Forest 

Service

Oregon’s Forest Resources, 

2006–2015: Ten-Year Forest 

Inventory and Analysis Report

United States Department of Agriculture

Pacific Northwest 

Research Station

General Technical Report

PNW-GTR-971

October

2018 DEPAR TMENT OF AGRICULT URE
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Technical Editors 

Marin Palmer and Glenn Christensen are foresters and Olaf Kuegler is a statistician, 

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

Forestry Sciences Laboratory, 620 SW Main Street, Suite 400, Portland, OR 97205. 

Contributing Authors

John Chase is a geographic information system/remote sensing specialist, Jeremy Fried

is a research forester, Sarah Jovan is a research ecologist, and Katherine Mercer is a 

forestry technician, U.S. Department of Agriculture, Forest Service, Pacific Northwest 

Research Station, 620 SW Main Street, Suite 400, Portland, OR 97205. Andrew Gray

is a research ecologist and David M. Bell is a research forester, U.S. Department of 

Agriculture, Forest Service, Pacific Northwest Research Station, 3200 SW Jefferson Way, 

Corvallis, OR 97331. Sara Loreno is a natural resource data scientist, Ecotrust, 721 NW 

9th Avenue #200, Portland, OR 97209. Todd Morgan is director of the Bureau of Business 

and Economic Research, University of Montana, Gallagher Business Building, 32 Campus 

Drive, Missoula, MT 59812.

Cover photo: The Imnaha River canyon with Douglas-fir and grand fir trees in foreground, Wallowa County, Oregon, 2017. Photo by J. Sprovkin.
Oregon’s Forest Resources, 2006–2015: 

Ten-Year Forest Inventory and Analysis Report

Marin Palmer, Glenn Christensen, and Olaf Kuegler, 

Technical Editors

Contributing authors: John Chase, Jeremy Fried, Sarah Jovan, 

Katherine Mercer, Andrew Gray, David M. Bell, Sara Loreno, 

and Todd Morgan

U.S. Department of Agriculture

Forest Service

Pacific Northwest Research Station

Portland, Oregon

General Technical Report PNW-GTR-971

October 2018

Abstract

Palmer, Marin; Kuegler, Olaf; Christensen, Glenn, tech. eds. 2018. Oregon’s forest 

resources, 2006–2015: Ten-year Forest Inventory and Analysis report. Gen. Tech. Rep. 

PNW-GTR-971. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station. 54 p.

Oregon has 30 million forested acres that cover roughly half the state’s land area. The 

Forest Inventory and Analysis (FIA) program reports on the status and trends of Oregon’s 

forest resources, producing comprehensive updates every 5 years. This report provides 

detailed estimates of forest area, tree species composition and distribution, volume, 

biomass, carbon, standing dead trees and down wood, and understory vegetation on forest 

land for the state of Oregon based on the annual FIA forest land inventory through 2015. 

It also includes the first estimates of annual growth, mortality, and removals on forest 

land available from remeasured annual inventory plots, representing 50 percent of the full 

10-year cycle. The FIA program collected inventory data on 9,439 forested plots during the 

2006–2015 measurement cycle. Oregon has more than 10 billion live trees on forest land 

that collectively represent nearly 107 billion ft3

 of net volume or nearly 1 billion Mg of carbon. Three-fourths of this forest volume occurs on the moist west side of the state. Douglas-fir, Oregon’s state tree, represents the majority of Oregon’s softwood lumber production. 

More than one-third of the forested area and more than one-half of forest volume occurs in 

stands dominated by Douglas-fir trees. 

Keywords: Biomass, carbon, dead wood, FIA, forest change, Forest Inventory and 

Analysis, forest land, inventory, timber volume, timberland, Oregon. 

Summary

Key Forest Inventory and Analysis (FIA) Statistics, Oregon, 2006–2015

• Number of forested plots measured by the FIA program (2006–2015): 9,439

• Estimated total forest area: 29.7 million ac 

• Estimated number of live trees: 10.3 billion 

• Estimated net live tree volume: 106.9 billion ft3

• Estimated aboveground net live biomass: 2.2 billion tons

• Estimated aboveground net live carbon: 975.6 million Mg
Contents

1 Background 

1 What Is Forest Inventory and Analysis?

1 How Does FIA Define a Forest?

1 What Is in This Report?

2 Where Can I Find Additional Information?

2 Forest Resources

2 Importance of Oregon’s Forests

2 Forest Area and Composition

9 Forest Ownership

11 Forest Volume

11 Forest Biomass and Carbon Storage

19 Forest Productivity

19 Timber Resources and Forest Productivity

23 Average Annual Growth, Removals, and Mortality

34 Wildlife Habitat 

38 Understory Vegetation and Nontimber Forest Products

40 Forest Recreation

41 Forest Health 

41 Damaging Agents

42 Wildfire

45 Online Tables 

50	 Common and Scientific Plant Names

51 Acknowledgments

51 Metric Equivalents

51 U.S. Equivalents

51 Literature Cited
1

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Background 

What Is Forest Inventory and Analysis?

The Forest Inventory and Analysis (FIA) program of the 

U.S. Forest Service was created in 1928 to provide comprehensive information on the nation’s forest resources 

necessary for economic and forest management planning. 

Forest inventories were conducted periodically in each state 

until the Agricultural Research, Extension, and Education 

Reform Act of 1998 (the Farm Bill) mandated a nationally 

consistent methodology in which a portion of all plots in 

each state were measured each year. States in the Pacific 

Northwest Forest Inventory and Analysis (PNW-FIA) unit 

are on a 10-year measurement cycle. 

How Does FIA Define a Forest?

The FIA collects data only in forested areas; therefore, 

the definition used for forest land affects the estimates 

produced in each inventory year. The FIA program 

defines a forest as currently or formerly (within 30 years) 

at least 10 percent canopy cover of trees of any size and 

not currently developed for nonforest use. Forests must be 

at least 1 ac in size where a minimum width of 120 ft is 

maintained. Prior to 2013, the FIA program used stocking 

tables to define forest based on a minimum of 10-percent 

stocking rather than canopy cover. This procedural 

change affects a small percentage of sampled plots, and 

estimates of forest land area-change between 2001–2005 

and 2011–2015 have been adjusted to consistently use the 

current definition. The PNW-FIA collected information 

on forested lands using both definitions to allow calibration between estimates.

What are the differences between timberland, other 

forest land, and reserved forest land? —

• Timberland: Forest land that is producing or is 

capable of producing crops of industrial wood and 

not withdrawn from timber utilization by statute or 

administrative regulation. (Note: Areas qualifying 

as timberland are capable of producing in excess of 

20 cubic feet per acre per year of industrial wood in 

natural stands. Currently inaccessible and inoperable 

areas are included.) 

• Reserved forest land: Land permanently reserved from 

wood products utilization through statute or administrative designation. Examples include national forest 

wilderness areas and national parks and monuments.

• Other forest land not capable of producing 20 ft3 of 

wood per acre per year, often occurring on sites with 

poor soils.

What Is in This Report?

This report presents a summary of Oregon’s forest resources, 

highlighting key forest characteristics estimated from inventory field plots sampled across the state over the 10-year 

period from 2006 through 2015. It also includes the first set 

of remeasurement data from the FIA annual inventory of 

Oregon (plots measured for the second time between 2011 

and 2015). Estimates presented here are an update to prior 

estimates reported in Donnegan et al. 2008 and Bansal et al. 

2017 and are based on field measurements of 9,439 forested 

plots, of which 4,594 have now been remeasured and can be 

used to assess change in forest conditions (fig. 1). We present 

estimates of current forest area, ownership, composition, 

volume, and distribution, as well as information on growth, 

mortality, and removals. We also provide information on 

forest health via occurrence of forest pathogens and stands 

affected by fires, and we include information on understory 

vegetation and down woody debris in Oregon’s forests.

Figure 1—Field crews measured 9,439 forested plots in Oregon 

from 2006 to 2015. Working in an area burned by the 2015 Canyon 

Creek Complex Fire, Malheur National Forest.

J. Sprovkin
2

GENERAL TECHNICAL REPORT PNW-GTR-971

An extensive set of 125 summary data tables accompanies this report and can be downloaded from the Web at 

https://www.fs.fed.us/pnw/pubs/pnw_gtr971-supplement.

pdf. These tables provide estimates of forest area, number 

of trees, volume, biomass, carbon, forest change, National 

Forest System (NFS) summaries, down wood, understory 

vegetation, tree damages, and timber-products output for the 

state. A complete list of online tables is available at the end 

of this report. 

Where Can I Find Additional Information?

Donnegan et al. (2008) and Bansal et al. (2017) provided 

detailed information on annual inventory methods and definitions as well as prior periodic inventories implemented in 

Oregon. The PNW-FIA website (https://www.fs.fed.us/pnw/

rma/) has most of the data used in this report accessible 

through the PNW-FIADB (Forest Inventory and Analysis 

Database) application (requires Microsoft Access1) that 

contains both national core data and regional variables collected only by the PNW-FIA unit. This site has up-to-date 

reports and statistics for each state in the PNW-FIA unit 

and field guides that include PNW-FIA regional variables. 

The main Web page for FIA is at https://www.fia.fs.fed.

us/. Links lead to resources such as publications or data and 

tools. EVALIDator and DATIM are the primary estimation 

tools that allow users to generate custom summaries from 

the most recent data in FIADB. Definitions of tables and 

fields are available in the FIADB user manual (O’Connell et 

al. 2017), and core FIA field guides contain details on how 

each data item was collected. A glossary of FIA terms can 

be found at https://www.nrs.fs.fed.us/fia/data-tools/state-reports/glossary/default.asp. 

Forest Resources

Importance of Oregon’s Forests

Forests provide many ecosystem services and benefits to 

society, including timber production, carbon storage, water 

regulation, aesthetic amenities, recreation, and wildlife 

(Binder et al. 2017, Boyd and Banzhaf 2007). Oregon forests 

provide each of these benefits, and forest lands across the 

state are managed in different ways to balance these and 

other priorities. The iconic temperate rainforests in the 

Pacific Northwest contain some of the oldest and tallest 

trees in the country and store more aboveground biomass 

than most other forest ecosystems worldwide (Keith et 

al. 2009). Forest products are an important component of 

Oregon’s rural economy. Many Oregonians experience their 

state’s forests through the lens of recreation, whether at sites 

as popular as Crater Lake or in remote wilderness areas. As 

Oregon’s population continues to grow, so will the importance of the state’s forests in providing ecosystem services. 

Forest Area and Composition

Oregon contains diverse and productive forest lands that 

cover almost half the state (fig. 2). The current forested area 

estimate of 29,656,200 ac (table 1) is remarkably similar 

to the state’s initial forest inventory estimate of 29,661,000 

ac in 1942, although exact forest land definitions differed 

across inventories, and some forested area has been lost in 

Nonforest land

51.6%

Unreserved other forest 5.2%

Reserved productive forest 4.2% 

Timberland

38.6%

Reserved other forest 0.4%

Figure 2—Forest Inventory and Analysis area classification by 

land class category, Oregon, 2006–2015.

1 The use of trade or firm names in this publication is for reader 

information and does not imply endorsement by the U.S. Department of Agriculture of any product or service.
3

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Table 1—Area of forest land, by ownership and land status, Oregon 2006–2015

Land status

Unreserved forests Reserved forests

Timberland Other forest Total Productive Other forest Total All forest land

Ownership Total SE Total SE Total SE Total SE Total SE Total SE Total SE

Thousand acres

USDA Forest Service:

National forest 11,091.6 54.6 539.2 29.7 11,630.8 50.7 2,248.2 52.3 199.2 33.2 2,447.4 46.5 14,078.2 48.0

National grasslands — — 14.9 5.2 14.9 5.2 — — — — — — 14.9 5.2

Total 11,091.6 54.6 554.1 29.9 11,645.7 50.7 2,248.2 52.3 199.2 33.2 2,447.4 46.5 14,093.1 48.1

Other federal government:

Bureau of Land Management 2,248.2 56.8 1,200.5 73.1 3,448.7 84.0 80.0 21.4 44.6 16.7 124.6 27.1 3,573.3 81.6

Department of Defense or Energy 0.1 0.1 — — 0.1 0.1 — — — — — — 0.1 0.1National Park Service — — — — — — 147.5 28.6 12.9 9.1 160.4 29.7 160.4 29.7

U.S. Fish and Wildlife Service — — — — — — 11.3 8.3 5.3 6.0 16.6 10.2 16.6 10.2

Other federal 6.1 6.2 — — 6.1 6.2 8.9 6.8 — — 8.9 6.8 14.9 9.2

Total 2,254.4 57.1 1,200.5 73.1 3,454.9 84.2 247.7 36.4 62.7 19.8 310.4 41.0 3,765.3 77.7

State and local government:

Local 129.0 27.2 41.7 14.9 170.7 31.4 16.6 10.4 — — 16.6 10.4 187.2 33.1State 821.7 36.2 76.6 20.8 898.3 40.5 37.0 14.7 6.4 5.2 43.4 15.4 941.7 40.3

Total 950.7 41.5 118.2 25.6 1,069.0 47.8 53.6 17.9 6.4 5.2 60.0 18.5 1,129.0 47.4

Corporate private 6,218.8 129.5 268.3 38.9 6,487.1 133.0 — — — — — — 6,487.1 133.0Noncorporate private:

Nongovernmental conservation or 

natural resource organizations

216.1 35.5 — — 216.1 35.5 — — — — — — 216.1 35.5

Unincorporated partnerships, 

associations, or clubs

4.5 4.6 11.8 8.4 16.3 9.6 — — — — — — 16.3 9.6

Native American 402.4 48.5 77.4 21.8 479.7 52.9 — — — — — — 479.7 52.9

Individual 2,527.5 106.2 942.0 70.7 3,469.6 123.5 — — — — — — 3,469.6 123.5

Total 3,150.5 115.7 1,031.2 74.0 4,181.7 132.3 — — — — — — 4,181.7 132.3

All private 9,369.3 112.1 1,299.5 82.5 10,668.8 118.6 — — — — — — 10,668.8 118.6

All owners 23,666.0 130.7 3,172.3 116.6 26,838.3 147.4 2,549.5 66.2 268.3 39.0 2,817.8 64.6 29,656.2 140.7

Note: Totals may be off because of rounding; data subject to sampling error; SE = standard error; — = less than 50 acres was estimated.
4

GENERAL TECHNICAL REPORT PNW-GTR-971

0

5

10

15

20

25

30

35

1940 1950 1960 1970 1980 1990 2000 2010 2020

Forest

Timberland

Area (million acres)

Year

Figure 3—Area of forest land and timberland (thousand acres) by inventory year in Oregon, 1942–2015. Note: estimates from 2000 

to 2015 are based on the annual inventory design and protocols, while prior estimates were based on periodic inventories which used 

different designs and methods (Bassett and Choate 1974, Campbell et al. 2004, Farrenkopf 1982, Gedney 1982, Metcalf 1965, Moravets 

et al. 1942). Differences shown here represent a combination of real change, wilderness designations that placed timberland into reserved 

status, and protocol differences over time such as the use of stockability factors during periodic inventories.

recent decades owing to land use change (Lettman et al. 

