenile wood was absent in roots and that roots 

have a relatively high density at a low cambial age (ring number from the pith). This 
GENERAL TECHNICAL REPORT PSW-GTR-238 

300

contradicts the common assumption that the cambium is constrained to produce short 

cells when it is young and after a certain period of time produces denser wood. 

Because roots, branches and stems have different mechanical and physiological 

functions, it is not safe to assume that above- and belowground components allocate 

C in the same way.

Modeling percent C as a function of the continuous variable ‘path distance’ from 

the lignotuber (fig. 3) will allow us to make better predictions of belowground C 

mass in tanoak. Given that most of the belowground biomass is centrally located near 

the stem, summing C estimates for discrete sections of roots with different C content 

will give more accurate estimates at the tree level than if the grand mean of 49.5 

percent C content was applied to estimates of total root system biomass.

Conclusions

Root wood density was highly variable within and between trees, but remained 

approximately constant on average with increasing distance from the lignotuber. 

Percent C did not remain constant throughout tanoak root systems. Accounting for 

density and C differences throughout the root system will allow for more accurate 

estimation of belowground C. 

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Response of Montia howellii (Howell’s 

montia) to Road Management in California 

Coastal Timberlands1

Maralyn A. Renner,2 James Regan,3 and Mark Colosio3 

Abstract

Howell’s montia (Montia howellii S. Watson), a tiny annual plant with a California Rare Plant 

Rank of 2.2 (rare in California but more common elsewhere), is found throughout its range in 

seasonally wet, natural and disturbed habitats. On Humboldt Redwood Company timberlands 

it occurs on native surface or lightly rocked roads and turnouts, and in wet meadows used by 

cattle. We examined the spatial and temporal extent of Howell’s montia on 10 road complexes 

over 6 years by counting the plants in consecutive fixed 10 meter segments of road. Using 

GIS event routing, we documented the changes in plant numbers in each segment, the 

movement of plants into new segments, and their decline and disappearance from segments 

over time. We found that opening and using seasonal, native surface roads was related to 

increases in plant numbers and spatial spread. After road use ceased, plants declined in both 

numbers and spatial extent. On rocked roads with heavy use and annual maintenance, 

populations were not well sustained even with a nearby seed source. We conclude that where 

Howell’s montia occurs on roads, periodic seasonal use and road maintenance appears to 

maintain the local population. 

Key words: GIS event routing, Howell’s montia, Montia howellii, rare plant mitigation, road 

management, seed bank 

Introduction

Howell’s montia (Montia howellii, fig. 1) is a tiny annual of the Portulacaceae 

(purslane family). Germinating in late fall, it grows through the early spring, flowers 

from February to May, then sets seed and quickly disappears. Its range generally 

coincides with the maritime coastal forests from southern British Columbia to 

Northern California (CNPS 2011, Hickman 1996, Hitchcock and Cronquist 1973). 

The Global Status is G3G4, or vulnerable to secure (NatureServe 2011). In California 

it is ranked S3 (CNPS 2011), in Oregon and British Columbia it is ranked S3S4, 

(Oregon Biodiversity Information Center 2010), and in Washington it has been 

dropped to watch status because it has been found to be more abundant than 

previously assumed (Washington Natural Heritage Program 2011). 

Throughout its range, Howell’s montia typically occurs in sparsely-vegetated 

moist to seasonally wet lowland areas such as river and pond edges, cattle and game 

trails, open fields, vernal pools, seeps, and wet prairies, often on compacted soil 

(CNPS 2011, Hickman 1996, Kaye 1991, Wilson 1998). It is also found on human- 

 

1 An abbreviated version of this paper was presented at the redwood science symposium: coast redwood 

forests in a changing California, June 21-23, 2011, Santa Cruz, California. 2 Stewardship Manager and Senior Botanist, Humboldt Redwood Company, LLC, P.O. Box 712, Scotia, 

CA 95565. (mrenner@hrcllc.com). 3 Staff botanists, Humboldt Redwood Company, LLC. (jregan@hrcllc.com; mcolosio@hrcllc.com).
GENERAL TECHNICAL REPORT PSW-GTR-238 

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Figure 1—A single plant of Montia howellii, a quarter, and redwood twigs.

disturbed habitats such as dirt roads, skid trails, landings, turnouts, parking areas, and 

lawns (CNPS 2011, Kaye 1991, personal observation), and it appears to need 

disturbance for survival (Kaye 1991, Wilson 1998). It occurs from near sea level to 

over 800 m (CNPS 2011, personal observation). 

It was believed extirpated in California until rediscovered in 1999 near the Van 

Duzen River in Humboldt County during plant surveys conducted prior to timber 

harvesting. Since then, 69 populations have been located in California (CNPS 2011), 

and threats are believed to exist from logging, road construction and maintenance, 

vehicles, and competition. On Humboldt Redwood Company land (84,000 ha), we 

have documented 43 populations totaling over 300,000 plants. 

From monitoring that we conducted from 1999 to 2004, we found wide site-level 

fluctuations in both plant numbers and spatial extent. Howell’s montia numbers 

declined and the density of other herbaceous species increased where we avoided 

impacts to Howell’s montia by closing roads, barricading turnouts with rebar stakes 

and flagging, and placing signs directing drivers to stay on the road running surface, 

(fig. 2). We found that plant numbers typically increased the following year after 

barricades were removed to allow road use in the summer while the populations 

existed as seeds. Plant numbers decreased where dirt road segments were upgraded to 

rocked segments, usually done to minimize sediment inputs to streams.

To better understand the changes that occur in Howell’s montia populations, we 

developed this case study to document the extent of temporal fluctuations in the 

numbers and locations of Howell’s montia on selected roads, and to correlate 

observed changes with the timing of road use and other disturbances. 
Response of Montia howellii (Howell’s montia) to Road Management in California Coastal 

Timberlands

305

Figure 2—Effects of mitigation applied 1999 to 2004 showing herbaceous 

overgrowth: a) Sign with overgrown turnout behind it, and b) a turnout barricaded for 

6 years; both sites are no longer suitable habitat for Howell’s montia.

Methods and materials

Study area selection

We selected 10 road complexes for this study (table 1) on Humboldt Redwood 

Company land. They include a full range of small to large populations, elevations 

from 45 m (150 ft) to over 800 m (2,625 ft), and are located in several major stream 

drainages representing the majority of the company’s land base and road 

management practices. Both rocked and native-surfaced roads were present in the 

road complexes, except for Chadd and Larabee which had no rocked roads. Mainline 

rocked roads and some of the seasonal native-surface roads have regular use and 

maintenance each year, while most seasonal roads have disturbance only in years 

when they are used for timber harvesting operations. Prior to beginning the study, we 

were aware that some areas had periodic light-vehicle or foot-traffic disturbance from 

our watershed monitoring activities or from trespassers. Other areas had continuing 

disturbance from cattle.

Table 1—Road complexes used in the study.

Road complex Cal Planning 

Watershed Sub-basins

Elevation 

range (m)

Topographic location Km

Booth’s Run Booth’s Run 524-610 Upper slopes 1.82

Chadd Chadd Cr. 183-408 Lower/middle slopes 5.20

Cummings Cr. Cummings Cr. 122-305 Lower/middle slopes 4.65

Jordan Jordan Cr. 61-122 Lower slopes 6.50

Larabee Scott Cr. Complex 701-884 Ridges, upper slopes 5.63

Monument A55 Monument Cr. and 

Kiler Cr.

183-427 Ridges, upper slopes 5.70

Stafford A51 Jordan Cr. 524-610 Ridges, upper slope 1.29

Van Duzen L35 Hely Cr. 61-110 Lower slopes 4.02

Van Duzen L64 Root Cr. 76-171 Lower slopes 4.02

Wrigley Lower N. Fork Elk R. 30-104 Lower slopes 2.57

Total Km in the study 41.40
GENERAL TECHNICAL REPORT PSW-GTR-238 

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The locations used for this study are shown in figure 3. We incorporated

approximately 25 percent of the populations4

 on the property, collectively 

encompassing approximately 80 percent of the plants as of 2004. 

Figure 3—Location of study sites on Humboldt Redwood Company lands in 

Humboldt County, California. Map inset shows the property in relation to surrounding 

counties in California.

Data collection 

Howell’s montia typically occurs in sparse to dense clumps of plants often

separated by long road segments with few or no plants. Given the miniscule size of 

 

4 Populations are defined as collections of occurrences separated by at least 1⁄4 mile.
Response of Montia howellii (Howell’s montia) to Road Management in California Coastal 

Timberlands

307

this plant and the variation in density, we knew that standard methods of sampling 

would result in non-normal, highly skewed, zero-rich data (McCune and Grace 

2002). A random allocation of fixed-area quadrats, especially where there were 

unoccupied segments of road in a sparsely-occupied road complex, would be an 

inefficient design (Green 1979, Salzer and Willoughby 2004). It would result in an 

inflation of the error variation among quadrats because of the clumped differences in 

abundance, and small new groups would be easily missed. For the same reason, point 

intercept or line intercept sampling methods would also be ineffective (McCune and 

Grace 2002). Therefore, we elected to conduct an extensive survey of the entire road 

prism and associated turnouts and landings along all interconnected roads in each 

study area; in other words, we counted the entire population at each site in each visit. 

Even though we did not use a sampling process, this study is sufficiently inclusive to 

enable us to make inferences about the management of Howell’s montia on roads in 

managed timberland settings in California (Elzinga et al. 1998, Elzinga et al. 2001, 

Mueller-Dombois and Ellenberg 2002, Quinn and Keough 2002). 

We collected data from mid-February through mid-April (end of March in dry 

springs), starting with lower elevation roads before progressing to higher elevations.

From a random start outside the area containing plants, we divided the road into fixed 

10 m lengths and counted the plants in each segment. If the area was sparsely 

occupied we counted individual plants; where the plants were denser, we made a 

careful estimate of the number5

. We monumented the random start so we could reestablish the location of the fixed 10 m segments in subsequent years. We continued

for a fixed distance of 500 m (0.31 mi) beyond the last observed Howell’s montia 

plant or until the habitat became unsuitable. This ensured that we were likely to find 

plants that had spread beyond the original extent of the occupied area. 

Data analysis

We recorded the data in a Microsoft Access table and linked it to our Global 

Information System (GIS) roads layer. We added a conversion to account for 

discrepancies between road (slope) distance and GIS (planar) representation, 

although we had to accept a small level of error on roads with steep slopes. This 

process gave each 10 m segment, as measured on the ground, an address along the 

road system in our GIS. This type of analysis is known as “event routing,” which 

characterizes each 10 m segment as an “event” containing the data while the GIS 

road layer is the “route” on which that data rides. We then used the event route tables 

to create a map set that very accurately displayed the plant locations and numbers for 

each year of the study. 

We queried our road work database and project archives to create a management 

history for each road system that included the specific roads used in any year and the 

type of management that occurred each year starting in 2004. 

Results

Plant number changes 

Plant numbers fluctuated widely at most sites (fig. 4) and even within individual 

10 m segments, similar to what we had documented prior to initiating this study. The 

 

5 All team members are experienced in counting and estimating Howell’s montia numbers.
GENERAL TECHNICAL REPORT PSW-GTR-238 

308

dates shown on the graphs in figure 4 indicate when the greatest amount of road use 

from timber harvesting operations occurred. Operational activities took place in the 

summer after plant counts were taken; any changes in numbers that may have 

resulted from the disturbance from operations were recorded in the next scheduled 

survey year. Plant numbers increased in all populations following disturbance, and 

declined within 2 years after disturbance ended. 

Figure 4—Montia howellii plant numbers, 2005 to 2010: a) Booth’s Run, b) Chadd, c) 

Cummings Creek, d) Jordan, e) Larabee, f) Monument A55, g) Stafford A51, h) Van 

Duzen L35, i) Van Duzen L64, and j) Wrigley. Dates indicate years of maximum 

disturbance.

In addition to disturbance from road use associated with timber harvesting, there 

were other sources of disturbance documented in all road complexes except the 

Chadd and Van Duzen L64 road complexes. Disturbance from cattle was present at 
Response of Montia howellii (Howell’s montia) to Road Management in California Coastal 

Timberlands

309

Booth’s Run, Larabee, Monument A55, and Stafford A51. At Cummings Creek, 

Jordan, Van Duzen L35, and Wrigley there was light vehicle use of the roads and 

turnouts by pickups and all-terrain vehicles. Where disturbance continued to maintain 

lightly-vegetated habitat conditions, plant numbers did not decline. 

Changes in density and location 

Two examples of temporal changes in plant density and location are shown in the 

following figures, generated from GIS event routing. Similar changes took place at 

the other road complexes.

The Chadd road complex (fig. 5) illustrates what we found when disturbance 

ended: competing vegetation became dominant while Howell’s montia numbers 

declined. Timber harvesting and road maintenance in 2006 and 2007 required 

opening all but the most eastern road. The population increased in 2008 to 4,880 

plants, more than double the 2,361 plants found in 2006, and plants were documented 

on two spur roads that had no plants at the beginning of the study. In 2008, road work 

occurred at two stream crossings; plant numbers in 2010 remained high near those 

locations but declined on all the other roads. 

Figure 5—Spatial changes at the Chadd road complex generated from GIS event 

routing: a) 2006, b) 2008, c) 2010; width of the symbol indicates number of plants in 

the 10 m segment.

For example, the southeast spur road outlined in figure 5 had no plants in 2006 

before it was opened and used for logging. In 2008 it had a low density of up to 20 

plants per 10 m, but no plants in 2010. The declining numbers documented on spur 
GENERAL TECHNICAL REPORT PSW-GTR-238 

310

roads such as this one resulted in a decrease in total plant numbers throughout the 

road complex to just over 1,600 in 2010. 

The Monument A55 road complex (fig. 6) is an example of what can happen 

when forest management operations open roads that are subsequently used by cattle. 

Here, timber harvesting and road maintenance took place 2005 to 2009 on the 

mainline road but the spur roads were opened and used only during 2005 to2006. 

Overall plant numbers in the entire road complex showed a steady increase from 486 

plants in 2006 to 2,133 plants in 2010. 

Figure 6—Spatial changes at the Monument A55 road complex generated from GIS 

event routing: a) 2006, b) 2008, and c) 2010; width of the symbol indicates number of 

plants in the 10 m segment. 

On the southwest spur road outlined in figure 6, our previous monitoring from 

2004 documented only 20 plants in a 670 m length. In the spring of 2006, the first 

time we counted the population for this study, we found no plants on this spur road. It 

was opened to allow harvesting in summer of 2006, and in 2008 and 2010 we 

recorded 171 and 673 plants respectively with plants present all along a previously 

unoccupied 400 m length of road. The increase through 2010 occurred even though 

the road was only used for harvesting operations in 2006 and closed when operations 

were completed. However, cattle are abundant in the area (from legal leases) and the 

increases in Howell’s montia numbers and locations were associated with continuing 

use of the newly-opened roads by cattle. 

In all areas, heavily used graveled mainline roads did not support plants except in 

some turnouts, even though large numbers of plants were present on nearby roads. 
Response of Montia howellii (Howell’s montia) to Road Management in California Coastal 

Timberlands

311

Discussion

When roads known to be occupied by Howell’s montia were opened and used for 

timberland management, we found short-term and sometimes surprisingly large 

increases in plant abundance as well as local changes in spatial extent following 

disturbance from operational activities. Plants spread into adjacent, previously 

unoccupied road segments in all 10 study areas when these roads were opened for 

use. Howell’s montia numbers typically declined within a year after the cessation of 

disturbance as the roads and turnouts became dominated by grasses and forbs. We 

speculate that new groups of Howell’s montia that appeared after opening some of 

these roads came from an in-situ seed bank, as may be the case for the Monument 

A55 spur described above. Other new groups may have come from seed spread by 

road graders and other equipment from nearby sites containing active populations. 

After roads were opened, in locations where the sparsely vegetated habitat on 

seasonal roads was maintained by cattle or light vehicle use, plant numbers either 

increased or declined more slowly than in the areas where there was no continued 

disturbance from cattle or vehicles. For example, at Stafford A51 (disturbance from 

cattle) and Wrigley (light vehicle use), plant numbers continued to increase after the 

roads were no longer used for harvesting operations. High numbers were also 

maintained at Jordan where no harvest-related use occurred on the roads occupied by 

Howell’s montia, but where there was ongoing light vehicle use. This disturbance 

apparently maintained the conditions needed to sustain Howell’s montia population 

numbers at these and other similar sites. Conversely, at Chadd and Van Duzen L64, 

where neither cattle nor light vehicle use were present to maintain an open, lightlyvegetated habitat, population numbers decreased sharply following the end of road 

use.

An unexpected benefit derived from this work has been to apply the GIS event 

routing mapping to operational needs. For example, work on a Van Duzen L35 road

in 2008 was adjusted to avoid significant impacts to most of the 10 m segments 

containing Howell’s montia. Plant counts more than doubled on that road the 

following year. 

The study results indicate that maintaining populations of this species can be 

compatible with active forest management. Where ongoing disturbance to 

populations from summer road maintenance and use occurs, conditions favorable to 

Howell’s montia have been preserved and population numbers remain fairly stable. 

As part of our Howell’s montia management strategy, we avoid heavy road rocking, 

excavation, and deep grading where plants are known to occur, since these activities 

can alter the microsite conditions or bury the seed bank. We will also continue 

periodic surveys, though on a less intensive schedule. 

The Global and California state status of Howell’s montia are not likely to 

change as a result of this study. The southern range extent in California is limited to 

two counties, and while known populations there can have high numbers of plants, 

most are on managed timberlands. If more populations are recorded on noncommercial timberlands and submitted to the Biogeographic Data Branch of the 

California Department of Fish and Game, this plant will be eligible for status review. 

Until then, more surveys are needed. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

312

References

California Native Plant Society (CNPS). 2011. Inventory of rare and endangered plants.

(online edition, v8-01a). Sacramento, CA: California Native Plant Society.

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Elzinga, C.L.; Salzer, D.W.; Willoughby, J.W. 1998. Measuring and monitoring plant 

populations. BLM Tech. Ref. 1730-1. Denver, CO: U.S. Department of the Interior. 477 

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Elzinga, C.L.; Salzer, D.W.; Willoughby, J.W.; Gibbs, J.P. 2001. Monitoring plant and 

animal populations. Malden, MA: Blackwell Press. 360 p. 

Green, R.H. 1979. Sampling design and statistical methods for environmental biologists. 

New York: John Wiley & Sons. 257 p.

Hickman, J.C., editor. 1996. The Jepson manual: higher plants of California. 3rd printing 

with corrections. Berkeley, CA: University of California Press. 1400 p.

Hitchcock, C. L.; Cronquist, A. 1973. Flora of the Pacific Northwest: an illustrated 

manual. Seattle, WA: University of Washington Press. 730 p.

Kaye, T.N. 1991. Montia howellii inventory, monitoring, disturbance ecology, and seed

bank. Salem, OR: Oregon Department of Agriculture. 34 p. Available from ODA,

Natural Resources Division, Salem, OR.

McCune, B.; Grace, J.B. 2002. Analysis of ecological communities. Gleneden Beach, OR: 

MjM Software Design. 300 p.

Mueller-Dombois, D.; Ellenberg, H. 2002. Aims and methods of vegetation ecology.

Caldwell, NJ: The Blackburn Press. 547 p.

NatureServe. 2011. NatureServe explorer: an online encyclopedia of life. [web 

application]. Version 7.1. NatureServe, Arlington, Virginia. http://www.natureserve.org/ 

explorer.

Oregon Biodiversity Information Center. 2010. Rare, threatened and endangered species of 

Oregon. Portland, OR: Institute for Natural Resources, Portland State University. 205 p.

Quinn, G.P.; Keough, M.J. 2002. Experimental design and data analysis for biologists. 

New York: Cambridge University Press. 537 p.

Salzer, D.W.; Willoughby, J.W. 2004. Standardize this! The futility of attempting to apply 

a standard quadrat size and shape to rare plant monitoring. In: Brooks, M.B.; 

Carothers, S.K.; LaBanca, T., editors. Proceedings of the symposium of the North Coast 

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313

‘Pygmy’ Old-Growth Redwood

Characteristics on an Edaphic Ecotone in 

Mendocino County, California

Will Russell1 and Suzie Woolhouse2 

Abstract

The ‘pygmy forest’ is a specialized community that is adapted to highly acidic, hydrophobic, 

nutrient deprived soils, and exists in pockets within the coast redwood forest in Mendocino 

County. While coast redwood is known as an exceptionally tall tree, stunted trees exhibit 

unusual growth-forms on pygmy soils. We used a stratified random sampling procedure to 

characterize forest composition, structure, and growth-form, across the pygmy/redwood 

ecotone. Results indicate that tree height, canopy cover, basal area, herbaceous cover, shrub 

height and cover, and the dominance of pygmy forest endemics decreased across strata, and 

were negatively correlated to soil pH. In addition, the structure of individual redwoods varied 

significantly across the ecotone, exhibiting three main growth-forms: 1) Stunted multistemmed (>100 stems) individuals >2 m in height; 2) Small diameter muti-stemmed (two 

tosix stems) individuals with an average height of 12 m growing as subcanopy under pygmy 

cypress and bolander pine; 3) Pygmy old-growth redwoods with a maximum height of 41 m 

growing as a co-dominant and exhibiting complex canopy structure. The results of this study 

indicate that while the growth-form of individual redwoods is significantly affected by pygmy

soil conditions, stunted trees on the edge of the pygmy formation exhibit structural 

characteristics and canopy complexity similar to full stature redwoods. 

Key words: Coast redwood, hydrophobic podisols, pygmy forest, Sequoia sempervirens

Introduction

Coast redwood (Seqouia sempervirens) is the tallest tree species in the world 

reaching heights exceeding 112 m (Preston 2007). Where site conditions are less than 

optimal, however, growth can be stunted (Noss 2000). In the most extreme cases, S. 

sempervirens exhibits a shrub-like growth-form with an abundance of clonal stems 

connected to a single root mass, with no single stem exerting apical dominance. In 

less extreme cases S. sempervirens will develop a growth-form similar to the giants 

for which the species is known, but on a smaller scale. The most dramatic transition 

from giant redwoods to stunted redwood shrubs occurs on the ecotone between the 

‘pygmy forest’ formation and the coast redwood forest in Mendocino County, 

California. 

The pygmy forest is found on a series of five coastal terraces that increase with 

age as they progress inland from the coast (Fox 1976, Yu et al. 1999); the oldest with 

soils of approximately one million years (Westman and Whittaker 1975). Variation in 

vegetation between terraces is related to soil conditions. The first terrace has well 

 

1 Department of Environmental Studies, San José State University, San José, CA 95192-0115; (415)-

505-5800. (will.russell@sjsu.edu). 2 Department of Biology, San José State University. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

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drained soils rich in organic matter and nutrients (Aitken and Libby 1994) supporting 

shore pine (Pinus contorta subsp. contorta), bishop pine (Pinus muricata), and sitka 

spruce (Picea sitchensis) (Sholars 1982). Coast redwood mixes with western hemlock 

(Tsuga heterophylla) and Douglas-fir (Pseudotsuga menziesii var. menziesii) on the

second terrace, where podzolized soils begin to develop. The third, fourth, and fifth 

terraces where pygmy forest are found contain highly acidic, extremely podzolized, 

soils with a hydrophopic hardpan (Aitken and Libby 1994). Consequently, pygmy 

forest species, dominated by two endemic species, bolander pine (Pinus contorta

subsp. bolanderi) and pygmy cypress (Hesperocyparis pygmaea), are well adapted to 

both high water table conditions (Sholars 1982, Wurzburger and Bledsoe 2001) and 

summer drought (Westman and Whittaker 1975). 

Complex lateral branching patterns, reiterated trunks, arboreal soils, and 

epiphytic plants have been well documented on full stature redwoods, which 

commonly occur on productive alluvial soils (Sillett and Van Pelt 2000). These 

features have been shown to provide habitat for threatened species such as the 

marbled murrelet (Brachyramphus marmoratus) and northern spotted owl (Strix 

occidentalis caurina) (Sawyer et al. 2000), and for less well known species such as 

the wandering salamander (Aneides vagrans) (Spickler et al. 2006). The occurrence 

of these features has not been adequately studied on less productive sites, such as 

those occurring adjacent to the pygmy forest formation. The objective of our research

was to characterize the structure and composition of vegetation across the 

pygmy/redwood ecotone with particular emphasis on the growth-form of S. 

sempervirens.

Methods

This study was conducted on the Russell Unit of the Mendocino Headlands State 

Park, a 50 ha property composed of mixed primary old-growth and mature secondgrowth redwood, with patches of riparian and pygmy forest habitat. Stratified random 

sampling was used to locate 10 (7 m diameter) sample plots within each stratum. 

Six stratum radiating out from the center of the pygmy formation were defined 

loosely on Westman (1975) and included: ‘extreme pygmy’ dominated by stunted 

pygmy cypress and bolander pine; ‘short pygmy’ with similar species composition 

but less stunted trees; ‘tall pygmy’ dominated by tall Ericaceous shrubs and large 

specimens of bolander pine and pygmy cypress; ‘transitional’ dominated by tall 

pygmy cypress mixed with bishop pine and sub-canopy coast redwood; ‘pygmy 

redwood’ characterized by stunted old-growth redwoods growing as co-dominants, or 

sub-canopy species, with bishop pine; and ‘extreme redwood’ dominated by tall oldgrowth redwoods with western hemlock, grand fir (Abies grandis), and Douglas-fir 

associates.

Data recorded on each plot included biotic factors including diameter (dbh) of 

trees by species, canopy cover, average canopy height, percent cover and height of 

shrub species, percent cover herbaceous species; and abiotic factors including pH of 

the A horizon, depth to the hardpan, and distance to the center of the pygmy 

formation. In addition, the growth-form of individual S. sempervirens specimens 

sampled on each plot were described with the following characteristics: height, 

number of stems emerging from root bole, diameter of largest stem, and presence of 
‘Pygmy’ Old-Growth Redwood Characteristics on an Edaphic Ecotone in Mendocino County, 

California

315

old-growth canopy characteristics (large lateral branches, reiterated trunks, epiphytes, 

and fire hollows). 

The relationship between stand characteristics and soil pH were analyzed using 

linear regression. Variation of response variables between strata was analyzed using 

ANOVA with Benferroni post-hoc analysis. 

Results

The size and growth-form of trees, composition of vegetation, and soil pH varied 

significantly across the pygmy/redwood ecotone. Soil pH ranged from 4.0 to 6.6, and 

was found to be the best abiotic predictor of stand characteristics. ‘Depth to hardpan’ 

and ‘distance to the pygmy center’ were found to be poor predictors. 

A positive linear relationship was found between canopy height and pH, 

suggesting a negative correlation between canopy height and pygmy soil conditions. 

ANOVA analysis confirmed this relationship with significant differences in canopy 

height between strata with the highest canopy found in the ‘extreme redwood’ 

stratum, and the lowest found in the ‘extreme pygmy’ stratum (table 1).

Table 1—Relationship between soil pH and six dependant variables measured across a 

pygmy/redwood ecotone on six strata; (I) extreme pygmy, (II) short pygmy, (III) tall pygmy, 

(IV) transitional, (V) pygmy redwood, and (VI) extreme redwood. Reported R2 and p-value 

result from linear regression analysis with soil pH. Strata sharing the same lower case letters 

did not exhibit significant differences based on ANOVA. 

I II III IV V VI R2 pvalue

Median soil 

pH 

4.8a 4.95b 4.95 b 5 b 5.25c 5.95c - -

Canopy 

Height (m)

2.09a 5.64b 11.95c 21.5d 39.6e 58.3f 0.29 >0.001

Canopy 

Cover (%)

37.1a 49.2b 59.2b 83.9c 91.7d 97.7d 0.25 >0.001

Shrub 

Cover (%)

70.8a 89.3b 78.1b 60.4c 34.1d 46.3d 0.23 0.003

Herb Cover

(%)

1.8a 1.3a 3a 0.4a 2.35a 16.4b 0.34 >0.001

Understory 

richness 

6a 10b 10b 10b 15c 24d 0.27 >0.001

Basal Area 

(m2/ha)

142.9a 186.6a 66.8b 109.4a 371.3c 479.8c 0.33 >0.001

Basal Area 

of 

Redwood

0a 0a 0a 101.9b 335.1c 371.3c 0.41 >0.001

Basal Area

of Pygmy 

Cypress 

136.8a 175.2a 61.1b 3.3c 0c 0c 0.35 >0.001

Percent tree canopy cover, shrub cover, and herbaceous cover, also exhibited 

linear relationships with soil pH as well as significant differences between strata. 

Tree canopy cover was relatively low on pygmy soils, while shrub cover was 
GENERAL TECHNICAL REPORT PSW-GTR-238 

316

relatively high. Herbaceous cover was uniformly low across the ecotone except for 

the ‘extreme redwood’ stratum, which was significantly higher.

Total basal area, and the basal area of coast redwood, exhibited positive linear 

relationships with soil pH, while the basal area of pygmy cypress exhibited a 

negative linear relationship (table 1). Pygmy cypress and bolander pine had the 

highest relative frequency on first three strata, and coast redwood and Douglas-fir on 

the last three strata (fig. 1). The presence of Douglas-fir in the ‘tall pygmy’ stratum 

and pygmy cypress in the ‘transitional’ stratum suggests a somewhat porous, 

boundary between the two communities. 

Figure 1—Relative frequency (n=60) of the four most commonly occurring tree 

species across six strata: (I) extreme pygmy, (II) short pygmy, (III) tall pygmy, (IV) 

transitional, (V) pygmy redwood, and (VI) extreme redwood, on a pygmy ecotone.

The maximum height, and growth-form, of coast redwood trees also varied 

significantly across the pygmy/redwood soil gradient (fig. 2). In the ‘extreme pygmy’ 

and ‘short pygmy’ strata the growth-form coast redwood was limited to rare multistemmed (>100 stems/plant) shrub-like forms. Still infrequent, but less stunted forms, 

were found in the ‘tall pygmy’ and ‘transitional’ strata. Individuals within these two 

strata tended to be vertical in form with fewer stems (two to six) and generally grew 

in a conical form with little lateral branching in the crown. 
‘Pygmy’ Old-Growth Redwood Characteristics on an Edaphic Ecotone in Mendocino County, 

California

317 

Figure 2—Canopy height of S. sempervirens across six strata (n=60); (I) extreme 

pygmy, (II) short pygmy, (III) tall pygmy, (IV) transitional, (V) pygmy redwood, and 

(VI) extreme redwood, on a pygmy forest ecotone in Mendocino, California (SE=0.26; 

0.76; 1.54; 4.31; 5.26; 7.34).

Individual redwood trees in the ‘pygmy redwood’ and ‘extreme redwood’ strata 

grew in a vertical upright form, and exhibited complex canopy features including 

lateral branching patterns and multiple trunk reiterations. Well-developed fire 

hollows were common on older trees in both strata (fig. 4), and epiphytic vascular 

plants such as leather fern (Polypodium scouleri) huckleberry (Vaccinium ovatum), 

and billberry (Vaccinium parvifolium) were observed growing in the canopy. In many 

ways the growth-form of old-growth trees was comparable between the ‘pygmy 

redwood’ and ‘extreme redwood’ strata, except in regard to scale. The maximum tree 

diameter measured in the ‘extreme redwood’ was 750 cm compared to 244 cm in the 

‘pygmy redwood’ and the maximum heights were 66 m and 41 m respectively. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

318

Figure 4—The ‘Owl Tree’ found in the ‘Pygmy Redwood’ strata with insert illustrating 

complex branching pattern at the top of tree. A continuous fire hollow ran from top to 

bottom, and was a nesting site for barn owls (Tyto alba). Photo courtesy of Dylan 

Crutchfield, Department of Environmental Studies, San Jose State University.

Similarities between the ‘pygmy redwood’ and ‘extreme redwood’ strata were 

less pronounced in regard to understory species. Both herbaceous cover and richness 

of understory species were significantly higher in ‘extreme redwood’ compared to all 

other strata (table1). There were, however, a number of species that were limited to 

pygmy soils including two California Native Plant Society listed species, pygmy 

manzanita (Arctostaphylos mendocinoensis) and the coast lily (Lilium maritimum) 

(table 2).
‘Pygmy’ Old-Growth Redwood Characteristics on an Edaphic Ecotone in Mendocino County, 

California

319

Table 2—Mean percent cover per plot of understory shrubs and herbaceous species

occurring on a pygmy forest ecotone across six strata, (I) extreme pygmy, (II) short pygmy, 

(III) tall pygmy, (IV) transitional, (V) pygmy redwood, and (VI) extreme redwood. Association 

designations indicate species that were limited to specific habitat types. 

Association I II III IV V VI

Pygmy Arctostaphylos 

columbiana

0 0 0.3 0 0 0

Pygmy Arctostaphylos 

mendocinoensisa

0 0.2 0.2 0 0 0

Redwood* Blechnum spicant 0 0 0 0 0 2.4

Redwood* Boschniakia strobilacea 0 0 0 0 0 0.1

Redwood Calypso bulbosa 0 0 0 0.1 0.25 0.5

Redwood* Cardamine californica 0 0 0 0 0 2.1

Redwood Chimaphila menziesii 0 0 0 0.1 0 0

Pygmy Chrysolepis 

chrysophylla

0 0 1.6 0 0 0

Claytonia sibirica 0 0.1 0 0 0.1 0.15

Redwood Clintonia andrewsiana 0 0 0 0 0.5 1.5

Redwood* Corallorhiza 

mertensiana

0 0 0 0 0 0.3

Redwood* Disporum hookeri 0 0 0 0 0 0.2

Redwood* Epipactis gigantea 0 0 0 0 0 0.1

Redwood* Equisetum telmateia 

subsp. braunii

0 0 0 0 0 0.2

Gaultheria shallon 8.9 8.9 9.4 7.5 9.5 23.2

Redwood Goodyera oblongifolia 0 0 0 0.1 0.2 0.1

Pygmy Ledum glandulosum 24.5 46 4.5 0 0 0

Pygmy Lilium maritimumb 0 0.1 0 0 0 0

Myrica californica 5.6 3.8 4.2 6.2 8.7 0

Redwood* Oxalis oregana 0 0 0 0 0 6.2

Redwood Polypodium scouleri 0 0 0 0 0.5 0

Redwood Polystichum munitum 0 0 0 0 0.3 9.8

Pteridium aquilinum 

var. pubescens

5.4 3.4 1.8 0.9 1.5 0.5

Redwood* Rhamnus californica 0 0 0 0 0 0.1

Rhododendron 

macrophyllum

3.5 4.2 29.5 13.1 4.6 7.3

Redwood* Smilacina racemosa 0 0 0 0 0 0.1

Redwood* Stachys bullata 0 0 0 0 0 0.1

Redwood* Tiarella trifoliata var. 

unifoliata

0 0 0 0 0 0.5

Redwood Trientalis latifolia 0 0 0 0 0.1 0

Redwood Trillium ovatum 0 0 0 0.1 0.7 1.4

Vaccinium ovatum 23.7 25.3 27 32.5 5.6 1.8

Redwood Vaccinium parvifolium 0 0.1 1.7 1.1 1.2 3

Viola sempervirens 0 0 0 0 0.1 1.25 a

CNPS special status 1B.2

b

CNPS special status 1B.1

*Species only observed in ‘extreme redwood’ strata
GENERAL TECHNICAL REPORT PSW-GTR-238 

320

Discussion

Westman and Whittaker (1975) described the pygmy forest region of northern 

California as the area containing the “smallest and the largest forests in the world.” 

This dramatic contrast between the pygmy and coast redwood communities is based 

on an edaphic gradient of soil pH, moisture, and nutrient availability. While massive 

redwoods growing on productive soils have been the subject of intense study, the 

tenacious specimens of S. sempervirens persisting on the edge of their ecological 

tolerance have been neglected in the literature. 

While our study involved an analysis of six strata, each with unique 

characteristics, we observed essentially three growth-forms of S. sempervirens: a 

muti-stemmed shrub-like form; a vertical, highly stunted sub-canopy form; and a tall 

vertical co-dominant form with complex canopy structure. S. Sempervirens is able to 

manifest multiple growth-forms as a result of prolific basal and epicormic sprouting. 

Sprouting in coast redwood is a stress response, and where the stresses are 

unremitting the sprouting is continuous. The muti-stemmed shrub-like form of S. 

sempervirens found in the ‘extreme pygmy’ is essentially a mass of basal sprouts 

emerging from a single half buried lignotuber. 

In addition to variation in the growth-form of S. sempervirens, stand structure 

and composition of the stand as a whole varied across the pygmy/redwood ecotone. 

As expected the dominance of pygmy cypress and bolander pine and the cover of 

Ericaceous shrubs (Arctostaphylos mendocinoensis, Gaultheria shallon, Ledum 

glandulosum, Rhododendron macrophyllum, Vaccinium ovatum) were at their 

maximum, and canopy cover and canopy height were at their minimum, within the 

pygmy formation. What was not predicted in the literature was the porosity of the 

boundary between the two communities with Douglas-fir observed within the ‘tall 

pygmy’ strata and pygmy cypress found growing in transitional stands. The influence 

of pygmy soil conditions on adjacent redwood stands was also surprising. In stands 

that would not be considered ‘pygmy’ by any of the traditional pygmy forest 

definitions, stand characteristics varied significantly from ‘extreme redwood’ stands 

and trended toward pygmy conditions. For example, lower cover of herbaceous 

species in the ‘pygmy redwood’ as compared to ‘extreme redwood’ suggests a 

sensitivity of understory species to pygmy soil conditions, possibly as a result of poor 

nutrient availability resulting from low soil pH (Northup et al. 1998). 

There is a tendency to think of coast redwood forests as uniformly impressive in 

terms of stature. In fact, redwoods are highly variable, and where redwoods grow at 

the edge of their ecological tolerance it is their resilience, and morphological 

flexibility, that is truly impressive.

Acknowledgments

This project was supported by the Mendocino Institute, the California 

Department of Parks and Recreation, and the spirit of Lewis and Ieda “Skilly” 

Russell. 
‘Pygmy’ Old-Growth Redwood Characteristics on an Edaphic Ecotone in Mendocino County, 

California

321

References

Aitken, S.N.; Libby, W.J. 1994. Evolution of the pygmy-forest edaphic subspecies of Pinus 

contorta across an ecological staircase. Evolution 48: 1009-1019.

Fox, W.W. 1976. Pygmy forest: an ecological staircase. California Geology 2: 1-7.

Northup, R.R.; Dahlgren, R.A.; McColl, J.G. 1998. Polyphenols as regulators of plantlitter-soil interactions in northern California’s pygmy forest: A positive feedback?

Biogeochemistry 42: 189-220.

Preston, R. 2007. The wild trees: a story of passion and daring. London: Allen Lane 

Publishers. 

Sawyer, J.O.; Sillett, S.C.; Libby, W.J.; Dawson, T.E.; Popenoe, J.H.; Largent, D.L.; Van 

Pelt, R.; Veirs, S.D. Jr.; Noss, R.F.; Thornburgh, D.A.; Del Tredici, P. 2000. Redwood 

trees, communities, and ecosystems: a closer look. In: Noss, R.F., editor. The 

redwood forest: history, ecology, and conservation of the coast redwood. Washington, 

DC: Island Press: 81-118.

Sholars, R.E. 1982. The pygmy forest and associated plant communities of coastal 

Mendocino County, California. Mendocino, CA: Black Bear Press.

Sillett, S.C.; VanPelt, R. 2000. A redwood tree whose crown is a forest canopy. Northwest 

Science 74: 34-43.

Spickler, J.C.; Sillett, S.C.; Marks, S.B; Welsh, H.H. 2006. Evidence of a new niche for a 

North American salamander: Aneides vagrans residing in the canopy of old-growth 

redwood forest. Herpetological Conservation and Biology 1: 16-26.

Westman, W.E. 1975. Edaphic climax pattern of the pygmy forest region of California.

Ecological Monographs 45: 109-135.

Westman, W.E.; Whittaker, R.H. 1975. The pygmy forest region of northern California: 

studies on biomass and primary productivity. Journal of Ecology 63(2): 493-520.

Wurzburger, N.; Bledsoe, C.S. 2001. Comparison of ericoid and ectomycorrhizal 

colonization and ectomycorrhizal morphotypes in mixed conifer and pygmy forests 

on the northern California coast. Canadian Journal of Botany 79: 1202-1210.

Yu, Z.; Dahlgren, R.A.; Northup, R.R. 1999. Evolution of soil properties and plant 

communities along an extreme edaphic gradient. European Journal of Soil Biology 

35: 31-38.

323

Size Distribution of Unharvested Redwood 

Forests in Mendocino County1

Bradley E. Valentine2

Abstract

Late-seral conditions in redwood forests are becoming a management goal on some 

timberlands. However, published information is rare regarding the structure of late-seral 

forests upon which silvicultural prescriptions can be guided, or upon which to measure 

success. Old-growth forests—those perceived to be near or at the successional climax—are 

the ultimate model. Yet, old-growth forests are a rare commodity in Mendocino County, 

limited mostly to state parks and small stands on private lands. Their rarity yields a poor 

sampling of the variation among stands, making historic sources of information valuable. 

Despite often incomplete information relative to ecologically important but non-commercial 

vegetation such as hardwoods or the structural complexity of their trees’ canopy and boles, 

historic timber inventories can yield insights to the range of unharvested forests conditions. A 

1929 data set derived from timber stands stratified into 20-thousand board feet per acre 

redwood classes on Caspar Lumber Company lands reveals an inverse J-shaped size 

frequency distribution based on diameter at breast height (DBH). Across the stand conditions, 

redwood comprised 67 to 96 percent of the tree density (31 to 51 trees per ac) and 73 to 97 

percent of the basal area (116 to 537 ft2

/ac); the DBH50 (diameter at which half of the trees 

were smaller) ranged from 17 to 30 inches DBH; while the DBH90 ranged from 42 to 70 

inches. The largest size classes measured were 126+ inches, 78 to 82 inches, and 42 to 46 

inches for redwood, Douglas-fir, and grand fir, respectively.

Key words: late-seral, late-successional, old-growth, stand structure, targets, hardwoods

Introduction

To enable setting goals and evaluating management actions, descriptive criteria 

of late-seral conditions can be important to forest managers in the redwood (Sequoia 

sempervirens) region. Where cut-over forests have been acquired in parks, restoration 

of more advanced and near-climax stages is a goal (e.g., Chittick and Keyes 2007). 

Other land managers desire to manage forest stands for late-seral values as well as for 

other values including commodity production (e.g., Thornburgh 2007). Still other 

forest land owners who have late-seral forests in a Timber Harvesting Plan can avoid 

significant impacts under the California Forest Practice Rules (Anon. 2011) if their 

harvests retain late-seral conditions after harvests.

Whether to establish success criteria for restoration or to consider the 

maintenance of or the degree of departure from late seral conditions, working 

definitions are lacking or imperfect. The Forest Practice Rules’ (Anon. 2011) 

definition includes trees greater than 24 in either with or lacking understory trees; an 

open to dense canopy; a minimum area threshold (20 ac); and the presence of an 

 

1 This paper was presented at the Coast redwood forest in a changing environment: a symposium for 

scientists and managers. June 21-23, 2011, Santa Cruz, California. 2 California Department of Fish and Game, Northern Region; 135 Ridgway Ave., Santa Rosa, CA. 

95401; (704) 523-3617. (bvalentine@dfg.ca.gov). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

324

unspecified density of large decadent trees, snags, and large down logs. This 

definition’s lack of specifics may be due to its intended use in many forest types 

across the state. However, equally important, its ambiguity may be a reflection that 

late-seral forests are variable. Not only may they vary locally due to site condition 

and localized disturbance dynamics, the late-seral stands may occupy any point along 

a successional continuum from mid-seral to climax conditions. Criteria developed 

specifically for different forest types and regions could enhance the use of the lateseral concept in forest management.

Unharvested redwood forests can be the source of information upon which to 

develop regional management goals. To the extent they represent near-climax 

conditions, unharvested forest represent perhaps the ultimate example of late-seral 

qualities. However, in Mendocino County, current unharvested stands are rare and of 

generally small acreage, limiting how much variation they may encompass. Despite 

the focus on economic values of forests, historic information can be mined to yield 

stand-based information to better understand the range of conditions present in lateseral forests. This paper characterizes the “virgin” forest conditions of conifers on the 

Caspar Block of the Caspar Lumber Company (Anon. 1929); a management unit that 

closely approximates the present-day Jackson Demonstration State Forest.

Methods and materials

According to the report (Anon. 1929), the lands inventoried were the “Caspar 

Block”, an area of 23,564 ac of which 18,629 ac were virgin timber. The Caspar 

Block was in the watersheds of Two Log, Chamberlain, James and Two Rock 

Creeks, and adjoining parts of the South Fork of Noyo and the Little North Fork of 

Big River.

While the methods are described in the inventory, the description is limited. In 

summary, Caspar Lumber Company had preexisting cruises organized by 40 ac units. 

However, stand conditions frequently covered such small areas and were so 

important to deriving an accurate inventory that evaluating the timber values based 

on the 40 ac units would not have shown the actual situation clearly. To solve this 

problem, overlapping aerial photographs, complimented by the cruise information 

were used to create a map of "economic types". Then "more than 200" one quarter ac 

sample plots separated by 5 chains were sampled. Neither the starting point(s) nor the 

orientation of the sampling frame is specified. A sample of trees was cored, and the 

thickness of the bark recorded; however, the report is not clear if the size 

distributions calculated included or excluded bark thickness. The plots were not laid 

out to achieve any specified level of sampling within or among the "economic types". 

Rather, a plot was assigned to its economic type based on where the plot fell on the 

map. The report does not provide a count of plots by economic type, except that there 

were "a large number of sample areas in each type".

The “economic types” to which virgin stands were assigned was based upon the 

quantity of redwood/acre as derived from company cruises adjusted to agree with the 

company’s cutting experience (table 1).
Size Distribution of Unharvested Redwood Forests in Mendocino County

325

Table 1—Identifers, definitions of economic types, and possible percentage of sample plots.

Identifier Redwood volume

Board ft/Acre thousands (M)

Area

(Acres)

Percent of

Samples

80+ more than 80 431 7

60 – 80 between 60 and 80 528 3

40 – 60 between 40 and 60 2643 10

20 – 40 between 20 and 40 7120 44

<20 less than 20 7907 36

A map in the inventory (Anon. 1929) displays the geographic distribution of 

assigned economic types, roads, watercourses, and ridges. Also included are 61 

numbered points that are neither identified on the map index nor the body of the 

report. These may reflect location information (possibly start points) for the plot 

sampling frame. To approximate the sampling distribution if it was based on these 

points, I calculated the percentage of points by the “economic type” in which they 

were placed (table 1).

Results

When the plot data for all conifers is grouped within economic types, each 

displays an inverse J-shaped curve (fig. 1a). Generally the curves are ordered 

according stand type, with the density of trees in the 80+ type greatest and that of the 

<20 type least. The ordering by stand type is most notable in the larger size classes. 

In the 14 to 22 in size class, the <20 type had the greatest density among the types. 

The size class distribution of redwoods (fig. 1b) also was ordered similarly among 

types, but with density of the 80+ types greater than the other in all size classes. 

Notably, the curve shows the smallest size class of redwood in the 80+ type being 

denser relative to the larger size classes than those of the other types, despite the 

presumably more heavily shaded understory in the 80+ stand. The largest redwood 

was in the 126 in size class, and was found in the 80+ type. Among types, the 

Douglas-fir (Pseudotsuga menziesii) size class distribution (fig. 1c) ranged from 

inverse J-shaped curves for the lowest economic types to flat curves for the highest 

types. The density of Douglas-fir in the latter types was very low, and much lower 

than for the lowest economic types. The largest Douglas-fir measured was in the 78 

in size class of the 20-40 type. Grand fir3

 (Abies grandis) also exhibited flat to 

declining size class distributions (fig. 1d), and there was no apparent relationship 

between their density and the economic types. Although not common in any type, 

grand fir was not recorded in the <-20 type and was most common in the 60-80 type. 

The largest grand fir (42 in size class) was measured in all but the 60-80 type. 

Total tree density ranged from 30 to 51 trees/ac (calculated values are rounded to the 

nearest whole number), increasing from the lowest to the highest economic type. 

Redwood comprised 67 to 96 percent of the trees in each type, with the highest 

economic type substantially greater than the other types. Graphs of cumulative 

percent of tree density by DBH class can enable a rapid assessment of the proportion

of trees in a stand either greater or less than a given DBH. For instance, among the 

types, the median density of trees ranged from 18 to 30 in DBH, and 90 percent of 

 

3 The inventory identifies the third conifer species as white fir without its specific epithet. White fir is 

not known from the vicinity, and the intended species was most likely grand fir.
GENERAL TECHNICAL REPORT PSW-GTR-238 

326

Fig. 1a. All conifers

0

1

2

3

4

5

6

7

8

9

10

1014182226303438424650545862667074788286909498

102106110114118122126

DBH (4 inch size class)

Trees per Acre

Type 0-20 M

Type 20-40 M

Type 40-60 M

Type 60-80 M

Type 80+ M

Fig. 1 b. Redwood

0

1

2

3

4

5

6

7

8

9

10

1014182226303438424650545862667074788286909498

102106110114118122126

DBH (4 inch size class)

Trees per acre

0-20 M 

20-40 M 

40-60 M 

60-80 M 

80+ M 

Fig. 1 c. Douglas-fir

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

10141822

26

303438424650545862667074788286909498

102106110114118122126

DBH (4 inch size class)

Trees per acre

0-20 M 

20-40 M 

40-60 M 

60-80 M 

80+ M 

Fig. 1d. Grand fir

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1014182226303438424650545862667074788286909498

102106110114118122126

DBH (4 inch size class)

Trees per acre

20-40 M 

40-60 M 

60-80 M 

80+ M 

Figure 1—Conifer density (trees per acre) by size class and stand type in virgin 

forests of the Caspar Block, 1929; a=all conifers, b=redwoods, c=Douglas-fir, and 

d=grand fir.

Fig. 2a. <20 M

0

10

20

30

40

50

60

70

80

90

100

10

18

2634425058

66

748290

98

106114122

DBH (4 inch size class)

Cumulative Percent

Redwood (23)

D. Fir (7)

All Sp. (30)

Fig. 2b. 20-40 M

0

10

20

30

40

50

60

70

80

90

100

1014182226303438424650545862667074788286909498

102106110114118122126

DBH (4 inch size class)

Cumulative Percent

Redwood (24)

D. Fir (9)

Grand Fir (2)

All Sp. (35)

Fig. 2c. 40-60 M

0

10

20

30

40

50

60

70

80

90

100

1014182226303438424650545862667074788286909498

102106110114118122126

DBH (4 inch size class)

Cumulative Percent

Redwood (34)

D. Fir (7)

Grand Fir (1)

All Sp. (41)

Fig. 2d. 60-80 M

0

10

20

30

40

50

60

70

80

90

100

1014182226303438424650545862667074788286909498

102106110114118122126

DBH (4 inch size class)

Cumulative Percent

Redwood (31)

D. Fir (4)

Grand Fir (6)

All Sp.(40)

Fig. 2e. > 80 M

0

10

20

30

40

50

60

70

80

90

100

1014182226303438424650545862667074788286909498

102106110114118122126

DBH (4 inch size class)

Cumulative Percent

Redwood (49)

D. Fir (1)

Grand Fir (1)

All Sp.(51)

Figure 2—Cumulative percent of conifer trees by diameter class and species in virgin 

forests of the Caspar Block, 1929; stand types a) <20 M, b) 20-40 M, c) 40-60 M, d) 

60-80 M, and e) 80+ M. Species-specific density is given parenthetically by stand 

type.
Size Distribution of Unharvested Redwood Forests in Mendocino County

327

the trees were less than 42 to 74 in DBH (fig. 2a to 2e). The values of both the 

median and 90 percent DBH increased with economic type. The similarity between 

the cumulative DBH curves for redwood and all conifers (fig. 2a to 2e) displays how 

the former dominates this metric of the stand condition.

Basal area ranged from 116 to 536 ft2

/ac, increasing substantially with an 

increase in economic type. Redwood comprised about 73 percent of the basal area in 

the lowest two economic types, 85 percent in the 40-60 and 60-80 economic type, 

and 97 percent in the 80+ type. Compared to the cumulative percent of trees by DBH 

class, the curves for cumulative percent of basal area by DBH class (fig. 3a to 3e) 

portrays relatively “s” shaped curves. The trace of redwood cumulative basal area by 

DBH class was most similar to that for all trees, showing the dominance of redwood 

as a determinant of basal area in these forests. The DBH of median basal area ranged 

from 36 to 66 in, while that at which 90 percent of the basal area was less ranged 

from 61 to 98 in. Both increased with economic type. 

Fig. 3a. < 20 M

0

10

20

30

40

50

60

70

80

90

100

101826344250586674829098

106114122

DBH (4 inch size class)

Cumulative Percent of Basal AreaRedwood (85)

D. Fir (31)

All Sp. (116)

Fig. 3b. 20-40 M

0

10

20

30

40

50

60

70

80

90

100

1014182226303438424650545862667074788286909498

102106110114118122126

DBH (4 inch size class)

Cumulative Percent

Redwood (156)

D. Fir (55)

Grand Fir (5)

All Sp. (216)

Fig. 3c. 40-60 M

0

10

20

30

40

50

60

70

80

90

100

1014182226303438424650545862667074788286909498

102106110114118122126

DBH (4 inch size class)

Cumulative Percent

Redwood (246)

D. Fir (40)

Grand Fir (4)

All Sp. (290)

Fig. 3d. 60-80 M

0

10

20

30

40

50

60

70

80

90

100

1014182226303438424650545862667074788286909498

102106110114118122126

DBH (4 inch size class)

Cumulative Percent

Redwood (285)

D. Fir (38)

Grand Fir (17)

All Sp. (340)

Fig. 3e. > 80 M

0

10

20

30

40

50

60

70

80

90

100

1014182226303438424650545862667074788286909498

102106110114118122126

DBH (4 inch size class)

Cumulative Percent

Redwood (522)

D. Fir (11)

Grand Fir (4)

All Sp. (537)

Figure 3—Cumulative percent of conifer basal area by diameter class and species in 

virgin forests of the Caspar Block, 1929; stand types a) <20 M, b) 20-40 M, c) 40-60 

M, d) 60-80 M, and e) 80+ M. Species-specific total basal area is given 

parenthetically by stand type.

Discussion

Metrics associated with tree size are convenient for describing stand conditions. 

Because this information is important in assessing the economic value, the methods 
GENERAL TECHNICAL REPORT PSW-GTR-238 

328

have a long history and common understanding among various users. In their 

literature review of coast redwood forest disturbance dynamics, Lorimer et al. (2009) 

characterize northern forests from several studies. Veirs (1982, in Lorimer et al.

2009) evaluated nine 2.53 ac plots in near-coastal, intermediate, and xeric slope 

forests near Redwood National Park. He reported the minimum size to reach canopy 

status to be 23.6 in, and a mean of 27.7 canopy trees/ ac (range 22.9 to 38.4 > 23.6 

in). Redwood comprised 41 to 95 percent of the canopy trees. Basal area averaged 

689 ft2

/ac (range 455 to 1085 ft2/ac) with redwood accounting for 43 to 97 percent. 

Lorimer et al. (2009) note that of Veirs’ nine sites, only two or three had size 

distributions that approximate a “negative exponential or rotated sigmoid curve” 

typical of uneven-aged, old-growth forests. This divergence from the expected size 

distribution is not explained for the mesic, near-coast sites; but they suggest upland 

sites may depart due to climatic shifts, limited sample size – and perhaps most 

importantly – moderate disturbance. The presence of Douglas-fir, a species requiring 

fire-related disturbance for recruitment was presented as evidence for the disturbance. 

Sample size is a likely difference between the clear inverse J-shaped curves for each 

economic type at Caspar and those reported by Veirs. While lots differed in size 

between the studies, the apparently more numerous plots in the Caspar Block data 

should have averaged out localized disturbance-induced variation that might 

overwhelm patterns at few sites.

Dagley and O’Hara (2003) summarize a number of studies on the density of trees 

in unharvested stands, and found the density is highly variable across the redwood 

range. They note that differences in methods and definitions complicate comparison. 

Based on upper canopy trees, the density ranged approximately from 20 to 150 

trees/ac, the majority being redwood. Direct comparison of these values to the Caspar 

Block data is limited. The preponderance of the summarized studies sites were at 

Bull Creek and Redwood National Park in the northern part of the range while central 

Mendocino County is in the central part of the redwood forest’s range (Sawyer et al. 

2000). Also, while considering only canopy tree density may have ecological 

relevance, determining what constitutes a canopy tree needs clarification. The studies 

reviewed by Dagley and O’Hara (2003) used unspecified or different DBH criteria. 

Still, the cumulative distribution graphs (fig. 2a to 2e) can facilitate enumeration by 

whatever DBH class is relevant.

Giusti (2007) presents historic inventory data from lands that became Redwood 

National Park in Del Norte County. As presented (fig. 5 of Giusti 2007), unharvested 

redwood from ARCO, Simpson, and Rellim Timber Companies consistently present 

an inverse J-shaped curve. Although Giusti (2007) did not fully describe the methods 

used in these historic inventories, they likely included averaging a large number of 

samples including upland and riparian areas over the 9,000 ac cruised. In addition, 

Giusti (2007) also tabulates tree density data from Redwood creek, Little Lost Man 

Creek, and Bull Creek in Humboldt County. Respectively, trees greater than 40 in 

averaged 11.3, 12, and 35 trees/ac. The density of trees in the Caspar Block that 

exceeded this size class ranged from 3 to 18 trees per ac for the < 20M and the 80+ 

M types, respectively (fig. 2a to 2e).

Hardwood associates in redwood/Douglas-fir forest likely common in the Caspar 

Block area include tanoak (Lithocarpus densiflorus), madrone (Arbutus menziesii), 

bigleaf maple (Acer macrophyllum), California bay (Umbellularia californica), and 

golden chinquapin (Castanopsis chrysophylla). These species, though of limited 
Size Distribution of Unharvested Redwood Forests in Mendocino County

329

economic value have great ecological value. They are often overlooked in timber

inventories, even though they may constitute a substantial component of forests. As 

for conifers, the hardwood content and stand structure of future stands is a direct 

outcome of present management (Harrington and Tappeiner 2009). Managers who 

focus on developing large conifers without simultaneously planning for a substantial 

hardwood component when developing restoration treatments may fail to achieve the 

broad ecological values of late-seral forests. Unfortunately, information is limited on 

the hardwood component of unharvested conifer stands upon which to evaluate either 

the range of natural variation or management goals.

In northwestern California, Bingham and Sawyer (1992) found the density of 

hardwoods and conifers to be 82 and 24 per ac, respectively, in old stands. Diameters 

of hardwoods averaged 15 in, while conifer DBH averaged 38 in. Using average 

density and DBH, the study concluded that the hardwood basal area of the old stands 

approximated 50 ft2

/ac, just over 20 percent of the total basal area.

The most comparable data from the central portion of the Redwood range comes 

from Montgomery Woods State Reserve (Giusti 2007). Data on tree species inclusive 

of hardwoods, size, and habitat elements were analyzed from an average of four 0.1 

ac plots at 98.4 ft spacing along 14 parallel transects that crossed the alluvial plain 

and extended into the adjacent upland. These plots collectively characterize a single 

stand. Unlike the size distributions observed on the Caspar Block, the plot for 

Montgomery Woods displays a flat, inverse J-shaped curve with redwood and 

Douglas-fir about equally dominant within each of the 10 in size classes. Twenty one 

trees/ac exceed 40 inches, with only one tree/ac – a redwood – exceeding 80 in. The 

flatness of the Montgomery Woods size distribution lead Giusti to conclude that 

recruitment may be limited on the site. Redwood dominated with nearly 60 percent of 

the large conifer density, Douglas-fir had the remainder. Importantly, Giusti (2007) 

found that by density, tan oak made up 85 percent of the less than 10 in DBH size 

class, 89 percent of the trees in the 11 to 20 in DBH class, and 7 percent of the > 20 

in size class. Giusti (2007) does not report basal area directly, but it can be 

approximated from his data. Using size class mid-points, the stocking of all tanoaks 

was 83 ft2

/ac, and those greater than 10 in DBH accounted for 49 ft2/ac; 

approximately 15 and 10 percent of the stands total basal area. The Montgomery 

Woods stand data indicate that both quantitatively and proportionately, tanoaks are a 

heavy and dominant understory component. The degree to which effective fire 

suppression since the early 20th century affects the species mix, especially in the 

smallest size class, is unknown.

The variation among the Caspar Block’s economic types may be due to many 

factors. The absence of plot-specific information prevents statistical analyses of 

differences between the types or the variance within types. Although the stands were 

virgin timber, the time elapsed since their last stand-replacing event may be variable; 

that is, their relative position along the successional continuum is unknown. The 

species mix may reflect topographic position, with redwood dominant on alluvial 

sites and a broader mix of conifer species upslope (Lorimer et al. 2009). Topography 

may well be the driver of processes that acts on tree physiology and disturbance 

dynamics to yield the differences observed in species composition and biomass 

across stands types. Topography constrains available moisture and soil 

characteristics. Both within and among economic class variation can result from 

disturbance dynamics that vary by topography. Localized disturbance events such as 
GENERAL TECHNICAL REPORT PSW-GTR-238 

330

individual tree fall can lead to substantial variation if sample size is few or the area 

sampled is small relative to the tree fall impact area. Because succession within late 

seral forest when scaled to large areas likely proceeds towards an asymptote over 

long periods, the points in the successional continuum at which a stand is studied can 

lead to among stand variation. Analysis of the map associated with the inventory 

(Anon. 1929) may help describe topographic relationships with the economic types. 

Stand structure that can be useful for describing late-seral management 

conditions and goals. However, the Caspar Block and Montgomery Woods studies 

are too few and of limited geographic range to have confidence in the amount of 

variation that may exist within regional unmanaged late-seral stands. Publication of 

historic inventories, despite their probable omission of non-conifer information could 

yield more useful descriptions of late seral structure. Collecting more comprehensive 

information on extant stands, while possibly being obscured by decades or more of 

fire exclusion can also broaden the picture of unharvested stand structures.

Tree size and density are in many ways a caricature of late-seral conditions. 

Simplistic stand tables fail to recognize or quantify the elements more important to a 

late-seral forest community. These elements include substantial amounts of the 

products that accumulate over time: tree decline, decadence, death such as snags 

(Giusti 2007) and logs (Bingham and Sawyer 1988, Porter and Sawyer 2007); 

mechanical and fire-induced disturbance such as reiterated branches (Sillett and Van 

Pelt 2000) and basal hollows (Finney 1996); establishment of epiphytes (Sillett and 

Van Pelt 2007); and late-seral associated species (Russell and Michels 2010). Foresttype and regional quantification of the elements at the scale of a stand will add 

substantially to tree size and density criteria to assure that late-seral management 

achieves ecological goals.

Acknowledgments

I would like to thank Marc Jameson, retired Forest Manager at Jackson 

Demonstration State Forest for surfacing and making this data set available to me. 

Also, Tony LaBanca encouraged me to publish this data through allotting work time.

References

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block with reference to selective cutting. Unpublished report prepared for the Caspar 

Lumber Company by Mason and Stevens, Portland, OR. Copy on file at Jackson 

Demonstration State Forest, Fort Bragg, CA.

Anonymous. 2011. California Forest Practice Rules, 2011. Sacramento, CA: California 

Department of Forestry and Fire Protection.

Bingham, B.B.; Sawyer, J.O. Jr. 1988. Volume and mass of decaying logs in an upland oldgrowth redwood forest. Canadian Journal of Forest Research 18: 1649-1651.

Bingham, B.B.; Sawyer, J.O. Jr. 1992. Canopy structure and tree condition of young, 

mature and old-growth Douglas-fir/hardwood forests. In: Harris, R.R.; Erman, D.E., 

technical coordinators, Kerner, H.M., editor. Proceedings of symposium on biodiversity 

of northwestern California, October 28-30, 1991, Santa Rosa, CA. Wildland Resources 

Center Report No. 29. Berkeley, CA: University of California: 141-149.
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Chittick, A.G.; Keyes, C.R. 2007. Holter Ridge thinning study, Redwood National Park: 

preliminary results of a 25-year retrospective. In: Standiford, R.B.; Giusti, G.A.; 

Valachovic, Y.; Zielinski, W.J.; Furniss, M.J., technical editors. Proceedings of the 

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PSW-GTR-194. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific 

Southwest Research Station: 271-280.

Dagley, C.M.; O’Hara, K.L. 2003. Potential for old forest restoration and development of 

restoration tools in coast redwood: A literature review and synthesis. Unpublished

report. Berkeley, CA: University of California. 72 p.

Finney, M.A. 1996. Development of fire scar cavities on old-growth redwood. In: 

LeBlanc, J., technical coordinator and editor. Proceedings of the conference on coast 

redwood forest ecology and management. U.C. Coop. Extension: 96-98.

Giusti, G.A. 2007. Structural characteristics of an old-growth coast redwood stand in 

Mendocino County, California. In: Standiford, R.B.; Giusti, G.A.; Valachovic, Y.; 

Zielinski, W.J.; Furniss, M.J., technical editors. Proceedings of the redwood region 

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Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest 

Research Station: 161-168.

Harrington, T.B.; Tappeiner, J.C. 2009. Long-term effects of tanoak competition on 

Douglas-fir stand development. Canadian Journal of Forest Research 39: 765-776.

Lorimer, C.G.; Porter, D.J.; Madej, M.A.; Stuart; J.D., Veirs, S.D. Jr.; Norman, S.P.; O’Hara, 

K.L.; Libby, W.J. 2009. Presettlement and modern disturbance regimes in coast 

redwood forests: implications for the conservation of old-growth stands. Forest 

Ecology and Management 258: 1038-1054.

Porter, D.J.; Sawyer, J.O. Jr. 2007. Upland log volumes and conifer establishment patterns 

in two northern, upland old-growth redwood forests, a brief synopsis. In: 

Standiford, R.B.; Giusti, G.A.; Valachovic, Y.; Zielinski, W.J.; Furniss, M.J., technical 

editors. Proceedings of the redwood region forest science symposium: What does the 

future hold? Gen. Tech. Rep. PSW-GTR-194. Albany, CA: U.S. Department of 

Agriculture, Forest Service, Pacific Southwest Research Station: 403-413. 

Russell, W.; Michels, K.H. 2010. Stand development on a 127-yr chronosequence of 

naturally regenerating Sequoia sempervirens (taxodiaceae) forests. Madroño 57(4):

229-241.

Sawyer, J.O.; Sillettt, S.C.; Popenoe, J.H.; LaBanca; A.; Scholars, T.; Largent, D.L.; Euphrat,

F.; Noss, R.F.; Van Pelt, R. 2000. Characteristics of redwood forests. In: Noss, R.F., 

editor. The redwood forest: history, ecology and conservation of the coast redwood. 

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Sillett, S.C.; Van Pelt, R. 2000. A redwood tree whose crown is a forest canopy. Northwest 

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Sillett, S.C.; Van Pelt, R. 2007. Trunk reiteration promotes epiphytes and water storage 

in an old-growth redwood forest canopy. Ecological Monographs 77(3): 335-359.

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Valachovic, Y.; Zielinski, W.J.; Furniss, M.J., technical editors. Proceedings of the 

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stand development in the Pacific Northwest. Corvallis, OR: Oregon State University: 

119-141.
333

Structure and Dynamics of an Upland OldGrowth Forest at Redwood National Park, 

California

Phillip J. van Mantgem1 and John D. Stuart2

Abstract

Many current redwood forest management targets are based on old-growth conditions, so it is 

critical that we understand the variability and range of conditions that constitute these forests. 

Here we present information on the structure and dynamics from six one-hectare forest 

monitoring plots in an upland old-growth forest at Redwood National Park, California. We 

surveyed all stems ≥20 cm DBH in 1995 and 2010, allowing us to estimate any systematic 

changes in these stands. Stem size distributions for all species and for redwood (Sequoia 

sempervirens (D. Don) Endl.) alone did not appreciably change over the 15 year observation 

interval. Recruitment and mortality rates were roughly balanced, as were basal area dynamics 

(gains from recruitment and growth versus losses from mortality). Similar patterns were found 

for Sequoia alone. The spatial structure of stems at the plots suggested a random distribution 

of trees, though the pattern for Sequoia alone was found to be significantly clumped at small 

scales (< 5 m) at three of the six plots. These results suggest that these forests, including 

populations of Sequoia, have been generally stable over the past 15 years at this site, though it 

is possible that fire exclusion may be affecting recruitment of smaller Sequoia (< 20 cm 

DBH). The non-uniform spatial arrangement of stems also suggests that restoration 

prescriptions for second-growth redwood forests that encourage uniform spatial arrangements 

do not appear to mimic current upland old-growth conditions. 

Key words: forest dynamics, forest structure, old-growth, spatial pattern

Introduction

Remnant old-growth stands represent only a small fraction of current redwood 

forest area (Sawyer et al. 2000a), but play crucial roles in conservation and 

restoration of these ecosystems. As our best analogue to redwood forest conditions 

prior to the arrival of industrialized human settlement, remnant old-growth redwood 

stands are used as reference conditions for managers seeking to accelerate the 

development of second-growth forests (e.g., NPS 2008). In spite of their importance, 

relatively little is known about the basic structure and function of old-growth 

redwood forests (Busing and Fujimori 2002, Lorimer et al. 2009). Part of the 

difficulty is that old-growth conditions are relatively difficult to describe; by 

definition old-growth forests contain trees from a wide range of ages and sizes, with 

areas of closed canopy and open gaps (i.e., high spatial complexity) (Franklin et al. 

2002). This structural complexity is magnified in old-growth redwood forests, which 

contain some of the oldest and largest trees known (Sillett et al. 2010). 

 

1 U.S. Geological Survey, Western Ecological Research Center, Redwood Field Station, 1655 Heindon 

Road, Arcata, CA 95521.Corresponding author: telephone: (707) 825-5189, FAX: (707) 825-8411. 

(pvanmantgem@usgs.gov). 

2 Department of Forestry and Wildland Resources, Humboldt State University, Arcata, CA 95521.
GENERAL TECHNICAL REPORT PSW-GTR-238 

334

Further complications arise from the fact that old-growth redwood forest 

conditions vary across topographic gradients, from alluvial terraces to steep hillsides 

and ridgetops. Redwood forests on alluvial flats are comprised of almost pure stands 

of redwood Sequoia sempervirens (hereafter Sequoia) while upland stands are 

composed of a mix of species including Sequoia, Douglas-fir (Pseudotsuga menziesii

var. menziesii (Mirb.) Franco), tanoak (Notholithocarpus densiflorus syn. 

Lithocarpus densiflorus) and other species (Sawyer et al. 2000b). Redwood stands on 

alluvial terraces and upland stands experience contrasting disturbance regimes, with 

stands found on alluvial areas subject to periodic inundation and deposition following 

floods, while upland stands are more prone to fire (and to a lesser extent landslides 

and windthrow) (Lorimer et al. 2009). There is some concern that Sequoia may not 

be able to maintain dominance in the absence of fire, although Busing and Fujimori 

(2002) show that at an alluvial habitat Sequoia populations have been stable. It is 

unclear how well this finding may hold in upland habitats where historically fires 

were more common (Lorimer et al. 2009). 

The spatial structure of stands is another important, but undocumented, potential 

difference between alluvial and upland habitats. The spatial arrangement of stems 

(the degree to which the distribution of trees in a stand can be considered clumped, 

random or uniform) is a defining structural element of stands, determining local 

competitive environments (Biging and Dobbertin 1992, Das et al. 2008). Recently, 

Dagley (2008) described old-growth alluvial redwood forest spatial structure as 

clumped to random for overstory forest trees. Establishing if non-random spatial 

structure is also common in upland stands is highly relevant for redwood forest 

restoration; many thinning prescriptions for second-growth forest restoration may 

create uniform conditions (NPS 2008), which may persist for decades, but may or 

may not mimic old-growth forest spatial patterns.

Here we present information on forest structure and dynamics from six upland 

forest stands in Redwood National Park. We analyze differences in forest structure 

among our sites in terms of species composition, stem size distributions and the 

spatial arrangement of stems. Our information is derived from repeated surveys of 

these sites, so we also are able to directly calculate key demographic rates, including 

recruitment, growth and mortality. Our results largely confirm earlier findings from 

alluvial forests (Busing and Fujimori 2002, Dagley 2008), in that redwood forest 

populations appear to be generally stable and forest spatial patterns are not uniform.

Methods

Study sites 

The region around Redwood National Park features a Mediterranean climate, 

with mild, rainy winters and cool, dry summers (Sawyer et al. 2000b). Annual mean 

temperatures are approximately 15 °C, with annual precipitation of about 170 cm, 

mostly occurring as winter rain. Summer fog is common near the coast, moderating 

the dry summer conditions. Soils are primarily derived from sandstone, mudstone and 

schist. Historically, fire has shaped coastal redwood forests, but has been largely 

excluded in the region of our study sites over the past 100 years (Ramage et al. 

2010). 
Structure and Dynamics of an Upland Old-Growth Forest at Redwood National Park, California

335

We surveyed six 1 ha plots to determine forest structure in an upland redwood 

forest (fig. 1). The sites have never been logged. Frequent fires characterized the 

forests prior to Euro-American settlement, but there is no recent record of fire in the 

areas containing the study plots. The plots were established in 1995 to compare forest 

structure in these old-growth areas to an adjacent second-growth stand known as the 

Whiskey Forty (Teraoka and Keyes 2011). Surveys mapped all stems ≥20 cm 

diameter at breast height (DBH, 1.37 m), measured tree diameters, and assessed tree 

status (live vs. dead) (table 1). In 2010 we surveyed these stands again for trees ≥20 

cm DBH, recording current DBH, mortality (of trees extant in 1995), and recruitment 

(trees now ≥20 cm DBH but not recorded in 1995). Radial growth was determined 

from repeated stem diameter measurements. There were 13 instances of negative 

growth and 21 instances of unrealistically large radial growth (>15 mm year-1), which 

probably arose from measurement error. We wished to remove outliers with 

exceptionally large negative and positive growth rates, but did not wish to bias our 

results in a positive direction by removing all negative growth rates. For this reason 

we removed from analysis stems that had radial growth rates < -2 mm year-1 or >15 

mm year-1, roughly 1 percent of our observations. 

 

Figure 1—Location of the six upland old-growth redwood forest plots. The plots are 

located near an area of second-growth forest (locally known as the “Whiskey 40”), 

but are in a large, otherwise undisturbed old-growth forest. 

Data analysis

We determined forest structure in terms of stand density (stems ha-1), basal 

area (m2 ha-1), and size class distributions. We measured patterns of stem size 

distributions at each plot using a departure index, M, that is similar to the Gini 

coefficient, but can distinguish both the magnitude and direction of change 

(Menning et al. 2007). The departure index M was calculated for 1995 versus 

the 2010 censuses, and compared against a null model that assumed no 
GENERAL TECHNICAL REPORT PSW-GTR-238 

336

Table 1—Characteristics of forest monitoring plots at the time of establishment in 1995 

(stems >= 20 cm DBH). 

Plot UTM* UTM Elevation Stem count (ha) Basal area (m2 ha-1)

identifier Easting Northing (m) 1995 2010 1995 2010

Plot 1 415657 4570743 472 230 244 174 165

Plot 2 415776 4570731 446 185 175 163 176

Plot 3 415440 4570690 460 134 131 205 231

Plot 4 415276 4570941 403 153 163 133 136

Plot 5 415645 4571428 461 185 193 138 146

Plot 6 415786 4571464 412 212 183 198 195

Table 1 (continued)

Plot

identifier Species comprising > 1% of stem counts**

Plot 1 TSHE 42%; SESE 27%; PSME 22%; LIDE 8%

Plot 2 TSHE 42%; SESE 29%; PSME 25%; LIDE 3%; ABGR 1%

Plot 3 SESE 46%; ABGR 21%; TSHE 16%; PSME 10%; LIDE 8%

Plot 4 SESE 38%; LIDE 27%; ABGR 17%; TSHE 13%; PSME 5%

Plot 5 LIDE 30%; SESE 29%; PSME 25%; TSHE 16%

Plot 6 SESE 37%; TSHE 37%; PSME 23%; LIDE 3%

* UTM coordinates in NAD 1983, zone 10.

** At time of plot establishment. ABGR = Abies grandis (Dougl. ex D. Don) Lindl.; LIDE = 

Notholithocarpus densiflorus syn. Lithocarpus densiflorus; PSME = Pseudotsuga menziesii var. 

menziesii (Mirb.) Franco; SESE = Sequoia sempervirens (D. Don) Endl.; TSHE = Tsuga heterophylla 

(Raf.) Sarg. Percentages may not add to 100 due to rounding.

differences between these measurement intervals. Differences in M between the 

observed values and null model were compared using a Wilcoxon signed rank test. 

We compared demographic rates (recruitment and mortality) as well as basal area 

dynamics (basal area gains from recruitment and growth versus basal area losses 

from mortality) using paired randomization tests to account for small sample sizes 

and non-normal distributions (Manly 2001). 

We described tree spatial distributions within each plot by considering individual 

trees as points, and examined nearest neighbor patterns at multiple scales using the 

inhomogeneous K-function, a second-moment measure that accounts for variability 

in the average density (also called intensity) of trees across each plot (Baddeley 

2008). Intensity is the expected number of points per unit area, and may be constant 

(homogenous) or vary across locations (inhomogeneous). Plots of kernel estimates of 

intensity suggested high variations in intensity, suggesting that inhomogeneous 

models were more appropriate for our data. For each plot we considered spatial 

patterns within a search radius of up to 25 percent the side of the plots, 25 m. We 

determined the significance of the departure from complete spatial randomness 

(CSR) by comparing observed values to the 95 percent simultaneous critical envelope 

(Baddeley 2008) [avoiding inflation of type I errors (Loosmore and Ford 2006)], 

calculated from 999 simulations of random point fields, with intensity patterns 

estimated using a kernel smoothing function. Results are presented in terms of the 

normalized K statistic, L(h) (where h represents the search radius), which is centered 

on zero. L(h) values within the 95 percent critical envelope are consistent with a 
Structure and Dynamics of an Upland Old-Growth Forest at Redwood National Park, California

337

random distribution of stems, while values below the critical envelope are considered 

significantly uniform, and values above the critical envelope are considered 

significantly clumped.

We used a marked point process model to directly test if Sequoia has a different 

spatial structure compared to other co-occurring species, using the inhomogeneous 

K-function normalized at zero [i.e., LSequoia, Other (h)]. We created a 95 percent

simultaneous critical envelope from 999 simulations using random toroidal shifts of 

the pattern for each taxonomic group, where observed values within the envelope 

indicate similar distributions, values below the envelope indicate the species groups 

“repulse” each other in space, values above the envelope indicate “attraction” in the 

groups’ spatial pattern. 

Results 

At the time of plot establishment in 1995 stem density for trees ≥20 cm DBH 

ranged from 134 to 230 trees ha-1 and averaged 183 trees ha-1 (±2 SE = 29) and basal 

area ranged from 133 to 205 m2

 ha-1 and averaged 169 m2 ha-1 (±2 SE = 24) (table 1). 

Although Sequoia comprised on average only a small proportion of stems at each plot 

(mean ± 2 SE = 61 ± 8 trees ha-1, 33 percent of stems), this species comprised the 

majority of average basal area (mean ± 2 SE = 100 ± 30 m2

 ha-1, 59 percent of total 

average basal area). There was little change in density or basal area for trees ≥20 cm 

DBH from 1995 to 2010 (table 2).

At the time of plot establishment in 1995 stems >20 cm DBH generally followed 

a negative exponential (“inverse-j”) size class distribution (fig. 2A). Stem size classes 

were similar in 2010, so that the negative exponential distributions were maintained 

(fig. 2B). The departure index M was relatively unchanged over this time period 

(average M = + 0.002, average range of M = -0.388 to 1.612), and was not 

significantly different compared against a null model of no change (Wilcoxon signed 

rank test, P = 1). For Sequoia, there was a suggestion that stems size distributions 

were becoming more skewed in favor of large stems from 1995 to 2010 (average M = 

+ 0.044, average range of M = -0.611 to 1.389, Wilcoxon signed rank test, P = 

0.049), but changes were small (fig. 2).

The relative lack of change in stand structure from 1995 to 2010 was also 

supported by demographic measurements. Plot-level average recruitment and 

mortality rates were balanced (annualized recruitment rate = 0.700 percent, 

annualized mortality rate = 0.698 percent, paired randomization test, 9999 iterations, 

P = 0.46) (table 2). The demographic rates for Sequoia also were essentially 

equivalent (annualized recruitment rate = 0.229 percent, annualized mortality rate = 

0.325 percent, paired randomization test, 9999 iterations, P = 0.77). The dynamics of 

basal area from 1995 to 2010 did not suggest substantial changes; annualized basal 

area gain from recruitment and growth (average = 0.98 m2

 ha-1 year-1) was roughly 

balanced by losses from mortality (average = 0.80m2 ha-1 year-1) (paired 

randomization test, 9999 iterations, P = 0.26) (table 2). Similar patterns in basal area 

dynamics also were found for Sequoia (average basal area gain from recruitment and 

growth = 0.50 m2

 ha-1 year-1; average basal area loss from mortality = 0.38 m2 ha-1

year-1; paired randomization test, 9999 iterations, P = 0.35) (table 2). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

338

20-50 50-100 100-150 150-200 200-250 250-300 300-350 350-400

Count

0

20

40

60

80

100

Other species

Sequoia

Stem diameter class (cm)

20-50 50-100 100-150 150-200 200-250 250-300 300-350 350-400

0

20

40

60

80

100

A

B

Contour plots of the spatial intensity showed that the density of stems was highly 

variable across each plot (not shown), indicating the need to use the inhomogeneous 

measures of spatial pattern. The inhomogeneous L(h) statistic showed a random 

arrangement of stems at most spatial scales across all plots (although a single plot 

showed a minor degree of clumping at small scales) (fig. 3A). Estimates of the spatial 

pattern of Sequoia alone suggest significant clumping at small scales for three of the 

six plots (fig. 3B). Direct comparison of Sequoia versus other co-occurring species 

suggests that these groups are strongly segregated at spatial scales greater than 

approximately 10 m (fig. 3C). 

 

Figure 2—Stem size class distributions averaged across 

six 1-ha plots for trees ≥20 cm DBH in 1995 (A), and in 

2010 (B).
Structure and Dynamics of an Upland Old-Growth Forest at Redwood National Park, California

339

Table 2—Annualized demographic rates and basal area dynamics (gains from recruitment 

and growth and losses from mortality) from 1955 to 2010 for trees >20 cm DBH. 

Demographic rates were roughly balanced (P = 0.46), as were losses and gains in basal area 

(P = 0.26) (paired randomization tests). Similar patterns were found for Sequoia. Confidence 

intervals were determined from 1000 bias corrected bootstrapped samples.

Plot Recruitment Mortality Basal area gain Basal area loss

identifier rate (%) rate (%) (m2 ha-1 year-1) (m2 ha-1 year-1)

All species Plot 1 1.02 0.73 1.02 1.57

Plot 2 0.35 0.64 1.04 0.36

Plot 3 0.53 0.46 1.23 0.17

Plot 4 1.01 0.59 1.02 0.82

Plot 5 0.98 0.60 0.75 0.48

Plot 6 0.31 1.16 0.78 1.41

average 0.70 0.70 0.98 0.80

95% CI 0.46 to 0.94 0.58 to 0.99 0.85 to 1.1 0.41 to 1.28

Sequoia only Plot 1 0.11 0.67 0.42 0.40

Plot 2 0.00 0.26 0.44 0.20

Plot 3 0.11 0.11 0.92 0.02

Plot 4 0.66 0.35 0.64 0.66

Plot 5 0.25 0.13 0.21 0.26

Plot 6 0.25 0.44 0.36 0.77

average 0.23 0.33 0.50 0.38

95% CI 0.1 to 0.43 0.19 to 0.5 0.35 to 0.71 0.19 to 0.61
GENERAL TECHNICAL REPORT PSW-GTR-238 

340

a

b

Linhomog(h) -2

-1

0

1

2 Random

Not random

LSequoia inhomog(h) -4

-2

0

2

4

Distance (m)

0 5 10 15 20 25 LSequoia, Other inhomog(h) -4

-2

0

2

4

A

B

C

Figure 3—Tree spatial pattern for all species at six upland old-growth redwood stands (A), the 

pattern for Sequoia alone (B), and Sequoia versus all other species (C). Lines are the observed 

normalized K-function [L(h)] for individual plots. Dashed intervals represent random distributions 

and solid intervals above and below the zero control line indicate statistically significant (α = 

0.05) clumping or repulsion, respectively. Significance was determined by departures from 95

percent simultaneous critical envelopes (Baddeley 2008). 
Structure and Dynamics of an Upland Old-Growth Forest at Redwood National Park, California

341

Discussion

Our old-growth redwood stands appeared to be generally stable from 1995 to 

2010, a finding in agreement with earlier observations from an alluvial terrace 

(Busing and Fujimori 2002). Stem size class distributions generally followed an 

“inverse-j” distribution, which suggests stable populations in old-growth stands 

(Avery and Burkhart 2002). Stable stem size distributions and direct measurements 

of forest dynamics suggest that these stands did not experience large changes over the 

15 year observation interval. 

There has been speculation that in the absence of moderate disturbance from fire 

Sequoia might fail to maintain its dominant status in these communities (Lorimer et 

al. 2009), but our observations failed to provide clear support for this idea. We found 

some evidence that Sequoia stem size distributions may have become less dominated 

by small trees over time, but recruitment and mortality rates for Sequoia were 

roughly balanced, as were gains and losses in basal area. However, our measurements 

of recruitment include only stems that were ≥ 20 cm DBH, so it is possible that we 

are missing early signals of reproductive failure in the absence of fire (Ramage et al. 

2010). More detailed observations of small tree dynamics are needed to fully 

document the reproductive output of Sequoia (whether by seed or sprouting) in 

upland old-growth forests under current conditions. Moreover, the 15 year length of 

observations presented here is short in comparison to ages of dominant trees in our 

study site. It may be that large changes in stand and population dynamics occur 

infrequently or will only be detectable over longer time scales. 

In terms of spatial structure, with very little exception we found a random 

arrangement of stems across all spatial scales at all six upland stands. This finding 

was promoted by the use of the inhomogeneous formulation of the K-statistic and a 

more statistically defensible method of determining statistical significance, resulting 

in tests that were more conservative and less likely to show significant clumping or 

uniformity. In spite of this, we still identified strong evidence of clumping at small 

spatial scales (from approximately 1 to 5 m) for Sequoia at half of the plots, an 

unsurprising finding given the sprouting habit of this species. Moreover, there 

appeared to be segregation between Sequoia and other species at large 

(approximately > 10 m) spatial scales. Thus, the general conclusions of Dagley 

(2008) concerning the restoration targets for alluvial stands appear to hold for upland 

stands: thinning prescriptions that encourage uniform spatial arrangements of stems 

do not appear to mimic current old-growth structure. 

How well current old-growth conditions reflect stand structure prior to European 

settlement is difficult to determine precisely (Stephenson 1999). The disruption of 

historic disturbance regimes, exotic species (including pathogens), and other changes 

have likely altered these forests. But until a better model for restoration targets is 

identified, these stands provide our best understanding of reference conditions. 

Continued measurement and monitoring of old-growth upland stands is needed to 

insure we are able detect any subtle, pervasive trends that may be occurring (van 

Mantgem et al. 2009). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

342

Acknowledgments

We thank Jon Hollis, Laura Lalemand and Jon Chin for their assistance in the 

field and Janelle Deshais for creating the plot map. Funding for this project was 

provided by the National Park Service. Any use of trade names is for descriptive 

purposes only and does not imply endorsement by the U.S. Government. 

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Sawyer, J.O.; Gray, J.; West, G.J.; Thornburgh, D.A.; Noss, R.F.; Engbeck, J.H.; Marcot, 

B.G.; Raymond, R. 2000a. History of redwood and redwood forests. In: Noss, R.F., 

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Forest Health

United States 

Department of 

Agriculture

Forest Service

Pacific Southwest 

Research Station

General Technical 

Report

PSW-GTR-238

April 2012

Proceedings of the Coast Redwood 

Forests in a Changing California: 

A Symposium for Scientists and 

Managers
347

Damage and Mortality Assessment of 

Redwood and Mixed Conifer Forest Types 

in Santa Cruz County Following Wildfire

Steve R. Auten1 and Nadia Hamey1 

Abstract

On August 12, 2009, the Lockheed Fire ignited the west slope of the Santa Cruz Mountains 

burning approximately 7,819 acres. A mixture of vegetation types were in the path of the fire, 

including approximately 2,420 acres of redwood forest and 1,951 acres of mixed conifer 

forest types representative of the Santa Cruz Mountains. Foresters and land managers were 

left with tough decisions on how to treat tree damage and mortality compounded by the Pine 

Mountain Fire which occurred in the same area in 1948. Big Creek Lumber Company (BCL), 

Cal Poly’s Swanton Pacific Ranch (SPR) and other professionals familiar with this region of 

redwood teamed up to develop a method for evaluating damage and mortality. Qualitative 

criteria for evaluating stand damage focused on historic defect, cambial death, root damage, 

and associated fire intensity. Quantitative damage criteria was used to contrive three mortality 

assessment tables, broken up by diameter class (1 through 8, 9 through 16, 17+), for all tree 

species and tested against 83, 1/5th acre fixed plots from SPR’s Continuous Forest Inventory. 

Since the initial mortality evaluation using the new tables in fall of 2009, each of the 2877 

trees have been re-evaluated in spring 2010 and spring 2011. Accuracy against the initial 

evaluation is 89.3 percent.

Key words: damage, hardwood, mortality, redwood

Introduction

What should be harvested to encourage regeneration of selectively-managed 

forestland in the Southern Subdistrict of the Coast Forest District following wildfire? 

What determines tree mortality for the purpose of amending the sustainability 

analysis (SA) of a Non-industrial Timber Management Plan (NTMP) following 

wildfire? Charged with managing and maintaining the health and vigor of the forest 

ecosystem, foresters and land managers need an accurate way of field-evaluating 

damage and mortality in conifers and hardwoods immediately following wildfire. 

These questions and many others not related to forest health, loomed for the local 

forestry community following the Lockheed Fire. This paper is a case study to 

provide other foresters and land managers with information and knowledge gained 

through our experiences following the Lockheed Fire to help make decisions about 

damage and mortality in conifers and hardwoods as a result of wildfire.

 

1 Registered Professional Foresters, Swanton Pacific Ranch, 125 Swanton Road, and Big Creek Lumber 

Company, 3564 Highway 1, respectively, Davenport, CA 95017. (sauten@calpoly.edu, nadiah@bigcreek.com). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

348

Seasonal context

The time of year and prevailing wind direction during the Lockheed Fire was 

very similar to conditions during the Pine Mountain Fire, which is the last recorded 

and mapped fire perimeter within the Lockheed Fire area. The Pine Mountain Fire 

burned in September 1948, 61 years ago, and consumed 15,899 acres. The Lockheed 

Fire also took place in late summer, a season when historically lightning strikes have

caused fires in the Santa Cruz Mountains; although the Lockheed Fire was humancaused. Other large historic fires are known to have occurred in the vicinity of the 

Lockheed Fire near the turn of the 19th century associated with logging and power 

generation projects in the Scotts Creek watershed. 

Damage assessment

The land management goals of the large Timber Production zoned parcels are for 

timber production and protection of associated resources such as wildlife, fisheries, 

and watershed. The mission of the landowners affected by this fire was to determine 

the level of defect and remove some of the most damaged wood to bring defect down 

to an acceptable level for future management. 

Consider the accounting for a timber harvest conducted a few years ago in an 

area heavily hit by the Pine Mountain Fire, where the defect was 23 percent, about 11

percent higher than “average” for the Santa Cruz Mountains. The loss of net return to 

the landowner was about $71,500 for approximately 1 million board feet harvested. 

Fire intensity

In order to understand burn intensity patterns, fire behavior was estimated for the 

day the fire started under the prevailing weather and fuel conditions. Five different 

fuel models, representing five vegetation types, were used in the BehavePlus 

computer simulation to estimate fire behavior. The BehavePlus fire modeling system 

is a collection of models that describe fire behavior, fire effects and the fire 

environment. 

Burn severity analysis was conducted initially by a Risk Assessment Team put 

together by Cal-Fire. The team used a Burned Area Reflectance Classification 

(BARC) satellite-derived map of post-vegetation condition made by comparing 

satellite near and mid infrared reflectance values. This data was evaluated in several 

ways. Some team members flew over the fire area on the first clear day and 

photographed post-fire conditions. Other team members made ground-based 

observations over the fire area while assisting with suppression and suppression 

repair efforts. Burn severity across the entire burn area was estimated to be 14

percent very high, 37 percent high, 43 percent moderate, and 6 percent low.

Research

Foresters working in the burned area began researching what to expect from the 

various levels of burn damage. Little research or literature is available relative to 

wildfire impacts on redwood defect and mortality, especially in this region. Several 

papers about fire damage and anticipated mortality from prescribed burns in mixedconifer forests were helpful. One paper emerged with practical insights on tree 
Damage and Mortality Assessment of Redwood and Mixed Conifer Forest Types in Santa Cruz 

County Following Wildfire

349

mortality and wildfire from Willis W. Wagener in 1961 (Wagener 1961), called 

“Guidelines for Estimating the Survival of Fire Damaged Trees in California.” 

Following a literature review, many conversations occurred with other foresters 

and land managers throughout the state to learn from their experiences. Contacts 

included: 

 Mike Jani and John Anderson from Mendocino Redwood Company, with 

experience the year prior conducting salvage operations on the Lightning 

Complex Fire. 

 Lathrop Leonard from California State Parks with experience in prescribed 

burning. 

 Rich Casale, District Conservationist, USDA Natural Resources 

Conservation Service.

 David Van Lennep and Mike Duffy from Redwood Empire Sawmills. We 

toured the Summit Fire area that has been salvage logged by them the year 

prior.

 Dale Holderman, Chief Forester emeritus for Big Creek Lumber Company, 

with significant experience in defect levels in the Santa Cruz Mountains. 

Repeatedly other land managers stated that the salvage operations undertaken in 

burned areas did not remove enough of the damaged timber. Significant loss of future 

commercial value is expected as a result of the persistent fire-scar defect. 

Cambium death, root damage and crown scorch

Determining the level of internal defect from the external visual indicators on the 

tree immediately post-fire was very difficult. The methodology evolved over the 

course of months investigating the extent of the burn and initiating salvage operations 

in the most severely burned areas, and is still ongoing. Foresters started out chipping 

into the bark of trees with a hatchet to see what types of bark characteristics are 

indicative of damage to the cambium layer. Immediately after the fire as the 

cambium was dying, that layer appeared very dry compared to live cambium which 

oozed resin. Dying cambium also sometimes appeared grey versus red or pink for 

live cambium. A particularly useful tool turned out to be delivering a sound kick to 

the tree. A hollow sound would indicate that the cambium had died and the wood 

separated from the bark. 

