United States

Department of

Agriculture

Forest Service

Proceedings of the Symposium on

Ecosystem Management Research

Southern Forest

Experiment Station in the Ouachita Mountains:

New Orleans,

Louisiana

General Technical Report

SO-I 12

’ August 1994

Pretreatment Conditions and

Preliminary Findings

Proceedings of the Symposium on

ECOSYSTEM MANAGEMENT RESEARCH IN THE OUACHITA MOUNTAINS:

PRETREATMENT CONDITIONS AND PRELIMINARY FINDINGS

Hot Springs, Arkansas

October 26-27, 1993

Compiled by

James B. Baker

Published by

U.S. Department of Agriculture

Forest Service

Southern Forest Experiment Station

New Orleans, Louisiana

1994
PREFACE

In August 1990, USDA Forest Service researchers from the Southern Forest Experiment Station and resource

managers from the Ouachita and Ozark National Forests embarked on a major ecosystem management (then called New

Perspectives) research program aimed at formulating, implementing, and evaluating partial cutting methods in shortleaf

pine-hardwood stands as alternatives to clearcutting and planting. The program consisted of three phases: Phase I-an

umeplicated stand-level demonstration project; Phase II-a scientifically based, replicated stand-level study; and Phase

III-a large-scale watershed or landscape study.

Harvesting treatments for the stand-level (Phase II) study were implemented during the summer of 1993. However,

soon after the test stands were selected in 1990, pretreatment monitoring of various parameters was begun by a research

team comprised of more than 50 scientists and resource managers from several Federal and State agencies and

universities (a list of the research team follows). The pretreatment monitoring continued through the summer of 1993.

A symposium, cosponsored by the USDA Forest Service Southern Forest Experiment Station and Ouachita and

Ozark National Forests, the University of Arkansas at Monticello School of Forest Resources, the Arkansas Cooperative

Extension Service, and the Ouachita Society of American Foresters, was held in Hot Springs, AR, on October 26-27,

1993,%to present these pretreatment conditions and preliminary findings. This Proceedings includes those presentations.

I would like to express my gratitude to all of the participants in this symposium, and especially to the authors who

have contributed to this effort. Also, there are a number of individuals whose contributions made the meeting a success,

and they deserve a special note of thanks. They include:

Dr. Larry Willett, Arkansas Cooperative Extension Service, Monticello, AR. Larry handled the

symposium announcements and registration and many other logistical chores that helped the symposium

to run smoothly.

Dave Hammond, O.D. Smith, Larry Hedrick, Bill Walker, Dan Nolan, Frank Yerby, and Frank Lewis USDA

Forest Service, Ouachita and Ozark National Forest staff officers and rangers who served as moderators for

the various sessions of the symposium and kept us on schedule.

The sponsors, without whose support the symposium could not have been held.

James B. Baker, Team Leader

USDA Forest Service

Southern Forest Experiment Station

Monticello, Arkansas
PHASE II RESEARCH TEAM

USDA Forest Service

Southern Forest Experiment Station

Dr. James Baker, Team Leader Mr. Charles McMahon, Research Chemist

Monticello, AR Auburn, AL

Dr. James Bamett, Research Ecophysiologist

Pineville, LA

Dr. Jerry Michael, Research Ecologist

Auburn, AL

Dr. Rod Busby, Research Economist

New Orleans, LA

Dr. Jim Miller, Research Forester

Auburn, AL

Dr. Margaret Devall, Research Ecologist

New Orleans, LA

Dr. Bernie Parreeol, Research Biometrician

New Orleans, LA

Dr. Pat Fowler, Research Hydrologist

Hot SpriIlgS, AR

Mr. Roger Perry, Wildlife Biologist

Hot SplilIgS, AR

Dr. Jim Guldin, Research Ecologist

Hot Springs, AR

Mr. Vie Rudis, Recreation/Landscape Ecologist

Starkville, MS

Dr. Howard Halverson, Research Hydrologist

Oxford, MS

Dr. Mike Shelton, Research Silviculturist

Monticello, AR

Dr. Jane Hayes, Research Forest Entomologist

Pineville, LA

Dr. Bryce Stokes, Research Forest Engineer

Auburn, AL

Dr. Pete Lorio, Soil Scientist

Piieville, LA

Dr. Ron ThiU, Research Wildlife Biologist

Nacogdoches, TX

Dr. Ted Leininger, Research Forest Pathologist

Stoneville, MS

Dr. Allen Tiarks, Soil Scientist

Pineville, LA

USDA Forest Service

Southeastern Forest Experiment Stntiun

Dr. Ken Cordell, Research Recreation Specialist

Athens, GA

Dr. Jim Hanula, Research Entomologist

Athens, GA

Dr. Don English, Social Scientist

Athens, GA

Ms. Christine Overdeveat, Sociologist

Athens, GA

USDA Forest Service

Ouachita National Forest, Hot Springs, AR

Mr. Roger Coleman, Archeologist

Mr. Mike Curran, Forest Supervisor

Mr. Alan Clingenpeel, Hydrologist

Mr. Larry Hedrick, Wildlife Staff Officer

Mr. Tim Mersmann, Forester

Mr. Dan Nolan, Planning/Recreation Staff Officer

Mr. Bill Pe& Ecosystem Management Coordinator

Mr. Bill Walker, Timber/Water Staff Officer

USDA Forest Service

Ozark National Forest, Russellville, AR

USDA Forest Servii, Southern Region

Forest Health, Pinedie, LA

Mr. Gary Hartman. Wildlife Staff Officer

Mr. Lynn Neff, Forest Supervisor

Mr. 0. D. Smith, Timber Staff Officer

Dr. Alex Mangini, Forest Entomologist

Mr. Dale Starkey, Forest Pathologist

. . . 111
USDI Fiih and Wildlife Service

Dr. Tom Martin, Wildlife Biologist

Montana Cooperative Wildlife Research Unit

Missoula, MT

Arkansas Nature Conservancy Smithsonian Environmental Research Center

Little Rock, AR Edgewrrter, MD

Mr. Lance Peacock, Ecologist

Arkansas State University

State University, AR

Dr. Julia Bollinger, Entomologist

Arkansas Natural Heritage Inventory

Lii Ruck, AR

Mr. Tom Foti, Ecologist

Dr. Dan Petit, Wildlife Biologist

Arkansas Tech University

Russellville, AR

Dr. Therwa Herrick, Recreation Specialist

Mississippi State University

Starkville, MS

Oklahoma State University

!3tilhvater, OK

Dr. Dennis Cengel, Nonmarket Valuation Specialist

Mr. Jim Clark, Landscape Architect

Ms. Rebecca Ray, Graduate Assistant

Dr. Larry Gering, Biometrician

Dr. Chuck Tauer, Forest Geneticist

Dr. Don Turton, Hydrologist

Dr. Bob Wittwer, Silviculturist

Texas A&M University, College Station University of Arkansas, Fayetteville

Dr. Jim Gramann, Recreation Specialist Dr. Chris Carlton, Entomologist

Mr. Jim Taulman, Wildlife Biologist

University of Arkansas, Monticello

Dr. Dick Kluender, Forest Economist

Dr. Ed Lawson, Hydrologist

Dr. Phiip Tappe, Wildlife Biologist

NCASI, Clemson University

Dr. Bently Wigley, Wildlife Biologist

iV
CONTENTS

Background and Overview

Evolution of Ecosystem Management and Research on the Ouachita and Ozark-St.Francis National Forests

M:lkeCurran.................................................................................. 1

Roles of Science and Research in Implementing Ecosystem Management on the Ouachita National Forest

William F.Pell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Implementing Ecosystem Management Research: Bringing Researchers, Managers, and Citizens Together

Timothy J. Mersmann, James B. Baker, James M . Guldin, and William F. Pell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

An Overview of Stand-Level Ecosystem Management Research in the OuachitalOzark National Forests

JamesB.Baker............................................................................... 1 8

Pretreatment Conditions and Preliminary Findings in Mature Pine-Hardwood

Stands on South-Facing Slopes of the Ouachita/Ozark National Forests

Plant Communities

Midstory and Overstory Plants in Mature Pine-Hardwood Stands on South-Facing Slopes of the OuachitalOzark

National Forests

James M. Guldin, James B. Baker, and Michael G. Shelton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Herbaceous Plant Diversity of Stands in the Ouachita and Ozark National Forests

Thomas L. Foti and Margaret S. Devall . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Multivariate Analysis of the Ground Cover Layer, Shrub Layer, Midstory, and Overstory of the OuachitalOzark National

Forests

Thomas L. Foti and James M. Guldin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

Wildlife Communities

Small Mammal Communities of Mature Pine-Hardwood Stands in the Ouachita Mountains

Phillip A. Tappe, Ronald E. Thill, Joseph J. Krystofik, and Gary A. Heidt . . . . . . . , . . . . . . . . . . . . . . , . . . . . . . . . . . . . . 74

Southern Flying Squirrels in Mature Pine-Hardwood Stands in the Ouachita and Ozark National Forests of Arkansas

James F. Taulman and Ronald E. Thill . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

Breeding Birds of Late-Rotation Pine-Hardwood Stands: Community Characteristics and Similarity to Other Regional

Pine Forests,

Daniel R. Petit, Lisa J. Petit, Thomas E. Martin, Ronald E. Thill, and James F. Tauiman . . . . . . . . . . . . . . . . . . . . _ . . . . . 103

Predicting the Effects of Ecosystem Management Harvesting Treatments on Breeding Birds in Pine-Hardwood Forests

Lisa J. Petit, Daniel R. Petit, Thomas E. Martin, Ronald E. Thill, and James F. Taulman . . . . . . . . . . . . . . . . . . . . . . . . . . 117

Wildlife Habitat Conditions in Mature Pine-Hardwood Stands in the Ouachita/Ozark National Forests

Ronald E. Thill, Phillip A. Tappe, and Nancy E. Koerth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126

V
Arthropod and Microbial Communities

Arthropod BiodiversitySampiing Protocol Development

C. E. Carlton, J. Bollinger, and L. C. Thompson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Seed, Cone, Regeneration, and Defoliating Insects in Forest Ecosystem Management

Alex Mangini. Chris Carlton, Roger W. Perry, and James Hanula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Southern Pine Beetle Risk Ratings

Pete.rL.Lotio,Jr. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..I....................................