2016). Timberland area estimates (the unreserved, productive component of forest land) have been more dynamic 

over the past eight decades owing to differing timber 

stocking definitions and reserved classifications at each 

inventory date, but productive timberland area in the state 

remains around 24 million ac (fig. 3). 

Conifers (softwoods) dominate the state’s forest cover 

as more than 85 percent of the total forest area, while 

hardwoods comprise 11 percent, and 4 percent is currently 

nonstocked (forested areas that currently lack 10-percent 

tree cover, typically on account of recent fire or harvest). 

Douglas-fir (10,942,600 ac) and ponderosa pine (5,169,300 ac) 

are the two predominant forest types with 37 and 17 percent 

of the state’s forest area, respectively (fig. 4). Forest area is 

evenly distributed on the east and west sides of the state, 

with 49 percent of Oregon’s forested land east of the Cascade 

Crest. Western Oregon’s forests are mainly composed of 

Douglas-fir forest types with some hemlock/Sitka spruce, 

alder/maple, and other hardwoods that thrive in the moist 

maritime climate. Eastern Oregon forests are mainly drier 

climate types; ponderosa pine forest types dominate, with 

elements of western juniper and lodgepole pine. Fir/spruce/

mountain hemlock forests grow at higher elevations along the 

Cascade crest (fig. 5).

Pacific Northwest forests contain a broad range of 

stands that are unique in their age and size, reflecting both 

young, intensively managed productive timber stands and 

intact old-growth forests and stands in large-diameter 

classes. While 54 percent of Oregon’s forests are between 

1 and 80 years old, 8 percent (more than 2 million ac) are 

greater than 200 years old (fig. 6). Douglas-fir stands tend 

to be younger than other common softwood species, and the 

same is true for alder/maple forest types compared to other 
5

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

0 2,000 4,000 6,000 8,000 10,000 12,000

Douglas-fir

Ponderosa pine

Fir/spruce/mountain hemlock

Western juniper

Lodgepole pine

Hemlock/Sitka spruce

Western larch

Other western softwoods

Alder/maple

Western oak

Tanoak/laurel

Other hardwoods

Elm/ash/cottonwood

Woodland hardwoods

Aspen/birch

Area (thousand acres)

Western Oregon Eastern Oregon

Figure 4—Area of softwood and hardwood forest type groups in eastern and western Oregon, 2015.

hardwoods (fig. 7). Differences in age and diameter distributions among species reflect a combination of ecology, 

natural disturbances, and forest management (fig. 8). 

Oregon is home to more than 10.2 billion live trees 

on forest land, or an average of 347 trees per forested acre 

Douglas-fir is the most numerous species, with nearly 

one-quarter (24 percent) of all trees in the state. Other 

top species groups include lodgepole pine, true firs, and 

ponderosa and Jeffrey pines. Tree numbers are more evenly 

distributed in the smaller diameter classes, while among 

large-diameter trees (greater than 30 in diameter at breast 

height [d.b.h.]), Douglas-fir dominates (fig. 9).
6

GENERAL TECHNICAL REPORT PNW-GTR-971

.

0 25 50

Miles

Forest type group

Douglas-fir 

Fir/spruce/mountain hemlock 

Hemlock/Sitka spruce

Western larch

Ponderosa pine

Lodgepole pine

Western juniper

Other western softwoods

Alder/maple

Western oak

Tanoak/laurel

Other hardwoods

Nonstocked

Forest

Nonforest

Figure 5—Distribution of forest type groups based on field observations at Forest Inventory and Analysis sample sites, Oregon, 

2006–2015 (forest/nonforest geographic information system layer: Blackard et al. 2008; Oregon boundary polygons: Oregon Bureau 

of Land Management, Oregon/Washington State Office).

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

Area (thousand acres)

Age class (years)

Softwoods 2005

Softwoods 2015

Hardwoods 2005

Hardwoods 2015

1–20 21–40 41–60 61–80 81–100 101–120 121–140 141–160 161–180 181–200 201+

Figure 6—Stand age distribution for softwoods and hardwoods in Oregon, 2005 and 2015. To ensure that the estimates are comparable, 

the 2015 estimates include only plots that were remeasured in 2011–2015. Therefore, they differ from the 2006–2015 estimates discussed 

elsewhere in this report.

J. Chase
7

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

0

500

1,000

1,500

2,000

2,500

3,000

Area (thousand acres)

Age class (years)

A

0

50

100

150

200

250

300

350

400

Area (thousand acres)

Age class (years)

Alder/maple

Western oak

Tanoak/laurel

Elm/ash/cottonwood

Other hardwoods

B

1–20 21–40 41–60 61–80 81–100 101–120 121–140 141–160 161–180 181–200 201+

1–20 21–40 41–60 61–80 81–100 101–120 121–140 141–160 161–180 181–200 201+

Douglas-fir

Ponderosa pine

Fir/spruce/mountain hemlock

Western juniper

Lodgepole pine

Figure 7—Stand age distributions of the most common (A) softwood and (B) hardwood species in Oregon, 2006–2015.
8

GENERAL TECHNICAL REPORT PNW-GTR-971

Figure 8—Species stand ages are influenced by life histories, disturbance, and management. (A) Douglas-fir is typically long lived, but 

often harvested on 50-year-or-shorter rotations, while (B) lodgepole pine frequently experiences mortality caused by insects and disease 

in densely stocked stands.

J. Sprovkin B. Borden
9

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Forest Ownership

Oregon’s forest lands are owned and managed by a variety 

of public and private entities. Thirty-six percent of forest 

land is under private ownership, of which 88 percent is considered productive timberland. Sixty-one percent of private 

forest land is owned by corporations, while 39 percent is 

noncorporate, mainly owned by American Indian tribes and 

individuals (4 and 33 percent, respectively). Privately owned 

forest lands tend to be at lower elevation sites and in higher 

productivity classes. Both ownership and site characteristics 

affect management; Oregon’s private forest lands tend to be 

managed more intensively than public lands (fig. 10), so they 

hold just 24 percent of the standing volume despite covering 

36 percent of the forest land base.

Almost 19 million ac of Oregon forest lands are 

under public management; 48 percent are managed by the 

National Forest System (NFS) and an additional 13 percent 

are under other federal management. State and local governments manage 4 percent of Oregon’s forest lands. Publicly 

owned forests tend to be at higher elevations and on average 

are on less productive sites, but these forests contain a range 

of characteristics and productivity classes. Fifteen percent 

of public forests are reserved (removed by statute from 

management for timber production), while 75 percent are 

classified as productive timberland. 

Ownership trends differ east and west of the Cascade 

crest (fig. 11). Western Oregon has a larger share of private 

corporate and state forest lands, while almost 60 percent of 

eastern Oregon’s forests are NFS managed. Eight percent 

of western Oregon forests are reserved and 88 percent are 

timberland, while eastern Oregon forests are 11 percent 

reserved and 71 percent timberland. Although statewide 

ownership estimates have changed slightly since the 2010 

inventory, Oregon’s forest ownership groups have remained 

mostly stable during this time period (fig. 12). 

0

25

50

75

100

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 49+

Percentage of live trees

Diameter class (d.b.h. inches)

All hardwoods

Sugar pine

Sitka spruce

Engelmann and other spruces

Western larch

Western redcedar

Incense-cedar

Western juniper

Other western softwoods

Western hemlock

Ponderosa and Jeffrey pines

True fir

Lodgepole pine

Douglas-fir

Figure 9—Proportional species composition on forest land by diameter class, Oregon, 2006–2015. Value shown on the horizontal axis 

represents the midpoint of the 2-inch diameter class, i.e., 6 inches refers to trees with diameter of 5 to 6.9 inches. D.b.h. = diameter at 

breast height.
10

GENERAL TECHNICAL REPORT PNW-GTR-971

Figure 10—Private land in Lane County, Oregon, demonstrating active timber management.

Western Oregon

County-municipal 0.8%

Other federal 0.1%

BLM

14.2%

State

5.1%

Private

corporate

30.5%

National

forests

36.2%

Private

noncorporate

13.1%

Eastern Oregon

County municipal 0.4%

State 1.2%

Other federal 0.1%

NPS 0.6%

National grasslands 0.1%

Private

noncorporate

15.1%

National

forests

59.4%

BLM

9.8%

Private

corporate

12.8%

Figure 11—Percentage of forest land by owner group in western and eastern Oregon, 2006–2015. BLM = Bureau of Land Management, 

NPS = National Park Service.

 B. Borden
11

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Forest Volume

Forest volume is a critical variable that facilitates accurate estimates of change in standing timber availability, 

growth and mortality, biomass and carbon mass accumulation, and as input to fuel and habitat models. The FIA 

volume estimates are typically calculated by species, 

using measurements of a tree’s diameter and height 

(Woodall et al. 2011).

Oregon’s forests contain almost 107 billion ft3

 of live 

tree volume, slightly more than the 101 billion ft3 estimated 

in 2005 (fig. 13). Fifty-five percent of current volume is 

located on NFS lands. The vast majority (85 percent) of 

volume resides in productive timberlands, while 15 percent 

is in reserved areas (table 2). Douglas-fir dominates with 58 

percent of total live tree volume and more than 5 billion ft3

resides in Douglas-fir trees greater than 49 inches d.b.h. (fig. 

14). Volume per acre provides an indication of the potential 

productivity of a site, but is highly dependent on relative 

density with young stands typically carrying less volume 

per acre than mature stands. Oregon averages 3,604 ft3

 of 

live tree wood volume per forested acre. Hemlock/Sitka 

spruce forest types carry the most standing volume per acre, 

while lodgepole pine and woodland species such as western 

juniper carry far less (fig. 15). 

Forest Biomass and Carbon Storage

Oregon forests contain 2.2 billion tons of aboveground live 

tree biomass. The National Forest System has the largest 

biomass share, with 55 percent of forest biomass, while 25 

percent is held on private ownerships. The moist west side 

of the state contains the majority (75 percent) of forest biomass, mainly in coniferous (softwood) species, which make 

up 91 percent of biomass statewide. More than 57 percent 

of Oregon’s biomass is in stands dominated by Douglas-fir, 

while the fir/spruce/mountain hemlock forest-type group is 

in second place at 14 percent. 

.

Forest Owner

USFS

BLM

Other public

State and local

Private and tribal

Nonforest

Water

Counties

Miles

250 50

Figure 12—Oregon forest ownership categories (Oregon boundary and ownership polygons: Bureau of Land Management, Oregon/

Washington State Office [BLM]). USFS = U.S. Forest Service.

J. Chase
12

GENERAL TECHNICAL REPORT PNW-GTR-971

0

20,000

40,000

60,000

80,000

100,000

120,000

2005 2015

All hardwoods

All other softwoods

Douglas-fir

Live tree net volume (million cubic feet)

Figure 13—Live tree net volume of softwoods and hardwoods in 

Oregon, 2005 and 2015. To ensure that the estimates are comparable, the 2015 estimates include only plots that were remeasured in 

2011–2015. Therefore, they differ from the 2006–2015 estimates 

discussed elsewhere in this report.

Figure 14—Diameter class distribution of live tree net volume on forest land, top five species groups, Oregon, 2006–2015. 

d.b.h. = diameter at breast height.

Douglas-fir True fir Ponderosa and Jeffrey pines Western hemlock Red alder

0

1,000

2,000

3,000

4,000

5,000

6,000

6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 49+

Diameter class (d.b.h. inches)

Net volume (million cubic feet)
13

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Table 2—Net volume of live treesa on forest land, by ownership and land status, Oregon 2006–2015

Land status

Unreserved forests Reserved forests

Timberland Other forest Total Productive Other forest Total All forest land

Ownership Total SE Total SE Total SE Total SE Total SE Total SE Total SE

Million cubic feet

USDA Forest Service:

National forest 46,351.6 538.9 559.5 61.7 46,911.2 534.6 11,885.5 517.4 371.5 106.4 12,257.0 507.0 59,168.2 656.1

National grasslands — — 1.5 0.8 1.5 0.8 — — — — — — 1.5 0.8

Total 46,351.6 538.9 561.0 61.7 46,912.6 534.6 11,885.5 517.4 371.5 106.4 12,257.0 507.0 59,169.7 656.1

Other federal government:

Bureau of Land Management 14,914.5 538.0 383.1 50.5 15,297.6 536.2 510.4 165.7 14.0 7.2 524.4 165.8 15,821.9 527.3

National Park Service — — — — — — 726.8 156.5 78.5 64.8 805.3 168.8 805.3 168.8Other federal 7.8 8.0 — — 7.8 8.0 37.5 30.1 — — 37.5 30.1 45.3 31.1

Total 14,922.3 538.1 383.1 50.5 15,305.3 536.2 1,289.2 225.0 94.0 65.2 1,383.3 233.4 16,688.6 515.3

State and local government:

Local 383.4 113.1 13.4 7.1 396.8 113.4 131.3 90.1 — — 131.3 90.1 528.1 144.5

State 4,476.7 284.2 38.5 22.0 4,515.2 284.9 363.4 175.7 23.8 30.8 387.2 177.8 4,902.4 305.0

Total 4,860.1 294.9 51.9 23.1 4,912.0 295.6 494.7 197.2 23.8 30.8 518.5 199.0 5,430.5 316.3

Corporate private 16,172.2 589.0 218.0 76.1 16,390.2 592.8 — — — — — — 16,390.2 592.8Noncorporate private:

Nongovernmental 

conservation or natural resource organizations

600.5 151.6 — — 600.5 151.6 — — — — — — 600.5 151.6

Unincorporated partnerships, 

associations, clubs

13.5 13.8 0.3 0.3 13.8 13.8 — — — — — — 13.8 13.8

Native American 1,172.7 208.8 40.3 20.6 1,212.9 209.6 — — — — — — 1,212.9 209.6Individual 6,867.3 411.8 494.6 59.0 7,361.8 414.0 — — — — — — 7,361.8 414.0

Total 8,653.9 469.9 535.2 62.3 9,189.1 471.6 — — — — — — 9,189.1 471.6

All private 24,826.1 625.3 753.1 97.8 25,579.3 626.1 — — — — — — 25,579.3 626.1All owners 90,960.2 1,001.4 1,749.1 128.2 92,709.3 998.4 13,669.5 597.7 489.3 128.6 14,158.8 592.6 106,868.0 1,058.9

Note: Totals may be off because of rounding; data subject to sampling error; SE = standard error; — = less than 50,000 cubic feet was estimated.a Includes all live trees ≥= 5 inches in diameter at breast height, consisting of growing stock, rough cull, and rotten cull tree classes.
14

GENERAL TECHNICAL REPORT PNW-GTR-971

Change in carbon mass is proportional to the change in 

biomass, and is a basic measure of productivity that can be 

used to determine forest carbon stocks and the flux of carbon 

into and out of atmospheric carbon pools. In Oregon, 976 

million Mg of aboveground carbon2

 is stored in live trees 

(table 3); note: metric units are used for carbon mass to remain 

consistent with accepted accounting practices). The Pacific 

Northwest is known for its old-growth forests; and large-diameter trees, while less numerous than small-diameter trees, 

store a large fraction of the carbon. Trees >25 inches d.b.h. 

stored more than 36 percent of the aboveground carbon (fig. 