On some trees bark burned completely through exposing the wood underneath. 

Other trees had cracks in the bark showing the wood indicating that the cambium had 

been burned. Other trees had hollowed-out bases where large quantities of roots had 

been burned. Reduced root mass affects the tree’s growth rate and if the damage is 

substantial, it can affect the trees stability and slow the rate of recovery. Many 

scorched trees that experienced crown fire lost all of their needles during the first 

winter, which provided a good carpet of mulch on the ground. 

Trees with cambium damage in multiple quadrants were considered to be 

substantially damaged, especially when occurring in conjunction with previous scars. 

Although redwood compartmentalizes rot as it grows over it, the dead cambium will 

rot wood interior to it. The effects of dead cambium introducing defect are 

immediate. As the water transport cells break down, the sapwood dries out and is 

therefore susceptible to dry rot and termite attacks. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

350

As the trees began to grow, the cracks in the bark where cambium had burned 

began to separate. Now, 2 years after the fire, the bark plates have separated where 

cambium died and you can see the cambium growing over the dead wood layer and 

re-sealing the perimeter of the tree. Badly burned trees developed a variety of fungus 

and lichen on the scorched bark, giving clues about the extent of internal damage. 

There was increased burn damage in certain environmental settings such as: 

where ladder fuels were present, next to a more flammable vegetation type, on ridges, 

in topographic chimneys, in dense stands of un-thinned trees and where there was a 

heavy duff layer, legacy stumps, or lots of downed wood. Canopy damage ranged 

from an un-phased crown to all but the biggest limbs completely consumed in a 

crown fire. Severely burned trees did not re-sprout from the limbs, but only from the 

bole, like a bottle-brush. Where new limbs or tops are formed, the dead wood will be 

subsumed in the new growth, creating a weak spot in the wood. 

 

Most second growth redwood trees that have experienced an intense wildfire in 

the past have an interior cylinder of rot. Using the U.S. Department of Agriculture, 

Forest Service Log Scaling and Grading Rules, that defect is “squared out” in order 

to account for waste when manufacturing dimensional lumber. The quality of the 

wood going into the mill is very important for the end result of producing sound 

building materials. Compounded defect from multiple fires would severely impact 

the manufacturing of high grade lumber. Experience dictates that defect levels 

elevated above 20 percent have dramatic consequences for the net return of a timber 

harvest for the landowner. 

Adaptive management

During the first fall after the fire, a small area (4 ac) was salvage logged with 

ground based equipment to see the extent of the burn damage. Initiating the salvage 

effort offered an opportunity for foresters to verify the external indicators used to 

determine defect. Once the trees were cut, the dead cambium sections were 

discernible in the cross-section because the usually fuzzy, fibrous inner bark becomes 

smooth and sometimes separated from the wood when it is dead.

The rot from the fresh fire scars had already started. Landowners wishing to grow 

sound trees for sustainable harvest had to react. More damage was sustained to the 

timber resource than was recouped in the salvage. Trees left with fire scaring and 

dead wood are more vulnerable to fire and insect attack going into the future. Due to 

the practice of leaving the healthiest residual trees to retain structure for wildlife and 

maintain microsite characteristics, many trees were left. It was not inexpensive to log,

nor did it produce windfall profits. Compounding the loss, the low profitability in 

Douglas-fir markets necessitated that many thousands of dead Douglas-fir trees be 

left standing. Redwood seedlings were under-planted in some of these areas. 

Helicopter salvage harvest

Multiple land managers elected to proceed with a salvage harvest by helicopter. 

Helicopter harvesting is extremely expensive, but avoids the ground disturbance of 

conventional harvest methods such as tractor logging. The salvage operation was a 
Damage and Mortality Assessment of Redwood and Mixed Conifer Forest Types in Santa Cruz 

County Following Wildfire

351

long-term land management decision to “cut the losses” and establish better wood 

quality in the future. Helicopter harvesting affects the bottom line, but weighing all 

decision-making factors, it made sense for the initial salvage effort due to the 

resource protection it affords as a result of the minimal ground impact. Other factors 

affecting the decision to fly included the relative inaccessibility of the ground, 

seasonal restrictions for sensitive species, the helicopters availability, and the desire 

to recover the damaged wood quickly. 

Mortality assessment

The SPR NTMP was approved in June of 2008. Encompassed in this document is 

the sustainability analysis (SA) required by the Forest Practice Rules to demonstrate 

movement toward a fully regulated state of harvest over time. In essence, this means 

a “cut what you grow” type system focused on the long term sustained yield of forest 

products. Once the Lockheed Fire burned over the majority of the SPR NTMP area, 

the SA had to be re-evaluated. What determines tree mortality for the purpose of 

amending the NTMP’s sustainability analysis following wildfire?

Mortality assessment method 

SPR’s Continuous Forest Inventory (CFI) samples approximately 2 to 3 percent 

of the forested area, probably considered by most to be a lower sample for most 

forest inventories. Where the SPR CFI system excels is in sampling intensity within 

the plot, measuring all trees in the plot down to one inch Diameter at Breast Height 

(DBH). Each tree is numbered and has a distance and bearing recorded to plot center 

so it can be tracked over time. Last re-measurement of the 83 CFI plots in the burn 

area was 2008 and 2003. This means an excellent record of tree condition prior to the 

fire now exists. 

The purpose of the mortality assessment was to test a set of guidelines based on 

professional opinion and available scientific literature for the forester or land 

manager to utilize to evaluate conifer and hardwood mortality levels immediately 

following wildfire. 

The mortality assessment began with an initial evaluation in fall of 2009. The 

data listed below was gathered on each tree in the plot and applied to tables 1, 2 and 

3 (below) to evaluate tree mortality:

1. Percent of crown remaining on each tree to 1 inch DBH 

2. Percent of crown sprouting on each tree to 1 inch DBH

3. Basal sprouting? Y/N

4. Percent of root system and cambium quadrants (four possible) destroyed by 

fire (not recorded, but evaluated) 

5. Will the tree live or die? Y/N

6. 10th acre plot regeneration less than 1 inch DBH

7. Plot photos in cardinal directions 

The tables below state the characteristics that were assessed on each tree to determine 

whether the tree would live or die. For example, look at table 2, Tanoak:

• zero percent canopy remaining

• less than 5 percent canopy sprouting 
GENERAL TECHNICAL REPORT PSW-GTR-238 

352

• missing more than 66 percent of its root system

• Two quadrants of cambium destroyed by fire 

• The tree was considered dead.

Table 1—Thresholds for determining tree mortality: 1 – 8 inch DBH classes (1.0” – 8.9”). 

Table 2—Thresholds for determining tree mortality: 9 – 16 inch DBH (9.0” – 16.9”). 

Tree Species Percent canopy Percent canopy Percent of root Cambium quadrants

remaining sprouting system missing destroyed by fire

Redwood (RW) 0% 5% 66% 2

California nutmeg (CN) 0% 5% 50% 2

Live oak (LO) 0% 5% 66% 2

Tanoak (TO) 0% 5% 66% 2

Red alder (RA) 0% 5% 50% 2

California bay laurel (CL) 0% 5% 50% 2

Pacific madrone (PM) 0% 5% 50% 2

Big leaf maple (BM) 0% 5% 50% 2

Douglas-fir (DF) 60% N/A 33% 1

Monterey pine (MP) 60% N/A 33% 1

Knobcone pine (KP) 60% N/A 33% 1

Table 3—Thresholds for determining tree mortality: 17.0+ inch DBH classes (17.0”+). 

Tree Species Percent canopy Percent canopy Percent of root Cambium quadrants

remaining sprouting system missing destroyed by fire

Redwood (RW) 0% 0% 66% 3

California nutmeg (CN) 0% 0% 50% 2

Live oak (LO) 0% 0% 66% 3

Tanoak (TO) 0% 0% 66% 3

Red alder (RA) 0% 0% 50% 2

California bay laurel (CL) 0% 0% 50% 2

Pacific madrone (PM) 0% 0% 50% 2

Big leaf maple (BM) 0% 0% 50% 2

Douglas-fir (DF) 60% N/A 33% 2

Monterey pine (MP) 60% N/A 33% 2

Knobcone pine (KP) 60% N/A 33% 2

Each tree was evaluated, qualitatively, around these guidelines, but if the tree met 

all of the thresholds by DBH category it was considered dead. 

Tree Species Percent canopy Percent canopy Percent of root Cambium quadrants

remaining sprouting system missing destroyed by fire

Redwood (RW) 0% 10% 33% 1

California nutmeg (CN) 0% 10% 33% 1

Live oak (LO) 0% 10% 33% 1

Tanoak (TO) 0% 10% 33% 1

Red alder (RA) 0% 10% 33% 1

California bay laurel (CL) 0% 10% 33% 1

Pacific madrone (PM) 0% 10% 33% 1

Big leaf maple (BM) 0% 10% 33% 1

Douglas-fir (DF) 70% N/A 33% 1

Monterey pine (MP) 70% N/A 33% 1

Knobcone pine (KP) 70% N/A 33% 1
Damage and Mortality Assessment of Redwood and Mixed Conifer Forest Types in Santa Cruz 

County Following Wildfire

353

Mortality assessment results 

The mortality assessment began with an initial evaluation in fall of 2009 These 

same 83 plots (2,877 trees) were re-evaluated in spring of 2010 and spring of 2011 to 

determine whether the initial mortality assessment in fall of 2009 was correct.

Overall weighted average for percent accuracy to date is 89.3 percent. See tables 4, 5, 

and 6 below for more detailed information on species, diameter class, percent 

accuracy and sample size.

 Table 4—Accuracy of tree mortality assessment: 1 – 8 inch DBH.

Tree Species Percent accuracy Sample size

Redwood (RW) 90.4% 470

California nutmeg (CN) 58.3% 12

Live oak (LO) 85.9% 207

Tanoak (TO) 88.0% 302

Red alder (RA) 62.5% 8

California bay laurel (CL) 84.0% 119

Pacific madrone (PM) 77.0% 61

Big leaf maple (BM) 0.0% 2

Douglas-fir (DF) 96.2% 290

Monterey pine (MP) 82.3% 17

Knobcone pine (KP) 0.0% 0

Weighted average 88.7% 1488

 

 Table 5—Accuracy of tree mortality assessment: 9 – 16 DBH.

Tree Species Percent accuracy Sample size

Redwood (RW) 93.2% 223

California nutmeg (CN) 80.0% 5

Live oak (LO) 88.0% 150

Tanoak (TO) 83.9% 181

Red alder (RA) 0.0% 0

California bay laurel (CL) 66.0% 50

Pacific madrone (PM) 73.0% 15

Big leaf maple (BM) 0.0% 0

Douglas-fir (DF) 97.5% 122

Monterey pine (MP) 78.9% 19

Knobcone pine (KP) 100.0% 3

Weighted average 88.1% 768

 

 Table 6—Accuracy of tree mortality assessment: 17.0+ inch DBH.

Tree Species Percent accuracy Sample size

Redwood (RW) 97.7% 271

California nutmeg (CN) 66.0% 3

Live oak (LO) 89.1% 74

Tanoak (TO) 95.4% 66

Red alder (RA) 28.6% 7

California bay laurel (CL) 55.0% 9

Pacific madrone (PM) 50.0% 6

Big leaf maple (BM) 0.0% 0

Douglas-fir (DF) 90.5% 180

Monterey pine (MP) 100.0% 2

Knobcone pine (KP) 100.0% 3

Weighted average 92.4% 621
GENERAL TECHNICAL REPORT PSW-GTR-238 

354

 

Mortality assessment discussion 

The mortality assessment was led in the field by the same SPR forestry technicians 

for all three evaluation periods maintaining continuity in an assessment that had a 

manageable level of subjectivity. 

Following the initial evaluation of the 83 plots in fall 2009 portions of the burn 

area were salvaged harvested in 2010 and harvested under the SPR NTMP in 2011. 

Forestry technicians were very systematic at determining if trees evaluated in 2009 

were affected by harvesting activities. If so, those trees were removed from the 

sample for the purposes of this test. 

Accuracy for the mortality assessment tables in the first two evaluation periods 

(spring 2010 and spring 2011) following the initial evaluation in fall 2009 at 89.3 

percent was strong, but the mortality assessment table faltered a little in the thinner 

bark species; California nutmeg, red alder, California bay laurel, Pacific madrone, 

and big leaf maple in the mid (9” to 16” DBH) and upper (17.0+” DBH) diameter 

classes. Based on the data set, reducing the “Cambium quadrants destroyed by fire” 

to “one” in both the mid and upper diameter classes would increase accuracy. These 

trees did not withstand as much cambial damage as expected.

The mortality assessment showed very strong results in redwood, tanoak, live 

oak, Douglas-fir, Monterey pine, and knobcone pine to date. Adjustments to increase 

accuracy for these species would likely require additional data on other burn 

characteristics such as scorch height and bark thickness.

Conclusion

A combination of factors affected the decision making process in regards to what 

trees were harvested to encourage regeneration of managed forestland following 

wildfire. One or more of the following criteria affecting an individual tree were 

reason to suspect substantial damage and sustained negative impacts from the fire: 

cambium damage on multiple sides of the tree, extensive root damage with voids 

under the tree, extensive crown consumption or scorching that kills limbs, and 

significant prior defect combined with damage. This is an ongoing learning 

experience that will be refined as time passes and managed forestland continues to 

burn and be harvested. 

The process of damage evaluation provided significant direction to determine an 

applied set of quantitative criteria to develop the mortality assessment. It is clear that 

more years need to pass to understand the full effects that the Lockheed Fire, 

compounded by the Pine Mountain Fire, had on the forested area in the Scotts Creek 

watershed. Follow-up surveys will re-visit the 2,877 trees each spring to see if the 

mortality assessment table continues to hold its accuracy. There is also movement 

from Cal Poly San Luis Obispo to begin sampling scorch height and bark thickness in 

addition to the mortality assessment in an attempt to create a local wildfire mortality 

equation. 
Damage and Mortality Assessment of Redwood and Mixed Conifer Forest Types in Santa Cruz 

County Following Wildfire

355

References

Wagener, W.W. 1961. Guidelines for estimating the survival of fire-damaged trees in 

California. Miscellaneous paper 60. Berkeley, CA: U.S. Department of Agriculture, Forest 

Service, Pacific Southwest Forest and Ranch Experiment Station. 11 p.

357

Decomposition and N Cycling Changes in 

Redwood Forests Caused by Sudden Oak 

Death 

Richard C. Cobb1 and David M. Rizzo1 

Key words: decomposition, litterfall, nitrogen mineralization, Phytophthora ramorum, 

redwood, selective species removal, sudden oak death

Introduction

Phytophthora ramorum is an emergent pathogen in redwood forests which causes 

the disease sudden oak death. Although the disease does not kill coast redwood 

(Sequoia sempervirens), extensive and rapid mortality of tanoak (Notholithocarpus 

densiflorus) has removed this important tree in much of the central and southern 

distribution of the redwood forest type. Phytophthora ramorum was first described in 

the 1990s and while the native range of the pathogen remains unknown, it has a 

narrow range of genetic variation characteristic of an exotic species (Rizzo et al. 

2005). P. ramorum has a broad host range in California but infection leads to very 

different impacts to host health. Infection in tanoak leads to rapid host mortality 

which can occur in as little as 2 years in large diameter trees (Cobb 2010a). 

Sporulation rates are also highly variable among redwood forest hosts. Tanoak and 

California bay laurel (Umbellularia californica) support sporulation sufficient for 

emergence of disease, but sporulation can be as much as 10 times greater in bay 

laurel during warm spring rain events (Davidson et al. 2008, 2011). Infection in bay 

laurel has no known negative impacts on bay laurel health at the individual or 

population level (Cobb et al. 2010, Davidson et al. 2008). These differences in 

sporulation are important drivers of pathogen spread across the range of redwood 

(Meentemeyer et al. 2011). Within stands, increased prevalence of infected bay laurel 

and tanoak increase tanoak mortality rates but infection in bay laurel has the greatest 

effect on tanoak mortality commensurate with the high rates of sporulation in this 

species (Cobb et al. 2010). Redwood stands with high densities of bay laurel are most 

likely to be invaded by P. ramorum (Meentemeyer et al. 2008) while stands with 

high densities of tanoak are likely to experience the greatest ecosystem impacts 

(Lamsal et al. 2011, Ramage et al. 2011). 

Foresters have recognized the importance of native insect pests and pathogens 

since the beginning of modern forestry but over the last 100 years, exotic pests and 

pathogens increasingly challenge the goals of ecosystem management including the 

maintenance of biodiversity and functional processes such as nutrient cycling (Eviner 

and Likens 2009, Lovett et al. 2006). Insects and pathogens can alter the chemical 

composition of plant material by physically damaging foliage or eliciting plant 

chemical defenses. These changes can result in altered rates of litter decomposition 

 

1 Plant Pathology, University of California Davis, One Shields Avenue, Davis, CA 95616-8751; (530) 

754-9894; (530) 752-5674 (Fax); (rccobb@ucdavis.edu). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

358

and nutrient release (Cobb et al. 2006). Mortality of individual trees arrests nutrient 

uptake and alters forest microclimate (Orwig et al. 2008) which can in turn cause 

increased nutrient cycling and decomposition rates (Cobb and Orwig 2008). When 

outbreak results in the removal of one species, a shift in forest community 

composition can lead to long-term changes to decomposition and nutrient cycling. 

Species removal can cause disproportionately large changes to an ecosystem if the 

removed tree has ecologically unique functions such as casting deep shade, 

producing especially nutrient rich, or nutrient poor litter (Cobb 2010b, Lovett et al. 

2006). While it is clear that tanoak is declining in much of the range of redwood 

forests, the implications of tanoak removal for redwood ecosystem function are 

unknown (Rizzo et al. 2005). 

Eradication of many exotic forest pests and pathogens is rarely an attainable goal. 

For P. ramorum, the broad host range, extensive geographic area which has been 

invaded, and the lack of impacts to bay laurel health suggest this pathogen is a 

naturalized part of many redwood forest communities. Furthermore, P. ramorum is 

expected to establish throughout the entire redwood range within the next 20 to 30 

years (Meentemeyer et al. 2011). Understanding how the pathogen has altered 

redwood ecosystem processes is essential to assessing the costs and benefits of 

disease management. However, almost no published studies have reported baseline 

rates of ecosystem processes for redwood forests. How substantial are P. ramorum

impacts on redwood ecosystem processes? What mechanisms are responsible for 

ecosystem change in these forests? We conducted a series of field studies quantifying 

soil N cycling, litterfall, and litter decomposition to begin addressing these questions. 

The objective of this paper is to report baseline rates of nutrient cycling for redwood 

forests and summarize the overall affects of sudden oak death on these processes.

Study design

We quantified litterfall dynamics in two second-growth redwood forests in 

Sonoma and Marin Counties, Jack London State Park and the Marin Municipal Water 

District respectively. At each site, 30 circular 500 m2

 plots were established in 2002 

to study the influence of community composition on pathogen establishment and 

disease progression (Maloney et al. 2005). We selected a subset of 15 plots at each 

site which spanned a range of tanoak biomass and pathogen prevalence. We 

examined plots across a range of disease impacts with the expectation that increasing 

mortality will lead to greater impacts to ecosystem processes. Litter traps were 

collected every 6 to 12 weeks from 2007 to 2009. Soil N cycling was quantified in 

situ using open-top, intact soil cores with incubation periods of 10 to 18 weeks. We 

made an additional measurement of species effects on soil N cycling at the Jack 

London site by collecting soils directly beneath individual redwood, tanoak, bay 

laurel, and P. ramorum killed tanoak. These soils were collected outside of our 

permanent study plots from the top 20 cm from eight locations at cardinal directions 

around each tree. All soils were returned to the laboratory on ice, sieved to pass a 2 

mm mesh screen and extracted with 1N KCL within 48 hours of collection. Litter 

decomposition of redwood, bay laurel, and tanoak litter was measured over 2 years 

with 1 mm mesh bags. 
Decomposition and N Cycling Changes in Redwood Forests Caused by Sudden Oak Death 

359

Results

Litterfall amounts were variable across seasons and among species. Monthly 

amounts of tanoak and bay laurel litterfall tended to peak in midsummer while 

redwood litterfall was greatest in late fall and early winter. Tanoak litterfall was the 

most consistent across seasons but reached the maximum (~100 kg ha-1 month-1) in 

May and June. Bay laurel litterfall peaked at ~50 kg ha-1 in August. Redwood 

contributes the greatest mass to litterfall in these forests with maximum amounts of 

~800 kg ha-1 in December. Cumulative tanoak mortality was associated with lower 

tanoak litterfall mass.

Soil N cycling rates were within the range of other coniferous forests (fig. 1) and 

N pools and N mineralization were frequently dominated by NO3-N. Mineralization 

rates in the field were an order of magnitude higher than rates measured in the 

laboratory (fig. 1) which may be a function of moisture availability. The open-top 

cores used in field incubations allow moisture to reach microbes and maintain 

mineralization processes while in the laboratory, we used field moist soils and did not 

add any additional water. N 

μg g

-1

0.00

0.25

0.50

0.75

1.00

1.25

1.50 NO3-N 

Total-N 

Nitrification 

N Mineralization

Laboratory

Field 2008

Field 2009

Proprotion NO

3-N

0.0

0.2

0.4

0.6

0.8 Extractable

Turnover

Figure 1—Extractable N and N turnover rates (top) and the proportion of NO3-N in 

extractable N and N turnover (Bottom). Data are from a 5-week measurement of 

field-moist soils conducted in the laboratory at 22 o

C (laboratory) and average rates 

(μg N g-1 soil d-1) or amounts (μg N g-1 soil) from 2 years of measurements in the 

field. All data are means.

Litter decomposition was most rapid in bay laurel, slowest in redwood, and 

intermediate for tanoak. Litter decomposition rates were very low during summer 

months and increased during the wet season between October and May. Bay laurel 
GENERAL TECHNICAL REPORT PSW-GTR-238 

360

consistently had the lowest mass remaining and was about 15 percent lower than 

tanoak and 30 lower than redwood. 

Discussion

Phytophthora ramorum and the subsequent disease sudden oak death have 

impacted redwood forests throughout the central and southern range of this forest 

type (Meentemeyer et al. 2008, Ramage et al. 2011, Rizzo et al. 2005). In our study 

sites, tanoak mortality decreased tanoak litterfall mass and increased the availability 

of NO3-N. Changes to NO3-N availability were modest, but tanoak litterfall is rapidly 

reduced by disease. Tanoak rapidly develops basal sprouts following mortality of 

above ground biomass (Cobb et al. 2010, Ramage et al. 2011) which maintains 

tanoak as part of redwood forest litterfall even after substantial mortality has 

occurred. Although tanoak will remain as a component of redwood litterfall for 

several years following disease outbreak, the amounts of litterfall from tanoak will be 

much lower relative to redwood forests not invaded by P. ramorum. 

Changes in species composition are likely to have the most long-lasting and the 

greatest magnitude of effect on ecosystem processes following the emergence of 

sudden oak death within stands. Although bay laurel accounts for a relatively small 

proportion of litterfall in redwood ecosystems, it has the highest N concentration of 

all species in these forests. Redwood has the lowest N concentration and tanoak was 

intermediate between the two species. These patterns suggest that redwood forest 

litter decomposition rates will either increase or decrease depending on whether bay 

laurel, redwood, or other species are able to exploit resources made available by 

tanoak mortality. Species shifts have been responsible for pronounced and longlasting ecosystem changes following other major outbreaks (Cobb 2010b, Paillet 

2002) which highlights the importance of understanding changes in species 

composition following outbreak of sudden oak death (e.g., Cobb et al. 2010, Maloney 

et al. 2006, Ramage et al. 2011). It is unclear how species composition will change 

over longer time scales in P. ramorum invaded redwood forests. However, shifts in 

species composition will likely have the greatest magnitude and longest-lasting 

impacts on the ecosystem processes focused on by this study. 

Identifying management goals is the most important step to assessing the need 

for disease management in redwood forests. While redwood is not directly threatened 

by P. ramorum (infection does not cause mortality in redwood), increased fire 

impacts and fire severity in some P. ramorum invaded forests may justify fuel 

reduction treatments (see Metz et al. 2011). Preemptive management is also likely to 

be most effective in retaining overstory tanoak and the unique flora and fauna 

associated with this tree (Cobb 2010a). For disease treatments to be effective in 

retaining overstory tanoak it will often be necessary to remove bay laurel and reduce 

the overall density of tanoak such as through the removal of small tanoak stems. 

Treatments will be most effective when they are designed or associated with 

management to increase the growth of redwood which may in turn lead to 

suppression of regeneration from sporulation supporting species like bay laurel and 

tanoak. Preventative treatments would be similar to many current silvicultural 

prescriptions to reduce tanoak competition with redwood but would require 

modifications that intentionally retain and protect individual tanoak with highbiodiversity value. By shifting species composition to a greater dominance of 
Decomposition and N Cycling Changes in Redwood Forests Caused by Sudden Oak Death 

361

redwood, ecosystem processes will also reflect characteristics typical of redwood 

ecosystems; specifically, slower litter decomposition rates, increased above ground 

biomass, and possibly increased soil C storage. However, the metric of success for 

these treatments should be based on their effectiveness in retaining unique 

biodiversity associated with tanoak. Lack of action is likely to increase the 

importance of bay laurel in many stands and this will shift ecosystem processes 

towards overall rates of N cycling, litter decomposition, and above ground biomass 

dynamics that reflect the autecology of bay laurel. For the individual manager facing 

the emergence of sudden oak death, the costs of these disease impacts must be 

weighted in the light of their overall goals to determine appropriate management 

actions.

Acknowledgments

We thank H. Mehl, S. Lynch, A. Westbrook, F. Fogel and C. Shoemaker for their 

field and laboratory support of this research. We thank M. Metz, E. Fichtner, and V. 

Eviner for helpful comments on the design of the study and analysis of the data. 

Additionally, we are grateful to the California State Parks and the Marin Municipal 

Water District for facilitating this research on their lands. This research was funded 

by the NSF-NIH Ecology of Infectious Diseases program EF-0622770, the Gordon 

and Betty Moore Foundation, the USDA Forest Service Pacific Southwest Research 

Station, and an Ernest E. Hill Climate Change Fellowship to RCC. 

References

Cobb, R.C. 2010a. Mechanisms of community change and impacts on functional 

processes by the generalist pathogen Phytophthora ramorum in California coast 

redwood forests. University of California Davis. Dissertation.

Cobb, R.C. 2010b. Species shifts drive decomposition rates following invasion by 

hemlock woolly adelgid. Oikos 119: 1291-1298.

Cobb, R.C; Orwig, D.A. 2008. Changes in decomposition rates and dynamics in hemlock 

forests impacted by hemlock woolly adelgid: restoration and conservation of 

ecosystem function in southern New England. In: Souto, D.; Onken, B.P., editors.

Symposium on the hemlock woolly adelgid in eastern North America. Gen. Tech. Rep. 

FHTET-2008-01. Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Forest 

Health Protection: 157-168.

Cobb, R.C.; Currie, S.C.; Orwig, D.A. 2006. Decomposition of green foliage in eastern 

hemlock forests of southern New England impacted by hemlock woolly adelgid 

infestations. Canadian Journal of Forest Research 36: 1331-1341.

Cobb, R.C.; Meentemeyer, R.K.; Rizzo, D.M. 2010. Apparent competition in canopy trees 

determined by pathogen transmission rather than susceptibility. Ecology 91: 327-333.

Davidson, J.M.; Patterson, H.; Rizzo, D.M. 2008. Sources of inoculum for Phytophthora

ramorum in a redwood forest. Phytopathology 98: 860-866.

Davidson, J.M.; Patterson, H.A.; Wickland, A.C.; Fichtner, E.J.; Rizzo, D.M. 2011. Forest 

type influences transmission of Phytophthora ramorum in California oak woodlands.

Phytopathology 101: 492-501.
GENERAL TECHNICAL REPORT PSW-GTR-238 

362

Eviner, V.T.; Likens, G.E. 2008. Effects of pathogens on terrestrial ecosystem function. In: 

Ostfeld, R.S.; Keesing, F.; Eviner, V.T., editors. Infectious disease ecology. Princeton, 

N.J.: Princeton University Press.

Lamsal, S.; Cobb, R.C; Cushman, H.; Meng, Q.; Rizzo, D.M.; Meentemeyer, R.K. 2011. 

Spatial estimation of the density and carbon content of host populations for 

Phytophthora ramorum in California and Oregon. Forest Ecology and Management 

262(6): 989-998.

Lovett, G.M.; Canham, C.D.; Arthur, M.A.; Weathers K.C.; Fitzhugh, R.D. 2006. Forest 

ecosystem responses to exotic pests and pathogens in eastern North America.

BioScience 56: 395-405.

Maloney, P.E.; Lynch, S.; Kane, S.; Jensen, C.E.; Rizzo, D.M. 2005. Establishment of an 

emerging generalist pathogen in redwood forest communities. Journal of Ecology 93: 

899-905.

Meentemeyer, R.K.; Anacker, B.L.; Mark, W; Rizzo, D.M. 2008. Early detection of 

emerging forest disease using dispersal estimation and ecological niche modeling.

Ecological Applications 18: 377-390.

Meentemeyer, R.K.; Cunniffe, N.J.; Cook, A.R.; Filipe, J.A.N.; Hunter, R.D;, Rizzo, D.M.; 

Gilligan, C.A. 2011. Epidemiological modeling of invasion in heterogeneous 

landscapes, spread of sudden oak death in California (1990-2030). Ecosphere 2: art17.

Metz, M.R.; Frangioso, K.M.; Meentemeyer, R.K; Rizzo, D.M. 2011. Interacting 

disturbances, wildfire severity affected by stage of forest disease invasion. Ecological 

Applications 21: 313-320.

Orwig, D.A.; Cobb, R.C.; D’Amato, A.W.; Kizlinski, M.L.; Foster, D.R. 2008. Ecosystem 

response to forest infestation by hemlock woolly adelgid. Canadian Journal of Forest 

Research 38: 834-843.

Paillet, F.L. 2002. Chestnut, history and ecology of a transformed species. Journal of 

Biogeography 29: 1517-1530.

Ramage, B.S.; O’Hara, K.L.; Forrestel, A.B. 2011. Forest transformation resulting from an 

exotic pathogen: regeneration and tanoak mortality in coast redwood stands affected 

by sudden oak death. Canadian Journal of Forest Research 41: 763-772.

Rizzo, D.M.; Garbelotto, M.; Hansen, E.M. 2005. Phytophthora ramorum, integrative 

research and management of an emerging pathogen in California and Oregon 

forests. Annual Review of Phytopathology 43: 309-335. 
363

Post-fire Response of Coast Redwood One 

Year After the Mendocino Lightning 

Complex Fires

Robert B. Douglas1 and Tom Bendure1

Abstract

Coast redwood (Sequoia sempervirens) forests have undergone significant changes over the 

past century and are now in state more conducive for wildfires. Because fires have been 

uncommon in redwood forests over the past 80 years, managers have limited data to make 

decisions about the post-fire environment. In June 2008, a series of lightning storms moved 

through northern California igniting numerous fires throughout the redwood region of 

Mendocino County. Here, we collected fire-injury data on 1024 redwood trees on commercial 

timberlands three months after the fire and quantified mortality and biological responses one 

year later. Although over half the sampled trees had at least 90 percent of their crowns 

scorched, only 18.2 percent were completely top-killed after one year; and 87.7 percent of this 

mortality was confined to trees less than 20.3 cm in diameter. Over 80 percent of the trees 

regenerated leaves and shoots from axillary buds, and a similar percentage resprouted basally. 

Logistic regression modeling indicated that diameter at breast height (DBH), cambium kill, 

and percent crown scorch were significant predictors of tree mortality. These results indicate 

that although small redwoods are predicted to have the highest mortality, their ability to 

resprout may obviate the need for replanting in areas where redwood is dominant. The 

management implications for the larger surviving trees are less clear and require further longterm study to examine delayed mortality, growth rates, and wood quality.

Key words: basal sprouting, fire injury, mortality, redwood, Sequoia, wildfire

Introduction

The fire ecology of coast redwood (Sequoia sempervirens) continues to be an 

area of active inquiry. Over the past century, timber harvesting, fire suppression, and 

human encroachment have substantially altered the environmental context of coast 

redwood (Sawyer et al. 2000, Scanlon 2007). A major concern in many western 

forests is that increased woody debris, along with younger and denser forests, and a 

drier regional climate will lead to higher fire frequency and more catastrophic 

wildfires (Stephens et al. 2009). Conditions within many redwood forests throughout 

the region have changed substantially in recent decades and are now reaching states 

more conducive for wildfires. 

Historically, large wildfires have been uncommon in coast redwood forests 

because of reduced ignitions and suppression policies of the past 80 years (Scanlon 

2007). The lack of fire in redwood forests has resulted in a significant information 

gap regarding the effects fire on this species. Currently, managers have limited data 

to make decisions about harvest in the post-fire environment (Finney and Martin 

1993, Ramage et al. 2010). In fact, there are no quantitative data on fire injury 

 

1 Mendocino Redwood Company (rdouglas@mendoco.com). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

364

characteristics and the post-fire response of coast redwood on second- and thirdgrowth growth commercial forestlands. 

On 20 and 21 June 2008, a series of lightning storms moved through Mendocino 

County during a second-year of drought igniting 129 fires and burning 22,193 ha 

(54,817 ac) over a four-week period in what became known as the Mendocino 

Lightning Complex (MLC). Approximately, 42.3 percent of the burned area 

encompassed a single forest landowner. This unprecedented event provided an 

opportunity to examine the relationship between fire-injury characteristics and the 

response of redwood on forestlands over a 5-year period. 

We present preliminary results on the response of coast redwood 1 year after the 

MLC fires. Specifically, our objectives were to: 1) quantify the biological response; 

2) model fire-injury characteristics and tree mortality; and 3) use these data to 

develop future management guidelines.

Methods

Study area 

Sampling sites were located in the North Coast physiographic province of 

Mendocino County, California and consisted of second- and third-growth coast 

redwood forests owned and managed by Mendocino Redwood Company for 

commercial timber production. These forestlands are primarily dominated by coast 

redwood, Douglas-fir (Pseudotsuga menziesii), and tanoak (Notholithocarpus

densiflorus), and a small percentage of other hardwood and conifer species. 

Sampling 

During September 2008 we established permanent plots across four separate fire 

areas of the MLC. Within each fire we selected plot locations from fire severity maps 

based on landscape-level crown scorch indices obtained from satellite imagery. Plots 

(17.8 m (0.1 ha) radius) were installed until ~250 redwood trees ≥ 9.9 cm (3.9 in) 

diameter at breast height (DBH) were measured for each fire. Adjustments to the plot 

centers were made to maximize the number of redwood trees in each plot and cover a 

range of tree sizes and crown scorch percentages. In each plot trees were painted and 

tagged to facilitate monitoring in subsequent years. 

Tree and fire-injury measurements

We measured tree DBH with a diameter tape (at 1.37 m above ground); total tree 

height and pre-fire height-to-crown base (HTCB) with a hypsometer. Fire-injury 

metrics such a percent volume crown scorched (PVCS) were visually estimated using 

a double-observer method until calibration was within 5 to 10 percent of each other. 

Crown scorch height (CSHT), maximum char height (CHHTMX), and minimum 

char height (CHTHMN) were measured with a hypsometer. Bark char was assessed 

by dividing tree circumference into four quadrants based on cardinal directions and 

visually classifying char severity within the first 30 cm above ground. Each quadrant 

was given a score (0=none; 1=low; 2=moderate; 3=severe) and all quadrant scores 

were summed to provide an overall score ranging from 0 to 12. Cambium kill was 

assessed by dividing the base of the tree into quadrants (similar to the bark char 

assessment). In the center of each quadrant, a cordless drill (with a 1.9 cm wide bit) 
Post-fire Response of Coast Redwood One Year After the Mendocino Lightning Complex Fires

365

was used to access the cambium below the bark to score (0=live; 1=dead). A 

cambium kill rating was calculated by summing all of the quadrant scores for an 

overall score ranging from 0 to 4. 

Biological response measurements 

During the fall of 2009 all fire plots were revisited to evaluate tree status (live or 

dead) and measure specific biological responses. Percentages of live and dead crown 

were measured visually, and the percentage of bole sprouting was measured as a 

proportion of total tree height. Bole sprouting was considered a distinct form of 

regeneration so it was separated from the live crown measurement, which was further 

divided into residual canopy (unburned) and regenerating canopy (limb sprouting). 

Basal sprouts were assigned to parent trees based on proximity, and the total number 

of sprouts was tallied and the tallest sprout in each group was measured with a height 

pole. 

Statistical analysis 

We calculated means and standard errors to illustrate measures of central 

tendency and variation, respectively. Most of the tree and fire-injury data deviated 

from the assumptions of parametric statistics, so we used the non-parametric 

Wilcoxon rank-sum test to compare means between groups.

We used logistic regression to develop a statistical model of tree mortality based 

on several combinations of tree and fire-injury variables (bole injury and crown 

scorch). Variables were evaluated for collinearity prior to inclusion in logistic 

regression models. Model fit was assessed using the χ2

 goodness-of-fit test and the 

discriminatory ability of each model was evaluated using the Receiver Operating 

Characteristic (ROC). All statistics were analyzed with the program Stata version 

11.1 and statistical significance was set at α=0.05.

Results

A total of 1024 trees were measured across a total of 29 plots (6 to 9 plots 

sampled per fire). Tree size distribution followed a reverse J-shape distribution, with 

over 72.8 percent of the trees occurring in the two smallest size classes, and the 

remaining trees distributed among the merchantable size classes (> 40.6 cm DBH) in 

descending order of increasing size. One year after the MLC fires, 187 redwood trees 

(18.2 percent of all trees measured) were observed to be dead (defined as a 

completely top-killed primary stem). All top-killed trees were in the two smallest size 

classes, 164 (87.7 percent) of which were in the smallest size class (9.9 to 20.3 cm 

DBH). 

Comparisons of tree characteristics showed that live trees were, on average, 

nearly twice as large (in diameter and total height) as dead trees. Dead trees, on 

average, exhibited significantly higher levels of crown scorch, bole char proportion, 

bark charring, and cambium kill compared to live trees (table 1). 

Crown regeneration for 837 live trees exhibited a pattern of increasing mean 

percentage of live crown and a decreasing mean percentage of bole sprouting in 

progressively larger size classes of trees (data not shown). Only 318 (37.9 percent) 

live trees exhibited sprouting on greater than 5 percent of the bole, usually confined 
GENERAL TECHNICAL REPORT PSW-GTR-238 

366

Table 1—Mean tree and fire injury characteristics for 1024 redwood trees sampled

with standard errors and ranges shown.

Variablesa Total Mean 

(n=1024)

Live Mean 

(n=837)

Dead Mean 

(n=187)

DBH (cm) 31.9 (0.68) 35.6 (0.78) 15.3 (0.35)b

9.9-151.9 9.9-151.9 9.9-33.8

TLHT (m) 19.5 (0.33) 21.4 (0.37) 11.1 (0.29)b

3.7-55.5 4.6-55.5 3.7-26.8

HTCB (m) 8.7 (0.22) 9.5 (0.23) 5.2 (0.19)b

1.2-36.0 1.5-36.0 1.2-18.6

CSHT (m) 14.1 (0.27) 14.9 (0.32) 10.8 (0.28)b

0-48.2 0-48.2 3.7-26.8

PRCS (%) 69.7 (1.15) 63.7 (1.31) 96.3 (0.85)b

0-100 0-100 10-100

CHHTMX (m) 5.5 (0.14) 5.7 (0.16) 4.8 (0.20)

0-28.0 0-28.0 0-19.8

CHHTMN (m) 2.8 (0.10) 2.7 (0.11) 3.1 (0.20)b

0-27.1 0-27.1 0-19.8

PRCHMX (%) 30.4 (0.64) 27.1 (0.61) 45.6 (1.83)b

0-100 0-100 0-100

BCR 8.5 (0.06) 8.3 (0.06) 9.4 (0.15)b

0-12 0-12 0-12

CKR 0.9 (0.04) 0.6 (0.04) 2.2 (0.11)b

0-4 0-4 0-4 a DBH = diameter at breast height; TLHT = tree height; HTCB = Pre-fire height-to-crown base; CSHT = 

crown scorch height; PRCS = crown scorch; CHHTMX = maximum bole char height; CHHTMN = 

minimum bole char height; PRCHMX = bole char proportion; BCR = bark char rating; CKR = cambium 

kill rating

b Significantly different from live trees (P<0.05)

to trees with a greater percentage of fire-injury, particularly those with dead tops and 

higher percentages of dead crowns. Mean percentage of limb sprouting increased 

with larger size classes indicating lower levels of canopy injury with increasing tree 

height. 

Basal sprouting was associated with a total of 822 out of 1024 trees (80.2 

percent). Sprouts were associated with 654 of 837 live trees (78.1 percent) and 168 of 

187 dead trees (89.8 percent). Basal sprouting patterns showed significant differences 

in both sprout number and maximum sprout height between live and dead trees (table 

2). 

Logistic regression modeling yielded five significant models consisting of twoand three-variable combinations, all of which had excellent model fit and 

discriminatory ability in predicting live and dead trees based on fire-injury (table 3; 

ROC values ≥0.8). The best model contained DBH, PRCS, and CKR as significant 

predictors of mortality. Alternative models with different measures of bole damage 

(BCR and PRCHMX) were also significant, but ranked lower than the three-variable 

model with CKR. DBH was the single-most important variable in determining 

probability of mortality, followed by measures of bole damage, and PRCS. 
Post-fire Response of Coast Redwood One Year After the Mendocino Lightning Complex Fires

367

Table 2—Mean maximum height and mean total number of basal sprouts by size 

class, live and dead trees. Standard errors () and ranges shown.

Live Dead

DBH 

Class (cm)

Mean Max 

Height (m)

Mean No. 

of Sprouts N

Mean Max 

Height (m)

Mean No. 

of Sprouts N

9.9-20.3 0.96 (0.04) 5.3 (0.30) 228 1.31 (0.05)b 7.7 (0.47)b 151

0.10-3.00 1-28 0.15-3.00 1-40

20.3-40.6 0.97 (0.04) 5.8 (0.34) 234 1.39 (0.19) 6.1 (1.26) 17

0.05-3.30 1-30 0.30-3.00 1-20

40.6-60.9 0.94(0.05) 7.1 (0.63) 128 NA NA NA

0.15-2.50 1-50

60.9-81.2 0.99 (0.10) 5.2 (0.60) 43 NA NA NA

0.15-2.50 1-16

> 81.2 0.99 (0.13) 7.2 (1.00) 21 NA NA NA

0.15-2.10 1-17

All Size 

Classes

0.96 (0.02) 5.9 (0.21) 654 1.32 (0.05) b 7.6 (0.44) b 168

0.05-3.30 1-50 0.15-3.00 1-40 b Significantly different from live trees (P<0.05)

Table 3—Top five mortality models for coast redwood one year post-fire. Model 1 is 

the best overall model.

Model 

Rank Intercept DBH PRCS CKR BCR PRCHMX ROC

1 -1.5039 -0.1698 0.0305 0.5425 - - 0.912

2 -4.4398 -0.1989 0.0427 - 0.3541 - 0.909

3 -1.9276 -0.1743 0.0349 - - 0.0253 0.904

4 1.2200 -0.1786 - 0.6690 - - 0.902

5 -1.8892 -0.1797 0.0454 - - - 0.893

Probability of mortality for the most significantly burned trees (PRCS ≥80, CKR =4) 

was high (>0.7) for trees 13.0 cm (5.11 in) DBH or less (fig. 1). As DBH increases, 

probability of mortality declines, nearly reaching zero (survival probability of 1) for 

trees with a DBH of 46.0 cm (18 in). We did not observe any mortality in trees 

greater than 33.8 cm (13.3 in) DBH. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

368

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 10 20 30 40 50 60

Diameter at Breast Height (cm)

P

r

o

b

a

b

l

i

t

y

o

f

M

o

r

t

a

l

i

t

y

Pr(X), PRCS= 80, CKR=0

Pr(X), PRCS= 80, CKR=1

Pr(X), PRCS= 80, CKR=2

Pr(X), PRCS= 80, CKR=3

Pr(X), PRCS= 80, CKR=4

Figure 1—Probability of mortality based on DBH for trees with 80 percent 

crown scorch (PRCS) at all levels of cambium kill (CKR).

Discussion

The ability of coast redwood to resist fire and other disturbances has been 

documented in several observational accounts (Abbot 1987, Fritz 1932). Our study is 

the first to provide quantitative measures of fire-injury and biological response of 

second- and third-growth redwoods, and possibly, for one of the largest wildfire 

complexes (by area burned) in the redwood region in over 70 years (Scanlon 2007). 

Our initial concern regarding the MLC fires was that a landscape comprised of young 

coast redwood combined with moderate to severe fires might result in significant 

mortality of merchantable size classes (> 40.6 cm), with even greater concerns about 

decreases in growth and development of defects. 

Mortality of merchantable sized trees was not observed in any of the plots one 

year following the MLC fires. Mortality was confined to the two smallest size 

classes, which is not surprising given that fire typically moves from the ground up 

and tends to impact smaller trees. Finney and Martin (1993) also observed mortality 

in the same size classes but for prescribed fires of differing intensities. Interestingly, 

they did not observe any mortality in trees larger than 32.4 cm (12.7 in) DBH, which 

was close to our maximum mortality size of 33.8 cm (13.3 in) DBH. However, a 

substantial portion of their sampling distribution included trees < 9.9 cm DBH 

whereas ours did not (Finney, pers. comm.). This sampling difference is an important 

distinction because mortality of trees < 9.9 cm DBH was disproportionate compared 

to larger DBH trees in their study. Although we did not directly measure trees this 

small, > 90 percent of these trees were observed dead in all plot-level tallies across 

our study sites. 

Coast redwood exhibited both resistance and system resilience to fire across all 

plots. Despite having sustained significant crown and bole injuries, nearly 75 percent 
Post-fire Response of Coast Redwood One Year After the Mendocino Lightning Complex Fires

369

of the trees ≤ 40.6 cm (16 in) DBH were still alive and were regenerating new crowns 

from epicormic sprouts. The incidence and extent of bole sprouting was greater in 

small trees because the original crown and dormant buds along their limbs were 

severely damaged or killed. Higher levels of limb sprouting were also seen in larger 

trees whose buds were located sufficiently above convective heat currents to avoid 

lethal temperatures. Basal sprouting occurred around all size classes of trees and was 

most vigorous around dead trees. Thus, already established redwood stands that 

experience significant fire, including those comprised of juvenile-sized trees, are 

likely to maintain site dominance into the future without the need for replanting. 

Furthermore, coppicing severely damaged young trees may further enhance sprout 

development and regeneration time. 

Our logistic regression modeling supports previous observations that tree size 

(DBH) and different measures of fire injury are important factors in predicting 

mortality of coast redwood (Finney and Martin 1993, Ramage et al. 2010). Based on 

our best model, trees exceeding 46 cm DBH are predicted to have nearly 100 percent 

survival probability regardless of fire injury. However, as tree DBH becomes 

progressively smaller, fire injury becomes a more important determinant of survival 

probability. This concurs with plot-level bole survival data recently published by 

Ramage et al. (2010) for second- and old-growth redwood stands. Mortality models 

for prescribed fire also illustrate a similar effect of DBH on survival probability 

(Finney and Martin 1993). 

The utility of the cambium kill metric in mortality models following wildfire has 

been reported by others but not for coast redwood (Hood et al. 2007). Measures of 

cambium kill significantly improved mortality predictions for trees ≤ 20.3 cm DBH 

with high levels of crown scorch. However, assessing cambium is labor intensive so 

alternative measures of bole injury (BCSUM and PRCHMX) may be preferable for 

field application. Previous research has shown that cambial damage is associated 

with fuel loading and fire behavior immediately surrounding individual trees (Ryan 

and Frandsen 1991). Although we did not have any pre-fire fuels data for our plots, 

we hypothesize that cambial damage was not only influenced by accumulated litter 

and woody debris, but also by the clumped distribution of regenerating trees 

surrounding remnant parent stumps that continued to burn and emit radiant heat long 

after the fire passed through. This latter hypothesis is supported by our observation, 

as well as others in the redwood region (Finney and Martin 1993), that many of the 

stump-facing sides of coppice-generated trees proximal to burned stumps had 

severely burned bark and dead cambium. 

Although PVCS was significant in the model, its ability to improve prediction 

was not as significant as CKR and other measures of bole damage. The ability of 

coast redwood to readily resprout from aerial buds may explain the lesser importance 

of this variable when compared to mortality models developed for other nonsprouting tree species. Nonetheless, PVCS along with measures of bole injury are 

important metrics of fire severity as they may capture physical and behavioral aspects 

of the fire that are spatially distinct and driven by multiple factors such as fuel 

loading, topography, adjacent vegetation, and weather conditions. 

The high regenerative capacity of coast redwood to wildfire is problematic for 

modeling mortality. First, categorizing responses into discrete groups (dead or alive) 

potentially results in significant loss of information that might be better represented 

along a continuum. For example, 40.7 percent of live trees (341 of 837) had dead 
GENERAL TECHNICAL REPORT PSW-GTR-238 

370

crowns of 50 percent or greater and varying amounts of cambium mortality, yet were 

grouped with live trees having significantly less or no damage. Such trees, if retained 

to grow for several decades, may exhibit reduced growth rates, have poor wood 

quality, and many defects. Uncertainty regarding the long-term effects of wildfire on 

redwood highlights a need to better define what characteristics constitute damage 

because using the likelihood of mortality as a standard for harvest may be 

inappropriate for this species.

Conclusions

Redwood exhibited considerable resistance and resilience to wildfire even on a 

landscape that has been significantly altered by over a century of commercial timber 

harvesting and several decades of fire exclusion. Overall, the fires of 2008 were an 

admonition that conditions conducive for wildfire exist on many landscapes 

throughout the redwood region. While many of the fires on our forestlands caused 

significant damage to young stands of redwood and other more fire-sensitive conifer 

species, at least 50 percent of the fires had minimal impact on the forests as they 

behaved like a prescribed fire. Given the state of our forests, this observation 

underscores the importance of reintroducing fire as a tool to reduce wildfire risk in 

many areas on large forested landscapes within the redwood region. Although our 

understanding of the short-term responses of coast redwood to wildfire fire is greatly 

enhanced by this research, further study is necessary to test many of our assumptions 

how wildfire affects coast redwood over a longer period of time. Annual monitoring 

of our permanent plots in these fire areas will continue into the future and is 

necessary to answer questions regarding delayed mortality, reduced growth rates, 

increased pathogen susceptibility, wood quality, and generation time for wildlife 

habitat. 

References

Abbott, L.L. 1987. The effect of fire on subsequent growth of surviving trees in an old 

growth redwood forest in Redwood National Park, CA. Arcata, CA: Humboldt State 

University. Master’s thesis.

Finney, M.A.; Martin, R.E. 1993. Modeling effects of prescribed fire on young-growth 

coast redwood trees. Canadian Journal of Forest Research 23: 1125-1135.

Fritz, E. 1932. The role of fire in the redwood region. Journal of Forestry 29: 939-950.

Hood, S.; Bentz, B. 2007. Predicting postfire Douglas-fir beetle attacks and tree mortality 

in the northern Rocky Mountains. Canadian Journal of Forest Research 37: 1058-

1069.

Ramage, B.S.; O’Hara, K.L.; Caldwell, B.T. 2010. The role of fire in the competitive 

dynamics of coast redwood forests. Ecosphere 1: 1-18.

Ryan, K.C.; Frandsen, W.H. 1991. Basal injury from smoldering fires in mature Pinus

ponderosa. International Journal of Wildland Fire 1: 107-118.

Sawyer, J.O.; Gray, J.; West, G.J.; Thornburgh, D.A.; Noss, R.F.; Engbeck, J.G. Jr.; Marcot, 

B.G.; Raymond, R. 2000. History of redwood and redwood forests, Chapter 2. In: 

Noss, R.F., editor. The redwood forest. Covelo, CA: Island Press. 339 p.

Scanlon, H. 2007. Progression and behavior of the Canoe Fire in coast redwood. In: 

Standiford, R.B.; Giusti, G.A.; Valachovic, Y.; Zielinski, W.J.; Furniss, M.J., editors. 
Post-fire Response of Coast Redwood One Year After the Mendocino Lightning Complex Fires

371

Proceedings of the redwood region forest science symposium: What does the future 

hold? Gen. Tech. Rep. PSW-GTR-194. Albany, CA: U.S. Department of Agriculture, 

Forest Service. Pacific Southwest Research Station: 223-231.

Stephens, S.L.; Moghaddas, J.J.; Edminster, C.; Fiedler, C.E.; Haase, S.; Harrington, M.; 

Keeley, J.E.; Knapp, E.E.; McIver, J.D.; Metlen, K.; Skinner, C.N.; Youngblood, A. 

2009. Fire treatment effects on vegetation structure, fuels, and potential fire 

severity in western U.S. forests. Ecological Applications 19: 305-320.

373

The Effects of Sudden Oak Death and 

Wildfire on Forest Composition and 

Dynamics in the Big Sur Ecoregion of 

Coastal California

Margaret R. Metz,1,2 Kerri M. Frangioso,1 Ross K. Meentemeyer,

3

and David M. Rizzo1

Introduction

Sudden oak death (SOD), caused by Phytophthora ramorum, is an emerging forest 

disease associated with extensive tree mortality in coastal California forests (Rizzo et al. 

2005). P. ramorum is a generalist pathogen that infects many hosts, but hosts differ in their 

ability to transmit the disease and in the impacts caused by the disease. In coast redwood 

forests, tanoak (Notholithocarpus densiflorus) is the main host dying from SOD and the main 

source of pathogen inoculum. SOD leads to compositional changes in these habitats through 

selective mortality of tanoak. 

The effect of SOD on forest dynamics does not happen in isolation from other 

disturbances. Rather, fire is an important part of the natural disturbance regime in California’s 

coastal forests. Elevated mortality by the disease may lead to increased fuel loads in these 

forests, leading to the potential for SOD to interact with wildfire severity (Valachovic et al. 

2011). In 2008, wildfires in SOD-impacted forests presented a natural experiment to examine 

the interaction between these two disturbances (Metz et al. 2011).

We used a long-term network of forest monitoring plots in the Big Sur region of central 

California to examine the separate and joint impacts of an emergent forest disease and 

wildfire on forest dynamics and diversity. The network contains burned and unburned areas, 

and areas with and without P. ramorum. Specifically, we asked: 1) Did redwood stands that 

became infested by P. ramorum differ in species composition from uninfested areas? 2) How 

is P. ramorum changing species composition in redwood forests? 3) How did mortality from 

SOD impact fire severity in burned areas? 4) Was fire mortality selective by species? 

Methods

The Big Sur region represents the southern limit of the ranges of both SOD and 

the coast redwood. Big Sur forests were a relatively early site of invasion by P. 

ramorum and are among the most impacted by the pathogen (Meentemeyer et al. 

2008). In Big Sur, the historical and current distribution patterns of redwood consists 

of scattered stands, primarily in wetter canyon areas near the coasts. The redwood 

habitat is usually found in close proximity to a variety of other habitat types, 

including oak woodlands, chaparral, or grasslands, leading to a very heterogeneous 

matrix of habitat types. Forest and disease dynamics in this landscape can therefore 

differ dramatically from what is observed further north in the ranges of redwoods and 

 

1 Department of Plant Pathology, 1 Shields Ave., University of California, Davis, CA 95616. 2 Corresponding author: mrmetz@ucdavis.edu. 3 Department of Geography and Earth Sciences, University of North Carolina, Charlotte, NC 28223.
GENERAL TECHNICAL REPORT PSW-GTR-238 

374

P. ramorum, where the climate is cooler and wetter and redwood stands exist in 

much larger swaths.

We established a network of 280 monitoring plots throughout the Big Sur 

ecoregion in coastal California in 2006 and 2007 to examine the impacts of SOD on 

forest dynamics. These plots were located in two habitat types, mixed-evergreen 

forests (n=164) and redwood-tanoak forests (n=116). Within each plot, we marked, 

measured, and assessed for pathogen symptoms and health every live or dead stem 

≥1 cm DBH. We also quantified the volume of large coarse woody debris, and the 

vegetation cover of all herbs, shrubs and trees. Here, we present results based on the 

116 redwood-tanoak plots. We used live basal area to represent current plot 

composition or species abundance during a given census. Total basal area, calculated 

by summing the basal area of live and dead standing stems, was used to re-construct 

pre-epidemic stand conditions, without considering disease-related or other mortality.

Two wildfires in 2008 (the Basin Complex and the Chalk fire) burned over a 

third of this network, providing the opportunity to compare forest dynamics in 

uninfested and infested areas, both within and outside burned areas, using pre-fire 

data on fuel availability and disease impacts and post-fire data on burn severity and 

tree mortality. Standing dead basal area and the volume of downed logs were used as 

measures of large woody fuel abundance prior to the fire. We conducted a survey of 

burn severity in 2008 (Metz et al. 2011), using the Composite Burn Index, and 

surveyed for tree mortality in 2009. 

Results

Of the 116 redwood plots, 70 were infested with P. ramorum in 2006 and 2007. 

There was a gradient among plots in dominance of tanoak or redwood, and some 

plots also contained another sporulating host, bay laurel. The species composition of 

infested plots differed significantly from that of uninfested stands. Stands that 

became infested had significantly greater total basal area (live and dead stems) of the 

sporulating hosts tanoak and bay laurel, and significantly lower abundance of 

redwood. At the same time, tanoak experienced far greater mortality in infested plots 

than in uninfested plots, and there was a trend towards lower mortality in bay and 

redwood in infested plots.

Infested plots had significantly greater abundance of standing dead snags and 

large surface fuels. However, burn severity did not vary according to pathogen 

presence alone, but rather with the abundance and type of fuels that occur at different 

stages of the disease progression (Metz et al. 2011). In areas with new SOD-caused 

mortality, where dead trees still retain a crown of dry, dead material, burn severity 

increased with increasing SOD impacts. Similarly, in areas where the disease had 

progressed further and surface fuels had accumulated, soil and substrate burn severity 

increased significantly with greater volume of host logs. However, the abundance of 

dead trees and logs were not significant predictors of burn severity across the entire 

network, when infested and uninfested areas were examined together. 

For trees that had been alive upon plot establishment in 2006 and 2007, the 

amount of basal area that was dead in 2009 was significantly higher in burned areas 

than unburned areas, regardless of the presence/absence of SOD. Outside of the 

burned areas, mortality was negligible except for canker hosts in infested areas, 
The Effects of Sudden Oak Death and Wildfire on Forest Composition and Dynamics in the Big Sur 

Ecoregion of Coastal California 

375

where mortality is increased by SOD. Within the burned area, fire-caused mortality

varied greatly among canker host species and non-host or foliar host species (which 

do not have lethal infections). Canker host mortality, primarily driven by tanoak 

mortality, was as high as 34 percent in burned, uninfested areas and 57 percent in 

burned, infested areas, on average, with great variation (difference between groups 

was nearly significant; t=-1.9669, df=36.98, p=0.057). Mortality of non-canker hosts 

(primarily redwoods, but also bay laurel) was much lower than for canker hosts. 

However, even non-canker host mortality was elevated in infested stands (16 percent) 

relative to uninfested stands (6 percent), indicating the potential for SOD mortality to 

worsen the effects of wildfire, although the difference was not significant (t=-1.6008, 

df=27.67, p=0.12). 

Discussion

Both sudden oak death and the 2008 wildfires have been altering the species 

composition in Big Sur redwood forests through selective mortality (Maloney et al. 

2005, Metz et al. 2011). Tanoak is dying in large numbers in areas infested with P. 

ramorum, and the 2008 wildfires caused greater mortality in canker hosts such as 

tanoaks relative to other dominant species in these stands (primarily redwoods). 

These changes in composition may lead to long-lasting impacts to forest diversity, 

dynamics, and structure in areas impacted by SOD in these fire-prone systems.

When trying to understand the impact of SOD on California’s coastal forests, it is 

very important to understand that P. ramorum is an important biotic disturbance that 

has been introduced into a system that already had a significant disturbance regime 

consisting primarily of periodic wildfires. Thus, the full impacts of either disturbance 

cannot be examined in isolation. The relationship between disease impacts and burn 

severity is not straightforward. Our surveys of tree mortality 1 year following the fire 

suggest that mortality of all species is higher in infested areas. 

We hypothesize that long-term forest composition will depend on the joint and 

interacting effects of disease and fire. Changes to tanoak abundance, whether caused 

by SOD or fire, will have important implications for establishment of P. ramorum 

and disease dynamics, especially in stands where tanoak is the sole sporulating host; 

stands with increasing redwood abundance are less likely to be infested. Within 

burned areas, SOD impacts may be elevating redwood mortality, perhaps through 

longer fire residence times or continued smoldering of surface fuels at the base of 

large trees that may otherwise be somewhat resistant to a fire that passes through 

quickly. This leads to the potential for SOD and fire to interact to create longerlasting impacts to the composition of these forests. Further investigation into these 

interactions is ongoing.
GENERAL TECHNICAL REPORT PSW-GTR-238 

376

References 

Maloney, P.E.; Lynch, S.C.; Kane, S.F.; Jensen, C.E.; Rizzo, D.M. 2005. Establishment of 

an emerging generalist pathogen in redwood forest communities. Journal of Ecology

93(5): 899-905.

Meentemeyer, R.K.; Rank, N.E.; Shoemaker, D.A.; Oneal, C.B.; Wickland, A.C.; Frangioso, 

K.M.; Rizzo, D.M. 2008. Impact of sudden oak death on tree mortality in the Big 

Sur ecoregion of California. Biological Invasions 10(8): 1243-1255.

Metz, M.R.; Frangioso, K.M.; Meentemeyer, R.K; Rizzo, D.M. 2011. Interacting 

disturbances: wildfire severity affected by stage of forest disease invasion.

Ecological Applications 21(2): 313-320.

Rizzo, D.M.; Garbelotto, M.; Hansen, E.M. 2005. Phytophthora ramorum: integrative 

research and management of an emerging pathogen in California and Oregon 

forests. Annual Review of Phytopathology 43: 309-335. 

Valachovic, Y.S.; Lee, C.A.; Scanlon, H.; Varner, J.M.; Glebocki, R.R.; Graham, B.D.; 

Rizzo, D.M. 2011. Sudden oak death-caused changes to surface fuel loading and 

potential fire behavior in Douglas-fir-tanoak forests. Forest Ecology and 

Management 261(11): 1973-1986. 
377

Regeneration and Tanoak Mortality in Coast 

Redwood Stands Affected by Sudden Oak 

Death1 

Benjamin S. Ramage2, Kevin L. O’Hara2, and Alison B. Forrestel2 

Abstract

Sudden oak death, an emerging disease caused by the exotic pathogen Phytophthora 

ramorum, is impacting coast redwood (Sequoia sempervirens) forests throughout coastal 

California. The most severely affected species, tanoak (Notholithocarpus densiflorus), is 

currently widespread and abundant in the redwood ecosystem, but diseased areas have begun 

to experience considerable mortality. Tanoak, which is extremely valuable as food source to 

numerous wildlife species, is unlikely to successfully regenerate in these areas, and thus 

affected redwood forests are transitioning to a novel state. In this study, to predict which 

species might replace tanoak, we investigated regeneration patterns in heavily impacted 

stands in Marin County, California. Our main findings were: (1) despite reductions in canopy 

cover, there is no evidence that any species other than tanoak has exhibited a regenerative 

response to tanoak mortality, (2) the regeneration stratum was dominated by redwood and 

tanoak (other tree species were patchy and/or scarce), and (3) some severely affected areas 

lacked sufficient regeneration to fully re-occupy available growing space. Our results indicate 

that redwood is likely to initially re-occupy the majority of the ground relinquished by tanoak, 

but also provide evidence that longer-term trajectories have yet to be determined and may be 

highly responsive to management interventions. 

Key words: Lithocarpus densiflorus, Notholithocarpus densiflorus, Phytophthora ramorum,

regeneration, redwood, Sequoia sempervirens, sudden oak death, tanoak

Introduction

Tanoak (Notholithocarpus densiflorus syn. Lithocarpus densiflorus), a broadleaf 

evergreen in the Fagaceae family, is currently widespread and abundant in coast 

redwood (Sequoia sempervirens) forests and is believed to be an integral component 

of the structure and function of these unique ecosystems (Burns and Honkala 1990, 

Hunter et al. 1999, Noss 2000). However, the close association between redwood and 

tanoak may be relegated to history if sudden oak death (SOD), an emerging disease 

caused by the exotic pathogen Phytophthora ramorum continues to spread 

throughout coastal California. Current research demonstrates drastic declines in 

tanoak populations and mounting evidence, from numerous field studies (for 

example, Maloney et al. 2005, McPherson et al. 2010, Ramage et al. 2010) and 

 

1 A longer version of this paper has been published. If you wish to cite this paper, please reference the 

original publication (Ramage, B.S.; O Hara, K.L.; Forrestel, A.B. 2011. Forest transformation 

resulting from an exotic pathogen: regeneration and tanoak mortality in coast redwood stands 

affected by sudden oak death. Canadian Journal of Forest Research 41: 763-772.). 2 Dept. of Environmental Science, Policy, & Management, University of California, Berkeley, CA 

94720-3114. Corresponding author: bsramage@berkeley.edu.
GENERAL TECHNICAL REPORT PSW-GTR-238 

378

several disease progression models (for example, Meentemeyer et al. 2004), suggests 

that SOD could eventually drive tanoak to extinction in redwood forests. 

Several tree species succumb to SOD, but tanoak is the most severely affected 

tree and the most abundant SOD-susceptible species in redwood forests (Burns and 

Honkala 1990, Rizzo et al. 2005). The extreme susceptibility of tanoak results from a 

combination of factors: (a) little or no genetic resistance, (b) susceptibility of all ages 

and size classes, and (c) ability of tanoak foliage and twigs to support pathogen 

sporulation, facilitating eventual lethal infection of the bole (all other species that are 

killed by SOD appear to require the presence of a secondary foliar host for bole 

infection; Maloney et al. 2005, Ramage et al. 2010, Rizzo et al. 2005). Furthermore, 

because many native species support sub-lethal foliar infections, including redwood 

(Davidson et al. 2008), P. ramorum has almost certainly become a permanent 

resident of infested areas, and thus it is unlikely that tanoak will ever return to preSOD abundances in diseased redwood forests. Tanoak stumps often sprout 

prolifically following death of the main bole (Cobb et al. 2010, Ramage et al. 2010), 

and it is feasible that root systems could be maintained indefinitely if adequate 

amounts of photosynthate are consistently produced prior to episodic SOD-induced 

sprout dieback; a similar situation has been occurring for approximately a century 

with the American chestnut, Castanea dentata, and the exotic disease chestnut blight, 

caused by Cryphonectria parasitica (Ellison et al. 2005). However, even if this 

scenario was to manifest, such an outcome would still represent a form of functional 

extinction (sensu Ellison et al. 2005). 

It is often assumed that redwood forests are relatively poor in tree species 

diversity because of the strong competitive effects of redwood, but there is 

surprisingly little evidence to support this conjecture. Given that tanoak is a nearly 

ubiquitous associate of redwood (Burns and Honkala 1990, Noss 2000), we cannot 

discount the possibility that tanoak is competitively excluding one or more species 

otherwise capable of persisting in redwood forests. Of particular concern is the 

question of whether functionally similar native tree species will be able to colonize 

and persist in areas previously occupied by tanoak. Tanoak regularly produces large 

nutritious acorns that are utilized by many wildlife species (for example, bear, deer, 

and several rodent and bird species), while redwood produces unpredictable crops of 

small and light seeds with limited wildlife value (Burns and Honkala 1990). If tanoak 

is not replaced by one or more functionally similar tree species (for example, a true 

oak species), its loss could result in serious cascading impacts. For instance, acorns 

are a primary food source for the dusky footed woodrat (Neotoma fuscipes), which is 

in turn a primary food source for the northern spotted owl (Strix occidentalis caurina; 

Courtney et al. 2004). 

Regeneration in SOD-induced mortality gaps is likely to differ from regeneration 

in areas not experiencing mortality, and – because SOD gaps represent a novel 

occurrence – unexpected patterns may emerge. Features such as standing dead trees 

and debris piles may attract birds and thereby increase the input of bird-dispersed 

seeds into disturbed areas (Rost et al. 2009). Seedling and sprout survival and growth 

rates may increase following the death of mature trees via: (a) improved 

photosynthetic capacity, which can occur with even small reductions in canopy 

cover, and/or (b) a reduction in the intensity of competition for water and soil 

nutrients (Oliver and Larson 1996, Smith et al. 1997); increased basal sprouting 

incidence could also occur due to bole damage from falling trees. These mechanisms 
Regeneration and Tanoak Mortality in Coast Redwood Stands Affected by Sudden Oak Death 

379

vary among species (Grubb et al. 1977) and thus relative abundances of regeneration 

in mortality gaps are likely to differ from the surrounding matrix. In the case of 

redwood, studies have shown that basal sprout survival and growth rates were greater 

in higher light environments (O’Hara and Berrill 2010, O’Hara et al. 2007), and that 

a greater proportion of established redwood stems had basal sprouts in an area 

experiencing SOD-induced tanoak mortality than in an unaffected area (Waring and 

O’Hara 2008). 

Our specific objectives were to: (1) test the hypothesis that regeneration is 

positively associated with tanoak mortality, (2) identify the species that are 

regenerating in the greatest numbers in areas severely affected by sudden oak death, 

and (3) consider the potential implications of the observed patterns. 

Methods

Fieldwork was conducted at the Marin Municipal Water District (MMWD), 

which occupies approximately 8500 ha of protected land on the northern slope of 

Mount Tamalpais in Marin County, California. Redwood forest, primarily secondgrowth stands that originated at the end of the 19th century or beginning of the 20th

century, is scattered throughout the watershed, covering a wide range of slopes, slope 

positions, and aspects. Unusual levels of tanoak mortality were first observed in 

Marin County in 1994, and SOD has been causing extensive tanoak mortality at 

MMWD since at least 2000 (McPherson et al. 2010, Rizzo et al. 2002). Most study 

plots (1/20 ha; 12.62 m radius) were randomly located (in redwood forest), but we 

also used a stratification protocol to ensure adequate representation of: (a) areas with 

high tanoak abundance but little or no tanoak mortality, and (b) areas with very high 

levels of tanoak mortality. Additional details are provided in the full version of this 

paper (Ramage et al. 2011).

Data for mature trees (> 10 cm diameter at breast height; 1.37 m height; DBH) 

were collected during the summer of 2008. Within each plot, we recorded species and 

DBH for all tree species, as well as health and deterioration status for all tanoaks; 

details are provided in the full version of this paper (Ramage et al. 2011). In 2008, we 

also collected one sample per plot of symptomatic tanoak (5 to 10 leaves and 2 to 3 

twigs) and/or California bay (Umbellularia californica; 5 to 10 leaves), to test for the 

presence of P. ramorum via polymerase chain reaction (PCR); methods are described 

in Hayden et al. (2006) and results are presented and discussed in the full version of 

this paper (Ramage et al. 2011). Regeneration and canopy cover data were collected 

during the summer of 2010. Counts of all seedlings (< 1.37 m height), basal sprouts 

(< 1.37 m height), saplings (seed or sprout origin stems > 1.37 m height and < 3 cm 

DBH), and juvenile trees (3to 10 cm DBH) were conducted for all tree species in two 

randomly selected quadrants per plot (for example, NW and SE). Canopy cover was 

measured with a spherical densiometer at five points per plot (plot center and 3 m in 

each cardinal direction) and values were averaged. 

To limit any potentially confounding effects of tanoak abundance, all plots with 

less than the median basal area (BA) of total tanoak (living and dead trees combined, 

calculated with the randomly located plots only; 14.4 m2

 per ha) were excluded from 

all analyses. Using this dataset (n = 16 plots), we tested the effects of tanoak 

mortality on canopy cover and tree regeneration with generalized linear models. For 

each response variable, we fit models in which either dead tanoak BA (in 2008) or 
GENERAL TECHNICAL REPORT PSW-GTR-238 

380

the number of dead tanoak stems (in 2008) was specified as the sole predictor 

variable (with and without squared terms). Response variables, data for all of which 

were collected in 2010, consisted of canopy cover and all measures of regeneration 

(seedlings, basal sprouts, saplings, and juvenile trees) for several species groups (all 

species combined, all non-tanoak species, non-tanoak hardwoods, and non-redwood 

conifers), as well as each tree species individually: tanoak, redwood, pacific madrone 

(Arbutus menziesii), California bay, bigleaf maple (Acer macrophyllum), Douglas-fir 

(Pseudotsuga menziesii), and California nutmeg (Torreya californica). 

To determine which species are beginning to replace tanoak, we examined tanoak 

mortality and species-specific regeneration patterns in areas heavily impacted by 

SOD (plots with > 300 dead stems per ha and/or > 15 m2

 dead BA per ha), termed

“severe” plots (n=8), and we present relevant data for these plots. We also reexecuted all of the models described above using only the “severe” plots. Finally, we 

identified three plots in which the total density of non-tanoak seedlings (in 2010) was 

less than the density of dead tanoak stems (in 2008), termed “regen-deficient” plots. 

Additional analytical details are provided in the full version of this paper (Ramage et 

al. 2011). 

Results

Effects of tanoak mortality on canopy cover and 

regeneration 

Canopy cover in 2010 was significantly affected by tanoak mortality in 2008 

(BA: p < 0.0001; stems: p = 0.0014). Squared terms were not significant in either 

model; predicted values are curved because of the logit transformation prior to model 

fitting and subsequent back-transformation prior to plotting (fig. 1). In the plots with 

the greatest mortality, canopy cover was below 60 percent, while canopy cover was 

generally above 90 percent in plots with little or no mortality. 

Figure 1—Canopy cover (2010) as a function of tanoak mortality (2008). Solid circles 

and asterisks were deemed severely impacted (“severe” plots); asterisks indicate 

“regen-deficient” plots; open circles represent all other plots (i.e., not “severe” or 

“regen-deficient”).
Regeneration and Tanoak Mortality in Coast Redwood Stands Affected by Sudden Oak Death 

381

Dead tanoak BA (in 2008) did not affect the density of tanoak seedlings, basal 

sprouts, or juvenile trees (in 2010), but the density of tanoak saplings was positively 

related to dead tanoak BA (p = 0.0105). The density of dead tanoak stems (in 2008) 

did not affect the density of tanoak seedlings, basal sprouts, or saplings (in 2010), but 

the density of tanoak juvenile trees was negatively related to dead tanoak stems (p = 

0.0007). Squared terms were not significant in either model; predicted values are 

curved because of the log transformation prior to model fitting and subsequent backtransformation prior to plotting. 

Tanoak mortality (in 2008) was entirely unrelated to regeneration (in 2010) of all 

species other than tanoak, including redwood. This was true across both tanoak 

mortality metrics (BA and stem counts) and all regeneration categories (seedlings, 

basal sprouts, saplings, and juvenile trees), and regardless of whether each species 

was analyzed individually or pooled into functional groups (non-tanoak hardwoods, 

non-redwood conifers). Similarly, tanoak mortality was unrelated to total 

regeneration (all species including tanoak and redwood), as well as all non-tanoak 

species. We also re-executed all these analyses using only the eight “severe” plots; all 

results were qualitatively identical, except for the relationship between tanoak 

juvenile trees and dead tanoak stems, which was insignificant in the “severe” 

analysis.

Severely impacted areas: regeneration and mortality 

In the eight “severe” plots (those with > 300 dead stems and/or > 15 m2 dead BA, 

per ha), the regeneration stratum was generally dominated by tanoak and redwood, 

but seedlings of other species were present at higher levels in certain areas. The 

median density of tanoak seedlings, basal sprouts, saplings, and juvenile trees was 

1960, 4600, 180, and 0 per ha, respectively. Corresponding values for redwood were 

1380, 1500, 100, and 40. Redwood accounted for 100 percent of non-tanoak basal 

sprouts, saplings, and juvenile trees, and the majority of non-tanoak seedlings in most 

plots (median non-tanoak seedlings = 1740; median redwood seedlings = 1380). 

Douglas-fir seedlings occurred in three of the eight severely impacted plots and 

exceeded densities of 3500 per ha in two of these plots. Pacific madrone and 

California bay seedlings were each present in four severely impacted plots, but their 

densities never exceeded 600 and 160 per ha, respectively. Seedlings of California 

nutmeg and bigleaf maple each occurred in only one plot, at densities of 240 and 40 

per ha, respectively. Complete regeneration data for all “severe” plots are provided in 

Table 1 of the full version of this paper (Ramage et al. 2011). 

In these plots, the median amount of dead tanoak (absolute value and percent of 

total), in terms of BA and stem counts, was 21.9 (m2

 per ha; 66.4 percent) and 450 

(per ha; 68.0 percent), respectively. As quantified by percent dead, the most severely 

impacted plot exhibited mortality exceeding 90 percent, in terms of both stem counts 

and BA. When quantified with absolute mortality, the most severely impacted plot

contained 46.4 m2

 dead BA per ha and 740 dead stems per ha. The median amount of 

dead tanoak that was broken/fallen (bole broken at a diameter of > 5 cm), in terms of 

BA and stem counts, was 15.8 (75.2 percent of dead) and 270 (79.1 percent of dead), 

respectively.
GENERAL TECHNICAL REPORT PSW-GTR-238 

382

Three plots (which we refer to as “regen-deficient”) exhibited a total density of 

non-tanoak seedlings that was less than the density of dead tanoak stems. 

Regeneration in these plots was consistently dominated by tanoak and redwood, but 

numbers were highly variable between plots and regeneration categories. With regard 

to other tree species, no basal sprouts, saplings, or juvenile trees were present in any 

plot, and seedlings were very uncommon. Seedlings of California bay (160 per ha) 

and bigleaf maple (40 per ha), the only other species present, occurred in only one 

plot each, both at densities insufficient to replace the number of tanoak trees that had 

already died by 2008. Densities of redwood basal sprouts, saplings, and juvenile 

trees, as well as tanoak regeneration (all categories combined), exceeded densities of 

dead tanoak stems in most (in the case of redwood) or all (in the case of tanoak) 

plots, but it is unlikely that these sources of regeneration will be able to fully reoccupy mortality gaps; this statement is justified in the discussion. 

In the three “regen-deficient” plots, canopy cover was highly variable (54.2, 82.5, 

and 90.1), as was dead tanoak BA (42.2, 21.8, and 15.2 m2

 per ha). The density of 

dead tanoak stems was more consistent (640, 540, and 500 per ha), as was the percent 

of total tanoak that was dead, whether quantified by BA (93.0, 95.6, and 82.6 

percent) or stem counts (86.5, 93.1, and 80.6 percent). The percent of dead tanoak 

that had broken/fallen was also consistently high, whether quantified by BA (81.5, 

91.7, and 76.3 percent) or stem counts (78.1, 88.9, and 80.0 percent), suggesting that 

much of this mortality occurred well before our 2008 measurements. 

Discussion

Broad regeneration patterns 

Despite a significant reduction in canopy cover, our data suggest that SODimpacted redwood forests in our study area are not exhibiting a regenerative response 

to tanoak mortality; tree regeneration was abundant in some mortality gaps, but 

regeneration levels were generally equivalent in severely impacted areas and 

relatively unaffected areas. These results were consistent across all mortality metrics, 

regeneration categories, and species (with the exception of tanoak saplings, which 

increased with dead tanoak basal area, and tanoak juvenile trees, which exhibited a 

negative relationship with dead tanoak stem density). Redwood and tanoak 

dominated the regeneration stratum in heavily diseased areas, and throughout the 

entire study area, while regeneration of other tree species was present only in isolated 

patches, and typically in very low densities. 

Cobb et al. (2010) suggested that California bay may benefit more than any other 

tree species from SOD-induced tanoak mortality in redwood forests, because of 

similarities in growth form and size between tanoak and California bay, as well as 

positive feedbacks between inoculum loads and the abundance of California bay 

(which supports the most prolific sporulation of any host, but is not killed by P. 

ramorum; Davidson et al. 2008). However, at our study site, current regeneration 

patterns do not support this hypothesis. Although California bay seedlings occurred 

in 50 percent of “severe” plots, their densities were uniformly low (never exceeding 

160 per ha, with a median of 20), and California bay basal sprouts, saplings, and 

young trees were entirely absent from all “severe” plots. In contrast, redwood 

regeneration occurred in all of these plots, and redwood seedlings alone had a median 

density of 1380 per ha (69 times that of California bay), suggesting that redwood is 
Regeneration and Tanoak Mortality in Coast Redwood Stands Affected by Sudden Oak Death 

383

currently much better poised to claim the space previously held by tanoak.

Regeneration patterns may differ in other affected areas (for example, stands with a 

greater abundance of mature California bay), but given that no previous studies have 

comprehensively examined tree regeneration in SOD-impacted redwood forests, 

researchers and land managers should consider the possibility that our findings will 

be applicable beyond our study area. 

Deficiencies in regeneration 

Although broad patterns indicate that regeneration is sufficient to replace dead 

tanoaks, we have identified some patches (1/20 ha in size) in which the density of 

dead tanoak stems exceeded the density of non-tanoak seedlings. Tanoak 

regeneration and other forms of redwood regeneration (basal sprouts, saplings, and 

juvenile trees) were abundant in some of these plots, but we have deemed these plots 

deficient in regeneration for the following reasons: (a) P. ramorum is established in 

all SOD-impacted areas and tanoak regeneration is thus unlikely to survive to 

maturity (Cobb et al. 2010), and (b) redwood basal sprouts will not be able to fully 

re-occupy large mortality gaps because these sprouts necessarily emerge at the base 

of existing redwood trees, which tend to exist in dense discrete clumps in secondgrowth redwood-tanoak forest (Douhovnikoff et al. 2004, Ramage and O’Hara 2010), 

and generally exhibit a strong vertical growth habit. The same rationale applies in 

large part to redwood saplings and young trees, many of which were associated with 

established trees and most likely of sprout origin. While additional regeneration will 

almost certainly appear in the future, an insufficient passage of time does not appear 

to fully explain the paucity of regeneration in some mortality gaps, or the 

corresponding absence of a regenerative response to tanoak mortality throughout the 

study area; in the full version of this paper (Ramage et al. 2011), we provide a 

justification for this assertion, as well as a thorough examination of mechanisms that 

may be inhibiting recruitment in SOD-impacted areas.

Tanoak regeneration patterns 

The positive relationship between tanoak saplings and tanoak mortality (dead 

basal area) probably reflects: (a) increased growth rates of advance regeneration in 

mortality gaps, and/or (b) the initial tendency of tanoaks that are top-killed by SOD, 

as well as tanoaks that are infected but still living, to sprout vigorously (Cobb et al. 

2010, Ramage et al. 2010). The absence of a relationship between tanoak mortality 

and tanoak seedlings or basal sprouts may: (a) indicate a balance between diseaseinduced recruitment and mortality within these regeneration classes, and/or (b) reflect 

the fact that tanoak seedlings and sprouts (which are extremely shade tolerant; Burns 

and Honkala 1990) are often abundant in healthy stands. The strong negative 

relationship between tanoak juvenile stems and tanoak mortality (dead stems) 

suggests that individuals in this size class (3 to 10 cm DBH) are suffering high rates 

of SOD-induced mortality and/or not recruiting in diseased areas.

Conclusions and management considerations 

SOD may ultimately create a niche opportunity (an opportunity for an absent or 

uncommon species to invade or increase in abundance; sensu Shea and Chesson 

2002), but we have not discovered evidence that this phenomenon is occurring in the 

redwood forests of our study area. Rather, tree species other than redwood and tanoak 
GENERAL TECHNICAL REPORT PSW-GTR-238 

384

have made only small and highly variable incursions into mortality gaps, and some 

areas appear to lack sufficient regeneration for full re-occupancy of growing space, 

demonstrating that the future composition of SOD-impacted redwood forests is still 

far from certain. The ultimate ability of potential tanoak replacement species to coexist with redwood in areas previously dominated by tanoak may only be apparent if 

and when such species are able to recruit in high numbers; at present, dispersal and 

recruitment limitation (both of which may be highly stochastic) are likely the 

dominant community assembly processes, but as these species begin to actively 

compete in areas previously occupied by tanoak, deterministic niche-related 

processes may become more important. For instance, tanoak develops a deep taproot 

(Burns and Honkala 1990), a characteristic that likely helps it to co-exist with 

redwood (which does not develop a taproot; Burns and Honkala 1990); this 

divergence in root morphology suggests that other deeply rooted tree species may be 

best equipped to compete with redwood in the absence of tanoak.

Numerous long-term impacts may result from SOD-induced tanoak decline (for 

example, trophic cascades resulting from the loss of tanoak acorns, reduced 

resistance and/or resilience in the face of future threats; sensu Suding et al. 2004). 

Land managers who wish to minimize the threat of such impacts should consider the 

intentional establishment of other native tree species in heavily impacted areas. Such 

efforts could optionally focus upon species at or near the northern extent of their 

range, in anticipation of generally warming climatic conditions. By choosing to direct 

ecological trajectories, managers may successfully alter long-term characteristics 

such as species composition and stand structure, but such actions will be most 

efficient in the early stages of community assembly (Thompson et al. 2001). 

Furthermore, because SOD-induced tanoak mortality gaps are a novel occurrence, 

and novel ecosystems are likely to present unfamiliar and unforeseen challenges 

(Hobbs et al. 2006), it is prudent to assume that successful plantings (or other 

mitigation actions) may require considerable experimentation. As an alternative 

approach, managers may opt to actively maintain the open nature of these sites, so 

that if and when SOD-resistant tanoak genotypes are discovered, these genotypes can 

be readily reintroduced into areas where tanoak previously dominated. 

Acknowledgments

We thank Save the Redwoods League for providing funding for this research and 

the University of California-Berkeley Forest Pathology Laboratory for molecular 

testing for Phytophthora ramorum in our study plots. In addition, we thank the Marin 

Municipal Water District for allowing this study to be conducted on their land, and 

two anonymous reviewers for valuable feedback. Finally, we are very grateful for the 

excellent work of our dedicated field assistants (Ben Ewing, Karla Martinez, and the 

many others who donated their time). 

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Wildlife, Fisheries,

Aquatic Ecology

389

Sonoma Tree Vole Habitat on Managed 

Redwood and Douglas-fir Forestlands in 

North Coastal California1

Sal J. Chinnici,

2 David Bigger,3 and Eric Johnson4

Abstract

The Sonoma Tree Vole (Arborimus pomo) – a small arboreal mammal associated with mature 

forests – is a California Species of Special Concern due to concerns regarding loss of habitat 

from harvest, fire, and conversion. By counting their nests, we examined A. pomo use of pole 

to mature forest seral stages from 2001 to 2005 using line transects at 64 study sites 

distributed across redwood (Sequoia sempervirens), mixed conifer, Douglas-fir (Pseudotsuga 

menziesii), and hardwood dominated stands. A total of 441 nests were found including 215 

active and 226 inactive nests. The highest percentage (33 percent) of nests was in unharvested 

and partially harvested old growth Douglas-fir stands. All pole and young stands, and stands 

that were predominantly redwood, had 77 percent fewer nests. This study suggests that A. 

pomo could benefit from forest management strategies aimed at retaining a mature Douglasfir stand component.

Key words: conservation, Douglas-fir, forest inventory, habitat, modeling, redwood, Sonoma 

tree vole

Introduction

Tree voles (Arborimus sp.) are small nocturnal mammals that primarily inhabit 

coniferous forests dominated by Douglas-fir, but they also live where Douglas-fir cooccurs with other species, including redwood, Sitka spruce (Picea sitchensis), 

western hemlock (Tsuga heterophylla) or grand fir (Abies grandis) (Jones 2003).

Even in such forests, populations appear to have a patchy distribution (Carey 1991). 

With their arboreal nature and diet almost entirely of Douglas-fir needles, tree 

voles are among the most unique and highly specialized rodents in the world. Further, 

their habitat use patterns and behavior make studies problematic. As a result, tree 

vole presence and relative abundance is most commonly inferred by their nests, 

distinguishable from other nests by discarded resin ducts from the needles they have 

consumed (Carey 1991, Thompson and Diller 2002). 

The abundance and distribution of suitable habitat may be a limiting factor for 

tree voles (Carey 1989). Although some studies (Swingle 2005, Thompson and Diller 

 

1 This paper was presented at the redwood science symposium: coast redwood forests in a changing 

California. June 21-23, 2011, Santa Cruz, California. 2 Humboldt Redwood Company, LLC, P.O. Box 712, Scotia, CA 95565. (schinnici@hrcllc.com). 3 1551 Brookshire Ct., Reston, VA 20190. (bigger.david@gmail.com). 4 Humboldt Redwood Company, LLC, P.O. Box 712, Scotia, CA 95565. (ejohnson@hrcllc.com). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

390

2002, Wooster and Town 19985) have shown that tree voles nest in younger forests, 

several studies (Aubry and others 1991, Corn and Bury 1986, Gillesberg and Carey 

1991, Gomez and Anthony 1998, Huff et al. 1992, Martin 1998) suggest that the 

species is most abundant in older forests. Thus, timber harvest may impact the 

species.

In northwestern California, the Sonoma tree vole is restricted to coastal forests of 

Humboldt, Mendocino, and Sonoma Counties (Jones 2003). The Sonoma tree vole is 

recognized in California as a Species of Special Concern (California Department of 

Fish and Game 2011). In addition to its status, tree voles are important prey species 

of the northern spotted owl (Forsman and others 1984), the Humboldt marten (Martes 

americana humboldtensis), and the Pacific fisher (Martes pennanti pacifica)

6

. 

The Sonoma tree vole is a covered species of the Humboldt Redwood Company 

(HRC) Habitat Conservation Plan (HCP) (PALCO 1999). A HCP management 

objective for the Sonoma tree vole is to sustain viable tree vole populations through 

retention of suitable habitat. Given the difficulties surrounding the study of this 

species and the questions concerning its habitat, we developed this study to test the 

assumptions regarding the availability and distribution of habitat that then could 

inform models relating timber management to vole abundance, and map current 

distribution on HCP lands. 

For this case study we: (1) examined Sonoma tree vole use of pole to mature 

forest seral stages from 2001 to 2005 at 64 study sites distributed across redwood, 

mixed conifer, Douglas-fir and Douglas-fir/hardwood stands, (2) conducted a 

statistical analysis to quantify the relationship between the number of nests and forest 

stand features, and (3) applied them to the current (2011) forest inventory to assess 

the availability and distribution of Sonoma tree vole habitat. 

Study area

HRC lands encompass approximately 84,000 ha, and are located in coastal 

Humboldt County, California. These lands are characterized by mountainous terrain, 

a maritime climate, and dense coniferous forests, primarily dominated by coastal 

redwood and Douglas-fir, with an understory typically composed of tanoak 

(Lithocarpus densiflorus), Pacific madrone (Arbutus menziesii), salal (Gaultheria 

shallon), and sword fern (Polystichum munitum). Elevations range from 45 m on 

river or creek benches to over 800 m along ridges. 

Methods

Study sites (n = 64) were randomly selected based on the following stand types: 

(1) Douglas-fir, (2) redwood, (3) Douglas-fir/hardwood, and (4) Douglasfir/redwood. All sites contained canopy closure >25 percent and were a minimum of 

10 ha in area. Within each type, 16 sites were selected among three seral stages: pole

(15 through 28 cm Diameter at Breast Height [DBH]), young-growth (29 through 61 

 

5 Wooster, T.W.; Town, P. 1998. California red tree voles within a coastal second-growth forest.

State of California, Department of Fish and Game, Yountville, CA. Unpublished report.

6 Slauson, K. 2011. Unpublished data on file, USDA Forest Service, Pacific Southwest Research Station, 

Redwood Sciences Laboratory, Arcata, CA.
Sonoma Tree Vole Habitat on Managed Redwood and Douglas-fir Forestlands in North Coastal 

California 

391

cm DBH), and mature (>61 cm DBH). 

From 2001 to 2005, we surveyed according to the draft study plan developed by 

the U.S. Department of Agriculture, Forest Service, Pacific Northwest Research 

Station7

. Following Anderson and others (1979), surveyors recorded tree vole nests 

along five 100 m transects in each stand. We attempted to distribute transects 60 m 

apart and parallel to elevation contour lines. The UTM locations of each transect’s 

mid-point was located with a GPS.

We attempted to locate Sonoma tree vole nests with a visual search of trees along 

both sides of the transect line. When a suspected nest structure was detected, the 

ground below the nest was searched for resin ducts, evidence indicative of tree vole 

activity (Jones 2003). If a nest could not be confirmed as belonging to a tree vole 

from the ground, the tree was climbed and the nest was inspected.

A general linear mixed-model analysis of variance (ANOVA) was used to 

quantify the relationship between the number of nests and habitat type as derived 

from forest inventory information. The number of nests per transect was the 

dependent variable. Tree size class (20 to 40 cm, 40 to 60 cm, 60 to 80 cm, and 80 to 

100 cm) and density of Douglas-fir by canopy cover (trace [<25 percent], subdominant [25 to 50 percent], dominant [50 to 75 percent], and pure [>75 percent]) 

were linear continuous effects. Site was treated as a random effect. The variance 

component was selected for the covariance structure. The full maximum likelihood 

estimation was used to model the fixed effects. 

To address the habitat mapping objective using 2011 forest inventory 

information, the Sonoma tree vole nest model was applied to HRC lands in the 

Mattole River watershed near Petrolia, CA using current vegetation type mapping 

and forest inventory data. 

Results

Field study 

A total of 441 Sonoma tree vole nests in the 64 sites were found, with 215 active 

and 226 not active. Occupancy was detected in 57 of the 64 surveyed sites (89 

percent). The sites varied widely in terms of stand area and vegetative characteristics. 

Stand size ranged from relatively small stands of 10 ha (minimum stand size) to 

relatively large contiguous stands of 898 ha. Stand characteristics ranged from unharvested old growth stands with dense canopies, to thinned pole sites with thick 

brushy understory vegetation. 

The greatest numbers of nests were in Douglas-fir trees (table 1). Twenty-nine 

trees were found to contain multiple vole nests. The diameter breast height (DBH) of 

trees with active nests ranged from 10.5 to 226.3 cm (mean 100.6 cm). 

 

7 Biswell, B.; Blow, M.; Finley, L.; Madsen, S.; Schmidt, K. 1999. Survey protocol for the red tree 

vole Arborimus longicaudus. (Interim Version 2.0). U.S. Forest Service, Pacific Northwest Research 

Station. Portland, OR. 31 p. Unpublished.
GENERAL TECHNICAL REPORT PSW-GTR-238 

392

Table 1—Percentage of Arborimus pomo nests by tree species on HRC land in northwestern 

California, 2001 to 2005 (n = 395).