Crown Health of Overstory Hardwoods

DaleA:Starkey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Water, Soils, and Cultural Resources

Woody Debris Dynamics in Zero Order Streams of the Ouachita National Forest: Preliminary Findings

Wm.Patrick Fowler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Water Chemistry of Ephemeral Streams

J. L. Michael, W. P. Fowler, H. L. Gibbs, and J. B. Fischer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Forest Floor Characteristics in Mature Pine-Hardwood Stands in the Ouachita Mountains

Michael G. Shelton and Edwin R. Lawson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

New Perspectives in Heritage Resource Management on the Ouachita National Forest

RogerE.Coleman.....................................................................

Scenic Quality

Esthetics Evaluation

Victor A. Rudis, James H. Gramann, and Theresa A. Herrick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Visitor Preference for Forest Scenery in the Ouachita National Forest

Theresa A. Herrick and Victor A. Rudis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . .

. . .

. . .

. . .

. . .

Effects of Hardwood Retention, Season of Year, and Landform on the Perceived Scenic Beauty of Forest Plots in the

Ouachita Mountains

James H. Gramann and Victor A. Rudis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Logging and Management Economics

Production Time, Total Costs, and Residual Damage at Varying Harvest Intensities

Richard A. Kluender, David A. Lortz, and Bryce J. Stokes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Understanding People and Natural Resource Relationships: Ouachita National Forest Timber Purchasers

and Changing Timber Harvest Policy

Christine Overdevest and Donald B. K. English . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Management Costs Associated with Various Reproduction Cutting Methods

Rodney L. Busby and Richard A. Kluender . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . _ . . . . . . . . . . . . . . . . . . . . .

. . 154

. . 162

. . 172

. . 182

. . 186

. . 191

. . 198

. . 202

. . 212

. 223

. 229

. 241

. 253

Each contributor submitted camera-ready copy and is responsible for the accuracy and style of his or her paper.

The statements of the contributors do not necessarily reflect the policy of the U.S. Department of Agriculture,

Forest Service or the Southern Forest Experiment Station.

vi
Evolution of Ecosystem Management and Research on the

Ouachita and Ozark-St. Francis National Forests

Mike Curran’

ABSTRACT

Progressive change has surrounded the development and management by the USDA

Forest Service of the Ouachita National Forest since its establishment in 1907.

Destructive logging practices that left the land in poor condition were followed by a

period of restoration and protection. As the forest matured, its valuable timber

products were once again in demand. Controversy erupted as the public saw national

forest lands being managed similar to timber industry lands. A protracted period of

planning, appeals, and lawsuits led to changes that contributed to the agency’s

movement into an ecosystem-based form of management. In 1993, the USDA Forest

Service management on the Ouachita and Ozark-St. Francis National Forests and

researchers at the Southern Forest Experiment Station were presented the first USDA

Forest Service Chiefs Ecosystem Management Award.

\ INTRODUCTION

At the turn of the century, public lands were being exploited throughout the country for their timber reserves.

Destructive logging practices that showed little regard for the future resulted in eroded soils and damaged watersheds. These

deteriorating conditions caught the attention of then President Theodore Roosevelt, prompting the establishment of national

forests that would be managed by the USDA Forest Service.

In a span of 85 years, the Ouachita National Forest progressed from that period of environmental disobedience to become

a national leader in ecosystem management. Once known as that “inaccessible burning and bleeding wilderness, ” the forest

now enjoys the proud distinction of being known as a laboratory for progressive change.

In the early years, forest managers gently tinkered with the parts while awaiting the restoration of the forest’s resilient

biological systems. In the absence of fire, forests returned, not as before, but as nature would have it, reincarnated as a new

forest with a new look and a new life. As nature replenished the forest, the public’s recognition of, and fondness for, these

new forest lands also evolved.

Following World War II, and accelerating into the 1960’s, dramatic change was occurring on a regional scale as millions

of acres of forest industry lands were converted to plantations. National forest lands were following suit, and the unfavorable

public response was inevitable. Just as surely as the commercial potential of these productive lands once fostered

exploitation, so has their restored beauty developed a passion for protection.

THE 1986 FOREST PLAN

The first version of a comprehensive

the spring of 1986. Controversy over

Forest Land Management Plan for the Ouachita National Forest was completed in

the strong timber emphasis and wide use of clearcutting erupted with multiple

administrative appeals and a drive by the environmental community to generate public support. Powerful coalitions were

developing, which aggressively promoted media interest and political support. Controversy surrounding the management

of the Ouachita National Forest provided the opportunity for Forest Service management to promote change from within and

to experiment with bold new initiatives.

’ Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

* Forest supervisor, Ouachita National Forest, Hot Springs, AR 71902.
With a new, but already tarnished Forest Plan some 10 years in the making, management’s task was to convince agency

leadership of the need to return to the planning process. It was clear that the plan did not have broad public support, and

that weaknesses in the plan would not survive numerous substantive appeals. With a willingness on the part of Forest Service

personnel to reevaluate the issues in good faith, the opportunity existed to forge a closer working relationship with alienated

public interests.

TH E NEW FOREST PLAN

Chief Dale Robertson agreed to suspend action on the appeals and allow the Forest Service to reenter the planning

process. Interim guidelines for management were defined for the period of time required to supplement the original Forest

Plan. However, the decision to supplement the Plan was not without considerable fanfare. Some greeted the decision with

anticipation, while others viewed it with skepticism.

In an attempt to demonstrate sincerity and generate a climate for constructive resolution of the issues, the Forest Service

announced to the media that “clearcutting was on the way out and selection logging was on the way in.” Enthusiasm was

beginning to build as most interests looked forward to a new day. However, the timber industry felt betrayed as they

thought they had already made numerous concessions in developing the original Forest Plan.

An important decision was made at the onset of planning to involve the public in all aspects of the decision process.

With Forest Service credibility rapidly declining, the intent was to draw all interests back into the planning process with the

hope of fashioning resolution on all or part of the issues. A comprehensive public participation plan was developed that

included periodic bulletins, news releases, public forums, and workshops. A high priority was placed on individual and

group contact on a continuing basis. Consensus building occurred throughout the process but resulted in limited success.

Some successful negotiations did occur: with the Wild Turkey Federation that resulted in the establishment of walk-in

turkey areas; with Tom McClure of the Wilderness Society that provided for the expansion and protection of special areas;

with the Oklahoma Department of Wildlife Conservation who successfully fought for the retention of hardwoods in all pine

stands; and with the timber industry that allowed for the further reduction of clearcutting.

Others, however, like the Ouachita Watch League (OWL) and the Sierra Club, chose to take advantage of public

indignation over clearcutting and pursued administrative and legal procedures to maximize their objectives. Given the

social/political climate surrounding forest management in Arkansas and Oklahoma at the time, it is doubtful that further

consensus building with these groups would have been possible.

A variety of issues including timber harvest methods, herbicide use, road construction, and recreation emphasis were

reevaluated. The overriding issue was, and still remains, the fear of change or reduction of hardwood composition within

the pine-vegetative type. The supplemental plan succeeded in attaining increased support from the public and most

appellants. In spite of the many changes incorporated into the new Forest Plan to accommodate the concerns of the

environmental community, OWL and the Sierra Club appealed the supplemental plan and filed a lawsuit.

The new plan issued in March 1990 reflects innovation and public responsiveness in forest management. Highlights

include:

Continuous and substantive involvement by the public in the decision-making process.

Major reduction in clearcutting from 16,000 acres per year to 5,200 acres per year, and presently, with

recent amendments, virtual elimination of clearcutting.

Increase in seed tree and shelterwood methods.

Experimental use of 15,000 acres per year of selection-harvest methods.

Significant increases in thinning.

Hardwood retention within pine stands.

Restricted timber harvest in hardwood types.

Maximum protection for stream corridors, which precludes any timber removal.

Major expansion of special areas (scenic, biologic, etc.)

Addition of two new wilderness areas and a National Recreation Area in Oklahoma.

Two new Wild & Scenic River designations for the Cossatot and Little Missouri Rivers.

Two new Scenic Byways for Hwy. ‘7 and the Talimena Scenic Drive.

Major increase in trail construction and reconstruction.

Initiation and completion of the first botanical inventory of the Ouachita National Forest.
As a result of the considerable efforts made to resolve the issues, the Forest Service was recognized with awards from

both the Arkansas and Oklahoma Wildlife Federations and in 1991 was the recipient of the Chevron Conservation Award

and the United Nations Environmental Programme Award.

NEW PERSPECTIVES

In August of 1990, an event of historic significance occurred when Chief Dale Robertson met with Arkansas Senator

David Pryor to discuss the continued use of clearcutting in the Ouachita National Forest. Labeled the “Walk in the Woods”

by the media, the meeting signaled the agency’s movement away from clearcutting as a predominant harvesting method.

More importantly, it signaled a move toward an ecosystem approach to management. In fact, the Walk in the Woods led

to the designation of the forest as a lead forest under the New Perspectives Program, opening the way for a unique

partnership between national forest management, researchers, and the public. Progressive change and innovation were

the hallmarks of this effort.