16). Forest carbon density is concentrated on the west side of 

the Cascades with Multnomah, Lane, Clackamas, and Benton 

Counties having the highest aboveground live tree carbon per 

hectare (fig. 17). The Douglas-fir species group has the highest 

total carbon storage (501 million Mg), with true firs in a distant second place (110 million Mg); however, sugar pines and 

Sitka spruce store the most aboveground carbon per live tree 

(on average, 301 and 242 kg of carbon per tree, respectively). 

Two important components of aboveground forest 

biomass and carbon storage are standing dead trees (snags) 

and down wood. These components are key to any comprehensive inventory of forest carbon pools. Oregon has 102 

million Mg of carbon in standing dead trees (table 4) and 

156 million Mg of carbon in down wood. The total amount 

of carbon mass and its distribution among the aboveground 

pools varies as stands age (fig. 18). Snag biomass is lowest 

on private ownerships, averaging 4 tons per ac, while there 

are 11 and 9 tons per ac in standing dead trees on NFS and 

0 2,000 4,000 6,000 8,000

Hemlock/Sitka spruce

Douglas-fir

Fir/spruce/mountain hemlock

Western larch

Ponderosa pine

Lodgepole pine

Other western softwoods

Western juniper

Alder/maple

Tanoak/laurel

Elm/ash/cottonwood

Other hardwoods

Western oak

Aspen/birch

Woodland hardwoods

Net volume (cubic feet per acre)

Figure 15—Average net live tree volume per acre on forest land by forest type group, Oregon, 2006–2015.

2 Metric units are used for carbon mass to remain consistent with 

accepted accounting practices. 
15

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Table 3—Aboveground carbon massa of live treesb on forest land, by ownership and land status, Oregon 2006–2015

Land status

Ownership

Unreserved forests Reserved forests

Timberland Other forest Total Productive Other forest Total All forest land

Total SE Total SE Total SE Total SE Total SE Total SE Total SE

Thousand megagrams

USDA Forest Service:

National forest 421,561.6 4,693.8 5,837.5 602.0 427,399.1 4,648.7 106,006.5 4,442.2 3,696.2 989.2 109,702.6 4,337.7 537,101.7 5,616.4

National grasslands — — 21.5 9.8 21.5 9.8 — — — — — — 21.5 9.8

Total 421,561.6 4,693.8 5,858.9 602.1 427,420.6 4,648.7 106,006.5 4,442.2 3,696.2 989.2 109,702.6 4,337.7 537,123.2 5,616.4

Other federal government:

Bureau of Land Management 133,714.7 4,632.5 5,109.8 636.9 138,824.6 4,614.4 4,639.5 1,469.8 239.1 134.8 4,878.6 1,475.6 143,703.2 4,521.2

National Park Service — — — — — — 6,671.2 1,435.8 747.4 615.4 7,418.6 1,556.9 7,418.6 1,556.9

U.S. Fish and Wildlife Service — — — — — — 249.1 183.9 21.3 25.4 270.4 185.7 270.4 185.7

Other federal 112.5 115.1 — — 112.5 115.1 315.2 241.4 — — 315.2 241.4 427.8 267.4

Total 133,827.3 4,634.0 5,109.8 636.9 138,937.1 4,615.9 11,875.1 2,029.7 1,007.8 630.5 12,882.9 2,115.8 151,820.0 4,390.7

State and local government:

Local 3,477.9 989.5 153.9 77.8 3,631.9 993.6 1,022.6 705.1 — — 1,022.6 705.1 4,654.5 1,215.3

State 38,491.4 2,391.5 457.3 242.7 38,948.7 2,401.5 2,774.2 1,326.9 268.0 312.3 3,042.2 1,357.0 41,990.9 2,509.3

Total 41,969.4 2,495.5 611.2 254.8 42,580.6 2,506.6 3,796.8 1,500.3 268.0 312.3 4,064.7 1,526.9 46,645.3 2,610.4

Corporate private 150,701.3 5,148.1 2,506.6 854.4 153,207.8 5,204.4 — — — — — — 153,207.8 5,204.4Noncorporate private:

Nongovernmental conservation or 

natural resource organizations

5,584.1 1,353.5 — — 5,584.1 1,353.5 — — — — — — 5,584.1 1,353.5

Unincorporated partnerships, 

associations, clubs

123.0 125.4 3.9 3.1 126.9 125.5 — — — — — — 126.9 125.5

Native American 10,452.1 1,778.4 464.5 225.1 10,916.7 1,790.0 — — — — — — 10,916.7 1,790.0

Individual 63,851.6 3,665.3 6,275.3 698.1 70,126.9 3,704.3 — — — — — — 70,126.9 3,704.3

Total 80,010.8 4,143.8 6,743.8 731.1 86,754.6 4,175.6 — — — — — — 86,754.6 4,175.6

All private 230,712.0 5,400.5 9,250.4 1,119.4 239,962.4 5,424.9 — — — — — — 239,962.4 5,424.9

All owners 828,070.3 8,627.0 20,830.4 1,443.6 848,900.7 8,604.7 121,678.4 5,109.1 4,971.9 1,213.9 126,650.2 5,061.9 975,550.9 9,033.8

Note: Totals may be off because of rounding; data subject to sampling error; SE = standard error; — = less than 50 megagrams was estimated.a Total aboveground carbon mass of the tree from ground to tip; includes stem wood, bark, and branches; calculated by applying a factor of 0.5 to aboveground biomass estimated from regional biomass equations, and converting to metric units. Convert megagrams of carbon to tons of biomass by multiplying by 2.204586. The result will be approximate because of rounding.b Includes all live trees ≥= 1 inches in diameter at breast height, consisting of growing stock, rough cull, and rotten cull tree classes.
16

GENERAL TECHNICAL REPORT PNW-GTR-971

Figure 16—Large trees with diameters greater than 25 inches such as this Douglas-fir in Linn County store 36 percent of the 

aboveground carbon in Oregon's forests. 

B. Borden
17

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Aboveground 

tree carbon

megagrams/hectare

0

0.1–40

40.1–80

80.1–20

120.1–160

>160

Counties

0 25 50

.

Miles

LAKE

HARNEY

MALHEUR

LANE

KLAMATH

GRANT

DOUGLAS

LINN

BAKER

CROOK

UMATILLA

WASCO

WALLOWA

UNION

JACKSON

COOS

DESCHUTES

CURRY

MORROW

WHEELER

CLACKAMAS

JEFFERSON

GILLIAM

MARION

JOSEPHINE

POLK

LINCOLN

CLATSOP

YAMHILL

BENTON

COLUMBIA

TILLAMOOK

WASHINGTON HOOD RIVER SHERMAN

MULTNOMAH

Figure 17—Average aboveground live tree carbon (tons per acre) by county, Oregon, 2006–2015 (Oregon boundary polygons: Oregon 

Bureau of Land Management, Oregon/Washington State Office).

0

50

100

150

200

250

1–20

21–40

41–6061–80

81–100

101–120

121–140141–160

161–180

181–200

201+

Carbon mass (megagrams per hectare)

Live trees Dead trees Down wood

Stand age class (years)

Figure 18—Average aboveground carbon mass per hectare on forest land, by stand age class, Oregon, 2006–2015.

J. Chase
18Table 4—Aboveground carbon massa of dead treesb on forest land, by ownership and land status, Oregon 2006–2015

Land status

Ownership

Unreserved forests Reserved forests

Timberland Other forest Total Productive Other forest Total All forest land

Total SE Total SE Total SE Total SE Total SE Total SE Total SE

Thousand megagrams

USDA Forest Service:

National forest 51,433.9 1,188.7 1,249.0 182.0 52,682.9 1,192.9 20,972.8 1,201.0 1,084.1 289.1 22,056.9 1,180.6 74,739.8 1,614.4

National grasslands — — — — — — — — — — — — — —

Total 51,433.9 1,188.7 1,249.0 182.0 52,682.9 1,192.9 20,972.8 1,201.0 1,084.1 289.1 22,056.9 1,180.6 74,739.8 1,614.4

Other federal government:

Bureau of Land Management 9,737.3 758.9 487.3 115.0 10,224.6 765.7 446.3 231.1 16.8 11.2 463.1 231.3 10,687.7 783.2

National Park Service — — — — — — 1,049.9 265.2 124.5 94.8 1,174.5 279.9 1,174.5 279.9

U.S. Fish and Wildlife Service — — — — — — 0.6 0.5 — — 0.6 0.5 0.6 0.5Other federal 7.0 7.2 — — 7.0 7.2 37.8 36.3 — — 37.8 36.3 44.8 37.0

Total 9,744.3 758.9 487.3 115.0 10,231.6 765.8 1,534.7 348.2 141.4 95.4 1,676.0 359.2 11,907.6 797.7

State and local government:

Local 282.7 102.3 — — 282.7 102.3 28.5 21.3 — — 28.5 21.3 311.1 104.4

State 3,049.3 377.2 25.4 21.2 3,074.7 377.8 225.4 125.0 2.2 3.1 227.6 125.0 3,302.3 386.3

Total 3,331.9 386.5 25.4 21.2 3,357.4 387.0 253.9 126.8 2.2 3.1 256.1 126.8 3,613.4 394.1

Corporate private 7,341.1 495.3 123.6 47.6 7,464.8 497.1 — — — — — — 7,464.8 497.1Noncorporate private:

Nongovernmental conservation or 

natural resource organizations

429.1 120.6 — — 429.1 120.6 — — — — — — 429.1 120.6

Unincorporated partnerships, 

associations, clubs

— — — — — — — — — — — — — —

Native American 1,380.6 339.0 184.5 89.7 1,565.1 350.0 — — — — — — 1,565.1 350.0

Individual 2,457.0 216.2 242.3 58.0 2,699.3 223.2 — — — — — — 2,699.3 223.2

Total 4,266.7 412.8 426.8 106.1 4,693.5 424.5 — — — — — — 4,693.5 424.5

All private 11,607.8 613.2 550.5 116.3 12,158.3 620.8 — — — — — — 12,158.3 620.8

All owners 76,118.0 1,578.5 2,312.2 245.6 78,430.1 1,588.0 22,761.3 1,256.8 1,227.7 304.5 23,989.0 1,240.5 102,419.1 1,938.5

Note: Totals may be off because of rounding; data subject to sampling error; SE = standard error; — = less than 50 megagrams was estimated.a Total aboveground carbon mass of the tree from ground to tip; includes stem wood, bark, and branches; calculated by applying a factor of 0.5 to aboveground biomass estimated from regional biomass equations, and converting to metric units. Convert megagrams of carbon to tons of biomass by multiplying by 2.204586. The result will be approximate because of rounding.b Includes all dead trees ≥= 5 inches in diameter at breast height; smaller dead trees were not measured in this inventory.
19

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

other federal lands, respectively. Biomass of down wood 

can be highly variable, but on average it is highest on state 

and local government lands (17 tons per acre) and lowest on 

private noncorporate ownerships (6 tons per acre).

The FIA also calculates carbon storage using the component ratio method (CRM) (Heath et al. 2009, O’Connell et 

al. 2017), which estimates belowground carbon and divides 

the aboveground tree carbon into distinct components. Live 

trees and saplings make up more than 70 percent of the 

total woody carbon; within this component, 82 percent is in 

boles, 14 percent is in tops and branches, and 4 percent is in 

stumps (fig. 19).

Forest Productivity

Timber Resources and Forest Productivity

Forest products are an important element of Oregon’s 

economy, especially in rural areas. In 2015, 3.8 billion board 

feet (BBF) Scribner were harvested from Oregon forests, 

with the vast majority (76 percent) coming from private 

and American Indian tribal lands (ODF 2016). Harvest 

totals reached a historic low in 2009 during the height of 

the economic recession, but since 2011 have rebounded to 

levels similar to those seen during the 1990s. Total sales of 

primary wood products were $7.1 billion in 2013 (Simmons 

et al. 2016). Oregon has long been the top state for softwood 

lumber, producing 5.2 BBF, 17 percent of the United States 

total, in 2015 (OFRI 2017). Although employment in the 

forestry sector has decreased significantly since 1990, wood 

products manufacturing still employed 22,500 Oregonians 

in 2015 and is expected to continue a slow post-recession 

growth (Rooney 2016). Total forestry sector employment in 

Oregon is around 61,000 (OFRI 2017).

Growing-stock or sawtimber volumes on timberland 

are one measure of the current stock of standing timber for 

a region, and trends over time have been used to ensure 

sustained yield. However, because management objectives 

differ widely among landowners and timber harvests are 

driven by market factors in addition to supply, timberland 

volume alone is not a direct measure of timber availability or 

future harvest levels. Growing-stock volume on timberland is 

currently 90.9 billion ft3. This estimate is difficult to compare 

to early periodic inventories owing to different definitions of 

timberland and commercial timber included at each measurement, but in general, growing-stock volume decreased 

Woody Carbon Components

Live trees 

and saplings

71.5%

Live tree 

coarse roots

16.0%

Down dead wood 

5.8%

Standing dead trees 

6.7%

Boles 57.6%

Tops and branches 

9.8%

Stumps 2.5%

Saplings 1.6%

Figure 19—Distribution of woody tree carbon components on forest land, Oregon, 2006–2015. Live tree carbon is subdivided into 

saplings (at least 1 but less than 5 inches diameter at breast height [d.b.h.]) and trees (at least 5 inches d.b.h.).
20

GENERAL TECHNICAL REPORT PNW-GTR-971

during the era of intensive timber harvesting between the 

first inventory in the 1930s and the 1980s and has since been 

on a steady increase as harvest rates have slowed (fig. 20). 

Oregon’s timberlands currently hold 80.6 billion ft3

or 394.1 BBF Scribner of live sawtimber trees. Sawtimber 

trees include only the sound portion of commercial species 

meeting minimum sawlog size. The five highest volume 

species groups include Douglas-fir (58 percent of sawtimber 

volume), ponderosa and Jeffery pines (11 percent), true firs 

(10 percent), western hemlock (8 percent), and red alder (2 

percent) (fig. 21). Over three-fourths of Oregon sawtimber 

volume is west of the Cascade Crest. Counties with the highest sawtimber volume on a per-acre basis are concentrated 

in northwest Oregon, ranging between 25,000 and 30,000 

board feet Scribner per acre. The average sawtimber tree 

volume per acre of timberland is 16,653 board feet Scribner 

per acre statewide. However, this varies significantly among 

owner groups, with an average of 9,252 board feet Scribner 

per acre on private lands and more than 30,000 board feet 

Scribner per acre on non-NFS federal lands (fig. 22). 

Another indicator of a forest stand’s potential productivity is mean annual increment at culmination, referred 

to by the FIA as the site productivity class (Hanson et al. 

2003). In Oregon, 41 percent of forest land area is classified 

as low productivity (capable of producing 20 to 84 ft3 ac-1

yr-1), 35 percent is medium productivity (85 to 1654 ft3 ac-1

yr-1), 12 percent is high productivity (at least 165 ft3 ac-1 yr-1), 

and the remaining 12 percent is classified as nonproductive 

other forest land incapable of producing at least 20 ft3 ac-1

yr-1. On average, western Oregon encompasses medium 

productivity sites, whereas eastern Oregon has lower productivity sites. Lane and Douglas Counties contain the most 

forested area classified as high productivity, with 675,105 

and 491,843 ac, respectively (fig. 23). The majority of highly 

productive stands falls outside of reserved areas, and most 

of the highly productive sites occur west of the Cascade 

crest (fig. 24). Hemlock/Sitka spruce forest types tend to 

grow on the most productive sites, followed by Douglas-fir, 

while dry-site forest types such as ponderosa and lodgepole 

pines thrive on low-productivity sites (fig. 25).