Common name Scientific name # A. pomo

nests

Percent of total nest 

trees

Douglas-fir Pseudotsuga menziesii 337 85.3

Grand fir Abies grandis 29 7.3

Tan oak Lithocarpus densiflorus 17 4.3

Redwood Sequoia sempervirens 8 2.0

Pacific madrone Arbutus menziesii 2 0.5

Interior live oak Quercus wislizenii 1 0.3

Pepperwood Umbellularia californica 1 0.3

Sonoma tree vole nests were in all seral stages except the young growth Douglasfir/hardwood type (fig. 1). By stand type and seral stage, the largest number (33 

percent) of vole nests was in mature Douglas-fir stands, followed by mature 

redwood/Douglas-fir stands (21 percent). Within stand types, mature stages contained 

the most nests and pole had the least. Approximately 11 percent of Sonoma tree vole 

nests were in pole Douglas-fir/hardwood stands. Contrary to the general positive 

relationship of nest density with seral stage, this finding may be due to the presence

of residual old growth Douglas-fir trees at a density that did not affect stand 

classification but still provided the structure for nesting and an adequate food source. 

Sonoma tree vole nests were not found in three of the hardwood pole sites, two of the 

redwood pole sites, and two of the redwood young growth sites. 

Figure 1—Percent of Arborimus pomo nests in pole, young, and mature stands 

relative to species composition for stands surveyed on HRC land in northwestern 

California, 2001 to 2005 (n = 441).

Habitat analysis 

When the stand size class increased, the number of nests per transect also

increased (fig. 2). The estimated slope describing the relationship between tree size 
Sonoma Tree Vole Habitat on Managed Redwood and Douglas-fir Forestlands in North Coastal 

California 

393

class and number of nests (b = 0.659 ± 0.174 (±1SEM)) was significantly greater 

than zero (t62 = 3.79, p < 0.001,). When the relative density of Douglas-fir increased 

from stand to stand, the number of nests per transect also increased (fig. 3). The 

estimated slope describing the relationship between relative density of Douglas-fir

and nests (b = 0.519 ± 0.177 (±1SEM)) was significantly greater than zero (t62 = 

2.931, p = 0.005).

Figure 2—Number of Sonoma tree vole (STV) nests in relation to a stand’s tree size 

class. Each point is the mean number of nests across transects, error bars are 

±1SEM, n is the number of transects that were surveyed.

Figure 3—Number of Sonoma tree vole (STV) nests in relation to Douglas-fir relative 

density within stand. Each point is the mean number of nests across transects, error 

bars are ±1SEM, n is the number of transects that were surveyed.

0

1

2

3

4

Trace Sub-dom Dom Pure

Douglas-fir relative density within stand

STV nests per transect (1SEM)

n = 90 125 20 75

0

1

2

3

4

20-40 cm 40-60 cm 60-80 cm 80-100 cm

Stand size class (DBH, cm)

n = 140 55 65 50

STV nests per transect (1SEM)
GENERAL TECHNICAL REPORT PSW-GTR-238 

394

The following equation describes the model: 

Nests = -1.934 + 0.659(SIZECLASS) + 0.519(DFRANK) 

Where Nests is the number vole nests along a 100 m transect. SIZECLASS is 

the tree size class where 3 = 20-40 cm; 4 = 40-60 cm; 5 = 60-80 cm, and 6 = 80-100 

cm. DFRANK is the relative density of Douglas-fir where 0 = trace; 1 = subdominant; 2 = dominant; and 3 = pure. 

Application of habitat model to current (2011) timber 

inventory 

The Sonoma tree vole nest model was applied to HRC lands using current (2011) 

vegetation type mapping. As an example, the estimated number of Sonoma tree vole 

nests per transect and the area of relative tree vole habitat are shown for the Mattole 

River watershed (table 2).

Table 2—Relative density of Sonoma tree vole nests predicted per 100 m transect and habitat 

area relative to Douglas-fir size and rank from the 2011 HRC forest inventory in the Mattole 

River watershed on HRC land in Humboldt County, CA.

Size Class DF Rank Nests/transect Acres Hectares

3 0 0.0 4847.3 1938.9

3 1 0.6 644.4 257.8

4 0 0.7 255.7 102.3

3 2 1.1 576.3 230.5

3 3 1.6 726.3 290.5

4 3 2.3 1702.5 681.0

5 3 2.9 2047.7 819.1

6 3 3.6 529.4 211.8

The habitat information resulting from the vegetation typing was used to map the 

estimated density per transect of vole nests on HRC lands in the Mattole River 

watershed (fig. 4). On figure 4 black and dark grey areas represent locations where 

nests should be dense or moderately dense respectively. Stippled areas represent 

places the model predicts nests to be absent or few, or are non-forested. 

In the Douglas-fir dominated Mattole River watershed, approximately 38 percent 

of habitat (1711.2 ha) is in the high density category and is scattered throughout the 

forestlands, with some relatively significant concentrations to the northwest on Long 

Ridge and near Taylor Peak (table 2 and fig. 4).

With the exception of Long Ridge and Taylor Peak, the best habitat appears to be 

relatively scattered but connected by stands with lower suitability and riparian zones. 

Thus, in this watershed retention of clumps of habitat and the connectivity between 

them would likely benefit Sonoma tree voles. 
Sonoma Tree Vole Habitat on Managed Redwood and Douglas-fir Forestlands in North Coastal 

California 

395

Figure 4—Relative density of Sonoma tree vole nests on HRC lands in the Mattole 

River Watershed, Humboldt County, CA.

Management implications

Swingle (2005) found through comparisons of nests located by visual searches 

from the ground versus nests located by following radio collared voles that many 

active nests could not be seen from the ground, and that nests located by visual 

searches were biased towards larger nests. Thus, our surveys should best be 

considered indices to relative abundance because we do not know the true number of 

nests in any stand type. Findings of this study relative to Sonoma tree vole habitat are 

consistent with others (e.g., Jones 2003, Thompson and Diller 2002). Mature stands 

with larger Douglas-fir trees and those with higher densities of Douglas-fir tend to 
GENERAL TECHNICAL REPORT PSW-GTR-238 

396

have the most nests while pole and young stands with relativity few or no Douglas-fir 

trees tend to have fewer nests (fig.2 and fig.3). The retention of large Douglas-fir 

trees combined with other conservation strategies such as riparian protection, other 

species protection measures (e.g. northern spotted owl nest zones), or as part of a 

structural element retention strategy wherein large trees with complex structure are 

retained may help maintain Sonoma tree vole populations. 

Maps of Sonoma tree vole habitat derived by applying the habitat model to 

timber inventory (e.g., fig.4) as the inventory is renewed over time can enable 

changes in Sonoma tree vole habitat to be visualized and monitored. Validating the 

model by predicting Sonoma tree vole nest density in stands outside the stands and 

watersheds where the model was developed would add confidence to its use for 

monitoring purposes. 

Looking forward, HRC plans to use the ForSee growth and yield model 

(California Growth and Yield Modeling Cooperative 2009) to project future stand 

conditions under planned management scenarios. The ForSee model produces present 

and future stand characteristics that can be used as input to the vole nest model

enabling forecasts of tree vole habitat value. Next steps for HRC will be to explore 

opportunities for refinement of the model using new or different inputs. Other 

forestland ownerships that have forest inventory data and Geographic Information 

System technology may be able to use these techniques as a tool for evaluating 

species conservation programs.

Acknowledgments

We wish to thank Christiana and Dana Laughlin for their tremendous effort in 

conducting the field work and gathering the data necessary to prepare this paper. 

Without their help it would not have been possible to complete this project. 

References

Anderson, D.R.; Laake, J.L.; Cain, B.R.; Burnham, D.P. 1979. Guidelines for line transect 

sampling of biological populations. Journal of Wildlife Management 43: 70-78.

Aubry, K.B.; Crites, M.J.; West, S.D. 1991. Regional patterns of small mammal 

abundance and community composition in Oregon and Washington. In: Ruggiero, 

L.F.; Aubry, K.B.; Carey, A.B.; Huff, M.H., technical coordinators. Wildlife and 

vegetation of unmanaged Douglas-fir forests. Gen. Tech. Rep. PNW-285. Portland, OR: 

U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station: 

285-294. 

California Department of Fish and Game. 2011. Special animals. State of California, The 

Natural Resources Agency, Biogeographic Data Branch, California Natural Diversity 

Database.January2011. www.dfg.ca.gov/biogeodata/cnddb/pdfs/SPAnimals.pdf .

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[Computer program, V 2.0]. www.cagym.com. 

Carey, A.B. 1989. Wildlife associated with old-growth forests in the Pacific Northwest.

Natural Areas Journal 9: 151-162. 
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California 

397

Carey, A.B. 1991. The biology of arboreal rodents in Douglas-fir forests. Gen Tech. Rep.

PNW-GTR-276. Portland, OR: U. S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station. 46 p.

Corn, P.S.; Bury, R.B. 1986. Habitat use and terrestrial activity by red tree voles 

(Arborimus longicaudus) in Oregon. Journal of Mammalogy 67: 404-406.

Forsman, E.D.; Meslow, E.C.; Wight, H.M. 1984. Distribution and biology of the spotted 

owl in Oregon. Wildlife Monograph 87: 1-64.

Gillesberg, A.M.; Carey, A.B. 1991. Arboreal nests of Phenacomys longicaudus in Oregon.

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Gomez, D.M.; Anthony, R.G. 1998. Small mammal abundance in riparian and upland 

areas of five seral stages in western Oregon. Northwest Science 72: 293-302.

Huff, M.H.; Holthausen, R.S.; Aubry, K.B. 1992. Habitat and management for red tree 

voles in Douglas-fir forests. Gen. Tech. Rep. PNW-GTR-302. Portland, OR: U.S. 

Department of Agriculture, Forest Service, Pacific Northwest Research Station. 16 p.

Jones, J.M. 2003. Habitat associations and ecology of the Sonoma tree vole (Arborimus 

pomo) in northwestern California. Arcata, CA: Humboldt State University. M.A. 

thesis. 55 p. 

Martin, K.J. 1998. Habitat associations of small mammals and amphibians in the central 

Oregon coast range. Corvallis, Oregon: Oregon State University. Ph.D dissertation. 

PALCO. 1999. Habitat conservation plan for the properties of The Pacific Lumber 

Company, Scotia Pacific Company, LLC, and Salmon Creek Corporation. Scotia, 

CA: The Pacific Lumber Company. 138 p.

Swingle, J.K. 2005. Daily activity patterns, survival, and movements of red tree voles 

(Arborimus longicaudus) in western Oregon. Corvallis, OR: Oregon State University. 

M.S. thesis. 118 p.

Thompson, J.L.; Diller, L.V. 2002. Relative abundance, nest site characteristics and nest 

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California. Northwestern Naturalist 83: 91-100. 

399

Two Decades of Research and Monitoring 

of the Northern Spotted Owl on Private 

Timberlands in the Redwood Region: What 

do We Know and What Challenges Remain?

Lowell Diller1, Keith Hamm1, David Lamphear1, and Trent 

McDonald2

Abstract

Surveys for northern spotted owls on Green Diamond Resource Company’s (formerly 

Simpson Timber Company) ownership in coastal northern California were initiated in 1989. 

The following year, a long-term demography study was initiated that has continued to the 

present time. A Habitat Conservation Plan was developed for the species in 1992 and 

numerous habitat studies followed. The extensive dataset generated was used to estimate the 

trend in owl numbers, develop resource selection functions for nighttime activity and nesting 

habitat, and analyze the factors influencing spotted owl survival, fecundity and habitat fitness 

(i.e., ability of the habitat to support a stable population of owls). Important conclusions 

generated to date include that habitat heterogeneity (i.e., juxtaposition of young and older 

stands) is critical to both survival and fecundity, as is precipitation during the early nesting 

season. A landscape projection of current and future habitat indicated an abundance of high 

quality habitat that has the potential to support an increasing population of owls.

Demographic analysis found the owl population was stable from 1990 to 2001, but has

declined in recent years. The decline coincided with an apparent increase in barred owls. 

Growing evidence including barred owl removal experiments indicate that the invasion of 

barred owls into northern California is responsible for the decline. Preliminary results of the

recently initiated removal experiment suggest that control of barred owls is feasible, and that 

spotted owls respond rapidly and favorably where barred owls are removed.

Key words: northern spotted owl, habitat fitness, habitat conservation plan, demography, 

barred owl removal experiment

Introduction

There has been extensive research on northern spotted owl (Strix occidentalis 

caurina) habitat requirements over the years. The majority of these studies have been 

conducted in landscapes with significant amounts of mature or old forests, which are 

the principal habitats for this species in most areas where it has been studied 

(Courtney et al. 2004). However, almost nothing was known about the northern 

spotted owl on private managed timberlands until the Northern Spotted Owl Status 

Review Supplement was published on April 21, 1989 by the US Fish and Wildlife 

Service (FWS). This review concluded that listing the northern spotted owl as a 

threatened species throughout its entire range was warranted, which we observed to 

have unleashed a flurry of spotted owl surveys on private lands in northern 

California. Included in this survey effort was the initiation of spotted owl surveys 

 

1 Green Diamond Resource Company, Korbel, CA 95550. (ldiller@greendimaond.com). 2 Western EcoSystems Technology, Inc., Cheyenne, WY 82001. ( tmcdonald@west-inc.com). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

400

across Green Diamond Resource Company’s (formerly Simpson Timber Company) 

in north coastal California.

Contrary to expectations, we found large numbers of spotted owl on Green 

Diamond’s (GDRC) ownership, which put the company on a collision course with 

the federal Endangered Species Act (ESA) when the owl was listed in 1990. In 

response, GDRC launched a long-term research and monitoring program on spotted 

owls that still continues today, they developed and got approved the first Habitat 

Conservation Plan (HCP) for spotted owls in 1992 and are in the process of 

developing a new HCP for spotted owls along with coverage for fishers (Martes 

pennanti) and tree voles (Arborimus longicaudus and A. pomo). Here we report the 

major findings of 2 decades of research and monitoring on spotted owls and describe 

the new challenges that threaten the long-term viability of this iconic species of the 

Pacific Northwest.

Methods

Each year, we attempted to locate all individual territorial spotted owls within the 

entire study area. Surveys were initiated each year beginning 1 March using protocols 

initially adapted from Forsman (1983) and further modified to support GDRC’s 

approved spotted owl HCP. Owls were initially located primarily at night using vocal 

imitations or recordings of their calls. Daytime surveys were used primarily to locate 

roosts and determine the status of owls at sites where they had been previously 

located or where nighttime responses had been heard. Once an owl was located, it 

was typically offered live mice to determine its identity (if previously captured and 

marked), paired and reproductive status (Forsman 1983). Most nests were initially 

located by following the male back to the nest where the male would commonly 

attempt to deliver the mouse to the female. Once a nest was located, it was revisited 

one or more times after the typical period for fledging (late May through early June) 

to determine the status of the nesting attempt. 

Most owls were captured with a snare pole and marked with a unique numbered 

FWS band attached to one tarsus and a plastic color band attached to the other tarsus. 

For the radio telemetry study, we fitted owls with tail-mounted radio transmitters 

(Holohil, model RI2C 6 g) equipped with either a 1- or 2-year battery (total mass = 

5.5 or 7.5 g, respectively). We attached radio transmitters to the proximal portion of 

the rachis of the two central rectrices using small zip-ties and epoxy (#332 Titan 

Corp., Lynnwood, WA). The time that transmitters remained attached to individual 

birds ranged from 1 to 15 months (mean ≥ 7 months) until the rectrices were molted. 

Owls fitted with radio transmitters were tracked with a two-element, hand-held 

directional H-antenna (Telonics model RA-14) and portable receiver (Telonics model 

TR-4). We radio tracked owls during all seasons, from April 1998 through September 

2000. Triangulations were attempted on two to four birds per night from roadside 

locations throughout the study area, with subsequent visual sightings if possible. 

When located, a bird was followed for 4 to 8 hours or until lost. Locations were 

recorded when the bird changed roosting sites, or every 30 minutes, whichever came 

first.

Results

Distribution
Two Decades of Research and Monitoring of the Northern Spotted Owl on Private Timberlands in 

the Redwood Region: What do We Know and What Challenges Remain?

401

The first surveys of northern spotted owls on GDRC’s ownership in 1989 did not 

cover the entire ownership, but it did demonstrate that spotted owls occurred 

throughout the majority of the ownership and their population density was unusually 

high in some regions. Surveys of all the main contiguous blocks of GDRC’s 

ownership occurred every year since 1989 and the pattern that emerged indicated that 

spotted owls were located throughout the ownership, but there were substantial 

differences in the density of owl sites. In general, owl densities were highest in 

regions with a mixture of mature second growth and young regenerating stands, and 

few owls were found in homogeneous stands of second growth. There was also a 

pattern of high density of owl sites distributed lower on the slopes along rivers and 

major creeks. A study based on surveys from 1990 to 1997 indicated that two regions 

(Korbel and Mad River) produced the highest estimates of crude densities for 

northern spotted owls, but there have been few statistically rigorous attempts to 

estimate population density throughout its range (Diller and Thome 1999). 

Habitat

GDRC’s original 1992 HCP was developed when there had been little spotted 

owl research in the coastal redwood region and only 3 years of site-specific owl 

surveys and research in the study area. As a result, only simplistic definitions of 

habitat existed and suitable habitat for spotted owls was defined as forest stands >30 

years old, because at least some stands in this age class were known to be used by 

spotted owls for foraging, roosting, and nesting (Folliard 1993). At the time, it was 

assumed that recently regenerated stands (0 to 5 years) had no direct value to owls. 

Stands 6 to 30 years were known to be woodrat habitat (Hamm 1995) and therefore 

potential spotted owl foraging habitat. Foraging, roosting, and occasional nesting 

occurred in stands 31 to 45 years old, and forest stands >45 years old were 

considered to be prime nesting and roosting habitat as well as foraging habitat. 

To describe and quantify the unique site-specific habitat used by spotted owls on 

a managed forest in the redwood region, GDRC used the extensive research and 

monitoring to develop a more sophisticated and spatially explicit definition of spotted 

owl habitat. Determining what habitat spotted owls used during their period of 

nocturnal activity was the first step. To gather data on what habitat spotted owls used 

at night, we conducted a radio telemetry study from 1998 to 2000 that included 28 

total owls that were followed all or a portion of that time. The resulting data was used 

to construct 95 percent kernel distributions based on what owls used versus a random 

selection of available points within the same area. These data were used to develop a 

resource selection function (RSF) for spotted owl nighttime activity. The top model 

indicated that owls tended to be found low on the slope in areas composed of 

approximately 70 percent age class 41+ years with a high percentage of hardwood. 

Furthermore, selection was highest if the nearest stand to the owl’s location was 

either 6 to 20 or 21 to 40 years, and lower if the nearest stand was either 0 to 5 or 41+ 

years. In other words, when active at night, spotted owls on GDRC’s ownership were 

most likely to be found in older more complex forest stands that were in close 

proximity to younger stands that have high densities of woodrats (Diller et al. 2010). 

To further refine spotted owl habitat, we conducted an analysis of the habitat 

selected for nesting by spotted owls on GDRC’s timberlands. Based on the locations 

of 182 successful nests (fledged at least one young) from 1990 to 2003, we estimated 

a RSF to characterize the habitat of an ‘average’ successfully nesting spotted owl. 

The top model for managed timberlands indicated that the relative probability of 
GENERAL TECHNICAL REPORT PSW-GTR-238 

402

locating a successful nest increased with age of the stand and ‘edge density’ within a 

600 m radius of the nest. ‘Edge density’ was calculated as m of edge (line between 

any two age classes) per ha, or in other words, the amount of stand age heterogeneity. 

In addition, selection was greatest in stands with approximately 55 percent basal area 

of residual older trees, 30 percent hardwood basal area and a large amount of good 

nighttime activity habitat within a 400 m radius of the nest. This indicated that for 

nesting, spotted owls were selecting older more complex stands that were in fairly 

close proximity to areas that had a high potential as foraging habitat (Diller et al. 

2010). 

Habitat fitness

‘Fitness’ (i.e., ability to survive and reproduce) has traditionally been considered 

an individual attribute, but the quality of the habitat occupied by a particular 

individual also influences its fitness. Therefore, the quality of the habitat relative to 

its impact on the fitness of individuals occupying that habitat can be defined as 

‘habitat fitness’ (Franklin et al. 2000). Combining the influence of habitat on both 

survival and reproduction provides the ultimate measure of habitat quality such that 

areas with high habitat fitness are capable of supporting a stable or increasing 

‘source’ populations while areas of low habitat fitness are associated with habitat 

‘sinks.’ GDRC’s long term demographic study along with geographically referenced 

and relatively detailed forest stand information on all parts of its ownership made it 

possible for us to directly relate habitat characteristics with survival and fecundity to 

estimate site-specific habitat quality (i.e., habitat fitness) for spotted owls. 

To estimate the impact of habitat on survival, we utilized capture-resight data 

from 1990 to 2003 and we used nesting information from the same time period to 

analyze the impact of habitat on fecundity. We included both habitat and non-habitat 

covariates such as regional precipitation and mean air temperature in the analyses 

along with some covariates related to the 1992 spotted owl HCP conservation 

program. The HCP allowed harvesting of a limited amount of occupied owl habitat 

(i.e., ‘take’ of the owl site), which provided a unique opportunity to assess the direct 

impacts of timber harvesting on spotted owls. We also analyzed the effect of 39 noharvest set-asides totaling 10,331 ac that were designated as part of the spotted owl 

conservation strategy in the HCP.

Increased days of precipitation during the early nesting entered with a negative 

coefficient the top survival and fecundity models. In contrast, increased temperatures 

during early nesting entered the top survival model with a positive coefficient. 

Positive effects on survival were also associated with increased nest site selection 

values (i.e., areas good for nesting conferred higher survival probabilities). Four 

habitat covariates were associated with higher fecundity, but collectively they were 

representative of areas having higher habitat heterogeneity. Harvesting or take of an 

owl site did not enter the survival model, but it did have a negative effect on 

fecundity. The effect of set-asides was complex with the highest survival and 

fecundity associated with areas near (< 1⁄2 mile) but not inside set-asides (Diller et al. 

2010). 

From the average survival and fecundity at a specific location, the largest 

Eigenvalue of the Leslie projection matrix was computed and defined to be the 

habitat fitness of the site. Relative to other categorical variables, habitat fitness was 

most sensitive to the location of the nest site/activity center relative to a set-aside. 
Two Decades of Research and Monitoring of the Northern Spotted Owl on Private Timberlands in 

the Redwood Region: What do We Know and What Challenges Remain?

403

Habitat fitness values were highest in the 1⁄2 mile buffer surrounding a set-aside with 

all other covariates being realistically equal. While considerably lower relative to the 

magnitude of the effect, take (i.e., harvesting an owl site) was the second most 

important categorical variable relative to habitat fitness. Relative to continuous 

variables, habitat fitness was most sensitive to changes in precipitation during the 

early nesting period such that increases in the total number of days of measurable 

precipitation within the early nesting period caused habitat fitness to decline. The 

second most important continuous variable was edge density, where increases in this 

variable resulted in higher values of habitat fitness. Relative to latent variables (i.e., 

variables generated from other models), habitat fitness was most sensitive to changes 

in survival followed by changes in fecundity and nesting habitat (Diller et al. 2010). 

Using anticipated harvest plans in the next 10 years and projected harvests 

derived through a newly developed harvest schedule model, we were able to project 

spatially explicit stand conditions into the future. Assuming important non-habitat 

variables (e.g., weather and barred owls) remain at the median values from the past, 

we were able to project spatially explicit estimates of habitat fitness on GDRC’s 

study area at 10 year intervals from 2010 to 2060. The changes in habitat fitness 

across GDRC’s ownership were dynamic at the sub-basin level with specific areas 

waxing and waning in their relative habitat value for owls. However, the overall 

proportion of the ownership in the highest category of habitat fitness (i.e., habitat 

capable of supporting an increasing population of spotted owls) increased from 35 

percent in 2010 to 64 percent of the ownership in 2060. In 2060, a total of 87 percent 

of GDRC’s ownership is projected to be in the two highest categories of habitat 

fitness, which is projected to be capable of supporting a stable or increasing 

populations of spotted owls if other non-habitat variables (e.g., weather and barred 

owls) remain within acceptable limits (Diller et al. 2010).

Based on a sensitivity analysis of habitat fitness, the habitat variables that most 

likely contributed to this trend were edge density and the proportion of older stands 

(41 to 60 years) adjacent to younger stands (6 to 20 and 21 to 40 years). 

Implementation of GDRC’s aquatic HCP that was approved in 2007 will create a 

future landscape in which an estimated 20 to 25 percent of the landscape will be in 

older stands associated with protected riparian or geologic reserves. Along with 

smaller clearcut openings mandated by the California Forest Practice Rules, the net 

affect will be much greater overall open edge density and a higher overall level of 

habitat heterogeneity, which appears to be highly beneficial to spotted owls in 

GDRC’s ownership. In summary, current models based on site-specific habitat data 

indicate a strong positive trend in habitat quality for spotted owls on GDRC’s 

ownership. 

Population trend

Mark-recapture studies were initiated throughout GDRC’s ownership in 1990 to 

estimate key demographic parameters and trends in the population. Along with other 

range-wide demographic studies of northern spotted owls, GDRC participated in 

three previous meta-analyses in 1998, 2004 and 2009. Results from the most recent 

meta-analysis that analyzed GDRC data from 1990 to 2008 indicated that mean 

apparent annual survival probabilities of adult spotted owls on GDRC land were 

0.851 and 0.853 for males and females, respectively, while estimated mean annual 

fecundity for adult spotted owls on GDRC land was 0.305. The estimated rate of 

spotted owl population change (“lambda RJS”) on GDRC land was 0.972, which is 
GENERAL TECHNICAL REPORT PSW-GTR-238 

404

similar to but slightly lower than the two nearby Willow Creek and Hoopa study 

areas. The trend in estimates of the realized population change indicated that the 

population of spotted owls on the GDRC study area was apparently stable or 

increasing until 2001 after which the population began an apparent downward trend. 

The barred owl covariate entered the top model for both survival and fecundity, 

which suggested that barred owls were the most likely cause for the recent decline of 

spotted owls on GDRC’s study area (Forsman et al. in press). 

Potentially, this downward trend was reversed with a 26.6 percent increase in the 

number of occupied owl sites on GDRC’s density study area in 2009 followed by a 

3.0 percent increase in 2010. Factors that may have contributed to this increase 

included modifications (i.e., using high quality digital callers and including a greater 

variety of recorded calls) of the survey protocol in 2009 to increase spotted owl 

detection rates, which resulted in locating banded resident spotted owls in historical 

sites that had appeared to have been abandoned in recent years. In addition, the lower 

Mad River Tract has large areas of third growth that apparently were just now 

reaching suitable habitat attributes for colonization by spotted owls. GDRC also 

initiated a barred owl removal experiment in 2009, which involved removing all 

barred owls from treatment areas (i.e., approximately half of the total study area). 

Barred owls were removed from historical spotted owl sites, which allowed these 

sites to be re-colonized by spotted owls and these treatment areas could be colonized 

by spotted owls free from interference from this expanding competing species (see 

preliminary barred owl results below). Therefore, the recent improved trend probably 

was a combination of improving survey techniques, increasing amounts of suitable 

habitat, and freeing approximately half of the study area from barred owls. 

Response of spotted owls to experimental removal of barred 

owls: preliminary results

In 2006, Green Diamond assisted the California Academy of Sciences (CAS) in 

obtaining a small collection of barred owls in California. These initial collections 

provided an opportunity to do preliminary “removal case studies” that would 

document the response of individual spotted owls to the removal of barred owls. 

Seven barred owls were collected from four different historical spotted owl sites 

during May and June 2006 on GDRC’s ownership in Humboldt County. Although 

based on just four “case studies”, these results suggested that spotted owls were quick 

to re-colonize their former territories following removal of barred owls. 

As part of the implementation of the recovery plan, a Barred Owl Work Group 

(BOWG) was formed to consider implementation of a suite of barred owl removal 

studies (USFWS 2008). The BOWG provided full support for a study on GDRC’s 

ownership that was designed to be complementary to other removal experiments that 

were being proposed for public lands in Washington, Oregon and California. Still 

working under CAS scientific collecting permits that allowed removal of 20 

additional barred owls, a preliminary barred owl removal experiment was initiated on 

a portion of GDRC’s spotted owl demographic study area in 2009. The study was 

designed to determine the impact of barred owls on site occupancy, survival and 

fecundity of spotted owls using paired treatment and control areas where barred owls 

were removed in treatment areas, while they were allowed to increase ‘naturally’ in 

control areas. The additional collections in 2009 also allowed for added removal case 

studies of the response of individual spotted owls to the removal of barred owls from 

sites that were previously known to be occupied by spotted owls. 
Two Decades of Research and Monitoring of the Northern Spotted Owl on Private Timberlands in 

the Redwood Region: What do We Know and What Challenges Remain?

405

The results of our early barred owl removal work were encouraging, but the 

sample sizes were still too small and the time interval too short making conclusions 

preliminary. In response, we were granted the authorization from the FWS and 

California Department of Fish and Game to fully implement a barred owl removal 

study within the GDRC spotted owl demography study area in 2010. The 

authorization allowed for a total of 70 barred owls to be taken over 3 years with a 

maximum of 30 individuals in any year. To account for geographic variation in 

habitat and both spotted and bared owl population densities, GDRC’s demographic 

study area was subdivided into three treatment (Salmon Creek, Korbel/Mad 

River/Little River and Wilson/Hunter/Terwer Tracks) and three control areas (Ryan 

Creek, Redwood Creek and Bald Hill/County Line Tracts).

One of the valuable findings from these initial removal efforts was that using a 

lethal method (i.e., adult territorial individuals were attracted to within 20 to 30 m 

using recorded calls and shot with a 20 gauge shotgun), barred owls could be 

collected humanely, efficiently and with relatively little effort and cost. For example, 

in late winter early spring of 2009, one field person made a total of 16 visits to six

territories with a mean of 1 hour 23 minutes per visit (not including vehicle travel 

time) to collect 100 percent of the known (11) territorial barred owls in the 

Korbel/Mad River treatment area. This equated to approximately 2 field hours per 

barred owl removed, which has been repeated in 2010 and 2011. By far, the biggest 

cost associated with the barred owl removal study is the initial surveys of the study 

area, but this is also needed for the spotted owl monitoring program so the barred owl 

removal study adds little additional cost above GDRC’s existing commitments.

To date, nine historical spotted owl sites meet the criteria for a removal case 

study (i.e., barred owls removed from a historical spotted owl nest site or activity 

center). All of the sites have been re-occupied by spotted owls with the time for reoccupation ranging from a minimum of 13 days to a maximum of 1 year. Four of the 

sites were re-occupied by the original resident spotted owls, including one female 

that had not been seen for 7 years, and the remaining sites were re-occupied by new 

or unknown individuals. The spotted owls were again displaced at three sites by reoccupation of barred owls: one the following year, one after 3 years and one after 

4years. 

The barred owl removal experiment has been too limited in time and scope to 

assess the impact on spotted owl fecundity and survival rates, but we have been able 

to assess preliminary changes in spotted owl occupancy rates for a portion of the 

study area. All the known barred owls (16) were removed from the Korbel/Mad 

River area in 2009, and in 2010, all of the barred owls (eight individuals) that 

recolonized this area were removed. The control area (i.e., no barred owl removal) 

immediately adjacent to the Korbel/Mad River treatment area occurred in the 

Redwood Creek watershed. Although there has not been enough time to fully 

investigate differences in occupancy rates between these two regions, we did a 

preliminary cursory analysis of the trend in the number of occupied spotted owl sites 

for the Korbel/Mad River treatment versus immediately adjacent Redwood Creek 

control area. The year 1998 was selected as a reference point, which was the year 

prior to when barred owl numbers began to rapidly expand in our study area. Figure 

1 below shows the recent trend in occupied spotted owl sites between the control and 

treatment area.
GENERAL TECHNICAL REPORT PSW-GTR-238 

406

Figure 1—Trend in occupied Northern Spotted Owl (NSO) sites on two adjacent 

tracts of land on Green Diamond Resource Company’s ownership in coastal northern 

California. Barred owls were removed from “Korbel/MR” in 2009 and 2010, but no 

barred owls were removed from “Redwood Creek.”

The apparent dramatic 43 percent increase in the number of occupied spotted owl 

sites in the Korbel/Mad River area from 2008 to 2009 was not due exclusively to 

historical spotted owl sites being “freed” of barred owls, because the number of 

newly occupied sites (16) greatly exceeded the number of sites (6) from which barred 

owls were removed. It probably was a combination of removing barred owls from 

historical spotted owl sites, improving survey techniques and increasing amounts of 

suitable habitat that led to the increase in occupied spotted owl sites in the treatment 

area. However, the lack of a similar increase in the Redwood Creek tract suggested 

that removal of barred owls in the Korbel/Mad River area may have had a synergistic 

effect on all of these factors. Specifically, creating an area free of barred owls may 

have increased the probability that resident spotted owls that previously were silent 

would now be more inclined to respond to surveys and it would make colonization of 

the area more likely when floater spotted owls were not being rebuffed by resident 

barred owls. The negative impact of barred owls in some stretches along Redwood 

Creek that historically had high densities of nesting spotted owls is quite dramatic. 

The spotted owls appear to have been almost totally replaced by barred owls, 

although some spotted owls because of their high adult survival are likely to still 

persist in these areas. However, every attempt to survey for them results in an 

aggressive response from a barred owl, which precludes any further attempts to 

locate spotted owls. 

When this study is complete, we will also be able to estimate impacts of barred 

owls on apparent survival and fecundity of spotted owls. Currently, we lack even 

preliminary estimates on these demographic parameters, but there is little doubt that 

if the trend in occupancy between treatment and control areas continues, there also 

will be dramatic differences in apparent survival and fecundity.

References

Courtney, S.P.; Blakesley, J.A.; Bigley, R.E.; Cody, M L.; Dumbacher, J.P.; Fleischer, R.C.; 

Franklin, A.B.; Franklin, J.F.; Gutiérrez, R.J.; Marzluff, J.M; Sztukowsk, L. 2004. 
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the Redwood Region: What do We Know and What Challenges Remain?

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Scientific evaluation of the status of the northern spotted owl. Sustainable 

Ecosystems Institute. Portland, Oregon. . 

Diller, L.; Hamm, K.; Lamphear, D.; McDonald T. 2010. Green Diamond Resource 

Company, northern spotted owl habitat conservation plan, ten-year review report.

Report available from U.S. Fish and Wildlife Service, Arcata Fish and Wildlife Office, 

Arcata, California. 193 p. 

Diller, L.V.; Thome, D.M. 1999. Population density of northern spotted owls in managed 

young-growth forests in coastal northern California. The Journal of Raptor Research 

33(4):275-28. 

Folliard, L.B.; Reese, K.P.; Diller, L.V. 2000. Landscape characteristics of northern 

spotted owl nest sites in managed forests of northwestern California. Journal of 

Raptor Research 34: 75-84.

Forsman, E.D. 1983. Methods and materials for locating and studying spotted owls. Gen. 

Tech. Rep. PNW-162. Portland, OR: U.S. Department of Agriculture, Forest Service, 

Pacific Northwest Research Station. 8 p.

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Schwarz, C.J.; Burnham, K.P.; Anderson, D.R.; Nichols, J.D.; Hines, J.E.; Lint, J.B.; 

Davis, R.J.; Ackers, S.H.; Andrews, L.S.; Biswell, B.L.: Carlson, P.C.; Diller, L.V.; 

Gremel, S.A.; .Herter, R.; Higley, J.M.; Horn, R.B.; Reid, J.A.; Rockweit, J.; Schaberel, 

J.; Snetsinger, T.J.; Sovern, S.G. [In press]. Demographic trends of northern spotted 

owls: a meta-analysis, 1985-2008. Studies in Avian Biology.

Franklin, A.B.; Anderson, D.R.; Gutierrez, R.J.; Burnham, K.P. 2000. Climate, habitat 

quality, and fitness in northern spotted owl populations in northwestern California.

Ecological Monographs 70: 539-590.

Hamm, K.A. 1995. Abundance of dusky-footed woodrats in managed forests of north 

coastal California. Arcata, CA: Humboldt State University. MS thesis. 46 p. 

U.S. Fish and Wildlife Service (USFWS). 2008. Final recovery plan for the northern 

spotted owl (Strix occidentalis caurina). Portland, OR: U.S. Fish and Wildlife Service, 

Region 1. 142 p.

409

How Do We Know How Many Salmon 

Returned to Spawn? Implementing the 

California Coastal Salmonid Monitoring 

Plan in Mendocino County, California

Sean P. Gallagher1 and David W. Wright

2

Abstract

California’s coastal salmon and steelhead populations are listed under California and Federal 

Endangered Species Acts; both require monitoring to provide measures of recovery. Since 

2004 the California Department of Fish and Game and NOAA Fisheries have been developing 

a monitoring plan for California’s coastal salmonids (the California Coastal Salmonid 

Monitoring Plan- CMP). The CMP will monitor the status and trends of salmonids at 

evolutionarily significant regional scales and provide population level estimates. For the 

CMP, data to evaluate adult populations are collected using a spatially balanced probabilistic 

design (e.g., Generalized Random Tesselation Stratified- GRTS). Under this scheme a twostage approach is used to estimate status. Regional redd surveys (stage 1) are conducted in 

stream reaches in a GRTS sampling design at a survey level of 15 percent or ≥ 41 reaches, 

which ever results in fewer reaches, of available habitat each year. Spawner: redd ratios are 

derived from smaller scale census watersheds (stage 2) where “true” escapement is estimated 

using capture-recapture methods. These are used to estimate regional escapement from 

expanded redd counts. In 2008 and 2009 we applied the results of our previous studies to 

estimate salmonid escapement for the Mendocino coast region, the first implementation of the 

CMP in the state. Here we present the results of the first 3 years of this monitoring effort and 

discuss our findings in context of expanding the CMP to all of coastal California. We discuss 

sample frame development, sample size, and present escapement data for six independent and 

eight potentially independent populations and two Diversity Strata within the Central 

California Coho Salmon Evolutionarily Significant Unit.

Key words: coho salmon, population monitoring, spawning surveys, status, trends

Introduction

Recovery of salmon and steelhead listed under the Federal and California 

Endangered Species Acts primarily depends on increasing the abundance of adults 

returning to spawn (Good et al. 2005), and monitoring the trend in spawner 

escapement is the primary measure of recovery. In California watersheds north of 

Monterey Bay, Chinook (Oncorhynchus tshawytscha), coho salmon (O. kisutch), and 

steelhead (O. mykiss) are listed species. Delisting will depend on whether important 

populations have reached abundance thresholds (Spence et al. 2008). 

In 2005, the California Department of Fish and Game (CDFG) and NOAA 

 

1 California Department of Fish and Game 32330 N. Harbor, Fort Bragg, CA 95437. 

(sgallagh@dfg.ca.gov). 2 Campbell Timberlands Management LLC, P.O. Box 1228, Fort Bragg, CA 95437. (David

Wright@Campbellgroup.com).
GENERAL TECHNICAL REPORT PSW-GTR-238 

410

Fisheries published an action plan for monitoring California’s coastal salmonids 

(Boydstun and McDonald 2005). This plan outlines a strategy to monitor salmonid 

populations’ status and trends at evolutionarily significant regional spatial scales and

provide population level estimates. The monitoring is similar to the adult component 

of the Oregon Plan, where data to evaluate regional populations’ are collected in a 

spatially explicit rotating panel design. Crawford and Rumsey (2009) and the Salmon 

Monitoring Advisor (https://salmonmonitoring advisor.org/) recommend a spawner 

abundance sampling design using a spatially balanced probabilistic approach (e.g., 

Generalized Random Tessellation Stratified -GRTS, Larsen et al. 2008). Similarly, 

Adams et al. (2010) propose a two-stage approach to estimate regional escapement. 

Under this scheme, first stage sampling is comprised of extensive regional spawning 

surveys to estimate escapement based on redd counts, which are collected in stream 

reaches selected under a GRTS rotating panel design at a survey level of 10 percent

of available habitat each year. Second stage sampling consists of escapement 

estimates from intensively monitored census streams through either total counts of 

returning adults or capture-recapture studies. The second stage estimates are 

considered to represent true adult escapement and are used to calibrate first stage 

estimates of regional adult abundance by associating precise redd counts with true 

fish abundance (Adams et. al. 2010). 

The Action Plan was tested and further developed in a 3 year pilot study 

(Gallagher et al. 2010a, 2010b). This study compared abundance estimates derived 

from a regional GRTS survey design to abundance measured using a more intensive 

stratified random monitoring approach, evaluated sample size and statistical power 

for trend detection, and evaluated the quality of the stage two data for calibrating 

regional surveys. Gallagher et al. (2010a) recommended that annual spawner:redd 

ratios from intensively monitored watersheds be used to calibrate redd counts for 

regional monitoring of California’s coastal salmonid populations because they were 

reliable, economical, and less intrusive than tagging, trapping, underwater 

observation, weirs, and genetics. Converted redd counts were statistically and 

operationally similar to live fish capture-recapture estimates, but required fewer 

resources than the other methods they evaluated. Gallagher et al. (2010b) found that 

redd counts and escapement estimates using annual spawner:redd ratios were reliable 

for regional monitoring using a 10 percent GRTS sample, and that increasing sample 

size above 15 percent did not significantly improve the estimates. Their evaluation of 

sample size suggested that a sample size of ≥ 41 reaches or 15 percent, whichever 

resulted in fewer reaches, would have adequate precision and sufficient statistical 

power to detect regional trends in salmon populations. 

 The 10 percent sample size recommended by Boydstun and McDonald (2005) 

was provided with little justification. Their Mendocino Coast example 10 percent 

GRTS sample resulted in an annual sample of 203 reaches. This size sample draw 

would likely result in costly over sampling of more reaches than necessary to 

encompass intra-reach variance. NOAA (2007) wrote that the issue of sampling 

intensity for a Coastal Monitoring Plan (CMP) has not yet been resolved.

 Beginning in 2008-09 we applied the results of our previous studies to estimate 

salmonid escapement for the Mendocino coast region. The study’s purpose was to 1) 

provide spawner: redd ratios for calibrating regional redd surveys and, 2) conduct 

regional spawning surveys in the Mendocino coast region (fig. 1) to estimate 

escapement and assess sample size at this scale. We present the coho salmon results 
How Do We Know How Many Salmon Returned to Spawn? Implementing the California Coastal 

Salmonid Monitoring Plan in Mendocino County, California

411

from the first 3 years of study and discuss our findings in context of the CMP. We 

discuss sample frame development, sample size, and present escapement data for six 

independent and eight potentially independent populations and two Diversity Strata 

(National Marine Fisheries Service 2010) within the Central California Coho Salmon 

Evolutionarily Significant Unit. 

Materials and methods

The three intensively monitored life cycle monitoring streams (LCS) (fig. 1) were 

selected for a variety of reasons. Pudding Creek has a fish ladder where fish can be 

marked and released and has been operated as a LCS by Campbell Timberlands 

management since 2006. The South Fork Noyo River has coho salmon data relating 

to the Noyo Egg Collecting Station, fish can be captured and marked there, and it has 

been operated as an LCS since 2000. Caspar Creek was chosen because of existing 

salmon monitoring data. In 2005 we built and operated a floating board resistance 

weir in Caspar Creek 4.9 km from the Pacific Ocean.

The Mendocino coast region extends from Usal Creek to Schooner Gulch (fig. 1). 

We followed Boydstun and McDonald (2005) to define the sampling universe, to 

create a sample frame (the sample universe broken into sampling units), and to 

produce a GRTS draw (the spatially balanced random sample). We defined the 

sampling universe as all coho spawning habitat in coastal Mendocino County. 

We estimated escapement using the Schnabel mark-recapture method (Krebs 

1989) and conducted redd censuses in our LCS. We marked and released fish with 

floy tags and recaptures were live fish observations made during spawning surveys. 

To estimate redd abundance for calculating spawner: redd ratios we used redd count 

and measurement data collected during spawning surveys following Gallagher et al. 

(2007). Over and under-counting errors in redd counts (e.g., bias) were reduced 

following Gallagher and Gallagher (2005). Surveys were conducted fortnightly from 

early December to late April each year in all spawning habitat in each LCS. 

To estimate regional abundance we conducted biweekly spawning surveys in 41 

GRTS reaches from mid-November through April each year. Our methods for redd 

count and measurement data on spawning surveys were the same as for LCS. We 

used the average annual coho salmon spawner: redd ratios from our LCS to convert 

bias corrected redd counts into fish number for each reach (Gallagher et al. 2010a). 

We followed Adams et al. (2010) to estimate regional abundance where the average 

number of redds in our 41 reaches was multiplied by the total number of reaches in 

our sample frame. We estimated 95 percent confidence intervals using the Bootstrap 

with replacement and 1000 iterations. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

412

Figure 1—Study area, survey reaches and life cycle monitoring streams in 

Mendocino County, California.

Results

Each year, nine of the 41 GRTS reaches (21 percent) were unavailable for 

sampling because landowners denied us permission to enter. These reaches were 

replaced by the next nine in the list to fill out our required sample size of n = 41 or a 

12 percent sample. The GRTS sample resulted in sampling reaches in all independent 

populations in two coho salmon diversity strata within the CCC ESU. 
How Do We Know How Many Salmon Returned to Spawn? Implementing the California Coastal 

Salmonid Monitoring Plan in Mendocino County, California

413

Each year sampling 41 reaches encompassed the variation in coho salmon redd 

density within coastal Mendocino County and redd density was not significantly 

different among streams (fig. 2). Because redd density was not statistically different 

among streams we used the average of all reaches to estimate total redd counts and 

escapement for the region and for individual populations within the region. We 

estimated an average of 877 (95 percent CI 377 to 1,515) coho salmon redds and 

1,167 (95 percent CI 488-2,068) adult coho salmon in coastal Mendocino County 

over 3 years (table 1). Regional coho salmon confidence limit widths averaged 64 

percent with n = 41 and decreased to 47 percent when we included reaches from the 

LCS’s (n =80). Escapement estimates for the two diversity strata and for individual 

streams had increased confidence limit widths due to smaller sample sizes (table 1).

Figure 2—Average coho salmon density by stream for regional surveys in coastal 

Mendocino County California 2009 to 2011. A. 2009. B. 2010. C. 2011. Numbers 

above estimates are sample sizes (the number of reaches surveyed). Thin lines are 

95 percent confidence limits.

To examine if we could use the regional average redd density to estimate redd 

abundance for streams we did not survey, we tested LCS redd census and estimates 

made by multiplying regional average density by LCS stream length with paired ttests. Coho salmon census redd counts were not significantly different than estimates 

made by multiplying regional redd density by stream length (t = 1.079, df = 4, p = 

0.35, α = 0.06). 

Confidence limit half widths for our regional sampling were greater than 30 

percent (table1). From our 2009 and 2010 regional data it appears to attain 

confidence limits with 30 percent precision and 90 percent certainty following our 

study design we need to sample 184 reaches (table 2). This level of sampling would 

require sampling more than half of the entire region for coho salmon. Variation 

around the mean coho salmon redd density peaked at n = 41 and remained constant 

after n = 58 reaches (fig. 3). The coefficient of variation (cv) in coho salmon redd 

density averaged 221 percent (n = 41) and improved insignificantly with continued 

sampling (cv = 220 percent, n = 80) over 3 years. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

414

Table 1—Coho salmon escapement estimates (95 percent confidence limits) for coastal 

Mendocino County California 2009 to 2011: ns = not surveyed, na = not available, and DS = 

diversity strata. Precision is the 95 percent confidence limit half widths relative to the mean 

these data are three year averages.

a Preliminary data. 

b Only one reach was surveyed in this stream so confidence bounds were not calculated. c Life cycle monitoring station complete census. d Low flows limited the number of fish that passed the weir and spawned above the egg collecting 

station in 2009.

e Four reaches in 2010 and 2011.

f Six reaches in 2010 and 2011.

Table 2—Estimated sample sizes (number of reaches) for five desired levels of precision 

(width of the 95 percent confidence limits relative to the mean) in coho salmon redd densities 

for regional monitoring.

Precision Confidence limits

90% 95%

10% 1635 2370

20% 413 593

30% 184 263

40% 103 148

50% 66 95

Stream N Number of Adults Precision

2009 2010 2011a %

Mendocino 

Coast

41 887 (415 to 

1545)

898 (555 to

1308)

1575 (534 to

2947)

61

Lost Coast DS 32 672 (295 to

1083)

1059 (515 to 

1711)

1318 (328 to 

2700)

69

Navarro Point 

DS

9 158 (41 to 342) 513 (108 to 

989

176 (18 to 369) 94

Albion River e 3 8 (0 to 22) 0 99 (0 to 297) 148

Big River e 6 80 (0 to 210) 134 (20 to 

214)

147 (0 to 435) 122

Big Salmon Cr.b 2 0 ns ns na

Brush Cr.

b 1 0 0 0 na

Caspar Cr.

c 6 6 5 (3-9) 30 na

Cottaneva Cr. 1 0 0 ns na

Garcia River e 3 69 (0 to 206) 9 (0 to 18) 65 (13 to 130) 166

Greenwood Cr.

b 1 9 ns ns na

Little River c 2 4 2 2 na

Navarro River 6 124 (18 to 124) 452 (159 to 

790)

137 (0 to 420) 103

Noyo River 10 294 (82 to 573) 286 (58 to 

650)

494 (24 to 583) 79

South Fork 

Noyo River c, d

12 19 63 (42 to 

112)

20 na

Pudding Cr. c 9 50 (32 to 96) 9 (4 to 27) na 97

Ten Mile R.

f 1 0 190 (4 to 

454)

295 (0 to 630) 113

Usal Cr. 3 10 (2 to 18) 2 (0 to 5) 7 (0 to 20) 104

Wages Cr.

b 1 0 0 0 na
How Do We Know How Many Salmon Returned to Spawn? Implementing the California Coastal 

Salmonid Monitoring Plan in Mendocino County, California

415

Figure 3—Cumulative mean coho salmon redd density (±SE) plotted against the 

number of sample reaches surveyed in coastal Mendocino County, California during 

2010.

Discussion

Boydstun and McDonald (2005) suggested their example sample frame would 

need refinement which might reduce the sample frame by 30 to 40 percent. We

reduced a list of 2033 stream reaches to 339, an 83 percent reduction by identifying 

known coho salmon streams (Spence et al. 2008) and using local knowledge to define 

coho salmon spawning habitat. The sample frame we produced is for Chinook, 

steelhead, and coho, with species designation for each reach (e.g., soft stratification, 

Larsen et al. 2008). Soft stratification is simpler and cheaper than having one sample 

frame for each species because each reach covers multiple species thus reducing 

logistics and field time. 

Adams et al. (2010) suggest a 3, 12, 30 year revisit design based on the life 

cycles of salmonids present. In 2009 we sampled the first 41 reaches on our GRTS 

draw. The Action Plan states that 40 percent of the GRTS sample reaches should be 

assigned as annual samples. During 2010 we sampled reaches 1 to 16 and 42 to 66

and in 2011 we sampled reaches 1 to 16 and 67 to 92. On average 21 percent of 

selected reaches were not available to sample because landowners denied us 

permission to enter. All unavailable reaches were on private land were replaced with 

reaches that were also on private land, reducing this source of bias in our study3

. 

For the third consecutive year we produced coho salmon escapement estimates 

for the entire coast of Mendocino County consisting of two diversity strata within the 

CCC Coho salmon ESU, six independent populations, and eight potentially 

independent populations. While the precision of these estimates (95 percent 

confidence half widths) was lower than expected, we now have estimates, with 

statistical certainty, of how many salmon escaped in this area. We believe, given the 

variance in redd density we observed, if we are confident in our regional estimates 

we can have confidence in individual population estimates despite the large 

confidence widths. 

 

3 C. Jordan, NOAA Fisheries, Northwest Fisheries Science Center, personal communication. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

416

In our earlier studies we suggested (Gallagher et al. 2010 b) if redd density 

variation in the pilot study area was representative of coastal California as a whole, a 

sample size > 41 reaches for coho salmon should have confidence interval widths of 

30 percent and sufficient statistical power for monitoring escapement trends. Our 

present application of these sample sizes to the entire area of coastal Mendocino 

County resulted in escapement estimates with larger confidence widths than we 

expected. We attribute this in large part to low abundance. When we included all 

reaches surveyed during each year, a systematic rather than design based GRTS 

sample, precision in our estimates improved. However, the coefficient of variation 

did not improve with increased sample size and variation about the mean (fig. 3) 

peaked out at n = 41 and did not substantially decrease after about 58 reaches (~15 

percent). Redd density (an index of abundance) in LCS was lower between 2009 and 

2011 than observed since 2000 and was outside the range of data we used earlier 

(Gallagher et al. 2010b) to develop sample size estimates. Courbios et al. (2008) 

found that a larger sampling fraction and higher redd abundance resulted in better 

accuracy for GRTS. At low redd abundance none of their sampling designs were 

accurate. In a GRTS sampling design for bull trout in the Columbia Basin, Jacobs et 

al. (2009) found that accuracy ranged from 15 percent to 35 percent and was 

dependent on redd distributions within basins and that there was no reduction in 

accuracy with sample sizes between 10 and 50 sites. Our results are similar in that 

increased sample size appears to only marginally improve the precision of our 

estimates. 

Crawford and Rumsey (2009) suggest that salmon monitoring programs strive for 

estimates that have a coefficient of variation (CV) of ± 15 percent. Our regional CVs 

for coho salmon averaged 221 percent (n = 41) to 220 percent (n = 80) and increased 

sample size did not substantially improve them. Given the cost to survey one reach 

for a season ($3,000/ reach, Gallagher et al. 2010b) and the fact that increasing our 

sampling fraction to 30 percent would result in sampling 184 reaches 

($552,000/year), which appears would not greatly improve precision, we recommend 

continued evaluation of smaller sampling fractions. The use of standardized data 

collection procedures and trained staff (Gallagher et al. 2007) will continue to 

contribute to increased precision in regional escapement monitoring. Finally, for 

regional monitoring at low abundance, managers may have to accept larger 

uncertainties in escapement estimates. However, management for recovery primarily 

means listing decisions, and a delisting decision will likely be based on data from 

sustained higher abundance levels when both precision and accuracy levels would be 

much improved. 

Acknowledgments

This work was funded by the California Department of Fish and Game’s 

Fisheries Restoration Grant Program. Too many individuals to mention by name 

from the following entities helped with this study: CDFG, Campbell Timberlands 

Management, NOAA Fisheries Santa Cruz, and the Pacific States Marine Fisheries

Commission. Be assured we value your help. A few we are compelled to mention by 

name include: Stan Allen for administrative support, Wendy Holloway for helping to 

craft fig. 1, and Shaun Thompson, Wendy Holloway, Chris Hannon, and Scott Harris 

for many long hours in the field. Thanks to Sean Hayes and Brad Valentine for 

critical review that greatly improved earlier versions of this manuscript.
How Do We Know How Many Salmon Returned to Spawn? Implementing the California Coastal 

Salmonid Monitoring Plan in Mendocino County, California

417

References

Adams, P.B.; Boydstun, L.B.; Gallagher, S.P.; Lacy, M.K.; McDonald, T.; Shaffer, K.E. 

2011. California coastal salmonid population monitoring: strategy, design, and 

methods. Fish Bulletin 180. California Department of Fish and Game. 82 p.

Boydstun, L.B.; McDonald, T. 2005. Action plan for monitoring California’s coastal 

salmonids. WASC-3-1295. Final report to NOAA Fisheries, Santa Cruz, CA. 78 p.

Courbios, J; Katz, S.L.; Isaak, D.J.; Steel, E.A.; Thurow, R.F.; Rub, A.M.W.; Olsen, T.; 

Jordan, C.E. 2008. Evaluating probability sampling strategies for estimating redd 

counts: an example with Chinook salmon (Oncorhynchus tshawytscha). Canadian 

Journal of Fisheries and Aquatic Sciences. 65: 1814-1830.

Crawford, B.A.; Rumsey, S. 2009. Guidance for monitoring recovery of Pacific Northwest 

salmon and steelhead listed under the Federal Endangered Species Act (Idaho, 

Oregon, and Washington). NOAA’s National Marine Fisheries Service-Northwest 

Region. Draft 12 June 2009. 129 p.

Gallagher, S.P.; Gallagher, C.M. 2005. Discrimination of Chinook and coho salmon and 

steelhead redds and evaluation of the use of redd data for estimating escapement in 

several unregulated streams in Northern California. North American Journal of 

Fisheries Management 25: 284-300.

Gallagher, S.P.; Hahn, P.K.; Johnson, D.H. 2007. Redd counts. In: Johnson, D.H.; Shrier, 

B.M.; O’Neal, J.S.; Knutzen, J.A.; Augerot, X.; O’Neil, T.A.; Pearsons, T.N., editors. 

Salmonid field protocols handbook: techniques for assessing status and trends in salmon 

and trout populations. Bethesda, MD: American Fisheries Society: 197-234.

Gallagher, S.P.; Adams, P.B.; Wright, D.W.; Collins, B.W. 2010a. Performance of spawner 

survey techniques at low abundance levels. North American Journal of Fisheries 

Management 30:1086-1097.

Gallagher, S.P.; Wright, D.W.; Collins, B.W.; Adams, P.B. 2010 b. A regional approach for 

monitoring salmonid status and trends: results from a pilot study in coastal 

Mendocino County, California. North American Journal of Fisheries Management 

30:1075-1085.

Good, T.P.; Waples, R.S.; Adams, P., editors. 2005. Updated status of federally listed ESUs 

of West Coast salmon and steelhead. NOAA Tech. Memo NMFS-NWFSC-66. U.S. 

Dept. of Commerce, 598 p.

Jacobs, S.E.; Gaeumand, W.; Weeber, M.A.; Gunckel, S.L.; Starcevich, S.J. 2009. Utility of a 

probabilistic sampling design to determine bull trout population status using redd 

counts in basins of the Columbia River Plateau. North American Journal of Fisheries 

Management 29: 1590-1604.

Larsen, D.P.; Olsen, A.R.; Stevens, D.L. 2008. Using a master sample to integrate stream 

monitoring programs. Journal of Agricultural, Biological, and Environmental Statistics 

13: 243-254.

National Marine Fisheries Service 2010. Public draft recovery plan for central California 

coast coho salmon (Oncorhynchus kisutch) evolutionarily significant unit. Santa 

Rosa, CA. National Marine Fisheries Service, Southwest Region,

NOAA. 2007. California coastal salmonid monitoring plan agreement No. P0210567 

final report. Santa Cruz, CA: NOAA Fisheries, Southwest Fisheries Science Center, 

Fisheries Ecology Division. 26 p. 

Spence, B.; Bjorkstedt, E.; Garza, J.C.; Hankin, D.; Smith, J.; Fuller, D.; Jones, W.; Macedo, 

R.; Williams, T.H.; Mora, E. 2008. A framework for assessing the viability of 
GENERAL TECHNICAL REPORT PSW-GTR-238 

418

threatened and endangered salmon and steelhead in north-central California coast 

recovery domain. Santa Cruz, CA: NOAA Fisheries. 154 p.
419

Ecology and Management of Martes on 

Private Timberlands in North Coastal 

California

Keith A. Hamm,1 Lowell V. Diller,

1 David W. Lamphear,1 and

Desiree A. Early1 

Abstract

Green Diamond Resource Company has conducted periodic studies of fishers on its California 

timberlands since 1994. A graduate study in 1994 and 1995 used track plates to investigate 

the distribution and habitat associations of fishers. Fishers were detected at 65 percent of the 

survey segments during both years combined but marten were not detected. A repeated track 

plate survey conducted a decade after the initial effort revealed the presence of marten west of 

a known population on public lands. An abbreviated track plate survey effort in 2006 again 

confirmed the presence of marten in the same area of the ownership and a potential expansion 

of the occupied area. During 2010 and 2011, we used remote cameras to survey 75 stations in 

a 2 km2 hexagonal grid in the northern portion of the ownership. We detected fisher at 45

camera stations, marten at eight stations and both species at six stations. Marten are persisting 

in areas where we initially detected them in 2004, but additional studies are necessary to 

investigate habitat use, demographics, dispersal and interactions with competitors like the 

fisher. 

Key words: camera, fisher, managed forest, marten, non-invasive survey, track plate 

Introduction

The marten (Martes americana) and fisher (Martes pennanti) are coexistent 

mesocarnivores inhabiting the coastal forests of northern California. Within north 

coastal California, the Humboldt subspecies of marten (M. a. humboldtensis) 

historically occurred in the coast redwood zone from the Oregon border south to 

northernmost Sonoma County. However, since 1995, surveys conducted in this 

region suggest that martens no longer occupy most of their historical range (Slauson 

2003, Zielinski et al. 2001). Currently, martens are known from only one small 

population in southern Del Norte and northern Humboldt Counties, which comprise 

less than 5 percent of its historical range in this part of the state (Slauson 2003). 

Historical records suggest that martens in northwestern California were closely tied 

to late-successional coast redwood (Sequoia sempervirens) forests (Slauson and 

Zielinski 2003); however, the one remnant population in this region occurs in an area

dominated by Douglas-fir (Pseudotsuga menziesii) and tanoak (Lithocarpus 

densiflorus) forest associations (Slauson et al. 2007), with coast redwood associations 

limited to the western edge of the currently occupied range (Slauson et al. 2007). 

This population uses two structurally distinct forest types with a common link of 

 

1 Green Diamond Resource Company, 900 Riverside Road, Korbel, CA 95550. 707-668-4437. 

(khamm@greendiamond.com). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

420

dense shrub cover; one occurring on serpentine soils and one on more productive 

non-serpentine soils (Slauson 2003, Slauson and Zielinski 2007, Slauson et al. 2007).

In California, fishers historically ranged from Marin County to the Oregon 

border, east to Mount Shasta and Lassen Peak and south through the Sierra Nevada to 

northern Kern County (Grinnell et al. 1937). Fishers currently exist in two disjunct 

populations in California: one on the west slope of the southern Sierra Nevada and 

the other in the Klamath Mountains and Coast Ranges of northwestern California 

(Zielinski et al. 1995). There has long been a concern over habitat loss and alteration 

due to rapid harvest of mature and old-growth Douglas-fir forests (Rosenberg and 

Raphael 1986). 

Both species have been petitioned for listing under state or federal endangered 

species acts. The United States Fish and Wildlife Service determined that the west 

coast population of fisher warranted protection under the Endangered Species Act, 

but were precluded from being added to the list of threatened or endangered species 

due to higher priority actions (USFWS 2004). The fisher was officially added to the 

candidate species list at the time of this ruling. The California Department of Fish 

and Game recently completed a comprehensive status review of fisher in response to 

a listing petition (CDFG 2010), but the species was denied protection under the state 

endangered species act. The Humboldt marten was recently petitioned for federal 

listing as a threatened or endangered species (Center for Biological Diversity and 

Environmental Protection Information Center 2010).

Green Diamond Resource Company (GDRCo) has conducted periodic studies 

focused on fishers inhabiting its California timberlands since 1994. These track plate 

surveys were suitable for detecting martens, and surveys conducted a decade after the 

initial effort revealed the presence of marten several km west of the known 

population on public lands. An impromptu survey effort in 2006 to investigate a 

potential regional decline in fisher numbers again confirmed the presence of marten 

in the same area and a potential expansion of the occupied area. The detection of a 

marten in Prairie Creek Redwoods State Park in 2009 (Slauson and Holden 2009) and 

about 11 km west of the detections on GDRCo ownership prompted additional 

surveys on select areas of GDRCo lands in 2010 and 2011. This paper summarizes 

results of non-invasive surveys for Martes conducted on GDRCo’s managed forests 

since 1994. 

Study area

We conducted surveys in Humboldt and Del Norte Counties, California on 

approximately 150,000 ha of timberlands owned primarily by GDRCo. Coast 

redwood forest dominated the coastal areas and lower elevations. Douglas-fir 

replaced redwood as elevation and distance from the coast increased. Hardwoods 

existed as pure stands or common forest components. Red alder (Alnus rubra) and 

maple (Acer macrophyllum) dominated in coastal mesic sites, while tanoak, madrone 

(Arbutus menziesii) and giant chinquapin (Chrysolepis chrysophylla) occurred at 

higher, more xeric sites. The entire study area was within 30 km of the Pacific Ocean, 

and elevation on the study area ranged from 5 to 1400 m. The maritime climate, 

which produces fog or low clouds throughout the year, has definite wet and dry 

seasons (NOAA 2001) with mean summer and winter temperatures of 8 and 15 o

C 

respectively (Zinke 1988). Annual precipitation occurs mostly as rain from 
Ecology and Management of Martes on Private Timberlands in North Coastal California

421

November through April and varied from 95 cm near the coast to 150 cm in the 

coastal mountains (NOAA 2001). Substantial and persistent snow occurred at 

elevations above 1000 m. Most of the study area had been subjected to timber harvest 

over the past century and consisted of second and third-growth forests, ranging in age 

from recently harvested to 120 years. 

Methods

We conducted surveys for mesocarnivores using enclosed track plates (Fowler 

and Golightly 1994, Ray and Zielinski 2008) in 1994, 1995, 2004, and 2006 and 

remote cameras from 2010 to 2011. We placed a maximum of six track plates 

(stations) in suitable habitat at approximately 1 km intervals within 5 km linear 

segments (Fowler and Golightly 1994). We baited each track plate with a piece of 

chicken. We re-baited and replaced sooted plates every other day for 22 consecutive 

days. We surveyed during January to May, but a subset of segments was surveyed 

during June to August to assess seasonal variation. We calculated detection ratios 

based on segments by dividing the number of segments with >one detection by the 

number of segments sampled. These detection ratios were used to assess trends in 

detection ratios (i.e., index of population size or density) over time and by region. 

Prior to 2010, no surveys were conducted with the specific objective of 

determining the distribution or habitat associations of marten on GDRCo’s 

ownership. However, our field techniques were equally suitable for martens. In 2010, 

we deployed remote cameras at stations centered on a 2 km2

 hexagonal grid 

randomly located on the ownership (Zielinski et al. 2007). We randomly selected 

units to sample, but also focused on areas where marten were detected during prior 

track plate surveys. We deployed cameras for a minimum of 3 weeks at each station. 

We baited stations with raw chicken and a commercial trapping lure (Caven’s Gusto 

Lure, Minnesota Trapline Products, Pennock MN) as an attractant. We baited and 

checked stations weekly with the general exception that some stations were baited 

and checked every other week due to complications with access due to weather or 

other demands on field personnel. During the pilot work in 2010, we tested several 

models of purchased and loaned cameras to assess reliability, ease of use, function 

and other important factors. In 2011, we began placing two RECONYX 

(RECONYX, Inc., Holmen, WI) cameras (models HC500 and PC800) at each sample 

unit. Cameras were located approximately 3 to 5 m and at right angles from the bait 

tree. 

Results

During all surveys in 1994, 1995, 2004 and 2006 we operated a total of 975 

individual track plate stations. We obtained 101 and 135 fisher detections in 1994 

and 1995 respectively on 26 of the 40 (65 percent) survey segments during both years 

combined. We obtained a total of 78 fisher detections at 20 of the 40 segments in 

2004. In 2006, we obtained 115 fisher detections at 12 of 18 segments surveyed. 

Mean detection ratios during the four sample periods from 1994 to 2006 varied from 

0.40 to 0.67 at the segment level. The mean latency to detection (LTD) for all 

surveys was 11.6 days. The distributional pattern of detections across the study area 

indicated that almost all survey segments in the more interior Douglas-fir and mixed 
GENERAL TECHNICAL REPORT PSW-GTR-238 

422

redwood-Douglas-fir regions had detections. We detected fewer fishers in the more 

coastal redwood areas, southern regions near Humboldt Bay and the Eel River 

drainage and the northern region near the Oregon-California border.

We did not detect marten during the 1994 or 1995 track plate surveys. The repeat 

track plate survey conducted in 2004 yielded a total of six marten detections at four 

track plates on two segments in the Klamath region of the ownership. To confirm that 

the tracks recorded on the sooted track plates were indeed marten, we put a camera 

trap at select locations and obtained photographic evidence of marten. With the 

repeat of the track plate survey in 2006, we obtained a total of 13 marten detections at 

nine track plates on three segments. We also confirmed marten presence in 2006 with 

a camera trap. 

We sampled 75 2 km2

 units with cameras between September 2010 and June 

2011. We obtained photographic evidence of fisher at 45 stations (60 percent) and 

marten at eight stations (10.6 percent). Seven out of eight stations had multiple visits 

by marten. Fishers were detected at 75 percent of the stations with marten. The mean 

LTD for marten was 11 days (minimum = 5, maximum = 16 days). 

Discussion

Our surveys indicate that fishers were relatively abundant and well distributed 

throughout the majority of the ownership during the periods of study, suggesting 

current forest management strategies are compatible with fishers habitat needs. 

However, Matthews and others (2011) found that indices alone were not adequate for 

detecting significant changes in a fisher population. Another study over a similar but 

larger geographic region including Redwood State and National Park and Humboldt 

Redwood State Park also indicated that fishers were generally less frequently 

detected in areas closer to the coast (Beyer and Golightly 1996). In addition, this 

broader survey also showed a pattern with few fishers detected in the northernmost 

(Smith River watershed) and southernmost (Eel River watershed) portions of the 

study area. A survey of Redwood National and State Parks provided corroboration 

relative to fisher habitat use in the redwood region (Slauson et al. 2003). An analysis 

of track plate surveys throughout old growth and second growth portions of the park 

indicated that fishers were found more than expected in second growth and less than 

expected in old growth. However, this study also found that fishers were associated 

with structurally complex portions of the second growth stands. 

Our current knowledge of the marten on the study area is very limited. The lack 

of detections of martens during most surveys does not prove that they were absent, 

but the preponderance of negative data certainly indicated that martens were either 

very rare or absent over most of the study area. With the overall dearth of marten 

detections, it is obvious that we lacked the data to assess any trends in the marten 

population, and we are not able to draw any valid conclusions about habitat use. 

Presumably, the martens detected on GDRCo’s ownership in 2004 and 2006 were 

dispersers or peripheral residents from the core population to the east on public lands. 

It may be strictly coincidental, but the potential expansion of martens onto our study 

area occurred at the same time that the regional population of fishers was temporarily 

declining. Our surveys in 2004 indicated a potential decline in fisher abundance as 

evidenced by fewer detections relative to the other survey years. Matthews et al.

(2011) documented a decline in relative abundance of fishers from 1998 to 2005 on 
Ecology and Management of Martes on Private Timberlands in North Coastal California

423

the neighboring Hoopa Valley Indian Reservation. Although we detected martens at 

track plates where fishers had been previously detected, no martens and fishers were 

detected at the same track plate during the same survey period in 2004. Fisher and 

marten were detected at only one track plate during the same survey period in 2006. 

While our survey results do not allow for a definitive assessment of the trend in the 

coastal marten population, it appeared as if martens were dispersing further from 

their core population during the mid-2000s relative to the 1990s. In addition, a 

marten was detected approximately 10 km further to the west in Prairie Creek 

Redwoods State Park in 2009. Regardless of any potential localized expansion of 

martens within GDRCo’s ownership, it remains clear that the marten population was 

small and isolated to only a small portion of the ownership. 

Our recent camera survey data suggests that fishers are relatively abundant 

within the Klamath region of the study and that they also overlapped the marten 

detections more than we observed during the prior track plate surveys. The negative 

interaction between fishers and martens has been noted in numerous locations 

throughout their range and the inverse relationship in abundance between the two 

species may be the result of this interspecific interaction. Although our sample size of 

marten detections was small (eight), we observed fishers at 75 percent of the cameras 

where marten were detected. We observed one bobcat (Lynx rufus) at a station where

we also detected marten and fisher. However, our surveys were not designed to 

attract bobcats and likely do not accurately represent the abundance of bobcats 

present within the managed landscape. Forest management activities that encourage 

growth of other mesocarnivore populations may also be considered a threat to marten 

populations, as some of these species (e.g., fisher and bobcat) may opportunistically 

kill martens when encountered (Hamlin et al. 2010). Loss, modification, and 

fragmentation of habitat are considered significant ongoing threats to the remaining 

population of martens in northwestern California (Hamlin et al. 2010). Past timber 

harvest activities have eliminated much of the late-seral forests in coastal northern 

California, and due to the specialized habitat requirements of martens, such as large 

diameter live trees, snags, and logs, it would likely require decades of little or no 

timber harvest in large areas to develop habitat with the necessary structural 

characteristics to support martens (Hamlin et al. 2010). 

Slauson et al. (2003) indicated that the marten should be considered a ‘highly 

imperiled taxon’ within the redwood region and that Redwood National and State 

Parks (RNSP) contains both the largest remnant patches and the largest total amount 

of old growth redwood forests. They concluded that the long-term persistence of 

martens within the coastal forests of northwestern California will likely require both 

the maintenance of areas currently occupied by martens and the expansion of their 

distribution. They further noted that expansion of the marten’s distribution would 

require the combined effects of the restoration of suitable habitat and functional 

landscape connectivity to enable recolonization of suitable, but currently unoccupied 

habitat. However, they went on to note the critical conservation dilemma that the 

restoration of forest habitats with the structural characteristics necessary to be 

suitable for martens may take decades while the small isolated extant population of 

coastal martens was at serious risk of losing genetic variation or elimination due to 

stochastic demographic or environmental events such as wildfire. This led Slauson et 

al. (2003) to conclude that while restoration efforts within the coastal parks may 

eventually facilitate recolonization by martens, other conservation measures may be 

necessary to re-establish martens due to significant barriers created by large areas of 
GENERAL TECHNICAL REPORT PSW-GTR-238 

424

primarily early-seral forest on private lands, the Klamath River and U.S. Highway 

101. 

Another proactive conservation option that could yield more immediate benefits 

to the marten population is human assisted dispersal. This approach would be similar 

to a reintroduction with the exception that limited evidence suggests that marten are 

currently capable of dispersing to the coastal parks. The marten observed in Prairie 

Creek Redwoods State Park in 2009 is presumably evidence of a naturally dispersing 

animal. However, natural dispersal of male and female martens is impeded by 

considerable ecological and anthropogenic barriers between the existing population 

and available habitat in the coastal parks. These barriers and the abundant 

mesocarnivore population on managed lands could constrain natural establishment of 

a population of martens in the coastal parks. If the martens we detected on private 

managed forests are reproducing, it may be possible to identify dispersers from this 

area and deliberately move them westward to suitable habitat on the coastal parks. 

This strategy is not without complexities that need to be thoroughly explored prior to 

implementation. For example, this project would likely involve multiple partners 

from federal, state, tribal and private organizations, a commitment to funding for 

implementation and monitoring, and some initial basic research such as 

investigations of dispersal of marten. It would also be prudent to evaluate species 

reintroduction guidelines in the context of this specific effort (IUCN 1998). Ideally, 

this collaborative action would increase survival of juveniles relative to that of 

natural dispersers, it would establish a viable population of martens within coast 

redwood habitat in the parks, and it could reduce the vulnerability of the population 

to stochastic events such as disease and wildfire. 

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science symposium: What does the future hold? Albany, CA: U.S. Department of 

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American martens in coastal forests of the Pacific states. Journal of Mammalogy 

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427

A Permeability Study on Salmonid 

Spawning Areas in Northern Humboldt 

County, California1

Claire Knopf2

Abstract

This research was conducted to determine if local salmonid, specifically coho salmon 

(Oncorhynchus kisutch), Chinook salmon (O. tshawytscha), and the steelhead trout (O. 

mykiss), redd location is dependent upon the permeability of the streambed. The study took 

place at four study sites in two coastal drainages in northern Humboldt County, California 

over a 16 month period (June 2004 to October 2005). This period covered pre and post 

spawning conditions, as well as changes in seasonal flow conditions. Sampling grids were 

established at each site to allow for repeatable permeability measurements which ranged in 

number from 37 to 105. Permeability measurements were taken using a battery operated 

pump to draw water through a perforated standpipe driven into the streambed at a depth of 

approximately 25 cm. Study results showed that permeability was not significant in predicting 

redd location. In addition, results showed that permeability measurements varied in orders of 

magnitude within as little as 30 cm. Graphic representations of the spawning areas were 

created using GIS and clearly display the heterogeneity of the streambed. The results of this 

study support the need for further investigation of spawning gravel assessment methods which 

can account for extreme spatial variation while minimizing disturbance to the streambed. 

Key words: fine sediment, monitoring, permeability, redd, salmon, spawning habitat

Introduction

Increased fine sediment levels in rivers and streams are a concern for many land 

managers due to possible detrimental effects on salmonid habitat. The need to 

quantify sediment levels in watercourses serves as a driving force of research and 

monitoring for both private and public resource managers in California’s north coast 

region. While all life stages of salmonids benefit from cool clean water, embryos and 

alevins require adequate flow of oxygenated water through the spawning gravel. 

Permeability, defined as the rate of flow through the substrate, is one parameter that 

has been used as an indicator of spawning gravel quality. 

Excess fine sediment can fill the spaces between gravel in the streambed, or bury 

it entirely, thereby decreasing permeability, impeding the delivery of oxygen, and 

reducing the removal of waste from the redd (Cordone and Kelley 1961). Chapman 

(1988) summarized prior studies showing that the survival of salmonid embryos is 

positively correlated to permeability (r2

 = 0.85). Coble (1961) found that there was no 

relationship between permeability and survival, but rather a relationship between 

apparent velocity and survival. The difference is that permeability describes the 

physical capacity of the substrate to transmit water whereas apparent velocity 

 

1 This article has been adapted from the thesis entitled A permeability study on salmonid spawning 

riffles in the Little River drainage and Cañon Creek in northern Humboldt County, California, by 

C.M. Knopf ; presented December 2010, Humboldt State University, Arcata, California. 2 Green Diamond Resource Company, P.O. Box 68, Korbel, CA 95550. (cmknopf@yahoo.com). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

428

describes the rate of flow of water through a unit area of substrate. While literature 

shows that redd placement is highly correlated with depth, velocity and bed material 

(Bjornn and Reiser 1991), there is continued research investigating the complexity of 

spawning site selection. Ongoing research provides reasons such as stream reach 

sinuosity, population densities and behavior as to why certain areas are more heavily 

utilized for spawning. 

Sampling methods to determine particle size distribution, such as bulk sampling 

(McNeil and Ahnell 1960), or freeze coring (Walkotten 1976), are frequently used to 

quantify substrate composition; however, both methods are destructive to the 

streambed and are more labor intensive than permeability measurements. 

Additionally, while bulk sampling measurements can adequately determine the 

particle size distribution, they do not provide a clear picture of how those particles 

are arranged in the streambed itself. 

The objectives of this study were to determine if streambed permeability explains 

why certain local salmonids, specifically coho salmon (Oncorhynchus kisutch), 

Chinook salmon (O. tshawytscha), and steelhead (O. mykiss) create redds in specific 

locations in the streambed and to create graphic representations which depict the 

spatial variation of permeability within a spawning area. Permeability measurements 

for this study were conducted at sites where historic spawning activity has been 

documented. The hypothesis was that the redd locations and areas of high 

permeability would be positively correlated. 

Methods

Study area 

Streambed permeability measurements were conducted at four study sites 

between June 2004 and October 2005. Study sites were located in two major river 

drainages, the Mad River and Little River, in northern Humboldt County (fig. 1). All 

study sites were on Green Diamond Resource Company property within 

commercially managed forests of coast redwood (Sequioa sempervirens) and 

Douglas fir (Pseudotsuga menziesii). The estimated total annual precipitation (Rantz 

1972) is 165 cm for the Cañon Creek (CC) site in the Mad River drainage and 178 

cm for the three Little River sites: mainstem Little River (MLR), Upper South Fork 

Little River (USFLR), and Lower South Fork Little River (LSFLR). During the study 

period (June 2004 to October 2005), the rainfall totals from the nearest rain gauges to 

each of the study sites indicate that the study period had slightly lower than average 

annual precipitation. 

The four sample areas were selected in areas known to have high spawning 

activity based on results of historical spawning surveys. These watersheds are all 

known to have spawning coho, Chinook, and steelhead. These sites were also chosen 

because of similar geology, gradient and substrate. All four sites are low gradient, 

depositional reaches located within watersheds dominated by formations that consist 

largely of sandstone. 
A Permeability Study on Salmonid Spawning Areas in Northern Humboldt County, California

429

Figure 1—Locations of study sites within Humboldt County, California.

Study design 

The method used to measure permeability in this study was based on those 

developed by Barnard and McBain (1994) and the Mark VI permeability standpipe 

(Terhune 1958). The sample design varied from the original protocol (McBain and 

Trush 2000) by greatly increasing the number of points sampled. Rather than using 

an average of five points at the riffle crest to determine the permeability at a site, a 

1.2 m grid was established across the pool tail/riffle crest area. The number of grid 

points sampled ranged from 37 to 105 depending on the wetted width and total length 

of the riffle at each site and sampling period in which it was sampled. 

Pre-spawning permeability measurements were recorded during summer 2004 at 

multiple stations throughout the grid, within the wetted width. Each permeability 

measurement location was marked with a survey flag. Streambed elevation, data 

point locations, and the wetted perimeters of the study areas were surveyed using a 

Leica TC307 total station. 

Spawning surveys were conducted during the fall/winter 2004 to 2005 run of 

steelhead, Chinook, and coho. Redd locations were marked with bricks and flags and 

later surveyed with the total station. Post-spawning permeability measurements were 

made at grid points and redd locations during early summer 2005. A second postspawning season measurement of permeability at grid points and redd locations was 

made in October 2005 at two of the four study sites: MLR and USFLR. These 

measurements had to occur prior to the onset of rain since increased flows could 
GENERAL TECHNICAL REPORT PSW-GTR-238 

430

potentially mobilize deposited sediments. This second measurement (October 2005) 

was to provide a comparison of seasonal variation at a site and to allow for repeatable 

measurements in exact locations. In addition, 13 grid points per site were selected at 

random and designated to have a 30 cm offset permeability measurement point 

during the October 2005 survey. These offsets were measured in an attempt to 

determine if permeability varies within very short distances across the study area. 

Data analysis

Due to the number of near zero permeability values, a natural log transformation 

of the data was used to attempt to create a normally distributed data set. Even with 

the transformation, the data failed normality tests. Logistic regression was used to 

determine if presence or absence of a redd could be predicted based on the measured 

variables. The variables used in the regression models were permeability (cm/hr), 

distance from the riffle crest (m), and distance from the thalweg (m). 

Spatial analysis of the data was performed using ArcGIS Spatial Analyst to 

interpolate permeability values between measured points at each of the study sites. 

This analysis was done using an inverse distance weighted method (IDW). One 

analysis used the transformed permeability values, and another used ranked 

categories. Permeability ranks were used to relate the data back to its biological 

significance: positive correlation between permeability and survival to emergence 

(Chapman 1988). The ranks represent three categories, defined as Low (L) (<1,000 

cm/hr), Medium (M) (1,000 -10,000 cm/hr) and High (H) (>10,000 cm/hr). Spatial 

patterns were analyzed to determine if salmonids select areas of high permeability to 

create redds. 

The analysis also investigated the within site and between site variation, the 

difference between years, seasonal differences, and offset differences. T-tests were 

used to determine if there were significant differences in permeability between pre 

and post spawning activity, early and late season measurements and original 

sampling locations compared to their corresponding offset points. 

Results

The mapped interpolated surface (fig. 2), shows the location of permeability 

measurements with their corresponding rates (cm/hr) and the location of redds 

observed between January and May 2005. The total number of reds marked at each 

site was (7) CC, (1) LSFLR, (14) MLR, and (9) USFLR. The placement of the redd 

markers on the map are for comparison only as they were not present during the prespawning sampling period. 

Logistic regression models were applied to the data set in order to determine if 

redd location could be predicted based on prior season permeability, distance from 

the thalweg or distance from the riffle crest. The models indicated that permeability, 

distance from the riffle crest and distance from the thalweg were not significant 

predictors in redd placement location. LSLFR was excluded from the models because 

of the occurrence of only one redd and the presence of an area of very high 

permeability created by a half-buried log. 
A Permeability Study on Salmonid Spawning Areas in Northern Humboldt County, California

431

Figure 2—IDW interpolation of pre-spawning substrate permeability at Mainstem 

Little River study site showing sampling locations and permeability rates in cm/hr.

The models were initially run with the exclusion of low permeability values 

(<1,000 cm/hr) in an effort to create a normal distribution of the data. This was based 

on the assumption that fish would not spawn in areas of low permeability due to the 

limited success of their redds in these areas. Upon further analysis of the data, it was 

shown that 61 percent of all redds among all sites were built in areas of low 

permeability; hence it did not seem valid or justified to remove the low permeability 

values from the analysis. 

Although none of the measured variables proved to be significant predictors of 

redd location, models were developed to provide insight to weak trends in the data. 

Multiple versions of the logistic regression model indicated that distance from the 

riffle crest was the most significant factor in predicting the presence of a redd and 

provided a better result than permeability alone. The prediction model showed that, 

for this study, the probability of a redd occurrence is more likely as distance from the 

riffle crest increases. The best fit model, which used categories of permeability, still 

only explained 52 percent of the variation of the data. The logistic regression models 

indicate almost no relationship between likelihood of redd presence and permeability.

Spatial analysis of the study sites showed that all three sites were dominated by 

areas of low permeability prior to the spawning season. There appeared to be no 

statistically significant change to the site permeability after spawning, or as the flows 

continued to drop into October. The relationship between the available area of each 

previously defined category (L, M, H) of permeability and the number of redds 
GENERAL TECHNICAL REPORT PSW-GTR-238 

432

present within that category are highly correlated. This distribution further 

demonstrates the lack of correlation between areas of high permeability and 

occurrence of redds.

The data were then analyzed to investigate if the fish were able to create their 

own permeable areas that would persist into the following sampling period. A paired 

t-test was performed to determine if a change in permeability could be detected 

between pre-spawning activity and post-spawning activity at individual redd 

locations. Although the data do show a small difference in the means before and after 

spawning, there was not a statistically significant difference between pre-spawning 

and post-spawning permeability (p = 0.70, α = 0.05). While pre- vs. post-spawning 

did not show a clear trend, the comparison of early to late summer median values did 

suggest that permeability decreased between May 2005 and October 2005, though 

not statistically significant. The difference in permeability values between the 

original point and the 30 cm offset point measured at MLR and USFLR sites in 

October differed by category (L, M, H) approximately 50 percent of the time. While 

the statistical analysis did not detect a difference in the median values, it is clear from 

the data that there was variation in permeability values within 30 cm. 

Discussion

This study used the following assumptions based on literature and established 

protocols. The first assumption was that the spatial heterogeneity of the gravel in the 

study sites was low enough that a 1.2 m grid was sufficient to capture the variation in 

permeability. Another was that the measurements were independent of flow and 

season. It was evident from the results of this study that the timing of data collection 

has significant effects on both the ability to actually collect the data and its biological 

significance. This study also demonstrated that if permeability sampling occurs 

during times of low flow conditions, then critical spawning locations may be 

excluded from the data set. The permeability testing for this study was not done while 

the redds were active to avoid harming incubating eggs. The redd locations were 

marked as soon as possible and sampled after the fry emerged from the gravel. 

Because of this, it was impossible to know the conditions while the eggs were buried 

in the substrate. The monitoring efforts of many governmental agencies and private 

landowners occur during summer months when weather and work schedules allow. 

While it is important to monitor organisms in natural conditions, it is difficult to 

weigh the importance of data collection and the possible impacts that certain methods 

and timing can have on the organism being studied. It is also important to consider 

the timing and methods of data collection that will provide scientifically sound and 

biologically significant data. 

In addition to timing or seasonality of data collection, the nature of spawning 

adds greater uncertainty in analysis of the data. Redd locations were surveyed as a 

single point, and therefore there are some problems in interpretation of the actual 

influence of the permeability on redd location. The point at which the redd was 

marked and surveyed is at best an estimation of the actual location of egg burial. The 

area of influence of fish activity on or around a redd varies depending on both fish 

and substrate size (Bjornn and Reiser 1991). Based on estimated measurements from 

this study, the average area of fish disturbance of the substrate at a redd was 

approximately 0.88 square meters, but a summary of studies show that redds can 
A Permeability Study on Salmonid Spawning Areas in Northern Humboldt County, California

433

average up to 10 square meters (Bjornn and Reiser 1991). Salmonids have the ability 

to clean the gravel by removing the fine particles while digging their redds. Chinook 

and steelhead have the ability to reduce the amount of fines within a spawning area 

by a range of 7 to 23 percent (Everest et al. 1987). It is unknown if the sites that were 

marked as redds were actually used for spawning, as fish were not present when the 

redds were marked. Fish can dig “test redds” and can also superimpose redds. While 

every effort was made to mark each and every redd location, there may have been 

some that were missed, or were not actual redds, but rather a test redd. Every location 

marked was assumed to be a single true redd. The sites were visited on a regular basis 

and redds were marked as soon as they were visible. Due to low visibility in the 

water during higher flows and the necessity to not disturb the fish during active 

spawning, the redds were marked as soon as it was feasible. In future studies, redd 

measurements such as total surface area, pot dimensions, and tailspill dimensions 

should be observed and recorded. 

There were questions that arose with the method and predetermined protocol as 

the field investigation continued. One issue was the depth at which the measurements 

were taken. In some cases, the depth that the permeability measurement was made 

may not necessarily be the depth at which the eggs are buried. The depth in the 

protocol comes from an average depth of salmonid species; therefore, due to differing 

geology of the underlying sediments, particle size of the streambed and fish size, the 

depth of measurement may not accurately represent the permeability of the egg 

pocket. 

The two study sites, MLR and USFLR, in which 30 cm offsets and late summer 

measurements were taken showed a decrease in permeability between early and late 

season measurements. The lower permeability in late summer may be attributed to 

infiltration of fines and organic matter as both surface flow and hyporheic flow 

decrease. The data also indicated that large variations of permeability can occur 

within a short distance. Coble (1961) found that permeability values varied at sites 

only 15 cm apart. Based on results from Kondolf et al. (2008) the zone of influence 

for each standpipe was less than a 20 cm radius. Because of this variation, and lack of 

potential spatial dependence, IDW may not have been the appropriate approach to 

analyze these data, though it appeared to be the best available method, and did 

provide insight into the complex distribution of the streambed matrix. 

Another issue encountered with the data is determining the source of variability, 

as shown in the permeability maps. The streambed is a very dynamic system and is 

constantly undergoing change. The spatial variation could be due to hyporheic flow, 

bed movement, surface flow, fish disturbance, or disturbance due to the sampling 

method. The variation in fine sediment in streambeds is so large that distinguishing 

between background and land-use augmented amounts is difficult (Adams and 

Beschta 1980). It is also hard to determine if the variation is an artifact of the method 

itself. Kondolf et al. (2008), using the same method, found that up to 68 percent of 

water that entered the standpipe may actually be surface water leakage along the edge 

of the pipe. They found that this was common in course gravel installations. 

Installation of the standpipe into the streambed often opened up pockets free of 

material allowing for excess water to move along the edge of the pipe. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

434

Conclusion

The results of this study suggest that redd location is not correlated with prior 

season substrate permeability as determined from a 1.2 m grid. The variation shown 

within study sites suggests that results are dependent upon where the standpipe is 

placed within a study area. The large variation suggests that many more sample 

points would be required to account for, or at least minimize, the variation between 

measurements. If more sample points are required, other issues arise. The 

measurements would no longer be independent due to influence of one point on 

another in close proximity. More sample points would also negate the major benefit 

of this method in that it is assumed to be a rapid sampling technique. If a large 

number of samples would be required in order to address variation, then the method 

is no longer a rapid and inexpensive approach. 

This study provides graphic representations of the heterogeneity of the streambed 

and indicates that redd location is not correlated with permeability. Regardless of the 

imperfections of the method, study results show the recorded permeability 

measurements indicate great variation in subsurface conditions. While monitoring 

permeability rates can describe general bed conditions in specific locations, 

individual or even average permeability values from individual sites should not be 

used to characterize spawning gravel conditions for watersheds or even smaller 

stream reaches.

References

Adams, J.N.; Beschta, R.L. 1980. Gravel bed composition in Oregon coastal streams. 

Canadian Journal of Fisheries and Aquatic Sciences 37: 1514-1521.

Barnard, K.; McBain, S. 1994. Standpipe to determine permeability, dissolved oxygen, 

and vertical particle size distribution in salmonid spawning gravels. Fish Habitat 

Relationships Technical Bulletin No. 15. U. S. Department of Agriculture, Forest 

Service. 

Bjornn, T.C.; Reiser, D.W. 1991. Habitat requirements of salmonids in streams. In: 

Meehan, W.R., editor. Influences of forest and rangeland management on salmonid 

fishes and their habitats. Special Publication No. 19. Bethesda, MD: American Fisheries 

Society: 83-138.

Chapman, D.W. 1988. Critical review of variables used to define effects of fines in redds 

of large salmonids. Transactions of the American Fisheries Society 117: 1-21.

Coble, D.W. 1961. Influence of water exchange and dissolved oxygen in redds on survival 

of steelhead trout embryos. Transactions of the American Fisheries Society 90: 469-

474.

Cordone, A.J.; Kelley, D.W. 1961. The influence of fine sediment on the aquatic life of 

streams. California Fish and Game 47: 189-228.

DeVries, P. 1997. Riverine salmonid egg burial depths: review of published data and 

implications for scour studies. Canadian Journal of Fisheries and Aquatic Sciences 54: 

1685-1698.

Everest, F.L.; Beschta, R.L.; Scrivener, J.C.; Koski, K.V.; Sedell, J.R.; Cederholm, C.J. 1987. 

Fine sediment and salmonid production: a paradox. In: Salo, E.O.; Cundy, T.W., 

editors. Streamside management: forestry and fishery interactions. Seattle, WA: College 

of Forest Resources, University of Washington: 98-142.
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435

Kondolf, G.M.; Williams, J.G.; Horner, T.C.; Milan, D. 2008. Assessing physical quality of 

spawning habitat. American Fisheries Society Symposium 65. 26 p.

McBain, S.; Trush, W. 2000. Permeability protocol. Green Diamond Resource Company. 7 

p.

McNeil, W.J.; Ahnell, W.J. 1960. Measurement of gravel composition of salmon stream 

beds. Circular No. 120. Seattle, WA: University of Washington, Fisheries Research 

Institute. 3 p.

Rantz, S.E. 1972. Mean annual precipitation in the California Region. U.S. Geological 

Survey. 1:1,000,000 map.

Terhune, L.D.B. 1958. The Mark VI groundwater standpipe for measuring seepage 

through salmon spawning gravel. Journal of the Fisheries Research Board of Canada 

15: 1027-1063.

Walkotten, W.J. 1976. An improved technique for freeze sampling streambed sediment.