In order to capitalize on this opportunity, the Southern Forest Experiment Station, on the research side of the Forest

Service, took prompt action to co-locate researchers with the Ouachita National Forest headquarters. Other Southern Station

researchers were assigned to assist this effort from their home units. What had been an arms-length relationship in the past

became a hands-on partnership for the future. The willingness of these two distinct sides of the organization to close ranks

in this manner was undoubtedly the biggest factor in the effort’s immediate success. Success in this case was measured by

the ability to move quickly to demonstrate and evaluate new ways of harvesting timber and sustaining forests of pine and

hardwood. With this narrow role as a starting point, the New Perspectives enthusiasm spread and grew throughout the

Ouachita. In an attempt to capitalize on the opportunity, the districts began developing their own demonstration projects.

Once again, research was available to provide support and assistance.

Two years later, the Ouachita National Forest management had developed a forest-wide old-growth policy, and two

ranger districts were developing their own large-scale old-growth management efforts. These projects emphasized the

importance of old-growth forest conditions to the biological diversity of the forest. Another ranger district focused its

attention on aquatic ecology and has since developed an aquatic learning center, which includes accelerated research,

monitoring, and protection efforts. The learning center also provides environmental education opportunities.

The most unique and comprehensive project includes three ranger districts and encompasses ove r 100,000 acres. This

landscape-scale project is designed to restore the pine-bluestem ecosystem to a portion of its historic range. This area is also

the home of the few remaining colonies of red-cockaded woodpeckers (RCW) in the forest. Because this ecosystem

represents ideal habitat for the RCW, optimism for recovery of the species is high. Several research studies have

accompanied this project in an attempt to characterize this ecosystem in terms of responses by other bird and animal species.

Studies to determine the effects of black rat snake and flying squirrel predation on the woodpecker are currently underway.

This project benefitted from the assistance of research and the willing participation of the public during its formative stages.

Another by-product of the Walk in the Woods was the establishment of a much closer working partnership with the

public. Chief Robertson authorized the designation of a technical advisory committee to work with the Ouachita National

Forest management and research scientists in defining what New Perspectives meant from their own varied backgrounds and

perspectives. Intellectual archetypes, such as the advisory committee, have a potential for eliciting a significant influence

over stalled environmental debate. The Chiefs intent was to take advantage of the collective intellectual consciousness of

this elite group of individuals.

Ecologist Bill Pell was hired to coordinate the New Perspectives program and to serve as a close liaison with the advisory

committee and the research community. For 2 years, the advisory committee met and debated a variety of issues. The first

year was spent developing a generic desired future condition statement for the Ouachita National Forest. The opportunity

to review and comment on Phase II (stand-level research) was also provided. Considerable time was spent discussing the

importance of the social context of resource planning. In 1992, in cooperation with Winrock International, the Ouachita

National Forest,and Southern Forest Experiment Station, a social science workshop was conducted. As a result of this

interest by the advisory committee, considerable attention has been placed on assessing the social context in which the

Ouachita National Forest exists.

DEMONSTRATIONS FOR THE PUBLIC

Due to considerable public interest generated in viewing New Perspectives practices and concepts on the ground,

demonstration projects to showcase these practices classified as Phase I areas were developed. Within a year, hundreds of

people were touring these sites, which proved extremely popular and were effective in demonstrating some of the practices

the districts were employing across the Ouachita National Forest. These sites also served as a prelude to the stand-level

research on alternative management practices (Phase II), which was then in its planning phases. It quickly became apparent

3
that spatial and temporal constraints of implementing this stand-level research would necessitate the need for a third phase

of research at the landscape or watershed scale to better address ecosystem values. This Phase III research will focus on

establishing and evaluating ecosystem functioning for different desired future conditions at the watershed scale over several

decades.

Two years after the advent of the New Perspectives program, then President George Bush announced a further reduction

of clearcutting nationwide and an emergence of ecosystem management as the new approach to the management of all

national forests. The Chief of the Forest Service announced the agency’s move toward Ecosystem Management on June 4,

1992, saying that national forest management would never be the same. Deputy Chief James Overbay followed with a policy

statement that delineated the magnitude and importance of embracing this new concept. It emphasized managing ecosystems

to sustain both their diversity and productivity in a way that is sensitive to social values. The intent was to chart a course

for making this concept the foundation for sound, multiple use, sustained-yield management.

Shortly thereafter, the Ouachita and Ozark-St. Francis National Forest management and the Southern Forest Experiment

Station researchers were awarded the Chiefs Ecosystem Management Award for their ongoing efforts. Perhaps the highest

compliment bestowed came from President Bill Clinton. The President, while participating in the timber summit in Oregon,

complimented the Chief for the leadership shown by the Ouachita National Forest in initiating ecosystem management. He

encouraged the Chief to expand these principles and changes across the entire agency.

CONCLUSION

Thus; we see the genesis of Ecosystem Management as a means to blend the needs of people and environmental values

in such a way that the national forests and grasslands represent diverse, healthy, productive, and sustainable systems. We

don’t have all of the answers, nor is all of the needed research yet in place. However, this shall not prevent us from

adapting to the inevitable change necessary to accommodate the needs of the people we serve. Our credibility as an agency

and as responsible stewards of the land depends on this.
Roles of Science and Research in

Implementing Ecosystem Management on the Ouachita National Forest’

William F. Pell’

ABSTRACT

On the Ouachita National Forest, USDA Forest Service management appears to be “out

in front of research” because management is more adaptive and less “cookbook” than

in the 1970’s and 1980’s, particularly now that ecosystem management is being pursued

aggressively. Science and research play significant roles in Ouachita National Forest

efforts to develop, refine, and implement ecosystem management solutions, notably in

terms of evaluating viable alternative strategies, enhancing understanding of system

structure, function, and dynamics and acknowledging uncertainties. Because those who

seek to apply ecosystem management are faced with a variety of potentially sustainable

alternatives, public participation and the multitude of values and relationships with the

land that people want to sustain are as vitally important to the process as scientific

information.

\ INTRODUCTION

Over the last 3 years, many have said that what Ouachita National Forest management is doing on an operational

basis, at least in terms of silviculture, is “out in front of [the] research.” Some observers have gone a step further and

said that ecosystem management, as currently attempted on the Ouachita National Forest, is “unscientific” or even “bad

forestry. ”

These comments and notions are worth thinking about. They reflect some deeper assumptions about the role of

research and therefore of science in land management. But they also suggest that neither the context nor the need for

ecosystem management research on the Ouachita National Forest have been clearly understood. These deficiencies will

be addressed by answers to the following four questions:

(1)

(2)

(3)

(4)

Is management of the Ouachita “out in front” of research in the sense that managers are implementing practices

before they have been thoroughly studied?

Is the way the Ouachita is currently pursuing ecosystem management “scientific?”

Will research define (or is research defining) what is, and what is not, ecosystem management?

To what extent should--or can--ecosystem management (or any kind of land management) be scientifically

based?

DISCUSSION

The way it is phrased, the answer to the first question is easy: “Yes, of course, the Ouachita is out in front of

research in the sense of implementing management practices before they have been thoroughly studied. ’

The Ouachita National Forest, for example, is implementing treatments such as single-tree selection and modified

shelterwood and seedtree harvests that researchers have only studied in the Ouachita Mountains since 1989. Managers are

using streamside management zones; aiming to retain more downed woody material on land and in streams; retaining snags

and multiple species of mature trees in all stands; protecting seeps and glades; and moving toward old-growth restoration.

None of these modifications or strategies have been thoroughly studied yet.

’ Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

2 Ecologist/Ecosystem Management Coordinator, USDA Forest Service, Ouachita National Forest, Hot Springs, AR,

71902.

5
Twenty or more years ago when clearcutting emerged and then became the predominant harvest method,the situation

may have been similar to the current one. Most foresters today certainly know more about regenerating pines under a

clearcut-and-plant regime than under partial harvesting and natural regeneration. But how long did it take for foresters

to achieve high rates of success at artificial regeneration ? Wasn’t management of the Ouachita “out in front of research”

in another sense until the mid to late 1980’s (Bamett 1992)?

Clearcutting and artificial regeneration can be said to be more “scientific” than partial harvesting and natural

regeneration only because successful tree regeneration is currently more predictable in the former. This is an extremely

limited view of science, though. Certainly knowledge of whole systems was no better under clearcutting than it is today.

The effects of different landscape vegetation patterns on forest interior species, for instance, was scarcely considered, let

alone understood. Just as poorly understood were the social consequences of extensive and highly visible clearcutting.

Part of the reason management now seems even further “out in front of research” is that, although managers and

researchers now have a great deal of knowledge about harvesting, planting, and using trees, knowledge about forest systems

as a whole remains limited. Most forestry research has focused on production and utilization. The biology of

noncommercial organisms, the function and dynamics of ecosystems, and the many human or social dimensions of

ecosystems have received little attention (National Research Council 1990). It is no coincidence that reports as varied as

“Forestry Research: A Mandate for Change” (National Research Council 1990). “the Sustainable Biosphere Initiative”

(Lubchenco and others 1991), and the Society of American Forester’s “Task Force Report on Sustaining Long-term Forest

Health and Productivity” (Society of American Foresters 1993) all call for increased emphasis on understanding ecosystems

and the many roles and values of people in those ecosystems.

Managers of the Ouachita are fortunate to have the Phase II research team and other scientists helping to develop

more /knowledge about Ouachita Mountain ecosystems. From now on, though, whenever someone suggests that

“management is out in front of research,” maybe it should be suggested that this is the way it must be; that land

management, by nature, is “a continual experiment and learning opportunity’“3 backed only partially by good science.

The second question, “Is the way the Ouachita is currently pursuing ecosystem management ‘scientific?, ” has already

been answered at least in part. But take a deeper look at some of the changes taking place in the Ouachita National Forest,

a sampling of which is included in Table 1. Since 1989 the pace of change and adaptation on this national forest has been

remarkable, at least by most standards. Some of that rapid evolution has been fueled by ongoing dialogue with researchers,

and most of the changes made to date have some basis in science. It is clear, on the other hand, that these changes have

not been driven by compelling scientific evidence that change was imperative. The charge that the adoption by the Ouachita

of some or all of these changes has been “unscientific” suggests that management acted without scientific proof that course

corrections would head off or reduce the probability of environmental catastrophe(s). It is true that such scientific proof

is lacking in most cases. It is equally true that waiting for such proof can be the utmost folly. In an adaptive management

framework, it makes far more sense to respond as best possible to persistent, genuine concerns rather than waiting for

disasters to manifest--even if those concerns, including biological diversity, esthetics, water quality, and long-term

productivity, are fed by both scientific and anecdotal observations.