0

50

100

150

200

250

300

350

400

450

0

10

20

30

40

50

60

70

80

90

100

1940 1950 1960 1970 1980 1990 2000 2010 2020

Growing-stock (cubic feet)

Sawtimber (Scribner board feet)

Growing-stock volume (billion cubic feet)

Year

Sawtimber volume (billion board feet, Scribner)

Figure 20—Growing-stock (billion cubic feet) and sawtimber (billion board feet, Scribner) volumes on unreserved timberland by 

inventory year in Oregon, 1942–2015. Note: the 2000–2015 estimates from are based on the annual inventory design and protocols, while 

prior estimates were based on periodic inventories, which used different designs and methods (Bassett and Choate 1974, Campbell et al. 

2004, Farrenkopf 1982, Gedney 1982, Metcalf 1965, Moravets et al. 1942). Not all inventory years reported each estimate (growing-stock 

or Scribner sawtimber). Differences shown here represent a combination of real change and protocol differences over time such as use of 

stockability factors during periodic inventories and updated volume equations.
21

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

0 50,000 100,000 150,000 200,000 250,000

Douglas-fir

Ponderosa and Jeffrey pines

True fir

Western hemlock

Red alder

Sawtimber volume on timberland (net board feet, Scribner)

Figure 21—Scribner board-foot volume found on timberland by species group (five highest-volume species groups), Oregon, 2006–2015.

0 5,000 10,000 15,000 20,000 25,000 30,000 35,000

All owners

USDA Forest Service

Other federal

State and local government

Private corporate

Private noncorporate

Average sawtimber volume per acre on timberland (net board feet, Scribner)

Figure 22—Average sawtimber tree volume per acre of timberland by ownership group (net board feet, Scribner), Oregon, 2006–2015.
22

GENERAL TECHNICAL REPORT PNW-GTR-971

Figure 23—Northwest Oregon boasts the highest annual growth rates, such as this Douglas-fir stand in Clatsop County, where average 

annual gross growth is 197 ft3

 ac-1 yr-1. 

M. Palmer

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0 25 50

Miles

.

Site productivity

Land cover

Reserved nonforest

Reserved forest

Nonforest

Forest

Water

!

!

225+ ft3/acre 

165–224 ft3

/acre 

Figure 24—Forest Inventory and Analysis plots on highly productive sites, Oregon, 2006–2015. Seventy-six plots were classified as 

capable of at least 225 ft3

/ac and 730 plots capable of 165 to 224 ft3/ac annual growth (forest/nonforest geographic information system 

layer: Blackard et al. 2008; Oregon boundary polygons: Oregon BLM). 

J. Chase
23

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Average Annual Growth, Removals, and Mortality

One unique aspect of the FIA sampling design is the broad 

network of field plots across all forest land ownerships. 

Because the same plots and trees are measured each 10-year 

cycle, the FIA is able to provide a detailed accounting 

of forest growth, removals, and mortality (GRM). GRM 

estimates represent average annual rates over the entire 

measurement cycle, and the GRM estimates in this report 

include 4,594 forested plots initially installed in 2001–2005 

and remeasured in 2011–2015, 50 percent of the Oregon FIA 

grid. As the second cycle is completed through 2020, the 

estimates reported here are not expected to change much, 

but their precision will improve.

Annual gross growth in Oregon averaged 95 ft3 ac-1

yr-1 statewide and was threefold higher in western Oregon 

than eastern Oregon (fig. 26). Net change (defined as gross 

growth minus mortality and harvest removals) was positive 

for each ownership group, meaning that Oregon’s forests 

are adding tree volume each year (table 5). Statewide, net 

change in volume was 35 ft3

 ac-1 yr-1 or a total addition 

to net volume of 1.0 billion ft3

 yr-1 (fig. 27, table 6). On 

both sides of the state, mortality rates are highest on NFS 

lands (34 ft3

 ac-1 yr-1) and harvest removals are highest on 

corporate private land (105 ft3 ac-1 yr-1), which compares to 

statewide mortality and removal averages of 24 and 37 ft3

ac-1 yr-1, respectively.

Mortality rates (ratios of average annual mortality to 

original standing net volume) give an estimate of the tree 

volume lost each year to a variety of natural agents such as 

fire, insects, disease, weather, or competition. The average 

annual mortality rate in Oregon, in terms of tree volume, is 

0.7 percent. Lodgepole pine and red alder have the highest 

mortality rates at 2.4 and 1.7 percent, respectively (fig. 28). 

Lodgepole pine is frequently attacked by mountain pine beetle (Dendroctonus ponderosae) and other insects; more than 

60 percent of lodgepole pine tree mortality was attributed 

to insects. The most frequent causes of death noted for red 

alder were windthrow and suppression/competition. The 

mortality rate for a given species can be an indicator of forest health, but is also highly dependent of each species’ life 

history or average stand age. Net growth is a better indicator 

of whether growth is offsetting mortality losses.

0

25

50

75

100

Hemlock/

Sitka spruce

Douglas-fir Fir/spruce/

mountain hemlock

Ponderosa

pine

Lodgepole

pine

ft3

 ac-1 yr-1

225+

165–224

120–164

85–119

50–84

20–49

Site class distribution

(percentage of timberland acreage)

Figure 25—Timberland site class distribution for major forest type groups, Oregon, 2006–2015. 
24

GENERAL TECHNICAL REPORT PNW-GTR-971

A Western Oregon

-200

-150

-100

-50

0

50

100

150

200

National forest Other federal State and local

government

Corporate

private

Noncorporate

private

Annual volume change (ft3 acre-1 year-1)

Growth

Removals

Mortality

Net change

-200

-150

-100

-50

0

50

100

150

200

National forest Other federal State and local

government

Corporate

private

Noncorporate

private

B Eastern Oregon Annual volume change (ft3 acre-1 year-1)

Growth

Removals

Mortality

Net change

Figure 26—Average annual change in volume (cubic feet per acre per year) of growth, mortality, and removals between 2001–2005 and 

2011–2015 by ownership group in (A) western Oregon and (B) eastern Oregon.
25

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Net growth, in forestry terms, is defined as the gross 

growth minus mortality losses. All species groups in Oregon exhibit positive net growth. Sugar pine and lodgepole 

pine have negligible annual net growth rates of 0.1 and 0.2 

percent, respectively, while the five highest volume species 

groups in the state are all adding volume at rates between 

1.5 and 2.6 percent annually. Sitka spruce represents less 

than 1 percent of total tree volume yet has the highest 

annual net growth rate, more than 2.8 percent, compared to 

an average net growth rate for all species groups in Oregon 

of 2.2 percent (fig. 29). 

The vast majority (80 percent or 889 million ft3

 annually) of harvest removals in Oregon occur on private forest 

land. National Forest System, state, and local ownerships 

each make up an additional 9 percent of annual harvest 

removals. Sixty-six percent of tree volume removed from 

forest land is Douglas-fir, which is the state’s most valuable 

timber species, while western hemlock comes in second 

place with just 11 percent of the removed volume (fig. 30). 

The net growth-to-removals ratio is an indicator of sustained yield, where >1 ratios indicate that more tree volume 

is growing than is being harvested but <1 ratios show that 

the available resource is being depleted. The desirable net 

growth-to-removals ratio depends on the land management 

objective; in areas being managed for timber production a 

~1 ratio may be a management goal. In Oregon, the average 

net growth-to-removals ratio is 1.93, meaning that each 

year Oregon’s forest lands add almost twice as much tree 

volume as is removed, after accounting for mortality losses. 

Two tree species are declining in terms of volume: sugar 

pine (0.15) and lodgepole pine (0.29). Both of these species 

have very minimal harvest removals but high mortality 

rates. Both state and federal agencies support programs to 

aid in the removal of western juniper, which has expanded 

well beyond its historical range and can degrade rangelands 

normally dominated by big sagebrush. Despite removal 

activities on both public and private lands, western juniper 

has a net growth-to-removals ratio of 1.49. 

Table 5—Average annual volume (cubic feet per acre) growth, removals, and mortality on forest land by 

ownership group, Oregon 2001–2005 and 2011–2015

Ownership group

Private

National

forest Other federal

State 

and local 

government Corporate Noncorporate

Total 

private All owners

Mean SE Mean SE Mean SE Mean SE Mean SE Mean SE Mean SE

Cubic feet per acre per year

All Oregon:

Growth 78.3 1.3 106.9 5.2 156.4 10.2 120.5 4.6 82.5 4.9 107.6 3.4 95.4 1.5

Mortality 34.1 1.7 16.9 2.2 28.1 6.4 12.1 1.6 11.0 1.8 11.7 1.2 23.7 1.0

Removals 6.9 0.8 6.3 2.2 87.6 22.1 104.6 10.5 41.4 8.4 83.2 7.4 37.3 2.8

Net change 37.2 2.3 83.7 5.7 40.8 25.7 3.8 12.2 30.1 9.5 12.7 8.7 34.5 3.5

Eastern Oregon:

Growth 48.7 1.0 18.1 3.3 49.8 11.2 40.1 2.6 36.8 3.2 38.5 2.0 42.6 0.9

Mortality 26.1 2.0 7.9 2.7 13.2 7.0 3.6 0.9 11.0 3.1 7.1 1.6 18.8 1.3

Removals 5.3 0.6 4.2 1.6 24.3 14.6 29.1 5.6 16.2 6.3 22.9 4.2 10.3 1.2

Net change 17.3 2.2 6.0 3.7 12.2 14.9 7.4 5.9 9.6 7.5 8.4 4.7 13.6 1.9

Western Oregon:

Growth 124.3 2.8 167.9 7.5 183.4 10.6 153.0 6.0 130.4 8.1 147.1 4.8 144.1 2.7

Mortality 46.6 3.2 23.1 3.2 31.9 7.8 15.6 2.2 11.1 1.8 14.4 1.7 28.2 1.5

Removals 9.5 1.8 7.7 3.5 103.6 27.5 135.1 14.5 67.8 15.6 117.6 11.4 62.1 5.3

Net change 68.2 4.8 137.1 8.5 48.0 31.9 2.3 17.0 51.5 17.6 15.1 13.4 53.8 6.5
26

GENERAL TECHNICAL REPORT PNW-GTR-971

A Western Oregon

-800

-600

-400

-200

0

200

400

600

800

National forest Other federal State and local

government

Corporate

private

Noncorporate

private

Annual volume change (ft3 acre-1 year-1)

Growth

Removals

Mortality

Net change

-500

-400

-300

-100

-200

0

100

200

400

300

500

National forest Other federal State and local

government

Corporate

private

Noncorporate

private

B Eastern Oregon Annual volume change (ft3 acre-1 year-1)

Growth

Removals

Mortality

Net change

Figure 27—Average annual change in volume (cubic feet per year) of growth, mortality, and removals between 2001–2005 and 2011–2015 

by ownership group in (A) western Oregon and (B) eastern Oregon.
27

Table 6—Average annual volume (cubic feet) growth, removals, and mortality on forest land by ownership group, Oregon 2001–2005 and 2011–2015

Ownership group

Private

National forest Other federal

State and local 

government Corporate Noncorporate Total private All owners

Mean SE Mean SE Mean SE Mean SE Mean SE Mean SE Mean SE

Thousand cubic feet per year

All Oregon:

Growth 1,106,703 17,849 407,823 19,002 175,971 12,394 851,459 38,338 298,019 22,633 1,149,478 37,779 2,839,975 46,135

Mortality 482,458 24,519 64,450 8,343 31,615 7,329 85,658 11,620 39,815 6,833 125,473 13,173 703,996 29,927

Removals 97,817 11,169 23,954 8,225 98,504 24,732 739,014 75,133 149,578 31,060 888,592 78,911 1,108,866 83,308

Net change 526,429 32,266 319,419 21,424 45,852 29,057 26,787 86,457 108,626 34,659 135,413 93,096 1,027,113 104,728

Eastern Oregon:

Growth 419,081 9,317 28,031 5,592 11,330 3,313 81,522 7,596 68,063 7,824 149,585 10,247 608,027 15,180

Mortality 224,744 17,219 12,249 4,357 3,005 1,709 7,359 1,889 20,315 5,978 27,674 6,205 267,672 18,892

Removals 45,229 5,229 6,473 2,544 5,540 3,564 59,182 12,093 29,947 11,925 89,129 16,810 146,370 18,130

Net change 149,108 18,705 9,310 5,836 2,784 3,362 14,982 12,096 17,800 13,917 32,782 18,370 193,984 27,078

Western Oregon:

Growth 687,623 16,216 379,791 20,013 164,641 12,592 769,937 38,743 229,957 21,980 999,893 39,479 2,231,948 47,727

Mortality 257,714 17,960 52,201 7,409 28,610 7,166 78,299 11,495 19,500 3,404 97,799 11,816 436,324 23,803

Removals 52,588 9,883 17,481 7,826 92,963 24,474 679,832 74,796 119,631 28,753 799,463 78,134 962,496 82,325

Net change 377,320 26,407 310,109 21,389 43,068 28,947 11,806 85,694 90,826 31,717 102,631 91,324 833,129 101,461
28

GENERAL TECHNICAL REPORT PNW-GTR-971

0.0 0.5 1.0 1.5 2.0 2.5 3.0

Cottonwood and aspen

Western juniper

Sugar pine

Western larch

Oak

Engelmann and other spruces

Incense-cedar

Sitka spruce

Western redcedar

Lodgepole pine

Red alder

Other western softwoods

Other western hardwoods

Western hemlock

Ponderosa and Jeffrey pines

True fir

Douglas-fir

Average annual mortality rate (percentage)

Species groups

Figure 28—Average annual mortality rates (percent) for species groups on forest land, Oregon, 2015. Species groups are shown ordered 

by total net standing volume; average annual mortality rate for all species is 0.7 percent.

0.0 1.0 2.0 3.0 4.0 5.0 6.0

Cottonwood and aspen

Western juniper

Sugar pine

Western larch

Oak

Engelmann and other spruces

Incense-cedar

Sitka spruce

Western redcedar

Lodgepole pine

Red alder

Other western softwoods

Other western hardwoods

Western hemlock

Ponderosa and Jeffrey pines

True fir

Douglas-fir

Average annual growth rate (percentage)

Species groups

Figure 29—Average annual net growth rates (percent) by species group for all live trees on forest land, Oregon, 2015. Species groups are 

shown ordered by total net standing volume.
29

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

0 100 200 300 400 500 600 700 800

Ponderosa and Jeffrey pines

True fir

All hardwoods

Western hemlock

Douglas-fir

Average annual removals (million cubic feet per year)

Species groups

Figure 30—Average annual removals (tree harvest and forest to nonforest diversion) for selected species groups on forest land, Oregon, 2015. 