Gen. Tech. Rep. PSW-281. Berkeley, CA: U.S. Department of Agriculture, Forest 

Service, Pacific Southwest Research Station. 11 p.

437

Mesocarnivores as Focal Species for the 

Restoration of Post-Logging Second 

Growth in the Northern Redwoods

Keith M. Slauson1 

Abstract

The management of second growth forests to accelerate the restoration of late-successional 

and old growth characteristics will be one of the greatest challenges for conservation in the 

redwood region over the next century. In the redwood region, the largest complex of protected 

areas exists in the north, however >50 percent of these forest reserves are composed of 

logged, degraded second growth forests. Strategic restoration actions have the potential to 

accelerate the restoration of old growth forest characteristics and the old growth forest species 

assemblage that requires these features. Restoration actions in degraded aquatic habitats over 

the last two decades have been guided by the needs of several salmonid species. Currently

there are no guidelines for how to strategically restore second growth forests based on the 

needs of old growth dependent wildlife species. We developed a focal species approach to 

provide restoration guidelines based on the spatial and compositional needs of the Humboldt 

marten (Martes americana humboldtensis), a mesocarnivore sensitive to the loss and 

modification of old growth forest conditions. In addition, two marten predators – the fisher 

(Martes pennanti) and bobcat (Lynx rufus) – were selected because they likely expanded their 

range or abundance, respectively, following the extensive logging of the 1900s. Successful 

restoration of the old growth forest mesocarnivore assemblage in the redwood region will 

require an increase in the amount and connectivity of old forest conditions and reduction of 

road densities which should result in the expansion of the remnant Humboldt marten 

population and decreases in the range and abundance of the fisher and bobcat. 

Key words: Martes, Humboldt marten, marten, mesocarnivores, second growth, restoration, 

focal species, redwood forest management

Introduction

State of forest reserves of the redwood region 

More than 95 percent of the primary, old growth, forests of the redwood region 

have been logged (Fox 1996, Thornburg et al. 2000) and dramatically altered from 

what it resembled in pre-European settlement times. Forest reserves, defined here as 

tribal, state, or federal agency administered lands with the primary goal of 

maintaining or restoring late-successional and old growth forest characteristics, 

include <20 percent of the redwood region but are composed of >50 percent logged 

and degraded, second growth forests (Noss et al. 2000). The greatest concentration of 

forest reserves occurs in the northern redwood region. Currently Redwood National 

Park includes >50,000, California State Parks >20,000, Yurok Tribe >15,000 and the 

Six Rivers National Forest >10,000 ac of fog-influenced second growth forest 

(California State Parks 2010, Keyes 1995). Collectively, the degraded portions of 

 

1 USDA Forest Service, Pacific Southwest Research Station, Redwood Sciences Laboratory, 1700 

Bayview Drive, Arcata, CA 95521. (kslauson@fs.fed.us). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

438

these forest reserves provide the greatest opportunity to restore a large-scale example 

of the fog-influenced forest ecosystem in the redwood region. 

Focal species approach for restoration design and 

biodiversity conservation 

Attempts to restore such a large amount of second growth forest to old growth 

conditions are unprecedented globally. Restoration requires that either historical or 

desired conditions be defined and methods identified to reconstruct or accelerate the 

restoration of compositional and spatial elements towards those conditions. While 

studying the structure and composition of remnant stands of old growth can provide 

important information to guide the development of silvicultural treatments, this 

information alone will not adequately address the needs of many wildlife species. A 

focal species approach is necessary to identify key limiting compositional features 

and design restoration actions at large enough spatial. The first step in the application 

of the focal species approach is to select the subset of species most sensitive to the 

loss and modification of the compositional and spatial characteristics of old growth 

forests. The habitat needs of the focal species are then used to guide restoration at all 

relevant spatial scales (Lambeck 1997). By selecting the suite of species most 

sensitive to the compositional elements and spatial amounts of old growth forests, 

they act as “umbrellas” for species that are less sensitive. 

The focal species approach has already been in practice in guiding restoration 

actions in the stream and rivers of the redwood region. Salmonids, such as Coho 

(Oncorhynchus kisutch) and Chinook (O. tshawytscha), have been focal species and 

compositional elements, such as suitable spawning gravels and more recently instream large woody structures have been targets for restoration where they have been 

degraded or lost. Meaningful spatial scales for salmonid habitat restoration have 

focused on entire watersheds to reduce sedimentation sources and improving overall 

habitat conditions with the goal of providing the amount of habitat to support 

populations similar to those supported by historical conditions. Restoration actions 

for terrestrial habitats have been slower to develop, due in part to the lack of 

information linking terrestrial wildlife to critical habitat characteristics and the 

growing acceptance that thinning trees in forest reserves is an essential tool for 

accelerating the restoration of historical and desired conditions (DeBell et al. 1997, 

Tappeiner et al. 1997). Given the scale of the challenge of restoring large areas of 

second growth forest with limited resources, a strategic focal species approach will 

be necessary to optimize the goals of restoring old forest characteristics and the 

species that most require them. The objective of this paper is to identify a suite of 

focal species and use them as the basis for developing strategic restoration guidelines 

for the terrestrial second growth forests of the northern redwood region. 

Methods

Process for selecting focal species

I first identified the suite of species that are unlikely to persist in the redwood 

region without restoration of features of old growth forests. Emphasis was given to 

taxa which are endemic or near-endemic, >75 percent of their distribution in the 

redwood region. However, taxa at risk (e.g., threatened or endangered) over larger 
Mesocarnivores as Focal Species for the Restoration of Post-Logging Second Growth in the 

Northern Redwoods

439

areas were also considered. I did not consider populations that are secure, unless their 

presence was identified as being a threat to the persistence of a species at risk. 

Second, I identified the processes that have contributed to the decline in the 

abundance or distribution of each candidate species (fig. 1). Species with similar 

responses to processes were grouped and for each process, the most sensitive to the 

process was selected. 

Figure 1—Schematic representation of the steps for the selection of focal species 

and development of restoration guidelines for reconstructing critical compositional 

and spatial habitat elements; modified from Lambeck (1997). 

Steps for designing restoration guidelines 

Landscape restoration and reconstruction will be required for species that are 

limited by (1) a shortage of critical resources, (2) an inability to move between 

suitable habitat patches, or (3) insufficient habitat to meet their resource needs or to 

support a viable population (Lambeck 1997). Once focal species were selected, the 

first step was to review and synthesize relevant literature on their ecology to identify 

limiting resources, area limitations, and dispersal limitations. Because everything

about a focal species’ ecology may not be known, areas of uncertainty were 

identified. Limiting resources are those that are linked to key life history 

requirements and lacking them precludes the species occurrence. Area limitations are 

those that lead to stable occupancy of at least one home range or breeding territory.

Dispersal limitations are considered for both within subpopulation movements of 

individuals and between subpopulation movements. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

440

Results

Focal species selection

Cooperider et al. (2000) identified 18 terrestrial or amphibious vertebrate taxa 

endemic or near-endemic to the redwood region. Of the nine that occur in the 

northern redwood region, I conclude only the Humboldt marten (Martes americana 

humboldtensis) is not likely to persist without restoration actions. The Humboldt 

marten has been extirpated from >95 percent of its historical range and persists in a 

single population numbering <100 individuals (Slauson et al. 2009b). The remaining 

eight near-endemic vertebrate taxa are either not strongly associated with old growth 

forest characteristics (e.g., fog shrew [Sorex sonomae sonomae], Pacific coast 

Aquatic garter snake [Thamnophis attratus attratus], California giant salamander 

[Dicamptodon ensatus]), have populations supported on forests managed for timber 

production (e.g., California tree vole [Arborimus pomo] ), or have comparatively 

secure populations in forest reserves (e.g., Del Norte salamander [Plethodon 

elongatus], Wandering salamander [Aniedes vagrans]; Cooperider et al. 2000). In 

addition to the marten, the marbled murrelet (Brachyramphus marmoratus) and 

northern spotted owl (Strix occidentalis caurina) are of conservation concern and 

have significant portions of their populations in the redwood region that likely 

influence their population status beyond the redwood region. While spotted owls and 

marbled murrelets are also potential candidates as terrestrial focal species, the 

remainder of this paper focuses on mesocarnivores.

The loss of old growth forest in the redwood region is the chief process that has 

driven the decline of the Humboldt marten (Zielinski et al. 2001). While extensive 

trapping in the late 1800s and early 1900s was the initial driver of population decline 

for the Humboldt marten (Grinnell et al. 1937), despite the closure of the trapping 

season for >50 years or approximately 10 marten generations only a single 

population remains in <5 percent of its historical range. The remnant marten 

population has been unable to recolonize adjacent areas of second growth forest, or to 

disperse across second growth landscapes to recolonize suitable old growth patches 

(Slauson and Zielinski 2003). 

In addition to the direct loss of old growth forests, the fragmented state of the 

remaining old growth forests further threatens population stability and growth for the 

marten. Highly fragmented habitat is more likely than contiguous old growth habitat 

to support unstable marten occupancy (Slauson et al. 2010). At the landscape scale, 

the largest remaining patches of old growth habitat suitable for martens to recolonize 

are currently too far apart and exist in a second growth matrix not compatible for 

marten movement and dispersal. 

Second growth forests in the northern redwood region up through at least 60 

years old support a highly altered mesocarnivore assemblage, dominated by species 

known to or capable of preying on martens. The conversion of the northern redwood 

region from primarily old growth to young second growth has facilitated the 

expansion of the range of the fisher (Martes pennanti) and increases in the abundance 

and distributions of bobcats (Lynx rufus), gray fox (Urocyon cinereoargenteus). 

Grinnell et al. (1937) identified the range of the fisher as distinctly inland from the 

coast and largely on the eastern edge of the redwood region. While some have 

questioned Grinnell et al.’s (1937) historical range of the fisher in coastal California 

(DFG 2010), the absence or rarity of fishers in coastal forests is both consistent with 
Mesocarnivores as Focal Species for the Restoration of Post-Logging Second Growth in the 

Northern Redwoods

441

their continental distribution (Giblisco 1994, Proux et al. 2000) and present day 

habitat associations from surveys conducted in the redwood region (Klug 1996, 

Slauson and Zielinski 2003). In the last century, fishers have expanded their range 

west and can now be detected near the ocean in second growth forests (Slauson and 

Zielinski 2003). Surveys within the largest remaining patches of old growth forest, 

including the area occupied by the remnant marten population, indicate fishers either

do not occupy or only use stands near their edges (Slauson and Zielinski 2003). 

While historical information on range and abundance for bobcats and gray foxes is 

not as detailed as that for fishers, the pattern of their detections occurring largely in 

second growth but rarely in the cores of remnant old growth patches mirrors that of 

the fisher (Slauson and Zielinski 2007; K. Slauson, unpublished data). 

Of the six studies reporting 57 predation events on marten in North America, 

mammalian carnivores were responsible for 75 percent, with bobcats (44 percent), 

coyotes (19 percent), and fishers (11 percent) the most frequent predators (Bull and 

Heater 2001, Ellis 1997, Hodgeman et al. 1997, McCann et al. 2010, Raphael 2004, 

Thompson 1994). Restoration actions will need to also result in the reduction in 

occupancy and abundance of marten predators in order to be successful in restoring 

martens and the coastal old growth mesocarnivore assemblage. Therefore, I propose 

the fisher, a forest specialist, and bobcat, a habitat generalist, as additional focal 

species.

 

Resource limitations 

Second growth forests are depauperate of two critical resources for martens, 

dense shrub cover and suitable resting/denning structures. Restoration prescriptions 

for critical resources should be applied at the stand scale. Larger spatial 

considerations will follow, see Area Limitations below, such that stand scale 

restoration prescriptions can be aggregated to meet larger scale needs of focal 

species.

Dense, spatially extensive shrub cover is a critical component of suitable habitat 

for the Humboldt marten and >95 percent of all detections (n = 50; Slauson et al. 

2007, Slauson et al. 2009b), rest sites (n = 55; Slauson and Zielinski 2009a), and 

active telemetry locations (n = 235; K. Slauson unpublished data) have occurred in 

stands that support it. Dense, spatially extensive shrub cover is a common understory 

structural layer in mature forests in the northern redwood region (Sawyer and others 

2000). Martens typically occupy old growth stands with shrub layers that average 

>70 percent cover, are dominated by long-lived shade tolerant species (e.g., 

evergreen huckleberry [Vaccinium ovatum], salal [Gaultheria shallon]), and form 

continuous structural layers that spread throughout and between adjacent forest 

stands (Slauson et al. 2007). Shrub layers provide multiple direct and indirect 

benefits to martens including: berries for food, overhead cover from avian predators, 

cover from larger-bodied mesocarnivores, and mast that supports prey population. 

Slauson and Zielinski (2007) measured shrub cover in >800 plots in northwestern 

California and found that dense shrub cover has been significantly reduced in logged 

second growth forests <20 km from the coast. 

Martens use resting structures daily between forging bouts to provide secure 

locations to sleep, conserve energy, and in some cases consume prey. Martens show 

little short-term re-use of structures and thus require many resting structures 
GENERAL TECHNICAL REPORT PSW-GTR-238 

442

throughout their home ranges to provide resting locations close to where they are 

foraging and to provide for seasonal thermoregulatory needs (e.g., platforms in 

summer for cooling, cavities and chambers in winter to provide refuge from 

precipitation and warmth; Schumacher 1999, Taylor and Buskirk 1994, Wilbert 

1992). Humboldt martens select large live and dead woody structures, including 

snags, logs, and live trees, that are typically >90 cm in diameter (Slauson and 

Zielinski 2008). Slauson et al (2010) found second growth stands in the Lost Man 

creek watershed and Mill creek watershed contain no suitable live tree structures and

<10 percent the density of suitable snag structures compared to old growth stands 

occupied by martens. Further, compared to marten occupied stands, suitable downed 

log densities were similar in the older second growth stands in the Lost Man creek 

watershed but were <20 percent of the densities in the Mill creek watershed. Natural 

recruitment of suitable resting structures will likely not begin for >2 centuries, as 

most resting structures used by martens were of greater age when living (Slauson and 

Zielinski 2009a). 

Area limitations 

In California, martens maintain home ranges of approximately 300 ha to provide 

for their year-round resource needs (Spencer et al. 1983). While Humboldt martens 

use stands other than old growth for foraging, a large patch of old growth forest is a 

prominent component of their home ranges (K. Slauson unpublished data). Humboldt 

martens are highly selective for patches of old growth habitat >100 ha (Slauson et al. 

2007). Patches <150 ha supported unstable marten occupancy (Slauson et al. 2009b).

Restoration actions that enlarge existing small patches of old growth habitat may be 

the most effective in the short term while designing stand scale restoration actions to 

aggregate into patches of >150 ha will provide for the development of patches that 

cam become the cores for new home ranges once suitable conditions are restored.

Dense road networks are ubiquitous in second growth areas. The Humboldt 

marten makes little use of roads (Slauson et al. 2010) and does not occupy areas with 

high roads densities (Slauson 2003). Roads fragment the dense understory shrub 

layers and create networks of edge habitat that has no natural precedent in coastal 

forests. Slauson et al. (2010) found that >75 percent of habitat generalist species 

detections occurred on roads and were dominated by bobcats and gray foxes. The 

development of roads created networks of edge habitat that has likely facilitated the 

increase in distribution and /or the abundance of bobcats and gray foxes in second 

growth landscapes. Furthermore, encounters between martens and potential predators 

on roads may lead to higher rates of predation as martens will be farther from escape 

cover (e.g., tree boles for climbing) than encounters in forest interiors. Without 

minimizing or eliminating road networks, martens may not become re-established in 

areas where other suitable habitat characteristics have been restored. 

Dispersal limitations 

Occupied marten home ranges typically do not occur in isolation from other 

adjacent marten home ranges, thus >150 ha patches should be aggregated into local 

clusters of ≥ four patches to provide enough habitat to support adjacent home range 

establishment by multiple individuals of each sex. While martens are capable of long 

distance dispersal movements >50 km (e.g., Slough 1989), most martens that 

disperse and successfully establish home ranges move <5 km (Johnson et al. 2009).
Mesocarnivores as Focal Species for the Restoration of Post-Logging Second Growth in the 

Northern Redwoods

443

Patch clusters should be located as close as possible to either occupied habitat or 

adjacent to other clusters < 5 km. Finally, initial restoration actions should be done in 

areas as proximal as possible to currently occupied habitat to increase the probability 

that restoration areas can be recolonized by martens once suitable conditions return.

Restoration design guidelines 

Restoration actions that will benefit the regeneration of dense shrub cover 

include reducing overhead cover from trees by thinning. Thinning treatments 

conducted 30 years ago (see Keyes 2005, Veirs 1986) have restored shrub cover to a 

median value of 55 percent compared to <10 percent in unthinned control stands 

(Slauson et al. 2010). Recently thinned stands (2 to 7 years ago) in the Mill creek 

watershed of Del Norte Coast Redwood State Park have also significantly increased 

shrub cover to a median of 30 percent compared to <10 percent in unthinned stands. 

Without canopy thinning, most stands would likely lose shrub cover completely if 

left to self-thin, requiring re-establishment of shrub species from seed and many more 

decades before the shrub layer is restored. 

Three methods may increase the number of resting structures in second growth 

habitats: enhancement, augmentation, and deployment of surrogate structures. 

Because these methods have not been developed for marten in the redwood region, 

these efforts should be initially undertaken in research and demonstration mode. 

Enhancement refers to creating suitable resting locations within existing structures 

such as using chainsaws to create cavities in downed logs and live trees of suitable 

size (e.g., Brown 2002). Augmentation refers to the transport of suitable structures to 

sites where they are deficient. This is likely the most expensive option as it requires 

both the acquisition of large diameter logs and deposition in target sites, necessitating 

the use of heavy machinery. The deployment of surrogate structures involves the 

building of artificial resting structures and placement in target stands. In Scotland, 

biologists have developed a marten den box has successfully provided the European 

pine marten with resting and even denning locations in forest stands where they are 

lacking (VWT 2010). Enhancement and the use of surrogate structures are likely the 

two techniques that if used in combination will provide the most cost effective 

methods to provide resting structures at large spatial scales. However, augmentation 

may be necessary in large areas where large diameter structures are particularly 

scarce. 

Implementation and monitoring 

One of the most critical phases of restoration projects is the monitoring that 

follows implementation to provide critical feedback to guide future restoration 

actions. While actions intended to restore critical habitat elements where they have 

been lost is founded in the ecology of the most sensitive species, success is not 

guaranteed. Therefore, post implementation monitoring will be critical for evaluating

restoration actions and to provide any refinement for future restoration actions. 

Discussion

The degraded state of much of the second growth forests in reserves cannot be 

left unmanaged due to the presence of many characteristics that are far outside the 

natural range of variability. Tree densities and species compositions depart greatly 
GENERAL TECHNICAL REPORT PSW-GTR-238 

444

from those present in mature and old growth forests (Keyes 1995, Veirs 1986). Just 

as the threats of sediment delivery lead to actions to decommission dense roads 

networks in these forests for restoring salmonid populations, terrestrial habitats too 

will need restoration actions to reconstruct critical compositional and spatial elements 

to accelerate the restoration of habitat for sensitive the terrestrial fauna of redwood 

forests. In combination with silvicultural objectives and aquatic focal species 

restorations actions, an approach using terrestrial focal species provides a 

comprehensive and strategic basis for designing restoration actions with the best 

chance for restoring old growth forest communities and ecosystems northern 

redwood region. 

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447

Northern California Redwood Forests 

Provide Important Seasonal Habitat for 

Migrant Bats

Theodore J. Weller1 and Craig A. Stricker2

Abstract

Bats are known to roost in redwood forests year-round, but their activities outside the summer 

season are poorly understood. To improve understanding of the use of redwoods by resident 

and migrant bats, we conducted 74 mist net surveys between February 2008 and October 

2010. Captures were dominated by Yuma myotis (M. yumanensis) in the summer and silverhaired bats (Lasionycteris noctivagans) in the winter. During November-February, silverhaired bats, accounted for 78 percent of 23 captures and male:female sex ratio was (9:9). By 

contrast, during June-August, silver-haired bats accounted for 13.8 percent of 269 captures 

and sex ratios were highly male skewed (34:3). In combination with other regional 

information, this indicates that female silver-haired bats migrate to redwood forests. To infer 

summer locations of bats captured in redwood forests, we analyzed stable isotopes of 

hydrogen, carbon, nitrogen, and sulfur in their fur. Despite spatial segregation between male 

and female silver-haired bats during presumed molt period, we did not find differences 

between the sexes in range of isotope values in their fur. Nor were their values different from 

Yuma myotis. Our findings highlight some of the challenges in using stable istotope analysis 

to infer migratory pathways in bats.

Key words: bats, Lasionycteris noctivagans, Lasiurus cinereus, Myotis yumanensis, redwoods, 

stable isotopes, migration, winter

Introduction

Studies of bats in redwood forests have focused largely on their roosting ecology, 

in particular their use of basal hollows (Fellers and Pierson 2002, Gellman and 

Zielinski 1996, Rainey et al. 1992, Zielinski and Gellman 1999, Zielinski et al. 2007). 

A novel result of two of these studies was documentation of bat activity during 

winter (Gellman and Zielinski 1996, Zielinski and Gellman 1999). Autumn–spring is 

the period when temperate-zone bats engage in important activities that critically 

affect their annual energy balance such as migration, mating, and hibernation (Weller 

et al. 2009). 

The silver-haired bat (Lasionycteris noctivagans, hereinafter LANO) is a treeroosting species that is thought to undertake seasonal migrations between its summer 

and winter habitat (Cryan 2003). Male and female LANO are geographically 

segregated during the summer months throughout much of North America (Cryan 

2003). In Douglas fir forests of northwestern California (hereinafter NWCAL) 

LANO was one of the most frequently captured species during summer; but captures 

were > 95 percent males (TJW unpublished data). The limited capture work in 

 

1 USDA Forest Service, Pacific Southwest Research Station, Arcata, CA. (tweller@fs.fed.us). 2 U.S. Geological Survey, Denver Federal Center, Denver, CO. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

448

NWCAL from October-March, suggested that female LANO were more abundant 

during this time period (Zielinski and Gellman 1999). However, sample sizes were 

too low to accurately estimate sex ratios by season. Therefore, an important objective 

of this study was to verify whether the proportion of female LANO increased during 

autumn–spring in redwood forests of NWCAL. If so, it would suggest that female 

LANO move to the redwoods for the purposes of wintering, and presumably, mating. 

We investigated the use of stable isotopes to help determine movement patterns 

and infer the summer range of LANO individuals that used NWCAL during winter. 

Hydrogen isotopes (δD) are commonly employed to infer migratory movements of 

vertebrates by exploiting characteristic latitudinal and elevational structure in the 

isotopic composition of precipitation (Bowen et al. 2005, Hobson and Wassenaar 

1997). Because tissues such as hair and feathers are metabolically inert, stable 

isotope ratios reflect the geographic areas where they were synthesized rather than 

where they are collected (Hobson and Wassenaar 1997). Bats generally molt their fur 

once per year during late-summer (Constantine 1957) and δD analysis has been used 

to estimate minimum distances traveled between the summer range and location at 

time of fur collection (Cryan et al. 2004). 

We explored the use of carbon (δ13C), nitrogen (δ15N), and sulfur (δ34S) isotopes 

to provide additional information and potentially improve the accuracy of geographic 

inference (Rubenstein et al. 2002, Wunder et al. 2005). We were particularly 

interested in evaluating the efficacy of δ34S because of the proximity of our study 

area to the Pacific Ocean (Zazzo et al. 2011). The ocean represents a uniform 

reservoir of sulfate with a sulfur isotopic composition of about 21‰. Due to sea 

spray effects, we expected bats that grew their fur in redwood forests to have higher 

values of δ34S than individuals that grew their fur further from the ocean. 

Our use of stable isotopes to infer seasonal movements of bats focused on 

quantifying the range of values for each isotope within the local population and 

comparing it against expectations of their movements. We speculated that fur 

samples from female LANO would have a wider range of isotope values than for 

males because they are largely absent from NWCAL during summer. However 

whether male LANO were year-round residents of NWCAL is uncertain. Therefore, 

we attempted to constrain inference by quantifying baseline levels of isotopic 

variation in a summer resident species, Yuma myotis (Myotis yumanensis, hereafter 

MYYU), while remaining cognizant of inter-species differences (Britzke et al. 2009).

The seasonal movements of MYYU are largely unknown (Verts and Carraway 1998) 

but based on size and ecomorphology, MYYU is not expected to travel long 

distances between summer and winter habitat. Accordingly, we expected narrower 

ranges of isotopic values in year-round resident MYYU than female LANO. If male 

LANO were summer residents of NWCAL, we expected their range of isotopic 

values to be similar to MYYU. If instead, the range of isotopic values in male and 

female LANO were similar to each other but different from MYYU, this might 

indicate that both sexes are moving to the redwoods from summer habitat elsewhere. 

Our study had three interrelated goals: 1) characterize year-round bat activity in 

redwood forests of NWCAL; 2) determine whether female LANO use redwood 

forests as wintering habitat; 3) evaluate the use of stable isotopes to infer summer 

locations of LANO and MYYU in NWCAL.
Northern California Redwood Forests Provide Important Seasonal Habitat for Migrant Bats

449

Study area 

Our study was conducted in redwood forests of Mendocino, Humboldt, and Del 

Norte Counties in NWCAL (fig. 1). We selected 18 sites in or adjacent to redwood 

forests based on ease-of-access and the potential to provide conditions conducive to 

bat capture during all seasons of the year. All sites were stream reaches ≤ 300 m long 

that generally retained surface flow throughout summer and early autumn, yet were 

still wadeable during high flows in winter. Capture sites were located on public 

(California State Parks, Redwood National Park) and private lands at distances of 1.4

to 31.4 km from the Pacific Ocean (fig. 1).

Figure 1—Location of bat captures sites relative to redwood forest habitat in 

northwest California. 

Methods

Field 

We captured bats by setting two to four (mean= 3.6 SD=0.55) 2.6 m high mist 

nets over the creek at each site. We selected the number and length (6 to 12 m) of 

mist nets to best suit the physical characteristics of each site. Mist nets were opened 

at sunset for a minimum of 2 hours or until at least 1 hour had passed since the last 

capture. Individuals were identified to species based on examination and 
GENERAL TECHNICAL REPORT PSW-GTR-238 

450

measurement of external morphological features; MYYU was identified using the 

methods of Weller et al (2007). Sex was determined via external inspection (Racey 

2009). We clipped 0.3 to 6 mg of fur from the dorsum of LANO and MYYU 

individuals for subsequent stable isotope analyses. All bats were released on site the 

same night. 

Stable isotope analyses 

Fur samples were triple-washed in a 2:1 chloroform/methanol solution, air dried, 

and weighed into silver (δD) and tin capsules (δ34S and δ13C/ δ15N). Samples were 

allowed to air equilibrate to ambient laboratory conditions for ≥ 2 weeks prior to δD

analyses (Wassenaar and Hobson 2003). All isotopic measurements were made by 

continuous flow isotope ratio mass spectrometry, with results reported in delta (δ)

notation, expressed as parts per thousand (‰) relative to internationally accepted

scales; δD data are specific to non-exchangeable hydrogen. Mean differences

between duplicate samples from the same individual were ± 4.1‰ for δD (n = 29), 

±0.2‰ for δ13C (n=6), ± 0.1 ‰ for δ15N (n=6), and ± 0.3‰ for δ34S (n=11); quality 

control and assurance was verified by repeated analyses of an in-house keratin 

standard, as well as primary standards analyzed as unknowns. 

Data analyses

We tested whether monthly sex ratios of LANO or MYYU differed from 50:50 

using the conditional test (Przyborowski and Wilenski 1940). The conditional test 

assumed that the observed count followed a Poisson distribution for both sexes and 

months with counts for sexes within a month being independent. We used a 2-factor 

Analysis of Variance (ANOVA) with species and sex as fixed effects to evaluate 

differences in isotope values. The ANOVA assumed separate variances for each

species and residuals for each isotope and sex-species combination were normally 

distributed. We evaluated differences in least-square means using a t-test with TukeyKramer adjustment of p-values; all tests performed were 2-tailed.

Results

Seasonal activity patterns

Between February 2008 and October 2010 we conducted 73 mist net surveys and 

captured a total of 476 bats, with a mean of 6.5 (SE = 0.78) per survey. Overall we 

captured 10 species of bats including Eptesicus fuscus (n = 15), Lasiurus blossevillii

(n =2), L. cinereus (n = 36), LANO (n=116), Myotis californicus (n = 27), M. evotis

(n=2), M. lucifugus (n=22), M. thysanodes (n= 7) M. volans (n =7), and MYYU (n = 

129). An additional 113 individuals were identified only as either M. lucifugus or 

MYYU. Bats were captured in every month surveyed though overall capture rates 

were higher during May-July (fig. 2). MYYU, or individuals identified as either 

MYYU or M. lucifugus, comprised 65 percent of 269 bats captured during JuneAugust. From May-September. females composed 36 to 63 percent of monthly 

captures of MYYU (fig. 3), and sex ratios did not differ significantly from 50:50 in 

any month (range: p=0.092 in Oct to p>0.999 in May). LANO was the second most 

frequently captured species and capture rates were relatively consistent throughout 

the year (fig. 3). LANO comprised 79% of 34 bats captured during November–

March. Sex ratios of LANO were male-biased in March-July (all p≤0.031) and to a 

lesser extent in August (p=0.065). Sex ratios of LANO were not different than 50:50 
Northern California Redwood Forests Provide Important Seasonal Habitat for Migrant Bats

451

Figure 2—Number of bat captures per survey (all species combined) by month in 

redwood forests of northwestern California 2008 – 2010. Boxes represent 1st and 3rd

quartiles, horizontal line is median, and whiskers represent maximum and minimum 

captures per survey. Number above whiskers is total number of surveys conducted in 

each month. 

in any other month (all p≥0.500). Capture rates for male LANO were lowest (0.29 – 

0.77 captures/survey) during August-October, however they comprised 67 to 100% 

of LANO captures during these months (fig. 3). Though not a primary focus of this 

study, 36 hoary bats were captured (6 from 11 April-16 May and 27 from 25 

September-5 October); all but two hoary bats were males.

Stable isotopes 

We analyzed stable isotope content in fur samples collected from bats during 

2008 and 2009. We found no difference in δD values between male and female 

LANO (t65= -0.57, p = 0.571, table 1). Although MYYU fur samples averaged 5 ± 

3‰ higher than LANO (table 1), the difference was not significant (F1,114= 2.98, p = 

0.087). The range of δD values in LANO fur from Jun-Aug (-94 to -52‰), when 

male:female sex ratio of samples were 13:3, was not substantively different from 

Nov-Feb (-103 to -55‰) when sex ratios of samples were 8:8. Further, neither 

differed from the range of values for MYYU during June-August (-111 to -49‰), or 

throughout their April-November activity period (-111 to -41‰). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

452

0

1

2

3

4

5

6

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Captures per Survey

MYYU

Female

Male

Figure 3—Mean monthly number of captures per survey and sex ratios for Yuma 

Myotis (MYYU) and silver-haired bats (LANO) captured during 74 mist net surveys in 

redwood forests of northwestern California 2008 to 2010.

Fur of LANO was higher than MYYU in δ 13C (F1,49.2= 5.86, p = 0.019; table 1) 

though mean difference between species was small (0.8 ± 0.3‰). We found no 

difference in δ

 15N between LANO and MYYU (F1,70.9= 2.77, p = 0.101). On average 

LANO fur was 1.9 ± 0.7‰ higher for δ 34S than MYYU (F1,91.1= 6.60, p = 0.012, 

table 1) and patterns differed between the species according to site where fur was 

collected. MYYU exhibited a visual trend toward lower δ 34S with increasing distance 

from the Pacific Ocean, but LANO did not (fig. 4). Neither sex (all p ≥0.240), nor the 

interaction of species and sex (all p ≥0.092), explained significant portions of the 

variation for any of the four isotopes. 

Discussion

Seasonal activity patterns

Our study confirmed that bats are active year-round in redwood forests of 

NWCAL but that the species responsible for this activity differ markedly on a 

seasonal basis. MYYU was the most frequently captured species and followed a 
Northern California Redwood Forests Provide Important Seasonal Habitat for Migrant Bats

453

Table 1—Mean stable isotope values (‰) in fur by sex, for Yuma myotis (MYYU) and silverhaired bats (LANO) captured during all seasons of the year in redwood forests of 

northwestern California 2008–2009. 

Element Species Sex n Mean Range

Hydrogen

(δD)

LANO M 51 -75 -113 to -39

F 16 -78 -94 to -53

MYYU M 34 -75 -111 to -53

F 22 -67 -105 to -41

Sulfur (δ 34S) LANO M 42 6.6 -3.5 to 12.9

F 15 6.2 1.6 to 9.2

MYYU M 32 3.5 -4.1 to 12.7

F 21 5.6 -0.8 to 10.7

Carbon (δ 13C)LANO M 31 -23.0 -25.0 to -21.5

F 11 -23.1 -24.8 to -21.9

MYYU M 24 -23.9 -29.6 to -21.5

F 12 -23.8 -26.2 to -21.2

Nitrogen 

(δ15N)

LANO M 31 6.4 4.9 to 7.8

F 11 6.8 4.2 to 9.1

MYYU M 24 7.0 5.0 to 10.4

F 12 7.1 5.6 to 8.6

Figure 4—Sulfur isotope ratios (δ 34S) in fur of silver-haired bats (LANO) and Yuma 

myotis (MYYU) versus distance of sample site from the Pacific Ocean during surveys 

in redwood forests of northwest California 2008 to 2009.

pattern typical for a summer-active resident bat species with captures peaking during 

June and July and LANO was the most frequently captured species during winter. 

Hoary bats made significant, if episodic, visits to redwood forests presumably as they 

migrated through the area.Previous studies with guano traps in basal hollows 
GENERAL TECHNICAL REPORT PSW-GTR-238 

454

established that bats are active throughout the winter in NWCAL, though at much 

lower levels than during summer (Gellman and Zielinski 1996, Zielinski and 

Gellman 1999). However, guano traps likely index of activity by Myotis spp. and big 

brown bats because LANO are not likely to make significant use of basal hollows 

(Zielinski et al. 2007). Both sexes of MYYU are summer residents of redwood 

forests and they likely hibernate during winter, although hibernation sites are 

unknown throughout their range (Verts and Carraway 1998). Although winter 

captures of LANO have previously been recorded in redwood forests (Zielinski and 

Gellman 1999), our results establish that such activity is common. Further our work 

is in agreement with previous reports that captures of LANO in redwood forests of 

NWCAL are nearly all male during summer while sex ratios are roughly equal from 

November-March (Zielinski and Gellman 1999). This strongly indicates that female 

LANO migrate elsewhere for parturition and pup-rearing before returning to the 

northwest coast of California to overwinter. 

The closest summer records of female LANO are from the upper Sacramento 

River Canyon (Rainey 1994), Whiskeytown National Recreation Area, and Lassen 

National Forest (Morrell and Duff 2005), all > 150 km inland. Whether LANO that 

winter in redwoods of NWCAL spend summers in these areas, or are drawn from a 

wider range of geographic locations, is unknown. The attractiveness of NWCAL may 

be explained by relatively moderate winter temperatures that are conducive to treeroosting (Cryan 2003). Areas, such as redwood forests of NWCAL, which maintain 

ambient winter temperatures of 5 to 10 °C may be energetically optimal for LANO 

(Dunbar 2007). Further, cool summer temperatures in redwood forests may enable 

male LANO to maximize use of torpor (Weller et al. 2009). The presence of both 

male and female LANO beginning in autumn and continuing throughout winter 

suggests that redwood forests may be important locations for mating in this species. 

Hence redwood forests of NWCAL could prove a vital area for maintenance of 

LANO populations at regional- or, perhaps, continental-scales.

Stable isotopes 

Ours is the first study to report stable isotope values in the fur of either MYYU or 

LANO. The range of values for all four isotopes was similar among both sexes and 

species. Contrary to our expectations we did not find that isotope values in female 

LANO differed from MYYU or male LANO. Instead, mean values were similar and 

LANO females exhibited the narrowest range of values for δD, δ13C, and δ34S (table 

1), although this group had the smallest sample size. 

The 40 to 70 ‰ range in δD we observed is similar to ranges of four species in 

the eastern U.S. (Britzke et al. 2009) and a sedentary population of big brown bats in 

Colorado (Cryan et al.3

). The wide range of δD values we observed could be 

associated with bats making relatively short regional movements (e.g., to Sacramento 

Valley) across a steep gradient in δD values from the Pacific Coast (Bowen et al. 

2005). As such, the range of δD values may not differ much between male and 

female LANO or MYYU individuals. We observed a 70‰ range of δD values for 

MYYU captured over 1.4° range in latitude. This is similar to the apprximately 60‰ 

range of δD over a 2° range in latitude reported for little brown bats (M. lucifugus; 

 

3 Cryan, P.M.; Stricker, C.A.; Wunder, M.B. Biologically structured isotopic variation in a sedentary 

population of bats. Unpublished draft supplied by authors.
Northern California Redwood Forests Provide Important Seasonal Habitat for Migrant Bats

455

Britzke et al. 2009). This level of within-area variability in δD is troubling because it 

could equally have been interpreted as movements over multiple degrees of latitude 

(Wunder et al. 2005, Cryan et al. unpublished draft); which seems particularly 

unlikely for MYYU. These findings underscore the challenges inherent in using 

isoscapes to characterize migratory movements of animals because assignment of 

tissue origin requires characterization of the isoscape at multiple spatial and temporal 

scales (Wunder 2010). 

The range of stable isotope values present in local bat communities has only 

recently been the subject of study (Britzke et al. 2009, Cryan et al. [see footnote 3]), 

and it is possible that it may be great enough to preclude identification of all but long 

distance seasonal movements (e.g. > 500 km). A primary impediment to the use of 

stable isotopes in bat fur is poor understanding of molt (Britzke et al. 2009). A single 

molt in bats is expected during July and August (Constantine 1957, Cryan et al. 

2004) but molt may be protracted over a month, even at a single locale (Constantine 

1957). In addition, timing of molt may vary by latitude, species, or sex (Constantine 

1957). The consequences of these molt characteristics are magnified if seasonal 

movements are concurrent with new fur growth (Britzke et al. 2009). Further 

impediments include poor resolution of δD baselines relative to the scale of daily or 

seasonal movements (Wunder and Norris, 2008), lack of controlled experiments 

linking diet and water to isotope values in mammalian consumers (Martinez del Rio 

et al. 2009), and inherent system noise. 

Although used successfully in other studies (Rubenstein et al. 2002) the 

combination of δD with δ13C and δ15N did not appreciably improve our 

understanding of the seasonal movement patterns of LANO or MYYU. The range of 

values we observed were relatively similar among the four species-sex groups we 

evaluated and to a population of big brown bats in Colorado (Cryan et al. 

unpublished draft). We believe the most parsimonious explanation for the wide range 

in δ13C and δ15N for both MYYU and LANO is that they are habitat and dietary 

(Ober and Hayes 2008) generalists.

We conjectured that δ34S may provide longitudinal inference because of our 

study area’s proximity to the Pacific Ocean (Zazzo et al. 2011). Indeed we observed a 

pattern in MYYU fur with lower δ34S values as distance from coast increased; a 

pattern not observed in LANO. Taken together these observations are consistent with 

the hypothesis that capture locations reflect location of fur growth for MYYU but not 

LANO. If confirmed, this pattern suggests that the δ34S gradient is quite steep inland 

from the ocean and that δ34S may be a useful tool for evaluating local- versus 

regional-scale movements of bats. 

Conclusions 

As a result of year-round capture activities we determined that the bat 

communities in redwood forests of NWCAL are dominated by MYYU in the 

summer, LANO in the winter, and may also provide important stopover habitat for 

hoary bats during fall and spring migration. Female LANO appear to migrate from 

the redwoods during spring and return to them during autumn. Male and female 

LANO are only together during autumn through spring when mating occurs, further 

emphasizing the importance of redwood forests of NWCAL to LANO populations at 

regional- and perhaps continental-scales. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

456

Despite spatial segregation between male and female LANO during their 

presumed molt period, we did not find differences between the sexes in range of 

isotope values in their fur. Further, the range of isotope values in the presumably 

migrant LANO did not differ from the presumably resident MYYU. Although 

differences in mean values were observed between the species for δ34S and δ13C, 

broad ranges in individual dietary preferences may obscure inferences about summer 

ranges of MYYU and LANO in our study area (Cryan et al. unpublished draft). 

Nevertheless, we noted a promising trend between δ34S and distance to coast for 

MYYU which may prove useful in future work. 

Acknowledgments

We thank M. McKenzie for assisting with bat captures and sample preparation 

and C. Gulbransen for conducting the isotope analyses. J. Baldwin provided 

statistical assistance. Bill Zielinski provided helpful comments on an earlier draft of 

this manuscript and Paul Cryan provided helpful guidance throughout. Funding for 

this work was provided by Save the Redwoods League and USDA Forest Service 

Pacific Southwest Research Station. Use of trade, product, or firm names is for 

descriptive purposes only and does not imply endorsement by the U.S. Government. 

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459

Measurements of Key Life History Metrics 

of Coho Salmon in Pudding Creek, 

California1

David W. Wright2, Sean P. Gallagher3, and Christopher J. Hannon4

Abstract

Since 2005, a life cycle monitoring project in Pudding Creek, California, has utilized a variety 

of methodologies including an adult trap, spawning surveys, PIT tags, electro-fishing, and a 

smolt trap to estimate coho salmon adult escapement, juvenile abundance, juvenile growth, 

winter survival, and marine survival. Adult coho salmon escapement and smolt abundance are 

closely related when spawner abundance is high. However, with decreasing escapement, 

smolt abundance appears to stabilize. Adult abundance has declined dramatically, from 1200 

in 2005 to 20 in 2010. Corresponding smolt abundance initially declined from 24,000 to 

approximately 15,000 but maintained at that level despite continued declines in escapement. 

Winter survival ranged from 17 to 80 percent, and appeared to increase as the juvenile 

population decreased. Juvenile growth rates within the upper watershed were low during 

summer and significantly higher in spring and fall. PIT tag detections indicated that thirteen 

percent of all coho outmigrants were two year old smolts that were smaller at tagging than 

one year old outmigrants, but larger than one year old fish at outmigration. Over three 

complete coho life cycles (2006 to 2010), ocean survival appeared to strongly affect adult 

returns. In all years since 2006, ocean survival for Pudding Creek spawners was notably lower 

than reported by others in streams throughout the Pacific Northwest in previous years.

Key words: coho salmon, escapement, life history, smolt, Mendocino County

Introduction

Pudding Creek is a small coastal tributary in Mendocino County, northern 

California, known to support populations of coho salmon (Oncorhynchus kisutch) 

and steelhead (O. mykiss). As a component of a larger regional project encompassing 

most streams and rivers in Mendocino County, the Pudding Creek Coho Salmon 

Project goals include: 1) estimation of adult escapement, 2) estimation of summer 

juvenile abundance, 3) estimation of outmigrant production, and 4) characterization 

of life-history patterns. This report characterizes life history traits of coho salmon

inhabiting Pudding Creek. 

 

1 This paper was presented at the redwood science symposium: coast redwood forests in a changing 

California: a symposium for scientists and managers, June 21-23, 2011 Santa Cruz, California. 2 Fisheries Biologist, Campbell Timberland Management, P.O. Box 1228, Fort Bragg, CA 95437. 

(dwright@campbellgroup.com). 3 Associate Biologist, California Department of Fish and Game, 32330 N. Harbor Drive, Fort Bragg, CA 

95437. (SGallagh@dfg.ca.gov). 4 Fisheries Biologist, Campbell Timberland Management, P.O. Box 1228, Fort Bragg, CA 95437. 

(channon@campbellgroup.com). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

460

Methods

Project area

The project area includes all fish-bearing stream reaches (approximately 22 km) 

within the Pudding Creek watershed (fig. 1). Most of the watershed is presently 

managed for timber production, and over 70 percent of the watershed is owned by the 

Hawthorne Timber Company, LLC and managed by CTM. Vegetation in the area is 

primarily comprised of coast redwood (Sequoia sempervirens) and Douglas-fir 

(Pseudotsuga menziesii). Red alder (Alnus rubra), willow (Salix spp.), and big-leaf 

maple (Acer macrophyllum) are the primary constituents of the riparian canopy, 

which is nearly continuous throughout the stream network. Pudding Creek drains 

approximately 45 km2

. Streambed gradient is generally < two percent throughout the 

mainstem reaches. 

Figure 1—The Pudding Creek watershed project area.

The Pudding Creek watershed includes a dam and an associated impoundment 

located 0.7 km upstream of the confluence with the ocean (fig. 1) which historically 

was a water supply for the now defunct Georgia Pacific mill site. The impoundment 

has a surface area of nearly 0.09 km2

 and a volume of approximately 25 hectaremeters. The resulting reservoir inundates nearly 4.3 km of the stream network. 

Due to the multiple life-history stages of coho salmon present in the Project Area, 

several study methods were used to characterize their abundances and life-history 

patterns, which follow. 

Adult trapping and spawning estimates 

Adult coho salmon are trapped and tagged at the Pudding Creek Dam fish ladder. 

Spawning surveys upstream of the pond produce estimates of spawning numbers 

using mark-recapture methods. The “recapture” component is the re-sight of fish 

tagged at the dam made by surveyors in the field.

Outmigrant trapping 

Outmigrating fish are captured in a rotary screw trap (RST) with a 5 ft diameter 

cone. The trapping station is 6.6 km from the ocean confluence and 1.6 km from the 
Measurements of Key Life History Metrics of Coho Salmon in Pudding Creek, California

461

top of pond habitat formed by the dam (fig. 1). The trap is operated from February 

until mid June. Fish are identified, implanted with PIT tags, and size (fork length) 

and weight are measured. Smolt population estimates are generated using the 

Darroch Analysis with Rank Reduction (DARR) method (Bjorkstedt 2000). During 

springtime low flow periods, juvenile salmonids are also captured at the Pudding 

Creek Dam on an opportunistic basis. 

Juvenile growth modeling 

The basic model assumption is that the weight of any individual as a function of 

time, wt , satisfies the stochastic differential equation

t

t t

t

dw g dt dB

w

= +σ , 

where t g is the instantaneous growth rate at time t and Bt is a standard Brownian 

motion. Under these assumptions, the growth over a finite time interval 1 2 [, ) t t is

2

2 1 1

1/2

2 1 ln( ) ln( ) ( ) t

ttt t w w g dt t t − = +− σ ε ∫ , 

where ε is a standard normal deviate.

Assuming that the same t g and σ apply to all individuals, the probability of 

observing N pairs of recoveries, where the k th recovery record includes the times 

k1 t and k 2 t of the recoveries and the weights wk1 and wk 2 at these times, is

( ) 2

1

2

2 1

1 2 2

2 1 2 1

ln( ) ln( ) 1 ( , ) exp

2( ) 2( )

k

k

t

kk t N t

k

k k k k

w w g dt

L g

t t t t

σ

πσ σ =

  − −   = − − −

 

∫ ∏ . 

For the generated results, the growth function g was taken to be piecewise constant, 

depending on the year and 

season:

from October of year Y through February of year Y +1

from March through May of year Y

from June through September of year Y

Y, winter

Y, spring

Y, summer

g

g g

g



 = 



Counting σ , this gives a statistical model with fourteen unknown parameters, from 

Spring 2006 through Spring 20105

.

Late-summer abundance surveys

Juvenile abundance during the summer rearing period is assessed using an

electro-fish sampling protocol based on a Generalized Random Tessellation Stratified 

(GRTS) sample draw. At 10, approximately 50 m selected reaches, juvenile 

abundance is estimated with depletion electro-fish sampling. PIT tags are implanted 

in unmarked fish. 

 

5 The data extend into June of 2010; this was folded into the “Spring 2010” period.
GENERAL TECHNICAL REPORT PSW-GTR-238 

462

PIT tags

All juvenile salmonids greater than 65 mm captured during summer surveys or 

during outmigrant trapping, are implanted with 11 mm full duplex (FDX) PIT tags.

PIT tag arrays 

To detect fish at the Pudding Creek Dam that have been PIT tagged at upstream 

locations, multiple antennae arrays have been affixed around the dam flashboards. 

These arrays record a time stamp for each fish detected. 

Results

Adult escapement 

Of the two methods traditionally used to estimate adult escapement, the markrecapture technique has proved most reliable. Thus, fish per redd estimates are shown

only for 2002 and 2003; the years before mark-recapture experiments were initiated

(fig. 2). Overall, fewer coho returned to spawn in water year 2010 than in previous 

project years. For comparison, escapement from eight regional streams is shown for 

the same time series (fig. 3)

6

. 

Outmigrant production 

Coho smolts were more abundant in 2006 than in all other monitoring years with 

a population estimate of approximately 24,000 fish. From 2007 to 2010, estimates 

varied from approximately 13,000 fish to 16,000 (fig. 4). When escapement estimates 

are plotted with the corresponding natal lineage of smolt abundance (fig. 5), smolt 

abundance does not appear closely correlated with the abundance of the parental 

brood-stock. 

 

6 Reichmuth, Fishery Biologist, Inventory and Monitoring Program, Point Reyes National Seashore. 

Unpublished.
Measurements of Key Life History Metrics of Coho Salmon in Pudding Creek, California

463

Juvenile growth 

The recapture of PIT tagged juvenile salmonids produced information on 

seasonal instream growth. Growth seasons were defined by the period between 

sampling regimes, or by the period in which the sampling regimes occurred. Over 

five years of sampling (2006 to 2010), coho salmon growth in Pudding Creek 

appeared greatest in spring (February - May. Fall/winter (October - March) produced 

moderate growth, and summer (May - September) appeared to be a period of limited 

growth (fig. 6). In some years, growth was negative over the summer period. 

Figure 6—Growth rates of Coho salmon (Oncorhynchus kisutch) in Pudding Creek. 

Fit of individual growth data from PIT recoveries to fourteen parameter model.

Based on smolt PIT tagged at the RST and recaptured at the dam, in 2009 and 

2010 significant growth occurred in the 6.1 km reach during outmigration. 

Respectively, mean coho smolt growth 10.6 mm (n = 268, s.e. = 0.62) and 11.8 mm 

(n = 41, s.e. = 1.62). 

Coho salmon ocean survival 

We examined six coho salmon cohorts (brood years) to estimate spawner to 

spawner ratios (2002 to 2010) – the ratio of the number of spawners to the number of 

their progeny that return as spawners. Two cohorts had ratios greater than 1 (more 
GENERAL TECHNICAL REPORT PSW-GTR-238 

464

progeny returned), and four had a ratio less than 1, suggesting poor yield from the 

spawning efforts after the 2003 water year (table 1). Outmigrant sampling combined 

with adult recaptures of the same cohort facilitates estimation of specific marine 

survival (smolt to spawner estimates) by two methods: Comparison of estimates 

between outmigrant and escapement indicates that ocean survival from 2006 to 2010 

ranged from 0.08 to 0.95 percent (table 2). Ocean survival based on PIT tag returns 

from these cohorts ranged from 0.04 to 0.44 percent. PIT tag return survival 

estimates remained consistently lower for all cohorts (table 2). 

Table 1—Adult escapement estimates and spawner-to-spawner ratios for six cohort classes 

of coho salmon.

Years 2002 to 

2005

2003 to 

2006

2004 to 

2007

2005 to 

2008

2006 to 

2009

2007 to

2010

SpawnertoSpawner 

(95% CI)

2.23

(2.05-

2.91)

1.93

(1.77–

2.21)

0.33

(0.28–

0.37)

0.2

(0.17-

0.25)

0.07

(0.05-

0.11)

0.02

(0.01-

0.05)

Table 2—Coho salmon ocean survival (smolt to spawner estimates), calculated from 

population estimates and tag returns. 

Ocean Years 2006 to 2008 2007 to 2009 2008 to 2010

Comparison of Population Estimates 

(Percent) 0.95 0.33 0.08

PIT Tag Returns (Percent) 0.44 0.14 0.04

Coho salmon over winter survival 

The proportion of juveniles PIT tagged during summer abundance surveys and 

recaptured at the RST indicates instream survival from late summer to spring 

outmigration (table 3). Over winter survival varied from 0.17 to 0.8. However, due to 

the low number of tags recaptured, confidence intervals were large, in some cases 

indicating unrealistic upper bounds as in 2007 and 2010. 

Table 3—Over winter survival.

Years 2007 2008 2009 2010

Over winter survival 

(95 percent CI)

0.71 0.17 0.61 0.8

(0.24-1.18) (0.13–0.22) (0.45–0.77) (0.57-1.02)

Juvenile size at outmigration 

The modal size class of coho salmon was 90 to 100 mm from 2006 to 2008. In 

2009, the modal size class was smaller (80 to 90 mm) and the frequency distribution 

appeared to be wider. The 2010 modal size class was 100 to 105 mm, and the 

frequency distribution was relatively narrow (fig. 7). In 2006 and in 2008 a bimodal 

distribution was observed, with the secondary peak at approximately 140 mm. This 

pattern was also observed to a lesser degree in 2010. In 2007 and 2009, the bimodal 

distribution was not apparent. The secondary modes in the small size classes (< 60 

mm) are newly emergent YOY.
Measurements of Key Life History Metrics of Coho Salmon in Pudding Creek, California

465

0

200

400

600

800

1000

1200

1400

1600

1800

30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200

Number of Smolts

2006 2007 2008 2009 2010

Figure 7—Smoothed histogram of coho salmon fork lengths at the outmigrant 

trapping station in Pudding Creek (2006 to 2010).

The mean value of annual juvenile cohort fork lengths since 2006 (table 4) from 

the RST captures indicate that the 2010 smolt were largest and the 2009 cohort were 

smallest.

Table 4—Mean juvenile coho fork lengths with 95 percent confidence intervals for Pudding 

Creek (2006 to 2010). 

Year 2006 2007 2008 2009 2010

Mean Fork Length 

(CI)

101.9 

(0.5)

96.5 

(0.4)

88.1 

(0.5)

87.7 

(0.5)

104.2 

(0.5)

Coho juvenile two year life history 

The use of PIT tags, the RST, and the PIT tag antennae array at the dam indicated 

evidence of a coho two year instream life history and several characteristics that 

appear to be associated with this behavior. Since 2009, 13 percent of all coho salmon 

detections at the dam array have been 2 year old juveniles. Since 2006 when 

downstream trapping was initiated at the RST, we have recaptured coho in their 

second year on multiple occasions (fig. 8). The recaptures at the RST also indicate 

that second year life history behavior is not annually consistent (fig. 8). 

The median fork length for first year smolt (92 mm) at initial capture was greater 

than the group that outmigrated in their second year (76 mm). At recapture, the

median value of second year smolts was greater (129 mm) than first year smolts (104 

mm). A Mann-Whitney Rank Sum Test (not normally distributed) indicates a 

significant difference between the median values of the two groups at first capture 

(P= <0.001). A t-test of the normally distributed recaptures indicates a significant 

difference between the mean values of the groups (P=<0.001). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

466

Figure 8—Length of individual Coho salmon at the Pudding Creek RST vs. time. The 

length of each fish measured in each spring survey is shown as a dot. Line segments 

join successive recoveries of the same individual PIT tag in spring surveys. All 

recaptures occurred at RST.

Figure 9—Fork lengths for first year smolts compared to second year smolts at first 

capture and recapture at the RST.

Discussion

Spawning abundance 

The current analysis of escapement and outmigration for coho salmon suggest the 

Pudding Creek population is following the trend found in other streams throughout 

California (fig. 3), which further suggests the causes for the immediate decline may 

be at the regional scale. 
Measurements of Key Life History Metrics of Coho Salmon in Pudding Creek, California

467

Juvenile abundance 

At the RST, coho salmon outmigrant numbers have remained consistent since 

2007 after a significant decrease from 2006 (table 1). A comparison of coho salmon 

spawners to their outmigrant offspring the following spring suggested the outmigrant 

population was dependent on the number of spawners from 2006 to 2008, a pattern 

not reflected in 2009 and 2010 (fig. 5).

The outmigrant trap is approximately 6 km from the ocean confluence, with 

spawning, rearing, and overwintering habitat located between it and the ocean. Thus, 

the trap may not actually estimate the true outmigrant population. PIT tag recaptures 

in returning adult coho salmon suggest that the outmigrant population may be 

considerably higher than our stated estimates (table 2). However, this is contingent 

on whether chronic mortality of PIT tagged fish is significant. To test for chronic 

mortality, in 2010, 50 percent of the tagged fish were tagged with a right maxillary 

clip rather than a PIT tag. The tag rate of these two groups in adults returning during 

water year 2012 will indicate whether chronic mortality is an issue. 

Over winter survival 

Based on the spring recaptures at the RST of fish originally PIT tagged in 

summer, over winter survival in Pudding Creek appears to increase as juvenile 

abundance decreases (table 4, fig. 4). We believe this is the result of reduced density 

dependent competition among rearing juveniles for habitat and feed. 

Marine survival

Coho salmon spawner-to-spawner and outmigrant-to-spawner ratios were low for 

the WY 2008, WY 2009 and WY 2010 runs (tables 1 and 2). A poor spawner-tospawner estimate indicates low production at any point in the coho salmon life cycle; 

however, poor smolt to spawner estimates clearly point to low survival at sea (table 

3). Our smolt to spawner estimates are much lower than observed in California 

coastal streams (e.g., greater than six percent in Waddell Creek [Shapovalov and Taft 

1954]) and in many streams further north (greater than 10 percent in Puget Sound 

[Mathews and Buckely 1976]), However, our results are consistent recent rates of 

less than one percent in Oregon streams (Lewis 2004). 

Size 

By mean fork length, smolts in Pudding Creek were largest in 2010 (table 5) and 

smallest in 2009. The summer of 2009 was extremely dry, which may account for the 

diminished size. Although 2006 and 2010 smolts were comparatively large, they 

were small compared to those in Waddell Creek, CA (Shapovalov and Taft 1954). In 

2009 and 2010, mean fork length increased by approximately 11 mm as fish migrated 

the final 6.1 km between the RST and the dam (near the ocean confluence). These 

additional 11 mm would make the Pudding Creek mean FLs as measured at the RST 

more comparable to those reported in the 1930s Waddell Creek study. However, the 

Waddell Creek weir was located 2.2 km from the ocean confluence. Waddell smolts 

probably also grew between trapping site and the ocean. We compared the length of 

Pudding Creek coho smolt captured between 2006 and 2008 to those captured in a 

similar monitoring project on Prairie Creek, Humboldt County, CA7

. The main land-

 

7 W. Duffy, California Cooperative Fisheries Research Unit, 2011, unpublished data.
GENERAL TECHNICAL REPORT PSW-GTR-238 

468

use difference between these two otherwise similar watersheds is that Prairie Creek 

has not undergone significant timber harvesting. Pudding Creek, on the other hand, 

has been managed for timber harvest for over a century. Coho outmigrants from 

Pudding Creek (97.5 mm) are somewhat larger than those from Prairie Creek (96.8 

mm; p = 0.011 for the two-sided heteroscedastic t-test). This information suggests 

that the characteristics of coho size at outmigration are variable by watershed. Coho 

forklengths were comparable to the size range reported by Bradford et al. (1997) 

throughout Oregon and Washington. 

Growth 

Coho salmon in Pudding Creek grow well in spring, and moderately in fallwinter. Summer appears to be a period of low growth, which is likely due to 

diminished carrying capacity stemming from the annual summer drought. These 

findings support the notion that stream enhancement projects intended to augment 

pool habitat (e.g., through the introduction of large wood into the channel) may be 

effective to increase juvenile salmon survival and growth over summer. 

Based on smolt captures at the dam that were tagged at the RST, on average coho 

smolt grew approximately 11 mm while traveling the last 6.1 km of stream, which is 

nearly 10 percent of their total growth within the last 100 days of stream residency. 

This suggests the importance of lower channel habitat for juvenile growth. 

Coho juvenile 2 year life history 

A second year life history likely supports three important life history functions. 

First, it allows undersized fish with little potential for marine survival a second year 

to increase size. Second, it is one pathway for genetic mixing between the cohort 

classes. Finally, a two year life history can help ensure adequate recruitment when 

poor spawning occurs by contributing juveniles from one year to the next. 

The mechanism for second year life history in juveniles appears to be, in part, the 

slower downstream movement exhibited by smaller smolts. We can determine the 

length of time smolt spend between the RST and the dam and compare this period to 

fork length measurements taken at the RST (fig. 10). The analysis of these data 

indicate that larger fish move rapidly through the stream network, while smaller fish 

take considerably more time in downstream migration. Considering that streamflow 

generally does not allow downstream migration in Pudding Creek past early June, 

which is approximately a 100 day window for migration, smaller fish will more 

likely be prevented from migrating to the ocean. 

In Pudding Creek coho salmon that stayed a second year were significantly 

smaller than the rest of their cohort upon initial capture (fig. 9). We found the mean 

fork length at first capture of these fish to occur at approximately 75 mm, which is 

also the size class that takes longest to outmigrate (fig. 10). However, when they 

outmigrated the following year they were significantly larger than that year’s cohort.

This is consistent with the findings of Bell and Duffy on Prairie Creek, CA (2007). 
Measurements of Key Life History Metrics of Coho Salmon in Pudding Creek, California

469

60

70

80

90

100

110

0 10 20 30 40 50 60 70 80 90 100 110

Time Elapsed (days)

Average Fork Length (mm)

Figure 10—Time elapsed between original capture at RST and subsequent detection 

at dam vs. initial measured fork length. Error bars are 95 percent confidence 

intervals.

The dam and impoundment raise many issues regarding the affects on salmonids, 

and presently we do not understand the degree to which it benefits or hinders them. 

On one hand, the impoundment may benefit coho because it acts as over-wintering 

refugia for juveniles during high winter flows, and as summer rearing habitat. 

However, dam and impoundment may be detrimental due to low dissolved oxygen 

levels in the pond during summer from decaying non-native vegetation, fish passage 

issues, predation, and the division of the coastal lagoon. Decisions regarding the 

future of the dam structure will soon be necessary due to changing regional socioeconomic conditions. More resources should be allotted to research on the dam as it 

relates to salmonids before these decisions are made. 

References

Bell, E.; Duffy, W.G. 2007. Previously undocumented two-year freshwater residency of 

juvenile Coho salmon in Prairie Creek, California. Transactions of the American 

Fisheries Society 16: 966-970.

Bradford, M.J.; Taylor, G.C.; Allan, A.J. 1997. Empirical review of coho salmon smolt 

abundance and the prediction of smolt production at the regional level. Transactions 

of the American Fisheries Society 126: 49-64.

Bjorkstedt, E.P. 2005. DARR 2.0: Updated software for estimating abundance from 

stratified mark-recapture data. U.S. Department of Commerce, National Oceanic and 

Atmospheric Administration, Nation Marine Fisheries Service, Southwest Fisheries 

Science Center. NOAA-TM-NMFS-SWFSC-368. 

Matthews, S.B.; Buckley, R. 1976. Marine mortality of Puget Sound coho salmon 

(Oncorhynchus kisutch). Journal of the Fisheries Research Board of Canada 33: 1677-

1684. 

Shapovalov, L.; Taft, A.C. 1954. The life histories of the steelhead rainbow trout (Salmo 

gairdneri gairdneri) and silver salmon (Oncorhynchus kisutch) with special 
GENERAL TECHNICAL REPORT PSW-GTR-238 

470

reference to Waddell Creek, California, and recommendations regarding their 

management. Fish Bulletin 98. California Department of Fish and Game. 375 p.

Lewis, M. 2004. Hatchery coho marine survival. Oregon Department of Fish and Wildlife, 

Salem, Oregon. 

http://nrimp.dfw.state.or.us/OregonPlan/default.aspx?p=134&XMLname=33.xml .
Silviculture and Restoration

473

Coast Redwood Live Crown and Sapwood 

Dynamics

John-Pascal Berrill,1 Jesse L. Jeffress,

1 and Jessica M. Engle1

Abstract

Understanding crown rise and sapwood taper will help meet management objectives such as 

producing long branch-free boles for clear wood and old-growth restoration, or producing 

sawlogs with a high proportion of heartwood. Coast redwood (Sequoia sempervirens) tree 

crown ratio data were collected 20 years after partial harvesting in a 65-year-old second 

growth stand. Crown ratio correlated with stand density and relative tree height, and differed 

between stand interior and edge locations. The sum of tree crown lengths in each plot gave 

crown length/ac which exhibited an asymptotic relationship with stand density (i.e., crown 

length/ac peaks at higher densities). Maximum crown length/ac can be used to constrain 

simulations of crown rise by limiting the increase in crown length following thinning. 

Sapwood cross-sectional area was sampled at breast height and at the base of the live crown 

(BLC) of redwood trees growing in northern, central, and southern portions of redwood’s 

natural range. Variability in sapwood area taper prevented detection of significant differences 

between regions, but on average sapwood tapered most rapidly among northern trees and least 

among southern trees. We present a robust sapwood taper model derived from the power 

function that has the desirable property of predicting zero taper for trees with BLC at breast 

height. Models predicting sapwood area at breast height from DBH allow prediction of 

sapwood from forest inventory data. Results indicated that dominant and codominant trees in 

the northern region had more sapwood than trees of similar size growing in the hotter, drier 

southern region. 

Key words: crown ratio, crown rise, heartwood, leaf area, live crown ratio, sapwood taper,

Sequoia sempervirens

Introduction

Contemporary management objectives for young coast redwood stands include 

old-growth restoration and clear wood and heartwood production. Distinguishing 

characteristics of old-growth forests include long branch-free boles. These can be recreated by artificial pruning, or by manipulating stand density to control crown rise. 

Crown height and size affect tree growth which largely comprises sapwood and 

heartwood development. Understanding the impacts of stand density on crown rise 

and its relationship with tree size, sapwood, and heartwood content permits us to 

design density management regimes for aesthetic and wood quality objectives. For 

example, it may be worthwhile to sacrifice tree diameter development to induce 

crown rise and produce valuable knot-free heartwood with narrower growth rings. 

Crown rise in monospecific plantations of loblolly pine (Pinus taeda) and Sitka 

spruce (Picea sitchensis) has been predicted successfully using estimates of average 

tree height and either tree count per unit area or average inter-tree distance (Valentine 

 

1

Assistant Professor and undergraduate students, respectively, Department of Forestry and Wildland 

Resources, Humboldt State University, 1 Harpst St, Arcata, CA 95521. (pberrill@humboldt.edu). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

474

et al. 1994). The same variables correlated with crown length in old-growth sprucefir forests in British Columbia (Antos et al. 2010). Tree size and stand density 

measures, and topographic site factors were useful predictors of crown ratio 

throughout the forests of Austria, where crown ratio differed between species and 

was most affected by competition (Hasenauer and Monserud 1996). Norway spruce 

(Picea abies) crown ratio and crown length varied between age groups and were 

affected by thinning (Kantola and Mäkelä 2004). 

Estimates of tree crown leaf area for individual trees and forest stands are useful 

predictors of tree growth and forest productivity in terms of tree growth efficiency 

(defined as the ratio of stem wood production to total leaf area), net primary 

productivity, and carbon sequestration. Growth efficiency can be used as a reference 

for a stand’s susceptibility to disease or insect attack or for other trends in forest 

health (Maguire and Batista 1996). The relationship between redwood tree growth, 

growth efficiency, and tree leaf area is affected by stand structure and the tree 

crown’s position within the stand (Berrill and O’Hara 2007a). Therefore redwood 

stand density and structure can be manipulated to affect leaf area, stand growth, and 

tree size at harvest (Berrill and O’Hara 2007b, 2009). The pipe model theory 

(Shinozaki and others 1964) proposes that a given amount of foliage is supported by 

a proportional cross-sectional area of ‘pipes’, i.e., a close functional relationship 

exists between sapwood area (SA) and leaf area (LA). Sapwood area at the base of 

the live crown (SABLC) is more strongly correlated with leaf area than sapwood area 

at breast height (SABH) (Waring et al. 1982). A taper model predicting SABLC from 

measured SABH will improve leaf area estimates (Waring et al. 1982). The existing 

sapwood taper model for redwood was constructed using data for second-growth

trees of varying size in different canopy positions within stands in the central portion 

of redwood’s natural range (Stancioiu and O’Hara 2005). 

We examined crown ratio data for redwood trees in the central portion of 

redwood’s natural range and sapwood area among redwood trees in the southern, 

central, and northern parts of the range. Our objectives were to: 

(i) Develop models that predict redwood crown ratio in managed and 

unmanaged stands. 

(ii) Construct an equation that predicts SABLC for the southern, central, and 

northern regions, and test for regional differences in sapwood taper. 

(iii)Model SABH as a function of diameter at breast height (DBH) to enable 

prediction of SABH and SABLC from traditional forest inventory data. 

Methods

Crown ratio data were collected in 234 permanent sample plots within the 260 ac 

Railroad Gulch Harvest Demonstration Area on Jackson Demonstration State Forest 

(JDSF), near Ft. Bragg in Mendocino County, north coastal California. After 

clearcutting in 1920, a mixture of redwood, Douglas-fir (Pseudotsuga menziesii) and

tanoak (Notholithocarpus densiflorus) regenerated naturally, supplemented by 

planting of redwood seedlings. In 1982, tenth-acre plots were established on a grid 

pattern across the 260 ac demonstration area. Then, the area was divided into 14 

blocks: individual tree selection was applied in four 20 ac treatment blocks, group 

selection applied in four 20 ac blocks, and a combination of both regeneration 
Coast Redwood Live Crown and Sapwood Dynamics 

475

methods was applied in four 20 ac blocks. Two smaller blocks were reserved as ‘no 

treatment’ control areas. The plots have been measured three times at 10 year 

intervals. Tree measurements included DBH, total height, and height to BLC. 

Sapwood data from the southern portion of redwood’s range were collected at

five sites between Santa Clara County and Napa County. These were relatively hot 

and dry redwood sites, being located near the inland limits of redwood’s range (fig. 

1). Sapwood data for the central region were obtained from a previous study on JDSF 

(Stancioiu and O’Hara 2005). Two study sites were chosen for sampling in the 

northern region: Arcata Community Forest and Freshwater Forest, near Humboldt 

Bay in Humboldt County. The northern sites are shrouded in fog for much of the 

growing season, and have an average mid-summer daytime high temperature of only 

64 0

F. Summer fog generally dissipates during the daytime at the central sites in 

Mendocino County, and average summer high temperatures exceed the value of 67 0

F 

reported for the weather station at the coast. At all study sites, most rainfall occurs 

between November and March. Mean annual precipitation is approximately 40 in at 

the northern and central sites and at the inland Napa County site (Las Posadas State 

Forest). However, we categorized the Napa site as ‘southern’ because it receives less 

fog and its summer temperatures are much higher (86 0

F in July), much like the other 

southern sites (76 to 88 0

F ). Annual precipitation averaged approximately 21 in at 

Gilroy near sampling sites at Bodfish Canyon and Mt Madonna in Santa Clara 

County and 26 in at Roberts and Redwood Regional Parks in Alameda and Contra 

Costa Counties, respectively (http://www.weather.com). 

Figure 1—Natural range of coast redwood and study site locations for northern, 

central, and southern regions.
GENERAL TECHNICAL REPORT PSW-GTR-238 

476

Dominant and co-dominant redwood trees approximately 80 to 130 years old and 

about 110 ft tall were selected for sapwood measurement in the northern and southern 

regions: 19 trees from the two northern sites and 18 trees from the five southern sites. 

Trees were climbed using a flip line and spurs. Total height and height to BLC were 

measured, where the lowest living vigorous branch defined BLC (whereby excluding 

epicormic branches found lower on the stem). Diameter at BLC and DBH were 

measured with a steel tape. Two increment cores were taken at both breast height and 

BLC. Bark thickness measurements were taken at the site of each increment core. 

The point of transition from translucent live sapwood to dry sapwood adjacent to the 

red-colored heartwood was marked on each core. Live sapwood radial bandwidths 

including the vascular cambium were measured using calipers. Data for 10 trees in 

the central region were obtained from a destructive sample of cross-sectional discs 

cut from felled trees (Stancioiu and O’Hara 2005). 

Analysis of crown ratio involved separating tree size and crown data from the 

most recent measurement at Railroad Gulch into damage classes: top damaged, 

forked, and undamaged (no top damage or forking). Differences in crown ratio 

between damage classes justified exclusion of damaged trees. Tree data were also 

separated into two crown class groups: dominant and codominant trees, and 

intermediate and suppressed trees, and summarized for each group. Differences in 

crown ratio between groups justified separate analysis of crown class groups. Too 

few dominant tree data were available to model data for individual crown classes. 

Data for height to BLC, crown length, crown ratio, and height – diameter ratio were 

regressed against redwood stand density index (SDI). Estimates of redwood SDI 

were obtained using an SDI-adjustment procedure where a new plot area was 

calculated for the redwood component growing in mixture within a sample plot. The 

ratio of redwood component SDI to plot SDI gave an estimate of the proportion of 

total growing space occupied by redwood within each plot. This ratio was applied to 

the plot area, giving an estimate of area occupied by redwood. This ‘SDI-adjusted’ 

redwood plot area was used to calculate stand-level estimates of average tree size, 

basal area, and SDI for redwood. Generalized linear mixed models were constructed 

to account for nesting of trees within plots within harvest treatment blocks. The 

models were fitted to crown ratio data for individual redwood trees from each crown 

class group using PROC GLIMMIX in SAS statistical analysis software (SAS 

Institute 2004). The effects of topographic and species composition variables on 

crown ratio were tested. A dummy variable for stand edge versus interior locations, 

and relative height – the height of a tree relative to the crown class group average – 

were also tested as explanatory variables. Tree height and crown data from previous 

measurements at Railroad Gulch were not amenable to crown ratio modeling, but 

pre-harvest species composition and stand density estimates were included in the 

crown ratio analysis. Random effects in the mixed models were plot and treatment 

block. Crown length was summed in each plot, giving total redwood crown length/ac. 

Crown length/ac estimates were binned in increments of stand density (for example 

SDI 50 to 150, 150 to 250, and so forth), and an approximation of their upper limit 

(99th percentile) regressed against SDI using PROC REG in SAS. This relationship 

was assumed to represent an approximate upper limit to average tree crown length for 

redwood in managed and unmanaged stands, for use constraining crown rise 

simulations within realistic limits.

Preparing data for sapwood analysis involved calculating heartwood diameter by 

subtracting the average live sapwood bandwidth from the total diameter inside bark 
Coast Redwood Live Crown and Sapwood Dynamics 

477

(DIB). Both DIB and heartwood diameter were converted to area. Sapwood crosssectional area (SA) for breast height and BLC were determined by subtracting 

heartwood area from basal area inside bark. Sapwood taper equations were fitted to 

sapwood data from each region using the non-linear regression analysis procedure 

PROC NLIN in SAS. The taper models predict SABLC as a function of SABH and 

breast height crown ratio (BHCR, defined as crown length/ (total height – 4.5ft)) for 

each region, and for all regions combined. Equations that predict SABH as a function 

of tree basal area were also fitted to sapwood and tree size data from each region 

using the linear regression analysis procedure PROC REG in SAS. 

Results 

Crown rise 

Of the 2,894 second-growth redwood trees within 234 plots at Railroad Gulch, 69 

percent did not show signs of forking or top damage, and 41 percent were classified 

as either dominant or codominant. Forty-four percent of intermediate and suppressed 

trees were forked or exhibited top damage. Among dominants and codominants, 

forked trees had the highest average crown ratios. Trees with top damage had lower 

crown ratios than other trees in the intermediate and suppressed crown class group 

(table 1). Therefore, trees with forks or top damage were excluded from analyses of 

crown ratio. Redwood tree and crown size varied according to position within the 

canopy (table 2). On average, edge trees were larger, more tapered, and had longer 

crowns than trees growing inside the stand (fig. 2). Average crown ratio among 

dominant and codominant trees in each plot decreased with increasing crowding 

(SDI). Dominant and codominant trees in plots with higher redwood SDI had higher 

crown base heights and less taper, but maintained similar live crown lengths to 

redwood trees growing in less crowded conditions (fig. 3). 

Table 1—Damage summary: count and crown ratio of second-growth redwood trees 

classified as either dominant or codominant (D+C), or intermediate or suppressed (I+S), with 

and without forking or top damage, at Railroad Gulch, JDSF. 

Number of trees Crown ratio

D+C I+S All trees D+C I+S All trees

Forked trees 40 52 92 0.48 0.35 0.41

Trees with top damage 129 732 861 0.42 0.30 0.32

Forked and top damage 156 754 910 0.44 0.30 0.33

No forking or top damage 1040 944 1984 0.43 0.36 0.39

All trees (incl. damaged) 1196 1698 2894 0.43 0.33 0.37

Table 2—Tree size and crown summary data for second-growth redwood trees without 

forking or top damage at Railroad Gulch, JDSF. Standard deviations listed in parentheses 

beside means for each crown class. 

Crown 

class

n DBH (in) HT (ft) H:D ratioa BLC (ft)b Crown 

ratio

Dominant 28 33.6 (9.2) 131.1 (18.1) 49.2 (09.9) 64.3 (14.3) 0.50 (0.11)

Codominant 1012 23.5 (5.9) 117.1 (20.6) 61.9 (11.9) 66.6 (16.0) 0.43 (0.11)

Intermediate 445 14.0 (4.8) 77.1 (23.1) 68.3 (16.0) 46.0 (17.5) 0.40 (0.15)

Suppressed 499 7.0 (4.2) 38.5 (17.7) 73.4 (23.5) 26.0 (12.3) 0.31 (0.15) a

H:D ratio = ratio of total height (ft) to diameter at breast height (ft). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

478

b

BLC = height to base of live crown.

Figure 2—Average crown ratio for each crown class (left), and for dominant and 

codominant second-growth redwood trees growing on stand edges and inside the 

stand (right) at Railroad Gulch, JDSF. Error bars depict standard deviation for each 

group mean. 

Figure 3—Average crown and stem taper data for dominant and codominant secondgrowth redwood trees and redwood stand density index (SDI) in 203 plots at Railroad 

Gulch, JDSF. 
Coast Redwood Live Crown and Sapwood Dynamics 

479

Species composition, aspect, and site index did not significantly affect redwood 

tree crown ratio. Dominant and codominant redwood crown ratios were slightly 

lower in plots with more Douglas-fir basal area, and slightly higher in plots with 

aspects tending towards northeast and in plots with higher site index, but these effects 

were not significant (Pr > t 0.49, 0.13, 0.46, respectively). Redwood crown ratio was 

unaffected by pre-harvest and current percent hardwood basal area and percent slope. 

Crown ratio was higher with greater relative height (height relative to average height 

of trees in each crown class group), and lower with increasing redwood SDI (fig. 4). 

The best crown ratio models in terms of AIC (goodness-of-fit criterion favoring 

models with fewer variables) included only tree location (edge or interior) and SDI 

(table 3). Model predictions indicated that tree location was a more important 

determinant of crown ratio among intermediate and suppressed trees than among 

dominants and codominants. The effects of relative height were important among 

trees in both crown class groups. 

Figure 4—Generalized linear mixed model predictions of redwood crown ratio among 

dominant and codominant (D+C) trees and intermediate and suppressed trees (I+S) 

in stand edge and interior locations (above), and for interior trees with different 

relative heights (below), at Railroad Gulch, JDSF. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

480

The approximate upper limit of the per-acre sum of redwood tree crown lengths 

in each plot attained 13,000 ft/ac at SDI 1000. The relationship was best described by 

a second-order polynomial equation (fig. 5).

Table 3—Generalized linear mixed effects models of redwood crown ratio as a function of 

tree location (stand edge, interior) and stand density index (SDI), with/without relative height 

(above/below), for dominant and codominant (D+C) and intermediate and suppressed (I+S) 

crown class groups at Railroad Gulch. Dummy variable for edge location is added to 

intercept; interior location is latent variable (intercept only).

Data Model fit Parameter Coefficient s.e. d.f. t Pr>|t|

D+C χ

2 = 10.19 Intercept (β0) 0.31800 0.03426 13 9.28 <.0001

(n=1028) AIC=-1709 Edge (d1) 0.01820 0.00926 987 1.96 0.0497

Relative height (β1) 0.16960 0.02980 987 5.69 <.0001

SDI (β2) -0.00009 0.00002 987 -4.47 <.0001

I+S χ

2 = 15.15 Intercept (β0) 0.34130 0.02655 13 12.86 <.0001

(n=900) AIC=-1011 Edge (d1) 0.08437 0.01452 859 5.81 <.0001

Relative height (β1) 0.13050 0.01857 859 7.03 <.0001

SDI (β2) -0.00010 0.00003 859 -3.35 0.0008

D+C χ

2 = 10.52 Intercept (β0) 0.48700 0.01721 13 28.29 <.0001

(n=1028) AIC=-1682 Edge (d1) 0.01917 0.00940 988 2.04 0.0417

SDI (β1) -0.00009 0.00002 988 -4.38 <.0001

I+S χ

2 = 16.02 Intercept (β0) 0.41040 0.02498 13 16.43 <.0001

(n=900) AIC=-969 Edge (d1) 0.09567 0.01482 860 6.46 <.0001

SDI (β1) -0.00010 0.00003 860 -3.59 0.0004

Relative height = tree height/average height for crown class group.

χ

2 = generalized chi-square for model.

Figure 5—Relationship between 99th percentile of crown length/ac in plots grouped 

by SDI and the average SDI for each group, where crown length/ac = 19.832 SDI -

0.0067 SDI2

. 

Sapwood taper 

Northern and southern sample trees were larger than trees from the central region 

where a wide range of tree sizes were sampled across all crown classes (table 4). 

Different taper model coefficients for region-specific models indicated that, on 

average, northern trees exhibited greater sapwood taper between breast height and 
Coast Redwood Live Crown and Sapwood Dynamics 

481

BLC (table 5, fig. 6). However, variability in sapwood taper within regions prevented 

detection of significant differences in taper between the different regions, justifying a 

combined model for the entire redwood range. When re-arranged to predict SABLC as 

a function of SABH, the non-linear power model gave a mean prediction error of 4.4 

in2 SABLC for n = 47 trees from northern, central, and southern regions. 

Table 4—Summary data for redwood sapwood sample trees by region.

Region Statistics DBH (in) Height (ft) BHCRa SABH (in2) SABLC (in2)

Northern Mean 31.1 115.8 0.73 179.5 122.7

(n=19) s.d. 7.5 24.6 0.11 69.4 47.8

Max. 51.4 158.8 0.93 304.6 204.2

Min. 19.4 75.1 0.49 84.0 54.7

Central Mean 13.6 78.1 0.68 59.3 41.2

(n=10) s.d. 10.3 42.6 0.13 73.3 52.9

Max. 36.5 148.3 0.84 248.3 179.5

Min. 3.7 27.9 0.50 8.3 6.9

Southern Mean 29.1 111.8 0.56 113.4 69.3

(n=18) s.d. 6.9 21.6 0.12 45.4 34.1

Max. 43.4 163.0 0.76 215.4 137.0

Min. 18.5 71.5 0.37 52.7 27.2 a

BHCR = breast height crown ratio; crown length/(total height - 4.5 ft). 

Table 5—Summary statistics for sapwood taper model SABLC = SABH * (1-(1-BHCR)a).

Location Coefficient s.e. Appr. 95% confidence limits

Lower Upper

Southern 1.1549 0.1123 0.9180 1.3917

Central 1.0776 0.0771 0.9031 1.2521

Northern 0.9020 0.0737 0.7471 1.0569

Combined 1.0362 0.0565 0.9224 1.1499

Regional coefficients for linear models fitted to tree basal area and SABH data 

were separated by greater than two standard errors (north: β1 = 0.20611 s.e. = 0.015; 

south: β1 = 0.15058 s.e. = 0.012), indicating that, on average, northern trees contained 

relatively more sapwood than southern trees for a given DBH. The models for 

northern and southern trees were compared against the model presented by Berrill 

and O’Hara (2007a) for 891 redwood trees >4 in DBH growing in all canopy 

positions within even-aged and multiaged stands on JDSF. Predicted sapwood at 

breast height for dominant and codominant sample trees from the northern and 

southern regions exceeded the published SABH – BA model predictions (fig. 6). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

482

Figure 6—Sapwood taper models for northern, central, and southern regions 

SABLC/SABH = 1-(1-BHCR)

a (left), and SABH – DBH relations for northern and southern 

regions SABH=0.155 a π (1.27 DBH)

2 and existing model for the central region (Berrill 

and O’Hara 2007a) (right). 

Discussion

Greater incidence of top damage sustained by relatively short redwood trees at 

Railroad Gulch reminds us that care must be taken to protect residual trees and 

advanced regeneration during partial harvesting. Damage rates reported in table 1

include damage from natural causes and harvesting, and could be used to estimate 

number of replacement trees required in younger cohorts under multiaged 

management. Retaining more replacement trees in younger cohorts leaves less 

growing space for other trees within multiaged stand structures (Berrill and O’Hara 

2009).

The crown ratio models apply to redwood trees in the oldest cohort of uncut and 

partially cut second-growth stands around age 85 years at Railroad Gulch. Plots with 

lower SDI had total crown lengths/ac below the curve for maximum crown length 

(fig. 5) suggesting that maximum crown length had not been attained 20 years after 

partial harvesting. Therefore the crown ratio model slope coefficients for SDI may be 

too low, and should be revised after future re-measurements. The models can be 

applied to simulate crown rise in managed stands using a bi-conditional approach 

where crowns do not rise until sometime after partial harvesting when crown 

length/ac approaches the upper limit (fig. 5), after which time crown ratio can be 

predicted from SDI (table 3). The relationships between stand density and tree taper, 

crown length and height, and crown ratio among dominant and codominant trees (fig.

3) may be explained by ‘plasticity’ in redwood physiology. Trees in crowded plots 

may have responded with increased allocation of energy to height growth, at the 

expense of diameter growth, resulting in reduced taper. While tempting to infer that 

redwood trees can maintain a long live crown under crowded conditions, it is more 

likely that winners and losers had emerged; that loss of crown length resulting from 

crowding (fig. 4) eventually led less competitive trees to relinquish their dominance 

within the canopy. 
Coast Redwood Live Crown and Sapwood Dynamics 

483

Redwoods regulate water use poorly (Burgess and Dawson 2004). We found that, 

on average, southern trees in hotter, drier climates had less SABH for a given tree size 

but a lower rate of sapwood taper above breast height (fig. 6). These differences may 

reflect on adaptation to conserve water resources in drier climates by restricting sap

flow. If the current trend of decreasing fog (Johnstone and Dawson 2010) continues, 

central and northern redwood trees may respond to increased evaporative demand by 

altering sapwood dimensions and crown morphology. Our sapwood taper sampling 

controlled for tree size and crown class between northern and southern regions, 

focusing on large dominant and codominant redwood. Faster growth in the north 

meant that sample trees were younger than trees of equivalent size in the south. 

Apparent differences in sapwood taper between regions (fig. 6) could be age-related. 

A large sample would be needed to examine effects of tree age, size, and position 

within the stand. 

We present a non-linear power model of sapwood taper that provides a more 

realistic depiction of sapwood taper than the existing model, SABLC = 0.7460SABH – 

3.8293(HBLC – 1.37) (Stancioiu and O’Hara 2005). The published model predicts 

negative values for SABLC for trees with small SABH, while our model makes realistic 

predictions for trees of all SABH and BHCR. Predicting SABLC as a function of BHCR 

in the non-linear model has the desirable property that when BHCR =1, the BLC is at 

breast height and, therefore, SABLC=SABH, making negative predictions for SABLC

impossible. We also developed models to facilitate implementation of the taper 

model by predicting SABH from DBH (fig. 6), but these only apply to large dominant 

and codominant trees (table 4), whereas the model presented by Berrill and O’Hara 

(2007a) applies to a wider range of tree sizes and growing conditions. When applied 

in combination, crown ratio and sapwood models can be used to predict SABLC from 

traditional forest inventory data. First, SABH can be predicted from DBH. Then, the 

sapwood taper model can be applied to the estimate of SABH, and BHCR calculated 

from tree height and BLC data or crown ratio model predictions, giving predicted 

SABLC, which in turn allows for prediction of tree leaf area and stand LAI. 

References 

Antos, J.A.; Parish, R.; Nigh, G.D. 2010. Effects of neighbours on crown length of Abies

lasiocarpa and Picea engelmannii in two old-growth stands in British Columbia.

Canadian Journal of Forest Research 40: 638-647.

Berrill, J-P.; O'Hara, K.L. 2007a. Patterns of leaf area and growth efficiency in young 

even-aged and multiaged coast redwood stands. Canadian Journal of Forest Research

37(3): 617-626.

Berrill, J-P.; O’Hara, K.L. 2007b. Modeling coast redwood variable retention 

management regimes. In: Standiford, R.B.; Giusti, G.A.; Valachovic, Y.; Zielinski, 

W.J., Furniss, M.J., editors. Proceedings of the redwood region forest science 

symposium: What does the future hold? Gen. Tech. Rep. PSW-GTR-194. Albany, CA: 

U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station: 

261-269.

Berrill, J-P.; O’Hara, K.L. 2009. Simulating multiaged coast redwood stand development: 

interactions between regeneration, structure, and productivity. Western Journal of

Applied Forestry 24(1): 24-32.
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Burgess, S.S.O.; Dawson, T.E. 2004. The contribution of fog to the water relations of 

Sequoia sempervirens (D.Don): foliar uptake and prevention of dehydration. Plant 

Cell Environment 47(8): 1023-1034.

Hasenauer, H.; Monserud, R.A. 1996. A crown ratio model for Austrian forests. Forest

Ecology and Management 84(1-3): 49-60.

Johnstone, J.A.; Dawson, T.E. 2010. Climatic context and ecological implications of 

summer fog decline in the coast redwood region. Proceedings of the National

Academy of Sciences 107 (10): 4533-4538.

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Karst.]. Trees - Structure and Function 18(4): 408-421.

Maguire, D.A.; Batista, J.L. 1996. Sapwood taper models and implied sapwood volume 

and foliage profiles for Douglas-fir. Canadian Journal of Forest Research 26 (5): 849-

861 

SAS Institute Inc. 2004. SAS/STAT 9.1 user’s guide, Vols. 1-7. 1st edition. Cary, NC: SAS 

Institute Inc.

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form—the pipe model theory. II. Further evidence of the theory and its application 

in forest ecology. Japanese Journal of Ecology (14): 133-139. 

Stancioiu, P.T.; O’Hara, K.L. 2005. Sapwood area—leaf area relationships for coast 

redwood. Canadian Journal of Forest Research 35 (5): 1250-1255. 

Valentine, H.T.; Ludlow, A.R.; Furnival, G.M. 1994. Modeling crown rise in even-aged 

stands of Sitka spruce or loblolly pine. Forestry Ecology and Management 69(1-3): 

189-197.

Waring, R.H.; Schroeder, P.E.; Oren, R. 1982. Application of the pipe model to predict 

canopy leaf area. Canadian Journal of Forest Research (12): 556-560.
485

Influence of Tree Spatial Pattern and

Sample Plot Type and Size on Inventory 

Estimates for Leaf Area Index, Stocking, 

and Tree Size Parameters

John-Pascal Berrill1 and Kevin L. O’Hara2

Abstract

Sampling with different plot types and sizes was simulated using tree location maps and data 

collected in three even-aged coast redwood (Sequoia sempervirens) stands selected to 

represent uniform, random, and clumped spatial patterns of tree locations. Fixed-radius 

circular plots, belt transects, and variable-radius plots were installed by simulation. Bootstrap 

sample means, coefficient of variation (CV), and 95 percent confidence intervals were 

calculated for sample estimates of eight important stand parameters. Percent CV models 

depicted sample precision and enable calculation of minimum sample size for forest 

inventories. Precision differed between stand parameters e.g., dominant height and mean top 

height estimates were most precise; in many cases four times as precise as density estimates. 

Precision was affected more by spatial pattern than plot type, and generally ranked: uniform > 

random >> clumped. Density, average diameter, and average height estimate precision was 

especially sensitive to spatial pattern, and generally poorer in variable-radius plots. However, 

variable-radius plots generally produced the most precise estimates of basal area, volume, and 

leaf area index. Quantitative descriptions of sample stand structure and spatial pattern provide 

a basis for comparison or application of results to other forests with similar characteristics.

Key words: bootstrap confidence intervals, coefficient of variation, precision, 

Ripley’s K, sampling simulation, Sequoia sempervirens 

Introduction

Forest inventory data are increasingly being used for objectives other than 

estimating wood product yields. Objectives include assessment of ecosystem 

structure and function, carbon storage and sequestration, and “ground truthing” 

remotely sensed data. Users of forest inventory data are often interested in a variety 

of parameters (e.g., stem density, stocking, leaf area index) and demand different 

levels of accuracy and precision of sample estimates. Factors such as forest 

community composition, size, and structure influence sample design when the 

objective is to obtain an adequate sample with minimal sampling effort. Comparing 

estimates of precision across a wide range of variability in tree size or spatial patterns 

in real stands shows how each variable affects precision. The influence of sample 

plot type and size, and spatial pattern of tree locations on the accuracy and precision 

of key stand parameter estimates has not been examined in regenerating stands of 

coast redwood (Sequoia sempervirens) in north coastal California. 

 

1

Assistant Professor, Department of Forestry and Wildland Resources, Humboldt State University, 1 

Harpst St, Arcata, CA 95521. (pberrill@humboldt.edu).

2

Professor, Department of Environmental Science, Policy, and Management, University of California, 

Berkeley. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

486

Redwood is shade tolerant and long lived. Clumping of stump sprout 

regeneration around cut stumps results in aggregated spatial patterns. As a 

consequence of these and other factors, regenerating redwood stands can have wide 

tree-size distributions and complex spatial arrangements of trees. Since spatial pattern 

is expected to affect precision of estimates obtained from sample plots (Lessard et al.

2002, Martin 1983), it may be advantageous to account for spatial pattern when 

sampling by altering plot size or the number of plots, or by stratifying sampling 

according to differences in spatial pattern. However, less is known about how much 

or how differently spatial pattern can affect inventory estimates for different 

parameters obtained from different plot types and plot sizes.

Sampling efficiency in forest types other than redwood has been examined 

extensively, but only for a restricted number of comparisons e.g., between plot types 

or stand parameters. When viewed collectively, patterns emerge from these results: 

Fixed-radius circular plots generally yielded the most accurate estimates of stand 

density and were more time-efficient than other fixed-area methods. Variable-radius 

plots were most time-efficient, but tended to underestimate density. Belt transects 

were least time-efficient (Sparks et al. 2002). Bormann (1953) tested different fixedarea plot shapes, and found that longer belt transects produced more precise estimates 

than shorter rectangular plots of the same area when sampling across changing 

contour, soil, or vegetation, and when sampling sporadic species. Lessard et al.