3 Robertson, F.D. 1992. Ecosystem management of the National Forests and Grasslands. Letter from Chief of the

USDA Forest Service to regional foresters and station directors, June 4, 1992. On file with: Office of the Chief, U.S.

Department of Agriculture, Forest Service, Washington, DC.
Table 1. - Ecosystem management: What’s really changing on the Ouachita National Forest?

0 Less emphasis on commodities (though still important) and increasing emphasis on land health:

The beauty, ecological integrity, and native diversity of Ouachita National Forest (ONF) lands

are becoming at least as important as forest products.

Examples: Maintaining forests that look like forests, with greater structural and

species diversity; more hardwoods and older forests.

Partial harvesting substituted for clearcutting throughout the forest.

Scenic byways and other scenic road corridors; wild and scenic rivers;

expanded heritage resources, trails, and interpretive programs.

0 Increasing emphasis on larger scale and more ecologically meaningful units--watersheds,

landscapes, ecoregions--for planning and evaluation.

Examples: Watershed-level project planning on many districts.

Ecological classification system under development for the ONF, Region,

and United States.

Participation in statewide gap analysis programs.

0 Expanded focus on meaningful public participation

Examples: Wilderness steering committees

Ecosystem Management Advisory Committee

Pre-decisional public involvement

0 Concern for maintaining ALL native plants and animals, not just the ones that are harvested;

more hardwoods; more emphasis on stream protection.

Examples: Mature hardwoods retained in all harvested stands

Rare plant inventories and protection

Red-cockaded woodpecker recovery

Aquatic-sensitive species and basin-area surveys; streamside protection

zones

The Ouachita’s response has been that although additional credible information is certainly needed and desired, public

and scientific uncertainty about these issues is sufficient to justify changes before all of the scientific information is in.

It makes more sense ecologically and from an adaptive management stance to designate streamside management zones and

to set standards for dead and downed woody material, snags, and mixed species stands than to wait for exhaustive

knowledge about such variables. Similarly, with the knowledge available now, it appears that partial harvesting should

meet most, if not all, management objectives including less fragmentation of forest interior habitat and more attractive

landscapes. But these are still hypotheses, and it will take years before they can be rejected or accepted on rigorous

scientific terms.

7
Ecosystem management on the Ouachita National Forest is still evolving and, very likely, always will be. It may be

helpful to think of ecosystem management as an iterative flow process, one that requires 1) broad and current knowledge

of the ecosystems of concern, 2) effective, ongoing public involvement and interdisciplinary planning aimed at

understanding existing conditions and making decisions about desired ecosystem conditions, 3) actions to move toward

desired conditions, and 4) periodic monitoring and evaluation of results. Each of these steps or processes is a source of

changing information, needs, and concerns that will contribute to continued evolution.

The third question is “Will research define (or is research defining) what is, and what is not, ecosystem management?”

Most managers and researchers realize that there really is no simple scientific or technical answer to the issue of how the

Ouachita National Forest should be managed. There is no single scientifically correct solution. In terms of ecological

potential, the land can produce many different kinds of communities, and does. In terms of silviculture, there is a broad

range of techniques to choose from, but not one that can meet all needs. Wherever one looks, there are multiple options,

not singlesolutions.

If ecosystem management was confined simply to technical understanding and evaluation of those options, ecosystem

management might indeed be defined solely by science or scientists. But if ecosystem management is viewed as a more

inclusive, framework for integrating ecological, social-cultural, and resource use concerns, both very technical and nontechnical issues and perspectives should be considered. Ecosystem management, in other words, is not another attempt

to provide a technological “fix” for the complex challenges of public land management. Although we must have the best

technical and scientific information available, forest managers also must be attuned to the desires, and have the consent

and support of, a diverse society. Building recognition, credibility, and trust between citizens and public land managers,

in other words, are goals as vital to ecosystem management as promoting ecological integrity and sustainable land use.

The Ecosystem Management Advisory Committee has pointed this out repeatedly.

Scientists, managers, and citizens must work together to achieve these goals. Although scientists play a major role,

they can, at best, contribute to the search for answers, not provide the definitive solutions. Scientific ingenuity is

particularly needed to help address issues, patterns, and processes at large scales over long time periods. Researchers will

increasingly be called on to engage in participatory research and to go beyond traditional agricultural experimental designs.

Research is a prominent part of sound ecosystem management. But is also takes other dynamic components,

interacting with research much like different components of an ecosystem interact, to produce the outcome called ecosystem

management. Some of the other components of ecosystem management include (1) inventory, mapping, and classification,

(2) planning and decision-making, (3) monitoring and evaluation, (4) citizen participation, (5) information management,

and (6) information sharing and interpretation. Citizen participation and partnerships are actually woven throughout

ecosystem management, and cannot be treated as ancillary or separate processes. Extra attention is given to it here, in part,

to recognize the importance of extraordinary efforts to more effectively engage citizens in dialogue and deliberations about

their (public) lands.

The final question is, “To what extent should--or can--ecosystem management be science-based?” Issues such as

biodiversity, long-term productivity, regeneration of pine-hardwood mixes, and cumulative impacts on streams simply must

be addressed with solid data in hand. Social concerns from local economic dependence to public participation in decisionmaking also demand good science.

In an ecosystem-based approach to evaluating management options, science plays a strong role. So too does public

participation and the multitude of values and relationships with the land that people want to sustain. Science and values

must be woven together throughout the process and throughout the kinds of work that will make ecosystem management

a reality.

Scientists have a major role to play, first, in terms of providing citizens and managers with sound information about

ecosystems, including their many cultural and social dimensions, and second, by providing or contributing to formation

of reliable alfe rnntives for ecosystem management (Mrowka 1993, Sesco 1992).

LITERATURE C LTATIONS

Bamett, J.P. 1992. History of shortleaf pine artificial regeneration task force and objectives of the workshop. In:

Proceedings of the Shortleaf Pine Regeneration Workshop; 1991 October 29-3 1; Little Rock, AR. Gen. Tech. Rep.

SO-90. New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station:

Lubchenko, J.; Olson, A.M.; Brubaker, L.B.; (and others). 1991. The sustainable biosphere initiative: an ecological

research agenda. Ecology. 72:#371-412.

8
Mrowka, R. 1993. What is different about ecosystem management? Timber Talk. Washington, DC. 2 p.

National Research Council. 1990. Forestry research: a mandate for change. Washington, DC: National Academy Press.

84 p.

Sesco, J. 1992. The role of research in taking an ecological approach to land and resource management. In: Taking an

ecological approach to management: Proceedings of the National Workshop; April 27-30, 1992; Salt Lake City, UT.

Washington, DC: U.S. Department of Agriculture, Forest Service: 16-22.

Society of American Foresters. 1993. Task force report on sustaining long-term forest health and productivity. Bethesda,

MD: Society of American Foresters. 83 p.

9
Implementing Ecosystem Management Research:

Bringing Researchers, Managers, and Citizens Together’

Timothy J. Mersmann, James B. Baker, James M. Guldin, and William F. Pell’

ABSTRACT

Ecosystem management encourages increased interaction among researchers, managers,

and citizens to resolve national forest issues. Ecosystem Management Research on the

Ouachita and Ozark National Forests has been an early example of such collaboration.

We recount the history of Phase I and II implementation, highlighting

researcher/manager/citizen interactions in accomplishing stand selection, compliance with

the National Environmental Policy Act, sale preparation, harvest, and site preparation.

We also share insights about interactions among these three groups and offer

recommendations to enhance collaboration for ecosystem management.

INTRODUCTION

Two primary themes of ecosystem management are: (1) increasing interactions between researchers and managers and

(2) improving public involvement (Overbay 1992, Robertson 1993). Ecosystem Management Research on the Ouachita and

Ozark National Forests has been one of the earliest and most highly profiled opportunities to bring these two themes together

in an operational program. As such, it is fruitful to examine its implementation and the resulting interactions among

researchers, managers, and citizens. Lessons learned here should be valuable to future efforts because it seems clear that

public land management will be increasingly defined through the shared influence of researchers, managers, and citizens.

It will take bringing together the perspectives and expertise of all three of these groups, in a working network or community,

to successfully and sustainably manage ecosystems for all the diverse uses and values that society demands.

Our objectives here are to: (1) describe the history of Phase I and II implementation, focusing especially on those

elements relevant to relationships among researchers, managers, and citizens, and (2) share our insights on the interactions

among these three groups.

A HISTORY: IMPLEMENTATION OF PHASES 1 AND 11

Phase I

The Ecosystem Management Research Program originated in August, 1990, during “The Walk in the Woods, ” a seminal

field trip on the Guachita National Forest that included Arkansas Senator David Pryor and USDA Forest Service Chief Dale

Robertson. Discussions during this trip resulted in the elimination of clearcutting on the Ouachita National Forest in favor

of alternative methods of reproduction cutting. The Ouachita National Forest was designated as a lead forest for the fledgling

New Perspectives program; the USDA Forest Service Southern Forest Experiment Station was charged with supporting the

Ouachita’s move to alternative silvicultural systems.