Research Application: Evaluating the 

Feasibility of Accelerating Forest 

Restoration in the Blue Mountains Region3

Accelerating the pace and scale of forest restoration 

has been of keen interest to state and federal agencies 

in the Blue Mountains region of eastern Oregon (FAC 

2012, USDA FS 2013), an area encompassing 3 million 

ac of unreserved forest land (fig. 31). In a partnership 

with the Oregon Department of Forestry, we modelled the effectiveness of restoration treatments over 

a 40-year period, estimating potential net revenues 

(revenue from sales of wood, less operations and 

transportation costs). We applied the BioSum modeling 

framework (Fried et al. 2017), which relies on Forest 

Inventory and Analysis (FIA) plot data as a representative sample of current forest fire hazard levels, then 

simulated 34 different silvicultural treatments with the 

Forest Vegetation Simulator. Our goal was to understand how the choice of restoration treatment affects 

economic costs across the landscape, and consequently, 

the proportion of the landscape for which forest restoration can be accomplished. 

To evaluate current fire hazard and to assess the 

effectiveness of silvicultural sequences in reducing fire 

hazard over time, we computed a hazard score (0–4) for 

each stand as it currently exists and at 10-year intervals 

over 40-year trajectories associated with each of up to 34 

simulated silvicultural treatments. Methods are defined 

in Loreno et al. (2015) and Jain et al. (2012). Treatments 

that reduce a stand’s mean hazard score compared to no 

treatment are deemed effective, and the treatment that 

reduces hazard score the most is assumed “best” for that 

stand. Treatment and haul costs and revenues from wood 

production determine the economic feasibility of each 

silvicultural sequence.

When best silvicultural sequences are implemented, hazard is initially reduced to a considerable 

extent (Loreno et al. 2015), though hazard score is 

reduced to zero on only about half of the area (fig. 32). 

As ladder fuels and stand density rebound, hazard 

reduction benefits gradually fade, so the immediate 

effect is perhaps not the best policy driver. For that 

reason and because stands are most ready to receive 

treatment at different times, depending on their stage 

of development, we chose to base effectiveness on the 

40-year mean hazard score.

3

Authors: Jeremy Fried and Sara Loreno.
30

GENERAL TECHNICAL REPORT PNW-GTR-971

Elgin

Adams

Joseph

Haines

Wallowa

Heppner

John Day

Umatilla

Monument

Dayville

Lewiston

Boardman

Clarkston

Pendleton

La Grande

Baker City

Enterprise Pilot Rock

White Bird

New Meadows

Grangeville

Prairie City

Elgin

Joseph

Monument

La Grande

Enterprise

Prairie City Mount Vernon

Bonners Ferry

Oregon Idaho

Washington Montana

OREGON

WASH INGTON

IDAHO

Study area

Unreserved, forested plots

Doug-fir

Ponderosa pine

Lodgepole pine

Grand fir

Other

Processing facilities

Bioenergy

Sawmill

0 10 205

.

Miles

Figure 31—Location of study plots and processing facilities within the Blue Mountain region.

S. Loreno
31

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Only 15 percent of the Blue Mountains forest area 

is hazard free, and the percentage of forest at hazard 

scores 1–4 is currently 28, 26, 18, and 13 percent, 

respectively. If cost were not a consideration, at least 

one of the silvicultural sequences we modeled would 

be effective on 54 percent of private and 67 percent of 

NFS area with current hazard scores between 1 and 4. 

If revenues must cover treatment costs, the effective 

areas would decrease to 43 and 55 percent, respectively. 

Although this analysis does not account for planning 

and administrative costs, it is clear that most forests 

in the region can realize at least some improvement 

in fire resistance if a broad spectrum of treatments 

are available from which to choose, without requiring 

significant subsidy. Constraining treatment choices, 

however, reduces the share of the forest that can benefit. 

For example, if a diameter cap of 30 inches is replaced 

with a 21-inch limit on the maximum tree size that can 

be harvested, the effectively treatable area drops to 36 

percent overall (on both private and NFS ownerships), 

and if proportional thinning (across all diameter classes) 

is removed as an option, leaving only thin-from-below 

treatments as alternatives to select from, it drops to 

32 percent. While thin-from-below treatments are, on 

average, slightly more effective than proportional thins 

(average improvement in a 40-year mean hazard score of 

Hazard

0

10

0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4

20

30

40

50

Acres (percentage)

Pre-treatment 1 year post-treatment 20 year post-treatment 30 year post-treatment

A B C D

Figure 32—Distribution of area by hazard score for stands in which a treatment sequence could begin today with immediate 

effect. (A) Before the first treatment in the sequence, (B) 1 year later, (C) 20 years later, and (D) 30 years later. Note that hazard 

distribution reflects the retreatment of some of these stands at year 20 or 30, as specified by the most effective silvicultural 

sequence for those stands.
32

GENERAL TECHNICAL REPORT PNW-GTR-971

0.675 versus 0.579 points), net revenue is much greater 

with a proportional thin owing to the harvest of more 

merchantable wood (fig. 33). Net revenue is also substantially greater, on average, with larger upper limits 

on the size of trees that may be removed. Either shifting 

from thin-from-below to a proportional thin or relaxing 

the diameter cap from 21 to 30 inches moves the average 

net revenue from a negative to a positive value of more 

than $700 per acre. The pace of restoration could be 

accelerated by moving forward now with the treatment 

of stands where net revenue is positive as little or no 

subsidy would be required. If net revenues from these 

acres can be retained and redirected to subsidize other 

priority acres where treatment costs exceed revenues, 

this could also present an opportunity to increase the 

scale of forest restoration.

A fully implemented fuel treatment program in 

the Blue Mountains region has the potential to produce 

substantial quantities of merchantable and energy wood 

as well as a net revenue (table 7) that could be important 

to the rural communities where this work would be 

conducted (table 5). Area treated annually increases as 

more acres attain treatment readiness and other acres 

treated in the first two decades become eligible for 

retreatment. Yield and net revenue likely decline over 

time owing to the availability of fewer high-value (e.g., 

larger) trees at the retreatment opportunity such that 

the self-pay requirement cannot be met, suggesting that 

subsidies may become more important in the future if 

hazard reduction is to be maintained on acres where this 

is a priority. 

Net revenue (dollars per acre)

0

500

1,000

1,500

C G

Prescription specification

Thinning style

Proportional thin Thin from below

Figure 33—Mean net revenue for thin-from-below and proportional thin versions of two prescriptions, one with an upper limit 

of 21 inches on the diameter of trees eligible for removal and 

one with a 30-inch limit; both prescriptions thin all trees greater 

than 5 inches diameter at breast height to a residual basal area 

of 75 ft2

/ ac using ground-based mechanical whole-tree harvest, 

rely on prescribed fire to reduce surface fuels, and are repeated 

in any decade (after skipping one decade) in which basal area 

exceeds 110 ft2

/ac. 

Table 7: Average annual estimates for the four decade planning horizon in the Blue Mountains region.

Time Period Area Treated Energy Wood Yield Merchantable Wood Yield Net Revenue

Acres - - - - - - - Million cubic feet - - - - - - - Dollars

Years 1-20 39,440 40,855 88,568 $81,965,000 

Years 21-40 50,434 35,460 64,980 $25,099,000 

Note: wood yield is classified as merchantable (delivered to facilities) or non-merchantable (delivered to bioenergy generators) based on species or 

size. Net revenue equals sales of wood minus treatment and transportation costs.
33

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

The BioSum framework used for this analysis is now 

available for anyone to use for analysis in five western 

states: California, Oregon, Washington, Idaho, and 

Montana. It facilitates prospective analysis of all kinds 

of scenarios involving alternative forest futures using 

the FIA plot data as a test bed. Software, documentation, articles describing its use, and sample data can be 

obtained at http://www.biosum.info.

Literature Cited

Federal Forest Advisory Committee [FFAC] 2012. 

National forest health restoration: an economic 

assessment of forest restoration on Oregon’s eastside 

national forests. Prepared for: Governor John 

Kitzhaber and Oregon’s Legislative Leaders. Portland, 

OR: Portland State University Northwest Economic 

Research Center. 94 p. https://www.pdx.edu/nerc/sites/

www.pdx.edu.nerc/files/Forest%20Restoration%20

Final%20Report_0.pdf. (24 May 2018).

Fried, J.S.; Potts, L.D.; Loreno, S.M.; Christensen, 

G.; Barbour, J.R. 2017. Inventory based landscapescale simulation of management effectiveness 

and economic feasibility with BioSum. Journal of 

Forestry. 115: 249–257.

Jain, T.J.; Battaglia, M.A.; Han, H.S.; Graham, R.T.; 

Keyes, C.R.; Fried, J.S.; Sandquist. J.E. 2012. A 

comprehensive guide to fuel management practices 

for dry mixed conifer forests in the northwestern 

United States. Gen. Tech. Rep. RMRS-GTR-292. Fort 

Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station. 331 p. 

https://www.fs.usda.gov/treesearch/pubs/42150. (24 

May 2018).

Loreno, S.; Fried, J.S.; Yost, A. 2015. Applying 

management modeling to assess the feasibility of 

accelerating landscape restoration on federal forests 

in eastern Oregon. In: Stanton, S.M.; Christensen, 

G.A., comps. Pushing boundaries: new directions 

in inventory techniques and applications: Forest 

Inventory and Analysis (FIA) symposium 2015.

Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station: 260–

265. https://www.fs.usda.gov/treesearch/pubs/50355. 

(24 May 2018).

U.S. Department of Agriculture, Forest Service 

[USDA FS]. 2013. Accelerated restoration. 

Portland, OR: Pacific Northwest Region. 

https://www.fs.usda.gov/Internet/FSE_

DOCUMENTS/stelprdb5423599.pdfhttps://

www.fs.usda.gov/detail/r6/landmanagement/

resourcemanagement/?cid=stelprdb5423597. (19 

December 2017).
34

GENERAL TECHNICAL REPORT PNW-GTR-971

Wildlife Habitat 

Standing dead trees (snags) and down dead wood provide 

key habitat components for forest wildlife in addition to 

their roles in carbon storage and nutrient cycling (fig. 34). 

Dead wood forest components are used by a variety of 

bird, mammal, and amphibian species for nesting, roosting, 

foraging, hibernating, and thermal cover (Rose et al. 2001). 

While local patterns and locations of dead wood structures 

are important in identifying species-specific habitat, 

broad-scale estimates of dead wood provided by the FIA 

are useful in comparisons within or across forest types or 

disturbance histories. 

There are 571 million standing dead trees in Oregon, 37 

percent occurring on Douglas-fir forest types. This amounts 

to 19 snags per acre on average, with >25 snags per acre 

in stands older than 100 years. The amount of snags and 

down wood varies considerably by ownership, with the vast 

majority of snag biomass (165 million tons) and highest 

density of total snags (27 per acre) occurring on NFS lands 

and the lowest snag densities (11 per acre) on private lands 

(figs. 35 and 36). 

The amount and distribution of down wood is highly 

variable among sites, often dictated by recent management 

and natural disturbances; however, broad-scale trends are 

evident. Expressed as volume, Oregon forests average 1,580 

ft3

 of down wood per acre, 11 percent less than Donnegan 

et al.’s (2008) estimate for 2001–2005 of 1,779 ft3/ac. There 

are on average 11.6 tons of down wood per acre, with almost 

twice as much on the moist west side of the state (fig. 37). 

Down-wood density is highly variable among forest type 

groups, ranging from more than 26 tons per acre on fir/

spruce/mountain hemlock sites to just 1.4 tons per acre on 

western juniper forest types.

Figure 34—Large coarse woody debris pieces serve important roles in wildlife habitat and nutrient cycling on forest lands.

M. Palmer
35

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Snags (trees per acre)

or down wood biomass (tons per acre)

0

5

10

15

20

25

30

Forest Service Other federal State and local

government

Corporate private Noncorporate

private

Ownership group

Snags Down wood

Biomass (million tons)

0

25

50

75

100

125

150

175

200

Forest Service Other federal State and local

government

Corporate private Noncorporate

private

Ownership group

Snags Down wood

Figure 35—Total biomass (million tons) in standing dead trees (snags) and down wood by ownership group, Oregon, 2006–2015.

Figure 36—Average number of standing dead trees (snags) per acre and down wood biomass (tons) per acre by ownership group, Oregon, 

2006–2015.
36

GENERAL TECHNICAL REPORT PNW-GTR-971

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0 25 50

Miles

.

Down wood 

biomass tons/acre

Forest

Nonforest

Counties

0

.1–30

30.1–60

60.1–90

90.1–120

 >120

!

!

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!

Figure 37—Plot distribution of total down wood biomass (tons per acre), Oregon, 2006–2015 (forest/nonforest geographic information 

system layer: Blackard et al. 2008; Oregon boundary polygons: Oregon Bureau of Land Management). Map: J. Chase.

Research Application: Unpacking 

Vegetation Mapping Uncertainties4

The Forest Inventory and Analysis (FIA) program 

provides consistent and extensive sampling of forest 

characteristics and conditions across all U.S. forest 

lands, but at finer scales higher plot sampling density is 

desired to improve support for forest planning, monitoring, and decisionmaking. Increased computing power 

and availability of high-quality satellite imagery offers 

several opportunities for creating small-area estimates 

that leverage FIA data for mapping and estimation at 

finer scales than using FIA data alone. In the Pacific 

Northwest, gradient nearest neighbor (GNN) imputation 

has emerged as a powerful tool for informing forest 

monitoring and planning. Imputation involves the 

substitution of observations (FIA plot data) for missing 

data (unmeasured pixels), providing wall-to-wall maps 

of forest attributes. For entire forested landscapes and 

regions, the flexible and multivariate GNN approach 

imputes, or maps, data to a location from the FIA plot 

4 that best matches a pixel in terms of satellite imagery, Author: David M. Bell.

J. Chase
37

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

climate, and topography. However, the utility of the 

resulting maps must be tempered by an understanding 

of the inherent uncertainties, such as the precision, or 

variability, of predictions. 

In a collaboration between Pacific Northwest 

Research Station and Oregon State University scientists, 

we modified existing methods for generating pixel-level 

measures of imputation-map uncertainties for GNN and 

examined the geographic patterns of uncertainties in live 

tree structure, dead tree structure, and species composition across regional environmental gradients in the western Cascade Mountains of Oregon (Bell et al. 2015). We 

found that live tree structure, which is directly observed 

by satellite imagery, exhibited the greatest prediction 

precision, while dead tree structure and composition 

exhibited less prediction precision. Spatial variation in 

precision was substantial and regional patterns differed 

by forest attribute under consideration. These patterns 

implied that imputation uncertainty may be tied to 

regional biogeography and disturbance history: mapping 

certain vegetation types and seral stages involved greater 

uncertainty than others. For example, quadratic mean 

diameter, a measure of tree sizes, exhibited substantial 

uncertainty in postfire environments whereas live 

aboveground forest biomass exhibited relatively high 

precision in predictions within the fire, but low precision 

in neighboring undisturbed old-growth forest (fig. 38). 

Additionally, this research has identified methods to 

operationalize pixel-level precision mapping for GNN, 

allowing for future map distributions to include maps 

of variable uncertainties along with traditional accuracy 

assessment reporting.

Literature Cited

Bell, D.M.; Gregory, M.J.; Ohmann, J.L. 2015. 

Imputed forest structure uncertainty varies across 

elevational and longitudinal gradients in the western 

Cascade Mountains, Oregon, USA. Forest Ecology 

and Management. 358: 154–164.