(2002) showed that, when sampling an average of n trees per plot, density estimates 

from fixed-radius plots were more precise than estimates obtained from n-tree 

distance sampling. However, fixed-area sampling was generally more timeconsuming than distance sampling methods. Kint et al. (2004) found that distance 

sampling was generally more efficient than plot sampling for estimation of structural 

indices (i.e., nearest-neighbor spatial statistics; species distribution patterns; tree-size 

differentiation) in forest stands. Markedly different sample sizes may be needed to 

achieve a specified level of accuracy or precision for different attributes or in stands 

with different tree sizes (Gray 2003). Sampling can be more efficient when more 

numerous smaller plots are installed, however below a certain plot size, estimates are 

prone to bias and many more plots are required to achieve a given level of precision 

(Lynch 2003). 

The objective of our study was to examine how sample estimates for eight 

important stand parameters were affected by sample plot type and size, and the 

spatial pattern of tree locations. Inventory estimates for traditional forest stand 

parameters (basal area, volume, density, average tree diameter and height, and 

dominant height), mean top height (an alternate height metric), and leaf area index 

were obtained by simulating the installation of three different plot types – each 

having a wide range of plot sizes tested - in three redwood stands with different 

spatial patterns. Leaf area index (LAI) was examined because it is emerging as a key 

variable in forest ecosystem research and modeling (Asner et al. 2003, Berrill and 

O’Hara 2007) and management (O’Hara 1998). Dominant height and mean top 

height were examined because of their role in site index determination. Site index 

estimates are sensitive to measurement error, height growth prediction error, sample 

size, and method of calculating average height for the larger trees in the stand (Garcia 

1998). Larger trees are selected based on conventions such as ‘top height’ or 

‘dominant height’. Top height is the average height of the n largest diameter trees per 

unit area. Theoretically this metric is not affected by thinning methods that target 

smaller trees for removal. Dominant height is the average height of dominant trees, or 
Influence of Tree Spatial Pattern and Sample Plot Type and Size on Inventory Estimates for Leaf 

Area Index, Stocking, and Tree Size Parameters

487

dominant and codominant trees, or trees above a certain proportion of the dbh 

distribution. It can be sensitive to changes in density when based on proportions of 

the dbh distribution. Sampling simulation results for these eight stand parameters 

were obtained in stands with similar structural characteristics but different spatial 

patterns (i.e., uniform, random, or clumped) to examine effects of spatial pattern on 

sample estimates. 

Methods

Redwood-dominated stands were sampled on Jackson Demonstration State 

Forest (JDSF) near Ft. Bragg, Mendocino County, California. Redwood stands on 

JDSF regenerated naturally, occasionally supplemented by planted seedlings, after 

the old growth forest was progressively removed mainly by diameter-limit cutting or 

commercial clearcutting between 1880 and 1950. In three stands, a well-stocked area 

dominated by redwood was selected for measurement. A large rectangular sample 

block was established: (i) in a dense stand located on an upper slope (0.2 ha); (ii) in a 

less dense stand on a lower slope (0.5 ha), and; (iii) in a stand comprising widelyspaced clumps of redwood trees located on an alluvial flat (0.4 ha). All trees >10 cm 

diameter at 1.37 m breast height (dbh) were mapped, and measured for dbh, total 

height, and height to live crown base – defined as stem height above which the tree 

crown was generally continuous on one or more sides. Two breast height increment 

cores gave sapwood data for tree leaf area estimation. Pith-to-bark cores collected 

from dominant trees gave approximate breast height age of the sample stands. 

Tree leaf area was predicted for each tree using tree-size and sapwood crosssectional area data and equations presented by Berrill (2008) and Stancioiu and 

O’Hara (2005). Tree volume was estimated from dbh and height (Wensel and 

Krumland 1983). Tree data, and volume and leaf area estimates were summarized for 

each large rectangular sample block. The spatial pattern of tree locations in each 

block was characterized using the Ripley’s K-function (Ripley 1981). Since a 

uniform pattern was not detected in any block, a low thinning was simulated in the 

largest block with the objective of reducing density in sprout clumps to create a more 

uniform pattern and concurrently reducing tree-size variability (to better align it with 

variability in the other two blocks). 

Sampling within the three large rectangular blocks (each representing either 

uniform, random, or clumped patterns) was simulated for three plot types across a 

range of plot sizes. Circular fixed-radius plots, variable-radius plots, and fixed-width 

transect plot types were tested. Toroidal edge correction was applied to each large 

rectangular block (Haase 1995). Thirty randomly located plot centers were generated 

using the S-Plus Spatial Module (Insightful Corp. 2005) for sampling within each 

block. Trees were classified as ‘inside plot’ when their stem center point fell within 

the boundaries of fixed-area circular or transect plots or within the critical radius Ri

for variable-radius sample plots. Trees inside plot boundaries were identified by 

calculating an inter-point distance between plot center and each tree location defined 

by pairs of x and y coordinates and comparing the inter-point distance against the 

defined plot radius or critical radius. 

Circular fixed-radius plots of areas 0.005, 0.01, 0.015...0.1 ha were established 

at each plot center point. Randomly located plot centers defined the easting (the x of 

an x,y pair of location coordinates) for the centerline of north-south fixed-area belt 
GENERAL TECHNICAL REPORT PSW-GTR-238 

488

transects running the entire length (same x, vary y approx. 50 m) of each large block. 

The transect width was varied to create rectangular belt transects with sample areas 

of 0.005, 0.01, 0.015...0.1 ha. Tree size and leaf area data for trees in each fixed-area 

circular and transect plot were summarized to the stand-level giving basal area (BA), 

volume, LAI, density, arithmetic average dbh and average height. Dominant height 

was calculated as average height of trees with dbh above the 75th percentile of the 

dbh distribution in each sample plot. Mean top height was average height of the 

largest 100 stems/ha in terms of dbh in each sample plot. 

Variable-radius plots were established on each randomly located plot center. A 

range of BA factors (BAF) were applied. Basal area per hectare was obtained by 

multiplying the count of sample trees by the BAF. The tree factor gave the number of 

trees per hectare represented by each sample tree (Husch et al. 2003). Stand density 

was the sum of tree factors for sample trees. Volume per hectare was calculated from 

tree volume and the tree factor for all sample trees. Leaf area index (LAI) was 

calculated from tree leaf area LAi and the tree factor TFi for all sample trees, such 

that: LAI = ∑(LAiTFi)/10000. The weighted average height of trees in the upper 25

percent of the diameter distribution, weighting by the tree factor, gave dominant 

height. The approximate diameter distribution was obtained by replicating each 

sample tree dbh a total of TFi times. Dominant trees had a dbh greater than the 75th

percentile of the replicated distribution. An approximate mean top height was 

obtained by taking the TFi-weighted average height of trees representing the largest 

100 stems/ha. 

For each plot type, re-sampling with replacement from the summary data for 

each plot size gave bootstrapped means, variances, and 95 percent confidence 

intervals for each stand parameter (Crawley 2002). To enable application of our 

findings in stands with different densities (having different number of trees per plot 

for a given plot size), results were presented in terms of average number of trees per 

plot instead of plot size, and bootstrap means and confidence intervals were presented 

as percent deviations from the population summary data for the large blocks. Results 

were summarized to give the minimum average number of trees per plot needed to 

obtain 95 percent confidence intervals for sample estimates within ±5 percent or ±10 

percent deviation from the estimate. Percent deviations of the bootstrap sample 

means and confidence intervals from the population summary data were plotted 

against the average number of trees at each plot size or level of BAF, depicting 

sample mean estimates and precision. Coefficient of variation of the mean (CV) – the 

ratio of bootstrap sample standard deviation to the sample mean – was also calculated 

in percent terms to enable direct comparison between stands with different spatial 

patterns that each had different stand parameters. To facilitate interpretation and 

future implementation of results, percent CV (Y) was regressed against average 

number of trees per plot (X) for each plot type sampling each spatial pattern. Five 

equations were tested: Power: b = aXY Logarithmic: += ln( ) XbaY

Exponential: bX = aeY Type III exponential: Xb aeY / = and Schumacher: c bX aeY − = (Schumacher 1939).

Fitted models were compared in terms of goodness-of-fit (AIC) and residual bias. 

Percent CV predicted using the best model was plotted against average number of 

trees per plot for each plot type and spatial pattern, depicting differences in sample 
Influence of Tree Spatial Pattern and Sample Plot Type and Size on Inventory Estimates for Leaf 

Area Index, Stocking, and Tree Size Parameters

489

precision. Data were analyzed using S-Plus statistical analysis software (Insightful 

Corp. 2005). 

Results

The three sample stands had relatively similar stocking in terms of BA and LAI, 

but different densities, average tree diameter, and total standing volume. Low 

thinning simulated in Block 1 removed stems ≤ 40 cm dbh, all Douglas-fir, and 

reduced density in redwood sprout clumps. Average tree size increased from 55 cm 

to 78 cm dbh. Dominant height, calculated as the average height of trees in the top 25 

percent of the dbh distribution, increased from 54.4 m to 58.0 m as a result of low 

thinning. Mean top height, the average height of the 100 largest dbh trees per ha, was 

less affected by thinning. It only decreased from 56.2 m to 55.4 m. The resulting pure 

redwood stand had a uniform spatial pattern at scales up to 7 m. Thinning to create a 

uniform pattern reduced density by 65 percent and BA by 40 percent in the lower 

slope stand, and the range and variability of tree sizes became comparable to the 

stands on the upper slope and alluvial flat with random and clumped spatial patterns 

respectively (table 1). 

Stem maps and Ripley’s K with L-function transformation depict spatial patterns 

in the three stands (fig. 1). The L(d) statistic for the upper-slope stand stayed within 
GENERAL TECHNICAL REPORT PSW-GTR-238 

490

‘envelope’ limits of complete spatial randomness despite the presence of a few 

multiple-stem clumps of redwood. Significant clumping was detected in the alluvial 

flat stand at scales < 12 m, while complete spatial randomness beyond 12 m 

suggested that widely spaced clumps were randomly distributed throughout the stand. 

Figure 1—Stem maps and Ripley’s K with L-function transformation for the lower 

slope (left), upper slope (center), and alluvial flat (right) stands. Circles represent tree 

locations in stem maps (above) and the L(d) statistic (below); lines represent upper 

and lower limits of complete spatial randomness. Uniform pattern indicated by L(d) 

falling below lower limit; clumped pattern when L(d) above upper limit. 

Sample simulation results showed that sample estimates from small plots 

deviated from the population mean. Differences between the estimate for the large 

sample block and the average estimate from n = 30 randomly-located sample plots 

were evident when fewer than 20 trees per plot were sampled in the uniform thinned 

stand and when sampling fewer than 30 trees per plot in the stand with a random 

spatial pattern. Results indicated that some differences between population and 

sample estimates can be expected irrespective of plot type or number of trees per plot 

when using 30 randomly-located plots to sample clumped stands (fig. 2). 

Sample variance for all stand parameters decreased as plot size increased. These 

increases in sample precision are depicted as ‘tapering’ of 95 percent confidence 

intervals around the bootstrap mean of sample plot estimates. However, the marginal 

benefit – in terms of greater precision – of expanding fixed-area plots or lowering the 

BAF in variable-radius plots to capture more trees generally decreased as number of 

trees per plot progressively increased. This effect was most pronounced when the 

average number of trees per plot increased beyond 30 trees for estimates of BA, 

volume, and LAI, and beyond 20 trees for dominant and mean top height. Results for 

density generally indicated that important improvements in precision were still being 

obtained as plots were expanded to capture around 40 trees per plot (fig. 2). 
Influence of Tree Spatial Pattern and Sample Plot Type and Size on Inventory Estimates for Leaf 

Area Index, Stocking, and Tree Size Parameters

491

Sample precision varied between 

stand parameters, plot types, and spatial 

patterns. There was no ‘best plot type’ 

that gave the most precise estimates for 

all stand parameters in all stands. 

Density estimates were especially 

sensitive to plot type. The 95 percent

confidence intervals for density 

estimates were narrowest for circular 

fixed-radius plots and 50 m north-south 

transects. Transects gave the most precise estimates of density when an average of 30

to 40 trees per plot were sampled. Variable-radius plots generally produced more 

precise estimates of stand BA, volume, and LAI, especially in the clumped stand. 

5

10152025303540

-2 0

-1 0

0

1 0

2 0 B a s a l a r e a

5

10152025303540

-2 0

-1 0

0

1 0

2 0 V o lu m e

5

10152025303540

-2 0

-1 0

0

1 0

2 0 S ta n d L A

5

10152025303540

-2 0

-1 0

0

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5

10152025303540

-2 0

-1 0

0

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5

10152025303540

-2 0

-1 0

0

1 0

2 0A v e r a g e h e ig h t

5

10152025303540

-1 0

- 5

0

5

1 0D o m in a n t 

5

10152025303540

-1 0

- 5

0

5

1 0M ea 

C . V a r ia b le - r a

A v e ra g e n u m b 

B o o ts tr a p m e a n = 

5

10152025303540

-2 0

-1 0

0

1 0

2 0 B a s a l a r e a

5

10152025303540

-2 0

-1 0

0

1 0

2 0 V o lu m e

5

10152025303540

-2 0

-1 0

0

1 0

2 0 S ta n d L A I

5

10152025303540

-2 0

-1 0

0

1 0

2 0 D en

5

10152025303540

-2 0

-1 0

0

1 0

2 0 A v e ra g e D B H

5

10152025303540

-2 0

-1 0

0

1 0

2 0A v e r a g e h e ig h t

5

10152025303540

-1 0

- 5

0

5

1 0D o m in a n t h

5

10152025303540

-1 0

- 5

0

5

1 0M ean 

B . T r a n s e c t p lo

Percent deviation (%)

5

10152025303540

-2 0

-1 0

0

1 0

2 0 B a s a l a r e a

5

10152025303540

-2 0

-1 0

0

1 0

2 0 V o lu m e

5

10152025303540

-2 0

-1 0

0

1 0

2 0 S ta n d L A I

5

10152025303540

-2 0

-1 0

0

1 0

2 0 D en

5

10152025303540

-2 0

-1 0

0

1 0

2 0 A v e ra g e D B H

5

10152025303540

-2 0

-1 0

0

1 0

2 0A v e r a g e h e ig h t

5

10152025303540

-1 0

- 5

0

5

1 0D o m in a n t h

5

10152025303540

-1 0

- 5

0

5

1 0M ean 

U N IF O R M S P A

A . F ix e d - r a d iu s 

101520253035404550

-2 0

-1 0

0

1 0

2 0 B a s a l a r e a 101520253035404550

-2 0

-1 0

0

1 0

2 0 V o lu m e 101520253035

404550

-2 0

-1 0

0

1 0

2 0 S ta n d L A 1015202530354045

50

-2 0

-1 0

0

1 0

2 0 D en

101520253035404550

-2 0

-1 0

0

1 0

2 0A v e ra g e D B H 101520253035404550

-2 0

-1 0

0

1 0

2 0A v e r a g e h e ig h t 101520253035404550

-1 0

- 5

0

5

1 0D o m in a n t 101520253035404550

-1 0

- 5

0

5

1 0M ea 

C . V a r ia b le - r a

A v e ra g e n u m b 

B o o ts tr a p m e a n = 

101520253035404550

-2 0

-1 0

0

1 0

2 0 B a s a l a r e a 101520253035404550

-2 0

-1 0

0

1 0

2 0 V o lu m e 10152025

3035404550

-2 0

-1 0

0

1 0

2 0 S ta n d L A I 101520253035404550

-2 0

-1 0

0

1 0

2 0 D en

101520253035404550

-2 0

-1 0

0

1 0

2 0 A v e ra g e D B H 101520253035404550

-2 0

-1 0

0

1 0

2 0A v e r a g e h e ig h t 101520253035404550

-1 0

- 5

0

5

1 0D o m in a n t h 101520253035404550

-1 0

- 5

0

5

1 0M ean 

B . T r a n s e c t p lo

Percent deviation (%)

101520253035404550

-2 0

-1 0

0

1 0

2 0 B a s a l a r e a 101520253035404550

-2 0

-1 0

0

1 0

2 0 V o lu m e 1015202530

35404550

-2 0

-1 0

0

1 0

2 0 S ta n d L A I 101520253035404550

-2 0

-1 0

0

1 0

2 0 D en

101520253035404550

-2 0

-1 0

0

1 0

2 0 A v e ra g e D B H 101520253035404550

-2 0

-1 0

0

1 0

2 0A v e r a g e h e ig h t 101520253035404550

-1 0

- 5

0

5

1 0D o m in a n t h 101520253035404550

-1 0

- 5

0

5

1 0M ean 

R AN D O M SPAT

A . F ix e d - r a d iu s 

101520253035404550

-2 0

-1 0

0

1 0

2 0 B a s a l a r e a 101520253035404550

-2 0

-1 0

0

1 0

2 0 V o lu m e 101520253035

404550

-2 0

-1 0

0

1 0

2 0 S ta n d L A 1015202530354045

50

-2 0

-1 0

0

1 0

2 0 D en

101520253035404550

-2 0

-1 0

0

1 0

2 0A v e ra g e D B H 101520253035404550

-2 0

-1 0

0

1 0

2 0A v e r a g e h e ig h t 101520253035404550

-1 0

- 5

0

5

1 0D o m in a n t 101520253035404550

-1 0

- 5

0

5

1 0M ea 

C . V a r ia b le - r a

A v e ra g e n u m b 

B o o ts tr a p m e a n = 

101520253035404550

-2 0

-1 0

0

1 0

2 0 B a s a l a r e a 101520253035404550

-2 0

-1 0

0

1 0

2 0 V o lu m e 10152025

3035404550

-2 0

-1 0

0

1 0

2 0 S ta n d L A I 101520253035404550

-2 0

-1 0

0

1 0

2 0 D en

101520253035404550

-2 0

-1 0

0

1 0

2 0 A v e ra g e D B H 101520253035404550

-2 0

-1 0

0

1 0

2 0A v e r a g e h e ig h t 101520253035404550

-1 0

- 5

0

5

1 0D o m in a n t h 101520253035404550

-1 0

- 5

0

5

1 0M ean 

B . T r a n s e c t p lo

Percent deviation (%)

101520253035404550

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-1 0

0

1 0

2 0 B a s a l a r e a 101520253035404550

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-1 0

0

1 0

2 0 V o lu m e 1015202530

35404550

-2 0

-1 0

0

1 0

2 0 S ta n d L A I 101520253035404550

-2 0

-1 0

0

1 0

2 0 D en

101520253035404550

-2 0

-1 0

0

1 0

2 0 A v e ra g e D B H 101520253035404550

-2 0

-1 0

0

1 0

2 0A v e r a g e h e ig h t 101520253035404550

-1 0

- 5

0

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1 0D o m in a n t h 101520253035404550

-1 0

- 5

0

5

1 0M ean 

C LU M P E D S P A

A . F ix e d - r a d iu s 

Figure 2—Bootstrap sample means and 

confidence intervals (α = 0.05) for stand 

parameters in terms of percent deviation 

from large-block ‘population’ values using 

fixed-radius circular plots (A), belt 

transects (B), and variable-radius plots 

(C) in redwood stand with uniform spatial 

pattern (upper left), random spatial 

pattern (upper right), and clumped spatial 

pattern (lower left).
GENERAL TECHNICAL REPORT PSW-GTR-238 

492

Plot type had little effect on precision of estimates in the uniform stand where ≤10 

trees per plot were needed to obtain a 95 percent confidence interval of ±5 percent

deviation from estimates of average dbh, average height, dominant height, or mean 

top height in all plot types (table 2).

Sample estimates for the clumped stand were almost always least precise. 

Variable-radius plots produced much poorer estimates of density in stands with 

random and clumped spatial patterns. Variable-radius plots needed an average of 42 

trees per plot to achieve a 95 percent confidence interval of ±10 percent deviation 

from density estimates in the stand with a random spatial pattern. This level of 

precision was not achievable sampling the clumped stand with over 50 trees per plot 

in 30 randomly located variable-radius plots (fig. 2). However, regression models 

depicting relationships between coefficient of variation (percent) and average number 

of trees per plot indicated that spatial pattern barely affected the precision - in terms 

of coefficient of variation – of variable-radius plot estimates of BA, volume, and 

LAI. Spatial pattern also had less effect on variable-radius plot dominant height and 

mean top height estimate precision than estimates from fixed-radius circular plots or 

belt transects. In general, sample precision was affected more by spatial pattern than 

plot type (fig. 3). Models describing coefficient of variation as a function of the 

number of trees per plot for each plot type and spatial pattern (table 3) had average 

prediction errors (RMSE) of only 1.1 percent (max. error 2.3 percent). 
Influence of Tree Spatial Pattern and Sample Plot Type and Size on Inventory Estimates for Leaf 

Area Index, Stocking, and Tree Size Parameters

493

Figure 3—Effect of spatial pattern (left) and plot type (right) on coefficient of variation 

(percent) for sample estimates from n = 30 fixed-radius circular plots, 50-m belt 

transects, and variable-radius plots in stands with uniform, random, or clumped 

spatial patterns.

Discussion

Sample precision is affected by stand structure (e.g., Gray 2003) and spatial 

pattern of tree locations (e.g., Lessard et al. 2002). Confounding effects of structural 

differences were reduced by sampling even-aged redwood stands with similar 

stocking (BA, LAI). Thinning in Block 1 (the older stand) reduced tree size 

variability to levels comparable with the two other (younger) stands (table 1). 

Thinning had a greater impact on the estimate of dominant height than mean top 

height, suggesting that measures of top height are more robust metrics than dominant 

height for site index estimation when diameter distributions of even-aged stands are 

altered by low thinning. However, both top height and dominant height estimates are 

sensitive to plot size due to tree selection effects; estimates typically increase with 

increasing plot size (Garcia 1998; Magnussen 1999). Similarly, estimates from 

smaller plots may be more sensitive to spatial autocorrelation of tree size i.e., from 

microsite differences and genetics of sprouting species such as redwood. The plot 

size effect was evident in this study when increasing bootstrap means for dominant 

height and mean top height of redwood were observed with increasing plot size in 

most sampling simulations irrespective of plot type or spatial pattern (fig. 2). 

5

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0

1 0

2 0

3 0

4 0

5 0 B a s a l a r e a

5

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1 0

2 0

3 0

4 0

5 0 V o lu m e

5

10152025303540

0

1 0

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3 0

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5

10152025303540

0

2 0

4 0

6 0

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5

10152025303540

0

1 0

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5

10152025303540

0

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5

10152025303540

0

5

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D o m in a n t h e

5

10152025303540

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5

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M ean 

B . R a n d o m s p a t 

5

10152025303540

0

1 0

2 0

3 0

4 0

5 0 B a s a l a r e a

5

10152025303540

0

1 0

2 0

3 0

4 0

5 0 V o lu m e

5

10152025303540

0

1 0

2 0

3 0

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5

10152025303540

0

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4 0

6 0

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5

10152025303540

0

1 0

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3 0A v e ra g e D B H

5

10152025303540

0

1 0

2 0

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5

10152025303540

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5

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D o m in a n t h

5

10152025303540

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5

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M ean 

C . C lu m p e d s p

A v e ra g e n u m b e 

P l o t t y p e : f i x e d - r a d i u s 

5

10152025303540

0

1 0

2 0

3 0

4 0

5 0 B a s a l a r e a

5

10152025303540

0

1 0

2 0

3 0

4 0

5 0 V o lu m e

5

10152025303540

0

1 0

2 0

3 0

4 0

5 0 S ta n d L A I

5

10152025303540

0

2 0

4 0

6 0

8 0 D en

 

5

10152025303540

0

1 0

2 0

3 0 A v e ra g e D B H

5

10152025303540

0

1 0

2 0

3 0A v e r a g e h e ig h t

 

5

10152025303540

0

5

1 0

1 5

D o m in a n t h

5

10152025303540

0

5

1 0

1 5

M ean 

E FFE C T O F P L

A . U n if o r m s p a t 

5

10152025303540

0

1 0

2 0

3 0

4 0

5 0 B a s a l a r e a

5

10152025303540

0

1 0

2 0

3 0

4 0

5 0 V o lu m e

5

10152025303540

0

1 0

2 0

3 0

4 0

5 0 S ta n d L A I

 

5

10152025303540

0

2 0

4 0

6 0

8 0 D en

 

5

10152025303540

0

1 0

2 0

3 0 A v e ra g e D B H

5

10152025303540

0

1 0

2 0

3 0A v e r a g e h e ig h t

 

5

10152025303540

0

5

1 0

1 5

D o m in a n t h

5

10152025303540

0

5

1 0

1 5

M ean 

E FFE C T O F S P

A . F ix e d - r a d iu s 

5

10152025303540

0

1 0

2 0

3 0

4 0

5 0 B a s a l a r e a

5

10152025303540

0

1 0

2 0

3 0

4 0

5 0 V o lu m e

5

10152025303540

0

1 0

2 0

3 0

4 0

5 0 S ta n d L A I

5

10152025303540

0

2 0

4 0

6 0

8 0 D en

5

10152025303540

0

1 0

2 0

3 0 A v e ra g e D B H

 

5

10152025303540

0

1 0

2 0

3 0A v e r a g e h e ig h t

5

10152025303540

0

5

1 0

1 5

D o m in a n t h

 

5

10152025303540

0

5

1 0

1 5

M ean 

B . T r a n s e c t p lo

Coefficient of variation (%)

5

10152025303540

0

1 0

2 0

3 0

4 0

5 0 B a s a l a r e a

5

10152025303540

0

1 0

2 0

3 0

4 0

5 0 V o lu m e

5

10152025303540

0

1 0

2 0

3 0

4 0

5 0 S ta n d L A

5

10152025303540

0

2 0

4 0

6 0

8 0 D en

 

5

10152025303540

0

1 0

2 0

3 0A v e ra g e D B H

 

5

10152025303540

0

1 0

2 0

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5

10152025303540

0

5

1 0

1 5

D o m in a n t 

5

10152025303540

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5

1 0

1 5

M ean 

C . V a r ia b le - r a

A v e ra g e n u m b 

S p a t i a l p a t t e r n : u n i f o 
GENERAL TECHNICAL REPORT PSW-GTR-238 

494

The marginal benefit - in terms of precision - of sampling additional trees (by 

increasing plot size) decreased with increasing number of trees sampled (fig. 2, 3). 

This result implied that smaller plots or higher BAF should be favored in terms of 

statistical efficiency. In practice, BAF are typically selected to capture around 5 to 12 

trees per plot (Avery and Burkhart 1994). However, simulation results indicated that 

below a threshold of approximately 10 redwood trees per plot, sample variance and 

confidence intervals for the sample mean could increase dramatically. The effect of 

spatial pattern on precision of some sample estimates was greater in smaller plots 

(fig. 3). The CV models (table 3) can be used to define approximate minimum 

sample size for various forest inventory strategies. For example, a fixed-radius plot 

size capturing an average of 20 trees in a clumped stand is predicted to generate BA 

estimates with a coefficient of variation of 36.8 percent, therefore the number of plots 

needed to obtain an estimate within ±5 percent of the population value at the 0.80 

probability level (t0.2,∞ = 1.282) is approximately n = ((1.282*36.8)/5)2 ≈ 89 (Avery 

and Burkhart 1994). Alternatively, the number of variable-radius plots (that also 

capture an average of 20 trees per plot) needed to obtain BA estimates with same 

level of precision and confidence is approximately 28 (based on predicted CV of 20.7 
Influence of Tree Spatial Pattern and Sample Plot Type and Size on Inventory Estimates for Leaf 

Area Index, Stocking, and Tree Size Parameters

495

percent). However, around 250 such variable-radius plots would be needed in the 

clumped stand to obtain density estimates within ±5 percent of the population value 

at the 0.80 probability level; density estimates from 28 variable-radius plots capturing 

an average of 20 trees per plot were predicted to be within ±15 percent of the 

population value at the 0.80 probability level. These examples illustrate the 

sensitivity of sample precision to changes in plot type and between stand parameters. 

The general trend in all plot types was of decreasing precision as spatial pattern 

changed from uniform to random to clumped (fig. 3). These findings are consistent 

with results presented by Lessard et al. (2002) showing that the expected variance of 

estimates from a Poisson-distributed random spatial pattern will always be less than 

estimates from a negative binomial-distributed approximation of a clumped pattern of 

tree locations. However, our results indicated that the effect of spatial pattern differed

markedly between some stand parameters and its effects can interact with plot type. 

For example, spatial pattern most affected precision of redwood density estimates 

from variable-radius plots and precision of average dbh and height estimates in all 

plot types. Precision of BA, volume, and LAI in variable-radius plots capturing >15 

trees was least affected by spatial pattern. Variable-radius plots generally made more 

precise estimates of ‘total’ stand parameters such as BA, volume and LAI where 

larger trees make a greater contribution towards the estimate. Average dbh and height 

estimate precision was poorest in variable-radius plots, except in smaller plots within 

the clumped stand where fixed-area plots performed poorly. Variable-radius plots 

consistently produced the least precise estimates of density for a given sample size. 

This problem was most pronounced in the stands with random or clumped spatial 

patterns (fig. 3). Hebert et al. (1988) and Schreuder et al. (1987) also found variableradius plots to make marginally more precise estimates of BA, but less precise 

estimates of density when compared with fixed-radius plots. Schreuder et al. (1987) 

found fixed-area sampling most efficient for stand density and number of small trees, 

and variable-radius sampling best for density in larger dbh classes. In differentiated 

stands or multiaged stands with numerous small trees and fewer large trees, fixedarea plots or transects can capture more small trees and fewer large trees than are 

needed. This problem can be mitigated by installing a series of concentric plots each 

sampling a different size class or stand component i.e., cohort or canopy layer (Spurr 

1952), by implementing a multistage design (Thompson 2002), or by using variableradius plots. 

The accuracy and precision of estimates can be affected by sampling and nonsampling error. Sampling errors arise because only part of the population of interest 

was sampled. They tend to decrease with increasing sample size, and can only be 

avoided by complete enumeration (Avery and Burkhart 1994). Non-sampling errors 

include measurement errors and incorrect sample plot establishment. These errors 

tend to have a greater impact in smaller plots, and persist with increasing sample size 

(Thompson 2002). Belt transects have a greater proportion of edge, and therefore a 

greater probability of sampling bias from incorrect plot establishment when 

‘borderline’ trees are present (Bormann 1953). Variable-radius plots are susceptible 

to systematic errors caused by incorrect calibration, hidden or leaning trees, and 

errors in slope correction (Avery and Burkhart 1994). Another potential nonsampling error is bias introduced by inappropriate volume tables or allometric 

equations (Chave et al. 2004). Our analysis ignores the uncertainty and propagation 

of errors associated with predictions of redwood tree volume and leaf area and 

therefore underestimates the uncertainty around these estimates. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

496

Sampling simulations were conducted using data collected in 85 to 100 year old 

redwood stands where density and tree size variability remained high despite many 

decades of competition. The range of spatial patterns and tree sizes should encompass 

conditions found in many size-differentiated natural stands of redwood. Stand 

attributes have been quantified using detailed stand summary data (table 1) and 

Ripley’s K analysis (fig. 1), giving three-dimensional characterizations of sample 

stand structure. Application of results in stands with different densities or tree sizes is 

facilitated because we reported coefficient of variation and confidence intervals in 

percentage terms, and average number of trees per plot instead of plot size. Narrower 

confidence intervals around sample estimates can be expected in stands with greater 

uniformity of tree size or spatial pattern, such as younger stands and plantations. 

Conclusion

Redwood forest managers and researchers interested in precise density estimates 

(e.g., to design and evaluate silvicultural treatments, monitor changes during stand 

development, or for spacing experiments), should favor fixed-area plots over 

variable-radius plots in stands with random or clumped tree spacing. Variable-radius 

plots were advantageous when sampling BA, volume, and LAI. Choice of plot type 

hardly affected precision of dominant and mean top height estimates, except in the 

clumped stand where estimates from variable-radius plots were more precise. In 

general, larger plots will be needed to achieve a desired level of precision when 

sampling stands with a higher degree of clumping. Larger plots are less likely to 

underestimate dominant height or top height. Top height was less affected by 

thinning and is recommended over dominant height in managed stands. Sampling in 

redwood forests should be preceded by careful definition of objectives and 

consideration of stand structure and spatial pattern before making decisions about 

plot type and sample size. 

References

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observations: implications for ecological and remote sensing studies. Global Ecology 

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499

Management Practices Related to the 

Restoration of Old Forest Characteristics in 

Coast Redwood Forests

Gregory A. Giusti1 

Abstract

A standardized, interactive, interview process was used with practicing Registered 

Professional Foresters asking a suite of questions to ascertain their management approaches to 

coast redwood (Sequoia sempervirens [D. Don] Endl.) stands that could best be transferred to 

other projects and lands interested in recruiting older forest characteristics. The assimilated 

results provided management insights that provide comparisons of similarities and vagrancies 

between properties, management styles and approaches. The survey included the properties 

and practitioners along the north-south geographic axis of coast redwoods to account for the 

diversity and range of physical and edaphic heterogeneity that is expressed within the forest 

type. 

Forest managers generally agreed that uneven-age management provided the basis from 

which to begin the discussion further recognizing that a fully stocked stand was equally 

important and may require a “transitional” period depending on the initial condition of the 

stand in question. Furthermore, it was generally recognized that a positive financial return for 

the forestland owner was vital in order to secure their support throughout the period of 

restoration while advancing the stands to incorporate and retain larger size class cohorts and 

other structural elements associated with older forests. 

In all cases the desire to increase the distribution of tree sizes classes (the inverse “J” curve) 

while simultaneously retaining existing conditions peculiar to older forests (i.e. tree trunk 

hollows, broken tops, reiterative branches, and others), affords the forest manager the ability 

to set the stand on a particular management pathway while affording the flexibility to adjust 

management decisions over time and capture market opportunities. Existing, archived datasets 

of unaltered old growth stands are used for comparisons in order to assist those interested in 

recreating old forest conditions. 

Key words: Sequoia sempervirens, coast redwood, restoration, old forest characteristics, management 

practices

Introduction 

The management for old forest characteristics in coastal redwood forests is a 

topic of interest among conservation interests and policy leaders in California. 

Unfortunately, a limited knowledge base regarding the structure and composition of 

older forests is available to land managers to assist them in making management 

decisions to achieve a specified future desired condition. Much of the scientific 

inquiry investigating the characteristics of redwood forests is relatively new and 

promises to provide useful and enlightening information in the years to come (Giusti 

2004, Sillet and Van Pelt 2000). 

 

1 UC Cooperative Extension, 883 Lakeport Boulevard, Lakeport, CA 95453. (gagiusti@ucdavis.edu).
GENERAL TECHNICAL REPORT PSW-GTR-238 

500

Historic and contemporary forestry practices have simplified the structural 

components of coast redwood forests (O’Dell 1996). Recruiting the structural 

elements commonly found in older forests is recognized as an important management 

objective in younger forest stands to address issues of biological diversity and forest 

integrity (Mladenoff 1993, Spies 2002). Simply stated, older forest characteristics are 

a function of time and chaotic events such as storms, wind, fire, and landslides whose

legacies shape forest structure and composition and which may be difficult to mimic 

through traditional management practices. Interest in recruiting old forest 

characteristics is not limited to the redwood region and has been document for other 

forest regions (National Research Council 2000). As land ownership patterns and 

objectives continue to shift away from corporate ownership it is generally expected 

that this interest will continue to grow and find application in other forest types 

throughout the West. 

Redwood characteristics through its range

The coast redwood forest, being dispersed along a north-south axis, has 

characteristics affected by geographic location and localized climate and edaphic 

conditions (Sawyer et al. 2000). Any comparison between redwood stands from 

differing geographic locations should be viewed as reference points for guidance 

purposes. Furthermore, numerical comparison between stands should recognize that 

differences exist in structural attributes between trees growing on upland sites vs. 

trees growing on alluvial flats and that comparisons should be limited to similar site 

characteristics. As illustrated in table 1 stands growing on alluvial deposits generally 

have higher tree densities then those stands on adjacent upland sites. This illustrates 

the need to recognize that no one description will define or articulate the structural 

elements of any particular site and any reference data should be used conservatively 

in management discussions. 

Table 1—Stand density comparison between old growth coastal redwood stands from 

different geographic locations with differing climatic and edaphic conditions (Giusti 2004).

Stand Age Old Growth Old Growth Old Growth Old Growth

Location Redwood Creek Little Lost Man 

Creek Bull Creek

Montgomery 

Woods State 

Reserve

County Humboldt Humboldt Humboldt Mendocino

Tree Size TPA TPA TPA TPA

> 24” dbh No data 20 40 16

> 32” dbh No data 15.7 40 ------

> 40” dbh 11.3 12 35 15

Redwood forest characteristics vary greatly throughout the range. In general, the 

presence of hardwoods increases with distance from the coast. Zinke (1988) 

demonstrated how moisture gradients affect species associates from Sitka spruce-
Management Practices Related to the Restoration of Old Forest Characteristics in Coast Redwood 

Forests

501

grand fir-hemlock in moist areas, redwood mixed with other conifers, redwood mixed 

with hardwoods, to Douglas-fir- hardwoods, to grassland-oak woodlands in the driest 

locations. The northern limit of the redwood forest is determined by winter 

conditions, particularly from frost damage to young trees (Baker 1965). 

Generally older forests in the northern part of the range are the largest, most 

continuous due to the higher amounts of winter rainfall and summer fog which help 

to moderate the effect of the rainless summers (Veirs 1996). As the sites become 

hotter and drier and elevation increases, a more favorable environment is created for 

Douglas-fir, and it can be found sharing the upper canopy with redwoods. 

Dagley and O’Hara (2003) report that near its southern extent redwood can be 

found 5 to 19 km inland with Douglas-fir, tanoak, and madrone (Zinke 1988). 

Moving inland it can be found in isolated patches up to 32 km from the coast while 

further south redwood is found only in very moist canyon bottoms, such as along the 

Big Sur River. Both Baker (1965) and Zinke (1988) have written that the limit to the 

southern range seems to be restrained by soil moisture. However, high summer 

temperatures may also help determine redwood’s southern boundary (Barbour et al. 

2001). 

There does exist some limited descriptive fieldwork for non-tree attributes of 

older redwood forests. Sholars (in Sawyer 2000) has cataloged 47 species of lichens 

as part of the Bryophytic component for an old growth forest. Similarly, Largent (in 

Sawyer 2000) has identified over 323 species of fungi associated with old growth 

redwoods. Others (Thornberg, personal communication) have taken their leads and 

are now pursuing field studies to determine the opportunities to inoculate previously 

logged stands that are missing these non-vascular botanical components as a means 

of recruiting missing botanical elements to mimic older forest stands. 

Structural characteristics of older forests in the northern 

tier of the redwood range

Baseline conditions for coast redwoods are found in limited quantities. In 1969 

the U.S. Department of Interior initiated a project to identify and purchase what is 

now known as Redwood National Park in the northwestern corner of California. As a 

result, stand structure data was collected in old growth redwood stands proposed for 

acquisition (Hammon, Jensen & Wallen, 1969 a, b, c, d). The synthesized 

information from the surveyed sites provides an opportunity to compare size class 

distributions in un-logged forests (fig. 1) and represents one of the few existing data 

sets for unaltered stands. 

The resultant data from the approximately 9,000 aggregated acres cruised 

demonstrates a relatively similar size class distribution over the surveyed area. Given 

the acreages of the cruised parcels, one can surmise that both upland and riparian 

sites were sampled. The average tree density of the three ownerships was 32 trees per 

ac, with tree sizes below 50 in dbh dominating. In each case, trees >50 in dbh were 

common and averaged >2 trees/ac. Similarly, each property averaged approximately 

one tree >90 in dbh per ac.
GENERAL TECHNICAL REPORT PSW-GTR-238 

502

Figure 1—Size class distribution of old growth redwood trees; ARCO, Simpson 

and Rellim timber companies. Del Norte County. 9,378 acres. ≈ 32 trees/acre. 

Source: HJW 1969 a, b, c, d.

Though each property shared similar traits when comparing size class 

distribution, they had strikingly different conifer composition. Of the properties 

surveyed by HJW in 1969 the Rellim property had the least percent by volume of 

redwood and the highest percent by volume of Douglas-fir (fig. 2). 

Figure 2—Relative percent by volume of tree species on ARCO, Simpson, GeorgiaPacific and Rellim Redwood Companies. Source: HJW 1969 a, b, c, d. 

70

27

1 1 1 2

0

10

20

30

40

50

60

70

80

90

100

ARCO

Simpson

GP

Rellim
Management Practices Related to the Restoration of Old Forest Characteristics in Coast Redwood 

Forests

503

Combined, these data demonstrate the need to recognize that not all redwood 

stands within the range are created equal. Understanding the location along the northsouth axis in addition to proximity to the coast with its influences is an important 

consideration when attempting to identify redwood associates and approximate 

species composition ratios. 

Methods 

Objective 

This project was designed to “identify and articulate the applied knowledge that 

exists from practitioners who have experience with silvicultural operations that might 

affect forest restoration efforts.” This was accomplished by identifying 

knowledgeable individuals widely recognized by their peers and others who have 

been part of an on-going discussion regarding recruitment of old forest characteristics 

or who have successfully or are attempting to retain or recruit old forest 

characteristics into their managed stands. Those interviewed represented managers of 

non-industrial, industrial and public lands. 

Survey design 

The project conducted range-wide surveys of managers with various 

management experiences in order to capture and synthesize their collective 

experiences at restoring old-forest characteristics in coast redwoods. The preliminary 

management survey review included identification of public and private landowners 

and land managers either (a) managing ancient coast redwood forests, or (b) 

conducting silviculture directed towards restoration of old-forest (or at least older)

characteristics in coast redwood forests.

The survey was predicated on four main premise “themes” that were designed to 

serve as the basis for a number of questions asked to each practitioner. The thematic 

premises where used to help focus the scope of the questions and responses to better 

compare and identify “key findings” – similarities in approaches. 

Results

Results of the survey are presented by premise. Each of the four premises is 

stated, followed by questions and key findings for each premise.

Premise 1 

Statement: Silviculture is widely viewed as the management option that holds 

the greatest potential to accelerate and restore old forest characteristics. The 

following questions are intended to identify those practices that best accomplish this 

objective. 

Question 1a 

Do you have an existing stand of older trees? How are you managing that stand 

to maintain old forest characteristics? Do you manage older stands of trees differently 

than any other?
GENERAL TECHNICAL REPORT PSW-GTR-238 

504

Key findings

In every case where older trees still exist they are identified by the 

owner/manager as an important component of the ownership that has High 

Conservation Values “HCV”. In all cases, the owner/manager recognizes the older

trees as “old growth” delineated as either whole stands or residual trees left from past 

harvest activities. In every case, stands that have not yet been harvested will not be 

entered and are being preserved. Where partial harvesting has occurred and residual 

trees remain, future harvest activities will focus on the trees within the matrix 

surrounding the residual old trees. In specific instances (MRC, SDSF, JDSF) policy 

language has been developed that 1) articulates the qualitative description of the 

stands/trees to be protected, 2) identifies the stands of old trees to be reserved, and 3) 

describes the management options available for the conservation of their values. 

Question 1b 

What are your management goals, monitoring techniques etc. toward redwood 

regeneration? 

Key findings 

In every case, the properties visited are being managed for the long-term 

production of timber and sawlogs. Hence, regeneration is a key component of the 

property’s management objectives. Shared management objectives regarding 

regeneration included:

1) Stump sprouting is promoted since it is a unique attribute of coastal redwood 

and it avoids genetic contamination of the stand. 

2) Harvest activities focus on the dominant and co-dominant trees within a 

sprout clump retaining the smaller size cohorts for future harvests. Thus 

retaining the genetic architecture of the redwood component of the stand. 

Harvest trees within clumps are selected on the basis of achieving both 

spacing and regeneration criteria. 

3) Timber volume data are collected and monitored using conventional field 

plots in combination with growth and yield models. Standing timber volumes 

and recruitment estimates across all size and age classes are commonly 

collected to ensure that regeneration and future harvest objectives will be 

assured. 

Question 1c

What are the most commonly applied silvicultural treatments on the properties 

you manage?

Key findings 

1) Commercial thinning of redwood is the most widely applied silvicultural 

practice. In all cases, the RFP is selecting trees “from below” selecting codominant trees while retaining dominant individuals. This prescription 

concurrently achieves spacing, growth and volume objectives while 

maintaining contiguous canopy cover (fig. 3). Figure 3 illustrates the concept 

of harvesting while continually increasing volume over time and space. The 
Management Practices Related to the Restoration of Old Forest Characteristics in Coast Redwood 

Forests

505

incremental volume is achieved through selection of large tree retention as 

well as recruitment of younger cohorts. 

2) To a lesser degree single-tree selection was the second most applied 

silvicultural practice. This selection approach was utilized to achieve specific 

site or ownership objectives regarding growth or volume. 

Figure 3—Humboldt Co. commercial thinning 1982- 2000. Site II. 70 acres. 

Birth of Stand 1915-1925. First commercial thin 1976. (Source: Able 

Forestry). 

Question 1d 

What is your philosophy regarding early spacing treatments (pre-commercial 

thinning) and when is it best applied (if ever)? 

Key findings 

Pre-commercial thinning (PCT) is virtually ignored as a management approach 

on most of the sites visited. Those individuals who practice PCT consider the 

optimum stand age to achieve desirable stand characteristics to be between 8 and 18 

years (JDSF & MRC). This is based on their field experience for optimal release of 

remaining redwoods. 

Question1e 

What is your philosophy about the relationship between commercial (midrotation) thinning and redwood regeneration? When is it best applied? 

Key findings 

Commercial thinning is the most widely utilized silvicultural practice of the sites 

visited. In all cases, the approach is similar. The RPF chooses the harvest trees after 

assessing dominant and co-dominant trees. Generally, dominant trees are retained in 

the stand to increase stand volume through release. Volume is increased from both 

increased diameter and height. Additionally, commercial thinning initiate’s gap phase 

0

500

1000

1500

2000

2500

3000

3500

Inventory (mbf)

year

Beginning

Ending

Ann. Cut
GENERAL TECHNICAL REPORT PSW-GTR-238 

506

successional processes allowing for natural recruitment of future crop trees from 

stump sprouting. 

The amount of wood volume harvested during each entry is dependent on the 

forester and the site. In some cases, RPF’s concentrate on removing 30 percent of the 

volume per entry, while other RPFs remove 1/3 of the trees. Figure 4 demonstrates 

the intent of this silvicultural approach. Here the “inverse J” curve is adjusted to 

move trees to the right of the “x” axis (harvestable trees) while addressing 

recruitment concerns along the “y” axis. 

Figure 4—Desired outcome over time from commercial thinning. Source: 

Blencowe Forestry.

Question 1f 

What experiences relative to recruiting old forest characteristics can you share 

regarding those treatments?

Key findings 

1) By design or happenstance the use of mid-rotation selection cutting has 

resulted in the gradual increase in both average tree girth and height while 

maintaining dense forest canopy. 

2) Mid-rotation thinning further allows the forester to identify and retain 

distinctive habitat elements that are present in the stand prior to harvest.

3) Furthermore, selection cutting allows for development of multiple age stands 

that address both old forest characteristic retention and future crop tree 

recruitment. 

4) When recruitment goals are not being met, mid-rotation thinning allows the 

RPF to select appropriate sites for group selection harvest units. This 

combination of silvicultural treatments allows for increased regeneration 

while minimizing canopy disturbance and retaining old forest characteristics 

in the remainder of the stand. 

Question 1g

Does your approach to regeneration require active vegetation control for 

undesirable species?

0

5

10

15

20

25

30

12 14 16 18 20 22 24 26 28 30 32 34 36

# trees

dbh

preharvest

postharvest
Management Practices Related to the Restoration of Old Forest Characteristics in Coast Redwood 

Forests

507

Key findings 

The majority of interviewees have no need to consider vegetation management 

scenarios in established stands. They are achieving control of unwanted plant species 

either through the use of shade and/or the direct impacts of logging which are 

targeting the removal of undesirable species. 

Question 1h 

Is pruning a viable option for improving tree vigor, stand characteristics, and 

economic returns?

Key findings 

Pruning is not generally being applied at the sites visited to improve tree vigor.

The consensus by those interviewed is that pruning is an activity to promote “clean 

log production” and the cost of pruning is not justified under the silvicultural 

methods being used. Furthermore, few saw the utility of pruning in recruiting older 

forest characteristics. 

Question 1i

What has experience taught you about the type of un-even age prescriptions that 

may have the greatest potential to provide information useful in old forest 

restoration? 

Key findings 

This question represents the primary purpose for undertaking this project. The 

guidance provided by the interviewees can inform future management decisions with 

regard to stand manipulations intended to achieve old forest characteristics. Key 

points are: 

1) Un-even age prescriptions allow the forester to identify and retain old forest 

characteristics already present in the stand while designing a system to 

ensure adequate stand regeneration to meet financial objectives. 

2) Managers are exploring and evaluating the harvest of all stems within a 

stump sprout to achieve both volume and regeneration objectives while 

creating canopy gaps.

3) Stump sprout harvesting most likely mimic the natural disturbance pattern 

for individual tree replacement in coast redwood. 

4) Silvicultural prescriptions should be viewed as a mechanism that achieves 

both volume production and initiates a stand response to set the path of 

growth and development into the future. 

5) Un-even age management does not commit the entire stand to a 

predetermined path of growth and habitat development. It allows the forester 

to make adjustments at any point in the development of the stand. 

6) Through the use of uneven-age management the forester is able to maintain 

continuous forest canopy thereby positively affecting ambient conditions in 

the stand i.e. shade, humidly, temperature, forest floor cover, mid-level 

canopy characteristics. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

508

Premise 2 

Statement: Natural disturbances are widely viewed as playing a key role in 

defining old forest characteristics. Many of those features include peculiar traits 

exploited by various species of terrestrial wildlife and flora. 

Question 2a 

What specific habitat elements do you view as being uniquely characteristic to 

coastal redwood forests? 

Key findings 

The respondents each identified several habitat characteristics of coastal redwood 

that they are mindful of during their management decisions. These generally can be 

categorized into biotic and abiotic characteristics. 

Biotic Elements Abiotic Elements

Trunk hollows (goose pens) the result of 

multiple burns. Not unique to coast 

redwood but difficult to recruit under 

current fire suppression regimes. 

Soil types, depth, slope and aspect of 

management unit and how these 

conditions affect species composition and 

tree growth.

Broken tops, deformed trunks, large 

woody debris caused by lighting, wind, 

disease and pests (in hardwoods) etc.

Rock outcroppings and shallow soils in 

the middle and southern portions of the 

range. Steep slopes and numerous 1st order 

streams common throughout the region. 

Reiterative branching unique of older 

trees and difficult to recruit using modern 

silvicultural time frames. 

Influences of past fire events (natural and 

induced) on stand composition and 

structure. 

Multiple layered canopy with redwood 

and Douglas-fir being dominant. 

Ability to sprout, a unique characteristic 

for a North American conifer. 

Longevity, compared to other species 

found in the redwood region. 

Question 2b

What specific management practices (if any) have you applied or come to 

recognize that best create specific wildlife habitat feature(s)?

Key findings 

1) Timber harvesting allows for the creation of canopy gaps of any desired size 

and shape. This freedom allows for canopy management using timber harvest 

to achieve regeneration goals as well as meeting wildlife management 

objectives. 

2) White woods are most likely to provide the greatest opportunity for rapid 

nest cavity recruitment. Recognizing the role of white woods, in addition to 

hardwoods, for habitat element maintenance and recruitment can assist a 

manager achieve desired wildlife habitat goals. 

3) Timber harvesting provides for a source of down and dead wood of any 

desired size and soundness. 
Management Practices Related to the Restoration of Old Forest Characteristics in Coast Redwood 

Forests

509

Question 2c

From your experiences, are there any habitat elements that are easily recruited 

through silvicultural practices?

Key findings 

A number of habitat elements are widely recognized as being relatively easy to 

recruit. These elements include: 

1) Dead and down wood; 

2) Large trees can easily be retained; 

3) White woods are easily regenerated and retained; 

4) Timber harvesting creates soil disturbance which aids in the germination of 

many botanical species; 

5) Slash and litter are easily recruited which provides for nutrient cycling and 

erosion prevention in addition to cover for small mammals and herps. 

Question 2d 

From your experiences, are there any particular habitat elements that are 

particularly difficult to recruit through silvicultural practices?

Key findings 

1) All respondents recognize the difficulty in recruiting trunk hollows (goose 

pens) associated with repetitive fire scarring. Subsequently, they further 

acknowledged the importance of trunk hollows as a habitat element and 

expressed a desire to see applied research projects designed to address this 

question. 

2) Each of the interviewees recognized the difficulty in recruiting and 

maintaining phenotypically inferior trees in the stand. This paradigm is 

entrenched namely that retaining any inferior tree will be viewed as “highgrading”. Though an important consideration, overly aggressive sanitation 

policies can inhibit the recruitment of habitat elements often associated with 

less thrifty trees. 

3) The other most notable characteristic not readily recruited through 

management are those elements directly associated with age i.e. reiterative 

branches, bryophyte colonization, and rotten logs. Most recognize the 

importance of allowing these conditions to develop over time. 

Premise 3 

Statement: Some natural disturbance patterns may not be easily mimicked by 

silvicultural practices i.e. fire, landslides. (These questions were designed to explore 

the practitioner’s management approaches in light of the fact that some variables may 

be out of their control.) 

Question 3a

In this time of aggressive fire suppression, how do you manage forest fuels? Can 

silviculture affect fuel loads? If so, how? 
GENERAL TECHNICAL REPORT PSW-GTR-238 

510

Key findings

There is strong agreement that silviculture should not be viewed as a surrogate 

practice that can always be substituted for fire. It is further recognized that fire serves 

as a catalyst in many forest processes such as nutrient cycling and the formation of 

key habitat elements as well as potentially depletion of forest nutrients and 

downstream eutrophication. However, there was strong consensus among those 

interviewed that silvicultural practices can be used to mitigate fuel loading in the 

absence of fire. Specifically, silviculture and timber harvest activities are often aimed 

at reducing wildland fire fuels: 

1) Lopping of slash is a common practice among RPFs working in areas where 

aesthetics and fuel suppression are equally important. 

2) Tractor crush. As the name implies, the machinery used in timber harvest is 

used specifically to reduce the height of slash and other residual vegetative 

materials generated by harvesting. 

3) Harvest activities that reduce ladder fuels are widely viewed as a positive 

activity associated with active silvicultural manipulations. 

4) Windthrow. All of those interviewed recognize the positive relationship 

between silviculture and tree spacing as a means of inhibiting the spread of 

fire into the crowns. Additionally, several individuals further recognize the 

importance of incorporating naturally occurring fuel breaks into their 

silvicultural designs. Windthrow and other naturally occurring breaks in the 

vegetation across the landscape are generally viewed as opportunities that 

should be incorporated into management designs to maximize their 

effectiveness to limit the spread and impact of wildland fires. 

Question 3b

How do you discourage the recruitment of less desirable tree species using 

silvicultural practices in absence of other natural disturbance regimes? 

Key findings

Respondents viewed this question more broadly to include all less desirable 

species, not just trees. 

1) Canopy management to maintain shade. Since all of the participants for this

project are utilizing un-even aged management they acknowledged the 

relationship between canopy management and the role of shade on the forest 

floor to inhibit the recruitment of some less desirable species into the forest 

canopy i.e. tanoak (Notholithocarpus (Lithocarpus) densiflorus). Subsequently, 

respondents further acknowledged that maintaining high shade component 

creates a greater chance of recruiting other less desirable species that are more 

shade tolerant i.e., grand fir (Abies grandis).

2) Species management using market conditions. Where applicable, particularly 

in the management of less desired conifers, positive market conditions often 

provide an opportunity to mark a stand to reduce the number of undesired trees 

and thus reduce potential seed sources for future recruitment. 

3) Neighbor awareness program. The Arcata Community Forest has initiated a 

neighbor awareness program aimed at increasing public consciousness to 

reduce the planting and introduction of exotic and noxious plant species on 
Management Practices Related to the Restoration of Old Forest Characteristics in Coast Redwood 

Forests

511

properties adjacent to the forest. By involving broader community 

participation, the managers of the forest hope they have been effective in 

slowing the recruitment of many less desirable species from the surrounding 

urbanized area. 

Question 3c

Is fire a useful tool? Is it realistic to assume that fire can be used effectively?

Key findings 

Yes. Fire was unanimously viewed as a useful tool. Cited as the “missing piece” 

in modern forestry practices, fire is seen as a key element in shaping the structure and 

composition of coastal redwood forests by all of the respondents. There was further 

consensus that serendipitous fire occurrences i.e. lightning strikes, are generally 

viewed favorably if conditions allow for low-intensity burns. 

Premise 4 

Statement: There may be differences in social preferences vs. scientific data for 

desirable characteristics of old forests. It is important to identify obstacles that exist 

that serve as an impediment to improving active management practices aimed at 

maintaining or recruiting old forest characteristics in redwood stands. 

Question 4a

Are there treatments or other considerations that we have not discussed that may 

be important in recruiting old forest characteristics and function while meeting 

landowner expectations? 

Key findings

Several pragmatic factors were identified by the respondents that regularly affect 

how the best intentions of an RPF can be negatively influenced. They include: 

1) Logging contractor decisions. 

2) Cable yarding considerations. 

3) Harvesting techniques and landowner expectations. 

4) Roads, landings and yarding corridors. 

5) Mill Infrastructure and availability 

6) Disincentive to produce large logs. 

7) Newly introduced pests and pathogens (SOD). 

Question 4b

Have you identified/delineated areas with High Conservation Values or other old 

forest characteristics? Have you articulated your management treatments in these 

areas in a management plan or some other document?

Key findings

In every case, interviewees have identified areas or elements of High 

Conservation Value (HCV). Generally, the larger ownerships/parcels tended to have 

their HCV areas/elements delineated in landscape plans, while smaller, non-industrial 

ownerships used the NTMP as the vehicle to identify HCV components. The most 

commonly identified and/or delineated HCV areas or elements included: 
GENERAL TECHNICAL REPORT PSW-GTR-238 

512

• Old growth trees & stands. 

• Riparian areas. 

• Wet areas. 

• Threatened and endangered (T&E) species sites. 

• Special project areas i.e. arbon sequestration sites. 

• Scenic corridors. 

Discussion

Little is known about how old redwood forests developed over time. 

Information on the development of redwood stands is important for determining 

if second-growth forests can develop old forest characteristics. The results of the 

survey suggest that periodic entries into a stand can place the stand on a pathway 

toward achieving some of the aspects of an older forest. This is supported by Hunter

and Parker (1993) who wrote old forests experience intervals of repeated smallscale disturbance events rather than a single disturbance event. They were able to 

illustrate the episodic nature of gap formation, the links between canopy tree 

biology and gap properties, and the relationship between topography and 

disturbance regime. They found half of the 80 canopy gaps in an old redwood 

forest to have resulted from more than one disturbance event. It appears that for 

redwood forests, the gaps created by small-scale disturbances contribute to the 

overall structural complexity of the forest, but do not affect the long-term 

composition of the overstory layer (i.e., redwood remains the dominant overstory 

species) (Sugihara 1996). 

Fire is considered a primary factor in shaping the structure and composition of 

old growth forests. The exclusion of fire is viewed by all interviewed as a principle 

constraint in our ability to recruit certain components found in older forests. 

Older forests are more complex than metrics that are limited to tree size, basal 

area and volume growth can accurately describe. Subtleties such as bark 

configurations, limb and branch configurations, epiphytic plant communities, trunk 

hollows (both conifers and hardwoods), persistent, large down woody materials 

(redwoods), mid and sub-canopy plant communities, and soil deposition and 

recruitment create a synergy that is very difficult to mimic in time frames 

comfortable for human acceptance. The best we can hope to accomplish is to retain 

and recruit (when possible) any of the remaining older forest characteristics lost 

during the period of intense timber harvesting of the 19th and 20th century under the 

constraints of the 21st century regulations.

The properties visited are not uniquely challenged when trying to address 

restorative actions similar to many other projects on the north coast who are 

concurrently wrestling with the condition of their lands. Collectively the lands and 

the practitioners surveyed believe that restoration and economic return on 

investments is a positive approach to addressing environmental and ecological issues 

associated with recruitment of old forest characteristics over time. 
Management Practices Related to the Restoration of Old Forest Characteristics in Coast Redwood 

Forests

513

References

Baker, H.G. 1965. Ecology of the redwoods: inter-relationship of redwood and its 

environment. University of California Extension Series on Redwood. Berkeley, CA: 

University of California, Berkeley. 12 p.

Barbour, M.; Lydon, S.; Borchert, M.; Popper, M.; Whitworth, V.; Evarts, J. 2001. Coast 

redwood: a natural and cultural history. First edition. Los Olivos, CA: Cachuma 

Press. 

Dagley, C.M.; O’Hara, K.L. 2003. Potential for old forest restoration and development of 

restoration tools in coast redwood: a literature review and synthesis. A report to 

Save the Redwood League. 79 p. 

Giusti, G.A. 2004. Management practices related to the restoration of old forest 

characteristics in coast redwood forests. A report to Save the Redwood League. 31 p.

Hammon, Jensen, & Wallen. 1969a. Timber inventory report. Proposed Rellim Redwood 

Company allocation of the northern purchase unit lands. Del Norte County. A 

report to the U.S. Department of Interior, Nov. 1, 1969. Humboldt State Univ. Humboldt 

Room, Ref. Library. Arcata, CA. 

Hammon, Jensen, & Wallen. 1969b. Timber inventory report. Proposed Simpson Timber 

Company allocation of the northern purchase unit lands. Del Norte County. A 

report to the U.S. Department of Interior, Nov. 1, 1969. Humboldt State Univ. Humboldt 

Room, Ref. Library. Arcata, CA. 

Hammon, Jensen, & Wallen. 1969c. Timber inventory report. Proposed Arcata Redwood 

Company allocation of the northern purchase unit lands. Del Norte County. A 

report to the U.S. Department of Interior, Nov. 1, 1969. Humboldt State Univ. 

Humboldt Room, Ref. Library. Arcata, CA. 

Hammon, Jensen, & Wallen. 1969d. Timber inventory report. Proposed Georgia-Pacific 

Timber Company allocation of the northern purchase unit lands. Humboldt 

County. A report to the U.S. Department of Interior, Nov. 1, 1969. Humboldt State 

Univ. Humboldt Room, Ref. Library. Arcata, CA. 

Hunter, J.C.; Parker, V.T. 1993. The disturbance regime of an old- growth forest in 

coastal California. Journal of Vegetation Science 4(1):19-24.

Mladenoff, D.J.; White, M.A.; Pastor, J.; Crow, T.R. 1993. Comparing spatial patterns in 

unaltered old growth and disturbed forest landscapes. Ecological Applications 

3(2):294-306.

National Research Council. 2000. Environmental issues in Pacific Northwest forest 

management. Washington, DC: National Academy Press. 259 p.

O’Dell, T.E. 1996. Silviculture in the redwood region: a historical perspective. In: 

LeBlanc, J., editor. Proceedings of the conference on coast redwood forest ecology and 

management. Arcata, CA: Humboldt State University. University of California 

Cooperative Extension: 15-17. 

Sawyer, J.O.; Sillett, S.C.; Popenoe, J.H.; LaBanca, A.; Sholars, T.; Largent, D.L.; Euphrat, 

F.; Noss, N.; Van Pelt, R. 2000. Characteristics of redwood forests. In: Noss, R., 

editor. The redwood forest: history, ecology and conservation of the coast redwood. 

Washington, DC: Island Press: 39-79.

Sillett, S.C.; Van Pelt, R. 2000. A redwood tree whose crown is a forest canopy. Northwest 

Science 74(1): 34-43.

Sugihara, N.G. 1996. The dynamics of treefall gaps in alluvial flat coast redwood 

(Sequoia sempervirens (D. Don) Endl.) forests. In: LeBlanc, J., editor. Proceedings of 
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514

the conference on coast redwood forest ecology and management. Arcata, CA: 

Humboldt State University. University of California Cooperative Extension. 

Spies, T.A.; Franklin, J.F. 1996. The diversity and maintenance of old growth forest. In: 

Szaro, R.C.; Johnson, D.W., editors. Biodiversity in managed landscapes. New York: 

Oxford Press: 296-314.

Veirs, S.D. 1996. Ecology of the coast redwood. In: LeBlanc, J., editor. Proceedings of the 

conference on coast redwood forest ecology and management. Arcata, CA: Humboldt 

State University. University of California Cooperative Extension: 170-185.

Zinke, P.J. 1988. The redwood forest and associated north coast forests. In: Barbour, 

M.G.; Major, J., editors. Terrestrial vegetation of California. Expanded edition. 

Sacramento, CA: California Native Plant Society: 679-698.
515

Carbon Storage in Young Growth Coast 

Redwood Stands

Dryw A. Jones1 and Kevin L. O’Hara1

Abstract

Carbon sequestration is an emerging forest management objective within California and 

around the world. With the passage of the California’s Global Warming Solutions Act (AB32) 

our need to understand the dynamics of carbon sequestration and to accurately measure 

carbon storage is essential to insure successful implementation of carbon credit projects 

throughout the State. As the leader in forest carbon credit projects within the U.S., California's 

forest carbon protocols are being looked to as templates for successful carbon credit 

accounting. Coast redwood (Sequoia sempervirens) stands have the largest measured biomass 

per acre making the argument for use of the species in long-term carbon sequestration projects 

self evident. To date no direct measurement of both carbon fraction and wood density of coast 

redwood has been undertaken. With this study we tested the applicability of the current forest 

carbon project protocols set out by the Climate Action Reserve for forest carbon credit 

projects within California. Specifically we tested the applicability of a carbon fraction of 0.5 

and a greenwood density of 0.34 g/cm3 for coast redwood trees. Our main findings were that:

1) a species-average of 0.34 g/cm3 significantly underestimated the wood density of the 

measured trees, 2) wood density varied predictably with tree height and wood type, 3) carbon 

fraction was significantly higher than the default 0.5, and 4) carbon fraction varied predictably 

in relation to wood type. Our results indicate that a simple approach to estimating carbon 

storage utilizing a carbon fraction of 0.5 and a species-average wood density underestimates

carbon budgets in young growth redwood stands. Given the regional nature of carbon credit 

projects our results indicate that forest project protocols should be adjusted to allow for 

calculations that incorporate directly measured wood density and carbon fraction values 

within the forest carbon project area.

Key words: biomass, Sequoia sempervirens, carbon fraction, sequestration projects, wood 

density

Introduction 

Carbon sequestration is emerging as an important goal for forestry. In order to 

make informed decisions related to managing forests for carbon sequestration it is 

necessary to have precise and empirically based estimates of carbon budgets (Brown 

2002). Forest carbon budgets are typically determined by estimating the volume of a 

tree using species-specific allometric equations or genus-specific equations (Brown 

2002, Jenkins and others 2003) to convert easily measured tree characteristics such as 

diameter at breast height into wood volume. The bone-dry wood density of the 

species is then used to convert this overall volume into tree biomass. Tree biomass is 

multiplied by a carbon fraction to estimate the mass of carbon contained in that tree.

Species-specific values of carbon fraction are not widely available and therefore a 

 

1 Graduate student and Professor, respectively, Department of Environmental Science, Policy & 

Management, University of California, Berkeley, CA 94705. (dryw@berkeley.edu; 

kohara@berkeley.edu).
GENERAL TECHNICAL REPORT PSW-GTR-238 

516

generalized value of 0.50 is typically used (Brown 2002, Goodale and others 2002, 

Harmon and others 1990, Pacala and others 2001, Van Deusen and Roesch 2011). 

Using a carbon fraction of 0.50 is problematic because carbon values that have 

been directly measured range from about 0.45 to 0.55 (Lamlom and Savidge 2003). 

The associated error with using 0.50 can therefore be as high as ten percent (Lamlom 

and Savidge 2003). 

Another source of error in carbon budget estimates arises from variation in 

species specific wood density values from region to region. The default value for 

young growth redwood whole-tree basic wood density (called wood density 

hereafter) is 0.34 g/cm3

 (CAR protocol methodology - climateactionreserve.org), 

however regional estimates range from 0.32 g/cm3

 to 0.38 g/cm3 (Luxford and 

Markwardt 1932) equating to deviations from the species average of 6 and 12 percent 

respectively. 

Due to the longevity of the species and it’s propensity to accumulate high levels 

of biomass (Busing and Fujimori 2005), young growth coast redwood forests have 

the potential to become significant carbon sinks for hundreds of years. Redwood 

stand volume production has been shown to be affected by stand density and 

structure implying that there is the potential to effect stand volume productivity with 

carefully planned silvicultural treatments (Berrill and O’Hara 2009). In addition to 

the high wood volume productivity within a stand of coast redwood, the wood 

products harvested from those stands has been shown to have long lifecycles 

(Highley and others 1995) allowing for long term carbon storage in wood products. 

This study focuses on second growth coast redwood trees to pursue the following 

study objectives: 1) determine whether any differences in carbon fraction exist within 

three wood types of the tree bole at breast height; 2) determine whether any 

differences in density exist between the three wood types; 3) determine whether any 

carbon is lost due to oven drying; 4) develop methodology to precisely determine the 

carbon fraction of tree boles in young growth redwood; and 5) compare the directly 

measured values in the study area to the default values specified in standard 

methodologies (carbon fraction of 0.50 and wood density of 0.34 g/cm3

).

Methods 

Study area and description 

Tree cores were collected from coast redwood stands located at Railroad Gulch 

on Jackson Demonstration State Forest near Ft. Bragg, California. Redwood stands at 

this location regenerated naturally from stump sprouts and from seedlings planted 

after removal of the old growth stands around 1920 (Jackson 1991). Sample trees 

were randomly selected from a database created in 1982 when Railroad Gulch was 

divided into 14 contiguous blocks. A total of 42 trees were selected ranging in breast 

height age from 23 to 87, ranging in diameter from 13 to 86 cm and ranging in height 

from 5 to 45 m. 

Core extraction and processing 

Two cores were taken perpendicularly to the bole axis at a 45oangle to slope 

aspect on opposite sides of sample trees. The increment corer was cleaned between 
Carbon Storage in Young Growth Coast Redwood Stands

517

trees to avoid contamination. A subset of four trees were selected for additional core 

extractions taken from halfway between base of live crown, at live crown and 

halfway between tree top and live crown. These cores were used for analysis of 

vertical variation in wood density. Cores were then placed in straws, sealed and 

labeled. 

Ten cores for paired carbon and density analysis were cut in half lengthwise and 

divided up into three categories: 1) juvenile heartwood (first seven growth rings from 

pith); 2) mature heartwood (three growth rings away from sapwood heartwood 

boundary and showing no curvature of the growth rings); and 3) sapwood 

(determined by color). This resulted in 30 samples analyzed for density (10 of each 

wood type) with corresponding halves of segments analyzed for carbon. Ninety-six 

additional core segments were selected strictly for carbon analysis, however, these 

samples were not cut in half. 

Core segment samples were ground into a fine powder which was placed into a 

sample tube with a two-stage cap to either permit or exclude airflow. To determine if 

differences in air-drying and oven-drying affected carbon fraction the tubes and wood 

powder were first air-dried in a vacuum chamber with desiccant then analyzed for 

carbon fraction. The same sample tubes were later oven dried at 65 oC and then again 

at 105 oC and carbon analysis was repeated each time to determine any potential loss 

of carbon due to volatilization of organic compounds. 

Carbon fraction 

Carbon fraction was determined by taking a 5 mg sample of wood powder from 

each of the 126 (42 of each wood type) sample tubes for the analysis of air-dried 

samples (Cai) then another 5 mg sample was taken from the same tubes after oven 

drying for the oven-dried carbon (Cov) samples at 65 oC then again at 105 oC. Mass 

lost due to oven drying was recorded for each sample at each stage. Each sample of 

wood powder was placed into a clean dry tin container (Costech Analytical 

Technologies, Inc.) that was first zeroed on a Metler Toledo microbalance. A CE 

Instruments NC 2100 Elemental Analyzer (Rodano, Milano, Italy) was used to 

quantify total carbon of each sample on a mass per mass basis using a calibration 

curve with an r2

 >0.9999. To ensure correct carbon values the air dried carbon 

fractions were adjusted by dividing the initial Cai value by one minus the result of 

subtracting the volatile carbon fraction (Cv) from the total mass lost fraction. 

Effectively this adjusted the initial carbon values to reflect the amount of residual 

moisture left in the wood powder.

Wood density 

The volume of the samples (Vs) used to determine the density of wood was 

determined by zeroing a graduated cylinder of deionized water with a submerged 

capsule used to hold samples on an OHAUS Analytical Plus scale. The wood 

samples were then placed into the capsule and submerged into the water making sure 

to lower the capsule to the same level as it was zeroed. The reading on the OHAUS 

scale was recorded as the volume of the sample after determining the proper density 

of the water at room temperature (20 oC), which was done by treating the scale 

reading as unitless and multiplying that reading by the density of water at 20 oC 

(0.998199 g/cm3

) (Aleksandrov et al. 2004). Density samples were oven-dried at 105 

oC until a constant mass was achieved. Once the samples were stable their masses 
GENERAL TECHNICAL REPORT PSW-GTR-238 

518

(Ms) were recorded and the density determined by calculating (Ms+Cv*Ms)/Vs. This 

density value adjusts for the mass of volatile carbon lost during oven drying. 

Statistical methods 

The mean and standard error of carbon fraction for 42 samples for each of the 

three wood types were determined. Variation in carbon fraction was tested using a 

one-way analysis of variance (α = 0.01) and significance of differences between the 

means of each wood type was determined using a Tukey-Kramer t-test (α=0.01). The 

mean and standard deviation of 10 replicates for each wood type were calculated and 

a one-way analysis of variance (α = 0.05) was used to test for differences in density 

among wood types. A z-test was used to determine the significance of differences in 

the overall mean from 0.34 g/cm3

. The mean for Cai and the mean of Cov were 

compared using a paired t-test. Linear regression was used to test relationships 

between carbon fraction of each wood type and growth rate, diameter at breast 

height, height, height to live crown and length of live crown. One standard error is 

represented by values in parenthesis within the text and tables.

Results

Variation in carbon fraction between wood types 

Analysis of carbon fraction for the three wood types showed that heartwood was 

consistently higher in carbon than sapwood and that mature heartwood was higher in 

carbon than juvenile heartwood samples (table 1). Means were significantly different 

between the three wood types using a Tukey-Kramer t-test (p<0.0001) and all were 

significantly different from a mean of 0.50 (p<0.0001). 

Table 1—Carbon fractions and associated standard errors for each wood type - juvenile 

heartwood (HWj), mature heartwood (HWm) and sapwood (Sw) - for two drying methods, air 

dried and oven dried to 105 oC. Forty two samples were used for each wood type for each 

drying method.

Drying HWj HWm Sw

Oven dried 0.5179 (0.00096) 0.5235 (0.00098) 0.5047 (0.00096)

Air Dried 0.5371 (0.00107) 0.5443 (0.00104) 0.5305 (0.00105)

Linear regression of Cai on the tested variables showed a significant negative 

relationship between carbon fraction of mature heartwood and average growth rate (p 

=0.026, r2

 = 0.134)). The relationship is described by the following equation: Cai 

(HWm) = 55.051 – 1.503*AveGrowth. AveGrowth is the average growth of the 

sample in cm/growth ring. No significant relationships existed between carbon 

fraction of juvenile heartwood or sapwood and any of the variables tested. Linear 

regression of Cov on the above tree variables showed no significant relationships for 

any of the tested variables. An ANOVA on wood types and carbon fraction resulted 

in an adjusted r2

 of 0.41 for Cai and 0.64 for Cov (p<0.0001). 

Oven-dried versus air-dried methods 

A paired t-test showed significant differences (p<0.0001) in carbon fractions 

between air-dried wood powder samples and oven-dried wood powder samples (table 
Carbon Storage in Young Growth Coast Redwood Stands

519

1). Mean differences for carbon fractions between air and oven dried samples were: 

0.0192 for HWj, 0.0208 for HWm and 0.0258. The volatile fraction between air dried 

and oven dried carbon samples (to 65 oC) was not significantly different from the 

volatile carbon fraction of samples dried at 105 oC therefore the 105 oC values are 

reported for incorporation with wood density dried to the same temperature. 

Density of wood types and overall wood density 

Wood density was significantly different for sapwood found above the live 

crown (ALC) versus below live crown (BLC) but not significantly different for 

heartwood by location in tree or between juvenile and mature heartwood. The mean 

wood densities of sapwood by location in tree (ALC or BLC) were: 0.300 g/cm3

(0.017) ALC, and 0.372 g/cm3

 (0.017) BLC. The mean wood density for heartwood 

was 0.382 (0.010). The mean for heartwood and below crown sapwood were 

significantly (p=0.010, α=0.05) higher than the 0.34 g/cm3 value for bone-dry density 

of redwood. The average of sapwood density sample values resulted in a mean of 

0.351 g/cm3

 (0.014). 

Carbon density comparison 

The average values for the combination of carbon fraction and wood density 

(carbon density) are given below (table 2). Significant differences existed between 

directly measured values of carbon density and the default values for carbon density 

obtained by multiplying a wood density for redwood of 0.34 g/cm3

 by the default 

carbon fraction of 0.50 (p<0.05). Only the ALC sapwood carbon density was close to 

the resulting value (default value).

Table 2—Comparison between default and measured values for carbon densities and 

standard errors for two wood types found within the boles of young growth redwood trees 

measured above live crown (ALC) and below live crown (BLC). 

Wood 

type

Location Default value

(g C/cm3)

Measured values

(g C/cm3)

Difference

(%)

Heartwood ALC 0.17 0.2052 (0.0037) 20.70

Sapwood ALC 0.17 0.1591 (0.0061) -6.41

Heartwood BLC 0.17 0.2076 (0.0037) 22.12

Sapwood BLC 0.17 0.1973 (0.0074) 16.06

Discussion

Carbon fraction variation 

The significant variation in carbon fraction between the three wood types 

indicated that using an overall average for carbon fraction, even a species specific 

one, may lead to underestimates of the carbon fraction of young growth redwood. 

There are few studies that have directly measured carbon fraction in trees (Chow and 

Rolfe 1989, Elias and Potvin 2003, Lamlom and Savidge 2003, Lamlom and Savidge 

2006, Thomas and Malczewski 2007), potentially explaining the reliance on a general 

carbon fraction of 0.50 to convert dry biomass to carbon mass despite the inherent 

inaccuracy of utilizing such an average to predict carbon fractions of unmeasured 

species. The overall measured mean of carbon fraction in young growth redwood is 

significantly greater than the 0.50 value that is often used for trees (Brown 2002, 
GENERAL TECHNICAL REPORT PSW-GTR-238 

520

Goodale et al. 2002, Harmon et al. 1990, Pacala et al. 2001, Van Deusen and Roesch 

2011). 

The differences in wood characteristics such as density, shearing strength and 

extractive content between old-growth redwood and young growth redwood (Resch 

and Arganbright 1968), make extrapolation of the values from this study to oldgrowth redwood inadvisable. The higher extractive content in old-growth redwood 

would most likely result in higher carbon fraction of the stem compared to young 

growth as extractives can be made up of as much as 66 percent carbon (Resch and 

Arganbright 1968). Wood type explained a good deal of the variation found in the 

tree boles with an adjusted r2

 of 0.41 for Cai predicted by wood type and an adjusted 

r

2

 of 0.64 for Cov predicted by wood type. The difference in r2 between the two 

drying methods indicated volatile compounds may vary independently from 

structural carbon components such as lignin and cellulose. Though the causes of 

carbon fraction variation within tree boles are not well understood (Elias and Potvin 

2002, Lamlom and Savidge 2003), it is clear from the data that volatile organic 

compounds are a significant portion of the overall carbon fraction. 

Densities 

Differences in wood density between wood types in redwood have been reported 

(Luxford and Markwardt 1932, Resch and Arganbright, 1968) but were not detected 

with our small sample size. Significant differences in wood densities from 0.34 g/cm3

(p<0.05) imply that utilization of an average density for young growth redwood may 

not be appropriate for all regions or for all stand structures. More studies into the 

factors controlling wood density in young growth redwood are needed in order to 

create accurate wood density prediction models to aid in predicting overall carbon 

stocks. The correlation of lower wood density to position in live crown of young 

growth redwood was not unexpected. Resch and Arganbright (1968) and Sillett and 

others (2010) found similar trends in old growth redwood implying that this trend is a 

species trait. The wood densities found in the study area are close to the 0.38 g/cm3

value reported by Luxford and Markwardt (1932) for Mendocino implying that 

despite the relatively small sample size the wood density numbers found in this study 

may be representative for the region. 

Loss of carbon during oven drying 

The loss of carbon during oven drying at 65 oC and 105 oC is a significant 

finding. The methodology for carbon measurement in woody tissues commonly calls 

for oven drying (Lamlom and Savidge 2003). Studies have found that oven drying 

can lead to the loss of carbon, however, they have either used very high temperatures 

(Lamlom and Savidge 2003, Thomas and Malczewski 2007) or have not directly 

measured differences in total carbon before and after oven drying (Beakler et al.

2007). Oven drying wood at temperatures as low as 65 oC and potentially lower 

(Beakler and others 2007) can lead to the loss of carbon. This suggests that oven 

drying should not be used in determining carbon fraction. Instead utilizing vacuum 

desiccation as outlined by Lamlom and Savidge (2003) or freeze drying as outlined 

by Thomas and Malczewski (2007) would be most appropriate. Kiln dried wood is 

typically processed at temperatures near 65 oC (Beakler and others 2007) so the ovendried carbon fractions from this study is appropriate for estimating carbon budgets 

for young growth redwood lumber. The oven dried values from this study are close to 

the value of 0.512 used by Wilson et al. (2010) indicating some consistency in carbon 
Carbon Storage in Young Growth Coast Redwood Stands

521

fraction of young growth kiln dried redwood. Timber production has been proposed 

as a potential method for increasing the amount of carbon stored by a given area of 

forest land (Skog 2008), however, it is important to understand the differences 

between carbon fractions of kiln dried lumber and that of live trees for accurate 

carbon accounting. 

Improved methodology 

The methodology presented in this study resulted in more precise and accurate 

carbon fraction values then the standard methodology. Measuring both carbon 

fraction and wood density is necessary in determining accurate values for a given 

species or location as these characteristics can be highly variable across species and 

regions (Chave et al. 2009, Lamlom and Savidge 2006). Lamlom and Savidge’s 

(2003) methodology works well in a laboratory setting but the destructive nature of 

the methodology does not allow for comparison of carbon fractions over time. The 

ability to measure stand conditions over time along with carbon fraction and wood 

density, could be very helpful in explaining some of the environmental factors 

impacting those two variables. It is important that future studies into carbon fractions 

of tree species utilize either the vacuum desiccation methods suggested by Lamlom 

and Savidge (2003) or the freeze drying method described by Thomas and 

Malczewski (2007). Additionally the loss of carbon due to oven drying must be 

accounted for both in total carbon fractions and in the wood density values in order to 

ensure accurate carbon stock estimates.

Comparison of measured values to default values 

The difference between the values suggested by the CAR protocols (0.17 g 

C/cm3

) and the values measured directly in this study were as high as 22 percent of 

the default estimate (table 2). The debate over improving carbon budget estimation 

seems to focus almost entirely on improvements in volume estimation (Jenkins et al 

2003, Van Deusen and Roesch 2011). This study, however, clearly indicates the 

magnitude of the error that can be introduced into carbon budget estimates if 

variation in carbon and wood density are not addressed. The current methodology 

(CAR) to estimate forest carbon budgets in redwood calls for the use of values that 

underestimate the amount of carbon stored within redwood trees. It is likely that the 

default values for other species could result in overestimates of their respective 

carbon budgets. For example it is known that hardwoods have carbon fractions that 

are typically lower than 0.50 (Lamlom and Savidge 2003) and therefore utilizing a 

default value of 0.50 for estimates of hardwood tree carbon will systematically 

overestimate the amount of carbon contained within many hardwood species. 

Additionally there is the likelihood that tree species within some regions will have 

lower wood densities than the species average and therefore local estimates of carbon 

sequestration rates will be biased when the species average us used. To alleviate 

these potential biases it will be necessary to measure carbon fractions of tree species 

found in California and to accurately estimate the regional and stand level variations 

in wood density that are known to occur. 

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Elias, M.; Potvin, C. 2003. Assessing inter-and intra-specific variation in trunk carbon 

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Goodale, C.L.; Apps, M.J.; Birdsey, R.A.; et al. 2002. Forest carbon sinks in the Northern 

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Jackson, W.F. 1991. Big River was dammed. Mendocino, CA: FMMC Books. 165 p. 

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estimators for United States tree species. Forest Science 49(1): 12-35.

Lamlom, S.H.; Savidge, R.A. 2003. A reassessment of carbon content in wood: variation 

within and between 41 North American species. Biomass and Bioenergy 25(4): 381-

388. 

Lamlom, S.H.; Savidge, R.A. 2006. Carbon content variation in boles of mature sugar 

maple and giant sequoia. Tree Physiology 26(4): 459-68. 

Luxford, R.F.; Markwardt, L.J. 1932. The strength and related properties of redwood.

Technical Bulletin 305. Washington, DC: U.S. Department of Agriculture, Forest 

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Pacala, S.W.; Hurtt, G.C.; Baker, D.; et al. 2001. Consistent land- and atmosphere-based 

U.S. carbon sink estimates. Science 292: 2316-2320. 

Resch, H.; Arganbright, D.G. 1968. Variation of specific gravity, extractive content and 

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Sillett, S.C.; Van Pelt, R.; Koch, G.W.; et al. 2010. Increasing wood production through 

old age in tall trees. Forest Ecology and Management 259(5): 976-994. 

Skog, K.E. 2008. Sequestration of carbon in harvested wood products for the United 

States. Forest Products Journal and Index 58(6): 56-72. 

Thomas, S.C.; Malczewski, G. 2007. Wood carbon content of tree species in eastern 
Carbon Storage in Young Growth Coast Redwood Stands

523

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Van Deusen, P.; Roesch, F.A.; Sampling, I. 2011. Sampling a tree for total volume, 

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Wilson, P.L.; Funck, J.W.; Avery, R.B. 2010. Fuelwood characteristics of northwestern 

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Department of Agriculture, Forest Service. Pacific Northwest Research Station. 58 p.

525

Variable-Density Thinning in Coast 

Redwood: a Comparison of Marking

Strategies to Attain Stand Variability

Kevin L. O’Hara1, Lathrop P. Leonard2, and Christopher R. Keyes3

Abstract

Variable-density thinning (VDT) is an emerging thinning method that attempts to enhance 

stand structural heterogeneity by deliberately thinning at different intensities throughout a 

stand. VDT may create stands with dense areas, open areas, and other areas that may be 

intermediate in density. Subsequent stand development forms a more varied structure than is 

common in many even-aged forest stands. VDT is becoming a treatment of choice in many 

restoration efforts where even-aged stands are being directed on trajectories towards old forest 

stand structure conditions because: 1) VDT enhances structural heterogeneity, and 2) a 

reduction in tree density provides for an accelerated development towards old forest 

conditions. A primary difficulty in marking VDT treatments is systematically attaining the 

variability necessary in a VDT prescription. Instead, markers/thinners are seemingly trained to 

implement a prescription by applying a uniform treatment across a stand that enhances 

structural homogeneity. 

In coast redwood (Sequoia sempervirens), VDT has become the primary restoration treatment 

for young stands within the national and state parks of Humboldt and Del Norte Counties. 

These stands are young and even-aged developing following clearcutting by previous 

industrial landowners. VDT is being used to increase structural heterogeneity, increase the 

proportion of redwood or other conifers, or accelerate development towards old forest 

structures. Six marking/thinning prescriptions are described that have been used to date to 

achieve the VDT objectives in coast redwood:

1) “Randomized grid – moderate density”: 371 tph (150 tpa). Required marker to visualize

grid area and randomly assign 0 to 3 trees for each grid area (more fully described in 

O’Hara et al. 2010). Used in research study to achieve target densities. Post-treatment 

densities ranged from 346 to 558 tph in three treatment areas (blocks). Labor intensive to 

use on operational basis. 

2) “Randomized grid – low density”: 185 tph (75 tpa). Same as number 1, but lower target 

density. Attempted to achieve target restoration density in one treatment. Lower density 

achieved by marker visualizing larger grid but still randomly assigning 0 to 3 trees to 

each grid area. Post-treatment densities ranged from 192 to 331 tph (more fully described 

in O’Hara et al. 2010).

3) “Dx rule” – in predominantly coast Douglas-fir (Pseudotsuga menziesii var. menziesii) 

stands. Largest Douglas-fir greater than 12.7 cm is identified, diameter in inches is 

multiplied by 2, and all trees between 12.7 and 24.5 cm are cut within that radius (feet) 

but not more than 6.1 m (20 ft). Performed on two contrasting sites where resultant 

densities were 238 and 576 tph. Feasible for thinners to implement without marking and 

allows heavier cutting of broadleaved trees (more fully described by Keyes et al. 2010).

4) “16 x 16 ft” or 4.9 x 4.9 m: Thinning attempted to leave most desirable trees on a 4.9 x 

4.9 m (+ 1.3 m). Did not cut any redwood stump sprouts and counted a redwood sprout 

 

1 University of California Berkeley, 137 Mulford Hall, Berkeley, CA 94720-3114; (510) 642-2127. 

(kohara@berkeley.edu).

2 California State Parks, Crescent City, CA.

3 University of Montana, Missoula.
GENERAL TECHNICAL REPORT PSW-GTR-238 

526

clump as one tree. Easy for thinners familiar with standard precommercial thinning 

methods. Easy to achieve target density but relatively low variability in spacing (table 1).

5) “20 x 20 ft” or 6.1 x 6.1 m: Thinning attempted to leave most desirable trees on a 6.1 x 

6.1 (+ 1.3 m). Similar attributes as “16 x 16 ft” treatment but achieved lower density and 

greater variability (table 1). 

6) “Localized release”: Thinners cut 7.6 m (25 ft) circles leaving three best retention trees in 

any position in circle. Spaces between two circles thinned to 3.7 x 3.7 m spacing. Spaces 

between three or four circles left unthinned. Did not cut any redwood stump sprouts and 

counted a redwood sprout clump as one tree. Achieved highly variable spacing (table 1) 

and approximately 112 tph with full exposure. More difficult to implement for thinners.

The coefficient of variation is used to provide a measure of variability for trees per ha 

between sample plots (table 1). Controls represent either unthinned controls for all six 

methods except Panther Creek where the controls were the pretreatment densities. All six 

methods resulted in an increase in the coefficient of variation indicating an increase in stand 

level spatial heterogeneity. O’Hara et al. (2010) also showed increased tree size variability 

with both the medium and low density treatments with the “randomized grid” method. 

Key words: Sequoia sempervirens, variable-density thinning, precommercial thinning, 

intermediate operations, timber stand improvement

Table 1—Coefficient of variation (CV) for the six prescriptions/marking tools. CV was 

calculated as the average of block CVs and the number of blocks is shown as the sample size 

(n). CVs for untreated stands are shown except for Panther Creek which is a pretreatment 

CV. Other prescriptions share the same untreated stand data. 

Prescription Site CV treated

stands

n CV untreated

stands or before

treatment

n

“Randomized grid 

moderate density”

Mill Creek 0.390 5

0.245 5 

“Randomized grid 

low density”

Mill Creek 0.432 9

“Dx Rule” Panther 

Creek

0.780 2 0.488 2

“16 x 16 ft” Mill Creek 0.179 5

“20 x 20 ft” Mill Creek 0.208 5 0.166 5 

“Localized release” Mill Creek 0.334 5

References

Keyes, C.R.; Perry, T.E.; Plummer, J.F. 2010. Variable-density thinning for parks and 

reserves: an experimental case study in Humboldt Redwoods State Park, 

California. In: Jain, T.B.; Graham, R.T.; Sandquist, J., technical editors. Proceedings of 

the 2009 national silviculture workshop. Integrated management of carbon sequestration 

and biomass utilization opportunities in a changing climate. RMRS-P-61. Boise, Idaho: 

U.S Department of Agriculture, Forest Service, Rocky Mountain Research Station: 227-

237.

O’Hara, K.L.; Nesmith, J.C.B.; Leonard, L.; Porter, D.J. 2010. Restoration of old forest 

features in coast redwood forests using early-stage variable density thinning. 

Restoration Ecology 18(S1): 125-135.
527

The Scotia Plantation: Implications for 

Multiaged and Even-aged Silviculture

Kevin L. O’Hara1

Abstract

The Scotia Plantation was established in 1982 on the large alluvial flat south of Scotia and 

adjacent to the Eel River. Seedlings, from local “woods run” seed sources, were planted on a 

3.1 x 3.1 m (10 x 10 ft) grid. Site quality was very high, with site index averaging greater than 

45 m (50 yr base). In 1997, the area was divided into blocks and a series of thinning 

treatments were randomly assigned to these blocks. Thinning treatments included alternate 

row, diagonal row, every-third row, a double-alternate row, and a low density treatment. Plots 

were established and measured in the winter of 2002 to20003 and remeasured in 2007 after 5 

growing seasons. 

Stump sprout development following thinning treatments was very sensitive to available light 

resources. In the most heavily thinned treatment, the largest understory sprouts were up to 

12.8 m (42 ft) in height and 12.7 cm (5 in) at dbh in only 10 years. However, at low light 

intensities many sprout clumps were completely dead. For example, in 2007 after 5 years, 

clump survival was only 9 percent in the third row treatment, but 100 percent in the low 

density treatment (O’Hara and Berrill 2010). Implications for multiaged silvicultural 

strategies suggest that treatments that create stump sprouts may not be sufficient by 

themselves for regenerating a new age class; additionally, light levels must also be sufficient 

to allow these sprouts to grow and survive. Our results suggest a light level of 40 percent of 

full sunlight is needed to sustain sprout height growth approaching 1 m/yr and light levels of 

10 percent of full sunlight is needed for sprout survival. These sprout development results are 

published in more detail in O’Hara et al. (2007) and mortality patterns in O’Hara and Berrill 

(2010).

Volume increment for the Scotia Plantation was comparable to the fastest growing conifer 

plantations in the world. Periodic annual increment (PAI) ranged from 42.9 to72.6 m3

/ha/yr 

(613 to 1082 ft3

/ac/yr) depending on treatment (table 1). Mean annual increment (MAI) 

ranged from 15.4 to 40.0 m3

/ha/yr (220 to 570 ft3/ac/yr); MAI was considerably lower than 

PAI suggesting MAI was far from culmination and that these values underestimate potential 

productivity for the Scotia Plantation. These results are comparable to the greatest production 

from other conifer and broadleaf plantations around the world and demonstrate the enormous 

production potential of coast redwood. 

Key words: Sequoia sempervirens, thinning, plantation management, forest production, 

coppice, sprout development

 

1 Professor of Silviculture, University of California Berkeley, 137 Mulford Hall #3114, Berkeley, CA 

94720-3114. (kohara@berkeley.edu). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

528

Table 1—Volume production of four thinning treatments and one control from the Scotia 

Plantation through age 21 and 25 years. Values are means from 2 to 3 plots per treatment. 