To meet this charge, Southern Station scientists met with cooperating scientists from universities and other agencies and

forest managers in October 1990 to begin research planning. Researchers viewed Chief Dale Robertson’s instructions--to

immediately demonstrate alternative silvicultural methods--as too limiting to allow rigorous scientific examination of many

important questions. Sampling bias resulting from use of existing sales was a major concern. Therefore, a three-phase

‘Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains:

Pretreatment Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

2Forester, USDA Forest Service, Ouachita National Forest, Hot Springs, AR 71902; Team Leader, USDA

Forest Service, Southern Forest Experiment Station, Monticello, AR 71656; Research Ecologist, USDA Forest

Service, Southern Forest Experiment Station, Hot Springs, AR 71902; Ecosystem Management Coordinator, USDA

Forest Service, Ouachita National Forest, Hot Springs, AR 71902, respectively.

10
approach was designed: Phase I - to get demonstrations in place as quickly as possible; Phase II - to take a statistically valid

look at effects of alternative silviculture; and, Phase III - to address questions relevant to scales larger than the stand scale.

The Southern Station and the Ouachita National Forest both committed full-time personnel to spearhead research

implementation. The Southern Station placed a full-time scientist in the Forest Supervisor’s office; the Ouachita National

Forest provided a full-time liaison and forestry technician, as well as additional assistance from the Forest’s New Perspectives

coordinator.

Beginning in January 1991, researchers worked with district managers to select 25 stands to serve as Phase I

demonstrations (Guldin and others 1993), representing 8 even-aged and 14 uneven-aged partial cutting methods, plus 3

clearcuts for comparison. Some of these stands had already been harvested, some had been sold and were awaiting harvest,

and some were being prepared for sale. Most had completed the National Environmental Policy Act (NEPA) process.

Stands this close to implementation were chosen intentionally to ensure that demonstrations would be in place quickly. All

stands were identified and harvested by October 1991.

Modification of original prescriptions was necessary in some cases to demonstrate a full range of methods. Negotiations

among researchers, district staff, and timber purchasers made these changes possible. Cooperation was excellent.

Researchers assisted managers in remarking some stands.

Phase I provided an important opportunity for researchers and managers to begin working together in an applied setting.

Disagreements occurred but always resulted in positive and good-natured discussion. Citizen involvement in Phase I

establishment was limited due to use of sales that had already completed the formal involvement processes required by

NEPA. Phase I stands have proven invaluable, however, as a tool for stimulating public involvement and awareness.

Thousands of people from citizens’ organizations, professional societies, other national forests, the Forest Service Regional

and Washington offices, and the USDA Secretary’s office have visited these sites on field trips. Our willingness to discuss

and debate silvicultural decisionmaking--even among ourselves in front of our guests--has earned us credibility and has

stimulated essential dialogue among both external and internal audiences.

Phase II

Stand Selection

Selection of the 52 stands (4 replicates of 13 treatments; Baker, this volume) needed for the more rigorous Phase II study

also began in January 1991. Stand selection turned out to be much more difficult than originally envisioned, primarily

because of constraints set by both researchers and managers. Study plans identified target characteristics for pretreatment

stands including that they be mature, pine-dominated forests, on predominately south or west slopes, of more than 35 acres,

and within subpopulation strips (Guldin and others 1993). In addition, researchers sought to minimize variation in initial

stand conditions by eliminating from consideration areas with a recent history of tire, extensive grazing, abundant advance

regeneration, or noticeably “untypical” forest composition or structure. A blocky shape to minimize edge were also

necessary characteristics for wildlife research.

National forest managers placed constraints on stand selection through Forest Plan standards and guidelines. Such

constraints included limiting adjacency to recent harvests, limiting the percentage of area in regeneration, and restricting

certain harvest methods in visually sensitive zones.

Candidate stands were identified by randomly selecting administrative compartments from within subpopulation strips.

Aerial photos, topographic maps, and stand maps were then used to identify all 40-acre blocks within a compartment that

met selection criteria. District staff with knowledge of the areas were asked to confirm or reject these areas as suitable for

reproduction cutting using any of the methods to be used in the study, including clearcutting. One stand was then selected

at random from those suitable stands within a compartment. Often compartments contained no candidate stands.

The first 15 candidate stands identified in this way within each experimental block (Baker, this volume) then received

an 8 to 10 percent inventory of woody vegetation using l/5-acre fixed-radius plots. These inventories were done by district

personnel using direction provided by researchers. Researchers reviewed inventory results for unusual stand characteristics

and visited each stand for a cursory visual examination before accepting it as a study stand. If a stand was rejected, the next

stand on the candidate list replaced it and an additional alternate stand was selected and inventoried. In this way, 52 stands

and alternates were identified for carrying into the environmental analysis process required by NEPA.

Despite this involved selection process, some stands in the study have characteristics that we may have wished to

exclude: some are much wetter than average, some are much rockier than average, some are more multi-canopied than we

desired, one has a lot of eastern red cedar (Juninerus virginiana L.), one contains a great blue heron (Ardea herodias L.)

rookery. In addition, reports of potentially confounding factors continually arise (e.g., this stand has free roaming cattle,

this stand has motorcycle tracks, this stand has a southern pine beetle infestation, and on and on).

These examples illustrate the difficulty of controlling unwanted variation in experimental units at this operational scale.

Researchers wish to control unwanted variation because fewer replicates are needed to document treatment effects at a given

11
level of confidence. To managers who confront this variety of conditions every day when making management decisions,

the effort to exclude confounding factors has sometimes been seen as a narrowing of the problem space to the extent that

research results may be correspondingly narrow in their applicability.

The NEPA Process

By mid-July 1991, initial stand selections and treatment assignments had been made, and NEPA analysis began. The

initial goal for Phase II implementation was to have harvest treatments completed by September 1992. This placed us on

the extremely ambitious schedule of completing public involvement, cultural resource surveys, biological evaluations,

environmental analysis, document write-up, the 45day appeal period, and sale preparation, advertisement, and awarding

within about 7 months--not to mention collection of pretreatment data. In addition, selected stands continued to change as

analysis proceeded: extensive cultural resources were found in one stand, red-cockaded woodpeckers in another, and public

opposition,scuttled others.

Given this tight schedule, we viewed an administrative appeal of the project decision as a highly undesirable event--one

that would almost certainly eliminate implementation in 1992, putting the entire project in doubt. Our goal for public

involvement therefore, in addition to gathering substantiative input from a wide variety of citizens, was to develop close

relationships with potential appellants, most of whom were members of the Ouachita Watch League. We wanted to ensure

that they had excellent access to the process. We wished !o eliminate surprises--for them and for us. We had great faith

that with enough communication, potential appellants in the environmental community would agree that this project was in

their interest and was an honest response to issues they had championed.

Yet, making this communication was difficult because of the deep chasm of mistrust that existed. Suspicions abounded.

For example, some of these citizens feared the research was a guise for cutting more timber. Some suspected research stands

were sales they had opposed earlier that had been “dumped” by ranger districts into the research project. We were accused

of being timber fixated because of the focus on silviculture. At the same time, many researchers and managers felt these

citizens would torpedo the project for political gain if given an opening, despite what they might say in face-to-face meetings.

We pursued a strategy of pleasantly relentless communication with potential appellants. Letters, phone calls, dinner

meetings, and house visits all played a part. We included them in research planning meetings. We listened and were as

responsive as possible. At least partly as a result of their input, we added unmanaged controls to the study design, eliminated

stands from the Lake Ouachita Management Area, and greatly strengthened research on soil, water, and diversity of plants

and insects. We also became more cognizant of our need to focus on ecosystem description, as well as looking at effects

of management. Researchers and managers alike recognize that the research program is better today as a result of this

interaction with citizens.

Trust and mutual respect grew. Exposure to researchers played a big role in developing this trust and respect. For the

most part, researchers came to be viewed as relatively objective and independent, earnestly interested in good science rather

than defending a particular position. Managers gained credibility in the eyes of these citizens through association with

researchers.

This intensive interaction was but part of the larger, formal public involvement process. Two large mailings were made,

one in August 1991 to approximately 1,800 individuals and organizations and another in November to approximately 250

individuals and organizations. The first gave a broad overview of New Perspectives, including the research program; the

second described the research and proposed stand locations and treatments in detail. We also produced a press release in

December 1991 to reach a wider audience. From all of these efforts, we received responses from 37 people. As with the

frequent appellants, we did our best to ensure that no issue was left unresolved, and that a personal touch was part of each

response.

Before a decision notice was signed, we released a draft of the environmental assessment (EA) to all who had been

involved in the process. This is not usually done for EA’s, but we were determined to ensure that no one would be surprised

by any aspect of the project. We sent out 80 copies and received 9 responses, resulting in some changes even at this late

date.

The New Perspectives Advisory Committee, a group of 13 citizen experts charged with reviewing and advising the

Ouachita National Forest’s move to new management approaches, was also part of the public involvement process. They

reviewed study plans and the EA. Like many other citizens, the), desired to see a broadening of emphasis from silviculture

to other disciplines, particularly the social sciences. Their satisfaction with Phase II grew as its scope broadened. A cultural

resources component was added at their suggestion.

As the planning process proceeded, the tight implementation schedule began to require comer cutting. Opportunities

to collect pretreatment data would be limited, along with opportunities for expanding the scope of research. Timber marking

and sale preparation would be rushed, with limited opportunity for review and adjustments.

On October 2, 1991, at a meeting of researchers aimed at designing interdisciplinary sampling plots, the subject was

broached: could we delay harvest treatments 1 year to summer 1993? Researchers agreed it would improve the quality of

12
the research. Within two weeks, the decision was made to extend pretreatment measurements for a year. Anticipation of

a poor cone crop in 1992 provided additional justification for this change in plans.

This was a critical decision to Phase II. Without it, a pretreatment symposium probably would have been unnecessary.

It also took pressure off of the relationships forming around Phase II, allowing researchers, managers, and citizens the time

to interact effectively.

The Decision Notice for Phase II was signed jointly on April 14, 1992, by Forest Supervisors Mike Curran (Ouachita)

and Lynn Neff (Ozark). No appeals were filed.