(A) 2011 aerial photograph (B) QMD imputation variability (C) AGB imputation variability

low high

Figure 38—Representation of the impacts of the Scott Mountain Fire west of Sisters, Oregon, on prediction precision. (A) Postfire 

aerial photograph, (B) quadratic mean diameter (QMD) prediction precision, (C) aboveground live biomass (AGB) prediction 

precision. Figure reproduced with permission from Bell et al. (2015).
38

GENERAL TECHNICAL REPORT PNW-GTR-971

Understory Vegetation and Nontimber 

Forest Products

Understory vegetation composition in forest communities 

has long been used as an indicator of forest health, moisture regime, or site productivity, and to classify extant 

vegetation assemblages. Understory vegetation contributes 

to the carbon storage of the site, and the composition of 

understory plants and tree seedlings is important in determining wildlife habitat as well as future forest succession. 

The Pacific Northwest FIA unit collects information on the 

predominant understory species in each life form (shrubs, 

forbs, and graminoids) and structural classifications for each 

life form on each forested plot. 

Average understory vegetation cover across all forested 

lands in Oregon is about 40 percent but is highly variable 

depending on each stand’s species composition, age, and 

disturbance history. In general, riparian forest types such as 

alder/maple tend to have the densest understory cover, while 

dry site forest types such as lodgepole pine have more sparse 

understories. Young stands with recent disturbance tend to 

have the highest cover of forbs and graminoids, while shrub 

cover tends to be highest in stands 20 to 39 years old (fig. 39). 

Nonnative, invasive plants on forest lands can affect 

forest composition and health, ecosystem processes, and 

wildlife habitat (Rapp 2005). The nonnative species covering the most forest land area in Oregon include cheatgrass 

and Himalayan blackberry, each estimated to cover more 

than 150,000 ac of forest land (fig. 40). Several other annual 

grasses are common nonnatives on Oregon forest land.

Nontimber forest products (NTFPs) include plants, 

fungi, and animal products that are used for both commercial and individual use. In the Pacific Northwest, evergreen 

boughs, floral greens, and edible mushrooms are frequently 

collected, and these products have tremendous cultural 

significance in addition to economic value (Alexander et 

al. 2011). Several forest understory species in Oregon are 

frequently collected for NTFP uses. The most abundant 

shrubs, in terms of acres of forest land with cover of each 

NTFP species, are vine maple, salal, and Cascade barberry 

(also called dwarf Oregon grape) (fig. 41).

0

10

20

30

40

50

Shrubs Forbs Graminoids All understory plants

Understory vegetation type

Percentage cover

0–19 years 20–39 years

40–79 years 80–159 years

160+ years

Figure 39—Cover of understory vegetation life forms by forest age class on forest land, Oregon, 2006–2015.
39

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

cheatgrass

Himalayan blackberry

bristly dogstail grass

medusahead

North Africa grass

hairy cat's ear

Scotch broom

common velvetgrass

0 50,000 100,000 150,000 200,000 250,000

Forest land cover by nonnative species (acres)

Nonnative species common name

Figure 40—Nonnative invasive species with the highest acreage cover on forest land in Oregon, 2006–2015. Nonnative species estimated 

to cover at least 10,000 ac are shown.

0 200,000 400,000 600,000 800,000 1,000,000

vine maple

salal

Cascade barberry

salmonberry

California blackberry

common snowberry

snowbrush ceanothus

thinleaf huckleberry

California huckleberry

beaked hazelnut

grouse whortleberry

oceanspray

Himalayan blackberry

Nontimber forest product species common name

Forest land cover by nontimber forest product shrub species (acres)

Figure 41—Total shrub cover (acres) on forest land by selected species used in nontimber forest products. Shrub species with at least 

150,000 ac cover are shown. 
40

GENERAL TECHNICAL REPORT PNW-GTR-971

Forest Recreation

Oregon’s forest lands provide tremendous recreation value, 

and user demand at Oregon’s recreation sites continues to 

increase with the state’s growing population. Although private landowners recreate on their own lands and some corporate forests are open to the public, most forest recreation 

activities occur on the 64 percent of Oregon forest lands 

that are publicly owned. Forest recreation on federal lands 

takes a multitude of forms, and the values that individuals 

receive from recreation are difficult to quantify. White et 

al. (2016) examined the top recreation activities occurring 

on federal lands, noting that the top activities on NFS lands 

include viewing scenery/natural features, hiking/walking, 

relaxing/hanging out, and viewing wildlife. National 

Forest System visitor recreation fee revenues for the Pacific 

Northwest Region (covering Oregon and Washington) have 

steadily increased during the 10-year period of this report, 

reaching $8,937,597 in 2015 (compiled from Recreation 

Fee Program Accomplishment Highlights, https://www.

fs.usda.gov/detail/r6/passes-permits/recreation/?cid=fsbdev2_026999USDA FS 2015). A 2012 analysis estimated 

that recreation visits to federal lands nationwide contributed 

$51 billion to the U.S. economy and supported 880,000 

jobs (English et al. 2014). Rural communities surrounding 

these recreation destinations benefit from recreation-related 

spending. Recreation activities expected to increase most in 

the next 15 years include developed skiing, visiting interpretive sites, day hiking, birding, and equestrian activities 

(White et al. 2016) (fig. 42). Oregon’s 2.8 million ac of 

reserved forest lands provide many recreation opportunities, and recreation occurs on many of the 19.0 million ac of 

publicly owned forests. 

Figure 42—Drift Creek Falls Trail, Columbia Gorge National Scenic Area. Day hiking is the most frequent recreation usage type on 

national forest lands. 

USDA Forest Service Pacific Northwest Region
41

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Forest Health 

Damaging Agents

Although many factors affect the health of each tree, physical signs of stress or damage can often be attributed to a 

primary agent. Damage can occur from a number of factors 

including animals, insects and disease, mistletoe, weather, 

or physical defects. Most of the damages assessed by FIA 

are natural agents that play a role in forest succession. 

Detecting trends in tree damages at the stand level can aid in 

assessments of a forest’s future composition and resiliency.

FIA field crews assess each measured live tree for 

damaging agents. In the Pacific Northwest states, regional 

damage codes that included location and severity were 

implemented at the start of the annual inventory. This damage coding system was replaced by a nationally consistent 

protocol in 2013. Details for both protocols are included in 

O’Connell et al. 2017, and the two systems are compatible 

when summarizing to general categories. 

A little more than one-quarter of all live trees in 

Oregon (2.75 billion) are affected by damage or defect. 

These affected trees represent one-third of Oregon’s total 

live tree volume. The most common damage agent, affecting 15 percent of all live trees and making up 56 percent of 

all recorded damages, was physical injury and defects (fig. 

43). This category includes fire damage; human activities, 

including damage caused by harvest activity; and deformities such as broken tops, crooks, or open wounds. Trees 

affected by dwarf mistletoe made up 9 percent of total live 

tree basal area. 

Physical injury and defects affected between 11 and 

19 percent of live trees for each of the five most common 

conifer species in the state (Douglas-fir, lodgepole pine, 

Damaging agent group

Animal

Bark beetle

Cankers

Defoliators

Dwarf mistletoe

Foliage diseases

Stem decay

Other insects

Physical injury and defects

Root disease

Weather

Area (thousand acres) or volume (million cubic feet)

Area Volume

0

5,000

10,000

15,000

20,000

25,000

Figure 43—Area and volume of live trees affected by one or more damage agents on forest land, Oregon, 2006–2015; volume is gross 

volume of live trees >5 inches diameter at breast height; area includes stands with >25 percent of the basal area with damage.
42

GENERAL TECHNICAL REPORT PNW-GTR-971

ponderosa pine, western hemlock, and grand fir). Lodgepole 

pine had the highest damage rate at 46 percent; cankers, 

dwarf mistletoe, and physical injury and defects each 

affected more than 15 percent of lodgepole pine. The only 

other damaging agents that affected more than 3 percent 

of a top species’ trees were dwarf mistletoe (10 percent of 

ponderosa pines and 9 percent of western hemlocks) and 

root disease (7 percent of grand firs). 

Wildfire

Wildfire plays an important role in both forest and nonforest ecosystems in the Northwest and is a driver of forest 

succession. Oregon’s forest composition today has been 

shaped by historical fires such as the Tillamook burns in the 

1930s and aggressive fire suppression efforts throughout the 

past century. Wildfire management remains a contentious 

issue; while some of Oregon’s forest ecosystems depend 

on fire to maintain forest health, uncontrolled wildfires can 

result in loss of timber value and changes in wildlife habitat, 

threaten structures and lives, and pose human health risks 

owing to smoke. The Northwest Interagency Coordination 

Center tracks wildland fire on an annual basis for Oregon 

and Washington, compiling statistics for large fires (at least 

100 ac on timberlands or 300 ac in grasslands/rangelands). 

In Oregon, between 2006 and 2015, an average of 492,174 

ac burned in large fires annually (NWCC 2017). The Long 

Draw Fire in sagebrush-dominated southeast Oregon 

burned 557,628 ac in 2012, the largest recorded fire in the 

Northwest since 1865. The years 2007, 2014, and 2015 were 

also active fire years, each with more acres burned than the 

10-year average.

FIA collects fire occurrence data on all forested field 

plots when fire causes mortality or damage to at least 25 

percent of all trees in a stand or 50 percent of a single 

species count, in addition to recording the year each fire 

occurs. These data can give an indication of the area of 

forest land burned by all fires regardless of their size. The 

10-year average using FIA field plot estimates was 157,821 

forested ac burned, with the majority of burned area occurring in eastern Oregon (fig. 44).

The number of burned acres over simplifies fire 

dynamics in ecosystems because fire severity is not 

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Fire year

Eastern Oregon Southwest Mountains Western Oregon

Forest area burned (acres)

Figure 44—Area of forest land affected by fire, by fire year and region, Oregon, 2006–2015.
43

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

uniform even within a single burn; to gauge effects on 

forest stands, individual tree measurements add valuable 

information on pre- and postfire carbon dynamics and 

stand regeneration. A comprehensive analysis of all Oregon 

and Washington NFS land indicated that less than half 

the area burned burns at high severity (Whittier and Gray 

2016). In addition, the amount of carbon per acre lost from 

stands within 5 to 10 years of fire is on average comparable 

to the amount lost from current thinning practices (Gray 

and Whittier 2014). 

The PNW-FIA implemented an additional postfire 

study starting in 2015 on recently burned plots to capture 

fire effects and gauge regeneration across the Pacific 

Northwest. The FIA grid provides prefire and postfire 

comparisons for a variety of fire intensities. Postfire 

measurements include individual live tree, dead tree, 

down wood, and groundcover and fuels variables. A study 

using these protocols on FIA plots in California determined that the conceptual carbon trajectories frequently 

used, which assume rapid flux of carbon out of woody 

pools, may not be appropriate for many postfire stands. 

Eskelson et al. (2016) found no evidence of net change 

in total wood carbon (wood in standing trees >5 inches 

d.b.h. and down wood >3 inches in diameter) over the 

postfire period regardless of fire severity class. Further 

analysis of postfire dynamics using this extensive network 

will provide new insights on the effects of fires on carbon 

stocks and regeneration.

Research Application: Moss and Urban 

Pollutants5

Since 1998, the Forest Inventory and Analysis (FIA) 

program has collected 5,500 surveys of epiphytic lichen 

communities used by scientists and land managers for 

evaluating air quality on the nation’s forests. The program recently piloted another approach to biomonitoring 

air quality—using chemical analysis of lichens and moss 

tissue for mapping heavy metals like cadmium, lead, 

arsenic, cobalt, and chromium. Lichens and moss absorb 

their nutrients and moisture from the atmosphere along 

with pollutants present in air and rainwater. Analysis 

of pollutant concentrations in their tissues provides an 

estimate of pollutant deposition in the sampled area. 

National Forest System air quality managers have 

used chemical analysis of lichens and moss for over 30 

years. The NFS method was adapted and piloted on forested FIA plots in the Midwestern United States. (WillWolf et al. 2017) as well as in an urban environment in 

2013. For the urban pilot, scientists sampled a common 

tree-dwelling moss at 346 sites in residential areas across 

Portland, Oregon, and created fine-scaled maps of heavy 

metals in moss (Gatziolis et al. 2016). They teamed up 

with the Oregon Department of Environmental Quality 

(DEQ), who had measured higher than expected cadmium levels with an air-quality monitoring instrument 

at Portland’s one permanent air quality monitoring site. 

Using moss as a screening tool, they found elevated 

cadmium in moss around art glass manufacturers in 

two neighborhoods, neither of which were known to 

regulators as major heavy metals sources (Donovan et al. 

2016). Moss near the larger facility also had high arsenic 

levels. The DEQ installed air-monitoring equipment 

near the larger facility and discovered that cadmium and 

arsenic levels were 49 and 155 times established Oregon 

health targets, respectively. 

What followed were months of intense media 

interest, community meetings, protests, and state-sponsored testing for cadmium in the urine and garden soils 

of residents. Studies evaluating possible public health 

impacts were initiated. Air quality improved after new 

pollution controls were installed on the glass furnaces of 

one of two art glass manufacturers thought to be primary 

contributors of the pollutants (the other manufacturer 

relocated to Mexico). Emissions regulations for these 

kinds of facilities have also been revised. Oregon Governor Kate Brown proposed the ”“Cleaner Air Oregon” 5

 Author: Sarah Jovan.
44

GENERAL TECHNICAL REPORT PNW-GTR-971

regulatory program (Senate Bill 1541) to overhaul air 

toxics regulations statewide with a health-based (vs. technology-based) permitting system for industrial sources of 

air toxics. The bill passed the Oregon State Legislature in 

March 2018, and the draft rules can be viewed along with 

related information at the Cleaner Air Oregon website: 

http://www.oregon.gov/deq/aq/cao/Pages/default.aspx.

The inability to observe air quality at a fine scale 

has been a long-standing challenge for monitoring the 

complex air quality of urban areas. Although moss data 

cannot tell us directly whether human health is at risk, 

testing moss is inexpensive and allows us to collect a 

large number of samples. Air monitoring equipment is 

necessary for understanding potential health concerns 

but can be too costly to use in more than a few locations 

at once. Both approaches used together, however, can 

be a powerful investigative tool that allows effective 

pollution screening and interpretation (fig. 45). 

Literature Cited

Donovan, G.H.; Jovan, S.E.; Gatziolis, D.; Burstyn, 

I.; Michael, Y.L.; Amacher, M.C.; Monleon, V.J. 

2016. Using an epiphytic moss to identify previously 

unknown sources of atmospheric cadmium pollution. 

Science of the Total Environment. 559: 84–93.

Gatziolis, D.; Jovan, S.; Donovan, G.; Amacher, M.; 

Monleon, V. 2016. Elemental atmospheric pollution 

assessment via moss-based measurements in Portland, 

Oregon. Gen. Tech. Rep. PNW-GTR-938. Portland, 

OR: U.S. Department of Agriculture, Forest Service, 

Pacific Northwest Research Station. 55 p.

Will-Wolf, S.; Jovan, S.; Amacher, M.C. 2017. Lichen 

elemental content bioindicators for air quality 

in upper Midwest, USA: a model for large-scale 

monitoring. Ecological Indicators. 78: 253–263.