References

O’Hara, K.L.; Stancioiu, P.T.; Spencer, M.A. 2007. Understory stump sprout development 

under variable canopy density and leaf area in coast redwood. Forest Ecology and 

Management 244: 76-85.

O’Hara, K.L.; Berrill, J-.P. 2010. Dynamics of coast redwood sprout clump development 

in variable light environments. Journal of Forest Research 15: 131-139. 
529

Coast Redwood Responses to Pruning

Kevin L. O'Hara1

Abstract

A large-scale pruning study was established in the winter of 1999 to2000 at seven different 

sites on Green Diamond Resource Company forestlands in Humboldt County. The objective 

of this study was to determine the effects of pruning on increment, epicormic sprouting, stem 

taper, heartwood formation, and bear damage on these young trees. Pruning treatments varied 

pruning severity and were usually applied in conjunction with thinning treatments. Trees were 

assessed six years after pruning. Basal area increment decreased with increasing pruning 

severity but results were inconsistent from one study site to another. Height increment was 

unaffected by pruning. Six-year volume increment results resembled those for basal area 

increment: heavier pruning sometimes resulted in lower increment. Additionally, the negative 

effects of pruning on tree increment were probably short-lived in redwood because of the fast 

growth rates of this species. The number of epicormic sprouts was generally unaffected by 

pruning severity with the notable exception of the most severe pruning treatments. By year 

six, the number of sprouts was no different in the unpruned treatments than in most pruned 

treatments. The exception was the severe crown removal that left only approximately 15 

percent residual live crown length. Epicormic sprouting does not appear to be a deterrent to 

pruning in redwood. Tree stem taper was also unaffected by pruning severity. Heartwood 

formation was expected to increase with pruning severity. However, no effects were evident 

in these data. Apparently, the greater heartwood expected in more severely pruned treatments 

was obscured by the same factors that minimized treatment effects on increment: in the six 

years following treatment, the pruned trees had rebuilt crown foliage and required similar 

sapwood for water transport as unpruned trees. Bear damage was observed at four of the 

seven study sites and was severe in several plots. However, no trends were evident relative to 

pruning treatment. In summary, pruning that leaves residual crown lengths of 40 to 60 percent 

should result in minimal levels of epicormic sprouting and no effects on tree increment.

Key words: Sequoia sempervirens, forest pruning, timber stand improvement, silviculture, 

wood quality

Introduction

Forest pruning is a common means to enhance wood quality in young forest 

stands. By removing lower branches, wood is formed over the branch wound that is 

clear and usually straight-grained. This clearwood is generally expected to produce 

higher grade wood products and earn a premium. Pruning may also improve stem 

taper from pruned logs and enhance heartwood development. In some species, such 

as coast redwood (Sequoia sempervirens), heartwood has desirable appearance and 

decay resistance properties which make it more valuable than sapwood. 

 

1 Professor of Silviculture, University of California Berkeley, 137 Mulford Hall #3114, Berkeley, CA 

94720-3114. ( kohara@berkeley.edu). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

530

Although the effects of pruning forest trees are generally positive, it can lead to 

excessive epicormic branch production in some species, including coast redwood. 

Epicormic sprouts respond to increased light or temperature on the pruned stem 

resulting in a profusion of branches. These can negate the value of the pruning 

treatment by producing wood quality defects in the clear wood produced in the outer 

tree boles. 

No previous study has provided an analysis of the effects of pruning on coast 

redwood. This paper describes a six-year study to look at the effect of pruning on tree 

increment, stem taper, epicormic sprouting, heartwood development, and bear 

damage. 

Project description

Pruning plots were established during the winter of 1999 to 2000 in seven stands 

(study sites) that received pruning treatments in the fall of 1999. All seven study sites 

were located in Humboldt County, California on Green Diamond land. These plots 

were designed to measure the effects of pruning on individual trees. Hence plots were 

assemblages of approximately 30 trees per treatment rather than being of fixed area. 

All study sites included control plots and some included more than one pruning 

treatment. Of the seven study sites, all but two were designed to represent standlevel, operational pruning treatments. The other two study sites – 299 Cutoff and Mline – provided variable pruning treatments over small areas, but not on an 

operational scale. At time of initial measurement, trees were tagged, and marked at 

dbh. Measurements taken at time of plot establishment included dbh, height, height to 

live crown after pruning, height to base of live crown on unpruned trees, counts of 

epicormic sprouts, and some upper stem diameter measurements (either at 2.7 or 5.5 

m height). Additionally, trees of common stump origin were noted. Tree 

characteristics at first measurement are presented in table 1. 

The plot remeasurements and data analysis in 2001/02 and 2006 included studies 

of epicormic sprouting, increment, heartwood formation and stem taper. Analysis of 

variance was used to compare treatment means within study sites. When ANOVA 

indicated significant differences between treatment means, Tukey’s HSD multiple 

range tests were used to identify significantly different means.

Growth response studies

Trees were remeasured in 2001 and 2002 and spring 2006 for height and dbh. 

Nearly all trees were also measured for diameter at tree height of 2.7 m (9 ft). The 

original plot measurements in 1999 to 2000 included height and dbh measurements, 

but not all trees were measured for the 2.7 m upper stem diameter measurement. 

Cubic volumes were estimated assuming the tree base to bh was a cylinder, bh to 2.7 

m a cone frustum, and above 2.7 m as a cone for smaller trees. Equations from 

Krumland et al. (1977) were used for larger trees. Relative growth was calculated as 

the 6-year volume increment divided by volume in 1999 to 2000. 

Results resemble those from pruning studies with other species except for an 

apparent lack of sensitivity to more severe pruning treatments in redwood than has 

been observed in other pruning studies (table 2). In other species, a strong decrease in 
Coast Redwood Responses to Pruning

531

increment with increasing pruning severity is usually found (O’Hara et al. 1995). In 

terms of plot comparisons, there were abnormalities in both the 299 Cutoff and MLine study sites. At 299 Cutoff, the control plot had much greater increment than 

expected. At M-Line, the 15 percent residual treatment had greater increment than 

expected. 

Table 1—Average pruning heights, initial tree heights and diameters by plot and study site 

(pruning heights for control treatments are live crown heights at beginning of study) Average 

residual crown lengths show actual average crown lengths following pruning. 

Basal area increment/tree was largely unaffected by pruning intensity. Many 

study sites experienced increased basal area increment following pruning as 

compared to controls (Maple Creek, Fortuna, and to a lesser extent M-150). 

However, at 299 Cutoff, the control basal area increment/tree was considerably 

greater than the pruned treatments. At M-line, no trend was evident and the 15

percent residual crown treatment had virtually the same basal area increment as the 

control. This suggests a combination of site irregularities across plots and the 

possible influence of more productive clones on some plots. For example, it is 

possible that one plot could be dominated by the sprouts of one stump that is very 

productive, whereas the next plot is dominated by a less productive sprout clump. An 

additional factor was pretreatment tree size variability and its affect on growth. 

Growth was therefore also expressed as “relative growth” by dividing 6-year basal 
GENERAL TECHNICAL REPORT PSW-GTR-238 

532

area increment per tree by pretreatment basal area. This analysis produced 

substantially different results than the absolute basal area increment/tree analysis. For 

the 299 Cutoff study site, the highest relative growth was in the 30 percent residual 

treatment whereas at M-line it was the 60 percent residual. 

There were few significant differences in height increment among study plots. 

This result was expected as only very severe pruning treatments generally affect 

height increment. Significant differences were found at other study sites between 

control and pruned height increment, but these may have been the result of bear 

damage preferentially affecting taller trees thereby reducing average increment.

Cubic volume increment followed similar trends as basal area and height 

increment (fig. 1, table 2). Statistical significance was only found at Mitsui and these 

results were influenced by bear damage. Relative volume increment (volume 

increment per unit of pretreatment volume) was statistically significant for some 

treatments/study sites. For example, at 299 Cutoff, the 30 percent residual treatment 

was significantly greater than the 15 percent and 35 percent treatment. This suggests 

an affect related to clonal patterns within measurement plots rather than a positive 

effect of that particular pruning treatment. 

In summary, pruning apparently has relatively minor effects on increment in 

coast redwood as represented by basal area increment, height increment, and volume 

increment. There is some evidence of reduced increment with the most severe 

pruning treatments, but for the operational range in pruning severity (> 35 percent

residual live crown) there is no effect 6 years after pruning. 

Figure 1—Cubic volume response after six years at 299 Cutoff.
Coast Redwood Responses to Pruning

533

Table 2—Six-year cubic volume increment and relative growth rates. Relative growth rates 

were volume increment divided by volume at time of pruning. Means followed by common 

letters within a study site were not significantly different (α=.05). Standard errors (SE) are 

given in parentheses following means.

Epicormic sprout studies

Approximately 10 trees per plot were randomly selected in 2002 for epicormic 

sprout sampling. For pruned trees, the pruned section of the bole was divided into six 

sections and one section was randomly selected for sampling and marked with paint. 

For example, a tree pruned to 3 m would have six 0.5 m sections and one of these 

sections would be randomly selected for measurement. In these sections, all sprouts 

were counted and the highest and lowest sprouts in the section were measured for 

length and caliper (diameter at base). The estimated number of sprouts per tree was 

the section count multiplied by six. Unpruned trees were sampled in a similar way: 

the section of bole, equal to 5.5 m or the highest level pruned in adjacent pruned 

plots, was divided into six sections and one section was randomly selected for 

measurement. On control plot trees, only sprouts that originated at the time of the 

pruning or after the pruning were counted. This may be a potential source of error as 

sprout age was difficult to determine. Caliper measurements on small sprouts may 

also be biased because the presence of scale-like leaves at the base of these sprouts 

may have exaggerated their diameter. The presence of leaves on larger sprouts had 

little effect on caliper measurements. This sampling procedure was followed in both 

2002 and 2006. The same stem section was therefore sampled at each measurement. 

Because of sprout mortality between 2002 and 2006, however, the same sprouts may 

not have been measured in both years. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

534

The estimated number of sprouts per tree was unaffected by pruning severity 

except at most severe pruning (table 2). Numbers of sprouts declined from 2002 to 

2006. Figure 2 shows the relationship between estimated number of sprouts and 

residual crown length for 2006 at 299 Cutoff. A flat trend in number of sprouts is 

apparent until a sharp increase with the 15 percent pruning. After 6 years, there were 

no significant differences in numbers of sprouts in any of the study sites except the 

most severe treatments at the 299 Cutoff and M-Line. However, variance was large in 

these samples because some trees appeared to be much more prone to sprouting than 

other trees in the same treatment. There may also have been a clonal component to 

these results where one clone dominated a plot and had a disparate influence on the 

plot average. In a separate analysis of these data, O’Hara and Berrill (2009) showed a 

clonal effect to sprouting where some clones were more likely to produce epicormic 

sprouts than others.

Figure 2—Estimated number of sprouts per tree in 2006 for treatments at the 299 Cutoff study 

site. The "5.5 m or 35 percent" residual crown length treatment was pruned to 5.5 m (18 ft) lift 

or no less than 35 percent residual live crown.

Larger sprout length and diameter is indicative of the size of the resulting wood 

quality defect, and probably indicative of sprout persistence over time. Larger sprouts 

were found on the most severely pruned trees which suggested these sprouts are a 

more important component of photosynthesis needs and are therefore likely to 

persist. This result is consistent with other species including giant sequoia (O’Hara et 

al. 2008). In this study, more severe pruning treatments resulted in a large increase in 

average sprout size in most study sites, and particularly in the 299 Cutoff and M-Line

study sites that included severely pruned trees. For example, at 299 Cutoff, the 

average sprout caliper in the 15 percent residual treatment was five times the average 

in the 60 percent residual treatment. Because of the decline in number of sprouts 

from 2002 to 2006 (table 3), the sample sizes for sprout measurements also declined 

during this period. This contributed to the high variation in sprout sizes, the lack of 

consistent trends in sprout size with increasing pruning severity, and the lack of 

statistical significance when means were quite different.
Coast Redwood Responses to Pruning

535

It should be noted that trees in unpruned plots also produced epicormic sprouts. 

Some of these plots received precommercial thinning treatments at the time of 

pruning while others were thinned up to three years before pruning. This indicates 

that some background level of sprouting is present on young redwood trees. In 

Table 3—Epicormic sprout data for pruned and unpruned plots in 2002 and 2006. The 

Carlotta plot D was not measured for epicormic sprouts because of extensive bear damage. 

Common lower case letters within study sites denote means that were not significantly 

different. Standard errors (SE) are given in parentheses following means.

unpruned trees, this sprouting is not a major consideration since clearwood is not an 

expectation from these plantations. In pruned trees, development and persistence of 

sprouts, whether background level or not, is likely to cause wood quality defects and 

reduce potential returns from a pruning investment. However, the results in 2006 

indicate no difference in level of sprouting or persistence of sprouts between the 

unpruned and all but the most severely pruned trees

Stem taper

A measure of stem taper was calculated by dividing tree diameter at 2.7 m (9 ft) 

by tree diameter at bh (1.37 m). Note that some plots were not measured at 2.7 m, or 

experienced so much bear damage by 2006 that samples were too small for analysis. 

Pruning generally reduces stem taper through reduced radial increment at the base of 

tree and only a minor effect further up the stem (O’Hara 1991). Results from this 

study showed virtually no affect of pruning on stem taper. 299 Cutoff showed 
GENERAL TECHNICAL REPORT PSW-GTR-238 

536

increased taper in the control but M-Line had the greatest taper in the most severe 

pruning treatment. Only the results at 299 Cutoff were statistically significant.

These results suggest that pruning has no effect on stem form as represented by 

the measure of stem taper used here. An upper stem diameter measurement higher on 

the stem may have yielded a stem form measure more sensitive to pruning. These 

results were also affected by the rapid growth rates and recovery of trees following 

pruning that may have obscured affects of pruning on stem taper. Additionally, all 

plots were thinned at about the same time as the pruning treatments. Since thinning 

generally increases stem taper, these two opposite effects were both affecting stem 

form of study trees. 

Heartwood formation

Sample trees were cored at time of establishment of this study, and again in 2006. 

These trees were randomly selected. Cores were removed at bh and were 

immediately measured for sapwood thickness based on the visual translucence of the 

sapwood. Sampling was limited to the same 10 trees/plot sampled for epicormic 

sprouts. 

Reducing the size of the crown reduces the transpiration requirements of the tree 

and also the need for sapwood conducting tissues. However, contrary to expectations, 

pruning had no effect on heartwood formation in this study. 

Possible explanations for the lack of a positive heartwood response in these data 

include the small sample sizes. The only post-pruning significant response was at 

Maple Creek where sample sizes were also highest. However, when ignoring 

statistical significance, these results do not reveal the expected trends of increasing 

percent heartwood with increasing pruning severity. At both 299 Cutoff and M-Line

the control treatments were among the highest in percent heartwood and heartwood 

expansion. A more likely explanation is the rapid growth of these trees over the 6 

year period has allowed them to rebuild crowns (through both height growth and 

epicormic sprouting) therefore requiring comparable sapwood conducting tissues 

regardless of treatment. Affecting heartwood at final harvest would apparently 

require repeated pruning or more severe pruning to significantly reduce crown size at 

end-of-rotation. 

Bear damage

Bear damage was noted in plots at both the 2002 and 2006 remeasurements. The 

circumference of the damage around the base the tree was estimated to the nearest 10 

percent. Bear damage was found in four of the seven study sites: M-Line, Carlotta, 

M-150, and Mitsui. The worst damage was at Carlotta and Mitsui, but concentrated 

in several plots. In the case of the Mitsui study site, the plots were considerable 

distance from each other. There were also no patterns evident with regard to pruning 

treatment. At Carlotta, two of the pruning treatments experienced damage to greater 

than 50 percent of the trees whereas the control and another pruning treatment 

experienced relatively light damage. At M-150, the percent of damaged trees was

constant across all treatments. The percent of bole circumference damaged is of 

limited value because of healing that might have taken place since the damage 
Coast Redwood Responses to Pruning

537

occurred that reduced the visible damage and the percent values were just visual 

estimates. Future studies to ascertain the effects of silvicultural treatments on bear 

damage should involve much larger treatment areas and larger measurement plots 

than those used in this study. 

Summary and recommendations

The response of coast redwood to pruning varies from typical responses of 

conifers. The typical decreasing increment with increasing pruning severity pattern 

was not observed in these study plots despite the inclusion of very severe pruning 

treatments. Instead, redwood growth is less sensitive to pruning and reductions in 

crown size than other conifers. 

Epicormic sprouting occurred following pruning and resembled patterns for other 

species. These included an initial sprouting response after pruning but a decline in 

sprouting over time. Six years after pruning, the number of sprouts in the moderate 

pruning treatments had declined to levels that were comparable to the unpruned 

controls. Pruning at moderate levels (leaving 40 to 60 percent live crown) had no 

effect on epicormic sprouting.

Pruning did not affect stem taper based on the ratio of diameter at 2.7 m (9 ft) 

and diameter at bh. A taper measure based on a higher stem diameter measure may 

have produced results that were consistent with other pruned conifers. Additionally, 

all plots were also thinned: pruned trees were therefore also reacting to the effects of 

thinning which generally increases taper. Similarly, there was no effect of pruning on 

heartwood development. The expectation was an expansion of heartwood because of 

reduced sapwood requirements for smaller crowns in pruned trees. The rapid 

recovery of foliage after pruning that contributed to the rapid growth recovery 

apparently required sufficient sapwood conducting tissues and negated the effect of 

crown reduction on heartwood development. 

Several pruning plots have experienced major damage due to bear girdling. There 

was no apparent pattern to this damage with regard to pruning treatment. However, 

these small plots were too small to assess bear preferences for pruning treatments. 

Without the threat of excessive bear damage to pruned trees, pruning would 

appear to be a viable treatment to enhance wood quality in coast redwood. The longterm effect of pruning on epicormic sprouting is minimal with moderate pruning 

regimes. Pruning has little effect on redwood volume or height increment making this 

species one of the least sensitive conifer species to pruning. 

References

Krumland, B.E.; Wensel, L.C.; Dye, J.B. 1977. Young growth volume tables for California 

coastal conifers. Res. Note No. 3. Berkeley, CA: University of California Berkeley, 

Coop Redwood Yield Research Project. 

O'Hara, K.L. 1991. A biological justification for pruning in coastal Douglas-fir stands.

Western Journal of Applied Forestry 6(3): 59-63.

O'Hara, K.L.; Parent, D.R.; Hagle, S.K. 1995. Pruning eastern Cascade and northern 

Rocky Mountain species: biological opportunities. In: Hanley, D.P.; Oliver, C.D.; 
GENERAL TECHNICAL REPORT PSW-GTR-238 

538

Maguire, D.A.; Briggs, D.G.; Fight, R.D., editors. Forest pruning and wood quality. 

Contribution No. 77. Seattle, WA: Univ. of Washington Institute of Forest Resources: 

216-237.

O’Hara, K.L.; York, R.A.; Heald, R.C. 2008. Effect of pruning severity and timing of 

treatment on epicormic sprout development in giant sequoia. Forestry 81(1): 103-

110.

O'Hara, K.L.; Berrill, J-.P. 2009. Epicormic sprout development in pruned coast redwood: 

pruning severity, genotype, and sprouting characteristics. Annals of Forest Science 

66(409): 1-9.
539

Using FORSEE and Continuous Forest 

Inventory Information to Evaluate 

Implementation of Uneven-aged 

Management in Santa Cruz County Coast 

Redwood Forests1

Douglas D. Piirto,2 Scott Sink,2 Dominic Ali,2 Steve Auten,3

Christopher Hipkin,4 and Reid Cody2

Abstract

Swanton Pacific Ranch in northern Santa Cruz County has been owned and managed by 

California Polytechnic State University (Cal Poly) Foundation since 1987. The California 

Forest Practice Rules specific to Santa Cruz County limit harvest rate and opening size. Cal 

Poly forest managers are implementing uneven-aged forest management on 1,182 acres of 80

to 110 year old, second-growth coast redwood forests using a modified BDq approach. The 

Lockheed Fire spread into most of the managed forest area during the summer of 2009 

causing significant mortality in lower diameter classes.

Little information is available on implementation of uneven-aged forest management for coast 

redwood stands in Santa Cruz County especially regarding the influence of fire. This McIntire 

Stennis funded, observational research study used the Forest and Stand Evaluation 

Environment (FORSEE) program and a 22 year Continuous Forest Inventory (CFI) record to 

evaluate changes in past and current stand structure using trees per acre, basal area per acre, 

and volume per acre. Stand structural changes associated with uneven-aged management and 

disturbance were detected using FORSEE analysis of the CFI records. FORSEE is a useful

inventory, growth and yield model that will become better with local calibration.

Key words: Sequoia sempervirens, coast redwood, multi-aged, BDq, FORSEE, growth and

yield model, fire effects, monitoring, Santa Cruz County

Introduction

Forest management at California Polytechnic State University’s Swanton Pacific 

Ranch and School Forest began in 1986 when owner Mr. Al Smith, requested Cal 

Poly assistance with management of his agricultural and forested properties which he 

bequeathed to Cal Poly in 1993. Mr. Smith’s long-term vision focused on Swanton 

 

1 This paper is dedicated to Mr. Smith who bequeathed Swanton Pacific Ranch to Cal Poly so that we 

could have a place for students, faculty, and staff to learn by doing.

2 Professor and Department Head (805-756-2968, dpiirto@calpoly.edu), Assistant Professor (805-756-

2272, sesink@calpoly.edu), and students (dali@calpoly.edu; mxchamp250@sbcglobal.net), 

respectively, Natural Resources Management Dept., California Polytechnic State University, One Grand 

Avenue, San Luis Obispo, CA 93407.

3 Resource Manager, Swanton Pacific Ranch, California Polytechnic State University, 125 Swanton 

Road, Davenport, CA 95017. (sauten@calpoly.edu).

4 FORSEE Analyst and Registered Professional Forester, Statewide Forestry Services, 607 Poirier 

Street, Oakland, CA 94609. (hipkin@pacbell.net).
GENERAL TECHNICAL REPORT PSW-GTR-238 

540

Pacific Ranch being sustainably managed as a working ranch and forest with many 

interdisciplinary learn-by-doing activities and projects involving students, staff and 

faculty.

Swanton Pacific Ranch is located in the southern sub-district of the Coast District 

(Cal Fire 2011). Very strict forest practice rules have been developed for this district 

due to citizen concerns about the extensive clearcut logging that occurred in the early 

1900s to help rebuild San Francisco after the 1907 earthquake. These current, subdistrict California Forest Practice Rules specify tree removal limits by diameter class, 

maximum permitted opening size, and Water Lake Protection Zone requirements.

In consultation with Big Creek Lumber Company and other forest managers, 

sustainable management of the working forest areas was approached through 

implementation of uneven-aged, modified BDq forest management practices as 

discussed in the 1991 forest management plan (Alexander and Edminster 1977, 

Baker et al. 1996, Big Creek and Cal Poly 1991, de Liocourt 1898, Guldin 1991, 

Leak and Gottsacker 1985, Marquis et al. 1992, Meyer 1943, Meyer 1952, O’Hara 

and Gersonde 2004). Two presentations at earlier Redwood Symposiums focused on 

initiation of forest management practices at Swanton Pacific Ranch (Piirto et al. 

1996b, Piirto et al. 2007). Further, a paper on approaches to managing tanoak at the 

Cal Poly’s Swanton Pacific Ranch was presented at the 1996 California Oak 

Symposium (Piirto et al. 1996a). Current forest management at Swanton Pacific 

Ranch is guided by the 2008 Non-Industrial Timber Management Plan (Big Creek 

and Cal Poly 2008). 

Forest managers must consider human and ecological legacy as they develop 

management plans for a specific forested area. Fire, windstorms, landslides, and 

flooding are several examples of ecological disturbance processes that affect coast 

redwood forests. Fire has been reported as being a low to moderate disturbance factor 

that can ultimately lead to multi-aged coast redwood stands (Lorimer et al. 2009). 

The ecological role of fire in Santa Cruz Mountain coast redwood forests has been 

and continues to be the subject of a number of recent studies (Brown and Swetnam 

1994, Greenlee and Langeheim 1990, Lorimer et al. 2009, Ramage et al. 2010, 

Stephens and Fry 2005, Stephens et al. 2004). A study by Hyytiainen and Haight 

(2010) reported that fire had differing effects in even-age stands (decreased optimal 

rotation lengths and planting densities) as contrasted to uneven-aged managed stands 

(reduced optimal diameter limits). The occurrence of the Lockheed Fire at Swanton 

Pacific Ranch in 2009 provided an opportunity to study the impact of fire on a forest 

under uneven-aged forest management.

Measuring key ecosystem attributes is fundamental to successful forest 

management. The application of ecosystem management principles requires 

understanding of past and present conditions (i.e., reference conditions) as desired 

future conditions are defined and adaptive forest management occurs (Manley et al. 

1995, Piirto and Rogers 2002). Given these considerations, are we succeeding with 

implementation of uneven-aged forest management at Swanton Pacific Ranch? The 

objectives of this observational study were to:

1. Consolidate and standardize the 1989 initial forest inventory, the 1997, 2008, 

and 2010 (post-fire) Continuous Forest Inventory (CFI) data (fig. 1) into one 

database for use in FORSEE.

2. Utilize the inventory data and the FORSEE model to test two hypotheses: 
Using FORSEE and Continuous Forest Inventory Information to Evaluate Implementation of 

Uneven-aged Management in Santa Cruz County Coast Redwood Forests

541

a. Stand structural changes can be detected using a CFI System and a 

FORSEE Analysis Tool; and

b. Major disturbance events quantifiably influence establishment and 

survival of young age-classes in uneven-aged managed stands.

Figure 1—Swanton Pacific Ranch CFI plots and vegetation types in study 

area. 

Methods

The process used to implement forest management, delineate the project area and 

map development, 1989 forest inventory methods, CFI methods (1997, 2008, 2010), 

data compilation, data auditing, data analysis, FORSEE calibration, and assumptions 

are described below.

Implementation of forest management 

A modified, specified residual basal area in square feet (B), maximum retained 

diameter class (D), and negative exponential constant between diameter classes (q) 

(de Liocourt 1898, Guldin 1991, Leak and Gottsacker 1985, Meyer 1952) approach 

was employed to implement uneven-aged forest management at Swanton Pacific 

Ranch consistent with current California Forest Practice laws and associated 

regulations (Cal Fire 2011). Detailed prescription reports were developed for each of 
GENERAL TECHNICAL REPORT PSW-GTR-238 

542

the stands in the Little Creek area of Swanton Pacific Ranch (Haupt and Piirto 2006, 

Piirto and Cross 1996 [revised 1999], Piirto and Piper 1990). Tree removal was 

guided by the tree marking rules with BDq adjustments made for specific stands.

Residual stand density basal area (B) target was set at 180 to 220 square feet 

per acre. This residual largely conifer stand density target was initially established as 

a percentage reduction of normal stocking as shown in Lindquist and Palley (1963)

and Piirto et al. (1996b) consistent with expected growth for the next 10-year 

growing cycle. This basal area target range thus results in retaining 42 to 51 percent 

of full stocking if we assume that: 1) a Lindquist and Palley (1963) normal stand with 

a site index of 130 (site class III, base age 100 years) has 431 square feet and 2) that 

this Lindquist and Palley (1963) normal basal area value is a reasonable estimate of 

complete site occupancy for a 100 year old coast redwood stand. Recent work by 

Berrill and O’Hara (2009) and Oliver et al. (1992) discuss stocking control in multiaged coast redwood stands.

The largest tree retained in the stand varied between 30 and 38 inches DBH in 

relation to individual stand objectives. Stand F (The Tranquility Stand), for example, 

was a favorite spot for Al Smith. He requested that we work to retain some of the 

larger second-growth trees in Stand F as part of the uneven-aged forest 

management objectives. As such, the maximum tree size in Stand F was set at 38 

inches with retention of a few larger trees consistent with Mr. Smith’s direction. A 

maximum DBH tree size of 34 inches for uneven-aged managed stands provides 

good yield and a sizeable individual tree heartwood core which is important to 

lumber grades and associated value (Piirto and others 1996b).

The negative exponential constant (i.e., in 2 inch DBH classes) was set between 

1.2 and 1.3 consistent with advice received from managers at Jackson Demonstration 

State Forest, Guldin (1991), and as described in Long and Daniels (1990). Further 

research by Berrill and O’Hara (2009) utilized growth and yield (CRYPTOS) and 

stocking assessment (redwood MASAM) models to simulate the effects of multiaged coast redwood management regimes and harvesting scenarios. The timber 

harvest projects administered by Cal Poly and Big Creek Lumber Company since 

1990 are shown in table 1 (harvest/stand area maps are available upon request).

Study area delineation 

The area delineated for this study was determined using the following criteria: 1) 

inventoried at least twice and preferably three separate times; 2) affected by at least 

one timber harvest activity since 1990; and 3) affected by the 2009 Lockheed Fire. 

The total area within the defined study area was 361 acres. Four forest vegetation 

types occur within the project area: Redwood Site Class III–202 acres; Redwood Site 

Class II–34 acres; Douglas-fir–8 acres; and Douglas-fir-Hardwood–117 acres. The 

project area, vegetation types, 1989 initial inventory plots, and 1997/2008/2010 CFI 

plots are illustrated in fig. 1. 
Using FORSEE and Continuous Forest Inventory Information to Evaluate Implementation of 

Uneven-aged Management in Santa Cruz County Coast Redwood Forests

543

Table 1—Swanton Pacific Ranch Little Creek timber harvest projects (1990 to 2011).

THP No. 

and Date Location Acreage Logging system

 Redwood Douglas-fir Total Redwood Douglas-fir Total Redwood Douglas-fir

THP 1-89-539 SCR

 1990 South Fork 59 T 285,810 391,260 677,070 215,530 281,930 497,460 24 28

THP 1-94-071 SCR North Fork 120

 1994 T, C 615,790 326,830 942,620 547,790 253,000 800,790 11 22

 1995 T, C 578,810 274,490 853,300 500,240 207,330 707,570 14 24

Emergency Salvage

 1998 Little Creek 10 C 4,760 7,740 12,500 4,290 6,490 10,780 10 16

THP 1-04-053 SCR Lower Little

 2004 Creek 102 T 588,350 82,280 670,630 495,290 57,320 552,610 16 30

1-07 NTMP-020 SCR

 2008 (NTO#1) North Fork 143 T, C 847,480 22,620 870,100 742,990 13,950 756,940 12 38

 2011 (NTO#2) South Fork 65 H 652,110 46,510 698,620 548,419 32,093 580,512 16 38

Emergency Salvage

1-10EM-006 Lockheed

 2010 Fire Area 148 H 838,440 20 838,460 700,010 20 700,030 17 0

Totals 4,411,550 1,151,750 5,563,300 3,754,559 852,133 4,606,692

Logging system: T = Tractor; C = Cable; H = Helicopter

Gross volume Net volume Defect (% )

1989 forest inventory

The forest resources of Cal Poly’s Swanton Pacific Ranch were inventoried for 

the first time in 1989 to support development of a Forest Management Plan (Big 

Creek and Cal Poly 1991, Piper and others 1989). A 500 foot grid system was 

established in relation to a baseline and benchmark on Swanton Road at the Little 

Creek Bridge. Fifty-two circular 1/5th acre plots (radius 52.7 feet) were installed 

using a systematic approach at the intersecting points of the grid (Piper 1989, Todd 

1988). Thirty-one of these plots in the upper Little Creek drainage affected both by 

timber harvesting and the Lockheed Fire were used for this study. This initial 1989 

forest inventory was never intended to be a permanent CFI system even though it was 

set up on the 500 foot grid system. 

1997, 2008, 2010 continuous forest inventories 

A CFI system with permanently located plots on a 500 foot grid system was 

developed under the direction of Cal Poly faculty and staff in 1997. One-fifth acre 

circular plots have been established. Witness trees were selected and where possible 

GPS coordinates were established to assure proper follow-up measurement of all CFI 

plots. A report describing the specific protocol was developed by Sarah Cross (1997). 

The CFI system was installed in 1997 after the first timber harvest project in Little 

Creek. The results of the 1997 CFI plot measurements are discussed in a separate 

report (Bonner 1998). The CFI plots were re-measured in 2008 just after the second 

timber harvest project for the North Fork area had occurred. The CFI plots were 

subsequently evaluated 2 years later in 2010 after the 2009 Lockheed Fire to 

determine the extent of mortality that occurred. The 2008 CFI measurements are 

discussed in the 2008 Swanton Pacific Ranch Non-Industrial Timber Management 

Plan (Big Creek and Cal Poly 2008). The South Fork area was harvested for a second 

time in 2011. 

Data compilation, data auditing, and data analysis 

All inventory entries were converted into one spreadsheet template with 

consistent species designations, fields, notation and formats. Data were sorted by 

each field and verified with the original field notes where possible (Ali and Cody 
GENERAL TECHNICAL REPORT PSW-GTR-238 

544

2011). All edits and assumptions were annotated and are nested within the master 

spreadsheet. Tree, stand, and site data went through an integrated auditing process as 

it was imported into Access and uploaded to FORSEE. 

FORSEE processing 

The inventory data were compiled and analyzed using the FORest and Stand 

Evaluation Environment (FORSEE) computer program (CAGYM 2011). The 

CRYPTOS growth model option within FORSEE was used to model forest growth, 

as this model is appropriate for the coast redwood forest type (Wensel et al. 1987). 

All suitable site trees within the project area (dominant/co-dominant trees with no 

observable abnormalities and greater than 30 percent crown ratio) for both the 1997 

and 2008 measurements were utilized to establish the initial site index value for the 

delineated project area (Cross 1997). The FORSEE calculated coast redwood site 

index (base age 50) came out to be 100 for this study (Krumland and Eng 2005) with 

a standard deviation of 10 which is considered to be an acceptable estimate. 

Estimates of site index (base age 100) based on Lindquist and Palley (1961, 1963) 

have ranged as low as 80 to a high of 200 with an average around 130 (Big Creek and 

Cal Poly 2008). Both of these average site index estimates fall into a Redwood Site 

Class III and are consistent with documented values (Big Creek and Cal Poly 2008).

The 1989 initial inventory, 1997, 2008, and 2009 post fire CFI inventories were 

processed and analyzed to evaluate stand attributes for: 1) all vegetation types 

(ALLTREES) over the entire 361 acres; 2) redwood vegetation types on site II 

(RW2) and site III (RW3) on 236.4 acres; and 3) Douglas-fir and hardwood 

vegetation types (DFHW). The Douglas-fir/hardwood timber type did not receive full 

evaluation due to high variability, significantly diminished sample size, and tendency 

for most forest management activities to occur in more productive vegetation types.

Results

The summarized information for the 1989 inventory and 1997, 2008, and 2010 

CFI inventories are shown in table 2, and figs. 2 and 3. For the ALLTREES scenario, 

there was an overall reduction in quadratic mean diameter (QMD) from 16.09 inches

in 1989 to 14.87 inches in 2008 with a subsequent increase following the 2009 

Lockheed Fire to 18.91 inches. Trees per acre (TPA) increased from 154.84 in 1989 

to 246.52 in 2008. Following the Lockheed Fire, TPA decreased by approximately 45 

percent down to 136.83 with significant mortality occurring in trees 12 inches in 

diameter and smaller. Volume and basal area averages increased from 1989 to 2008. 

The percent standard errors for these per acre estimates are also shown in table 2. 
Using FORSEE and Continuous Forest Inventory Information to Evaluate Implementation of 

Uneven-aged Management in Santa Cruz County Coast Redwood Forests

545

Table 2—Swanton Pacific Ranch FORSEE current status by inventory period for all 

vegetation types combined (361 acres).

 Species Plot % SE % SE % SE % SE

Inventory Acres Group Number TPA BA QMD BF/AC CF/AC TPA BA BF/AC CF/AC

1989 361 Conifers 31 73.87 161.68 20.03 31,295 5,262 11 12 16 14

1989 361 Hardwoods 31 80.97 56.03 11.26 7,404 1,597 16 17 44 31

1989 361 Totals 31 154.84 217.72 16.06 38,699 6,859 9 9 14 12

1997 361 Conifers 33 122.12 191.63 16.96 42,930 6,927 9 8 12 11

1997 361 Hardwoods 33 106.82 67.90 10.80 10,387 2,268 22 16 26 21

1997 361 Totals 33 228.94 259.53 14.42 53,316 9,195 11 6 10 8

2008 361 Conifers 33 139.85 231.15 17.41 54,907 8,600 9 7 11 10

2008 361 Hardwoods 33 106.67 66.22 10.67 8,777 2,020 20 16 22 19

2008 361 Totals 33 246.52 297.37 14.87 63,683 10,620 10 6 9 7

2010 361 Conifers 30 81.50 209.60 21.71 51,789 8,044 12 9 13 11

2010 361 Hardwoods 30 55.33 57.32 13.78 8,545 1,930 16 16 22 20

2010 361 Totals 30 136.83 266.92 18.91 60,333 9,974 9 7 10 9

Figure 2—Stand structure for combined redwood site II and III vegetation types 

(includes hardwoods and conifers on 236.36 acres). 

Figure 3—Stand structure for combined redwood site II and III vegetation types

(236.36 acres). One standard error is illustrated.

The FORSEE current status analysis for the combined RW2 and RW3 (236.4 

acres within the 361 acre project area) areas indicate a similar reduction in QMD 

from 17.35 to 15.28 inches from 1989 to 2008, and a subsequent increase to 19.05 

inches following the Lockheed Fire (table 3). Trees per acre (TPA) for the combined 
GENERAL TECHNICAL REPORT PSW-GTR-238 

546

Table 3—Swanton Pacific Ranch FORSEE current status for redwood vegetation types.

 Species Plot % SE % SE % SE % SE

Inventory Acres Group Number TPA BA QMD BF/AC CF/AC TPA BA BF/AC CF/AC 

1989 236.36 Conifers 20 87.50 213.05 21.13 45,301 7,467 11 9 13 12

1989 236.36 Hardwoods 20 71.25 47.71 11.08 4,158 1,105 19 23 32 31

1989 236.36 Totals 20 158.75 260.76 17.35 49,459 8,571 10 8 11 10

1997 236.36 Conifers 23 128.26 222.25 17.82 52,091 8,379 10 6 11 10

1997 236.36 Hardwoods 23 88.70 52.00 10.37 6,137 1,502 30 22 27 26

1997 236.36 Totals 23 216.96 274.25 15.22 58,228 9,880 13 5 9 8

2008 236.36 Conifers 23 154.57 263.02 17.66 65,587 10,215 9 6 9 8

2008 236.36 Hardwoods 23 95.43 55.28 10.31 6,945 1,641 26 23 30 28

2008 236.36 Totals 23 250.00 318.30 15.28 72,532 11,856 11 5 8 7

2010 236.36 Conifers 20 105.50 253.27 20.98 64,446 10,019 11 6 10 9

2010 236.36 Hardwoods 20 46.75 48.19 13.75 6,775 1,573 21 24 28 27

2010 236.36 Totals 20 152.25 301.46 19.05 71,221 11,592 9 5 8 7

RW2 and RW3 vegetation type showed a similar increase as the ALLTREES 

scenario going from 158.75 in 1989 to 250 trees in 2008 with a subsequent decrease 

in 2010 following the Lockheed Fire to 152.25. Increases in basal area and volume 

also occurred similar to the ALLTREES scenario from 1989 to 2008 with some 

reduction occurring after the Lockheed Fire. The percent standard errors for these per 

acre estimates are also shown in table 3. 

The 1989 even-age stand structure prior to initiation of Cal Poly forest 

management is shown in figs. 2 and 3. Significant development of understory trees in 

the 2, 4, 6, 8, and 10 inch diameter classes leading to a reverse J shaped curve 

representation occurred after implementation of uneven-management which began in 

1991. A subsequent reduction in the smaller diameter classes occurred after the 

Lockheed Fire (tables 2 and 3; figs. 2 and 3).

Discussion

A number of good lessons were learned as a result of this 25 year effort to initiate 

uneven-aged forest management at Cal Poly’s Swanton Pacific Ranch in the truest 

sense of our motto of learn-by-doing. First, we did not have 1989 inventory and 

1997, 2008, and 2010 CFI in one database. The four Swanton Pacific inventories 

were completed by different individuals and analyzed per procedures established for 

that inventory with a subsequent written or electronic report for each. Using FORSEE 

to evaluate and to predict how our stands were likely to change over time required 

that we: 1) put all data into one database in a consistent manner; 2) fully consider the 

appropriate volume equations for standing trees; 3) establish and adhere strictly to 

plot measurement and site tree selection protocols; and 4) delineate a project area in 

relation to the objectives of the study. All previously collected inventory information 

is now in one database for future studies. 

Second, we have been collecting separate stand exam information to support 

individual stand prescriptions and associated marking rules. Whereas this stand 

specific data was useful for the prescriptions, it could not be used for monitoring 

purposes given that the plots were not permanently located. Thus, we decided to 
Using FORSEE and Continuous Forest Inventory Information to Evaluate Implementation of 

Uneven-aged Management in Santa Cruz County Coast Redwood Forests

547

utilize 1997, 2008, and 2010 CFI inventory data to evaluate if reliable trends in stand 

structural changes could be detected from timber harvest and disturbance events such 

as the Lockheed Fire. We have shown here that our CFI system, when delineated to a 

defined project area, does provide reliable trend information. Both the stratified, 

combined (RW2 and RW3) and no vegetation type classifications (ALLTREES) 

show similar abilities to monitor changes in stand structure when there is a large 

sample of plots, though this threshold is far from being determined. Smaller 

stratification layers, such as the DFHW type, tend to exhibit larger variance due to 

smaller sample sizes. In essence, vegetation stratification needs to ensure statistically 

viable sample sizes in order to meet variance standards commonly used by the 

professional forestry community, but this requires a much broader study. 

Third, we have defined in this study the significant changes in stand structure that 

resulted with implementation of uneven-aged forest management. Stand structure 

(refer to tables 2 and 3; figs. 2 and 3) in 2008 was approaching a regulated state in 

relation to the BDq targets discussed in Piirto et al. (1996b). The Lockheed Fire 

caused a substantial reduction in the recruited trees less than 12 inches. The extent of 

that mortality is illustrated in figures 2 and 3. It is clear that a void in the understory 

diameter classes less than 12 inches has resulted from the Lockheed Fire which will 

affect forest regulation. These results point out the difficulties and challenges 

foresters face as they implement, monitor, and adjust their uneven-aged forest 

management procedures.

Fourth, FORSEE requires the user to thoroughly and systematically audit 

potential errors and inconsistencies. Once data are prepared and successfully 

imported, the user can generate custom inventory reports and forecast growth and 

yield under different harvest scenarios. There is concern among some Swanton 

Pacific Ranch field foresters that results generated from FORSEE are overestimating 

current volume per acre from what is actually observed (Big Creek and Cal Poly 

2008). This could be related to CFI sample size, plot location, the need for local 

calibration of volume equations or other factors. FORSEE must be validated for 

southern coast redwood stands. Additional fall-and-buck studies would validate or 

provide local coefficients for volume equations. CFI data could be used to validate 

growth model projections once more repeat measurements are collected. Further 

research is required.

Conclusions and management implications

Success of uneven-aged forest management in coast redwood stands is dependent 

on a number of factors in addition to land owner objectives and forest practice 

regulations. Uneven-aged forest management is as much an art as it is a science in 

determining the correct residual basal area (B), maximum retained diameter class 

(D), negative exponential constant between diameter classes (q), and cutting cycle 

length. Implementing stand management prescriptions via marking rules is 

complicated by coast redwood’s clumpy spatial distribution which results from 

coppice sprouting. In that context, we offer the following suggestions based on our 

25 years of working and monitoring selection forestry. 

Frequency and/or intensity of harvesting can profoundly affect success of 

coppice development (O’Hara and Gersonde 2004). Maintaining a continuous forest 

cover in terms of residual basal area stocking therefore must be tempered with site 
GENERAL TECHNICAL REPORT PSW-GTR-238 

548

conditions, growing space considerations, harvesting impacts, risk of catastrophic 

fire, and landowner needs for recurring income. The highly varied nature of Santa 

Cruz Mountain redwood stands suggests a silvicultural prescription and associated 

marking rules that adaptively responds to these conditions. Knowing that deficits 

exist in lower DBH size classes should be considered in relation to leaving a few 

larger trees to cover that deficit on subsequent entries (modified BDq approach). 

Long-term success of uneven-aged forest management in coast redwood stands 

requires development of a documented prescription that describes 1) implementation 

of individual tree and/or group selection regeneration methods; 2) tree marking rules; 

3) follow-up reforestation; 4) timber stand improvement treatments (for example, 

fuels treatment, site preparation, tanoak control); and 5) resource concerns. 

There are a large number of complexities associated with implementing unevenaged management in coast redwood stands. Much remains to be determined as to the 

“correct” approach for Santa Cruz County coast redwood stands. We suggest more 

research to: 1) regionalize FORSEE particularly with regard to southern coast 

redwood forests; 2) include biomass and carbon quantification as a component of 

FORSEE; 3) examine how uneven-aged managed coast redwood stands respond after 

a damaging fire to filling deficit diameter classes; and 4) examine how multi-aged 

coast redwood stands respond to various stand manipulation approaches. 

Acknowledgments

We thank here the many individuals, students, organizations, companies, and 

agencies who have contributed over the years to advancing Cal Poly’s learn-by-doing 

forest management and environmental stewardship work at Swanton Pacific Ranch.

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549

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553

Using Wood Quality Measures to Evaluate 

Second-Growth Redwood 

Stephen L. Quarles1and Yana Valachovic2

Abstract

Redwood (Sequoia sempervirens) a valued species for use in appearance grade applications, 

such as decking, exterior siding and interior paneling, because of its dimensional stability. It is 

also valued for certain exterior-use applications because of its natural decay resistance. 

Studies have found that young-growth redwood is less resistant to decay fungi, and also 

exhibits greater shrinkage and swelling than old-growth redwood. Differences in natural 

decay resistance and dimensional stability between old-growth and young-growth could be 

accounted for by changes in the extractives found in the heartwood and changes in 

themicrofibril angle(MFA) in the S2 layer of the cell wall, respectively. Can silvicultural

practices that influence growth rate be used to enhance the natural decay resistance and 

dimensionally stability of second-growth redwood? The objectives of this preliminary study 

were to 1) review anatomical characteristics of redwood that influence in-service performance 

and 2) present results of measurements made from second-growth redwood stumps that 

showed different growth rates. Decay testing data is not available.

Key words: dimensional stability, durability, microfibril angle, redwood, wood quality

Introduction

Redwood has long been a valued species because of the natural decay resistance 

of its heartwood and its dimensional stability. Both of these attributes contributed to 

redwood’s long-term in-service performance, and therefore its value and reputation 

as a durable species. In this respect, “durability” encompasses both biological and 

non-biological performance characteristics – redwood that is performing poorly can 

be removed from service because it is rotting (a biological process) or because it is 

badly warped (a non-biological process). Common uses for redwood have included 

decking, siding and fencing (both as boards and posts). Decay resistance and 

dimensional stability are desirable features for products used for these applications.

The decay resistance of the sapwood (the part of the tree closest to the bark) of 

any species is considered nonresistant. The decay resistance of the heartwood of any 

species is related to the amount and type of extractable (i.e., nonstructural) materials 

that are deposited when sapwood undergoes the transition to heartwood. The decay 

resistance of heartwood (untreated) is typically classified, from least to most 

resistant, as “slightly or nonresistant”, “moderately resistant” or “resistant or very 

resistant” (Wood Handbook 1999). 

 

1

University of California Cooperative Extension (Advisor Emeritus), UC Richmond Field Station, 1301 

S. 46th St., Bldg. 478, Richmond, CA 94804; (510) 665-3580. (steve.quarles@berkeley.edu). 2

University of California Cooperative Extension – Humboldt/Del Norte Counties, 5630 S. Broadway, 

Eureka, CA; (707) 445-7351.( yvala@ucdavis.edu). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

554

The ratio of dimensional change in the tangential (the direction tangent to the 

growth rings) and radial (the direction extending from pith to bark) directions is 

sometimes considered a measure of dimensional stability. The tangential to radial (or 

T:R) ratio typically ranges from 1.5 to 2.5 for all wood species, with a lower number 

indicating greater dimensional stability. Whereas longitudinal shrinkage and swelling 

is normally considered negligible, it can be relatively large in products containing 

wood from near the center of the tree, often referred to as the pith. Dimensional 

change in the longitudinal (and tangential) direction is a function of the microfibril 

angle (MFA) in the S2 layer of the cell wall. When this angle is small, dimensional 

change in the longitudinal direction is also small. As this angle increases, so does 

longitudinal shrinkage and swelling. Meylan (1968) reported only negligible 

longitudinal shrinkage for Jeffery pine (Pinus jeffreyi) when the MFA was less than 

25° but a rapid increase in longitudinal shrinkage when MFAs were greater than 25 

to 30°. This change results in a corresponding reduction in dimensional change in the 

tangential direction. Because the S2 layer constitutes the largest portion of an 

individual wood fiber, it dominates the respective physical properties (e.g., 

dimensional change and some mechanical properties).

Differences in decay resistance and dimensional stability between “old growth” 

and “young growth” redwood have been summarized in the Wood Handbook (Forest 

Products Laboratory 1999). In the Wood Handbook, the natural decay resistance of 

old growth redwood is listed as “resistant or very resistant” and that of young growth 

as “moderately resistant”. This difference in decay resistance is based on published 

research by Clark and Scheffer (1983). The decay resistance of redwood has been 

attributed to its water soluble extractives (Anderson 1961) and, more recently, its 

non-water soluble extractives (Wilcox and Piirto 1976). Regardless of the particular 

type of extractives that impart decay resistance to redwood, it is clear that the 

resistance of young growth redwood is lower and more variable than that of old 

growth. This is particularly true in the inner heartwood area (Clark and Scheffer 

1983). 

The Wood Handbook reported T:R ratios for old growth and young growth 

redwood were 1.7 and 2.2 respectively (Forest Products Laboratory 1999). This 

increase in T:R ratio increases the likelihood of “cup” in a deck board. Another 

component of dimensional stability is movement in the longitudinal direction (i.e., in 

the length direction of a board or post).If longitudinal shrinkage was uniform 

throughout a given member (e.g., a board, post or plank), the expected change in 

dimension could be accounted for during the manufacturing process (i.e., the member 

could be cut longer). However, as discussed by Nault (1989), longitudinal shrinkage 

provides an indication of warping through differential (non-uniform) shrinkage. The 

non-uniform shrinkage in a member (i.e., having higher and lower levels of 

longitudinal shrinkage) would result in twist or crook in service.

The wood formed in the central zone of the tree near the pith has been referred to 

as “juvenile wood”, “core wood”, and “crown” or “crown formed” wood 

(Amarasekara and Denne 2002) and has important influences on dimensional 

stability of lumber. Wood further from the pith has been referred to as “mature 

wood” and “outer wood”. Characteristics of wood vary with distance away from the 

pith, and become more stable with distance (Amarasekara and Denne2002). The 

transition to dimensional stability is not abrupt, which makes it difficult to discuss the 

“juvenile wood zone” (the term used in this publication) in absolute terms, however, 
Using Wood Quality Measures to Evaluate Second-Growth Redwood

555

juvenile wood is negatively influenced by larger MFAs. Much of the research on 

physical properties of juvenile wood has been conducted on southern yellow pine 

(Pinus palustris) grown in the southeastern U.S. and radiata pine (Pinus radiata, 

various clones) grown in New Zealand and Australia. The lack of an abrupt transition 

means that the number of growth rings that make up the juvenile zone is variable. 

The juvenile zone is often considered to encompass the first 15 to 20 growth rings 

and anatomical characteristics and physical properties that would result in more 

durable in-service performance are lower in the juvenile region (Bendsten 1978). 

Juvenile wood in trees is inevitable, but when silvicultural practices are followed 

that result in an increased growth rate (and therefore increased volume) during this 

period, the relative proportion of the tree’s cross-section that is comprised of 

“juvenile wood” is much larger than when silvicultural practices result in slower 

growth. When processing siding, deck boards, or posts from the tree, the chance of a 

given piece having some juvenile wood is greater in the “managed for volume” tree. 

Can silvicultural practices that influence growth rate be modified with redwood 

in such a way to maximize quality attributes? The purpose of this preliminary study 

was to begin exploring whether there was an effect of different growth rate in 

redwood based in quality measures that have traditionally been relied for long-term 

in-service performance. This portion of the study was limited to evaluating the effect 

of growth rate on the MFA in the S2 layer (and inferring the resulting impact on 

longitudinal shrinkage). The decay resistance of side-matched samples is being 

evaluated at another institution and is not currently available.

Methods

Experimental study site and management history 

The forest stand where the tree cross sections were taken is located near Arcata, 

California. The forest was classified as a Site II – III redwood. The stand was 

originally harvested in the 1890s and again partially harvested in the 1950s.For these 

entries the largest and best formed trees were harvested. Since in the 1980’s, three 

commercial thinnings have occurred. Today redwood is the most common tree 

species with lesser components of Douglas-fir (Pseudotsuga menziesii) and grand fir 

(Abies grandis). The trees used in this study were harvested from the stand in 

2010.While it is known that wood quality is responsive to both silvicultural and 

genetic manipulation (Zobel 1984), no information was collected about the genetics 

of this stand.

Sample collection – stump to cross-section 

In January 2011, four recently harvested stumps from different sprout clumps 

were selected for study. Five centimeter thick cross section samples were taken from 

the entire top of each stump at stump heights ranging from 20 cm to 68 cm above the 

ground (table 1). The sample trees were characterized as either “slow” or “fast” 

growing as defined by the amount of growth between rings. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

556

Table 1—Growth information on trees selected for use in this study.

Tree

number

Number

Of rings

detected

Growth rate

classification

Stump

height

Mm (in)

Diameter

mm (in)

Average

growth

(rings/mm)

2 72 Fast 685 (27) 775 (30.5) 10.7

6 74 Fast 225 (9) 940 (37) 12.7

3 88 Slow 335 (14) 520 (20.5) 5.9

4 100 Slow 200 (8) 445 (15.5 4.5

Sample processing – creating radial rectangular specimen 

The sections collected were delivered to the University of California Richmond 

Field Station for processing the samples into square rods approximately 18mm by 18 

mm by the radial (pith to bark) length of the sample. Two sets of side matched square 

rods were cut from each tree sample. One square rod specimen was used for the MFA 

analysis and one was reserved for use in a decay resistance test. After processing, all 

square rods were placed in a controlled environment room to dry. After equilibrating, 

one set of the square rods was shipped to FP Innovations, Paprican Division 

(Vancouver, British Columbia, Canada) for further processing and MFA analysis. 

The second set was shipped to Mississippi State University for additional analysis 

and testing to determine decay resistance. The specimens were further processed at 

Paprican, cutting the 18 x 18 mm square rods into rectangular sections that were 7 

mm in the longitudinal direction, 2 mm in the tangential direction, and the length 

from pith to bark in the radial direction. The MFA was then evaluated using a 

Silviscan instrument that utilizes x-ray densitometry, x-ray diffraction and image 

analysis to measure a range of wood properties (age, density, and the modulus of 

elasticity (MOE) that indicates stiffness).

Results and discussion

The relationship between growth ring and MFA is shown in fig.1. Elevated MFA 

was most evident in tree #5. In this case the MFA did not decrease with tree age as 

was the case with the other trees. Local increases in MFA were observed in trees # 6 

(around year 40), #2 (around year 30) and #3 (around years 50 and 80). Based on 

results from studies on southern yellow pine variation in MFA can be expected, but 

according to Megraw (1985), a negative relationship exists between MFA and tree 

age during the first 15 to 20 years, and at which time MFA remains relatively 

constant with increasing tree age. These localized increases in MFA could result from 

changes in growth rate during those periods. Trends in MFA that do not agree with 

published trends, such as those observed here, are possible with small sample sizes3

. 

As previously stated, the samples for this study were taken from the tree stumps and 

this sampling location may drive some of the observed relationships reported here, 

with higher MFA typically being observed at lower heights above the ground 

(Megraw 1985). Future research should incorporate a much larger sample size and 

include multiple samples from a given tree. 

The relationship between MFA and modulus of elasticity (MOE and a measure of 

stiffness) and MFA and density are given in figs. 2 and 3. In the Silviscan analysis, 

MOE is generated using a correlation developed with several species between MFA 

 

3 L. Schimleck, Professor, University of Georgia, personal communication, 2011. 
Using Wood Quality Measures to Evaluate Second-Growth Redwood

557

Figure 1—Microfibril angle as a function of growth ring in the four sampled trees 

characterized by their rate of growth.

Figure 2—The relationship between microfibril angle and modulus of elasticity in the 

four sampled trees characterized by their rate of growth.
GENERAL TECHNICAL REPORT PSW-GTR-238 

558

Figure 3—The relationship between microfibril angle and density in the four sampled 

trees characterized by their rate of growth.

and MOE. As such, it is unlikely that redwood samples were included in the 

development of the correlation. However, increasing MFA would result in between 

cellulosic unit hydrogen bonding to predominate during the tension test used to 

determine MOE. With lower MFA, the covalent ß (1-4) linked D glucose units that 

comprise the cellulose molecule would dominate. It is therefore reasonable to expect 

increasing MFA to result in lower MOE (in tension parallel to the grain). As seen in 

fig. 2, higher MFA resulted in lower MOE. Again, this was most clear with tree #6. 

The MFA in tree #2 was not consistently lower than the MFA in trees #3 and #4, but 

in tree #2 MOE is consistently lower than the MOE in trees #3 and #4. Based on the 

results of the SilviScan analysis, the average density of tree #2 was approximately 25 

percent lower than trees #3 and #4. Since strength is highly correlated with density 

(Bowyer et al. 2003), this difference in density can help explain the differences in 

MOE observed in trees #3 and #4 (“slow growth rate”) and #2 (“fast growth rate”), 

even though the MFAs were similar. This relationship is confirmed when viewing the 

relationship between MFA and density (fig. 3).Density (specific gravity) is one of the 

physical properties that will increase with age during the juvenile period (Bendsten 

1978). The density values for tree #6 ranged from near the minimum to maximum 

values observed for trees # 2, 3 and 4. Because of the consistently high MFA in tree # 

6, the predicted MOE is consistently lower than that for trees # 3 and 4.The overall 

lower density in tree #2 samples, and that corresponding effect on MOE, explains the 

relatively low MOE even though tree #2 MFA values are similar to the MFA values 

for trees #3 and #4. 

Summary and conclusions

Higher MFA was observed in the faster growth tree #6. The trend observed in 

tree #2 was similar to those observed in trees #3 and #4. Particularly with tree # 6, 
Using Wood Quality Measures to Evaluate Second-Growth Redwood

559

MFA did not decrease with age as would be expected. Inconsistent results can be 

expected when measurements are made on an individual tree at a single stem 

location. A future study would be greatly enhanced by considering genetics and a 

range of sample locations within the tree bole. However, except for places where 

redwood is grown in plantations, there will always be genetic diversity in managed 

redwood forests and silviculture techniques may be used to compensate for some 

genetic characteristics.

Decay resistance and extractive content are very more important factors 

regarding the effect of second-growth issues on the in-service durability of redwood. 

When these data are available it will help round out the results reported here. 

With this preliminary study, we have shown that when considering all 

measurements available with Silviscan, differences in faster growth and slower 

growth redwood could be discerned that may affect in-service performance of 

redwood lumber. These redwood samples followed the general trends observed in 

other conifer species where wood quality measurements have been investigated. 

References

Amarasekara, H.; Denne, M.P. 2002. Effects of crown size on wood characteristics of 

Corsican pine in relation to definitions of juvenile wood, crown formed wood and 

core wood. Forestry 75(1): 51-61.

Anderson, A.B. 1961. The influence of extractives on tree properties. 1. California 

redwood (Sequoia sempervirens).Journal of the Institute of Wood Science 8:14-34.

Bendsten, B.A. 1978. Properties of wood from improved and intensively managed trees.

Forest Products Journal 28(10):61-72.

Bowyer, J.L.;Shmulsky, R.; Haygreen, J.G. 2003. Forest products and wood science: an 

introduction. Fourth edition. Ames, IA:Iowa State Press.554 p.

Clark, J.W.; Scheffer, T.C.1983.Natural decay resistance of the heartwood of coast 

redwood Sequoia sempervirens (D.Don) Endl.Forest Products Journal. 33(5):15-20. 

Dinwoodie, J.M. 1981. Timber: its nature and behaviour. New York:Van Nostrand 

Reinhold. 190 p. 

Forest Products Laboratory. 1999. Wood handbook—wood as an engineering 

material.Gen. Tech. Rep. FPL-GTR-113. Madison, WI: U.S. Department of 

Agriculture, Forest Service, Forest Products Laboratory.508 p.

Megraw, R.A. 1985. Wood quality factors in loblolly pine: the influence of tree age, 

position in tree and cultural practice on wood specific gravity, fiber length, and 

fibril angle. Atlanta, GA: Tappi Press.88 p.

Meylan, B.A. 1968. Cause of high longitudinal shrinkage in wood. Forest Products Journal. 

18(4):75-78.

Nault, J.R. 1989.Longitudinal shrinkage, Chapter 3. In: Kellogg, R.M., editor. Second 

growth Douglas-Fir: its management and conversion for value. Special Publication 

No.SP-32.Vancouver, BC: Forintek Canada Corporation.173 p.

Wilcox W.W.; Piirto, D.D. 1976.Decay resistance in redwood (Sequoia sempervirens) 

heartwood as related to color and extractives. Wood and Fiber 7(4):240-245.

Zobel, B. 1984.The changing quality of the world wood supply. Wood Science and 

Technology 18(1):1-17.

561

Forest Restoration at Redwood National 

Park: a Case Study of an Emerging Program

Jason R. Teraoka1

Abstract

For more than 30 years, Redwood National Park has been working to establish a Forest 

Restoration Program to rehabilitate its impaired, second-growth forests. This case study 

outlines the Park’s history of using silviculture as a restoration tool, which began in 1978 after 

the Park’s expansion. The most recent effort was the 1,700 acre South Fork of Lost Man 

Creek Forest Restoration Project where two silvicultural prescriptions were used. Low 

thinning on ridge-top sites reduced basal area by 40-percent, and wood generated was sold as 

forest products. Crown thinning on steep mid-slope sites reduced basal area by 25-percent, 

and the wood was lopped-and-scattered. Permanent plots were established before thinning and

were re-assessed after thinning. Data were analyzed to determine whether the silvicultural 

prescriptions altered stand structure and species composition to promote redwood dominance. 

Before thinning, Douglas-fir dominated stand density. Both prescriptions shifted composition 

in favor of redwood. The ridge-top prescription resulted in 191.3 percent more redwood 

trees/acre than Douglas-fir, and 80.2 percent more redwood basal area, making redwood the 

dominant species. The mid-slope prescription resulted in 4.3 percent more redwood trees/acre 

than Douglas-fir, but Douglas-fir had 5.9 percent more basal area. This project is the Park’s 

first successful attempt at large-scale forest restoration.

Key words: crown thinning, low thinning, monitoring restoration, redwood, silviculture

Introduction

Today over 50,000 acres of second-growth forests occur within Redwood 

National Park. These forests have developed into dense stands characterized by 

deficient redwood (Sequoia sempervirens [Lamb. ex D. Don] Endl.) composition, 

low tree vigor, homogeneous structure, and little bio-diversity (Chittick and Keyes 

2007, Teraoka and Keyes 2011). This case study outlines the Park’s 30 year history 

of forest restoration planning and how the history culminated in the South Fork of 

Lost Man Creek Forest Restoration Project.

Redwood National Park was created in 1968 to preserve intact, old-growth 

redwood ecosystems. Under the Redwood National Park Expansion Act of 1978, 

48,000 acres were added to protect the Park from encroaching logging activities. The 

expansion included 38,000 acres that had been logged, so the new law mandated a 

program of rehabilitation to restore these lands. This marked the beginning of the 

Park’s forest restoration planning efforts. 

In 1978, the Park established a 200 acre experimental thinning referred to as the 

Holter Ridge Thinning Study. The area had been clearcut in 1954, was dominated by 

Douglas-fir (Pseudotsuga menziesii [Mirb.] Franco), and averaged 1,000 trees/acre 

24 years after clearcutting (Chittick and Keyes 2007). A low thinning had been 

 

1 Vegetation Management, Redwood National Park, Orick, CA 95555. (Jason_Teraoka@nps.gov). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

562

conducted to determine its effects on tree growth, forest composition, and understory 

vegetation (Chittick and Keyes 2007). This marked the first time that trees were cut 

down at Redwood National Park as a restoration effort. National Park Service 

executives, however, disagreed with the notion that thinning could be used as a 

restoration tool; others expressed frustration that the Park was cutting down trees on 

land removed from timber production. Finally, a moratorium on thinning secondgrowth forests in the Park was established in 1979, and the Park’s first attempt at 

forest restoration came to an end. 

In the 1990s, the listing of the northern spotted owl (Stix occidentalis caurina 

[Merriam]) as a threatened species made forest management on public lands a 

contentious issue and led to the development of the Northwest Forest Plan. Research 

began on ecosystem management practices that could maintain timber production 

while protecting, and creating, spotted owl habitat. Redwood National Park used this 

shift in paradigms to revive forest restoration planning, which resulted in a 40 acre 

experimental thinning in 1995 referred to as the Whiskey 40 Thinning Study. The 

area had been clearcut in 1962 and averaged 2,200 trees/acre 33 years after 

clearcutting. The thinning had been conducted in part to promote redwood 

composition (Stuart and Cussins 1994) and to demonstrate potential management for 

a larger forest restoration program. 

A funding opportunity to support forest restoration came about when a 

neighboring timber company planned to log over 500 acres of old-growth stands that 

were acquired as a land swap connected to the creation of Redwood National Park. 

Because the marbled murrelet (Brachyramphus marmoratus [Gmelin]) was a newly 

listed threatened species, the timber company proposed to mitigate their logging by 

providing the Park $1.7 million for thinning. The Park quickly drafted a forest 

restoration plan (United States 1996) and it was distributed for public review in 1996. 

A local environmental group responded with a legal challenge, arguing the plan 

lacked cumulative effects analysis on marbled murrelets from the timber company’s 

proposed logging and failed to state where the Park planned to thin. The Park’s plan 

could not be approved and the mitigation dollars were not accepted; thus, the Forest 

Restoration Program was once again put on hold. 

This unsuccessful planning effort, however, increased public awareness of the 

Park’s impaired forests and increased public support for forest restoration. In 1999, 

the Park’s General Management Plan (United States 1999) was approved, and 

provided the compliance needed to revive the Forest Restoration Program. To build 

momentum for the program, a park-wide forest inventory was conducted to describe 

the range of resource conditions and to use the data to prioritize areas for treatment. 

In addition, the Whiskey 40 Study was revisited in 2002 and the Holter Ridge Study 

was revisited in 2003 to aid managers in prescribing future silvicultural practices for 

restoring forests. The results from both studies were similar in that they both showed 

that residual trees responded well, there was a significant increase in biodiversity, 

and the overstory composition was unaffected as Douglas-fir continued to dominate 

because thinning intensities were too conservative or too much redwood was 

removed (Chittick and Keyes 2007, Teraoka and Keyes 2011).

Based on the assessment of the Park’s second-growth forests, the South Fork of 

Lost Man Creek drainage was chosen as the first major forest restoration project 

(United States 2009). Planning began in 2004 and the plan was approved in 2009. 

The plan’s objectives were in part to reduce stand density to promote redwood 
Forest Restoration at Redwood National Park: a Case Study of an Emerging Program

563

composition, initiate understory vegetation, and promote vigorous tree growth. To 

address logistic, economic, and regulatory constraints, five silvicultural prescriptions 

were used; the two most prominent prescriptions are discussed in this case study. 

Regardless of prescription, Douglas-fir was primarily targeted for removal. On ridgetops, where slopes were less than 30 percent, low thinning was used to reduce the 

stand basal area by 40 percent, and the Park sold the merchantable timber, a 

byproduct of the restoration, to the contractor that conducted the restoration work. 

Non-merchantable wood was sent to a cogeneration power plant. On mid-slope sites, 

where slopes exceeded 30 percent, crown thinning reduced the stand basal area by no 

more than 25 percent, and felled trees were lopped-and-scattered. Crown thinning 

removes trees in the dominant and co-dominant crown classes to benefit trees of the 

same crown classes. This method was used on mid-slope sites to benefit redwood and 

reduce stand density while only cutting a few trees. Since logs were not extracted 

from mid-slope sites, the accumulation of cut wood was a major constraint.

Methods

For this analysis, a subset of preliminary data was used from the project’s 

monitoring effort, which began in 2009. Data collected after thinning were analyzed 

to determine whether the two prescriptions immediately altered stand structure and 

species composition to promote redwood dominance. 

The South Fork of Lost Man Creek Project comprises 1,700 acres. Most of the 

area was clearcut in 1954; the rest was clearcut in 1962. The latitude/longitude is

N41o

 17 W123o 58. Elevation ranges from 800 ft to 2,200 ft, and annual precipitation 

averages 65 inches. 

Species and diameter at breast height (dbh) of live trees larger than 10.5 inches 

dbh were recorded in six 3/5-acre square plots. A 1/40-acre square subplot was 

nested at each corner of the 3/5-acre plot (four subplots per 3/5-acre plot). In the 

1/40-acre subplots, the same data were recorded for trees 4.5 to 10.5 inches dbh. 

Plots were re-inventoried immediately after thinning. Three plots represented the

thinning at the ridge-top site and averaged 15 percent slope. Three plots represented 

the thinning at the mid-slope site, and averaged 50 percent slope. Both sites were on 

northwest-facing aspects and were adjacent to each other. Means and standard 

deviations for stand density (trees/acre, basal area/acre) and quadratic mean diameter 

(QMD) were calculated for both inventory phases. Diameter distributions were 

plotted for both inventory phases. Data for western hemlock (Tsuga heterophylla

[Raf.] Sarg.) and grand fir (Abies grandis [Dougl. ex D. Don] Lindl.) were grouped 

and named “Other” species. 

Results

Thinning on ridge-top site 

Prior to treatment, the ridge-top site’s stand density consisted of 566.1 trees/acre 

and 366.7 ft2

/acre basal area (table 1). The majority of the stand consisted of three 

species: Douglas-fir, redwood, and tanoak (Lithocarpus densiflorus [Hook. & Arn.] 

Rehder). Before thinning, redwood and Douglas-fir had similar average diameters, 

both larger than tanoak. Douglas-fir dominated stand density in terms of trees/acre 
GENERAL TECHNICAL REPORT PSW-GTR-238 

564

and basal area. However, redwood dominated the 22 inch diameter classes and 

greater (fig. 1, top). The thinning reduced stand basal area by 38.4 percent (the target 

reduction was 40 percent), reduced the number of trees by 46.7 percent and increased 

stand QMD by 6.3 percent, demonstrating the thinning was successfully implemented 

as designed (table 1). All removals were in the 4 to 20 inch diameter classes (fig. 1,

bottom), with a QMD of 9.9 inches for all removed trees.

Table 1—Stand conditions before and after thinning at the ridge-top site expressed in 

number of live trees/acre, basal area (ft2

/acre), species composition (%), and quadratic mean 

diameter (QMD, inches) for redwood, Douglas-fir, tanoak, and other species.

Trees/acre Basal Area (ft2/acre) QMD 

(inches

) Mean SD % Mean SD % 

Before Thinning

Redwood 167.2 55.4 29.5 132.5 18.7 36.1 13.9

Douglas-fir 221.1 80.0 39.1 185.9 31.8 50.7 14.0

Tanoak 177.2 134.8 31.3 47.3 38.2 12.9 7.6

Other 0.6 1.0 0.1 1.0 1.7 0.3 17.9

Total 566.1 69.9 - 366.7 14.3 - 11.2

After Thinning

Redwood 150.6 50.4 49.9 125.6 16.2 55.6 14.6

Douglas-fir 51.7 24.2 17.1 69.7 21.2 30.8 18.9

Tanoak 98.9 74.4 32.8 29.6 27.4 13.1 8.0

Other 0.6 1.0 0.2 1.0 1.7 0.4 17.9

Total 301.7 46.4 - 225.9 19.3 - 11.9

The thinning increased redwood composition relative to Douglas-fir (table 1). 

Prior to thinning, there were 32.2 percent more Douglas-fir than redwood and 

Douglas-fir had 40.3 percent more basal area than redwood. Immediately after 

thinning, there were 191.3 percent more redwood than Douglas-fir and redwood had 

80.2 percent more basal area than Douglas-fir. 

Stand QMD increased by 6.3 percent after thinning. This small boost in stand 

QMD was associated with leaving redwood virtually uncut and retaining 

approximately half of all the tanoaks in the smallest diameter classes (fig. 1). 

Douglas-fir represented 64.1 percent of the total number of trees removed and 82.5 

percent of the total basal area removed. The removals concentrated on smaller 

diameter Douglas-fir (fig. 1); thus, its increase in QMD was 35.0 percent (from 14.0 

to 18.9 inches), while redwood and tanoak QMD increased by 5.0 percent and 5.3 

percent, respectively. 
Forest Restoration at Redwood National Park: a Case Study of an Emerging Program

565

Figure 1—Diameter distributions at the ridge-top site stacked by species immediately 

before thinning (top) and after thinning (bottom).

Thinning on mid-slope site 

Prior to treatment, the mid-slope site’s stand density consisted of 391.7 trees/acre 

and 364.3 ft2

/acre basal area (table 2). The majority of the stand consisted of two 

species, Douglas-fir and redwood. Tanoak occurred in the stand, but was a minor 

component. Before thinning, redwood and Douglas-fir had similar average diameters. 

Although Douglas-fir and redwood had similar compositions, Douglas-fir represented 

most of the stand density in terms of trees/acre and basal area. However, redwood 

dominated the 20 inch diameter class and greater (fig. 2, top). The thinning reduced 

stand basal area by 11.0 percent (the target reduction could not exceed 25 percent), 

reduced the number of trees by 14.0 percent and had virtually no effect on stand 

QMD. The thinning was successfully implemented as designed; however, the 

reduction in basal area was low. All removals were in the 4 to 18-inch diameter 

classes (fig. 2, bottom), with a QMD of 11.5 inches for all removed trees, and 

concentrated on Douglas-fir. Douglas-fir represented 68.7 percent of the total 

trees/acre removed and 87.9 percent of the basal area removed.

The thinning had minor effects on redwood composition relative to Douglas-fir

(table 2). The thinning virtually inverted the proportions of Douglas-fir to redwood in 

terms of number of trees, but failed to do so in terms of basal area, although it 

brought balance to the overall basal area composition. Prior to thinning, there were 

11.4 percent more Douglas-fir than redwood, and Douglas-fir had 27.2 percent more 

basal area than redwood. Immediately after thinning, there were 4.3 percent more 

redwood than Douglas-fir, but Douglas-fir had 5.9 percent more basal area than 

redwood, which was an improvement to the pre-thinning condition. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

566 

Table 2—Stand conditions before and after thinning at the mid-slope site expressed in 

number of live trees/acre, basal area (ft2

/acre), species composition (%), and quadratic mean 

diameter (QMD, inches) for redwood, Douglas-fir, tanoak, and other species.

Trees/acre Basal Area (ft2/acre) QMD 

(inches

) Mean SD % Mean SD % 

Before Thinning

Redwood 160.6 34.3 41.0 148.0 51.2 40.6 13.0

Douglas-fir 178.9 41.4 45.7 188.3 16.5 51.7 13.9

Tanoak 36.1 42.8 9.2 9.0 9.4 2.5 6.8

Other 16.1 10.0 4.1 18.9 4.2 5.2 14.7

Total 391.7 43.1 - 364.3 50.2 - 13.1

After Thinning

Redwood 147.2 34.7 43.7 145.0 55.0 44.6 13.4

Douglas-fir 141.1 46.0 41.9 153.5 27.9 47.3 14.1

Tanoak 32.8 37.3 9.7 8.4 8.6 2.6 6.9

Other 15.6 9.2 4.6 17.8 5.5 5.5 14.5

Total 336.7 20.5 - 324.7 63.8 - 13.3

Figure 2—Diameter distributions at the mid-slope site stacked by species 

immediately before thinning (top) and after thinning (bottom).

Discussion

More than 30 years after the first attempt at establishing a Forest Restoration 

Program at Redwood National Park, regulatory agencies, the environmental 

community, and conservation organizations have embraced the idea that thinning 

young forests can improve ecosystem values. The effects of restoration thinning have 

been documented throughout the Pacific Northwest (Carey 2003, O’Hara and Waring 

2005). Interest in the restoration of young-growth redwood forests has grown in part 
Forest Restoration at Redwood National Park: a Case Study of an Emerging Program

567

because the range of old-growth forest continues to decline (Evarts and Popper 

2001), fragmented old-growth redwood stands have been deemed inadequate as 

reserves leading to increased landscape-scale efforts to connect these fragmented oldgrowth stands (Noss et al. 2000, Porter et al. 2007), and young forests in reserves 

exhibit declines in vigor and redwood dominance. 

Teraoka and Keyes (2011) found that applying low thinning that targets all 

species for removal can result in a reduction of redwood composition relative to 

Douglas-fir and an intense low thinning targeting Douglas-fir could better achieve 

restoration objectives. This issue was addressed in the current case study. At the 

ridge-top site, the objectives of immediately altering stand density conditions while 

enhancing redwood dominance was successful because it was intense enough to 

immediately make redwood dominant. Although redwood dominated the largest size 

classes after thinning, the largest Douglas-firs were retained and Douglas-fir had the 

largest increase in QMD. This suggests that a gain in Douglas-fir’s competitive 

potential in the upper canopy classes may occur during subsequent stand 

development, but this remains to be determined. 

At the mid-slope site, the objective of immediately altering stand density 

conditions while enhancing redwood dominance was not fully met by low-intensity 

crown thinning; however, stand density conditions and redwood composition were 

improved. Results may have been more favorable if the basal area reduction was 

closer to 25 percent. The intent of this prescription was to remove fewer trees, while 

targeting Douglas-fir in the upper crown classes. Thus, a minor reduction in stand 

density could be achieved while releasing redwood in the upper crown classes. 

Regardless of the thinning intensity, all removals focused on redistributing growing 

space for redwood. Whether the thinning provided redwood with a more competitive 

position over the course of subsequent stand development remains to be determined.

The lop-and-scatter prescriptions were funded by the Centennial Challenge 

Initiative and the American Recovery and Reinvestment Act of 2009, which provided 

the Park $629,084 to thin 1,267 acres, a rate of $497/acre. In contrast, approximately 

2.5 million board-feet were removed from 226 acres of ridge-top sites and sold to the 

contractor, which resulted in the contractor paying the government $221/acre to 

perform the restoration work. This project has demonstrated that excess wood, a 

byproduct generated from the restoration work, could be sold to offset the cost of 

implementing the project without compromising restoration objectives.

The Park is planning its next forest restoration project, which calls for managing 

1,200 acres within the Lost Man Creek Drainage. In addition to traditional thinning 

methods, the Park proposes to implement variable density thinning, which has shown 

to be effective as a restoration tool in the redwood region (O’Hara et al. 2010, Keyes 

et al. 2010). In addition to ground-based equipment, the Park proposes to thin 

intensely on steeper slopes using cable yarding systems, which would allow the Park 

to remove excess biomass.

The challenge ahead for managers is to develop diverse silvicultural restoration 

treatments that are founded on the knowledge of forest dynamics in young stands and 

structural references from old-growth ecosystems, suit a variety of stand conditions, 

and are appropriate for an array of social and economic constraints. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

568

Acknowledgments

I thank Leonel Arguello and Scott Powell for their many contributions. I thank 

Emily Teraoka and Christopher Keyes for their reviews of the manuscript.

References

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forest: inducing spatial heterogeneity with variable-density thinning. Forestry 

76(2):127-136.

Chittick, A.J.; Keyes, C.R. 2007. Holter Ridge thinning study, Redwood National Park: 

preliminary results of a 25-year retrospective. In: Standiford, R.B.; Giusti, G.A.; 

Valachovic, Y.; Zielinski, W.J., Furniss, M.J., technical coordinators. Proceedings of the 

redwood science symposium: what does the future hold? Gen. Tech. Rep. PSW-GTR194. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest 

Research Station, Forest Service: 271-280.

Evarts, J.; Popper, M. 2001. Coast redwood: a natural and cultural history. Los Olivos, 

CA: Cachuma Press. 228 p.

Keyes, C.R.; Perry, T.E.; Plummer, J.F. 2010. Variable-density thinning for parks and 

reserves: An experimental case study at Humboldt Redwoods State Park, 

California. In: Jain, T.B.; Graham, R.T.; Sandquist, J., technical editors. Proceedings of 

the 2009 national silviculture workshop. RMRS-P-61. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain Research Station: 227-237.

Noss, R.F.; Strittholt, J.R.; Heilman, G.E., Jr.; Frost, P.A.; Sorensen, M. 2000. Conservation 

planning in the redwood region. In: Noss, R.F., editor. The Redwood forest: history, 

ecology, and conservation of the coast redwoods. Washington, DC: Island Press: 201-

228.

O’Hara, K.L.; Waring, K.M. 2005. Forest restoration practices in the Pacific Northwest 

and California. In: Stanturf; J.A.; Madsen P., editors. Restoration of boreal and 

temperate forests. Boca, Florida: CRC Press: 445-461.

O’ Hara, K.L.; Nesmith, J.C.B.; Leonard, L.; Porter, D.J. 2010. Restoration of old forest 

features in coast redwood forests using early-stage variable-density thinning.

Restoration Ecology 18(S1): 125–135.

Porter, D.; Gizinski, V.; Hartley, R.; Kramer, S.H. 2007. Restoring complexity to 

industrially managed timberlands: the Mill Creek interim management 

recommendations and early restoration thinning treatments. In: Standiford, R.B.; 

Giusti, G.A.; Valachovic, Y.; Zielinski, W.J., Furniss, M.J., technical coordinators.

Proceedings of the redwood science symposium: What does the future hold? Gen. Tech. 

Rep. PSW-GTR-194. Albany, CA: U.S. Department of Agriculture, Forest Service, 

Pacific Southwest Research Station: 283-294.

Stuart, J.D; Cussins, D. 1994. Restoration of a 32-year-old stand to an old-growth-like 

condition in Redwood National Park. In: Proceedings of the 1994 Society of 

American Foresters/Canadian Institute of Forestry convention. Bethesda, MD: Society 

of American Foresters: 509-510.

Teraoka, J.R.; Keyes, C.R. 2011. Field note: low thinning as a forest restoration tool at 

Redwood National Park. Western Journal of Applied Forestry 26: 91-93.

United States Department of the Interior, Redwood National and State Parks. 1996. Secondgrowth forest recovery plan and environmental assessment-draft. Report of file at 

South Operations Center of Redwood National Park, Orick, CA. 89 p.
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Redwood National and State Parks. 103 p.

571

Whiskey Springs Long-Term Coast

Redwood Density Management; Final 

Growth, Sprout, and Yield Results 

Lynn A. Webb,

1 James L. Lindquist,2 Erik Wahl,1 and Andrew 

Hubbs3 

Abstract

Multi-decadal studies of commercial and precommercial thinning in redwood stands are rare 

and consequently of value. The Whiskey Springs study at Jackson Demonstration State Forest 

has a data set spanning 35 years. In addition to growth and yield response to commercial 

thinning, the results provide important information for evaluating regeneration and alternative 

silviculture treatments. 

In 1970, the original treatment thinned a 40 year-old redwood forest from below to densities 

representing 25, 50, and 75 percent of the initial basal area (approximately 400 ft2

/ac). Three 

0.2-ac plot replicates within each of the four density levels were assigned in a randomized 

design. In the 35 years after thinning, the basal area of the 25, 50, 75 and 100 (control)

percent retention areas increased by 168, 232, 226 and 210 ft2/ac of basal area respectively. 

There was some indication that mean annual increment (ft3

/ac) had culminated at age 70 years 

for some treatments. 

Redwood sprouts and other conifer seedlings were abundant in the 25 and 50 percent 

retention areas. Precommercial thinning subplots were established within these two treatments 

in 1986, reducing the understory to 200, 300, and 400 sprouts/ac. The understory diameters 

ranged from 2 to 6 inches at DBH for the 25 percent retention 35 years after the commercial 

thinning. 

Key words: Sequoia sempervirens, coast redwood, commercial thinning, precommercial 

thinning, regeneration, sprouting

Introduction

This report provides the final measurements for what began as the Whiskey 

Springs Redwood Commercial Thinning Study. It was established by the USDA 

Forest Service and the California Department of Forestry and Fire Protection staff in 

1970 on Jackson Demonstration State Forest (JDSF) in 1970 near Fort Bragg, 

California. This study spans 35 years after thinning of a 40 year-old, well stocked 

second growth stand. The original experimental design included three sites located in 

the redwood region. Oliver et al. (1994) reported the first 15 years of growth (1971 

to1985) for all three sites. James Lindquist has summarized periodic remeasurement 

 

1 Forester, California Department of Forestry and Fire Protection Jackson Demonstration State Forest, 

802 North Main St., Fort Bragg, CA 95437. (lynn.webb@fire.ca.gov, eric.wahl@fire.ca.gov). 2 Retired Researcher, Arcata, CA. 3 Forester, California Department of Forestry and Fire Protection, San Luis Obispo Unit, 

(andrew.hubbs@fire.ca.gov). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

572

data at JDSF (1988, 2004). The now 75 year-old stand has literally outgrown the 

study design and has transitioned into an educational demonstration site.

The study was designed to test treatments to help realize the productive potential 

of young redwood forests. The original study plan called for a final harvest at 70 

years of age based on the projected culmination of the mean annual increment on a 

cubic foot volume basis for a 100-year site index of 180 ft. 

Vigorous coast redwood (Sequoia sempervirens [D.Don] Endl.) sprouting 

occurred after the commercial thinning. A secondary regeneration focused study was 

established to examine this sprouting. The understory sprouts were precommercially

thinned to a range of densities. Natural regeneration and redwood sprout growth were 

measured periodically beneath the thinned overstory. 

The objective of the experiment was to test a range of commercial thinning 

intensities for the purpose of comparing total yield. The experiments’ growth and 

yield data aids in planning silvicultural prescriptions in redwood to achieve 

maximum board foot volume production or other attributes such as target tree size. 

This data provided stand structure information to help inform decision-making 

regarding multiple goals in redwood forest management. The sprout response 

provided information for transitioning from even to multi-aged stand management. 

This paper will provide a focused update on the final 35 year results and explore 

total yield and some density attributes. This long term experiment will be discussed 

in more detail in a California Forestry Report under preparation. 

Methods

Site 

The Whiskey Springs study was located approximately 9 miles from the Pacific 

coast, in redwood forest. There was an east to northeast aspect and an elevation range 

from 600 to 900 ft. The old-growth stand was clear-cut in the late 1920s. Natural 

regeneration of a nearly pure stand of redwood sprouts followed. There was evidence 

as well as records (Caspar Lumber Co.) that the area was planted with redwood 

seedlings around 1929. Breast-height age of redwood ranged from 39 to 41 years in 

1970. Site index ranged from 172 to 212 ft, using 100 years as the base age 

(Lindquist and Palley 1963). The pretreatment basal area of trees greater than 4.5 

inches in diameter at breast height (DBH) was 401.3 ft2 per ac. The pre treatment

species composition of trees by basal area was 91.8 percent redwood, 7.6 percent 

other conifers (Douglas–fir, Pseudotsuga menziesii [Mirbel]-Franco); grand fir, Abies 

grandis [Douglas] Lindley) and the remainder tanoak (Lithocarpus densiflorus [Hook 

&Arn.] Rehder). 

Design 

The main study established 12, 0.4-ac treatment blocks (132 x 132 ft). 

Measurement plots were established in a central 0.2-ac (93.3 x 93.3 ft.) section of 

each block. The blocks were located so that inter-plot basal area, site index, and 

species composition were as uniform as possible. Four thinning treatments were 

assigned to 12 blocks in a randomized design (Lindquist 1988). Figure 1 shows the

layout of the main study plots. 
Whiskey Springs Long-Term Coast Redwood Density Management; Final Growth, Sprout, and Yield 

Results

573

Commercial thinning in 1970 reduced basal area to approximately 100 ft2

/ac (25 

percent retention), 200 ft2

/ac (50 percent retention), 300 ft2/ac (75 percent retention), 

and retained an untreated control of 400 ft2

/ac. 

Selection of leave trees was implemented to favor healthy dominant and 

codominant redwoods while leaving trees well distributed on the plot. Hardwoods 

and any conifers less than 4.5 inches DBH were removed. All trees were permanently 

tagged. After treatment in 1970 a total of seven plot measurements were conducted at 

approximately 5 year intervals ending in 2005. 

Monitoring the effects of redwood sprouting under the four different treatment

levels began in 1972. The secondary precommercial thinning study was implemented 

in 1986 in the 25 percent and 50 percent retention plots. The secondary study design 

divided treatment blocks into 1/10 ac quadrants. Each quadrant was randomly 

assigned to an understory regeneration stocking level of 100, 200, or 300 trees per ac

and an untreated control. Leave trees for the precommercial thin were based on 

diameter and height, but desirable spatial distribution was also a goal (Lindquist

1988). All of the leave trees were tagged then diameters and heights were measured. 

Subsequent periodic measurements of the thinned understory occurred in 1991, 1999, 

and 2007. 

Data analysis

Data was summarized for each of the seven measurement dates. It was evaluated 

by the statistical functions in Microsoft Excel 2007. Two way ANOVA tests were 

Figure 1—Plot locations at study site on topographic map and vicinity map for 

Whiskey Springs. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

574

conducted for treatment averages though the 35 year study period. For some 

attributes, one way ANOVA with replicates were conducted for the 2005 data. 

New redwood site index equations have been developed with a base age closer to 

the stand age (50 vs.100 year) since the study was established. Krumland and Eng 

(2005) site was calculated using individual tree site values though the 35 year span 

for base age 50. For each plot the five best sites were averaged. 

Because the stand structure became more complex as a result of the sprouting, 

SDI was calculated using the summation method (Tappeiner et al. 2007): SDI= Σ( Di

/10)1.0605. Understory diameters were adjusted to the measure date for overstory 

(2005). 

At the beginning of the study, a limited number of trees were measured for 

heights. Lindquist (2004) described the method used to estimate heights for all trees. 

Over the 35 year study period, methods for computing volume have advanced. For 

this final measurement a new computation method was used. To establish height for 

all other trees, a nonlinear regression model (R Development Core Team, version 

2.2.0, 2006) was used to develop equations based on all the measured trees (by 

species) for each measure year. Equations used to calculate cubic and board foot tree 

volumes were developed by the Redwood Yield Cooperative (Wensel et al. 1987) 

and locally calibrated with the JDSF fall-and-buck study (Griffen 1986). Board foot 

volumes were computed by the Scribner log rule using a one-foot stump height and a 

top diameter of 6 inches. 

Because prior reports indicated between treatments cubic foot volume growth 

increments were similar (Lindquist 2004), and date of measurement varied during the 

study period; seasonal growth adjustments were made to diameters. Data from JDSF

(Bawcom et al. 1961) was used to adjust diameters to a common measure date.

Results 

Site quality 

The treatment-wide averages for site index (Krumland and Eng 2005) 

were 140 ft for 25 percent retention, 133 ft for 50 percent retention, 139 ft for 

75 percent retention, and 124 ft for the untreated control using 50 year base 

age. Small watercourses are found in about half the treatment blocks, but none 

in the control blocks. The average site index for plots by treatments indicated 

the site quality of the treatment plots were not significantly different in terms 

of site index (P = 0.370). 

Mortality 

During the study period, the untreated plots exhibited the highest mortality 

of 50 to 75 year old trees. The number of trees per ac (greater than 4.5 inches 

DBH) declined steadily after the first decade to 133 trees per ac or 21 percent 

less than the initial measurement. The 75 percent retention experienced 

limited mortality starting in 1985, totaling six trees per ac or about three 

percent of the initial measurement. No mortality was observed for overstory trees 

in the 25 and 50 percent retention plots. 
Whiskey Springs Long-Term Coast Redwood Density Management; Final Growth, Sprout, and Yield 

Results

575

Diameter

Heavier thinning from below (removing the smallest stems) resulted in larger 

average stem diameters as shown in fig. 2. Error bars of one standard deviation are 

graphed illustrating that 50 percent retention had the most variation between plots.

Quadratic mean diameter was significantly different between treatments through the 

35 year study period (P <.01). 

Basal area

The initial treatment basal area of trees greater than 4.5 inches in diameter are 

depicted in fig. 3. The treatment’s effect on total basal area per ac remained 

significant throughout the 35 year study period (P <.01). 

Figure 3—Basal area in square feet per ac by initial 

thinning density though the 35 year study period.

Figure 2—Mean tree diameter by treatment through 

time. Error bars represent one standard deviation. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

576

Volume 

The untreated controls continued to have the largest cubic foot volume 

through the study period. For cubic foot volume there were significant 

differences between treatments though the 35 year study period (P <.01). 

Mean annual increment 

A biological characteristic that is of management interest is the change in growth 

rate by treatment through time. Mean annual increment (MAI) is the average annual 

growth over the life of the stand. For cubic foot volume per ac MAI; there were 

significant differences by treatment (P <.01), but not through the 35 year study period 

(P = 0.0228).

One purpose of the initial study was to determine when mean annual cubic foot 

growth increment peaks. For all treatments except the control, the MAI for cubic foot 

growth per ac reached its highest value at stand age 70 (fig. 4). Vertical error bars of 

one standard error help illustrate variably between plots for a single treatment. The 

decline in MAI was less than one percent per year, so at this point the projected 

culmination of mean annual increment at age 70 was suggested but not definitive. 

 

Figure 5—Stand Density Index (SDI)

by treatment through time. The 25 

percent and 50 percent retention at 

age 75 includes regeneration.

Figure 4—Mean Annual Increment of 

cubic foot volume per year by thinning 

retention treatment. Vertical error bars 

indicate variability of data.
Whiskey Springs Long-Term Coast Redwood Density Management; Final Growth, Sprout, and Yield 

Results

577

In contrast with the MAI for cubic foot volume, the board foot volume MAI for 

the final measure interval continued to increase for all treatments over 35 years, but 

the increases were smaller than the standard errors between plots. The final MAI in 

board feet volume was 1,467 for 25 percent retention, 1,694 for 50 percent retention, 

1,704 for 75 percent retention and 1,528 for the unthinned control. For board foot 

volume MAI there were significant differences for both through the study period and 

by treatment (P < .01).