Timber Sales

With the NEPA process complete and time available to implement carefully, we moved to sale preparation. Using stand

inventories taken during stand selection, researchers prepared stand-specific marking guidelines, detailing numbers of trees

in each diameter class to be harvested to meet target residual stands.

These guidelines, along with background information, were presented to timber markers and timber managers from 11

districts at a 2-day marking workshop held in Mena, AR, on May 21-22, 1992. The second day was reserved for a field

exercise. The field exercise resulted in considerable discussion and disagreement between seasoned timber markers and

equally seasoned researchers as to which were “cutters” and which were “keepers” under various silvicultural systems.

Researchers carried the day by accepting responsibility for any silvicultural disasters that might result. This opportunity for

interaction, beyond its necessity for research implementation, was extremely educational to both the researchers and managers

involved.

’ After marking Phase II stands, districts submitted actual marking tallies to the Silviculture Group for review, where

comparisons were made with prescribed tallies. On several occasions, districts were asked to modify their marking to more

closely match research prescriptions.

Our goal was to keep sale preparation and harvesting as close to operational as possible while still meeting research

needs. However, it became apparent that in our decentralized agency, the 11 districts varied widely in their implementation.

Differences in extent and layout of streamside zones, and use of different paint colors to designate unit boundaries,

inclusions, temporary road rights-of-way, caused some confusion among researchers and concern about standardization.

Treatment of hardwoods also varied by district. Some districts commonly sold hardwoods for the firewood and

pulpwood markets, whereas others had little market and so rarely, if ever, sold hardwoods. To standardize hardwood

treatment, we required districts to include hardwoods in the sale if volumes exceeded approximately two cunits per acre, in

essence forcing purchasers to harvest trees they normally would not. This is an example of the kind of compromise of

operational implementation that was required to meet researchers’ desires for standardization.

The 48 harvested units were grouped into 24 timber sales. Most sale contracts were prepared and advertised by the end

of September 1992; the remaining followed shortly after. All units were sold by the end of 1992. Total volume sold was

17.2 million board feet at a total revenue of over $2.2 million. Sale volumes, prices, and purchasers are listed in Table 1.

Harvesting began in some stands on May 15, 1993, and was complete in all stands by our target date of September 30,

1993. Sales were administered by districts in the manner used for nonresearch sales. Site preparation began in October 1993

and will proceed through the winter.

NEW RELATIONSHIPS

What have researchers, managers, and citizens learned about each other through the process of implementing Phases

I and II?

We must preface our answer to this question with the recognition that what follows are the perspectives of the authors.

Although we have been closer to Phase I and II implementation than most, many others undoubtably have gained valuable

insights on the interactions among researchers, managers, and citizens through their experience with this project. We would

like to see a more comprehensive assessment of these perspectives conducted through a survey of those involved, so that the

full value of our experience can be shared with others.

Researchers and Managers

In general, bringing researchers and managers together for this project has been a very positive experience for both.

We have learned a great deal about each other and about what had previously been our surprisingly separate professions.

Even those who have prided themselves on being “applied” researchers have learned much about the constraints managers

face. This can’t help but improve the usefulness of the information these researchers will generate.

On the other hand, managers have learned about the constraints necessary to maintain scientific rigor and the limits to

legitimate scientific inference. They have also been exposed to new or at least more accessible sources of expertise. Many

13
Table I .--limber sale volumes and prices for Ph ase II research stands. Ouach ira and O z ark National Foresu, 19 9 2-9 3

Stand Treatment’ Sale

No.

Acres Volume Sol&

Pine Pine Hwd

Saw Pulp Pulp

Price ner unit of volume

Pine Pine Hwd

Saw Pulp Pulp

Purchaser

Caddo 21-l

Caddo 62-8

Caddo 35-41

Caddo 35-42

Kiamichi 218-l 1

Choctaw 62-6

Foutche 428-2

Fourche 443-3

Fourche 456-9

Fourche 457-12

Fourche 458-10

Fourche 458-16

Jessieville 609-9

Kiamichi 231-17

Kiamichi 246-17

Kiamichi 248-6

Magazine 14-18

Magazine 46- 18

Magazine 70- 10

Mena 833-1

Mena 845-6

Mena 895-1

Oden 1036-17

Oden 1044-3

Oden 1067-15

Oden 1073-10

Oden 1077-19

Oden 1084-7

Oden 1094-4

Oden 1097-6

Oden 1106-9

Oden 1119-5N

Oden 1119-5s

Oden 1124-11

Oden 1125-5

PI. Hill 367-04

Poteau 1284- 1

Poteau 1286-19

Poteau 1292-2

Poteau 1314-16

Womble 1646-B

Womble 1654-16

Womble 1658-16

Womble 1658-5

Womble 1648-1

Womble 165 1-6

Womble 16606

Wombfe 1649-13

Totals

PHSWns 1

LlSTSs 1

PSWS 2

PHGSns 2

PHSWs 3

PHGSns 3

PHSTSs 4

PSWS 5

PHSWs 6

PHSWns 6

PSTs 6

CCns 6

PHSTSns 7

LIST% 8

PHSTSns 8

PHSTs 8

PGSns 9

PHGSns 10

PHSTSns IO

PHSWns II

PSTs 12

PSWS 13

PHSTs 14

PSTSs 14

CCns 15

PHSTSs I5

LISTSs 16

PSTs 16

PHSWs 17

PSWS 17

PGSns 17

PHSWns 18

PHSTs 18

PHGSns 18

PSTSs 18

LISTSs 19

PSTSs 20

PGSns 20

CCns 21

PHSTSs 21

PSTs 22

PHSTSs 22

PSTSs 22

CCns 22

PGSns 23

PHSTs 23

PHSWs 23

PHSTSns 24

39 309 165 0

42 82 14 0

35 239 134 0

52 248 76 0

36 160 212 0

70 250 75 0

49 307 50 0

40 205 81 0

41 216 164 0

40 369 108 0

41 373 I50 77

41 496 148 177

41 98 24 0

47 167 31 0

51 101 82 76

37 280 128 42

51 361 45 0

48 185 29 35

46 296 36 0

34 220 88 60

35 368 49 147

33 171 92 69

33 216 268 99

81 289 69 284

32 210 191 64

57 344 99 0

52 139 49 104

33 193 288 66

30 I05 87 0

36 104 230 144

53 282 119 0

36 222 167 72

39 383 195 117

53 270 60 0

43 133 37 0

45 208 0 0

31 155 125 41

37 218 83 0

37 410 169 45

40 244 82 0

40 458 143 140

54 132 18 92

47 138 12 94

39 415 94 76

41 178 62 0

40 369 234 100

35 98 71 112

47 255 70 85

2,060 11,669 5,003 2,418

$192.27 $8.27

$192.27 $8.27

$215.05 $6.53

$215.05 $6.53

$156.10 S7.52

$156.10 $7.52

$191.43 $6.52

$181.00 $5.90

$188.22 $8.98

$188.22 $8.98

$188.22 $8.98

$188.22 $8.98

$158.10 $1.00

$165.27 $5.17

$165.27 $5.17

$165.27 $5.17

$212.13 $13.68

$198.10 $6.80

$198.10 $6.80

$187.11 $1.65

$192.15 $6.00

$165.00 $6.43

$158.10 $6.60

$158.10 $6.60

$172.71 S6.27

$172.71 $6.27

$156.62 $4.43

$156.62 $4.43

$170.00 $4.86

$170.00 $4.86

$170.00 $4.86

$189.15 $9.88

$189.15 $9.88

$189.15 $9.88

$189.15 $9.88

$248.86 NA

$165.15 $5.81

$165.15 $5.81

$178.65 S9.67

$178.65 $9.67

$192.10 S2.95

$192.10 $2.95

$192.10 $2.95

$192.10 $2.95

$197.72 $9.41

$197.72 $9.41

S197.72 $9.41

$204.15 $10.64

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

$1.74

$1.74

NA

NA

$1.51

$1.51

SlY

NA

$0.60

$0.76

$1.05

$1.46

$1.46

$1.80

NA

$1.83

$1.83

NA

$0.60

Sl:?

$1.65

NA

NA

NA

$4.69

NA

f4.72

NA

$0.60

$0.60

$0.60

$0.60

NA

$2.31

$2.31

$4.38

Weyerhaeuser

Weyerhaeuser

Anthony Timberlands

Anthony Timberlands

Travis Lumber

Travis Lumber

Bibler Brothers

Bean Lumber

Weyerhaeuser

Weyerhaeuser

Weyerhaeuser

Weyerhaeuser

Dewey Halsell

K.A. Shug Morris

K.A. Shug Morris

K.A. Shug Morris

Deltic Farm & Timber

Deltic Farm & Timber

Deltic Farm & Timber

Weyerhaeuser

Weyerhaeuser

Bean Lumber

Charles Forga

Charles Forga

Weyerhaueser

Weyerhaueser

Bean Lumber

Bean Lumber

Bean Lumber

Bean Lumber

Bean Lumber

Weyerhaueser

Weyerhaueser

Weyerhaueser

Weyerhaueser

Bibler Brothers

Weyerhaueser

Weyerhaueser

Travis Lumber

Travis Lumber

Weyerhaeuser

Weyerhaeuser

Weyerhaeuser

Weyerhaeuser

Bean Lumber

Bean Lumber

Bean Lumber

Weyerhaeuser

. CC--Clearcut PGS--Pine group selection

PST--Pine seedtree PHGS--Pine/hardwood group selection

PHST--Pine/hardwood seedtree PSTS--Pine single-tree selection

PSW--Pine shelterwood PHSTS--Pine/hardwood single-tree selection

PHSW--Pine/hardwood shelterwood LISTS--Low impact single-tree selection

s--stand will be divided or “split” for comparing methods of vegetation management

ns-stand will not be divided or “split” for comparing methods of vegetation management

+ Pine sawtimber volume in thousands of board feet; pine and hardwood pulpwood volumes in hundreds of cubic feet

14
have spent their time with researchers in a steady flow of questions. For these reasons, the Ecosystem Management Research

Program has been tremendously successful in beginning dialogue between researchers and managers.