Figure 45—Common tree-dwelling mosses such as (left) Orthotrichum lyellii can provide an inexpensive method for sampling air 

pollutants at finer scales than is possible with (right) costly air monitoring equipment. The combined approach has proved to be a 

powerful tool for pollution screening.
45

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Online Tables 

A suite of 125 summary data tables that accompany this 

report are available online at https://www.fs.fed.us/pnw/

pubs/pnw_gtr971-supplement.pdf and listed below for 

reference.

Number of plots:

Table 1—Number of Forest Inventory and Analysis plots 

measured by sample status, land class, and ownership 

group, Oregon 2006–2015

Area:

Table 2—Area of sampled land and water by land status 

and ownership group, Oregon 2006–2015

Table 3—Area of forest land by county and land status, 

Oregon 2006–2015

Table 4—Area of forest land by county and ownership 

group, Oregon 2006–2015

Table 5—Area of forest land by ownership and land status, 

Oregon 2006–2015

Table 6—Area of forest land by forest type group and land 

status, Oregon 2006–2015

Table 7—Area of forest land by forest type group and site 

productivity class, Oregon 2006–2015

Table 8—Area of forest land by forest type group, ownership group, and land status, Oregon 2006–2015

Table 9—Area of forest land by forest type group and 

stand size class, Oregon 2006–2015

Table 10—Area of forest land by forest type group and 

stand age class, Oregon 2006–2015

Table 11—Area of forest land by ecological section and 

land status, Oregon 2006–2015

Table 12—Area of forest land by forest type group and 

stand origin, Oregon 2006–2015

Table 13—Area of timberland by forest type group and 

stand size class, Oregon 2006–2015

Number of trees: 

Table 14—Number of live trees on forest land by county 

and land status, Oregon 2006–2015

Table 15—Number of dead trees on forest land by county 

and land status, Oregon 2006–2015

Table 16—Number of live trees on forest land by county 

and broad species group, Oregon 2006–2015

Table 17—Number of dead trees on forest land by county 

and broad species group, Oregon 2006–2015

Table 18—Number of live trees on forest land by species 

group and diameter class, Oregon 2006–2015

Table 19—Number of dead trees on forest land by species 

group and diameter class, Oregon 2006–2015

Table 20—Number of live trees on forest land by forest 

type group and ownership group, Oregon 2006–2015

Table 21—Number of dead trees on forest land by forest 

type group and ownership group, Oregon 2006–2015

Table 22—Average number of live trees per acre on forest 

land by forest type group and ownership group, Oregon 

2006–2015

Table 23—Average number of dead trees per acre on forest 

land by forest type group and ownership group, Oregon 

2006–2015

Table 24—Number of growing stock trees on timberland 

by species group and diameter class, Oregon 2006–2015

Tree volume:

Table 25—Net volume of live trees on forest land by 

ownership and land status, Oregon 2006–2015
46

GENERAL TECHNICAL REPORT PNW-GTR-971

Table 26—Net volume of dead trees on forest land by 

ownership and land status, Oregon 2006–2015

Table 27—Net volume of live trees on forest land by county and land status, Oregon 2006–2015

Table 28—Net volume of dead trees on forest land by 

county and land status, Oregon 2006–2015

Table 29—Net volume of live trees on forest land, by 

county and broad species group, Oregon 2006–2015

Table 30—Net volume of live trees on forest land by forest 

type group and stand size class, Oregon 2006–2015

Table 31—Net volume of dead trees on forest land by forest type group and stand size class, Oregon 2006–2015

Table 32—Net volume of live trees on forest land by forest 

type group and ownership group, Oregon 2006–2015

Table 33—Net volume of dead trees on forest land by forest type group and ownership group, Oregon 2006–2015

Table 34—Net volume of live trees on forest land by species group and ownership group, Oregon 2006–2015

Table 35—Net volume of dead trees on forest land by species group and ownership group, Oregon 2006–2015

Table 36—Net volume of live trees on forest land by species group and diameter class, Oregon 2006–2015

Table 37—Net volume of dead trees on forest land by species group and diameter class, Oregon 2006–2015

Table 38—Net volume of live trees on forest land by forest 

type group and stand origin, Oregon 2006–2015

Table 39—Net volume of dead trees on forest land by forest type group and stand origin, Oregon 2006–2015

Table 40—Net volume of live trees on forest land by forest 

type group and stand age class, Oregon 2006–2015

Table 41—Net volume of dead trees on forest land by forest type group and stand age class, Oregon 2006–2015

Table 42—Average net volume per acre of live trees 

on forest land by forest type group and stand age class, 

Oregon 2006–2015

Table 43—Average net volume per acre of dead trees 

on forest land by forest type group and stand age class, 

Oregon 2006–2015

Table 44—Average net volume per acre of live trees on 

forest land by forest type group and stand size class, 

Oregon 2006–2015

Table 45—Average net volume per acre of dead trees 

on forest land by forest type group and stand size class, 

Oregon 2006–2015

Table 46—Average net volume per acre of live trees on 

forest land by forest type group and ownership group, 

Oregon 2006–2015

Table 47—Average net volume per acre of dead trees on 

forest land by forest type group and ownership group, 

Oregon 2006–2015

Table 48—Net volume of growing stock trees on timberland 

by species group and diameter class, Oregon 2006–2015

Table 49—Net volume of growing stock trees on timberland by species group and ownership group, Oregon 

2006–2015

Table 50—Net volume of sawtimber-size trees on timberland by species group and ownership group, Oregon 

2006–2015

Table 51—Net board-foot volume (Scribner rule) of 

sawtimber trees on timberland by county and ownership 

group, Oregon 2006–2015

Table 52—Net board-foot volume (Scribner rule) of sawtimber trees on timberland by forest type group and ownership group, Oregon 2006–2015

Table 53—Net board-foot volume (Scribner rule) of sawtimber trees on timberland by forest type group and stand 

size, Oregon 2006–2015
47

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Table 54—Net board-foot volume (Scribner rule) of sawtimber trees on timberland by species group and diameter 

class, Oregon 2006–2015

Table 55—Net board-foot volume (International 1⁄4-inch 

rule) of sawtimber trees on timberland by species group 

and diameter class, Oregon 2006–2015

Table 56—Net board-foot volume (International 1⁄4-inch 

rule) of sawtimber trees on timberland by species group 

and ownership group, Oregon 2006–2015

Table 57—Average net board-foot volume of sawtimber 

trees per acre (Scribner rule) on timberland by forest type 

group and ownership group, Oregon 2006–2015

Table 58—Average net board-foot volume of sawtimber 

trees per acre (Scribner rule) on timberland by forest type 

group and stand size, Oregon 2006–2015

Biomass:

Table 59—Aboveground biomass of live trees on forest 

land by ownership and land status, Oregon 2006–2015

Table 60—Aboveground biomass of dead trees on forest 

land by ownership and land status, Oregon 2006–2015

Table 61—Aboveground biomass of live trees on forest 

land by county and land status, Oregon 2006–2015

Table 62—Aboveground biomass of dead trees on forest 

land by county and land status, Oregon 2006–2015

Table 63—Aboveground biomass of live trees on forest 

land by forest type group and ownership group, Oregon 

2006–2015

Table 64—Aboveground biomass of dead trees on forest 

land by forest type group and ownership group, Oregon 

2006–2015

Table 65—Aboveground biomass of live trees on forest 

land by forest type group and stand size class, Oregon 

2006–2015

Table 66—Aboveground biomass of dead trees on forest 

land by forest type group and stand size class, Oregon 

2006–2015

Table 67—Aboveground biomass of live trees on forest 

land by forest type group and stand age class, Oregon 

2006–2015

Table 68—Aboveground biomass of dead trees on forest land by forest type group and stand age class, Oregon 

2006–2015

Table 69—Aboveground biomass of live trees on forest land 

by species group and diameter class, Oregon 2006–2015

Table 70—Aboveground biomass of dead trees on forest 

land by species group and diameter class, Oregon 2006–2015

Table 71—Aboveground green weight biomass of live 

trees on forest land by ownership and land status, Oregon 

2006–2015

Table 72—Aboveground green weight biomass of live 

trees on forest land by species group and diameter class, 

Oregon 2006–2015

Table 73—Average aboveground biomass per acre of live 

trees on forest land by forest type group and ownership 

group, Oregon 2006–2015

Table 74—Average aboveground biomass per acre of dead 

trees on forest land by forest type group and ownership 

group, Oregon 2006–2015

Table 75—Average aboveground biomass per acre of live 

trees on forest land by forest type group and stand size 

class, Oregon 2006–2015

Table 76—Average aboveground biomass per acre of dead 

trees on forest land by forest type group and stand size 

class, Oregon 2006–2015

Table 77—Average aboveground biomass per acre of live 

trees on forest land by forest type group and stand age 

class, Oregon 2006–2015

Table 78—Average aboveground biomass per acre of dead 

trees on forest land by forest type group and stand age 

class, Oregon 2006–2015
48

GENERAL TECHNICAL REPORT PNW-GTR-971

Carbon:

Table 79—Aboveground carbon mass of live trees on forest land by ownership and land status, Oregon 2006–2015

Table 80—Aboveground carbon mass of dead trees on forest land by ownership and land status, Oregon 2006–2015

Table 81—Aboveground carbon mass of live trees on forest land by forest type group and ownership group, Oregon 

2006–2015

Table 82—Aboveground carbon mass of dead trees on forest land by forest type group and ownership group, Oregon 

2006–2015

Table 83—Aboveground carbon mass of live trees on forest land by forest type group and stand size class, Oregon 

2006–2015

Table 84—Aboveground carbon mass of dead trees on forest land by forest type group and stand size class, Oregon 

2006–2015

Table 85—Aboveground carbon mass of live trees on forest 

land by species group and diameter class, Oregon 2006–2015

Table 86—Aboveground carbon mass of dead trees on 

forest land by species group and diameter class, Oregon 

2006–2015

Table 87—Average aboveground carbon mass per hectare 

of live trees on forest land by forest type group and ownership group, Oregon 2006–2015

Table 88—Average aboveground carbon mass per hectare 

of dead trees on forest land by forest type group and ownership group, Oregon 2006–2015

Table 89—Average aboveground carbon mass per hectare 

of live trees on forest land by forest type group and stand 

size class, Oregon 2006–2015

Table 90—Average aboveground carbon mass per hectare 

of dead trees on forest land by forest type group and stand 

size class, Oregon 2006–2015

Down wood:

Table 91—Biomass of down wood on forest land by forest 

type group, ownership group, and land status, Oregon 

2006–2015

Table 92—Carbon mass of down wood on forest land 

by forest type group, ownership group, and land status, 

Oregon 2006–2015

Table 93—Biomass of down wood on forest land by county and land status, Oregon 2006–2015.

Table 94—Carbon mass of down wood on forest land by 

county and land status, Oregon 2006–2015

Table 95—Average biomass per acre of down wood on forest land by forest type group, ownership group, and land 

status, Oregon 2006–2015

Table 96—Average biomass per acre of down wood on forest land by ownership and land status, Oregon 2006–2015

Table 97—Average biomass per acre of down wood on forest land by county and land status, Oregon 2006–2015

Combined dead trees and dead wood (standing dead trees 

and down wood):

Table 98—Average biomass per acre of all dead wood 

(standing dead trees and down wood) on forest land by 

county and land status, Oregon 2006–2015

Table 99—Volume of live trees, standing dead trees, and 

down wood on forest land by stand age class, Oregon 

2006–2015

Table 100—Biomass of live trees, standing dead trees, 

and down wood on forest land by stand age class, Oregon 

2006–2015

Table 101—Carbon mass of live trees, standing dead trees 

and down wood on forest land by stand age class, Oregon 

2006–2015

Table 102—Average volume per acre of live trees, standing dead trees, and down wood on forest land by stand age 

class, Oregon 2006–2015
49

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Table 103—Average biomass per acre of live trees, standing dead trees, and down wood on forest land by stand age 

class, Oregon 2006–2015

Table 104—Average carbon mass per hectare of live trees, 

standing dead trees, and down wood on forest land by 

stand age class, Oregon 2006–2015

National Forest System (NFS):

Table 105—Area of forest land by national forest and land 

status, Oregon 2006–2015

Table 106—Net volume of live trees on forest land by national forest and land status, Oregon 2006–2015

Table 107—Aboveground biomass of live trees on forest 

land by national forest and land status, Oregon 2006–2015

Table 108—Aboveground carbon mass of live trees on 

forest land by national forest and land status, Oregon 

2006–2015

Table 109—Average net volume per acre of live trees 

on forest land by national forest and land status, Oregon 

2006–2015

Table 110—Average aboveground biomass per acre of 

live trees on forest land by national forest and land status, 

Oregon 2006–2015

Table 111—Average aboveground carbon mass per hectare 

of live trees on forest land by national forest and land status, Oregon 2006–2015

Tree damage:

Table 112—Number of live trees with damage on forest 

land by species and type of damage, Oregon 2006–2015

Table 113—Gross volume of live trees with damage 

on forest land by species and type of damage, Oregon 

2006–2015

Table 114—Area of forest land with more than 25 percent 

of basal area damaged by forest type and type of damage, 

Oregon 2006–2015

Understory vegetation:

Table 115—Mean cover of understory vegetation on 

forest land by forest type group and life form, Oregon 

2006–2015

Table 116—Mean cover of understory vegetation by 

forest type class, age class group, and lifeform, Oregon 

2006–2015

Table 117—Estimated area of forest land covered by 

selected nonnative vascular plant species and number of 

sample plots by lifeform and species, Oregon 2006–2015

Table 118—Estimated area of forest land covered by the 

most abundant vascular plant nontimber forest products by 

plant group and species, Oregon 2006–2015

Timber products output and removals:

Table 119—Total roundwood output by product, species 

group, and source of material, Oregon 2013

Table 120—Volume of timber removals by type of removal, source of material, and species group, Oregon 2013

Annual growth, removals, and mortality:

Table 121—Average annual volume (cubic feet per acre) 

growth, removals, and mortality on forest land by ownership group, Oregon 2001–2005 and 2011–2015

Table 122—Average annual volume (cubic feet) growth, 

removals, and mortality on forest land by ownership 

group, Oregon 2001–2005 and 2011–2015

Table 123—Average annual biomass (tons per acre) 

growth, removals, and mortality on forest land by ownership group, Oregon 2001–2005 and 2011–2015

Table 124—Average annual biomass (tons) growth, removals, and mortality on forest land by ownership group, 

Oregon 2001–2005 and 2011–2015

Evidence of fire:

Table 125—Forest land area on which evidence of fire 

was observed, by year and ecosection group, Oregon 

2006–2015
50

GENERAL TECHNICAL REPORT PNW-GTR-971

Common and Scientific Plant Names (continued)

Life form Common name Scientific name

Trees: Alder Alnus spp. 

Ash Fraxinus spp. 

Aspen, quaking aspen Populus tremuloides Michx.

Birch Betula spp. 

Cottonwood Populus spp. 

Douglas-fir Pseudotsuga menziesii (Mirb.) Franco

Elm Ulmus spp. 

Engelmann spruce Picea engelmannii Parry ex Engelm.

Hemlock Tsuga spp. 

Incense cedar Calocedrus decurrens (Torr.) Florin

Jeffrey pine Pinus jeffreyi Balf.

Laurel Umbellularia californica (Hook. & Arn.) Nutt.

Lodgepole pine Pinus contorta Douglas ex Loudon

Maple Acer spp. 