Total yield 

To address the original management question of effects of different 

commercial thinning intensities on total yield, both the commercial thinning 

yield at year 40 and the theoretical final harvest yield at year 75 were 

considered. At the Thirty-five years post-harvest, the highest yield was 

realized in the 50 percent treatment block (table 1).Total cumulative cubic foot 

volume per ac results differed slightly from board foot results. The highest two 

cumulative cubic foot volume per ac in thousands are for the 75 and 50 percent 

retention (25.0 and 24.6 respectively) with the control at 23.1 and 25 percent 

retention at 21.3. 

Table 1—Compilation of total yield at stand age 75 using thousand board feet volume (Mbf) 

per ac. Commercial thinning treatments retained a range of initial basal area (100 to 400 

ft2

/ac).

Treatment Age Thousand board ft/ac volume

Cut Standing Cumulative

25% 41 31 17 48

46 23 54

51 32 63

56 43 73

62 53 84

70 70 100

75 78 109

50% 41 17 31 48

46 40 57

51 51 68

56 64 81

62 79 96

70 100 117

75 111 128

75% 41 5 40 46

46 50 55

51 61 66

56 72 77

62 85 90

70 106 111

75 116 121

100% 41 0 39 39

46 49 49

51 60 60

56 73 73

62 87 87

70 105 105
GENERAL TECHNICAL REPORT PSW-GTR-238 

578

75 119 119

Stand density 

Stand Density Index (SDI) is a relative density measure that describes the level 

of inter–tree competition experienced by individual trees growing in a stand 

(Tappeiner and others 2007). The maximum theoretical SDI value for coast redwood 

is 1,000 (Reineke 1933) on an ac basis. The highest SDI value (887) was derived for 

the control in 2005 (fig. 5, above). The final SDI for 75 percent retention was 707. 

The final SDI for 25 and 50 percent retention treatments including regeneration were 

385 and 556 respectively. The understory comprised about 22 percent of the entire 

SDI for 25 percent retention and 4 percent for the 50 percent retention. 

Calculation of the SDI by the summation method provided lower values than 

those calculated in prior work (Lindquist 2004). Using the equation in prior studies; 

SDI= TPA (Dq/10)1.605 where Dq is the quadratic mean diameter the result is 917 

versus 887 for the control in 2005. 

Understory regeneration 

The redwood sprouting response after commercial thinning was inversely 

proportional to the overstory density. No sprouts were found in the un-thinned 

controls. The 75 percent retention plots had 5,130 redwood sprouts per ac in 1972. 

Twenty one years later these sprouts had diminished to the point that they did not 

merit further study (Lindquist 2004). The 25 and 50 percent retention plots had a 

similar number of sprouts initially (more than 10,000 sprouts/ac in 1972). 

The regeneration measured in 25 percent retention treatment had a larger 

diameter than in the 50 percent retention treatment at the end of the study period as 

shown in figures 6 and 7 (P <.01). Seedling in-growth tallied in 2007 had a higher 

proportion of western hemlock and grand fir than the first wave of regeneration in 

this study; 36 and 80 percent respectively in the 25 and 50 percent overstory retention 

treatments. After 35 years the 25 percent retention plots regeneration stems ( > 4.5 

inches DBH) was measured to be 451 cubic feet per ac. 

Figure 6 and 7—Growth of the redwood sprouts precommercially thinned to a 

range of densities within a commercially thinned to retain 100ft.

2

/ac of basal 

area per ac (fig. 6, left) or 200 ft.

2

/ac. (fig. 7, right). Note the diameter scale for 

the 50 percent retention on the right is twice as large as the 25 percent retention 

on the left.
Whiskey Springs Long-Term Coast Redwood Density Management; Final Growth, Sprout, and Yield 

Results

579

Discussion

As a result of the 35 year study period, each experimental treatment resulted in 

unique and quantifiable stand structures. The greatest mortality occurred in the 

control plots. Self thinning (onset of mortality) is expected to occur above an SDI of 

550 (Tappeiner et al. 2007). The control was above this density threshold for the 

entire study period. 

A substantial portion of the stems in the untreated control remained below the 

10.5 inch threshold for production of board feet, but above the 4.5 inch threshold for 

cubic foot volume. Volume results vary between treatments depending on which 

volume measurement attributes were used. 

The updated height estimation methodology resulted in slightly greater height 

estimates for the control trees than Lindquist’s prior methods (2004). Diameter/height 

relationships in the study area are influenced both by site quality (plot basis used by 

Lindquist) and stand age (this study). Though height data is limited for early 

measurements, further exploration of this data could clarify results. 

The 75 percent retention produced a total yield with slightly lower board foot 

volume than the 50 percent. The 75 percent retention consistently had the highest 

cubic foot MAI. Some sprouting was observed during the first decades after 

treatment, but the sprouts did not persist. O’Hara and Berrill (2010) noted complete 

sprout mortality at low light levels. The 75 percent retention surpassed the SDI 

threshold of 550 in 1980 and the first mortality was noted in 1985. 

The 50 percent retention had quadric mean diameter of 26 inches at the end of 

the study period. This density level may offer log value or aesthetic benefits when the 

final diameters are compared to other treatments. 

At the end of the study period the 35 year old stems under the 50 percent 

retention treatment averaged less than two inches in diameter. The SDI for this 

treatment exceeded the 550 threshold at the end of the 35 study period. Leaf area 

index is considered to be more integral to stand productivity and growing space 

occupancy than other measures (Berrill and O’Hara 2009). These authors conclude 

that removing a large fraction of the basal area such as this 50 percent treatment can 

promote a vigorous understory and high productivity. The observed slowing of 

understory diameter growth with time since treatment suggests that the reentry period 

is critical to maintaining understory vigor. 

The 25 percent retention provides about 85 percent of the highest board foot 

yield (table 1), and has a mean diameter of 33 inches with an established understory. 

The initial 40 year old even aged stand had an average diameter of slightly over 10 

inches in contrast to the now 35 year old regeneration with a treatment-wide average 

diameter of approximately four inches. This treatment does seem to provide a viable 

route to creating a multi-age stand if reentry periods are carefully planned. 

Conclusion

The first phase of the Whiskey Springs commercial thinning study has concluded 

in 2011 with a second thinning. The next phase will have a demonstration and 

education objective because the plot size and corresponding edge effects make future 
GENERAL TECHNICAL REPORT PSW-GTR-238 

580

experimentation problematic at this site. The trees are now twice as tall as they were 

35 years ago.

Long-term permanent plots in complex terrain present opportunities as well as 

challenges. An experimental site must provide adequate uniformity so that treatment 

effects are not confounded by site influences. Treatment buffers surrounding study 

plots need to be sufficient size to minimize edge effects. In addition, remeasurement 

must be continued over decades. The Whiskey Springs provided valuable research 

for the first 35 years. It confirms the importance of long-term studies and has 

provided insight beyond the original focus. A future California Forestry Note will 

include more details and additional analysis. The study area’s resulting stand will 

continue to tangibly illustrate density management tradeoffs. 

References

Berrill, J.P.; O’Hara, K.L. 2009. Simulating multiage coast redwood stand 

development: interactions between regeneration, structure, and productivity.

Western Journal of Applied Forestry 24(1): 24-32.

Bawcom, R.; Hubbell, R.; Burns, D. 1961. Seasonal diameter growth in trees on 

Jackson State Forest. State Forest Note, No. 6. Sacramento, CA: Calif. Dept. of 

Forestry and Fire Protection. 5 p. 

Griffen, J.R. 1986. Fall and buck study results: volume equations for Jackson State 

Forest. JDSF Newsletter 22. Sacramento, CA: Calif. Dept. of Forestry and Fire 

Protection. 3 p.

Krumland, B.; H. Eng, H. 2005. Site index systems for major young-growth forest 

and woodlands species in northern California. California Forestry Report No. 4. 

Sacramento, CA: Calif. Dept. of Forestry and Fire Protection. 219 p.

Lindquist, J.L. 2004. Growth & yield report for the Whiskey Springs redwood 

commercial thinning study. A twenty-nine year status report (1970-1999). Calif. 

Forestry Report No. 3. Sacramento, CA: Calif. Dept. of Forestry and Fire Protection.24 

p.

Lindquist, J.L. 1988. Commercial thinning at Whiskey Springs Jackson 

Demonstration State Forest. Calif. Dept. of Forestry and Fire Protection. Unpublished 

report. 23 p.

Lindquist, J. L.; Palley, M.N. 1963. Empirical yield tables for young-growth 

redwood. Bull. 796. Berkeley, CA: Univ. of California College of Agriculture, 

Agricultural. Exp. Station. 47 p.

O’Hara, K.L; Berrill, J.P. 2010. Dynamics of coast redwood sprout clump 

development in variable light environments. Journal of Forest Research 15: 131-139.

Oliver, W W.; Lindquist, J.; Strothmann, R. 1994. Young-growth redwood stands 

respond well to various thinning intensities. Western Journal of Applied Forestry 

9(4): 106-112 p.

Reineke, L.H. 1933. Perfecting a stand-density index for even-aged forests. Journal 

of Agricultural Research 46(7): 627-638. 

R Development Core Team. 2006. R Version 2.2.0. A language and environment for 

statistical computing. R foundation for statistical computing. www.R-project.org. 

Tappeiner, J.C.; Maguire, D.A.; Harrington, T.B. 2007. Silviculture and ecology of 

western U.S. forests. Corvallis, OR: Oregon State University Press. 440 p.
Whiskey Springs Long-Term Coast Redwood Density Management; Final Growth, Sprout, and Yield 

Results

581

Wensel, L.C.; Krumland, B.E.; Meerschaert, W.J. 1987. CRYPTOS user's guide: the 

Cooperative Redwood Yield Project Timber Output Simulator. Bull. 1924. 

Berkeley, CA: University of California Ag. Expt. Station, Division of Agriculture and 

Natural Resources. 89 p. 

Economics

585

Observations About the Effectiveness of 

Utilizing Single Tree Selection Silviculture 

in Redwood Forestlands 

Bob Berlage and the Big Creek Lumber Company Forestry 

Department Staff1 

Abstract 

Harvesting in predominantly redwood forests has been ongoing in the Santa Cruz Mountain 

region for over 150 years. Under California Forest Practice rules specific to the Southern 

Subdistrict of the Coast District, clearcutting has been outlawed since 1970. Since that time, 

single tree selection has been the only silvicultural practice allowed in the Southern 

Subdistrict. Big Creek Lumber Company has been practicing some form of selective 

harvesting throughout coastal redwood forestlands in the Santa Cruz Mountains since 1946. 

Sixty-five years of experience makes it is possible to form general observations about the 

effectiveness of this silvicultural practice within a redwood forest environment. Increasing 

population and urban sprawl have created pressures on redwood forestlands in California, and 

particularly on the Central Coast. Tensions resulting from population increases and ongoing 

urban encroachment into forestlands in the Santa Cruz Mountains have increased over time. 

This has created significant logistical and socio-political challenges for the local forest 

products industry. Not surprisingly, these challenges are now beginning to be seen elsewhere 

in the redwood region. Selection harvesting can provide positive benefits, particularly 

adjacent to densely populated areas. These benefits include providing local, sustainable 

products for local consumers, supporting working forestlands that provide a buffer against the 

pressures of land conversion and urban sprawl, as well as being a mechanism for maintaining 

complex redwood forest ecosystems.

Introduction

This paper is not intended to be a scientific analysis. Rather it is a case study and 

compilation of experiences gleaned from forest resource professionals over the past 

sixty years. Particular thanks go to Frank (Lud) McCrary, Homer T. (Bud) McCrary 

and Dale Holderman, Registered Professional Forester No. 69, for their perseverance 

in seeing the concept of single-tree selection forestry through to a successful outcome 

in the Santa Cruz Mountains.

Harvest history

The extraction of forest products in the Santa Cruz Mountains by European 

settlers undoubtedly commenced on their arrival. However, the first recorded 

commercial lumber ventures were those of Thomas Larkin and Jose’ Amesti during 

the year 1832, in what is now Santa Cruz County. These operations were very crude. 

Logs were placed straddling a pit and a worker above and below the log would run a 

whipsaw down the length of the log to create boards. Mechanical sawmilling began 

 

1 Bob Berlage, Big Creek Lumber Company, 3564 Highway 1, Davenport, CA 95017. (bobb@bigcreek.com).
GENERAL TECHNICAL REPORT PSW-GTR-238 

586

around 1841. The first mechanical mills used water power to drive the saws. During 

this time, draft animals (oxen and horses) were primarily used to transport logs to the 

mills from the forest and lumber to the end user. 

By the 1850s, steam began to replace water flow as the power source in many 

sawmills. Steam driven log yarders (steam donkeys) were used in woods operations 

starting in the latter 1880s. With the development of new technologies, the rate of 

harvest increased. Two seminal events contributed to increased forest resource 

extraction in the Santa Cruz Mountains. The first was the 1849 California gold rush. 

While few local forest products were actually delivered to the Sierra gold country, 

there was a tremendous demand in San Francisco, which had become the primary 

hub for materials and manpower destined for the gold fields. The second event that 

spurred forest resource production in the Santa Cruz Mountains was the 1906 San 

Francisco earthquake and fire, which destroyed many of the existing wood-frame 

structures. By 1897, there were 32 fully operational sawmills in Santa Cruz County 

alone. The procurement, production and transporting of forest products was the 

primary industry in Santa Cruz County from 1850 to 1925. 

Not all felled timber was turned into dimensional lumber. In fact, it is likely that 

more old-growth redwood was cut in the Santa Cruz Mountains to make “split stuff” 

(shakes, fence posts, railroad ties and grape stakes) than lumber. Hardwoods, logging 

debris and mill ends were used for fuel in heating, cooking and the generation of 

steam power. Tanoaks were felled and the bark transported to local tanneries. 

Clearcutting of the redwood/Douglas-fir conifer forests of the Santa Cruz Mountains 

continued more or less unabated until the mid-1920s. By 1930, most of the 

contiguous stands of old-growth timber had been cut or transferred to park land. 

Big Creek Lumber Company

Big Creek Timber Company was established in 1946. The Company’s first 

sawmill was located approximately 5 miles up Waddell Canyon on land that is now 

part of Big Basin State Park. This forestland had been previously harvested by 

William Waddell from the mid-1860s until 1872. In 1946 this forestland was 

comprised of some residual old-growth and robust stands of small second-growth 

redwood and Douglas-fir ranging from 70 to 80 years old. 

State regulations at that time required that four “seed trees” per acre, 18 inches in 

diameter or larger, be retained. All other trees could legally be cut. However, Big 

Creek Lumber decided to not cut that heavily and instead selectively harvested some 

of the residual old-growth trees and some of the larger second-growth. Trees that 

were too small to be economically profitable and trees that were too large for the 

sawmill were left uncut. The company continued sawmill operations in Waddell 

Canyon until 1955 when Waddell Creek experienced a significant flood. The 

company moved its sawmilling operation to the west side of California Highway 1, 

near its present location. The company became incorporated in 1960 and the name 

was changed to Big Creek Lumber Company. After 1955, Big Creek Lumber began 

to concentrate on harvesting second growth timber. 
Observations About the Effectiveness of Utilizing Single Tree Selection Silviculture in Redwood 

Forestlands 

587

Development of single tree selection silviculture in the 

Santa Cruz Mountains

The development of selection harvesting in the Santa Cruz Mountains was more 

a gradual transitional awareness than it was a singularly planned outcome. Big Creek 

Lumber Company concluded that the kind of forest management practiced on the 

North Coast of California at that time would not be acceptable to the local public. 

Urban development had slowly encroached into Santa Cruz Mountains forestlands 

and by 1946 there were few potentially harvestable forested parcels that did not have 

some degree of residential influence. From an aesthetic perspective, an acre with only 

four seed trees was not significantly different than a total clearcut. It made sense to 

consider a harvesting strategy that reflected local attitudes and concerns.

From Big Creek Lumber Company’s perspective there was also a practical 

business consideration in its approach to forest management. The composition of 

redwood forestland in the Santa Cruz Mountains was considerably different in 1946 

than prior to 1925. While there was no legal prohibition against harvesting oldgrowth, most of the larger contiguous stands of old-growth had been cut by 1946. 

Most harvesting at this time involved cutting scattered residual old-growth and was 

conducted on a smaller scale than the turn of the century operations. At that time 

there were far more acres of young second-growth. It became clear that the secondgrowth constituted a larger and rapidly growing resource base. However, given the 

improvements in logging equipment, it was also evident that harvesting these secondgrowth lands under the existing regulatory standard of retaining four trees per acre 

would have resulted in the depletion of the resource within several decades. 

Harvesting at more conservative levels not only addressed neighborhood concerns, it 

also insured a sustainable resource.

Absent any regulatory mandate, local timber operators voluntarily formed the 

Central Coast Timber Operators Association in July 1956. The purpose of this 

organization was to create a mutually agreeable set of logging standards beyond what 

state and local regulations required. The impetus for these self-imposed voluntary 

standards was the increasing public concern over logging operations and their 

potential affect on streams, roads and particularly drinking water. At that time there

were a few careless logging operators whose lack of consideration for these 

legitimate public concerns resulted in increasing conflict between neighbors and 

timber harvesting. On August 14, 1956, the Central Coast Timber Operators 

Association adopted self-imposed rules which included an assessment of surface 

water on every proposed timber harvest site to determine whether the water was 

being used for domestic purposes, rigorous confirmation of property lines and rightsof-way, strict attention to logging slash treatment and a prohibition of log hauling on 

weekends and legal holidays. The Central Coast Timber Operators Association also 

began discussions regarding developing practices for improving stream crossings, 

road and landing construction as well as establishing buffer zones adjacent to creeks. 

In 1967, representatives of Big Creek Lumber Company participated in Board of 

Forestry sub-committee discussions of county-specific forest practice rules. It was 

during these discussions that the basic principles of selection silviculture began to 

take shape. These principles would eventually be formally established as government 

regulation in the Santa Cruz Mountains. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

588

Three operational standards were adopted at this time which formed the basis for 

single-tree selection silviculture in San Mateo, Santa Cruz and Santa Clara Counties. 

The first was the 60-40 Rule. This rule stated that no more than 60 percent of trees 18 

inches in diameter or larger could be cut during any harvest entry and no more than 

40 percent of the trees 8 inches to 18 could be cut per entry. 

The second operational standard established at this time was the minimum 

reentry time period. It was set at 10 years, based on harvest entry intervals being 

practiced by several local foresters at that time.

The last standard was lopping. This operational concept was first tested for 

economic effectiveness by Big Creek Lumber Company on a harvest site in San 

Mateo County in the 1960s. The eventual outcome of this standard was that all 

logging slash now had to be cut to within 30 inches of the ground. Interestingly it was 

this requirement that had the most immediate impact on timber operations in the 

Santa Cruz Mountains. Once operators became responsible for the cleanup of logging 

slash, the quality of timber operations improved significantly. Timber fallers and 

equipment operators could no longer knock down or damage smaller conifers and 

hardwoods, at least not without incurring prohibitive cleanup costs. 

In 1973, the legislature passed the Z’berg-Nejedly California Forest Practice Act, 

enabling legislation that charged the California Board of Forestry and Fire Protection 

with establishing the California Forest Practice Rules. The Act permitted individual 

counties to create their own separate logging regulations as long as those regulations 

were more protective than state regulations. On January 1, 1983 Senate Bill 856 was 

passed. This legislation removed county authority to regulate the conduct of timber 

operations. The impetus for SB 856 was that Santa Clara County Board of 

Supervisors had decided in 1980 to completely disallow timber harvesting within the 

county. 

SB 856 also recognized the fact that counties might have specific needs. The 

legislation empowered individual counties to petition the Board of Forestry for 

Special County Rules. In the early 1980s, not long after the passage of SB 856, 

several counties, including San Mateo, Santa Clara and Santa Cruz, petitioned the 

Board of Forestry for such rules. Primarily using the threshold of necessity, the Board 

of Forestry passed some of the requested Special County Rules and rejected others. 

Interestingly, the rules that filtered out of this process were remarkably similar to the 

operational standards adopted by the Central Coast Timber Operators Association 

during the 1950s. 

Observations from an industry perspective

From Big Creek Lumber Company’s perspective, the development of an unevenage silvicultural paradigm served several purposes. First, it was an effective strategy 

to address several public concerns regarding aesthetics and resource protection. 

Second, it had the potential to provide a dependable and renewable resource over 

time. There was also a sense of what forestlands managed under selection harvesting 

might look like over time, but it would be years before there was an understanding of 

the results of multiple harvest entries. 
Observations About the Effectiveness of Utilizing Single Tree Selection Silviculture in Redwood 

Forestlands 

589

By the 1950s, foresters and timber operators were well aware of the ability of 

individual coastal redwood trees to exhibit significant, and at times phenomenal, 

release growth when competing trees were removed. Cross sections of residual trees 

frequently showed a small core section of very slow growth and a fast growing outer 

section. These were small, suppressed trees that released when the adjacent oldgrowth overstory was felled. The increased sunlight, coupled with an existing 

established root system created an opportunity for rapid growth. Foresters at that time 

theorized that selection thinning could result in increased growth on individual uncut 

trees. Over 60 years of periodic selective harvesting in the Santa Cruz Mountains has 

demonstrated that this is generally true. 

Big Creek Lumber Company’s timber marking and harvesting philosophy has 

remained fundamentally unchanged both before and after the passage of the Z’bergNejedly California Forest Practice Act. Defective trees with little growth potential are 

harvested, allowing overall stand growth to be distributed on better formed trees. 

More recently, larger trees with recognizably pronounced cavities or other potential 

wildlife habitat attributes are generally retained. The remainder of the redwoods are 

thinned using the principal objective of increasing spacing between adjacent 

dominant and co-dominant trees. This would not be considered “thinning from 

below”. It is our experience that limiting harvesting to understory trees results in little 

growth release in the dominant and co-dominant trees and does not sufficiently open 

the canopy to allow for successful sprout regeneration. 

Careful consideration is also given to the logistics of each proposed timber 

harvest. It is not sufficient to solely consider silviculture when marking trees for 

harvest. Logging is a mechanical process and selection harvesting has a value set that 

does not exist in even-age management: protection of the unmarked trees, also 

referred to as the “leave stand”. Foresters are trained to consider how a tree will be 

felled and yarded when they mark timber. It is counter-productive to mark timber that 

cannot be felled or yarded without breaking the marked tree or damaging the leave 

stand. Our newly hired foresters spend significant time working directly with logging 

crews in order to understand the mechanical principals of logging operations. Big 

Creek Lumber has always placed the responsibility for road and log landing layout 

with its foresters. At the same time, logging crew personnel are trained to minimize 

damage to the leave stand when conducting yarding operations. 

Three timber yarding methods are utilized in local selective harvesting; groundbased tractor/skidder yarding, cable yarding and helicopter yarding. Terrain and 

infrastructure usually dictate which yarding method is used. 

Ground based yarding 

This method is utilized when the terrain permits and there is either an existing 

skid road system or the ability to construct skid roads without creating potential 

environmental problems. Cable and helicopter yarding methods are used when the 

terrain is excessively steep, the forestland is inaccessible or new road construction is 

not feasible. Ground-based yarding is the least expensive. Particular care is taken to 

minimize soil disturbance when conducting ground-based operations and all skid 

roads are seeded, straw mulched or covered with logging slash to prevent erosion 

following harvest operations. A direct advantage of this yarding method is that 

tractors can be used to distribute logging slash on skid roads and then crush the slash 

to create an effective barrier against erosion.
GENERAL TECHNICAL REPORT PSW-GTR-238 

590

Cable yarding 

This method is primarily used when the terrain is too steep for ground-based 

yarding. Cable yarding is operationally more challenging in a selection harvest 

because of the need to protect the leave stand. Cable corridors are designated and 

trees are felled on an angle towards the corridor in order to minimize damage to 

standing timber. Local operators are able to maintain cable corridors no wider than 

15 feet. Within several years the canopy closes in over these corridors and they are 

no longer visible. 

Helicopter yarding 

This is the most expensive method, roughly twice the cost of ground-based 

yarding. It is primarily used when there is neither existing road infrastructure nor the 

ability to create new roads. It is the least intrusive relative to ground disturbance. 

Because of steep terrain and limited road access, lopping of logging slash on cable 

and helicopter operations is restricted to hand crews and is considerably more 

expensive and less effective than lopping operations on tractor-logged ground.

The 60-40 cutting rule has been in effect since the 1960s, first as a self-imposed 

operational standard, and then as California Forest Practice Rules specific to the 

Southern Subdistrict of the Coast District. While this rule technically allows sixty 

percent of the trees over 18 inches in diameter to be harvested every ten years 2

, the 

reality is that few properties have been cut that heavily during an initial entry and 

almost no forested parcels have been harvested at that rate repetitively. In reality, 

logging in the Santa Cruz Mountains has evolved into a self-regulating system that 

has resulted in harvest levels that have consistently fallen short of the regulatory 

limits. There are several reasons for this. 

Under certain circumstances in a densely stocked second-growth forest, a heavy 

initial harvest level can be justified from a silvicultural perspective. It can stimulate 

accelerated growth in the leave stand and promotes successful regeneration. An 

argument can be made for a slightly less aggressive harvest during a second entry, 

but heavy cutting on short intervals over time does not make sense economically and 

could theoretically result in smaller average tree size. Simply put, the growth may not 

be sufficient to make future harvest operations economically desirable. The loggers, 

sawmill and landowners do not necessarily want small trees and the landowner has an 

expectation of a reasonable return from harvest operations and their commitment to 

responsible land stewardship. To be certain, there are a number of variables that 

affect decisions about harvest levels and entry periods. For example, the growth 

potential of the forestland is an important factor. Nevertheless, the result over time is 

that the harvest levels in the Santa Cruz Mountains have not approached the 

regulatory limits and the average size of trees harvested has consistently increased.

Looking forward

Responsible forest management in the Santa Cruz Mountains faces considerable 

challenges. These challenges are not dissimilar from those occurring elsewhere in 

California or the nation, but they began earlier here than in other areas and are 

 

2 In Santa Cruz County, if the harvest level is between 50 and 60 percent, the minimum reentry period is 

14 years.
Observations About the Effectiveness of Utilizing Single Tree Selection Silviculture in Redwood 

Forestlands 

591

frequently more intense. The Santa Cruz Mountains have been subjected to urban 

sprawl, including development encroachment into forestlands for more than a 

century. 

More recently, the transition of the Santa Clara Valley into a regional economic 

powerhouse has predictably placed extreme land use pressures on adjacent rural lands 

and particularly on local forestlands. Properties that historically were owned and 

maintained with periodic selective harvesting as an objective have now became 

desirable as an upscale bedroom community for Silicon Valley. This dynamic not 

only creates competing economic pressure on local forestlands, it has also resulted in 

a population of new residents who have little knowledge of local logging practices of 

the area’s longtime history sustainable forest management. Communicating this 

information to a constantly changing general public, their elected representatives and 

various government regulatory agencies is an ongoing necessity for the local forestry 

community. 

One of the current challenges to maintaining sustainable forestry and a forest 

products industry in the Santa Cruz Mountains is the loss of viable timberlands to 

preservation policy. In the last 30 years, tens of thousands of acres of potentially 

harvestable forestland have been taken out of production by park and open-space 

acquisition. While many of these lands technically could be harvested, that has 

generally not been the policy objective of those administering these lands.3

Encouragingly, several open space organizations are now considering the potential of 

responsible forest management as a mechanism to achieve their conservation goals. 

Time will tell what decisions are made.

In conclusion, selection harvesting has evolved into an effective and sustainable 

forest management methodology within the Santa Cruz Mountains. It was not created 

by government regulation alone, but is better explained as the result of multiple 

inputs which include: industry initiative, social and political pressure, as well as 

environmental considerations. While this kind of forest management works well in 

the predominantly redwood forestlands of the Santa Cruz Mountains, it remains to be 

seen whether it would be appropriate in other forest ecosystems.

 

3 A significant exception to this dynamic is the Byrne/Milliron forest owned and managed by the Land 

Trust of Santa Cruz County. This sustainably managed and harvested parcel has generated over $1.1 

million, funds which in turn have been used by the Land Trust to support their conservation work.

593

The Watershed TMP: a Proposal to Manage 

the Redwood Ecosystem Under Convergent 

Environmental, Economic and Social Goals

Frederick D. Euphrat1

Abstract

Under present California Forest Practice Rules, mandated by the Legislature and codified by 

the State Board of Forestry, Non-industrial Timber Management Plans (NTMPs) give small 

landowners the flexibility to operate under a specific set of rules 'forever,' allowing short 

notice (3 days or less) for pre-approved harvest operations. This permit is presently restricted 

to forestland ownerships less than 2,500 acres, requires uneven-aged management (selection 

harvest), and allows forest managers to both react to market conditions and have certainty of 

regulation. There is no comparable tool for larger ownerships. Using this concept for larger 

ownerships, with an explicitly directed primary outcome of wildlife, watershed benefits or 

carbon sequestration, and timber as a subsidiary output, would improve environmental 

quality, reduce landowner costs and reduce regulatory time for forestry under the California 

permit process. A Legislative bill or Board of Forestry initiative could create a Watershed 

Timber Management Plan as a low-intensity, watershed-scale forest management permit. This 

tool would be particularly useful in California's coast redwood ecosystems, where selection 

harvest is a demonstrated way of managing for both ecosystem services and timber 

production.

Key words: silviculture, watershed, forest policy, forestry, California, redwood, NTMP, 

natural capital, ecosystem services

Background

Private timberlands in California fall under control of the State Legislature. The 

Z’Berg-Nejedly Forest Practice Act of 1973 and amendments give the State Board of 

Forestry (Board) the formation language for the California State Forest Practice 

Rules (FPRs). That legislation reflects the intent of the State Legislature to:

“create and maintain an effective and comprehensive system of regulation 

and use of all timberlands so as to assure that: 

(a) Where feasible, the productivity of timberlands is restored, enhanced, and 

maintained. 

(b) The goal of maximum sustained production of high-quality timber 

products is achieved while giving consideration to values relating to 

sequestration of carbon dioxide, recreation, watershed, wildlife, range and

 

1 Forest, Soil & Water, Inc. PO Box 1802, Healdsburg, CA 95448; (707) 591-5966. (fred@euphrat.org).
GENERAL TECHNICAL REPORT PSW-GTR-238 

594

forage, fisheries, regional economic vitality, employment, and aesthetic 

enjoyment.2

 

The implementation of this intent is the responsibility of the Board through its 

rulemaking procedures, then accomplished through the agency of the California 

Department of Forestry and Fire Protection (CalFire). In practice this has created a 

set of ‘classes’ of permits for timber harvesting: timber harvest plans (THPs), 

modified timber harvest plans (MTHPs), non-industrial timber management plans 

(NTMPs), sustained yield plans (SYPs) (still requiring a THP), program timber 

environmental impact reports (PTEIRs), exemptions and emergency notices. 

Additional federal permitting requirements for large ownerships may also mandate or 

justify a Habitat Conservation Plan, to be implemented and referenced in subsequent 

THPs. While this plethora of approaches exist, choices for landowners narrow 

quickly.

THPs are flexible, may cover large areas, and are good for 3 years, with 

extensions granted by CalFire. All silvicultural (harvest) methods are allowable in 

THPs. MTHPs are for parcels 100 ac and less, and do not allow even-aged (clearcut 

and functional equivalents) methods, among other significant restrictions. MTHPs are 

time-limited in the same manner as THPs. SYPs are intended to be a supporting 

element for THPs over a broad area, but are used little because of the documentation 

required for the THP. PTEIRs are also for very large areas, establishing a local set of 

forestry rules through an EIR process, followed by subsequent Program THPs, 

smaller in scope than a full THP. PTEIRs are a very useful tool for local 

‘regulations’, though they are acknowledged to be complicated, expensive, and 

require broad buy-in to begin. 

NTMPs are allowed for landowners with less than 2,500 total ac, and require 

uneven-aged management (selection harvest). NTMPs are permanent. With 50 or 

more years of harvest and yield projections, NTMPs are intended to be continued into 

the future with the simple notification of a Notice of Timber Operations. Some 

elements of NTMPs must remain up-to-date, such as water quality and species 

considerations administered through other agencies. 

It is important to note that these options trade size for silviculture (table 1). But 

this means that large landowners, such as ranchers, organizations and industry, 

cannot make the same trade. This is counterintuitive; the landowner, the public and 

the ecosystem all need the opportunity for and benefits of less intensive silviculture 

over large areas, particularly individual watersheds that may be of great natural 

capital value, such as for domestic water supply or listed fisheries. Without large, low 

intensity operations, forest managers tend to seek the most cost-effective solution of 

compressing harvests into a set of THPs, with concomitant high-yield cutting 

patterns. It is this approach that may define checkerboard clearcuts as the most costeffective management approach (fig. 1). While this even-aged matrix may be as 

effective at protecting forest resources as an uneven-aged system, no option presently 

exists for landowners who specifically want to devote land to ecosystem services 

while still harvesting trees.

 

2

 Z’Berg-Nejedly Forest Practice Act, Division 4, Chapter 8, Public Resources Code, sec. 4513. 

Effective January 1, 2010. 
The Watershed TMP: a Proposal to Manage the Redwood Ecosystem Under Convergent 

Environmental, Economic and Social Goals 

595

Table 1—Selected California Forest Practice Rule Harvest Permits. 

CalFire Permit Maximum size 

(acres)

Silvicultural 

limitations

Time Period Additional 

Permit 

required

MTHP 100 Uneven-aged 3 years* No

NTMP 2,500 Uneven-aged Permanent No

THP None None 3 years* No

SYP None n/a Permanent THP

PTEIR None Within PTEIR 

frame

Permanent PTHP

Exemption: 

Dead, Diseased 

and Dying

None 10% cut, only 

damaged trees

1 year No

Emergency 

Notice

None Only damaged 

trees**

1 year No

* May be extended in one-year amendments.

** With exceptions.

Discussion

There is a bias in the options available for California private forest management. 

Managing below 2,500 ac favors uneven-aged management, granting unchanging 

rules and short notice harvests. No permit alternative exists for larger lands to ‘trade’ 

management intensity for increased certainty of harvest and reduced cost in the 

future. In CalFire’s own assessment of the cost-effectiveness of NTMPs: 

“The cost of preparing an NTMP is about 25 to 50 percent more than a 

typical THP, much of which comes from the required sustained yield 

analysis. However, this cost is recaptured over time because subsequent 

NTMP harvest entries can be conducted under a much simpler notice to 

CDF, which triggers the inspection and enforcement process.”(CalFire 2003). 

The bias exists because the Legislature and the Board of Forestry identify two 

classes of landowners: Non-industrial private forest landowners (NIPFs) and 

industrial landowners. NIPFs do not own more than 2,500 ac of timberland in 

California and are “not primarily engaged in the manufacture of forest products” (see 

footnote 2). CalFire estimates that more than half a million additional acres would be 

available for NTMPs if the maximum were increased to 5,000 ac (CalFire 2003).

There is no ‘industrial’ alternative to NTMPs, trading uneven-aged silvicultural 

practices for long-term certainty in regulation. This seems counterintuitive; 

California’s sequestration of carbon dioxide, recreation, watershed protection and 

wildlife can all benefit from uneven-aged management. For example, carbon 

sequestration of an uneven-aged forest is effective because (1) Climate Registration 

Protocols require a baseline of timber to be in place before ‘additional’ timber can be 

valued (Climate Action Reserve 2010), and (2) large trees, in general, put on more 

volume of wood per acre per year than small trees (Lindquist and Palley, 1963). 

Some industrial owners operate successfully using only uneven-aged systems, such 

as Big Creek and Mendocino Redwoods (MRC), operating within the THP system 

and (in MRC's case) developing an HCP, as well. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

596

The PTEIR may be a choice for large landscapes, but Calwater watersheds and 

other intermediate size areas, from 2,500 ac to 15,000 ac, are too small for such an 

investment. In addition, the PTEIR harvests, designed for multiple ownerships, are 

managed via individual Program THPs with their own costs. 

Prudent management

In California and the redwood region, cut blocks in even-aged management are 

regulated by the FPRs, with a maximum size from 20 to more than 30 ac. Adjacent 

areas must be restocked for 5 years prior to even-aged treatment, with logical 

boundaries in between cut blocks. Figure 1 shows the Gualala River watershed, 

managed with even-aged silviculture.

Figure 1—Even-aged redwood silviculture in the Gualala River watershed.3

(photo: Fred Euphrat).

Seen from a statewide perspective, permanent forestry plans with a lighter impact 

would be useful for managing important landscape elements, such as streams and 

watersheds, wildlife habitats and corridors, and urban interface areas. Consider that 

the average Calwater 2.2a planning watersheds units recognized by CalFire are 7,537 

ac (Smith 2008); that habitat for many species is reduced by fragmentation (Andren 

1994); that biological corridors require continuity (Noss and Cooperrider 1994); and 

that parcel development reflects a loss of cost-effectiveness of forest management. 

The corridor issue is addressed, to an extent, by the FPRs - stream corridors provide 

riparian passage. Other biodiversity hotspots, such as ridgetop and saddle corridors, 

edge to forest ratio, and the encroachment of urban and agricultural areas remain 

unaddressed. Larger, permanent uneven-aged plans may mitigate many of the 

 

3 www.krisweb.com. 1999. Gualala watershed, hypothesis no. 3. “Figure 9. Clear cuts in unstable, inner 

gorge locations of upper Little North Fork Gualala River in 1999. Arrows designate landslides.
The Watershed TMP: a Proposal to Manage the Redwood Ecosystem Under Convergent 

Environmental, Economic and Social Goals 

597

biodiversity problems of industrial timber management while making it more costeffective.

Indeed, the State Legislature finds forest management, in combination with 

uneven-aged methods, “prudent,” in its enaction of NTMP legislation. The intent in 

section 4593 of the Public Resources Code is:

(b) The Legislature further finds and declares that minimal environmental 

harm is caused by prudent management of nonindustrial timberlands because 

low volume production and dispersion around the state of these small tracts 

reduces damage to aesthetics, air quality, watersheds, and wildlife.4

 

Recognizing that the Legislature's finding of 'prudent' forestry also embraces 

low-volume harvest and dispersed production, the inclusion of uneven-aged 

management allows demonstrated protection of aesthetics and habitat (Thornburg et 

al. 2000), particularly with the inclusion of old individual 'heritage' trees and group 

selection.

It is a timely moment in California to transition to uneven-aged management. For 

example, a two-aged stand is shown in fig. 2. This is the kind of forest where singletree selection can both harvest the larger trees and promote the growth of smaller 

ones. The larger trees put on more high quality volume; the smaller trees fill canopy 

gaps and increase growth in response to additional light and space. Uneven-aged 

stands may be harvested every 10 to 15 years and produce an even flow of timber 

while maintaining a continuous forest, depending on the site and other tree growth 

characteristics (Arvola 1978).

The watershed approach to forest management

This discussion has been oriented towards the use of uneven-aged silviculture as 

a method to increase the quality and quantity of forest benefits. This is reflective of 

the considered opinion of the Legislature, which supports uneven-aged management 

with the reward of the permanent NTMP. But this belies the fact that there are many 

approaches to uneven-aged management, and there is no direct causal link recognized 

between specific forest management and particular outcomes in the FPRs. Selection 

harvesting is considered better for NTMPs, but without benefits stated explicitly. 

It stands to reason that, if goals were explicit, with cause-and-effect relationships 

that could be measured, inventoried and modeled, the State would get greater benefits 

from forest management. Goals of carbon sequestration, watershed or wildlife 

management could be implemented with certainty, and the State would be able to 

quantify those benefits. This does not mean moving away from timber; it means 

using silviculture to achieve other benefits, rather than expecting trickle-down 

benefits from a purely silvicultural approach. 

A Watershed TMP would allow forestry for specific attributes determined by 

what is important in a locality. Examples are: watershed management above sensitive 

waterways, habitat management for particular species, or aesthetic and fire 

 

4 Division 4, Chapter 8, Public Resources Code, sec. 4593 (b).
GENERAL TECHNICAL REPORT PSW-GTR-238 

598

Figure 2—Two-aged redwood stand in Jackson State Demonstration Forest (photo: 

Fred Euphrat).

management adjacent to residential zones. All of these require varied forest 

management. The Calwater Planning Watershed system is a reasonable first step of 

organizing and delineation. Multiple watersheds can be used to create larger elements 

but, under a Watershed TMP, would still be modeled, evaluated and permitted by 

watershed to address local issues.

Expanding the NTMP approach to more timberlands would create both increased 

certainty and social benefit. In the words of CalFire, 

“This change would benefit both landowners and the state by providing an 

opportunity for these additional timberlands to be placed into a sustained 

yield and uneven-aged management regime.” (CalFire 2003). 

It must be stated that industrial timberlands already meet criteria for sustained 

yield under the FPRs. Expanding an NTMP approach may not, in itself, make the 

lands more ‘sustained,’ as cutting patterns would shift, though timber output would 

not necessarily change. But it would clearly expand the opportunity for uneven-aged 

management to benefit California. 

It must also be stated that, on a watershed level, it is not the intention of this 

paper to propose that selection cutting has less impact, over time, than even-aged 

methods. Good road practices, revegetation and harvest methods appropriate to stand 

dynamics are critical to any harvest. Rather, uneven-aged methods, with their 

concomitant combination of closed canopy forests and their continuous accumulation 

of carbon is preferred by the public, via the legislature, to be an action of less 

potential negative consequence, thus requiring less scrutiny, as in the NTMP 

legislation discussed above.
The Watershed TMP: a Proposal to Manage the Redwood Ecosystem Under Convergent 

Environmental, Economic and Social Goals 

599

In the redwood region, the utility for Watershed TMPs may be greater than the 

rest of the state. Redwoods coppice and are relatively shade tolerant. The highly 

productive redwood forests produce effective (though not biological maximum) 

growth in uneven-aged conditions. Forests have been effectively managed through 

uneven-aged silviculture for decades, and are a sustainable source of wood and jobs. 

Model rules 

A Watershed TMP would require its own legislation and its own section in the 

FPRs. Elements that section would include are:

• A maximum size of one planning watershed. 

• Disconnected sub-areas within one planning watershed OK. 

• Ability to reasonably adjust Calwater lines for property and resource 

management. 

• One landowner. 

• No assessment of total landowner forestland holdings. 

• No differentiation between industrial and non-industrial ownership. 

• Only uneven-aged management. 

• Primary resource NOT timber. 

• Explicit goals for outcomes of primary and subsidiary resources. 

• Inventory and Modeling of primary resource. 

• Inventory and Modeling of timber. 

• Re-inventory schedules. 

• Accommodation for other agencies’ review as necessary through time. 

• Plan setting in context with adjacent parcels, permits and Watershed TMPs. 

• Permit for harvest by Notice of Timber Operations. 

The political landscape 

In California there is a constituency for every side of an issue. Conversations 

regarding a Watershed TMP approach have yielded a variety of responses. One forest 

manager said, ‘Of course, we already do that, we just don’t get any credit for it.’ The 

Watershed TMP may be welcomed by industries that are already using selection 

forestry to their current advantage. This is also a good tool for industry lands seeking 

compliance with Federal Habitat Conservation Plans. In most cases, this would 

reduce cost for the submitter and the agency, and may well bring significant acreage 

into uneven-aged management for specific ecosystem services. 

An environmental advocate said ‘No way will we accept permanent logging 

plans.’ But advocates are not all of one mind. Others see this as an opportunity to 

focus on particular watersheds, species or aesthetics to the benefit of the community 

and its job base. It allows public trust advocates to look at a manager's big picture, 

rather than having to address watershed via THPs in a piecemeal fashion. Permanent 

plans with continuous monitoring allow for flexibility and focus on locally important 

resources. The Watershed TMP could spread the benefits of ‘prudent’ management 

throughout the redwood region and the state. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

600

A Watershed TMP scenario 

An industrial manager chooses to prepare a Watershed TMP, with combined 

goals of water quality, habitat, carbon sequestration and timber harvest. The plan will 

cover about 7,500 ac. That area will modify the Calwater watershed, to better 

encompass a watershed on the property. That watershed is adjacent to two other 

Watershed TMPs, so conjunctive planning will occur. 

Emphasizing water quality and carbon accumulation, smaller watercourses will 

be cut less than allowed by the rules. Overall stocking will be maintained at 20

percent above FPR floors. While clearings will be limited to the regulatory maximum 

of 2.5 ac, their locations will avoid habitat elements, preserving saddles and creating 

continuity with adjacent watersheds. Cutting frequency will be increased relative to 

even-aged silviculture, necessitating an active road system, which will allow constant 

monitoring. 

Following a higher up-front cost for the Watershed TMP, significantly less 

capital will be required for later permit compliance. Jobs will be less cyclic, because 

of the certainty of this and other plans, adding regional economic vitality. As now, 

the entire area will continue with owl surveys, murrelet surveys and wildlife 

inventory, and stay apprised of changes in State and Federal species listings. Carbon 

sequestration will continue to progress on site, due to standing trees on site and 

quickly increasing volume. 

Conclusion

The Legislature has created a two-tier system of forest landowners in California, 

creating divergent opportunities and outcomes. Landowners with less than 2,500 ac 

are given the opportunity to manage forests with uneven-aged methods and a 

permanent plan in the NTMP process. The legislature considers uneven-aged 

methods part of a 'prudent' approach. Larger landowners, specifically forest 

industries, must manage with short-term permits and face changing CalFire rules. 

While landowners with greater than 2,500 ac may choose to use uneven-aged 

methods, there is no incentive to manage forestlands for resources other than for 

timber productivity.

A Watershed TMP would provide a reason for industry and other forest 

landowners with greater than 2,500 ac to produce specific benefits from uneven-aged 

management. The incentive is a permanent permit at a watershed scale of one 

Calwater planning watershed, which would require only a Notice of Timber 

Operations to proceed, in addition to statutory requirements from other agencies. The 

Watershed TMP would be oriented towards one or more of many benefits received 

from forests as well as timber, with inventory and monitoring to match. 

The goal of Watershed TMPs is to allow large landholdings to use uneven-aged 

management across as broad a range of California forests as possible. It allows 

landowners to evaluate the range of positive outcomes from silviculture. It promotes 

multi-watershed planning of wildlife habitat. It helps create long-term certainty in 

jobs and local economies, and sequesters forest carbon more effectively than other 

means. 
The Watershed TMP: a Proposal to Manage the Redwood Ecosystem Under Convergent 

Environmental, Economic and Social Goals 

601

At this writing, the California Legislature is considering SB 455, Watershed 

Timber Harvest Plans5

. While similar in some ways to the proposal above, it differs 

in that it would not require uneven-aged management, plans would be larger than one 

planning watershed, and requires both a watershed and fish and wildlife assessment. 

The bill also affects conversions of forest to non-forest uses. 

Watershed TMPs may be a tool most effective in the redwood region, because of 

the relative shade tolerance and resprouting ability of redwoods, the steep slopes and 

the sensitive species. The natural capital of our forests is great, the ecosystem 

services they provide are priceless It is time for the law to encourage silviculture to 

become and active agent in watershed protection, carbon sequestration and habitat 

protection in California.

References

Andren, H. 1994. Effects of habitat fragmentation on birds and mammals in landscapes 

with different proportions of suitable habitat: a review. Oikos 71: 355-366.

Arvola, T.F. 1978. California forestry handbook. Sacramento, CA: Department of Forestry. 

233 p.

California Department of Forestry and Fire Protection. 2003. Nonindustrial timber 

management plans in California: report to the Legislature. 18 p.

Climate Action Reserve. 2010. Forest Project Protocol Ver. 3.2. 30 August 2010. 140 p.

Lindquist, J.; Palley, M. 1963. Empirical yield tables for young-growth redwood. Ag. Exp. 

Sta. Bull. 796. Berkeley, CA: UC Berkeley. 

Noss R.; Cooperrider, A. 1994. Saving nature’s legacy: protecting and restoring 

biodiversity. Covelo, CA: Island Press. 

Smith, R.D. 2008. Russian River Watershed Adaptive Management Plan, baseline 

watershed assessment synthesis report. U.S. Army Corps of Engineers. February 

2008. review draft. 97 p.

Thornborough, D.A..; Noss, R.A.; et al. 2000. Managing redwoods. In: Noss. R., editor. The 

redwood forest: history, ecology and conservation of coast redwoods. Washington, DC: 

Island Press: 229-261.

 

5 Pavley, 2011. SB 455, California State Legislature. As introduced, not amended, as of 20 Oct 2011.

603

Protecting Forests Across Landscapes and 

Through Generations: the Sonoma County 

Forest Conservation Working Group 

Frederick D. Euphrat,1 Steven Swain,2 Dee Swanhuyser,3 Jill 

Butler,4 Amy Chesnut,5 Kim Batchelder,6 Caerleon Safford,7 and 

Earle Cummings8 

Abstract

There are approximately 513,000 acres of coniferous forests and oak woodlands in Sonoma 

County, California, situated about 50 miles north of San Francisco. Most of the oak 

woodland, and over 68 percent (132,000 acres) of the coniferous forestland, is in private 

ownerships of 50 acres and less. These forests are unique, with 10 species of true oak and 19 

species of conifer in the county. While Sonoma’s forests provide a suite of benefits, factors 

create pressure to parcelize, convert to viticulture, and fragment the forest ecosystem. In order 

to address these threats, an ad-hoc committee created the Sonoma County Forest Conservation 

Working Group (Working Group). 

The Working Group provides information and resources to forest landowners with the goal of 

protecting the health and long-term tenure of forests and woodlands. Lessons learned 

highlight landowners’ interest in fire and forest management, but also a lack of wildland and 

forest management knowledge, a reluctance to spend money, and institutional gaps that 

ultimately increase fire danger and ecosystem fragmentation. This experience demonstrates 

the importance of our mission, ‘Protecting Forests Across Landscapes and Through 

Generations.’ 

Key words: community forestry, extension, Sonoma, fire control

Introduction

Sonoma County is unique among forested counties in California. Because of its 

proximity to San Francisco, fertile soils, abundant water and quicksilver mines, the 

area was settled early relative to much of the state. Its timber resources were accessed 

by rail in the 1870s for the development of San Francisco (Codoni and Trimble 

2006). Most of the land ended up in private hands, generally going back to Spanish 

Rancho demarcation. For this reason, there is very little public ownership of 

timberlands or oak woodlands in Sonoma County. Forest health and ecosystem 

continuity depends, in a very large part, on the private landowner.

 

1 Forest, Soil & Water, Inc. PO Box 1802, Healdsburg, CA 95448; (707) 591-5966. (fred@euphrat.org).. 2 University of California Cooperative Extension. 3 Greenbelt Alliance. 4 California Department of Forestry and Fire Protection. 5 Sonoma Land Trust. 6 Sonoma County Agricultural Preservation and Open Space District. 7 Fire Safe Sonoma. 8 Sotoyome Resource Conservation District. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

604

The Working Group grew out of a meeting convened in February, 2005, by 

Sonoma Land Trust, to talk about issues including small, private parcels of forest in 

Sonoma County, California. The ‘problem’ with these parcels is their abundance in 

the County; Sonoma County is the most highly parcelized county in California 

(Greenbelt Alliance, 2006). North of San Francisco and Marin, the million-acre 

county has more than 513,000 acres of true oak woodland (Quercus spp.) and coast 

redwood-Douglas-fir (Sequoia sempervirens and Pseudotsuga menziesii) forest, 

about one-third of which is held in parcels of 100 acres or less. In coniferous forests, 

parcels of 50 acres and less constitute 68 percent, or 132,000 acres9

. This relatively 

small size of ownership of a wide-ranging ecosystem creates parcels that are 

uneconomic for timber harvest or rangeland, historic uses of this land when it was in 

larger parcels. The general use at this time is ‘no-action’.

The no-action alternative is a concern to the colloquium of forest, land trust and 

trail managers. The county has unique forests with 10 native species of true oak and 

19 native conifers10 (CalFlora Data Base 2011). While most of the old-growth 

redwood and Douglas-fir forest was logged since the California gold rush, the 

ecosystem remains. The second growth redwood-Douglas-fir forest is in various 

stages of succession in response to previous harvests. Most of the seral stages are 

now fire-prone in this once frequent-fire ecosystem. The oak savannahs are similarly 

subject to the effects of fire, an indigenous practice in Sonoma’s valleys (Anderson 

2005). Some species, such as knobcone Pine (Pinus attenuata) are fire-dependent. In 

addition, Sudden Oak Death (caused by Phytophthora ramorum), irregular 

management practices, and land tenure changes all contribute to fire hazard. And 

most importantly, the smaller size of ownerships with dwellings increases both the 

likelihood of fire and the severity of fire damage, including the potential for loss of 

life.

The Working Group formed from a group of the Sonoma Land Trust meeting’s 

participants and has focused on finding those private landowners with ‘small’ 

parcels, and providing the tools they need to plan, manage and conserve their land for 

themselves and the generations to come. The mission of the Working Group is: 

Protecting Forests Across Landscapes and Through Generations.

Methodology

The core partners in the Working Group are: the Sonoma Land Trust; the 

Greenbelt Alliance; the State Department of Forestry and Fire Protection (CalFire); 

the University of California Cooperative Extension; Sotoyome and Gold Ridge 

Resource Conservation Districts; Sonoma County Agricultural and Open Space 

District; Fire Safe Sonoma; the Bodega Land Trust; Coast Ridge Community Forest; 

and interested individual and forestry professionals. People and organizations 

contributed space for meetings. There is no paid staff. Volunteer members rotate 

duties to provide agenda, facilitation, and take minutes at monthly meetings, as well 

as representing their respective organizations, interests, and capacities.

 

9 Sonoma County Agricultural Preservation and Open Space District. 2009. Analysis of forested parcels 

and ownerships in Sonoma County, California. Unpublished. 10 Sonoma County Agricultural Preservation and Open Space District. 2010. Oak woodland plan. 

Unpublished.
Protecting Forests Across Landscapes and Through Generations: the Sonoma County Forest 

Conservation Working Group 

605

With the combination of capacity and will, the Working Group has been 

engaging with the public and learning from its experiences. The Working Group has 

successfully coordinated Forest Stewardship workshops and two house meetings to 

date, as well as engaging large rural-subdivision neighborhood residents in dialogue 

about their needs, possibilities and future options for forest management. House 

meetings are informal get-togethers in a rural neighborhood, hosted by a resident, 

with two or three Working Group members to discuss the local situation and to 

familiarize the community with resources for rural landowners.

Forest Stewardship workshops are all-day classes, with a morning session 

focusing on forest ecology, roads and fisheries, fire safety, Sudden Oak Death, and 

conservation easements as a tool for family succession. The afternoon is a field tour 

for participants to visit sites that highlight the practices discussed during the morning 

session. Because the Working Group represents a broad base of knowledge and 

resources, many individuals can connect with the people or program they most need: 

cooperative extension, land trusts, foresters, federal and state grant coordinators, or 

even free chipping of dead and thinned brush and trees. 

In addition, we have had a series of ‘brownbag’ seminars in Santa Rosa, 

presenting topical issues related to forests and their management. These are hourlong seminars with one speaker on a specific topic. Presenters’ subjects have 

included the carbon cycle, carbon sequestration, and monetizing carbon credits; oak 

ecology and history in Sonoma County; Sonoma County fire history and ecology; 

and climate change and its potential impacts to the county. The audience for the 

seminars includes many land and resource professionals from local and regional 

government, creating an opportunity for people to ‘get to the woods’ while eating 

their lunch in town. The continued success of the Working Group has included the 

melding of the brownbag program in Santa Rosa with workshops and house meetings 

in Sonoma’s rural areas. This balance has developed a needed rapport between the 

county’s urban center and its forested periphery. 

This success has also been driven by the diverse nature of the core partners of the 

Working Group, which includes representatives from farm, forest, environment, 

government, academia, non-profit agencies and local volunteers. Based on 

workshops and outreach, the partners seek to fulfill the public’s need: How do I 

manage my forest?

Case studies 

The cumulative effect of combining agencies and volunteers for a common goal 

is that many resources are already available, others can be had inexpensively, and 

some can be derived from the community that receives the benefit. The combination 

of resources which has worked for the Working Group includes: help with outreach 

from all three local Resource Conservation Districts and UC Cooperative Extension; 

educational funding and support from UC Cooperative Extension; grant funding from 

the Community Foundation of Sonoma County and the Ernie Carpenter Fund for the 

Environment; donations of food, coffee, field transportation and meeting space from 

neighborhood groups; and donated time from both volunteer and professional 

educators. With this, the Working Group was able to engage the most important 

resource to the forests of Sonoma County, a cross-section of its landowners.
GENERAL TECHNICAL REPORT PSW-GTR-238 

606

Six workshops and six brownbags have been conducted by the Working Group 

over the last four years in Sonoma County. They are presented in table 1 as 

categorized case studies, because they all differ in content, ecosystem and 

community. Workshop attendees (table 1) do not include Working Group members, 

and are dominantly local landowners. Because of coordinated outreach and topics of 

interest, some people travel many hours to attend workshops. 

Table 1—Summary of outreach activities by the Sonoma County Forest Conservation 

Working Group. 

Workshop or 

series

Date AttendanceEcosystem Field tour

Mark West Creek 9/29/2007 40 Mixed Douglas-fir Yes

Occidental 10/13/2007 50 Redwood-Douglas-fir Yes

Cazadero 10/4/2008 38 Redwood-Douglas-fir Yes

Mill Creek 10/18/2008 48 Redwood-Douglas-fir Yes

Cavedale Road 3/19/2011 40 Mixed Douglas-fir No

Shone Farm 5/7/2011 28 Mixed Douglas-fir Yes

Brownbags Six to date 25 per Santa Rosa No

An average of 40 percent of workshop attendees report either having changed or 

planning to change land management practices as a result of the information learned. 

The attendees also felt they had significantly increased their understanding of forest 

processes, ecology, fire and fire breaks, disease and succession.

Our now-standard Healthy Forests curriculum is forest ecology, watersheds and 

roads, Sudden Oak Death, and fire safety. We have also presented panels on funding 

sources, economics of forest management, conservation easements, carbon credits, 

biomass utilization and lessons from Trinity County. 

We speak of the classes as “101” and “102”, because people consistently want 

more in-depth knowledge of particular topics. In addition to fire planning, heritance 

planning and ecosystem management, future Forest Stewardship workshops which 

will address Healthy Forests, Healthy Economies, and Healthy Communities on an 

on-going basis. Brownbags will continue to address carbon, wildlife management, 

ecological services, oak woodland management, wood cogeneration, and the forest 

assets of Sonoma County. House meetings will continue to address the individual 

concerns of specific neighborhoods. 

The Cavedale Road workshop, requested by the community, focused on “What’s 

killing our trees and what to do about it.” The agenda covered tree health and beetle 

outbreak in Douglas-fir and madrone (Arburtus menziesii), fire safety and the chipper 

program, and how to protect wildlife habitat while doing fuels management work. 

This was a less organized, less formal workshop in a person’s home, which generated 

lots of interest and good feedback. The community has requested that the Working 

Group present a full Forest Stewardship workshop next fall.

The Shone Farm workshop was also a new approach for the Working Group. On 

land managed by Santa Rosa Junior College, the theme was Community Forests, with 
Protecting Forests Across Landscapes and Through Generations: the Sonoma County Forest 

Conservation Working Group 

607

updates on selected forest conservation projects presently in the county. The field trip 

was a tour of the Shone Farm forest led by the students of recreation at the College.

Discussion

Our lessons learned may be summarized in the following points: 

• Stop looking for money to hire someone else. The experts are already in the 

room. 

• Find all the agencies that may have an interest, public and private. Both 

efficiency and synergy can be created with existing agencies, though they 

may seem ‘unlikely.’ Everybody wants to help the forest. 

• People are hungry for information. While ‘old-timers’ may remember the 

methods, contractors and agencies related to land management, new 

landowners are eager to learn.

• People generally do not perceive fire danger in forested lands, nor 

understand how to prepare for it. With information, they become more 

motivated to protect their homes and property. 

• People are ready to meet and learn, but not so ready to spend money. While 

fire danger may threaten valuable homes, people are reluctant to pay full 

costs for clearance. The free chipper program from Fire Safe Sonoma is an 

effective, tangible incentive.

• The general forest management goals of most landowners are relatively 

uniform: fire danger reduction, large tree dominant ecosystems, and liberty 

to manage their lands. 

• Many landowners have wildlife, pest, disease or other forest health goals, 

but generally have neither the knowledge nor the capability to effectively 

achieve those goals.

• There is a significant need for management strategies to coordinate multiple 

owners for multi-parcel management. For instance, one rural subdivision 

near Santa Rosa has 104 parcels, ranging in size from 4 to 40 acres, in 

about 1000 acres.

• People want to manage sustainably and achieve their goals, but do not have 

a definition for sustainability.

• People are generally not familiar with the conservation easements that may 

be used to protect elements of their land for succeeding generations.

Lessons learned are only a part of this; much of the benefit has gone to the 

individual members of the Working Group. It serves as a networking and support 

group for all those who do or want to do forestry education and outreach to the 

interested public. 

The Working Group has just finished its first brochure for outreach to the 

community. We are working to have a web presence, and to develop, publish and 
GENERAL TECHNICAL REPORT PSW-GTR-238 

608

distribute a forest landowner’s manual. That manual would outline and elaborate on 

the information presented in the workshops.

The intention of the Working Group is not to create new information, only to get 

good information into the right people’s hands. In Sonoma County, behind almost 

every vineyard is a forest, and above almost every grassland is an oak savannah. In a 

region that depends on private land ownership to achieve public goals of (1) fire and 

watershed protection, (2) ecosystem maintenance and (3) aesthetic protection, yet 

where economic decisions drive forest management, it appears critical that an 

organization like the Sonoma County Forest Conservation Working Group exists.

In retrospect, the Working Group has learned a great deal in conducting outreach 

to hundreds of forest landowners in Sonoma County. We have also learned how to 

focus our efforts to achieve the goals at hand, moving forward on volunteer and 

lunchtime energy. It is important to note that, while many people have served on the 

ad-hoc committee that forms the Working Group, everyone does so with the 

enthusiasm, readiness-to-work and positive attitude that often accompanies the word 

‘volunteer.’ Conducting outreach has been our goal, but the creation and 

perseverance of the Working Group has been our pleasure. 

Conclusion

The Sonoma County Forest Conservation Working Group was formed in 2005 to 

address the needs of forest landowners throughout the county. The need for the 

Working Group was perceived due to the paucity of public lands in the county, and 

its extensive parcelization. Most of the oak woodland and the coniferous forestland 

are in private ownerships of 50 acres and less. 

The Working Group was established to address threats to Sonoma County’s 

forestland. A number of factors, including population growth, regulatory 

requirements, estate issues and changes in the economy have created pressure to 

convert Sonoma’s forests to other uses. 

The Working Group has used community workshops, seminars and 

neighborhood meetings and lunchtime ‘brownbag’ seminars to disseminate 

information and connect experts, landowners and resource managers to access 

technical and financial support. Four years of outreach experience and feedback has 

allowed the Working Group to look back and assess lessons learned.

Our experience demonstrated the need for learning both in the Working Group 

and the public. The Working Group found that the synergy of interested individuals 

and agencies could create a cost effective, well-equipped educational forum. With 

small grants and donations, we used our own energy and expertise on our mission. 

Landowners showed an interest in information on fire, ecosystems, wildlife and 

sustainability. The outreach also highlighted a lack of wildland management 

knowledge, a reluctance to spend money, and a no-management practice across the 

landscape that ultimately degrades forest health and increases fire danger and 

ecosystem fragmentation. 

This experience demonstrated the importance of our mission, ‘Protecting Forests 

Across Landscapes and Through Generations.’ At this time, forests remain 
Protecting Forests Across Landscapes and Through Generations: the Sonoma County Forest 

Conservation Working Group 

609

vulnerable, and significant education, policy, and public will are necessary to achieve 

long term success. 

References 

Anderson, M. K. 2005. Tending the wild: native American knowledge and the 

management of California’s natural resources. Berkeley and Los Angeles: University 

of California Press Ltd. 555 p.

CalFlora Data Base. 2011. Calflora.org.

Codoni, F.; Trimble, P.C. 2006. Northwestern Pacific Railroad. Arcadia Publishing. 144 p.

Greenbelt Alliance. 2006. At risk: the Bay Area greenbelt. San Francisco, CA: Greenbelt 

Alliance. 32 p.

611

California’s Coast Redwood in New Zealand

Tom Gaman1

Abstract

New Zealanders are making a significant effort to develop their forest industry to benefit from 

rapid growth exhibited by Sequoia sempervirens on both the North Island and South Island. 

US and New Zealand forest products companies have established redwood plantations in the 

past decade, and have found that microclimate, site preparation, soil chemistry, fertilization 

and precise silvicultural practices are all of utmost importance. Farm foresters have 

established experimental redwood tree crops alongside Pinus radiata and many other western 

US and NZ native species. The NZ Farm Forestry Association Redwood Working Group has 

many experimental growth monitoring plots scattered around the country. Nursery producers 

are testing several California redwood clones that have shown exceptional promise. 

Researchers have been monitoring plantations of these and other clones here in California and 

in New Zealand. Genetic traits such as wood density, growth rates, and knot size are known to 

affect final product quality. Tree growers recognize the importance of investment in improved 

growing stock. While New Zealand plans to develop domestic and Australian markets for 

redwood products, growers hope to develop a redwood timber that will be competitive in 

international forest products markets.

Key words: redwood, New Zealand, plantation, tree improvement, farm forestry

Introduction

As New Zealand farm foresters and forest industry seek to diversify the country’s 

plantation forest, they recognize California’s coastal redwood as a key species for 

plantation forestry. Many New Zealand coastal districts have climatic conditions very 

similar to California and redwood grows rapidly there. With careful site selection, 

ongoing research, clonal propagation of improved provenances, and careful timing of 

silvicultural practices, New Zealanders have no doubt that they can produce a 

consistent product with desirable qualities. They hope that such timbers will 

favorably compete with second and third growth California-grown redwood in the 

global marketplace.

History of coast redwood in New Zealand

During the boom of the 19th and 20th centuries, enormous agricultural industries 

were developed in the isolated New Zealand economy. Sheep outnumbered people by 

30 to 1. As lamb and wood exports declined, a plan in the 1970s projected that timber 

exports could provide 20 to 25 percent of foreign exchange earnings for the fragile 

New Zealand economy (O’Neill 1975) by early in the 21st century. Pinus radiata, 

known locally as simply “radiata”, had been introduced in the 1860s and was widely 

planted on old field and volcanic sites by government, industry and farm foresters 

starting early in the 20th century. Also in the 1860s, coast redwood seed was imported 

from California. Today the Kaingaroa Forest, in the center of the North Island, is a 

240,000 ha plantation almost entirely of radiata. Also, many of the early redwood 

 

1 East-West Forestry Associates, Inc. P.O. Box 276, Inverness, CA 94937; (415) 237 0075; 

(tgaman@forestdata.com; www.forestdata.com). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

612

plantations are magnificent groves today. Recognizing its potential and value New 

Zealand foresters in 1923 imported and planted a ton of redwood seed from 

California. Though wood quality turned out to be poor, and many trees were lost due 

to frost damage, weed competition, and inappropriate site selection, generations of 

redwood trees have been successfully grown at hundreds of New Zealand locations. 

Little of this redwood, however, was utilized for forest products and the tree was 

widely viewed as a novelty giant from afar.

As with much change in the world, visionary leadership is vital. Bill Libby, forest 

genetics professor emeritus of UC Berkeley, has been involved in New Zealand tree 

improvement since his 1969 sabbatical at the New Zealand Forest Research Institute 

in Rotorua. In a 1995 address to the New Zealand Farm Forestry Association 

(NZFFA) Libby urged the membership to establish commercial California redwood 

plantations. Foresters Wade Cornell, Rob Webster, forest nursery owner Robert 

Appleton and many others responded enthusiastically to Libby’s call for a new New 

Zealand redwood industry, and the NZFFA established its Sequoia Action Group. On 

this side of the Pacific, Libby and Kuser selected exemplary redwood trees from 

native stands in every California county, and established a clonal research trial 

plantation at University of California’s Russell Reservation in the East Bay hills. 

New Zealand farm foresters and several US companies started forestry 

plantations on both the North and South Islands. Even the California forest industry 

became interested. In 2001 California’s Soper-Wheeler company established the New 

Zealand Redwood Company and purchased a 2500 ha tract, a former sheep station, at 

Conway River near Kaikoura on the east coast of the South Island. Later the 

company acquired the adjoining 2500 ha property. Today the New Zealand Redwood 

Company has 2000 ha of redwood planted on the South Island and 1200 ha on the 

North Island, the country’s largest redwood plantations. Port Blakely Tree Farms of 

Seattle created Blakely-Pacific Tree Farms and has embarked upon redwood planting 

on its lands in New Zealand. Though radiata remains by far the dominant species 

planted, scores of New Zealand tree farmers are also actively planting California 

redwood. 

Research, tree improvement, clonal propagation, and 

product quality

With the goal to expand export timber production in the face of intense 

competition from Chile and many other southern countries, New Zealanders know 

they must produce a high quality product that will survive in discerning world 

marketplaces, particularly Australia, North America and Asia. The NZFFA Sequoia 

Action Group found that eight clones planted at 34 sites had highly variable 

performance ranging from 55 to 455 cm height in 4 years (Brown et. al. 2011), so it 

became clear that careful attention to growth rates, genetic selection, site selection 

and preparation, fertilization, plantation practice, pruning practices, branch size, 

wood density are all critical factors in selecting the proper clone to plant. 

In the early years of the radiata industry most questions were answered by trial 

and error, but it was soon evident that continuing research and education programs 

are necessary in order to assure measured and successful development of the New 

Zealand plantation forest industry. The NZ Forest Service established the Forest 
California’s Coast Redwood in New Zealand 

613

Research Institute at Rotorua in 1947 at the site of 1901 experimental plantations, 

including the Whakarewarewa Redwood Grove. Though the FRI facility was created 

primarily to support the radiata plantation industry, the fine plantations of redwood 

and Douglas-fir (Pseudotsuga menziesii), macrocarpa (Cupressus macrocarpa) and 

other species are of continuing interest. Today the research campus is operated for 

Crown Forest Research by Scion, a private organization with over 350 researchers 

and staff. Interestingly, the Whakarewarewa Redwood Grove is protected as a 

memorial grove and a site of historic trees.

The NZFFA has a membership of over 300 farm foresters from around the 

country, all with intense interest in forests and trees of the world. Almost 50 

members have voluntarily established test plots on their farms throughout the 

country. The NZFFA Sequoia Action Group has field days, collects data, does 

provenance testing, and tracks the performance of selected clones. Farm foresters, the 

industry and researchers are working together on their common interest in redwood 

research. 

Today virtually all redwood planting stock is clonally produced via tissue culture. 

The genetic material is obtained from the most outstanding provenances. Many new 

clones have been imported from California while other proven trees derived from the 

early historic plantings were also selected for development. Fifty new clones, derived 

from the 1923 seed import project, are tested each year by NZ Redwood Company. 

The California clones, originally selected from all the counties in California where 

redwood is native, are being tested for a variety of qualities on the NZFFA 

membership test plots. The original clones were selected either by complete chance, 

or because the parent trees seemed to possess desirable traits for New Zealand 

plantations. Meanwhile foresters have recognized that redwoods grown rapidly with 

very wide rings often do not produce the most desirable wood products. Clonal 

sources for tissue culture are being selected for moderate growth rates, smaller knot 

size and desirable heart color. Redwood clones are also selected to represent the 

average of natural range densities of 330 to 350 kg/m3

. Genetic testing is ongoing, 

but early results show that some of the California-sourced clones, with names such as 

R2 and R52, outperform their peers in growth and uniform small knot size2

, while 

some of the naturalized New Zealand clones are more adapted to varying New 

Zealand climatic conditions and growing sites3

. Further wood density, durability, and 

structural tests are now underway to assure that the selected clones possess desirable 

market characteristics. Nicholas, Silcock and Webster of NZFFA, have calculated 

that investments in redwood plantations that can produce timber with these desirable 

traits show an internal rate of return of 9.3 percent net of land costs (Nicholas 2011, 

Chapter 9). 

Redwood growers and silviculture

New Zealanders expect to produce redwood timbers from the selected genotypes 

that compete very handsomely with second and third growth redwood on the market 

in California. Trees are planted on frost-free or low frost prepared sites below 700 m 

elevation with medium to good quality soils in areas of moderate rainfall that are 

naturally sheltered from prevailing winds. High soil moisture capacity is important 

 

2

 R. Appleton, Appleton Nurseries, Brightwater. 2010. Personal communication. 3

 R. Coker, New Zealand Redwood Company. 2011. Personal communication.
GENERAL TECHNICAL REPORT PSW-GTR-238 

614

but fog drip is not essential. Sites require suitable redwood mycorrhizal inoculation to 

perform well. Weed control is critical for establishment. NZ Redwood Company 

originally used mechanical site preparation methods to clear weeds, mostly gorse, 

bracken and broom, on abandoned sheep paddocks. This method has been replaced 

with a combination of herbicide application and burning, which is cheaper and 

preserves soil structure (see footnote 3). Redwoods have performed adequately on 

clay soils on the North Island. As in California, New Zealand redwood plantations 

have been relatively pest free. Fungicide applications are in some locations necessary 

for establishment. There are enormous brushtail possum (Trichosurus vulpecula) 

populations in some areas, and they have damaged redwood leaders, so possum 

control is necessary. In wet areas drywood termites are sometimes problematic. 

Minor problems with leaf rollers and cankers have been reported. There has been 

some branch node dieback that may be attributable to soil boron deficiencies (see 

footnote 2). Minute boron applications on such sites seem to cure the problem. 

Robert Appleton has imported natural boron from Africa and South America and 

applied it in the Tasman Region using aerial dusting.

Plantings increase each year. Trees are planted at 500 to 600 stems per ha. After 

9 years trees are generally about 8 to 9 m in height. Pruning would be necessary to 

produce the clear heart redwood prized by the market. However the species responds 

to moderate or heavy pruning by producing epicormic branches. Therefore pruning 

trials, which field test pruning of varying intensity and stages of development, are 

ongoing. Ideally trees would be pruned to about 4 m so that a clear log is produced in 

each tree.

Trees are planted with the intent of production of clear saw logs within 25 to 40 

years. New Zealanders recognize that consistent quality is going to be vital when it 

comes time to develop an export market. If the clones selected today produce timber 

with traits such as durability, high specific density, good heart color, and small knot 

size, the market return should dramatically exceed that from radiata pine, and this 

group of creative researchers and land managers will have developed yet another 

valuable forest product and a source of foreign exchange for New Zealand. 

Acknowledgments

Thanks to Robert Appleton, Russell Coker, Simon Rapley, and Bill Libby for 

sharing their insights, which contribute to this paper. 

References

Brown, I.; Low, C.; McConnochie, R.; Nicholas, I.; Webster, R. 2011. In: Nicholas, I., editor. 

Best practice with farm forestry timber species. No. 3. Redwoods. (Chapter 3, Site 

selection). www.nzffa.org.nz/special-interest-groups/sequoia-action-group).

Cown, D. 2008. Redwood in New Zealand – an end-user perspective. New Zealand 

Journal of Forestry 52(4): 35-41.

Nicholas, I., editor. 2011. Best practice with farm forestry timber species. No. 3. 

Redwoods. www.nzffa.org.nz/special-interest-groups/sequoia-action-group.

Nicholas, I.; Silcock, P.; Webster, R. 2011. In: Nicholas, I., editor. 2011. Best practice with 

farm forestry timber species. No. 3. Redwoods. (Chapter 9, Economic analyses). 
California’s Coast Redwood in New Zealand 

615

O’Neill, G.M. 1975. Forestry production and planting targets. New Zealand Journal of 

Forestry 20(1): 72-82.

617

Subdivide or Silviculture: Choices Facing 

Family Forest Owners in the Redwood 

Region1

William Stewart,2 Shasta Ferranto,3 Gary Nakamura,2 Christy 

Getz,2 Lynn Huntsinger,4 and Maggi Kelly2,4

Abstract

Families or family businesses own nearly all of the private redwood forestland in California. 

Family forest owners have practiced both subdivision and silviculture for decades but the 

dominant theme for most family owners is environmental stewardship. Parcel size is more 

important than expressed values as a predictor of resource management activities. All 

landowners with more than 50 acres undertook high levels of resource stewardship regarding 

controlling invasive species, protecting water quality, improving fish and wildlife habitats, 

and removing individual trees to promote forest health. Timber harvesting was undertaken by 

80 percent of the ownerships with 500 acres or more, but became progressively less common 

for smaller ownerships. Sustainable timber production is the most significant legal revenuegenerating alternative to real estate for forest properties. Unlike most other resource 

management activities that are discretionary, timber harvesting in California can require 

permission from up to five state agencies and three federal agencies. High transaction costs 

limit involvement to forest owners with both large land holdings and strong skills in business 

management. It is not inconceivable that California’s forest ownership pattern could become 

more like Washington State over time where small rather than large holdings represent the 

majority of family forestland. 

Key words: family forests, land use change, sustainable forestry, timber harvesting 

Introduction

Over the past 40 years, resource management of private lands in the redwood 

region has been a source of controversy as old growth redwood forests were logged 

and regenerated, wild and hatchery raised salmon populations fluctuated, and 

invasive species such as Phytophthora ramorum (cause of Sudden Oak Death) spread 

rapidly. A recurring theme in the public debate is whether timber harvesting is 

positively or negatively correlated with environmental stewardship activities. While 

the practices of the large industrial ownerships of forestland are well known due to 

their extensive permitting and planning documents, much less is known about 

resource management practiced by families with smaller ownerships. To increase 

understanding of the family owned forest and rangeland properties, a team of 

 

1 A version of this paper was presented at the Rredwood science symposium, June 22-24, 2011, Santa 

Cruz, California. 2 Extension Specialists, Department of Environmental Science, Policy, and Management (ESPM), 130 

Mulford Hall MC # 3114, University of California, Berkeley, CA 94720-3114. 

(billstewart@berkeley.edu, ferranto@berkeley.edu). 3 Graduate Student Researcher, Department of Environmental Science, Policy, and Management 

(ESPM), 130 Mulford Hall MC # 3114, University of California, Berkeley, CA 94720-3114. 4 Professor, Department of Environmental Science, Policy, and Management (ESPM), 130 Mulford Hall 

MC # 3114, University of California, Berkeley, CA 94720-3114. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

618

University of California Cooperative Extension and campus-based researchers 

surveyed California forest and rangeland owners in 2008. This paper uses a 

subsample of forest landowners (half from coastal forests and half from inland 

forests) to test hypotheses concerning resource management on family forests. We 

conclude with some hypotheses on the potential interaction of resource management 

and forest ownerships over the coming decades. 

Methods

A mail questionnaire was sent to a sample of forest and rangeland owners on 

parcels greater than 3 acres in size from 10 representative counties in California. The 

counties included in the study were Humboldt, Sonoma, Mendocino, Shasta, Sierra, 

Plumas, El Dorado, Santa Barbara, San Diego, and Contra Costa. 

Within each county, individual survey recipients were selected based on a 

stratified random sampling design. The sample was drawn from a statewide land 

parcel database created in 2003 by CalFire for the Forest and Range Assessment 

(CDF 2003). Parcel size was then sub-categorized into four groups: 3 to 9 acres, 10 to 

49 acres, 50 to 499 acres, and greater than 500 acres. Equal samples were pulled from 

each size category. The resulting sample demographics have more small and medium 

size landowners compared to the proportion of total private forest and range land they 

own (Butler 2008). Due to the high standard errors on statewide estimates and the 

large variation in county-to-county forestland ownership patterns, definitive regional 

implications cannot be drawn from the statewide data analyses. The greater value 

comes from insights into factors such as ownership size, values, affluence, and local 

residency on resource management actions. 

A statewide subsample of 200 forest owners was taken from the 670 forest and 

rangeland respondents for this analysis. Although only half of the forest owner 

respondents were from Sonoma, Mendocino and Humboldt counties, we used the 

total data set of statewide forest owners to provide greater statistical power. There 

was no statistically significant difference in the level of resource management 

activities between the coastal and inland forest areas. 

Results and discussion 

The survey results also included responses related to positions, values, actions, 

and additional information requests. We used the answers they provided on a 17-part 

question on their reasons for owning their land to create four unique groups based on 

environmental, family and community, and financial values (table 1). The results

were analyzed using the K means cluster routine in the JMP software program (SAS 

Institute 2009). We gave the resulting four groups different names that match the 

results of Butler et al. (2007) in their analysis of a nationwide data set of family forest 

owners. It is important to note that our ‘forest investor’ group often own multiple 

parcels and had considerably larger ownerships than the other groups. 

The names given to the different values-based clusters capture a dominant trait of 

each group. The percentages in the following tables refer to the number of answers 

that considered an attribute to be an important reason for forestland ownership. 
Subdivide or Silviculture: Choices Facing Family Forest Owners in the Redwood Region 

619

Table 1—Summary of characteristics of California family forest owners clusters based on 

environmental, family and community, and financial values. 

Forest 

investor

Business 

family

Gardener 

family

Inheritor

Percent of total sample 16% 49% 22% 13%

Butler et al. (2007) typology Supplemental 

income

Working 

the land

Woodland 

retreat

Ready 

to sell

Sample Size 30 91 41 25

> 50 acres 25 43 18 10

< 50 acres 5 42 23 14

No size reported 0 6 0 1

Median size in acres 1260 50 40 35

Reasons to own forestland

Environmental values (n=5) 51% 71% 79% 20%

Family and community values (n=6) 16% 58% 56% 26%

Financial values (n=11) 50% 45% 23% 27%

The forest investor type captured all of the very large land holdings in the sample 

and was the only group where less than half the group did not live on the land or 

within 50 miles. Notwithstanding their moniker and large land holdings, their median 

annual income was considerably lower annual incomes than either of the two family 

groups. Annual income did not have a significant positive or negative influence of 

resource management actions across the whole sample. While the two family types 

have very similar values on most topics, the business family group had a stronger 

focus on the positive financial values related to owning forestland. The gardener 

family appears to most closely represent the archetypal city dweller that chose to 

move to a rural area. The inheritor group (the ‘ready to sell’ group in the Butler 

(2007) typology) generally had lower incomes, less interest in a children-friendly 

environment, and a greater interest in selling rather than managing the forestland. 

Table 2 provides demographic information on the specific responses used to create 

the groups in the preceding table. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

620

Table 2—Positive responses to “reasons for owning land” questions from family forest 

owners in the University of California Landowner survey. 

UC Landowner Survey 

Family Forest Typology

Forest 

investor

Business 

family

Gardener 

family

Inheritor

Sample Size 30 91 41 25

DEMOGRAPHICS

live on land or nearby 37% 59% 78% 72%

income > $100,000/year 37% 45% 51% 20%

retired 20% 36% 37% 28%

timber/range job 20% 19% 15% 8%

ENVIRONMENTAL

protect environment 80% 68% 83% 4%

grow own food 0% 44% 59% 4%

preserve open space 67% 67% 85% 8%

live near natural beauty 50% 95% 98% 52%

recreational opportunities 57% 81% 68% 32%

simpler life 13% 84% 80% 44%

FAMILY AND

COMMUNITY

small community 20% 82% 76% 28%

good to raise children 13% 54% 61% 20%

escape city crime pollution 20% 87% 68% 36%

ex-city dweller 37% 32% 49% 36%

close to friends and family 0% 36% 15% 16%

connect to higher power 10% 31% 46% 0%

FINANCIAL

add land 73% 46% 2% 20%

source of income 53% 40% 15% 16%

support local economy 43% 27% 17% 4%

family tradition/business 47% 52% 34% 16%

good financial investment 80% 82% 15% 36%

land appreciation 80% 84% 32% 52%

harvest timber 67% 38% 27% 32%

approached to sell 53% 36% 39% 36%

will sell 3% 12% 7% 32%

will give to children 47% 73% 68% 52%

will donate 0% 0% 0% 0%

How long have families owned their land? 

The large number of willing buyers and willing sellers of family forestland in 

California as well as succession within families has led to a significant turnover in 

family forest ownership. Figure 1 compares the length of time the forest property has 

been in the family for the different clusters. Both the business family and the 

gardener family had very high percentages of relatively recent land purchases. Across 

all groups, nearly 80 percent of the current owners became owners of their property 

after 1970. 
Subdivide or Silviculture: Choices Facing Family Forest Owners in the Redwood Region 

621

Figure 1—Length of time of family forest ownership. 

Is ownership size or values the more important driver of 

resource management actions? 

In addition to responses on positions (e.g., “I would like access to more land for 

hunting and fishing in my area”), and values (e.g., “I own land to help protect the 

environment”), we also collected responses on resource management activities 

undertaken by landowners. We used a small subset of those action responses that 

range from simple (remove exotics by pulling up weeds) to complicated (file a timber 

harvest plan) to compare the actions undertaken by different sub-samples of owners. 

Figure 2 illustrates the resource management activities undertaken by the four 

value-based clusters for the medium and large ownerships (greater than 50 acres). 

Figure 2—Resource management activities for ownerships larger than 50 acres by 

value group.
GENERAL TECHNICAL REPORT PSW-GTR-238 

622

Among these ownerships, all the owners with strong environmental, family and 

community values also reported high levels of environmental stewardship activities. 

There was less consistency with regard to timber harvesting across the value-based 

clusters. 

As shown in fig. 3, ownership size had more explanatory power across the range 

of resource management activities. The first five actions in both figures require 

expenditures of time and money by the landowner and can be considered as 

environmental ‘gifts’ since the benefits spill over across the landscape. It is 

noteworthy that few of the forest landowners reported being recipients of cost share 

awards or grants for these activities. They also did not have positive opinions 

regarding the quality of management advice they received from state and federal 

agencies associated with water quality and habitat issues. (Ferranto et al.5

). Overall, it

is apparent that forest owners with parcels larger than 50 acres are willing to invest 

considerable amounts of their own resources in environmental stewardship. Timber 

harvesting was practiced by 80 percent of owners with 500 acres or more, but 

dropped by half for each successively smaller ownership size class in our study.

Figure 3—Resource management activities by ownership size.

For ownerships larger than 50 acres, there is a strong correlation between timber 

harvesting and four of the five other resource management activities. Table 3

summarizes the probability of an owner with more than 50 acres undertaking an 

action as a function of whether they reported timber harvesting. 

 

5 Ferranto, S.; Huntsinger, L.; Stewart, W.; Getz, C.; Nakamura, G.; Kelly, M. 2011. Consider the 

source: the impact of media and authority in outreach to California's forest and rangeland 

owners. Unpublished. 
Subdivide or Silviculture: Choices Facing Family Forest Owners in the Redwood Region 

623

Table 3—Correlation between environmental stewardship activities and timber harvesting 

for forest ownerships larger than 50 acres (n=96).

Environmental 

stewardship activity

Harvest 

timber

Do not 

harvest 

timber

p value

Remove exotics .525 .457 .5245

Improve water quality .738 .389 .0007

Improve riparian habitat .721 .389 .0012

Improve wildlife habitat .836 .486 .0003

Cut trees for forest health .921 .500 .0001

When the two analytical approaches are compared, ownership size has a much 

stronger explanatory effect than the expressed values, especially for ownerships 

larger than 50 acres. Timber harvesting was less common than the other activities for 

most forestland owners. Unlike most other resource management activities that are 

discretionary, timber harvesting in California can require permission from up to five 

state agencies and three federal agencies. Done successfully, it can provide enough 

revenue to justify the ownership of land that has a high market value for alternative 

uses. The relatively low percentage of timber harvesting among medium (40 percent) 

and small (20 percent) sized ownerships suggests that there are a significant 

disincentives involved to this activity.

Does ‘local’ matter? 

Since many of the environmental stewardship outcomes can only be appreciated 

by the owners if they visit the land regularly, we tested whether having a primary 

residence on the forestland or living within 50 miles of the forest property had an 

impact of resource management activities (table 4). For ownerships larger than 50 

acres, the ‘local’ bonus varied from 19 percent to 49 percent. The flip side is that 

non-local forest owners are considerably less active in both environmental 

stewardship and timber harvesting activities. 

Table 4—Influence of local residency on resource management activities for ownerships 

larger than 50 acres. 

Remove 

exotics

Improve 

water 

quality

Improve 

riparian 

habitats

Improve 

wildlife 

habitats

Cut 

trees for 

forest 

health

Harvest 

timber

Not Local

(n=42)

45% 51% 50% 56% 67% 48%

Local (n=56) 54% 68% 70% 81% 87% 71%

Local/Non 

Local ratio

1.19 1.33 1.40 1.45 1.30 1.49

How many forest ownerships are at risk of getting smaller in 

the redwood region? 

The preceding analysis illustrates very strong resource management values and 

actions among family forest owners in California with more than 50 acres of 

forestland. They place considerable value on the self-provision of environmental 

outcomes such as improved water quality, fish and wildlife habitats, and forest health 

or resiliency. Although their goals seem to match those of the regulatory agencies, 
GENERAL TECHNICAL REPORT PSW-GTR-238 

624

there appears to be only limited cooperation. However, the general trend of 

increasing real estate prices compared to flat or declining commodity prices suggests 

that current land use and resource stewardship patterns could change. The following 

figures (fig. 4, fig. 5) show the distribution of forestland by parcel size (large 

ownerships are typically comprised of a number of medium sized parcels) for 

Sonoma, Mendocino and Humboldt counties. There are large acreages that 

potentially could be owned and managed as much smaller operational units without 

any need to request a parcel split. 

Figure 4—Area of forestland in family and business ownership in Sonoma, 

Mendocino, and Humboldt Counties. 

While the rates of other environmental stewardship activities were positively 

correlated with timber harvesting, only timber harvesting generates revenue. For all 

forest landowners, there is a vibrant real estate market ready to purchase the 

ownerships ‘as is’ or to be further broken down into smaller units. California 

currently has a distribution of family forest ownerships very similar to Oregon where 

larger ownerships comprise most of the family forestland. However, the comparative 

economic advantages of non-timber valuation for small and medium sized 

ownerships could shift family forest ownership patterns towards those of Washington 

state. 
Subdivide or Silviculture: Choices Facing Family Forest Owners in the Redwood Region 

625

Figure 5—Distribution of family forestland in California, Oregon, and Washington 

(from Butler 2008).

Conclusion 

Families own a substantial portion of the forests of the redwood region. Most of 

these parcels have changed ownership in the past forty years. Family forest owners 

have practiced both subdivision and silviculture for decades but the dominant theme 

for most family owners is environmental stewardship. The results of a 2008 survey of 

forest landowners documented very high levels of environmental stewardship 

activities that produce no revenue and provide benefits that extend beyond the 

property boundaries. Environmental stewardship actions were positively correlated 

with timber harvesting. All actions were more common for ownerships larger than 

500 acres and declined as ownerships became smaller. It is smaller ownerships, 

however, that would be most affordable to the next wave of urban and suburban 

residents who would like to buy their own forest retreat. While the goals of stricter 

state environmental quality regulations seem to be closely aligned with the goals of 

most family forest owners in California, there does not appear to be much mutual 

recognition of common goals. The survey data also suggests that the high transaction 

costs limit involvement in timber harvesting to forest owners with large land holdings 

and strong skills in business management. Since sustainable timber production is the 

most significant legal alternative to real estate sales as a means for generating 

revenue from forest properties that are too large to be used as a single residential 

property, it is not inconceivable that California’s forest ownership pattern would 

become more like Washington State over time where small rather than large holding 

represent the majority of family forest land. 

References

Butler, B.J. 2006. Family forest owners of the United States. Gen. Tech. Rep. NRS-27. 

NewTown Square, PA: U.S. Department of Agriculture, Forest Service, Northern 

Research Station. 72 p.

Butler, B.J.; Tyrrell, M.; Feinberg, G.; VanManen, S.; Wiseman, L.; Wallinger, S. 2007. 

Understanding and reaching family forest owners: lessons from social marketing 

research. Journal of Forestry 105: 348-357.
GENERAL TECHNICAL REPORT PSW-GTR-238 

626

[CDF] California Department of Forestry and Fire Protection. 2003. The changing California: 

forest and range 2003 assessment. Sacramento, CA: California Department of Forestry 

and Fire Protection. Fire and Resource Assessment Program.

SAS Institute Inc. 2009. JMP® 8. Introductory guide. Second edition. Cary, NC: SAS Institute 

Inc.
627

Is it Economical to Manage Jointly for Wood 

and Carbon Under the Climate Action 

Reserve Protocol?

Richard P. Thompson1 and Steve R. Auten1

Abstract

To quantify the benefits and costs of modifying forest management for additional climate 

benefits, Cal Poly’s Swanton Pacific demonstration forest was used to test the Climate Action 

Reserve’s protocol and identify management strategies for both wood and carbon markets. 

Residing in the Southern Sub-district with its clearcutting restrictions, Swanton offers an ideal 

test site for landowners transitioning from even-aged to uneven-aged management. However, 

the increased minimum baseline condition for the region effectively precludes joint 

production of wood and additional carbon. The much lower baseline on the North Coast could 

allow for a joint production strategy that could meet some landowners’ goals.

Key words: baseline condition, carbon registry, climate action reserve, CO2e, forestry-offset

Introduction

The perception of an impending ‘cap and trade’ system for greenhouse gases in 

the United States has spurred the growth of tradable carbon-storage credits, or 

offsets, from a wide range of proven and new sequestration technologies. One of the 

most obvious is to add forests, known as forestry-offset projects, since trees are the 

only plants that retain woody tissue comprised of about 50 percent carbon by weight. 

Another reason for interest in forests for sequestering carbon is they are relatively 

inexpensive to establish and also provide a host of other environmental services. 

Nevertheless, there are a number of obstacles in the path toward full use of forestryoffset projects in meeting national and international policy goals on reducing 

atmospheric greenhouse gas (GHG) emissions.

For carbon-storing forestry-offset projects to be viable, the net revenue from 

carbon services must be competitive with expected cash flow for the forest 

landowner. This can be fairly low for forest landowners who prefer a reduced or zero 

harvest rate but will be much higher for forest landowners managing their land for 

maximum sustained harvest levels. The costs of additional inventory and monitoring 

actions required by carbon exchange protocols loom as a major issue in 

competitiveness (Mader 2007, Rudell et al 2007). Assuming that additional carbon 

inventories can be counted as a tradable benefit, Simpson (2008) reports that minor 

modifications for carbon storage of loblolly plantation management on a 30-year 

rotation can increase rates-of-return from 7.0 percent to 9.2 percent (NPVs from 

$364/ac to $520/ac) with just $5/tonne CO2e prices, if all three CCX forestry-offset 

 

1 Professor and graduate student, respectively, Natural Resources Management Department, California 

Polytechnic State University, San Luis Obispo, CA 93407. (rpthomps@calpoly.edu; 

sauten@calpoly.edu). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

628

protocols are used. He also noted that carbon monitoring and trading costs were 25 

percent of the carbon revenue and that thinnings have a negative effect on carbon 

revenues. The CCX offset market closed in 2010 and is quite different than the CAR 

protocols (CAR 2010) that are better known in California. The goal of our research is 

to provide small to medium-sized forest landowners with information on carbon 

credits available under uneven-aged management, the costs of offering carbon credits 

on the market, and the likelihood of receiving sufficient revenues that justify the 

investment. 