Both researchers and managers have also benefitted from sharing costs and labor to accomplish a project of mutual

desire. Through partnership, researchers and managers have engaged issues that increase the relevance and importance of

both to society.

Yet, in addition to these successes, we have also recognized differences that must be addressed. Even the authors still

have some disagreement on the proper roles of researchers and managers in this new relationship. Although we share a focus

on natural resources, researchers and managers are part of two very different professional subcultures.

The researcher’s goal is to produce knowledge through relatively well-defined means--generally referred to as the

“scientific process”-- staunchly maintained through peer review. The goal of the public land manager is to produce goods

and services for citizens, while caring for the land. This is accomplished through a variety of means. Researchers’ results

are usually precisely defined, often with a level of certainty attached. Manager’s results are often ambiguous with unknown

levels,of certainty attached. Researchers try to control many sources of variability in order to isolate factors and causes and

effects. Managers must embrace all sources of variability in order to shepherd entire systems of cause-and-effect

relationships toward desired states.

These differences leave a wide gulf--one that contains important work to be done. Who is going to gather, analyze, and

make useful all of the information available outside the realm of formal scientific experiments, especially that complex,

empirical and experiential information created when management actions are implemented? Who has the time? Who has

the expertise? Who has the incentive?

l$lanagers would like researchers to get in the trenches with them to help them understand the complexities they face

every day. No matter how statistically significant research results turn out to be, unknown levels of uncertainty are present

when these results are carried into actual field situations, complete with all their additional sources of variability. This is

particularly true if those sources of variability were excluded from experimental designs. Managers would like help setting

up monitoring programs, identifying tendencies, and forming best guesses, even though statistical probabilities are unknown

or fall short of traditional significance levels. To a manager, this is important information necessary to supplement formal

published studies. Managers recognize they should be involved in generating this knowledge because they are implementing

the actions and will be primary users of the information. Yet, they are limited by their need to continue producing expected

services, and most do not have the expertise to rigorously design and analyze complex data.

In our experience, researchers generally have not been eager to fill this role. Some are philosophically agreeable, but

hesitate because results from this kind of effort are rarely publishable; others genuinely have no interest in getting this close

to the job of management. This approach to knowledge generation is not given much weight in the peer review process.

Therefore, there are few professional rewards for this kind of involvement. Yet, researchers have an important role to play

here: it is closely allied to their professional charge to produce knowledge, and they have much expertise in extracting

knowledge from data.

Phase II splits some of these differences. It has expanded the realm of traditional replicated research by its scale and

operational nature, both of which have made high levels of variability inevitable. In the final analysis, we will likely get

useful results from both traditional analyses and from case-study descriptions that will be necessary to explain unexpected

outcomes in some stands.

What about Phase II as a model for research/management interaction.9 It has obviously been useful for getting us

together and is suited for addressing big issues such as the Ouachita’s move from clearcutting to other methods. The future,

however, lies in developing a more integrated day-today interaction through which good working hypotheses are generated

and modified--working hypotheses that can guide managers in their decision making and researchers in setting priorities for

directed studies.

Researchers and Citizens

Significant interaction of citizens and researchers has been a relatively new phenomena for both. NEPA analysis has

provided the impetus and the forum for most of these interactions. Researchers generally have been very wary of NEPA.

Not only is it replete with arcane regulations and legal trip wires requiring expertise to navigate, it also subjects their

research plans to public review. It has been difficult for researchers to subject their study plans to public review because

of fears that citizens will not be knowledgeable enough to comment intelligently, but may be politically powerful enough to

force modification of such plans.

The Phase II experience however has resulted quite positively. Researchers have been impressed by the intelligence of

public comments, and modifications made as a result have strengthened the research. In addition, the scrutiny provided by

public review has required researchers to be more precise and definitive in their planning. This too has strengthened the

research, and has helped internal communications. And, contrary to what many believed, it has been possible to generate

acceptable alternatives to original study proposals that meet research objectives and address environmental issues identified

15
through the NEPA process.

The ability and willingness of researchers to be active and skilled participants in public involvement will be increasingly

necessary as we move to an era of large-scale manipulative experiments and adaptive management approaches.

This new relationship between researchers and citizens is causing some researchers to view research as more than just

science--but also as an integral part of policy debate. This is viewed ambivalently. Some feel that science is at risk and can

be easily compromised. On the other hand, program funding, profile, and relevance can be enhanced by the public support

generated through this interaction.

In fact, we may be seeing the rise of an important new user group of research results. There are many in the public

who simply want to know more about the natural systems on their public lands. They are interested in this knowledge for

their own enjoyment and for use as participants in the ongoing dialogue about national forest management.

Managers and Citizens

The relationship between managers and citizens is not a new one, having reached special intensity during recent

development of the Forest Plan. We see evidence that Phases I and II have contributed to improving some elements of this

relationship, particularly between forest managers and our closest watchdogs in the environmental community. These citizens

have expressed general satisfaction with the Phase I demonstrations and have become supporters of Phase II. Their primary

desire is to see more.

In addition to having an excellent project in the Ecosystem Management Research Program--one that is very responsive

to public concerns--this improvement in relationships can also be attributed to the addition of researchers to the mix. Citizens

generally give much more deference to researchers than they do managers. Their credentials as experts are generally better

than managers, and they are usually unsullied by the battles over national forest decision making. They are viewed as

objective. Managers can gain credibility with citizens by their association with researchers, especially if research

independence is maintained. So, while it may be desirable for researchers to join managers in the trenches to some extent,

maintaining independence of voice is critical for the three-way dynamic to survive in healthy dialogue.

Key Points

From our experience, we share the following key points:

(1) Colocation of researchers and managers has been critical. Implementing a program like this, as well as generating much

needed dialogue, cannot be done part-time ove r the phone or at meetings. A full-time liaison, who understands the need s

of both research and management, has also been critical.

(2) Colocation of researchers from multiple disciplines is also needed to encourage interdisciplinary research planning.

Dispersion of key researchers has hindered planning and implementation. Cooperative agreements with local universities

allow use and involvement of local expertise.

(3) Direct contact between researchers and citizens has been positive and should be encouraged. This does, however,

depend somewhat on the personalities available. For these interactions to be productive, researchers must be willing to listen

to citizens without condescension or resentment.

(4) Both interdependence and independence of researchers and managers are critical. Researchers and managers should run

within different but overlapping circles in order to maintain credibility and the diversity of viewpoints necessary for

productive dialogue.

(5) All participants must be forthright but ready to compromise. This is about power sharing. Managers and researchers

must be confident enough to disagree in front of citizens. This openness is essential to stimulating dialogue and trust. There

is no room for prima donnas or hold-outs.

(6) Sustained funding is needed to stimulate a program such as this one. Congressional support has been essential.

(7) Researchers need incentives to move from traditional roles into cooperative ventures such as this one. Funding and

administrative support have been important in our case. Further professional rewards are needed to stimulate widespread

voluntary interest.

16
(8) To progress further, we need nontraditional research protocols especially tailored to scales and processes not suited to

traditional research methods. We need champions to integrate research and monitoring. We need improvement in data and

information management to close the circle of adaptive management.

CONCLUSION

We, as a society, have a lot of work to do to decide how we are going to relate to natural systems, in general, and

national forests, in particular. Much of that work will be done by researchers, managers, and citizens discussing, debating,

and deciding together. So, as we look at our early results--and beyond that as we begin the collection of posttreatment data--

let’s not lose sight of the truly new ground we are breaking by bringing researchers, managers, and citizens together to

resolve national forest management issues. Our research results are necessary and important. But, more information will

not solve our problems. Our ability to work together will.

REFERENCES CITED

Baker, James B. (1994). Stand-level ecosystem management research: an overview. In: Proceedings of the Symposium on

Ecosystem Management Research in the Ouachita Mountains: pretreatment conditions and preliminary findings; 1993,

October 26-27; Hot Springs, AR. Gen. Tech. Rep. New Orleans, LA: U.S. Department of Agriculture, Forest Service,

Southern Forest Experiment Station.

Guldin, J.M.; Shelton, M.G.; Wittwer, R.F. [and others]. 1993. New Perspectives/Ecosystem Management Research on

the Ouachita/Ozark National Forests: silviculture research. Study Plan RWU-4110, FS-SO-4106-81 (Problem 3), U.S.

Department of Agriculture, Forest Service, Southern Forest Experiment Station, Monticello, AR 71656.

Overbay, James C. 1992. Ecosystem management. In: Proceedings of the national workshop on taking an ecological approach

to management; 1992 April 27; Salt Lake City, UT: U.S. Department of Agriculture, Forest Service, WO-WSA-3: 3-15.

Robertson, F.D. 1993. Letter dated June 4 to Regional Foresters and Station Directors. On file with: Ouachita National

Forest, P.O. Box 1270, Hot Springs, AR 71902.

17
An Overview of Stand-Level Ecosystem Management

Research in the OuachMOzark National Forests’

James B. B&err

ABmRACT

A scientifically based, replicated stand-level study (Phase II) was installed in mature,

shortleaf pine (P&s echinatu Mill.)-hardwood stands in the Ouachita and Ozark National

Forests during the summer of 1993. The study is established to test and evaluate a range

of partial cutting methods and vegetation management treatments at an operational scale

but imposed in a scientifically rigorous manner. Thirteen treatments include both evenaged and uneven-aged reproduction cutting methods, with long-term retention of various

densities, compositions, and structures of overstory pines and hardwoods. Two controls,

an unmanaged control and a clearcut control, are also included as part of the 13 treatments. Four levels of vegetation management treatments (site preparation and release)

are also being investigated. The effects of harvesting/vegetation management treatments

will be evaluated in terms of multiple resources and noncommodity values, including:

plant and animal communities, arthropod and microbial communities, soils, water,

cultural resources, scenic quality, recreational opportunities, and harvesting and management costs.