Mountain hemlock Tsuga mertensiana (Bong.) Carrière

Oak Quercus spp. 

Ponderosa pine Pinus ponderosa Lawson & C. Lawson

Red alder Alnus rubra Bong.

Sitka spruce Picea sitchensis (Bong.) Carrière

Spruce Picea spp. 

Sugar pine Pinus lambertiana Douglas

Tanoak Lithocarpus densiflorus (Hook & Arn.) Rehder

True fir species Abies spp. 

Western hemlock Tsuga heterophylla (Raf.) Sarg.

Western juniper Juniperus occidentalis Hook.

Western larch Larix occidentalis Nutt.

Western redcedar Thuja plicata Donn ex D. Don

Shrubs: Beaked hazelnut Corylus cornuta Marshall

Cascade barberry, dwarf Oregon grape Mahonia nervosa (Pursh) Nutt.

California blackberry, trailing blackberry Rubus ursinus Cham. and Schltdl.

California huckleberry Vaccinium ovatum Pursh

Common snowberry Symphoricarpos albus (L.) S.F. Blake

Dwarf mistletoe Arceuthobium spp. 

Grouse whortleberry Vaccinium scoparium Leiberg ex Coville

Himalayan blackberry Rubus discolor Weihe & Nees

Oceanspray Holodiscus discolor (Pursh) Maxim.

Salal Gaultheria shallon Pursh

Salmonberry Rubus spectabilis Pursh

Scotch broom Cytisus scoparius (L.) Link
51

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Common and Scientific Plant Names (continued)

Life form Common name Scientific name

Snowbrush ceanothus Ceanothus velutinus Douglas ex Hook.

Thinleaf huckleberry Vaccinium membranaceum Douglas ex Torr.

Vine maple Acer circinatum Pursh

Forbs: Hairy cat’s ear Hypochaeris radicata L.

Graminoids: Bristly dogstail grass Cynosurus echinatus L.

Cheatgrass Bromus tectorum L.

Common velvetgrass Holcus lanatus L.

Medusahead Taeniatherum caput-medusae (L.) Nevski

North Africa grass Ventenata dubia (Leers) Coss.

Acknowledgments

The tremendous FIA dataset would not be possible without 

the dozens of field staff who trek near and far each year to 

collect our field data. Thanks also to our quality assurance 

staff who work tirelessly to ensure the most accurate datasets possible, and to the information management specialists 

who compile and store these data and make them available 

to the public. 

Metric Equivalents

When you know: Multiply by: To find:

Inches (in) 2.54 Centimeters

Feet (ft) 0.3048 Meters

Acres (ac) 0.405 Hectares

Board feet 0.0024 Cubic meters

Cubic feet (ft3

) 0.0283 Cubic meters

Cubic feet per acre 

(ft3

/ac) 

0.0670 Cubic meters per 

hectare

Tons per acre 2.2417 Megagrams per 

hectare 

U.S. Equivalents

When you know: Multiply by: To find:

Kilograms (kg) 2.2046 Pounds

Megagrams (Mg) 1.1023 Tons

Megagrams per 

hectare

0.4461 Tons per acre

Literature Cited

Alexander, .J.; Oswalt, S.N.; Emery, M.R. 2011.

Nontimber forest products in the United States: Montreal 

Process indicators as measures of current conditions and 

sustainability. Gen. Tech. Rep. PNW-GTR-851. Portland, 

OR: U.S. Department of Agriculture, Forest Service, 

Pacific Northwest Research Station. 36 p.

Bansal, S.; Brodie, L.; Stanton, S.; Waddell, K.; Palmer, 

M.; Christenson, G.; Kuegler, O. 2017. Oregon’s 

forest resources, 2001–2010: Ten-year Forest Inventory 

and Analysis report. Gen. Tech. Rep. PNW-GTR-958. 

Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station. 130 p.

Bassett, P.M.; Choate, G.A. 1974. Timber resource 

statistics for Oregon, January 1, 1973. Resour. Bull. PNWRB-56. Portland, OR: U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station. 37 p.

Bell, D.M.; Gregory M.J.; Ohmann J.L. 2015. Imputed 

forest structure uncertainty varies across elevational 

and longitudinal gradients in the western Cascade 

Mountains, Oregon, USA. Forest Ecology and 

Management. 358: 154–164.

Binder, S.; Haight, R.G.; Polasky, S.; Warziniack, 

T.; Mockrin, M.H.; Deal, R.L.; Arthaud, G. 2017. 

Assessment and valuation of forest ecosystem services: 

state of the science review. Gen. Tech. Rep. NRS-170. 

Newtown Square, PA: U.S. Department of Agriculture, 

Forest Service, Northern Research Station. 47 p.
52

GENERAL TECHNICAL REPORT PNW-GTR-971

Blackard, J.; Finco, M.; Helmer, E.; Holden, G.; 

Hoppus, M.; Jacobs, D.; Lister, A.; Moisen, G.; 

Nelson, M.; Riemann, R.; Ruefenacht, B.; Salajanu,

D.; Weyermann, D.; Winterberger, K.; Brandeis, 

T.; Czaplewski, R.; McRoberts, R.; Patterson, P.; 

Tymcio, R. 2008. Mapping U.S. forest biomass using 

nationwide forest inventory data and moderate resolution 

information. Remote Sensing of Environment. 112(4): 

1658–1677.

Boyd, J.; Banzhaf, S. 2007. What are ecosystem services? 

The need for standardized environmental accounting 

units. Ecological Economics. 63(2–3): 616–626.

Campbell, S.; Dunham, P.; Azuma, D. 2004. Timber 

resource statistics for Oregon. Resour. Bull. PNWRB-242. Portland, OR: U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station. 67 p.

Donnegan, J.; Campbell, S.; Azuma, D. 2008. Oregon’s 

forest resources, 2001–2005: five-year forest inventory 

and analysis report. Gen. Tech. Rep. PNW-GTR-765. 

Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station. 188 p.

Donovan, G.H.; Jovan, S.E.; Gatziolis, D.; Burstyn, I.; 

Michael, Y.L.; Amacher, M.C.; Monleon, V.J. 2016.

Using an epiphytic moss to identify previously unknown 

sources of atmospheric cadmium pollution. Science of 

the Total Environment. 559: 84–93.

English, D.B.K. [et al.]. 2014. Outdoor recreation: jobs 

and income. Federal Interagency Council on Outdoor 

Recreation. https://www.fs.fed.us/research/docs/outdoorrecreation/recreation-economy.pdf. (17 October 2017).

Eskelson, B.N.I.; Monleon, V.J.; Fried, J.S. 2016. A 

6 year longitudinal study of post-fire woody carbon 

dynamics in California’s forests. Canadian Journal of 

Forest Research. 46: 610–620.

Farrenkopf, T.O. 1982. Forest statistics for eastern Oregon, 

1977. Resour. Bull. PNW-RB-94. Portland, OR: U.S. 

Department of Agriculture, Forest Service, Pacific 

Northwest Forest and Range Experiment Station. 84 p.

Federal Forest Advisory Committee [FFAC] 2012.

National forest health restoration: an economic assessment 

of forest restoration on Oregon’s eastside national forests. 

Prepared for: Governor John Kitzhaber and Oregon’s 

Legislative Leaders. Portland, OR: Portland State 

University Northwest Economic Research Center. 94 p. 

Fried, J.S.; Potts, L.D.; Loreno, S.M.; Christensen, G.; 

Barbour, J.R. 2017. Inventory based landscape-scale 

simulation of management effectiveness and economic 

feasibility with BioSum. Journal of Forestry. 115: 249–257.

Gatziolis, D.; Jovan, S.; Donovan, G.; Amacher, M.; 

Monleon, V. 2016. Elemental atmospheric pollution 

assessment via moss-based measurements in Portland, 

Oregon. Gen. Tech. Rep. PNW-GTR-938. Portland, OR: 

U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station. 55 p.

Gedney, D.R. 1982. Timber resources of western Oregon—

highlights and statistics. Resour. Bull. PNW-RB-97. 

Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Forest and Range Experiment 

Station. 84 p.

Gray, A.N.; Whittier, T.R. 2014. Carbon stocks and 

changes on Pacific Northwest national forests and the 

role of disturbance, management, and growth. Forest 

Ecology and Management. 328: 167–178. http://www.

treesearch.fs.fed.us/pubs/46566.

Hanson, E.J.; Azuma, D.L.; Hiserote, B.A. 2003. Site 

index equations and mean annual increment equations 

for Pacific Northwest Research Station forest inventory 

and analysis inventories, 1985–2001. Res. Note PNWRN-533. Portland, OR: U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station. 24 p.

Heath, L.S.; Hansen, M.H.; Smith, J.E.; Miles, P.D. 

2009. Investigation into calculating tree biomass and 

carbon in the FIADB using a biomass expansion factor 

approach. In: McWilliams, W.; Moisen, G.; Czaplewski, 

R., comps. Forest Inventory and Analysis (FIA) 

Symposium 2008. RMRS-P-56CD. Fort Collins, CO: 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station. 1 CD.
53

Oregon’s Forest Resources, 2006–2015: Ten-Year Forest Inventory and Analysis Report

Jain, T.J.; Battaglia, M.A.; Han, H.S.; Graham, R.T.; 

Keyes, C.R.; Fried, J.S.; Sandquist. J.E. 2012. A 

comprehensive guide to fuel management practices for 

dry mixed conifer forests in the northwestern United 

States. Gen. Tech. Rep. RMRS-GTR-292. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station. 331 p. https://www.

fs.usda.gov/treesearch/pubs/42150.

Keith, H.: Mackey, B.G.; Lindenmayer, D.B. 2009. Reevaluation of forest biomass carbon stocks and lessons 

from the world’s most carbon-dense forests. Proceedings 

of the National Academy of Sciences of the United States 

of America. 106: 11625–11640.

Lettman, G.; Gray, A.; Hubner, D.; McKay, N.;

Thompson, J. 2016. Forests, farms, and people: land 

use change on non-federal land in Oregon 1974–2014. 

Oregon Department of Forestry. http://hdl.handle.

net/1957/58941. (22 November 2017).

Loreno, S.; Fried, J.S.; Yost, A. 2015. Applying 

management modeling to assess the feasibility of 

accelerating landscape restoration on federal forests in 

eastern Oregon. In: Stanton, S.M.; Christensen, G.A., 

comps. 2015. Pushing boundaries: new directions in 

inventory techniques and applications: Forest Inventory 

and Analysis (FIA) symposium 2015: 260–265. https://

www.fs.usda.gov/treesearch/pubs/50355.

Metcalf, M.E. 1965. Timber resource statistics for the 

Pacific Northwest as of January 1, 1963. Resour. 

Bull. PNW-RB-9. Portland, OR: U.S. Department of 

Agriculture, Forest Service, Pacific Northwest Research 

Station. 38 p.

Moravets, F.L.; Rogers, N.S.; McCullouch, W.F.;

Cronemiller, L.F. 1942. Forest resources of Oregon. 

Salem, OR: Oregon State Board of Forestry. 67 p.

Northwest Interagency Coordination Center [NWCC]

2017. NWCC annual fire report archive, 2006–2015.

https://gacc.nifc.gov/nwcc/admin/publications.aspx. (21 

November 2017).

O’Connell, B.M.; Conkling, B.L.; Wilson, A.M.; Burrill, 

E.A.; Turner, J.A.; Pugh, S.A.; Christensen, G.; 

Ridley, T.; Menlove, J. 2017. The Forest Inventory and 

Analysis Database: Database description and user guide 

version 7.0 for Phase 2. U.S. Department of Agriculture, 

Forest Service. 830 p. http://www.fia.fs.fed.us/library/

database-documentation/.

Oregon Department of Forestry [ODF]. 2016. Timber 

harvest data 1942–2016. https://data.oregon.gov/NaturalResources/Timber-Harvest-Data-1942-2016/9cuv-nijj. (19 

September 2017). 

Oregon Forest Resources Institute [OFRI]. 2017. Oregon 

forest facts 2017–2018 edition. http://oregonforests.

org/sites/default/files/2017-05/OFRI_FactsFacts_1718_

WEB_1.pdf. (19 September 2017).

Rapp, V. 2005. Invasive plants in 21st century landscapes. 

Science Update 9. Portland, OR: U.S. Department of 

Agriculture, Forest Service, Pacific Northwest Research 

Station. 12 p.

Rooney, B. 2016. Oregon’s wood product manufacturing 

industry is still important, especially in rural areas.

Salem, OR: Oregon Employment Department. https://

www.qualityinfo.org/-/oregon-s-wood-productmanufacturing-industry-is-still-important-especially-inrural-areas. (19 September 2017).

Rose, C.L.; Marcot, B.G.; Mellen T.K.; Ohmann, J.L.; 

Waddell, K.L.; Lindley, D.L.; Schreiber, B. 2001. 

Decaying wood in Pacific Northwest forests: concepts 

and tools for habitat management. In: Johnson, D.H.; 

O’Neil, T.A., eds. Wildlife-habitat relationships in 

Oregon and Washington. Corvallis, OR: Oregon State 

University Press: 580–623. Chapter 24.

Simmons, E.A.; Scudder, M.G.; Morgan, T.A.; Berg, 

E.C.; Christensen, G.A. 2016. Oregon’s forest products 

industry and timber harvest 2013 with trends through 

2014. Gen. Tech. Rep. PNW-GTR-942. Portland, OR: 

U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station. 58 p.
54

GENERAL TECHNICAL REPORT PNW-GTR-971

U.S. Department of Agriculture, Forest Service 

[USDA FS]. 2013. Accelerated restoration. https://

www.fs.usda.gov/detail/r6/landmanagement/

resourcemanagement/?cid=stelprdb5423597. (19 

December 2017).

U.S. Department of Agriculture, Forest Service[USDA 

FS] 2015. Recreation fee program accomplishment 

highlights 2006–2015. https://www.fs.usda.gov/detail/

r6/passes-permits/recreation/?cid=fsbdev2_026999. (19 

October 2017).

White, E.M.; Bowker, J.M.; Askew, A.E.; Langner, L.L.; 

Arnold, J.R.; English, D.B.K. 2016. Federal outdoor 

recreation trends: effects on economic opportunities. 

Gen. Tech. Rep. PNW-GTR-945. Portland, OR: U.S. 

Department of Agriculture, Forest Service, Pacific 

Northwest Research Station. 46 p.

Whittier, T.R.; Gray, A.N. 2016. A tree mortality based 

fire severity classification for forest inventory surveys: 

a Pacific Northwest national forests example. Forest 

Ecology and Management. 359: 199–209. https://www.

fs.usda.gov/treesearch/pubs/50918.

Will-Wolf, S.; Jovan, S.; Amacher, M.C. 2017. Lichen 

elemental content bioindicators for air quality in upper 

Midwest, USA: a model for large-scale monitoring. 

Ecological Indicators. 78: 253–263.

Woodall, C.W.; Heath, L.S.; Domke, G.M.; Nichols,

M.C. 2011. Methods and equations for estimating 

aboveground volume, biomass, and carbon for trees in 

the U.S. forest inventory, 2010. Gen. Tech. Rep. NRS-88. 

Newtown Square, PA: U.S. Department of Agriculture, 

Forest Service, Northern Research Station. 30 p.


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