Forestry-offset projects – the basics

Although forestry-offset projects have been voluntarily used worldwide to 

comply with Kyoto, they remain controversial due to the transitory, albeit long-term, 

nature of trees. The CCX, and the more recent CAR protocols, use verifiable 

standards that forestry-offset projects must satisfy in order to “sell” carbon credits. 

The interpretation of the following four accounting issues are very important in how 

many offset credits are considered marketable for any individual project.

1. Permanence – sequestered carbon must be long-term to be of value in 

mitigating climate change.

2. Additionality – forest management must result in additional carbon storage in 

the forest and where the harvested products are used that would not have 

occurred with business-as-usual (“Common Practice”), estimated over a 100-

year time horizon. 

3. Baseline – carbon that would have been stored in lieu of new activities to 

store additional carbon, aka, business-as-usual.

4. Leakage –increased carbon storage can induce reduced carbon storage due to 

higher local timber prices, those leakages must be subtracted from the 

measured local benefits.

There are a growing number of carbon registries for forestry and other offset 

projects.2

 The CAR protocol is one of the newest (Version 2.1 in 2007, Version 3.2 

in 2010); this study used Version 3.2. 

Climate Action Reserve offset projects

The Climate Action Reserve (CAR or the “Reserve”), the successor to the 

California Climate Action Registry, is a non-profit organization created by the State 

of California in 2001 to “promote and protect businesses early actions” designed to 

reduce or offset their GHG emissions (CAR 2010). The Reserve is financed by GHG 

emitters interested in creating tradable offset credits that will presumably be less 

expensive than other forms of GHG reductions. It includes a number of detailed and 

very specific protocols, setting high standards for those applying to sell carbon 

storage credits. Climate Reserve Tonnes (CRTs or “carrots”) can be sold to parties 

that want to offset current emissions or resell these offsets when there is a state or 

national system of required emission reductions. 

 

2 for example, American Carbon Registry (Environmental Resources Trust. Winrock International 

1996), Verified Carbon Registry System (Verified Carbon Standard Association, Version 2, October 

2006); Markit Environmental Registry (formerly TZ1. 2009).
Is it Economical to Manage Jointly for Wood and Carbon Under the Climate Action Reserve 

Protocol?

 

629

Figure 1 illustrates the distribution of the CAR’s offset projects. “Listed” 

projects are those that have been submitted to the Reserve but have not been verified 

yet by a Reserve-approved auditor. Once verified, the project is then “Registered” 

with a specific number of CRTs per year (known as “vintages”). The most common 

Reserve projects are offsets for landfill gases, nearly half of which have been 

registered. There are three types of forestry offset projects: (1) Reforestation, (2) 

Improved, formerly Conservation-Based, Forest Management (IFM, CFM), and (3) 

Avoided Conversion. Forestry-offset projects are the third largest in number among 

all projects. Although IFM/CFM are the most common among forestry-offset 

projects, only four have been registered: Lompico Forest Carbon Project in Santa 

Cruz with 11,708 CRTs in 2010, Garcia River Forest in 2004 with 715,268 CRTs 

from five vintages, The van Eck Forest with 274,403 CRTs from four vintages (2006 

to 2009), and Big River/Salmon Creek Forests in 2007 with 736,517 CRTs from 

three vintages. Thus far, all registered forestry-offset projects are in the coast 

redwood region of California, and all three CFM registered projects are in the North 

Coast redwood region. However, none of these projects involve managing for carbon 

without significant reduction in (or elimination in Lompico’s case) timber 

production. 

Figure 1—Climate action reserve offset projects. 

Climate Action Reserve forestry-offset protocol

CAR’s forest-offset protocol has gone through five iterations with the first 

announced on June 13, 2005 and the current version (3.2) approved on August 31, 

2010. Listed and Registered projects can differ in requirements and standards 

depending upon the protocol version pertinent at the time of listing. Calculating 

CRTs under the IFM protocol is an involved and costly process. The process 

described hereafter greatly simplifies what is a much more detailed calculation.

One starts with an inventory of the subject forest property; this sets the year of 

the CRT vintage. Precision has a significant effect on available CRTs, where a 
GENERAL TECHNICAL REPORT PSW-GTR-238 

630

sampling error (SE) greater than 20 percent eliminates any carbon credits, from 5.1 to 

20 percent reduced CRTs by 5 percent, and 5 percent SE or less has no deduction. 

Inventories should include all standing timber with volumes estimated using CARapproved cubic foot volume equations for tree boles. Next total above-ground metric 

biomass is calculated where bark and live crown biomass is added based on species 

and diameter. Carbon biomass is 50 percent of total above-ground bone-dry biomass 

which is then converted to metric tonnes (0.001 tonnes/kg). Under the current 

protocol, carbon weight must be converted to CO2 equivalent (CO2e) to represent the 

atmospheric effect of CO2 emissions on climate (carbon tonnes x 3.67). Thus the 

Actual Above-ground, Live Carbon Stock (AC) in year y is calculated as follows: 

AC (CO2e) = Σ (cfvoli)(kg/cfi)(0.5 C)(.001 C tonnes/kg)(3.67 CO2e/tonne), 

where i = species

 The CAR protocols are based on creating offsets for owners who hold higher 

than ‘average’ inventories (common practice). While half of all parcels are going to 

be above the regional average in any case, the 100 year contract would require 

owners to maintain a high inventory for the following century. 

Once AC is calculated, one then determines the minimum baseline (MBL). First, 

the carbon stock based on the Common Practice (CP) for the Assessment Area of the 

subject project is obtained from Appendix F of the protocol. The Common Practice 

for Version 3.2 was estimated using Forest Inventory and Analysis (FIA) plots on 

private forestlands. The equation for MBL depends on whether the initial carbon 

stock (actual above-ground carbon stock, AC) is greater or less than CP. The 

following MBL equation is used when AC > CP. 

MBL = max (CP, min(AC, CP+AC-WCS), 

where WCS is the weighted average of above-ground AC for all 

 landholdings in addition to the subject property. If there are none, then 

AC = WCS, resulting in MBL = CP.

At this stage, it is important to estimate whether there exists any additionality as 

a result of the Initial Carbon Stock (ICS) being greater than the MBL If not, the 

remaining calculations are unnecessary since there is no additionality available in the 

ICS. Further, additionality per CAR protocol is only derived from existing, not 

predicted (from growth & yield modeling), carbon stocks. 

If additionality appears to exist, one proceeds to model the baseline carbon stock 

(BC) for all required (in other words, live, above-ground timber) and optional carbon 

pools (e.g., shrubs, soil) through a series of growth and yield cycles over 100 years. 

This is needed to demonstrate that carbon credits (CRTs) can be maintained based on 

reliable predictions. The model must reflect all legal and financial constraints. The 

average of the growth and yield results is used for the BC calculation and must not 

fall below MBL. 

If AC is predicted to still be greater than BC, one then adds below-ground 

biomass and standing dead biomass estimates to AC, along with other optional 

carbon pools. Interestingly, the equation for below-ground biomass (BBD) is an 

exponential functional of above-ground biomass (ABD) regardless of species [BBD 

= exp(-0.7747 + 0.8836 x ln(ABD))]. Equation 6.1 provides the calculation that leads 

to CRTs, or Quantified Reductions (QR) for each year’s (y) carbon stock: 
Is it Economical to Manage Jointly for Wood and Carbon Under the Climate Action Reserve 

Protocol?

 

631

QRy – [(∆ C onnsite - ∆BC onnsite) + (ACwood products, y - BCwood products, y ) x 80 

 percent + SEy] + Ny-1

where,

∆AC = (AC onnsite, y)(1-confidence deduction y) - AConnsite, y-1)(1-confidence 

 deduction y-1), if y is the first year, then (AC onnsite, y-1) = 0. 

∆BC = (BC onnsite, y)(1-confidence deduction y) - BConnsite, y-1)(1-confidence 

 deduction y-1), if y is the first year, then (BC onnsite, y-1) = 0. 

ACwood products, y = actual carbon in wood products produced in year y projected 

to remain stored for at least 100 years.

 BCwood products, y = average annual baseline carbon in wood products that would

have remained stored for at least 100 years.

SE = Secondary Effect GHG emissions caused by the project activity in

year y. 

 N = Any negative carryover from the prior year (see footnote 9, p. 38 

 Version 3.2). 

The first two terms are referred to as the Primary Effect. Wood products can 

either be processed by mills, with adjustments for mill efficiency, or “stored” in 

landfills for some types of projects. The 80 percent adjustment is intended to model 

market response to reduced wood product production where every tonne diverted to 

carbon storage will be compensated with an increase in harvesting 0.2 tones on other 

lands, i.e., leakage. While the 20 percent leakage may be a realistic estimate of local 

substitution, leakage at the timber market scale for North America has been estimated 

at over 80 percent (Murray et al. 2004). Wood residues that are harvested but used to 

generate energy are also ignored in the CAR accounting system. Over a 100 year 

lifetime, wood used for energy can constitute over half of initially harvested volume 

(Smith 2009). 

Once QR is calculated, all remaining deductions (mainly risk of loss/reversal) are 

formula-driven. These deductions address the financial, managerial, social and 

natural disturbance risks that could result in release of CRTs. Finally, CRTs are 

reduced by the calculated risk percentage, and contributed to a Buffer Pool. However, 

as with leakage, little or no scientific support or rationale is offered for these 

constants. Table 6.4 of the Protocol provides a step-by-step procedure for these 

calculations. 

The Lompico Project – an example

To exemplify the Version 3.2 protocol, the Lompico project was chosen for two 

reasons. First, it’s the only CAR forestry-offset project adhering to the current 

protocol; the other earlier registered forestry projects were not required to provide as 

much information. Second, Lompico is in the Southern Sub-district of the Coast 
GENERAL TECHNICAL REPORT PSW-GTR-238 

632

district where this study’s project is located. The only drawback to Lompico for our 

purposes is their management objectives exclude timber harvesting.

Lompico, located about 10 miles north of Santa Cruz, was purchased by the 

Sempervirens Fund from Redwood Empire Co. as part of the Fund’s mission to 

preserve redwood forestland. Carbon storage from precluding timber harvests on 285 

ac of Timber Production Zone (TPZ) parcels within the 425 ac ownership was the 

basis for their application for IFM carbon credits through the Reserve.

First, Common Practice (CP) was determined to be 280 CO2e tonnes/ac

according to the protocol in order to establish the minimum baseline (MBL). Version 

3.2 increased CP to 280 CO2e tonnes/ac from the earlier version’s 224. The new CP 

is quite high for the average of managed timberlands in the Santa Cruz and San 

Mateo Assessment Area, an issue that will be addressed again later in the paper. 

Second, the Fund’s initial carbon stock in 2007 was estimated at 322 CO2e tonnes/ac 

(with a 5.6 percent SE). Next, growth and yield modeling was performed based on 

thinning 30 percent of the timber greater than 18” DBH, giving a baseline condition 

(BC) that averaged slightly above MBL. Subtracting BC from the ICS resulted in 42 

CO2e tonnes/ac (11,970 total) of additionality for the 2007 vintage (fig. 2). Further 

additionality is derived from timber growth from the inventory date to the CAR 

application - 2008 and 2009 vintages of about 4 CO2e tonnes/ac each year.

Figure 2—Lompico modeled baseline condition for live, above-ground

carbon stocks. 

What remains to determine CRTs after the calculation of the carbon stock is 

much smaller in magnitude but more detailed in procedure. After calculating the 

below-ground carbon stock, the second part of the Primary Effect is to calculate net 

wood product carbon stocks - planned harvests less baseline harvests. This is 

followed by estimates that are essentially deductions required to ensure permanency 

and avoid risks of human and naturally caused losses. In Lompico’s case the net 

harvest carbon storage was negative because of the Fund’s non-harvest philosophy. 

In the end, Sempervirens Fund was successful in selling 11,798 CRTs. 
Is it Economical to Manage Jointly for Wood and Carbon Under the Climate Action Reserve 

Protocol?

 

633

Swanton Pacific Demonstration Forest – Valencia Unit

Cal Poly owns two properties in Santa Cruz County for education and research – 

Swanton Pacific Ranch (3200 ac) near Davenport, and Valencia (620 ac) near Aptos. 

The Valencia unit is almost completely forested with the following characteristics:

• 480 ac of redwood-fir production lands. 

• 60 percent redwood, 10 percent Douglas-fir, 30 percent hardwoods. 

• Average high Site Class III.

• Areas with two to three age-classes from light thinnings in the 60s and 70s. 

• Well-stocked, over 40 mbf/ac in conifer volume, 260 BA. 

• FSC certified, approved NTMP. 

Both forested properties are managed for educational and research purposes. 

Southern Sub-district Rules prohibit even-aged management. Valencia is managed 

for an uneven-aged structure using Guilden’s BDq model is to guide silvicultural 

decisions (Guilden 1991). Fig. 3 displays the current Valencia structure for the 

average stand compared to the BDq guide curve, with the following residual stand 

parameters: BA = 175 ft2

/ac, max DBH = 34”, DeLiqourt’s q = 1.15. 

Figure 3—Current average Valencia stand structure compared 

to the target stand structure.

Although Valencia has a CFI system in-place and was scheduled for reinventory, the Lockheed fire at Swanton delayed it making it necessary to install a 

separate inventory for this project. A VPS inventory was conducted in August 2010 

according to the CAR protocol at a cost of $5000, resulting in the volume estimate 

stated above. Inventory costs were somewhat less than normal since DBH and height 

data were available from past CFI inventories. The sampling error was only 1.8 

percent, thus no CAR deduction is necessary. The live, above-ground carbon stock 

was calculated to be 376 metric tonnes/ac of CO2e. 

As shown in the Lompico Carbon Project, the Santa Cruz Assessment Area’s CP 

is 280 CO2e tonnes/ac (MBL). Since Valencia’s ICS > MBL, it may appear that 

additionality exists, but the average baseline carbon stock projected over 100 years 
GENERAL TECHNICAL REPORT PSW-GTR-238 

634

must also exceed MBL. No reasonable harvest level could be found such that the 

average baseline carbon stock exceeded MBL. This is not economical since current 

stumpage prices of around $500/thousand board feet (BOE 2011) are far above the 

$10/metric ton of CO2 (roughly equivalent to a stumpage price of $75/mbf). 

North Coast uneven-aged management for wood and 

carbon

The initial concept for a carbon project on Cal Poly’s forest properties in Santa 

Cruz County presumed revenue possibilities existed based on earlier Protocol 

versions. However, the current version raised CP so high as to preclude joint timber 

and carbon management at Valencia. A possible explanation for this high value will 

be discussed at the end of this paper. Nevertheless, an opportunity for combining 

wood and carbon production exists on the North Coast where CP on equivalent “low” 

site quality is drastically lower - 165 CO2e tonnes/ac (even North Coast high site is 

only 188 tonnes). Therefore, we propose to describe Valencia’s carbon-offset 

potential as if it were in the heart of the coast redwood region, where Sub-district 

rules do not apply. 

Figure 4 illustrates two sustained yield analyses: (1) baseline condition (BC) growth 

and harvests that are sustainable where the average carbon stock is at or above 

Common Practice (MBL), and (2) the average actual carbon (AC) resulting growth 

and yield modeling using residual stand BDq parameters stated above. The BC 

analysis reduced growing stock to about MBL, required a longer 15-year growing

cycle. The average carbon stock was about 165 CO2e tonnes/ac, or about 20 

tonnes/ac greater than the Sub-district’s MBL.

Figure 4—Sustained yield analysis for both baseline condition and

uneven-aged timber management objectives.

Sustained yield analysis for the actual carbon stock started with a thinning that 

somewhat aggressively reduced live, above-ground CO2e from 376 to about 230 

tonnes/ac by harvesting nearly all trees above max DBH and drastically reducing the 

hardwood component. This reduced standing volume from about 43 mbf/ac total to 

about 28 mbf/ac. Afterward, a 10-year thinning cycle varies roughly between a 

residual volume of 28 mbf/ac and growing to 38 mbf/ac. The result is a growth rate 
Is it Economical to Manage Jointly for Wood and Carbon Under the Climate Action Reserve 

Protocol?

 

635

of approximately 1000 bf/ac/yr, or 3.5 percent/yr. At a stumpage price of at least 

$500/mbf, that is an annualized revenue of $240,000. It would not make economic 

sense to substitute this one-time carbon revenue for this wood product income 

stream, even at conceivably higher carbon prices.

If a forestland owner in the North Coast region were to manage a property like 

Valencia on an uneven-aged management regime as prescribed, there would be an 

Initial Carbon Stock (ICS) well-above the North Coast MBL, providing about 65 

tonnes/ac of additional live, above-ground CO2e carbon stock. Further additionality 

from below-ground carbon adds about another 5 tonnes/ac. (Note that residual carbon 

stocks drop slightly below 230 requiring either adjustments to the sustained yield 

analysis or slightly reducing ICS.)

The remaining term in the Primary Effect is the solidwood product carbon stock. 

Equation 6.1 (CAR 2010) gives credit for actual carbon sold from harvests after 

project initiation, plus the average from predicted harvests, minus the average from 

baseline predicted harvests. The vast majority of the timber would be sold with the 

residues treated as if landfilled. After adjusting for mill efficiency and market 

response, solidwood product carbon stock could add roughly another 35 CO2e 

tonnes/ac, mostly coming from the initial harvest of about 17 mbf/ac. 

Given manuscript size limits, the remaining secondary effects are not described 

in detail. In the end, at least 80 CRT tonnes/ac. should be verifiable, or 38,000 tonnes

toal. At recently heard OTC CO2e prices of $10/tonne, or a one-time revenue of 

$380,000 to compensate for the unharvested volume that must be protected from all 

disturbances for 100 years. Even allowing for estimation error, such revenue certainly 

justifies the cost of application and additional inventories, if necessary. However, one 

must keep in mind that annual reports, periodic inventories and audits are required to 

certify that the live tree CRTs sold remain on site.

Final thoughts

Joint management for carbon and timber under the current CAR protocol can be 

profitable under specific conditions. There appears to be profitable opportunities for 

joint management in regions where the “common practice” reflects stocking levels 

from a balanced range of stand ages. Such is the case in the North Coast redwood 

region; not so in the Sub-district region where heavy cutting 80 to 100 years ago 

spurred regulations requiring higher average stocking, the basis for the CAR’s 

regional baseline. It would not be economical for Sub-district forestland owners to 

substitute carbon for wood production goals at current or conceivable product prices. 

Although Sub-district common practice carbon stocks are expected to be higher 

than on the North Coast, the magnitude of the difference seems unjustified, especially 

when comparing CO2e estimates with equivalent volume and basal area averages in 

Appendix F. One explanation may be due to stratifying FIA plots only by private 

land. However, in Santa Cruz and San Mateo counties, zoning regulations further 

limit lands where timber management is permitted.

This study did not test whether even-aged management offers a joint production 

opportunity but the large price differential between redwood stumpage and generic 
GENERAL TECHNICAL REPORT PSW-GTR-238 

636

carbon prices suggests disadvantages. However, for forestland owners who are 

considering a switch to uneven-aged management may be further encouraged to do 

so with these results. This result should be transferrable to other forest types where 

lower growth rates are offset by lower, more carbon substitutable, wood prices. 

Finally, one wonders what effect contracting to sell CRTs would have on 

property values. Since these contracts “go with the land” (somewhat like a 

conservation easement) limiting management options, property values would be 

reduced, though partially compensated from carbon revenues. Further value 

reductions are likely when a prospective buyer discovers that they are committing to 

annual reporting, inventories and audits. 

Acknowledgments

The authors wish to thank Dr. William Stewart, UC Cooperative Extension 

Specialist, Center for Forestry, for his advice and contribution to this paper. Any 

errors are the sole responsibility of the authors. 

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Ruddell, S.; Sampson, R.; Smith, M.; Giffen, R.; Cathcart, J.; Hagan, J.; Sosland, D.; Godgee,

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Agriculture, Forest Service, Washington Office. 336 p.

Wear, D.N.; Murray, B.C. 2004. Federal timber restrictions, interregional spillovers, and 

the impact on US softwood markets. Journal of Environmental Economics and 

Management 47(2): 307-330.
Monitoring

639

Comparing LiDAR-Generated to GroundSurveyed Channel Cross-Sectional Profiles 

in a Forested Mountain Stream

Brian C. Dietterick,1 Russell White,2 and Ryan Hilburn3

Abstract

Airborne Light Detection and Ranging (LiDAR) holds promise to provide an alternative to 

traditional ground-based survey methods for stream channel characterization and some 

change detection purposes, even under challenging landscape conditions. This study 

compared channel characteristics measured at 53 ground-surveyed and LiDAR-derived crosssectional profiles located in six study reaches of Little Creek, a forested headwater stream on 

Cal Poly’s Swanton Pacific Ranch, near Santa Cruz, CA. Three LiDAR datasets were 

compared in this study, with flights in 2002, 2008, and 2010, a period of rapid improvement 

in LiDAR technology. Visual and statistical agreement between field-surveyed and LiDARderived channel characteristics (bankfull depth, bankfull width, bankfull area, and thalweg 

elevation) show improvement as LiDAR technology has matured. Improvements are 

explained, in part, by the decrease in point spacing along the cross-sectional profiles 

(averaging 3.0 m in 2002, 1.0 m in 2008, and 0.49 m in 2010). Bankfull width was more 

accurately measured than bankfull depth or cross-sectional area. In 2010, two thirds of the 

LiDAR-derived cross-sections provided bankfull width within 10 percent (0.46 m) of the 

field-surveyed width. These initial findings show the improvements in LiDAR capabilities 

over time, though also point to difficulties that remain for remotely measuring channel 

geometry on small, headwater mountain streams. 

Key words: bankfull, change detection, channel, LiDAR 

Introduction

Channel features are currently measured using a variety of ground survey 

techniques (e.g., Harrelson et al. 1994). Field surveys often require significant 

personnel commitments and funding to complete, and may lack the sample density 

(longitudinally along the channel) necessary to describe change throughout the 

system. The prospect of utilizing airborne Light Detection and Ranging (LiDAR) to 

map channel features and detect change over time, has generated considerable 

interest for applications in environmental assessment and monitoring. LiDAR 

technology has become well-established for producing detailed bare-earth Digital 

Elevation Models (DEM). Results from several studies show that LiDAR accuracy 

ranging from ± 0.02 m to 0.30 m root mean square error (RMSE) vertically and 0.15 

to 0.30 m horizontally can be achieved in optimal survey conditions of flat even

terrain, free from obstructions such as vegetation (Csanyi et al. 2005, Frenc 2003, 

McKean et al. 2005, Reutebuch et al. 2003). In mountainous and forested terrain, 

 

1 Professor and Director, Swanton Pacific Ranch, College of Agriculture, Food, and Environmental 

Sciences, Cal Poly State Univ., San Luis Obispo, CA (805)756-6155. (bdietter@calpoly.edu). 2 Research Assistant, Natural Resources Management Department, Cal Poly State Univ.

3 Forester, W.M. Beaty and Assoc.; formerly graduate student, Natural Resources Management 

Department, Cal Poly State Univ., San Luis Obispo, CA.
GENERAL TECHNICAL REPORT PSW-GTR-238 

640

additional sources of error are attributed to terrain slope (Kraus and Pfeifer 1998), 

aspect and topographic ruggedness (McKean et al. 2005), and density of forest 

overstory and understory vegetation (Reutebuch et al. 2003). Other factors pertain to 

flight and sensor parameters of the survey including flying height, aircraft speed, 

pulse rate, scan angle, and positional error imparted from the GPS and IMU (Hyyppä 

et al. 2005). Software processing of LiDAR data can also introduce error through 

mis-classification of bare-earth terrain points, and in the interpolation of the final 

digital elevation model. Despite the additional challenges encountered in 

mountainous terrain, wide consensus has formed supporting the use of LiDAR for

high-resolution terrain mapping (McKean et al. 2005). 

Agreement between ground-surveyed and LiDAR-derived channel features has 

been demonstrated with promising results in the semi-arid grassland and shrub-steppe 

environment of southeast Arizona (Miller et al. 2004) and in the more mountainous 

terrain of northeastern Oregon (Faux et al. 2009). Measuring channel morphology in 

densely forested environments can be more problematic, due to the lower groundpoint densities achieved under dense cover (James et al. 2007). However, given 

sufficient flight and sensor specifications, detailed feature extraction and 

measurement is possible, even in dense forest settings (White et al. 2010). It now 

appears that airborne laser mapping technology is becoming capable of providing an 

alternative to traditional survey methods for at least some measurements of channel 

geometry. 

Approach

Conventional ground survey data are compared to LiDAR-derived measurements 

of channel shape, ultimately necessary for channel characterization and change 

detection purposes. The primary objective of this study was to evaluate and compare 

the accuracy of channel cross-sectional profiles derived from three separate LiDAR

flights. It was hypothesized that LiDAR-derived channel characteristics are visually 

and statistically similar to ground-surveyed channel characteristics. Further goals 

included an evaluation of LiDAR technology to aid the monitoring of geomorphic 

change. 

Study area 

The study site is located within the Little Creek watershed, 22 km north of Santa 

Cruz in the central part of California’s Coast Ranges (fig.1). The Little Creek 

watershed is a 526 ha tributary watershed to Scotts Creek and is partially located 

within Swanton Pacific Ranch. Swanton Pacific Ranch is an education and research 

facility of the California Polytechnic State University promoting informed land 

stewardship. Terrain within the study area is steep and rugged, with elevations 

ranging from 12 m to 488 m and inner gorge ground surface slopes that exceed 80 

percent. The watershed contains approximately 6.5 km of stream length, for a 

drainage density of 1.2 km/km2

. Streams include first-, second-, and third-order 

channels as defined by Strahler (1964), based on the USGS 10 m DEM, topographic 

mapping, and field verification. Average channel gradient ranges from 1.8 percent to 

5.0 percent and the channel type can be characterized as step-pool (Montgomery and 

Buffington 1997). Mean bankfull channel width is approximately 5 m. The mostly 
Comparing LiDAR-Generated to Ground-Surveyed Channel Cross-Sectional Profiles in a Forested 

Mountain Stream

641

forested watershed is dominated by second-growth coast redwood (Sequoia 

sempervirens), and includes components of Douglas-fir (Pseudotsuga menziesii var. 

menziesii) and tanoak (Notholithocarpus densiflora). knobcone pine (Pinus 

attenuata) and brittle-leaf manzanita (Arcostaphylos crustacea) are also found along 

portions of the watershed ridgelines. Mature red alder (Alnus rubra) dominates the 

riparian community and is among the few deciduous overstory species present. The 

percentage of riparian overstory canopy cover ranges from approximately 40 percent 

to 95 percent, with an average of 80 percent. 

Figure 1—Little Creek watershed and locations of study reaches. 

Field survey methods 

As part of the Little Creek Study, a long-term watershed monitoring project 

being conducted at Swanton Pacific Ranch, channel features were surveyed annually 

(2000 to 2011) at six study reaches (A through F) (fig. 1) for the purpose of observing 

channel change over time. The study reaches differ in channel size and shape, valley

confinement, and overstory canopy cover. More complete descriptions of the study 

reaches are found in Hilburn (2010). Annual surveys using traditional ground-based 

surveying methods ensue at the six reaches, each with 10 monumented crosssectional profiles spaced approximately 4.6 m apart over 50 m of stream channel. As 

part of the field survey, characteristics describing geomorphic features, including 

bankfull elevation, thalweg elevation, and edge-of-water are identified. This 

information is used to calculate bankfull depth (bfd), bankfull width (bfw), and 

bankfull area (bfa) for each cross-sectional profile. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

642

LiDAR data collection 

Airborne LiDAR surveys of the study area were conducted in March and April

2002, February 2008, and March 2010 for the purposes of evaluating watershed 

features, evaluating the ability to detect change, and to document improvements in 

LiDAR capabilities over time. Comparisons of ground-surveyed and LiDAR-derived 

measurements of forest roads and stream channel characteristics began in 2002 and 

are ongoing (Hilburn 2010,White 2010, White et al. 2010). Data from 2002 were 

collected by Spencer B. Gross Inc., Portland, Oregon, while the 2008 and 2010 

datasets were collected by Airborne 1, El Segundo, California. 

LiDAR flight and sensor parameters represent “high-resolution” survey 

specifications provided by vendors at the time of the surveys. The LiDAR data 

collected in 2002 were evaluated at 21 open and flat checkpoints, with a vertical 

RMSE of 0.08 m. Data from 2008 and 2010 were evaluated at over 1000 RTK-GPS 

checkpoints and a show similar precision of 0.09 m and 0.06 m RMSE, respectively. 

These values are useful to ensure proper system calibration and performance, but are 

not indicative of vertical accuracy in areas of steep slopes and dense vegetation. 

Parameters of each flight and specifications of the LiDAR sensors differed across 

flights, but are not addressed extensively here. One noteworthy difference was sensor 

pulse rate, which increased from 20,000 pulses per second in 2002 to 100,000 pulses 

per second in 2008 and 150,000 pulses per second in 2010. Bare-earth filtering was 

provided by the vendor to classify points as either ground or non-ground and this 

classification was used for the remainder of the analysis.

LiDAR feature extraction 

Each LiDAR dataset was used to create a Triangular Irregular Network (TIN) 

surface, from which the cross-sectional profiles were extracted. Horizontal 

coordinates for the left and right endpoints of each cross-section were established in 

the field survey using a total station and local control network. A 0.5 m buffer was 

constructed around each profile line and ground returns located within this buffer 

were used to construct a TIN for that profile. Bankfull elevation as identified in the 

field was used to calculate bankfull depth (bfd), bankfull width (bfw), and bankfull 

area (bfa). Ground survey data from 2010 are used in this study and assumed to 

represent ground conditions across all flights. Survey data from 2008 was also plotted 

to show the small magnitude of change experienced over the study period. Similarly, 

while the LiDAR flights occurred in early spring and the ground surveys were 

conducted during summer months, no channel-changing flow events occurred during 

those intervening months. 

Results and discussion

Results are presented with a discussion focusing on ground return point spacing 

along profiles, qualitative observations showing visual agreement, and finally, a 

quantitative evaluation describing agreement for each channel feature. Further 

emphasis is placed on describing improvement over the three LiDAR datasets. 
Comparing LiDAR-Generated to Ground-Surveyed Channel Cross-Sectional Profiles in a Forested 

Mountain Stream

643

LiDAR ground return points 

One measure of LiDAR performance and suitability is found by examining the 

density of ground points. In 2002, the average spacing between ground returns in the 

Little Creek watershed was 2.05 m; this number dropped to 1.1 m in 2008, and

ultimately to 0.53 m in 2010. Given that the channel cross-sections are located under 

dense riparian canopy, ground point density is expected to be less than the overall 

watershed average. In this study, the average spacing between ground points along 

the profile lines is 3.03 m in 2002, 1.00 m in 2008, and 0.49 m in 2010. That is, on 

average, the number of LiDAR points along the profile lines increased from 3, to 16, 

to 28 observations across the three flights. It should be noted that the average number 

of LiDAR observations per transect is approaching the average number of fieldsurveyed points. In many cases individual cross-sectional profiles had more LiDAR 

points than surveyed observations. Questions still remain, however, regarding how

well the ground-return points reflect actual channel elevations, and how many 

observations are necessary to accurately characterize the channel and aid channel 

change detection. 

Visual and measured comparisons 

Observing the graphical representations of the LiDAR-derived and groundsurveyed cross-sectional profiles is an important first step in understanding the 

agreement between the derived and surveyed profiles. Figure 2 provides examples 

using the B10 cross-section. Figure 2a shows the agreement between the 2008 and 

2010 field surveys. The error associated with field surveys is also important to 

understand in relation to the derived profiles. The B10 field surveys show good 

agreement for the 2008 and 2010 surveys. However, other profile locations are more 

problematic due to large obstructions in the channel and difficulties associated with 

the vertical positioning of the Philadelphia rod. There is also human error introduced 

by having different field personnel perform the surveying. Preliminary error 

estimates performed for the 2002 field survey found bed elevations to vary by ± 0.05 

m and profile areas to vary by ± 1.22 m2

. 

There are substantial visual differences between the LiDAR-derived profiles for 

B10 in 2002, 2008, and 2010 (fig. 2b). Most notable is the 2002 survey which had 

only four ground points within the 0.5 m buffer around the profile line, versus 27 in 

2008 and 84 in 2010. Field surveyors collected 35 and 41 points for B19 in 2008 and 

2010, respectively. A question to be answered is how many LiDAR returns are 

necessary to describe the profile for characterization and aid in change detection? 

Visually comparing the 2010 field survey to 2010 LiDAR-derived profile (fig. 2c) 

provides further evidence that, at least for the B10 cross section, superior agreement

can be achieved with the 2010 LiDAR. One challenge is to determine how to assess 

the agreement between LiDAR-derived and measured cross-sectional profiles for the 

purposes of channel characterization and change detection? One way is to compare 

measures of channel geometry that are typically made from field surveys of stream 

channels. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

644

Figure 2a-d—B10 cross-sectional profile agreement for a) 2008 and 

2010 ground- survey profiles, b) 2002, 2008, and 2010 LiDAR-generated 

profiles, c) 2010 LiDAR-generated and 2010 ground-survey profiles, and 

d) 2010 LiDAR-generated and 2010 ground-survey profiles showing 

water surface, bankfull, and flood-prone elevations.

Channel geometry measures often include bankfull dimensions. Indicators of 

bankfull stage are identified in the field during the surveys. Although a subjective 

determination based on field indicators, the importance of the bankfull relationships

in fluvial processes and channel restoration is widely recognized in the literature 

(Leopold et al. 1964, Rosgen 1994). The B10 cross section shows good visual 

agreement for bankfull width (fig. 2d), and arguably, decent agreement for estimating 

bankfull depth and area. A more quantitative assessment of agreement follows. 

Scatterplots and linear regression are used to summarize and compare fieldsurveyed versus LiDAR-derived dimensions (after Miller et al. 2004) across all cross 

sections (fig. 3). Results from the 2002 LiDAR are generally poor. Profiles from 

2002 tended to overestimate bankfull dimensions; channels appeared to be deeper, 

wider and larger than when compared to those using field survey data. Both 2008 and 

2010 LiDAR data show substantial improvements over the 2002 data. Bankfull depth 

and area are underestimated in the 2008 data, although bankfull width estimates are 

nearly unbiased. The 2010 cross sections showed the best overall correspondence to 

field survey measurements. These cross-sections have the highest R-squared values 

and are the most consistent across the range of surveyed channel dimensions. Still, 

both the 2008 and 2010 LiDAR estimates routinely underestimate bankfull depth. It 

is possible that the shallow water depth present during the LiDAR flights inhibited 

accurate measurement of the channel bed (Faux et al 2009). 
Comparing LiDAR-Generated to Ground-Surveyed Channel Cross-Sectional Profiles in a Forested 

Mountain Stream

645

The average error of the LiDAR-derived feature measurements is presented in 

figure 4. In this figure, error is presented as a percentage of the field-surveyed 

bankfull

0.1

0.3

0.5

0.7

0.9

1.1

0.1 0.3 0.5 0.7 0.9 1.1

LiDAR Depth (m)

Surveyed Depth (m)

2002 Bankfull Depth y = 0.431x + 0.410

R2 = 0.047

0.1

0.3

0.5

0.7

0.9

1.1

0.1 0.3 0.5 0.7 0.9 1.1

LiDAR Depth (m)

Surveyed Depth (m)

2008 Bankfull Depth y = 0.692x + 0.091

R2 = 0.411

0.1

0.3

0.5

0.7

0.9

1.1

0.1 0.3 0.5 0.7 0.9 1.1

LiDAR Depth (m)

Surveyed Depth (m)

2010 Bankfull Depth y = 0.799x - 0.031

R2 = 0.653

0.0

2.0

4.0

6.0

8.0

10.0

0.0 2.0 4.0 6.0 8.0 10.0

LiDAR Width (m)

Surveyed Width (m)

2002 Bankfull Width y = 0.832x + 1.273

R2 = 0.215

0.0

2.0

4.0

6.0

8.0

10.0

0.0 2.0 4.0 6.0 8.0 10.0

LiDAR Width (m)

Surveyed Width (m)

2008 Bankfull Width y = 0.986x - 0.224

R2 = 0.715

0.0

2.0

4.0

6.0

8.0

10.0

0.0 2.0 4.0 6.0 8.0 10.0

LiDAR Width (m)

Surveyed Width (m)

2010 Bankfull Width y = 0.929x + 0.299

R2 = 0.810

0.0

1.0

2.0

3.0

4.0

5.0

0.0 1.0 2.0 3.0 4.0 5.0

LiDAR Area (m2)

Surveyed Area (m2)

2002 Bankfull Area y = 0.760x + 0.864

R2 = 0.255

0.0

1.0

2.0

3.0

4.0

5.0

0.0 1.0 2.0 3.0 4.0 5.0

LiAR Area (m2)

Surveyed Area (m2)

2008 Bankfull Area y = 0.854x - 0.094

R2 = 0.753

0.0

1.0

2.0

3.0

4.0

5.0

0.0 1.0 2.0 3.0 4.0 5.0

LiDAR Area (m2)

Surveyed Area (m2) 

2010 Bankfull Area y = 0.919x - 0.195

R2 = 0.859

Figure 3—Scatterplots showing LiDAR- and field-surveyed channel features (bankfull 

depth, width, and area) from 2002, 2008, and 2010 data. A 1:1 line is drawn for 

reference.

dimension. While the absolute error for bankfull width, depth and area measurements 

were relatively small, taken as a percentage of bankfull channel dimensions, these 

errors appear more substantial. In the 2010 survey, two thirds of the LiDAR-derived 

cross-sections provided bankfull width within 10 percent (0.46 m) of the field values. 

Over 90 percent of cross-sections provided width measurements within 20 percent 

(0.91 m) of the field-surveyed value. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

646

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

BFD (m) BFW (m) BFA (m2) TWE RMSE (m)

Average Error (%)

Average Error for Channel Features

2010

2008

TWE RMSE (m)

2002

Figure 4—Average error between surveyed and LiDAR-derived channel features.

Comparing the LiDAR-derived thalweg elevations to field-surveyed elevations 

provides a measure of vertical accuracy. Scatterplots (fig. 5) show the reduction in 

vertical error in successive flights. Elevation differences are summarized with RMSE 

values of 0.7 m, 0.2 m, and 0.175 m for 2002, 2008, and 2010, respectively. One 

concern is the apparent positive bias (0.13 m) in the 2010 LiDAR elevation data. At 

this point it is unclear whether this is a characteristic of LiDAR returns reflecting 

from the water surface, or if there is a bias in the field survey control network. 

Additional survey work is planned to evaluate this anomaly further. If this bias were 

subtracted from the RMSE, the resulting RMSE would be 0.05 m, similar to the 0.06 

m reported from the vendor accuracy report. 

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

0 10 20 30 40 50 60

Thalewe Elevatoin Error (m)

2002

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

0 10 20 30 40 50 60

2008

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

0 10 20 30 40 50 60

2010

Figure 5—Error between surveyed and LiDAR-derived thalweg elevations. 

Summary 

Improvements in LiDAR technology translate to an increased ability of LiDAR 

to describe the physical characteristics of stream channels under challenging 

landscape conditions. The 2010 LiDAR survey was conducted during leaf-off 

conditions with a pulse repetition frequency of 150,000 laser pulses per second in 

order to maximize ground return density in this forested environment. While point 

density improved in 2010 versus 2008, improvements in overall accuracy were only 

marginal. This may result as point spacing approaches laser footprint size on the 

ground and the horizontal accuracy of pulse positioning (~ 0.3-0.5 m). Overall, many

of the LiDAR-derived profiles agree quite well with the ground-surveyed profiles, 

yet many are considered inadequate for fine-scale characterization or geomorphic 

change detection. Limitations still exist due to water depth at the time of the LiDAR 

survey, obstruction from near-ground vegetation, dense overstory canopy coverage, 

and steep channel side slopes. Depending on the accuracy that is required, airborne 

LiDAR can provide useful measurement and characterization of small mountain 
Comparing LiDAR-Generated to Ground-Surveyed Channel Cross-Sectional Profiles in a Forested 

Mountain Stream

647

streams. As this technology continues to advance, the suitability of LiDAR and its 

performance for various applications should continue to be evaluated. 

References

Csanyi, N.; Toth, C.K.; Grejner-Brzezinska, D.; Ray, J. 2005. Improvement of LIDAR data 

accuracy using LIDAR specific ground targets. Proceedings, ASPRS Annual 

Conference. Baltimore, MD. CD ROM.

Faux, R.; Buffington, J.M.; Whitley, G.; Lanigan, S.; Roper, B. 2009. Use of airborne nearinfrared LiDAR for determining channel cross-section characteristics and

monitoring aquatic habitat in Pacific Northwest rivers: a preliminary analysis. In: 

Bayer, J.M.; Schei, J.L., editors. Remote sensing applications for aquatic resource 

monitoring. PNAMP special publication. Cook, WA: Pacific Northwest Aquatic 

Monitoring partnership: 43-60.

French, J.R. 2003. Airborne LiDAR in support of geomorphological and hydraulic 

modeling. Earth Surface Processes and Landforms 28: 321-335.

Harrelson, C.C.; Potyondy, J.P; Rawlins, C.L. 1994. Stream channel reference sites: an 

illustrated guide to field technique. Gen. Tech. Rep. RM-245. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain Forest and Range 

Experiment Station. 61 p.

Hilburn, R. 2010. A comparison of LiDAR channel features with ground-surveyed 

channel features in the Little Creek watershed. San Luis Obispo, CA: California

Polytechnic State University. M.S. thesis. 105 p.

Hyyppä, H.; Yu, Z.; Hyyppä , J.; Kaartinen, H.; Kaasalainen, S.; Honkavaara, E.; Rnnholm, P. 

2005. Factors affecting the quality of DTM generation in forested areas. In: 

Proceedings of the ISPRS Workshop Laser Scanning 2005, Enschede, The Netherlands: 

36: 97-102. 

James, L.A.; Watson, D.G.; Hansen, W. F. 2007. Using LiDAR data to map gullies and 

headwater streams under forest canopy: South Carolina, USA. Catena 71: 132-144.

Kraus, K.; Pfeiffer, N. 1998. Determination of terrain models in wooded areas with 

airborne laser scanner data. ISPRS Journal of Photogrammetry and Remote Sensing

54: 193-203.

Leopold, L.B.; Wolman, M.G.; Miller, J.P. 1964. Fluvial processes in geomorphology. San 

Francisco, CA: W.H. Freeman and Co. 

McKean, J.; Roering, J. 2005. Operational accuracy of LiDAR in mountainous terrain.

Boise, ID: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research 

Station. 

Miller, S.N.; Shrestha, S.R.; Semmens, D. 2004. Semi-automated extraction and validation 

of channel morphology from LiDAR and IFSAR terrain data. Proceedings, ASPRS 

Annual Conference. Denver, Colorado. 

Montgomery, D.R.; Buffington, J.M. 1997. Channel-reach morphology in mountain 

drainage basins. Geological Society of America Bulletin 109: 596-611.
GENERAL TECHNICAL REPORT PSW-GTR-238 

648

Reutenbuch, S.E.; McGaughey, R.J; Anderson, H.; Carson, W.W. 2003. Accuracy of a highresolution LiDAR terrain model under a conifer forest canopy. Canadian Journal of 

Remote Sensing 29(5): 527-535.

Rosgen, D.L. 1994. A classification of natural rivers. Catena 22: 169-199. 

Strahler, A.N. 1964. Quantitative geomorphology of drainage basins and channel 

networks. In: Chow, V., editor. Handbook of applied hydrology. NY: McGraw-Hill: 39-

76.

White, R.A. 2010. Accuracy of forest road and stream channel characteristics derived 

from LiDAR in forested mountain conditions. San Luis Obispo, CA: California 

Polytechnic State University. M.S. thesis. 118 p.

White, R.A.; Dietterick, B.C.; Mastin, T.; Strohman, R. 2010. Forest roads mapped using 

LiDAR in steep forested terrain. Remote Sensing 2(4): 1120-1141.
649

Tree Height Estimation in 

Redwood/Douglas-fir Stands in Mendocino 

County

Helge Eng1

Abstract

In this study, height-diameter equations were developed for managed stands of coastal 

redwood/Douglas-fir stands in Mendocino County. Equations were developed by species to 

predict tree height as a function of diameter as well as other factors that are known to 

potentially explain tree height, including site class and live crown ratio. Two equation forms 

were compared and evaluated. Forest inventory data from Jackson Demonstration State Forest 

were used to fit the equations. These height-diameter equations will be useful in explaining 

height-diameter relationships in largely uneven-aged coastal redwood/Douglas-fir stands, and 

for predicting missing heights in forest inventories.

Key words: generalized height-diameter equations, live crown ratio, site class

Introduction

The objective of this study was to develop height-diameter equations for major 

tree species in largely uneven-aged managed stands in western Mendocino County. 

Height was estimated from diameter at breast height (DBH) alone and from DBH in 

combination with live crown ratio and site class. 

Height-diameter equations are used to predict heights from measured diameters. 

These equations avoid the need for expensive and time-consuming height 

measurements in forest inventories. In addition to DBH and other variables, height is 

measured on a sub-sample of trees. These data are used to fit regression equations 

that predict heights from DBH and potentially other tree and stand variables. These 

equations are then used to predict the heights of the remaining trees. 

Height-diameter equations are often fitted to regional data sets of tree heights and 

diameters. Such equations provide reasonable predictions in local applications as 

long as the local data are similar to the larger regional data set used to fit the 

equations. This study developed height-diameter equations specifically for western 

Mendocino County. All the data used to fit the equations came from Jackson 

Demonstration State Forest, a research and demonstration forest managed by the 

California Department of Forestry and Fire Protection on behalf of the public.

Height-diameter models commonly use only DBH as a predictor variable. 

Several authors however, have explored the use of additional variables that might 

influence the height-diameter relationship. Curtis (1967) developed equations 

including age in addition to DBH. Larsen and Hann (1987) reported that including 

site index as a predictor variable improved height estimation. Temesgen and von 

 

1 State Forests Program Manager, California Department of Forestry and Fire Protection. 

(Helge.Eng@fire.ca.gov).
GENERAL TECHNICAL REPORT PSW-GTR-238 

650

Gadow (2004) used measures of stand density and relative tree position. The average 

height and diameter of the largest trees in the stand, a measure of top height, has been 

used by Hanus et al. (1999) and Krumland and Wensel (1988). 

Methods

Data 

Because the objective of this study was to characterize the height-diameter 

relationship in managed stands, no stands were excluded from the analysis due to 

management activity. The majority of the data used in this study (table 1) were 

collected on Jackson Demonstration State Forest (JDSF) in western Mendocino 

County during the 2005 field season. The data include a temporary plot inventory 

consisting of 4,920 plots located on a 5 chain (330 ft) by 20 chain (1,320 ft) grid 

across the Forest, and 143 permanent plots located on a 60 chains by 60 chains grid 

across the Forest. Only the 2005 remeasurement data were used from the permanent 

plot data set. Data used to fit madrone and western hemlock equations also included 

additional data from a 1991 JDSF temporary plot inventory, which had the same 

design as the 2005 temporary plot inventory.

Table 1—Description of the data used to fit height-diameter equations.

Species Trees

Mean 

DBH 

(inches)

Std. 

Dev. Min Max

Mean 

Height 

(feet)

Std. 

Dev. Min Max

Redwood 2,235 24.0 10.6 5.1 76.3 107.4 36.8 19.0 244.0

Douglas-fir 1,567 23.8 10.5 5.1 61.3 126.8 43.6 24.0 241.0

Grand fir 225 22.1 10.1 5.2 50.2 121.2 42.2 28.0 217.0

Western 

hemlock

 234 14.7 6.2 5.2 39.7 89.6 27.4 32.0 168.0

Tanoak 819 13.3 5.9 5.0 43.3 60.4 18.5 18.0 122.0

Madrone 527 13.4 5.5 5.8 36.2 58.7 15.4 15.0 107.0

The 1991 and 2005 temporary plot inventory consisted of variable radius plots 

with a concentric 1/100th ac fixed area regeneration plot on the same plot center. The 

variable radius plots included trees 5.0 in DBH and greater. The continuous forest 

inventory permanent plots, first installed in 1959, were one-fifth acre circular plots. 

The minimum DBH measured was 7.0 in. The most common tree species on JDSF 

include coast redwood, Douglas-fir, grand fir, western hemlock, tanoak and madrone. 

Analysis

Two sets of height-diameter equations were developed. The first set of equations 

estimated height using DBH as the only predictor variable. The second set of 

equations estimated height as a function of DBH in combination with other tree or 

stand variables. In addition, two model forms were used. This produced four model 

forms to be evaluated for each species. The model form that provided the best fit was 

selected for each height-diameter equation for each species. 

The following equations were fitted to the data:
Tree Height Estimation in Redwood/Douglas-fir Stands in Mendocino County

651

1. Height = 4.5 + exp(a + bDBHc) 

2. Height = 4.5 + a(1 – exp(bDBHc

))

3. Height = 4.5 + exp(a0 + a1ASC + bDBHc

) 

4. Height = 4.5 + exp(a0 + a1ASC + a2LCR + bDBHc

) 

Other predictor variables used in addition to DBH included: 

Aggregated site class (ASC). ASC was a binary variable in which the value 1 denoted 

site class II or better, and the value 0 denoted site class III or less productive.

Live crown ratio (LCR). LCR is the percent of the bole of a tree that contains live 

crown. This measurement consisted of a visual estimate by cruisers. Two sides were 

averaged in the case of non-uniform crown length. 

Temesgen et al. (2007) found equation 1 to be the best equation when using DBH 

as the only predictor variable. The equation 1 model form was also used by Hanus et 

al. (1999) and Larsen and Hann (1987). Unlike equation 1, equation 2 is downward 

concave, with no inflection point. Huang et al. (1992) found equation 2 to give the 

best results.

Equation parameters were estimated using a nonlinear least squares estimation 

procedure with the Gauss-Newton estimation method. The STATISTICA software 

(StatSoft 2011) was used to fit all equations. 

Results

Table 2 shows the coefficients and their standard error of estimate in parentheses, 

root mean squared error (MSE) and coefficient of determination (R2

) for equations 1 

and 2. MSE is the square root of the division of the sum of squared residuals by the 

degrees of freedom. R2

 is the proportion of the variation explained by the regression 

(regression sum of squares divided by the total sum of squares).

Equations were evaluated for predictive ability using the MSE, R2

, the t-statistic 

of the coefficients and their confidence intervals. Plots of residuals versus predicted 

heights indicated no lack of fit. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

652

Table 2—Regression coefficients and standard errors for equations 1 and 2, by species. The 

best fit is shown for each species. All parameter estimates were significantly different from 

zero (p<0.05).

Coefficients

Species Eq. a b c MSE R2

Redwood 1 5.6911 

(0.087)

-7.3644 

(0.582)

-0.6294 

(0.052)

20.1 0.969

Douglas-fir 1 5.9429 

(0.125)

-6.2041 

(0.450)

-0.5531 

(0.059)

22.6 0.972

Grand fir 1 5.8095 

(0.281)

-6.3265 

(1.290)

-0.6015 

(0.159)

20.9 0.974

Western 

hemlock

2 162.7225 

(30.625)

-0.05723 

(0.010)

0.9763 

(0.152)

16.9 0.968

Tanoak 1 4.5343

(0.090)

-6.4926 

(1.942)

-1.0345 

(0.195)

14.7 0.946

Madrone 2 68.9322 

(5.383)

-0.1767 

(0.065)

0.8723 

(0.220)

13.9 0.948

Table 3 shows the coefficients and fit statistics for equation 3. Adding aggregated 

site class as a predictor variable in addition to DBH improved the accuracy of height 

prediction, for the species shown in table 3. 

Table 3—Regression coefficients and standard errors for equation 3, by species. The best fit 

is shown for each species. All parameter estimates were significantly different from zero 

(p<0.05).

Coefficients

Species a0 a1 b c MSE R2

Redwood 5.5535 

(0.075)

0.0775 

(0.008)

-7.7612 

(0.657)

-0.6782 

(0.053)

19.8 0.970

Douglas-fir 5.6268 

(0.087)

0.1138 

(0.01)

-6.6508 

(0.591)

-0.6601 

(0.061)

21.6 0.974

Grand fir 5.7813 

(0.294)

0.0686 

(0.026)

-6.1524 

(1.203)

-0.5855 

(0.158)

20.6 0.975

Tanoak 4.597 

(0.121)

0.1162 

(0.018)

-5.3565 

(1.366)

-0.8725 

(0.184)

14.3 0.949

Table 4 shows the coefficients and fit statistics for equation 4. Adding aggregated 

site class and live crown ratio as predictor variables in combination with DBH 

improved the accuracy of height prediction, for the species shown in table 4. 
Tree Height Estimation in Redwood/Douglas-fir Stands in Mendocino County

653

Table 4—Regression coefficients and standard errors for equation 4, by species. The best fit 

is shown for each species. All parameter estimates were significantly different from zero 

(p<0.05).

Coefficients

Species a0 a1 a2 b c MSE R2

Redwood 5.9093 

(0.110)

0.0753 

(0.008)

-0.0036 

(0.000)

-6.812 

(0.457)

-0.5656 

(0.050)

19.3 0.971

Douglas-fir 5.8146 

(0.103)

0.111 

(0.009)

-0.0027 

(0.000)

-6.2817 

(0.507)

-0.6101 

(0.060)

21.2 0.975

Tanoak 4.756 

(0.153)

0.0996 

(0.019)

-0.0019 

(0.001)

-5.0244 

(1.124)

-0.7834 

(0.174)

13.8 0.951

Conclusions

Equations one through four were all found to adequately predict height from 

DBH alone or in combination with other predictor variables, for the species 

indicated. Adding aggregated site class and live crown ratio as predictor variables 

incrementally improved the height predictions. In practice, the choice of which 

equation to use will depend primarily on ease of use and availability of data for the 

additional predictor variables.

Additional tree and stand characteristics in combination with DBH can improve 

height prediction, but the repeated harvest entries that are typical of uneven-aged 

managed stands have the potential to confound their effect. Some of these additional 

variables proved to be relatively unaffected by management activity and were 

therefore useful additional predictor variables in the height-diameter equations. Other 

variables provided no additional information, presumably because management 

activity had confounded any possible correlation with height. 

Stand characteristics such as basal area and stand density are directly 

manipulated in harvest entries and were therefore not investigated further. 

Aggregated site class, a stand characteristic that is arguably relatively unaffected by 

management activity, proved to be a significant contributor to estimating heights in 

some species in this study. 

Some tree characteristics such as live crown ratio also appeared to be relatively 

unaffected by harvest activity. Live crown ratio proved to be a useful estimator in 

addition to DBH for estimating height in some species. Other tree characteristics such 

as crown class, which can be changed instantly by a harvest entry in a stand, were not 

significantly correlated with height for any of the species investigated in this study. 

References

Curtis, R.O. 1967. Height-diameter and height-diameter-age equations for second-growth 

Douglas-fir. Forest Science 13: 365-375.

Hanus, M.L.; Marshall, D.D.; Hann, D.W. 1999. Height-diameter equations for six species 

in the coastal regions of the Pacific Northwest. Research Contribution 25. Corvallis, 

OR: Forest Research Laboratory, Oregon State University. 11 p.
GENERAL TECHNICAL REPORT PSW-GTR-238 

654

Huang, S.; Titus, S.J.; Wiens, D.P. 1992. Comparison of nonlinear height-diameter 

functions for major Alberta tree species. Canadian Journal of Forest Research 22: 

1297-1304.

Krumland, B.K.; Wensel, L.C. 1988. A generalized height-diameter equation for coastal 

California species. Western Journal of Applied Forestry 4: 113-115. 

Larsen, D.R.; Hann, D.W. 1987. Height-diameter equations for seventeen tree species in 

Southwest Oregon. Research Paper 49. Corvallis, OR: Forest Research Laboratory, 

Oregon State University. 16 p.

StatSoft Inc. 2011. STATISTICA. Version 10. www.statsoft.com.

Temesgen, H.; von Gadow, K. 2004. Generalized height-diameter models for major tree 

species in complex stands of interior British Columbia, Canada. European Journal of 

Forest Research 123: 45-51.

Temesgen, H.; Hann, D.W.; Monleon, V.J. 2007. Regional height diameter equations for 

major tree species of southwest Oregon. Western Journal of Applied Forestry 22: 213-

219.
655

Prioritizing Treatment of Second-Growth 

Forests Using LiDAR

Lathrop P. Leonard1 and Daryl Van Dyke2 

We used multi-return light detecting and ranging (LiDAR) to develop a costeffective method for describing forest conditions and prioritizing stands for treatment 

in over 14,000 ha of second-growth forests (11 to 85 years old) in Del Norte Coast 

Redwoods State Park (DNCRSP). DNCRSP consists primarily of redwood and 

Douglas-fir dominated forests with scattered tanoak dominated stands. Our objectives 

were to inventory and prioritize 30+ year old stands for treatment to promote growth 

and the development of late-seral conditions in overly dense stands. 

A stratified sampling design was implemented to establish plots throughout the 

range of age classes and vegetation types within the property in 2009. We compared 

summary data from fixed ground plots to first return LiDAR data from the same 

approximate location. A key step to building a model to predict forest metrics with 

LiDAR is to ensure that each fixed-radius ground plot was accurately represented by 

an extracted plot LiDAR point cloud cylinder. To accomplish this, we attempted to 

obtain sub-meter accuracy for all ground plot centers by using a Trimble XH with a 

Zepher antennae GPS system. A minimum of 300 points were averaged for each plot, 

and then the resulting positions were checked and occasionally adjusted to match 

stem mapped trees visible in the point cloud. We also established plots in locations 

that appeared to be relatively uniform so that any LiDAR point cloud cylinder 

extracted within two meters of the actual plot center would be similar.

We used Forest Vegetation Simulator (FVS) software to calculate current plot 

conditions and account for 2 to 3 years of growth, corresponding to the number of 

growing seasons between the LiDAR flight in 2007 and the plot installation in 2009. 

We could then back-calculate relative change in basal area and other metrics for each 

plot at the time of the flight. 

Descriptive statistics of the cylinders of normalized LiDAR data for each 

extracted plot were developed using the USDA Forest Service Fusion/LTK tools. 

Statistics derived included: quantile values of vertical height (e.g., the 95th percentile 

height), metrics of percent cover in LiDAR returns (e.g., the percentage of pulses that 

reflected off vegetation above 3 m), and the proportion of returns absorbed in slices 

above the ground surface (e.g. of all returns from above 3 m, what percentage was 

above 6 m). To create two to four parameter multivariate regression relationships for 

each metric, we paired observed stand conditions and the statistical descriptions of 

the LiDAR data within each plot on a minimum of 60 plots. To date, we have 

developed models for four metrics: basal area (R2

 = 0.89), quadratic mean diameter 

 

1 California State Parks, 1111 2nd St., Crescent City, CA 95531; (707)465-7383. 

(lleonard@parks.ca.gov). 2 U.S. Fish and Wildlife Service 1655 Heindon Road, Arcata, CA 95521; (707)825-5153. 

(Daryl_Van_Dyke@fws.gov). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

656

(R2 = 0.90), stand density index (SDI) (R2 = 0.80), and tree density (R2 < 0.50). We 

obtained an R2 for tree density of 0.70 for second-growth that was at least 30 years 

old. 

We delineated stands of relatively uniform conditions using the LiDAR derived 

canopy height model and then calculated stand-level forest metrics using our 

regression models. We then ranked stands independently based on both their SDI and 

the coefficient of variation of LiDAR first returns (CV). Stands with a high SDI and a 

low CV were ranked as having a greatest need of treatment. A high SDI indicates 

overcrowding where density management is most needed to promote growth. A low 

CV is an indication of less variability in tree heights (differentiation). Therefore a 

stand with a low CV is less able to self thin and progress rapidly towards late-seral 

conditions. A high CV could indicate a greater degree of differentiation or a stand 

where the canopy has not closed. CV was also useful in helping to identify unevenaged stands (high CV). Since SDI cannot be readily calculated for uneven-aged 

stands, any stand with a high CV may have an inaccurate SDI. Stands will similarly 

be ranked by tree density as another indication of crowding. Standing volume could 

also be considered if timber extraction is used to offset the cost of implementation. 

The North Coast Redwoods District of California State Parks is adopting this 

method to prioritize stands for forest restoration treatments but the methodology 

could be adopted for other objectives, such as thinning and harvesting schedules, 

habitat delineation or general inventories. We did not use this method for younger 

stands (<30 years-old) in part because this age class was already inventoried. Stem 

density may also be more critical for prioritizing young stands since their SDI is 

changing rapidly. Limitations of this method include the inability to describe species 

composition or diameter distribution.
657

Land Surface Phenology as a Coarse-Filter 

Indicator of Disturbance and Climatic 

Effects Across the Coast Redwood Range1

Steven P. Norman2 and William W. Hargrove2

Abstract

Satellite-based measurements provide a systematic measure of the seasonal fluctuations and 

general condition of forest vegetation, including that of the coast redwood region. Year-toyear variation in greenness may be caused by gradual disturbances, successional recovery or 

climatic variation, while within-year variation reflects disturbance events and the response of 

vegetation types to seasonal change. Here we show how inter- and intra-year redwood forest 

vigor is captured by the Normalized Difference Vegetation Index (NDVI) using a MODISbased vegetation change model developed as part of the USDA Forest Service’s Threat 

Assessment Centers’ Early Warning System. Results show how the land surface phenology of 

mature and young forests changed before and after wildfire. Following the 2003 Canoe Fire, 

the productivity of young forests reversed from being higher to lower than mature forests. The 

early summer 2008 wildfires in Mendocino County did not cause this reversal, presumably 

because fire effects in second growth were less severe. The August 2009 Lockheed Fire in 

Santa Cruz County experienced a sharp drop in second growth productivity, as did the early 

season 2008 wildfires to the south. As a coarse-filter monitoring tool, this product reflects this 

variation across vegetation types caused by climate and disturbances for the entire 

conterminous United States.

Key words: climate change, cumulative effects, fire, landscape ecology, monitoring, NDVI, 

phenology, Sequoia sempervirens

Introduction

Having the right knowledge at the right time builds a cornerstone for effective 

long-term, broad-scale forest management. But what is this knowledge, and what is it 

not? Taking a broad perspective, this knowledge involves being aware of trends in 

the condition of the forest, predicting likely consequences to forest values from an 

array of threats, and having the means to integrate this information in an effective 

way. 

Early awareness of forest change has been an elusive part of forest management 

because natural systems are complex, forests often cover vast areas, and subtle or 

local changes are difficult to contextualize and interpret. As a result, the onset of 

change often goes undetected and seemingly normal year-to-year variability obscures 

trends. Should we be concerned about an unusually light snowpack, a seemingly 

unprecedented outbreak of lightning fires, or a few more dead trees? Systematic 

landscape monitoring helps us answer these questions. It provides baseline 

 

1 An abbreviated version of this paper was presented at the symposium, coast redwood forests in a 

changing California, June 21-23, 2011, Santa Cruz, California. 2 Research ecologists, USDA Forest Service, Southern Research Station, Eastern Forest Environmental 

Threat Assessment Center, 200 WT Weaver Blvd, Asheville, NC 28804. (stevenorman@fs.fed.us; 

whargrove@fs.fed.us).
GENERAL TECHNICAL REPORT PSW-GTR-238 

658

information prior to change, it allows us to track and contextualize change after it 

occurs. Both help us address the effectiveness of broad management strategies. 

Monitoring from space provides a coarse-filter way to detect departure from past 

conditions caused by a range of stressors, yet despite the general availability of raw 

satellite imagery, processing and data analysis has been too time consuming to 

provide a near-real time monitoring tool for broad landscapes. That obstacle is falling 

as formal change-detection systems are being developed for the United States 

(Hargrove et al. 2008). A second challenge of space-based monitoring is that it can 

be difficult to translate changes observed from above with the things we actually care 

about on the ground. That translation involves not just monitoring, but an 

interpretative assessment. 

How well can space-based monitoring capture the overall condition of the coast 

redwood forest? During recent decades, notable changes in the coast redwood forest 

have resulted from land use conversion for development, logging, wildfire and 

Sudden Oak Death. Looking ahead, monitoring needs to include not just the effects 

of these factors individually, but how they collectively interact with each other and 

with changes in climate. 

The dual purposes of this paper are to (1) demonstrate how space-based 

monitoring technology can track forest changes across the coast redwood region, and 

(2) to provide a coarse-filter assessment of the impacts of recent wildfires and climate 

variability across the coast redwood range. 

Methods

To describe vegetation within and among years, we used an 11year dataset of the 

Normalized Difference Vegetation Index (NDVI) developed for the National Early 

Warning detection system (Hargrove et al. 2009). This MODIS-derived product 

provides NDVI values for the conterminous United States using a moving -week 

window, delivered at 8-day intervals at a resolution of 232 m. NDVI is a measure of 

live green vegetation calculated from two bands of reflected solar radiation that 

plants have evolved to preferentially absorb for photosynthesis (red wavelengths) and 

reflect (the near infrared). In the West, NDVI values for dense coastal evergreen 

forest typically fall between 0.8 and 0.9, while open forests with deciduous or grass 

understories fluctuate seasonally and typically range from 0.5 to 0.8. This moderate 

resolution, high frequency NDVI time series has sufficient resolution to capture these

seasonal dynamics, in addition to sudden changes in vegetation vigor caused by 

disturbance-associated stress (Hargrove et al. 2009).

Digital maps of wildfire boundaries and coast redwood vegetation were 

downloaded from the California Department of Forestry and Fire Protection 

(http://frap.cdf.ca.gov/, Fox 1988). Coast redwood vegetation was mapped from 

1:130,000-scale 1986 color infrared aerial photos supplemented with NASA and 

USGS aerial photos in the southern range with a minimum mapping unit of 40 acres. 

While this mapping effort targeted redwood vegetation in particular and provides 

coarse-vegetation polygons consistent with the needs of MODIS-resolution data, the 

product varies in accuracy. Forest age is not always as mapped, particularly in the 

south, and in the north, logging between the mid-1980s and 2000 may further affect 

results on private lands. Wildfires in coast redwood forest were selected that fell 
Land Surface Phenology as a Coarse-Filter Indicator of Disturbance and Climatic Effects Across 

the Coast Redwood Range

659

within a temporal window (2001 to 2009) that would allow comparison of pre- and 

post-fire NDVI conditions. Multiple fires that initiated during a 2008 lightning storm 

were separated into a north and south group. The 2003 Canoe fire in Humboldt 

Redwoods State Park and the 2009 Lockheed Fire in Santa Cruz County provided 

two additional fire analysis units for examination. In total, the portion of 19 fires 

were analyzed that included redwood or redwood-associated forest types (table 1). 

The midpoints of each 231m MODIS pixel that fell within the 125 m-buffered edge 

of these fire boundaries were intersected with each 8-day raster for the 2000 to 2010 

period using GIS. This resulted in four 506 column tables with one table for each of 

the four county-year based fire analysis units (table 1). 

Table 1—Fires grouped by county-year analysis unit.

County Fire name Active fire dates Fire area (GIS acres) 

Humboldt Canoe 09-03 to 10-06 2003 11,044 

Mendocino Middle

Lost Pipe

Hardy Creek

Indian

Table Mountain

Navarro

Williams

Orr Series

Horse

Low Gap

Cowshed

Cliff Ridge

Sugarloaf

06-23 to 07-15 2008

07-04 to 07-10 2008

06-21 to 07-11 2008

06-26 to 07-12 2008

06-21 to 06-26 2008

06-21 to 06-26 2008

06-21 to 06-27 2008

07-04 to 07-12 2008

06-28 to 07-04 2008

07-04 to 07-15 2008

06-21 to 07-15 2008

06-22 to 07-12 2008

06-21 to 07-09 2008

2,067

1,187

5,354

 327

2,096

1,853

445

3,416

576

1,347

4,466

4,658

6,928 

Santa Cruz Lockheed 08-12 to 08-23 2009 7,783 

Monterey and 

Santa Cruz

Basin Complex

Trabing

Martin

White Hurst

06-21 to 07-27 2008

06-20 to 06-22 2008

06-11 to 06-16 2008

06-21 to 06-23 2008

163,606

594

483

256

The midpoint of each MODIS pixel was also intersected with the map of coast 

redwood vegetation (Fox 1988) to help distinguish mature and young forest types. 

While this did not always capture the dominant vegetation type within a given 

MODIS pixel, it provided an efficient means of data extraction. Both the pixel purity 

and undocumented logging-associated change may reduce any difference among 

vegetation types. Pixels were then averaged for each fire analysis unit across the 506-

step NDVI time series to see how vegetation types responded to seasonal dynamics 

and fire events.

To provide a more inclusive assessment of the condition and trends in NDVI 

across the coast redwood region, a second analysis was conducted using an elevenyear assessment of NDVI for the entire coast redwood range as delimited by Fox 

(1988). Four 8-day periods in January and four 8-day periods in August were 

averaged, by year, for mature redwood and young redwood-plantation vegetation 

types. This analysis included 104,227 pixels to the north and 16,592 pixels to the 

south of San Francisco. Pixel midpoints that fell on associated vegetation types 

dominated by hardwood and Douglas fir were excluded. Yearly NDVI values for 

January and August were graphed for all pixels across the range, and then just for 

those pixels that did not burn during the 11-year analysis period, in order to better 

distinguish fire effects from climate effects.
GENERAL TECHNICAL REPORT PSW-GTR-238 

660

Results 

Coast redwood forests exhibited notable variation in NDVI during and among 

years. For forests that burned, both pre-fire and post-fire greenness decreased toward 

the south, but the reduction attributable to fire was not consistent among vegetation 

types (table 2). The severity of the reduction in NDVI with fire sharply increased 

toward the south, but this reduction involved complex local differences among 

vegetation types. In the two 2008 fire analysis units, mature forests declined more 

than young forests, although this was a marginal difference compared to the extreme 

declines observed between young and mature forests in the 2003 Canoe fire and 2009 

Lockheed fires. After the Canoe and Lockheed events, the high pre-fire NDVI of 

young forests reversed relative to mature forests (fig. 1A, 1C). This reversal did not 

occur after the 2008 events. Young forests remained greener than mature forests in 

the north while remaining less green than mature forests in the south (fig. 1B, 1D).

Table 2—Change in mean annual NDVI for coast redwood forests that burned from the prefire year to the post-fire year.

Forest type Pre-fire NDVI Post-fire NDVI Percent drop

2003 Canoe Fire (Humboldt Co.) (n=692)

Mature .86 .79 7.9 

Young .86 .77 10.9 

Overall .86 .78 9.8 

2008 Mendocino County Fires (n=1938)

Mature .83 .76 8.9 

Young .85 .78 8.7 

Overall .85 .76 8.7 

2009 Lockheed Fire (Santa Cruz County) (n=351)

Mature .75 .72 4.8 

Young .82 .69 15.8 

Overall .82 .69 15.1 

2008 Santa Cruz- Monterey County Fires (n=830)

Mature .78 .63 20.3 

Young .72 .59 17.7 

Overall .80 .65 19.5 

A: 2003 Canoe Fire
Land Surface Phenology as a Coarse-Filter Indicator of Disturbance and Climatic Effects Across 

the Coast Redwood Range

661

B: 2008 Mendocino fires

C: 2009 Lockheed Fire

D: 2008 Santa Cruz-Monterey County fires
GENERAL TECHNICAL REPORT PSW-GTR-238 

662

Figure 1—An 11-year, 8-day time series of the Normalized Difference Vegetation 

Index (NDVI) for four fire analysis units across the coast redwood range. A: 2003 

Canoe Fire, B: 2008 Mendocino fires, C: 2009 Lockheed Fire, D: 2008 Santa CruzMonterey County fires. 

Figure 2—Trends in mean January and August NDVI for mature and young coast 

redwood forests north and south of San Francisco, California showing the forest’s 

range-wide status (top row) and just those areas that did not burn during the 2000 to 

2010 period (bottom row).

Across the entire coast redwood range, NDVI varied among seasons, years, and 

vegetation types from 2000 to 2010 (fig. 2). Mature forests south of San Francisco 

were less green than mature forests to the north, while young forests were less

distinguishable by latitude. In January, young forests were consistently greener than 

nearby mature forests, but, by August, this relationship reverses in the north. 

The disproportionate effects of recent fires across the coast redwood range are 

apparent across the two rows of graphs. Given the larger portion of coast redwood 

forest in the north that did not burn, the effects of fire on regional NDVI are

indistinguishable there, but not so in the south. A larger portion of mature forest in 

the south has burned and this depressed the NDVI of mature forests there. Note that 

January NDVI declines across all vegetation types, even after burned areas are 

removed. In August, this decline is only evident in the south. 

Discussion

Change in NDVI provides a useful mechanism for monitoring the vigor of coast 

redwood forests at moderate resolution and in near-real time. In areas without 

disturbance, changes in monthly NDVI reflect seasonal variation in forest greenness 

related to phenology and cover types, while year-to-year differences reflect variation
Land Surface Phenology as a Coarse-Filter Indicator of Disturbance and Climatic Effects Across 

the Coast Redwood Range

663

in climate (Hargrove et al. 2009). The winter peak in greenness and the late summer 

low generally correspond to gross seasonal vegetation productivity within this 

Mediterranean climate, but (with the exception of the Lockheed fire area, fig. 1C), 

this NDVI peak precedes the maximum period of cambial activity (spring to early 

summer) by several months. This phenological pattern of winter maximum, summerminimum contrasts with the pattern of spring greenup and autumnal brown down that 

typifies other temperate climates that support deciduous forest cover.

The greater decline in greenness after fire in the south (table 2) may relate to 

latitudinal differences in fire weather (i.e., temperature and fuel moisture) or to 

differences in the distribution of vegetation types across slopes caused by differences 

in climate or history. In the south, mature forests are restricted to narrow riparian 

areas, so that the area in mature forest constitutes a small portion of the landscape. 

This greater likelihood of a mixed pixel effect in the south may explain the rapid 

increase in mature forest NDVI after the 2008 fires in Santa Cruz and Monterey 

Counties (fig. 1D). The vegetation classification in the south is also of question-able 

accuracy as the area burned by the Lockheed fire has less mature forest than was 

mapped. 

The effects of wildfire on the productivity of mature and young forests are 

generally consistent with the mixed severity behavior expected from wildfires that 

burn across complex topographies within the region (Lorimer et al. 2009). Apart 

from impacts from logging, older forests tend to naturally occur in protected portions 

of the landscape where fire is less likely to be severe. Field observations and casual 

examinations of aerial imagery from before and after wildfire support this 

explanation. However, note that the reduction in young forest vigor after the 2008 

Mendocino fires paralleled that of mature forest; that is, it did not decline more than 

mature forest as seen after the Canoe Fire (fig. 1A, 1B). This may be because the 

2008 fires burned earlier in the growing season when fuel moistures were higher and 

fire behavior and severity were accordingly reduced. 

Seasonal conditions associated with the winter-wet, summer-dry climate explain 

the marked and consistent differences between January and August NDVI, but yearto-year climate variation does not consistently align with annual changes in forest 

vigor (fig. 2, fig. 3). January 2006 was the least droughty of the eleven years as 

measured by the Palmer Drought Index both north and south of San Francisco, and 

this month experienced a decline in NDVI. However January 2003, an El Niño 

winter, was also non-droughty in the north, yet NDVI values peaked. Variation in 

January’s NDVI is not readily explained by monthly drought. In summer, the peak 

wetness of August 2005 corresponds to maximum NDVI across vegetation types, 

both in the north and south. However, droughty Augusts were not consistently 

associated with low NDVI values, particularly in 2001 and 2009. However, the years 

2002 and 2008 experienced both dry conditions and low NDVI values in August. 
GENERAL TECHNICAL REPORT PSW-GTR-238 

664

Figure 3—Variation in the Palmer Drought Severity Index (PDSI) for climate divisions 

401 (north of San Francisco) and 402 (south), 2000 to 2010 (www.ncdc.noaa.gov).

This complex effect of moisture stress on NDVI from January to August and 

inconsistent effects among years suggest that predicting how coast redwood is likely 

to respond to climate change is difficult. In as much as variation in NDVI can be used 

as a surrogate for productivity and as a predictor of vigor under a changing climate, 

coast redwood viability may be maximized by cool-wet summers. Such summer 

conditions are less likely to be associated with wildfire, which has a profound 

potential for eroding forest productivity far more than does interannual climate 

variability, as shown by this research. Across much of the coast redwood range, cool 

summers generally depend on the frequency of fog-stratus cover, which is sensitive 

to climate variation. 

Conclusion

As a coarse-filter tool for monitoring vegetation change, NDVI time series 

provide insights into the seasonal and year-to-year dynamics of coast redwood 

vegetation. The vigor of this evergreen forest responds to changes in climate and 

disturbance. In the north, forests are less affected by recent wildfires due to the 

greater cover of forest there and less area burned. Coast redwood forests in the south 

are already limited by the drier climate and ownership history. The decline in mature 

forest vigor after fire in both the north and the south is of great management concern, 

as these forests were historically resistant to fire that burned at high to moderate 

frequencies (Lorimer et al. 2009). If these patterns of disturbance and recovery 

continue, active fuels management may be necessary to restore resiliency to highvalue stands. As baseline conditions may reflect decades of fire exclusion and 

ingrowth, the landscape patterns of disturbance and recovery from remote sensing 

must be paired with ground-level monitoring to ensure that objectives are being met. 

This forest monitoring tool reveals not just where change takes place at moderate 

spatial resolution, but the magnitude and context of that change. Climate effects on 

the vigor of coast redwood vegetation are complex, but year-to-year variation in 

NDVI provides context for the magnitude of change caused by disturbances, such as 

wildfire. As this forest continues to change in coming years, such tools provide a way 

to monitor the cumulative effects of climate change and disturbances across and 

beyond the coast redwood range. 
Land Surface Phenology as a Coarse-Filter Indicator of Disturbance and Climatic Effects Across 

the Coast Redwood Range

665

Acknowledgments

J. Spruce helped develop the datasets used and W. Christie assisted with analysis. 

References 

Fox, L. 1988. A classification, map, and volume estimate for the coast redwood forest in 

California. California Department of Forestry and Fire Protection. 

http://frap.cdf.ca.gov/. 

Hargrove, W.W.; Spruce, J.P.; Gasser, G.E.; Hoffman, F.M. 2009. Toward a national early 

warning system for forest disturbances using remotely sensed canopy phenology.

Photogrammetric Engineering and Remote Sensing 75: 1150-1156.

Lorimer, C.G.; Porter, D.G.; Madej, M.A.; Stuart, J.D.; Veirs, S.D.; Norman, S.P.; O’Hara, 

K.L; Libby, W.J. 2009. Presettlement and modern disturbance regimes in coast 

redwood forests: implications for the conservation of old-growth stands. Forest 

Ecology and Management 258: 1038-1054.

667

Use of LiDAR and Multispectral Imagery to 

Determine Conifer Mortality and Burn 

Severity Following the Lockheed Fire

Russell A. White1 and Brian C. Dietterick1 

Abstract

The effects of wildfire on tree mortality, stand structure, and regeneration are major concerns 

in many California ecosystems. These effects are often highly variable across the landscape 

and can be difficult to assess at broad scales. There are few datasets that provide a detailed 

description of stand conditions, both before and after wildland fire, particularly in the Coast 

Redwood forest type. This study provides a unique collection of pre- and post-fire remote 

sensing data to evaluate the effects of the 2009 Lockheed Fire, a 7,817 ac wildland fire that 

occurred near Santa Cruz, California. High resolution, discrete-return airborne LiDAR 

collected in 2008 and 2010, provide detailed metrics of horizontal and vertical structure of 

second-growth Coast Redwood forest impacted by fire. In addition, 1 m color infrared 

imagery collected in 2009 and 2010, enable “fusion” of the three-dimensional LiDAR 

attributes with multispectral imagery. Remotely-derived estimates of burn severity will be 

compared to field-based assessments of burn severity and tree mortality conducted at 83 GPSlocated forest inventory plots. With these data, many parameters are available to characterize 

changes in vegetation condition following the fire including overhead canopy cover, 

vegetation height, vertical distribution of LiDAR returns, and indices of surface reflectance, 

such as NDVI. 

Key words: burn severity, coast redwood, GIS, LiDAR, remote sensing 

Introduction

Wildland fire is an important natural disturbance that initiates dramatic changes 

to bio-physical structure and processes across the landscape. Areas of diverse 

vegetation and rugged terrain can experience fire behavior that is similarly diverse. 

Given these conditions, characterizing different types of ecosystem responses to fire, 

and mapping their spatial extent can be a difficult task. In addition, the rate at which 

fire-adapted vegetation communities respond to fire is tremendous compared to 

periods without disturbance. Finally, in managed timber lands, understanding the 

effects of actions such as timber salvage, occurring within this period of rapid change 

remains a challenge. Remote sensing offers the ability to collect data over broad 

extents and at increasingly higher resolutions, and can supplement field observations 

that are often limited. This project aims to provide a rich geospatial dataset to help 

characterize ecosystem responses in a system affected by fire and also intensively 

managed. The following is a preliminary report of objectives, methods, and data 

collected, and provides a brief outlook on analyses that may be useful for 

investigating fire response in managed second-growth coast redwood forests. 

 

1 Research Assistant and Professor, respectively, Natural Resources Management Department, Cal Poly 

State Univ., San Luis Obispo, CA. (rwhite@calpoly.edu; bdietter@calpoly.edu). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

668

Burn severity maps for major fires throughout the nation are produced by the 

USDA Forest Service Remote Sensing Applications Center and the USGS Earth 

Resources Observation and Science. The intent of these programs is to provide 

broad-scale, accurate and timely map information to support post-fire hazard 

assessments and mitigation planning. These maps, termed Burned Area Reflectance 

Classification (BARC), are derived primarily from pre- and post-fire Landsat TM or 

ETM+ images using the Difference Normalized Burn ratio method (dNBR) (Key and 

Benson 2006). This approach has been validated in number of field studies and is 

considered appropriate given the emergency response objectives that the maps serve 

(Hudak 2004). Burn severity estimated through dNBR is also widely used to 

characterize and predict a variety of ecosystem responses to fire (Keeley 2009). For 

detailed assessments however, the relatively coarse 30 m resolution of Landsatderived products produces some limitations, which are especially apparent when 

compared to higher-resolution satellite data (Kokaly et al. 2007). As a spectral index, 

dNBR and other methods do not portray vegetation structure or changes in structure 

resulting from fire, only the relative change in spectral reflectance. In sparsely 

vegetated areas, it is possible that only a small change in reflectance is observed, 

despite significant changes occurring on the ground (Wang and Glenn 2009), thus 

severity in these cases may be underestimated depending on the density or 

reflectance of the pre-fire vegetation. As more remote sensing platforms become 

available, there are new opportunities to evaluate post-fire changes, beyond current 

operational methods. However, appropriate data analysis methods, and validation 

with field-measured ecological responses must also be developed. 

Airborne Light Detection and Ranging (LiDAR) is a method of remote sensing 

capable of providing highly detailed measurements of ground surface topography and 

above-ground vegetation characteristics. Use of LiDAR for measuring tree height, 

canopy closure, stand density and other characteristics has received widespread 

attention for resource management applications (Hudak et al. 2009). The prospect of 

using LiDAR to evaluate post-fire conditions in forestland settings has been 

acknowledged as promising (Lentile et al. 2006), though this application has only 

recently been explored (Angelo et al. 2010, Wing et al. 2010, Wulder et al. 2009). 

Information derived from pre- and post-fire LiDAR flights provides the opportunity 

to evaluate burn severity, not only in terms of spectral response, but now with respect 

to changes in the horizontal and vertical structure of the burned vegetation (Wang 

and Glen 2009). The limited extent of current LiDAR availability, the relatively high 

cost of new acquisitions, and the unpredictable nature of when and where wildland 

fires occur, do limit opportunities for widespread use of such pre- and post-fire 

analysis. However, as larger regional LiDAR datasets are acquired the likelihood 

increases that “pre-disturbance” data will exist for future analyses.

While research specific to pre- and post-fire analysis is relatively new, use of 

LiDAR for characterizing forest structural attributes has grown tremendously in the 

past decade (Hudak et al. 2009). Generally, LiDAR-derived metrics of forest 

attributes are compared to field measurements at either the plot scale, or by 

identifying individual trees. When evaluated at the plot scale, LiDAR point data are 

typically aggregated into fairly large pixels (20 m), and a host of statistical metrics 

are computed to describe the vertical distribution of points within each pixel 

(Falkowski et al. 2009). Such statistics include the maximum, average, standard 

deviation, or any percentile of point heights, percentage of canopy returns versus 

ground returns, percentage of first returns, percentage of returns within a given height 
Use of LiDAR and Multispectral Imagery to Determine Conifer Mortality and Burn Severity 

Following the Lockheed Fire

669

bin, and so on. Calculation of these parameters can be facilitated through the Fusion 

software developed and made available by the US Forest Service Remote Sensing 

Application Center (McGaughey 2010). LiDAR-derived metrics of stand structure 

can then be related to traditional field-based measurements through either stepwise 

multiple linear regression, or the non-parametric Regression Tree approach 

(Falkowski et al. 2009). Once a suitable model is developed, plot-level structural 

parameters can be predicted from the LiDAR data for all remaining pixels, forest 

wide.

This general approach has been used to characterize stand successional class 

(Falkowski et al 2009), estimate basal area and trees per acre (Hudak et al. 2008), and 

to estimate canopy height, canopy base height, canopy fuel weight, and bulk density 

(Andersen et al. 2005). Examples of LiDAR analysis in stands of second-growth 

redwood are limited, but in one study Gonzales et al. (2010) used field-measured 

heights in plots dominated by second-growth coast redwood to validate plot-level 

LiDAR-derived height with suitable results (r = 0.94, p < 0.0001). 

Approach

The purpose of this study is to evaluate the use of plot-level metrics derived from 

pre- and post-fire LiDAR and multispectral imagery to detect fire effects and 

mortality in second-growth coast redwood forest stands impacted by the 2009 

Lockheed Fire. Forest inventory data collected at permanent, fixed-radius plots 

within the burn area have been updated with post-fire mortality information to 

characterize stand conditions following the fire. Vegetation characteristics derived 

from the vertical distribution of LiDAR points, and from color infrared imagery will 

be extracted at inventory plot positions. Relationships between field-based and 

remotely-derived parameters will be used to characterize post-fire conditions 

throughout the broader forest. 

Study area 

The study area is located approximately 22 km north of Santa Cruz, California at 

Swanton Pacific Ranch, a 1295 ha educational and field research facility managed by 

California Polytechnic State University, San Luis Obispo. Topography is rugged with 

elevations ranging from 2 m to 466 m and ground surface slopes ranging from 0 

percent to over 100 percent. Approximately 512 ha of the property are forested, 

primarily by second-growth coast redwood, with associated species characteristic of 

the redwood series vegetation (Sawyer and Keeley-Wolf 1995). In August 2009 the 

Lockheed fire burned over 460 ha of Swanton Pacific Ranch, affecting approximately 

340 ha of the forested area. Within the redwood forest type, burn severity was 

predominantly low to moderate, with some instances of high severity crown fire near 

the ridgetops.

Field data collection 

Personnel and students at Swanton Pacific Ranch conduct forest inventory using 

a Continuous Forest Inventory (CFI) network comprised of permanent, 0.49 ha (1/5 

acre) fixed-radius plots located on a 152 m (500 ft) systematic grid (Piirto et al. these 

proceedings). Diameter and species are recorded for all trees greater than 2.54 cm 

DBH, while tree height, height to crown base, and crown class are recorded for all 
GENERAL TECHNICAL REPORT PSW-GTR-238 

670

conifers. A total of 83 CFI plots were located within the burn perimeter of the 

Lockheed Fire (fig. 1). Thirty-five of these plots were inventoried last in 2008 with 

the remaining 48 inventoried in 2003. 

Following the Lockheed Fire, a major effort was undertaken to re-establish CFI 

plots damaged from the fire. Plot center monuments lost or destroyed were reestablished based on distance and bearing information from three witness trees 

spaced throughout the plot. In December 2009, a post-fire mortality assessment was 

conducted to update the existing forest inventory with tree status indicating “living”, 

“dead”, “removed”, or “missing”. Components of the field mortality assessment are 

discussed by Auten and Hamey (these proceedings). The procedure was repeated in 

August 2010 for a first-year mortality assessment (fig. 2), and again May 2011. In 

each case, plot inventory was updated to reflect new mortality and to identify trees 

harvested in salvage operations. State Plane coordinates for all plots were recorded 

using a Garmin 60CSx GPS unit, logging points with a 30 second average. This plotlevel inventory data can be used to summarize different fire effects such as overall 

mortality, mortality by species, by diameter class and so on. Plot-level summaries 

will be related to remotely-derived metrics at these plots for the purpose of estimating 

fire-related changes throughout the forest. 

Figure 3—Eighty three continuous forest inventory plots located within the Lockheed 

Fire perimeter on Swanton Pacific Ranch, Davenport, CA.

LiDAR datasets 

A total of four airborne LiDAR flights have been conducted over the study area 

from 2008 to present. This represents one of the richest datasets in the southern Coast 

Range, and may be unique for characterizing coast redwood response to fire. Of 

these, two were initially planned for use at the start of this study. The original, now 

“pre-fire” dataset was collected in February 2008 during leaf off conditions by 

Airborne 1, El Segundo, California. The LiDAR sensor used was an Optech ALTM 

3100 sensor operating at 100 kHz pulse repetition frequency. The 2008 LiDAR flight 

and sensor parameters used (White et al. 2010) were:

LiDAR Survey Parameters
Use of LiDAR and Multispectral Imagery to Determine Conifer Mortality and Burn Severity 

Following the Lockheed Fire

671

Altitude (m AGL) 850 

Beam divergence (mrad) 0.23 

Scan angle (0

) 14 

Scan width (m) 425 

Swath overlap (%) 50 

Pulse rate (kHz) 100 

Sampling density (pulses/m2

) 6 

Following the fire, a second flight was contracted and flown by Airborne 1 with 

the goal of achieving the best possible bare-earth DEM given the reductions in 

overhead canopy and near-ground vegetation after the fire. This flight took place in 

March 2010 with similar flight parameters, but used an updated sensor, the Optech 

ALTM Orion operated at 150 kHz pulse repetition frequency. Two additional flights 

have taken place over the study area. The next flight to take place was a region-wide 

collection coordinated by the Association of Monterey Bay Governments (AMBAG) 

covering a 1700 square mile area including Santa Cruz County, and portions of 

Monterey and San Benito Counties. This flight was flown during leaf-on conditions 

in August 2010 with flight and sensor parameters designed to meet the USGS base 

LiDAR specifications for projects funded under the 2009 ARRA. 

Finally, the most recent flight was coordinated by researchers at UC Santa Cruz 

and conducted by the National Center for Airborne Laser Mapping (NCALM). This 

flight took place in leaf-off conditions in February 2011 covering the Scotts Creek 

watershed. Together, these datasets present valuable opportunities by improving the 

temporal resolution of post-fire change analyses. This can be particularly important 

for understanding the sequence of natural and anthropogenic changes following the 

fire.

Image datasets

To complement the rich structural information provided by LiDAR datasets, 

natural color and near-infrared imagery was also collected over the study area in July 

2010, approximately 1 year following the fire. This imagery provides additional high 

resolution (0.5 m) spectral information of overstory crown condition, which can be 

used to characterize fire effects. Three consecutive years of infrared imagery are 

planned to document changes in vegetation condition over an intermediate 

timeframe. Work is presently underway to orthorectify the first- and second-year 

imagery using the LiDAR-derived Digital Surface Model. Together these data will 

provide coincident information of tree crown reflectance and vertical structure.

Preliminary analysis

The following example may illustrate how the data available in this study can be 

used to investigate different types of ecosystem responses. For example, the loss of 

the understory strata in the uneven-aged structured coast redwood forest type may be 

difficult to assess using airborne imagery alone, especially where the overstory 

remains intact (fig. 2). 
GENERAL TECHNICAL REPORT PSW-GTR-238 

672

Figure 2—Understory coast redwood before fire in 2008 (left), and after fire (2009).

Characterizing the vertical distribution of LiDAR returns before and after the fire 

may enable such distinctions to be made. For an initial evaluation, a 5 m resolution 

grid measuring percent canopy cover was derived from the 2008 and 2010 LiDAR. 

Canopy cover was calculated as defined by McGaughey (2010) as the ratio of LiDAR 

returns falling above a given height (in this case 1 m), divided by the total number of 

returns for each pixel. The difference in 2008 and 2010 canopy cover layers (fig. 3) 

indicates areas experiencing drastic reductions in cover (dark regions), whereas other 

areas, predominantly the near stream channels, experienced little to no measured 

reduction in cover. Further vertical stratification of LiDAR returns within the canopy 

may be useful for identifying changes to specific understory strata. 

Figure 3—Difference in percent canopy cover: Mar 2010 - Feb 2008. Darker shading 

represents reductions in canopy cover.

Separate types of analysis are possible with this dataset, and the choice of

analysis method can highlight different changes across the study area. In a second 

example, the Digital Surface Models (1 m resolution grids of highest-hit elevations) 

from three datasets Feb 2008, March 2010 and August 2010 were differenced to 

identify trees removed over the intervening time periods (fig. 4). This map provides 

an estimate of overstory trees removed a) following the fire, b) during initial salvage 

operations, and finally c) combined over the time period from 2008 to 2010. 
Use of LiDAR and Multispectral Imagery to Determine Conifer Mortality and Burn Severity 

Following the Lockheed Fire

673

Figure 4—Difference in DSM: a) Before and after fire, Feb 2008 to March 2010, b) 

Before and after salvage operations, Feb 2010 to August 2010, c) Cumulative 

change, Feb 2008 to August 2010. Shaded regions indicate a negative height 

change greater than 3 m.
GENERAL TECHNICAL REPORT PSW-GTR-238 

674

Conclusion

While preliminary in nature, this effort documents the field-based and remote 

sensing data collected at Swanton Pacific Ranch following the Lockheed Fire. Fieldbased forest inventory at permanent plots provide a basis for evaluating changes in 

stand characteristics over time. Relating field-measured stand characteristics to 

remotely-derived metrics from LiDAR and multispectral imagery can expand the 

spatial extent of forest measurement and provide a continuous map of forest 

attributes. Utilizing high resolution remote sensing products both before and after 

disturbance can further enhance our understanding of how forest attributes respond to 

disturbance. This preliminary exploration of the data suggest many potential modes 

of data analysis, useful for addressing different ecological responses following fire, 

however, these methods must be further developed and ultimately validated by field 

measurement. As remote sensing data are collected at higher spatial and temporal 

resolutions opportunities exist to supplement traditional forest inventory approaches, 

particularly useful for areas of heterogeneous forest conditions and areas responding 

to both natural and anthropogenic disturbances. 

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