INTRODUCTION

In August 1990, the decision was made by the Southern Region of the USDA Forest Service to discontinue the use of

clearcutting and planting as the primary harvesting and reproduction cutting method in stands traditionally classified as pine

and pine-hardwood types in the Ouachita National Forest. As alternatives to clearcutting, the USDA Forest Service wanted

to use more ecologically sensitive and socially acceptable partial cutting methods that involved long-term retention of a

mixed-species overstory and natural regeneration.

Unlike clearcutting and planting, many of the partial cutting methods-particularly with the long-term retention of a pinehardwood overstory-were untried and untested reproduction cutting methods for the shortleaf pine (Pinus echinatu Mill.)-

hardwood forests growing in the Ouachita Mountains. Thus, several concerns regarding the implementation of these innovative but untested techniques surfaced. Some of them included:

(1) Would the nontraditional partial cutting methods, with the retention of midstory and overstory hardwoods, be

biologically sound; that is, would they regenerate and sustain desired pine-hardwood mixtures?

(2) What combinations of residual pine and hardwood overstory densities would allow for establishment and

development of both pine and hardwood reproduction?

(3) Would partial cutting methods result in stands consisting of pine-hardwood mixtures that represent current species

compositions and stand structures?

(4) How would the partial cutting methods affect important resources such as wildlife populations and habitat,

b&liver&y, visual quality, water, and soil?

(5) How would implementation of the partial cutting methods affect logging and management costs and timber supplies

and values?

’ Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

’ Team leader, USDA Forest Service, Southern Forest Experiment Station, Monticello, AR 71656.

18
To address these and other concerns,researchers and resource managers from the USDA Forest Service Southern Forest

Experiment Station and Guachita and Ozark National Forests, in cooperation with several universities, other State and Federal

agencies and some special interest groups, formulated a three-phase “New Perspectives” (now called Ecosystem Management)

research program. The basis of the overall program was the need and desire to manage National Forest lands using

silvicultural practices consistent with sustainable ecosystem management.

Phase I, an unreplicated stand-level demonstration project implemented in the summer of 1991, provided an early

operational demonstration of some partial cutting methods that retained various densities, compositions, and structures of

pine/hardwood overstories. Phase I has been completed; however, the stands are still being used for demonstration purposes

and for preliminary observation of developing trends and conditions.

Phase II is a scientifically based, replicated stand-level study in which a range of partial cutting methods and vegetation

management treatments are being tested and evaluated at an operational scale but in a scientifically rigorous manner.

Pretreatment evaluations have been completed. Partial cutting treatments were implemented during the summer of 1993,

and site preparation treatments will be conducted during the 1993-94 dormant season.

Phase III, still in the final planning stage, will be a large-scale (watershed or landscape) study that will permit the

evaluation of biological, physical, and social processes, functions, and linkages at various spatial and temporal scales.

In this paper an overview of the Phase II component of the Ecosystem Management Research Program in the Guachita

and Ozark National Forests is provided. The objectives of this stand-level (Phase II) study are to evaluate:

(1) The biologic and economic feasibility of using partial cutting methods and long-term retention of pine-hardwood

overstories to establish and maintain mixed pine-hardwood stands that reflect indigenous vegetation and historical

stand structure on south-facing slopes of the Guachita Mountains.

(2) The effects and trade-offs of the partial cutting methods on various commodity and noncommodity resources and

values.

STUDY AREA

Geology and Soils

The Chtachita Mountains consist of a series of east-west ridges and structural valleys. Narrow-topped mountains with

steep side slopes alternate with rolling to gently sloping valleys. Elevations range from about 500 to 2,800 feet above sea

level. Parent materials in the area, primarily of sedimentary origin, range in age from the Ordovician to Pemrsylvanian

periods and consist of cherts, shales, slates, sandstones, and novaculites. All geologic materials have been intricately folded

and faulted, and at many places they dip at angles of 40“ or more from the horizontal. Because of the inclined and fractured

nature of the patent material, tree roots can often pexretrate to considerable depths, although the soils are generally shallow

(Graney 1992).

Soils common to ridges and upper slopes are shallow (Clibit and Bismark series) with a site index for shortleaf pine

ranging from about 40 to 70 feet at 50 years. Soils on middle to lower slopes are deeper and are derived from shales

(Camasaw and Bengal series) or sandstone (Sherwood, Pirum, and Zafra series). These soils have a site index for shortleaf

pine ranging from about 50 to 80 feet at 50 years (Graney 1992).

Climate

The climate in the Guachitas is characterized by warm and humid summers and mild winters (Skiles 1981). Mean annual

temperature ranges from about 57 “F in the northern portion of the Guachitas to about 61 “F in the southern extremities (fig.

1). Mean annual precipitation ranges from about 44 inches in the northern and western extremities of the Guachitas to about

54 inches in the eastern and southern portions of the region. Both mean ammal temperature and precipitation generally

decrease from the eastern and southern portions to the western and northern portions of the Guachitas.

Ecorkgions

The Guachita Mountains are commonly divided into two ecoregions-the Arkansas River Valley Ecoregion and the

Ouachita Mountain Ecoregion (Giese and others 1987). The Arkansas River Valley Ecoregion lies between the Boston

Mountains to the north and the Guachita Mountains to the south. It is a transitional area between these two uniquely different

landforms. The Arkansas River Valley Ecoregion has slowly to moderately permeable soils underlain by folded shales and

sandstones. General topography is rolling, but mountains and mesas are also present.

19
a

E

0 44’

I

4

Y 44’

0 52’

54’

54’

MEAN ANNUAL PRECIPITATION On*W

-- -MEAN ANNUAL TEMPERATURE (s)

Figure 1. -Phase II study area shown in bCJX With Statewide climatic gradients.

/ I

/

/

/

/
Since ecoregions are generally defmed as areas having homogeneous land surface forms, potential natural vegetation,

soil types, and land uses, the Ouachita Mountain Ecoregion has been subdivided into upper and lower sub-ecoregions

(Clingenpeel and Co&ran 1992)(fig. 2). A distinguishing feature between the sub-ecoregions is that streams in the Lower

Ouachita Mountain Sub-Ecoregion tend to be perennial, whereas those in the Upper Ouachita Mountain Sub-Ecoregion tend

to be ephemeral (USDA FS 1990).

For purposes of this study, the Upper Ouachita Mountain Sub-Ecoregion was divided into eastern and western

components, corresponding primarily to mean annual temperature and precipitation gradients. Thus, the following four

ecoregions and sub-ecoregions were recognized as having the most similar land forms, vegetation types, and climatic

conditions: the Akansas River Valley Ecoregion [N], the Lower Ouachita Mountain Sub-Ecoregion [S], the eastern Upper

Ouachita Mountain Sub-Ecoregion [El, and the western Upper Ouachita Mountain Sub-Ecoregion w(fig. 2).

METHODS

Treatments evaluated in this study include an array of reproduction cutting methods and associated vegetation

management techniques. The reproduction cutting methods were imposed in forty-eight 35 to 40-acre stands. Four

additional stands (controls) will receive no harvest cutting. Vegetation management treatments (site preparation and/or

release techniques) will be imposed on lo-acre subplots within 24 of the 48 stands that are harvested. A subset of 28 of the

stands (including 24 of the harvested stands plus the 4 unmanaged controls) will not be subdivided; thus, they will permit

ev‘aluation of interior forest species (particularly some migrant and resident birds) that require a minimum of 40 acres of

similar stand conditions.

Reproduction Cutting Methods

The reproduction cutting methods include various nontraditional (untried and untested) partial cutting techniques that

retain both pines and hardwoods in various densities, compositions, and structures. Some cutting methods will establish new

stands having even-aged structure; others will develop and maintain stands having uneven-aged structure. Harvesting to

implement the reproduction cutting methods began in May 1993 and was completed in September 1993. Trees left after the

reproduction cut will be retained on the site indefinitely.

Uneven-aged Methods.--The following partial cutting methods, listed in increasing order of harvesting intensity and/or

site disturbance, were imposed to develop and maintain uneven-aged pine-hardwood stands:

(1)

(2)

(3)

(4)

(5)

Low-impact, pine/hardwood single-tree selection (IA-STS, not split)-Some pines and hardwoods are harvested on

a lo-year cutting cycle using single-tree selection. Residual basal areas of pines and hardwoods range from 60 to 80

fi%cre, with up to 50 ft2/acre being in hardwoods. Understory woody vegetation will be controlled by manual

techniques only when needed to maintain development of pine and hardwood reproduction. No herbicides will be used.

Pine/hardwood single-tree selection (PH-STS, not split)-Some pines and hardwoods are harvested on a lo-year

cutting cycle using single-tree selection. Residual basal areas range from 45 to 65 ft%cre, with 5 to 20 f&acre being

in hardwoods. Site preparation and release from woody competition will use manual techniques as needed and will be

applied uniformly over the site.

Pine/hardwood single-tree selection (PH-STS, split)-The same as (2) except that the harvested area was subdivided

(split) to allow comparison of various combinations of site preparation and release treatments (see Vegetation

Management section that follows).

Pine single-tree selection (P-STS, split)-Some pinea are harvested on a lo-year cutting cycle using single-tree

selection. Residual basal areas in pines are 45 to 65 fflacre. All hardwoods were harvested or removed except those

needed to meet den-tree and mast-production standards for wildlife (2 to 5 @/acre). The harvested area was subdivided

to allow comparison of various combinations of site preparation and release treatments (see Vegetation Management

section that follows).

Pine/hardwood group selection (PH-GS, not split)-All pines and some hardwoods were harvested or removed in

group openings ranging from about 0.1 to 1.0 acres (representing from one to three times the height of adjacent trees).

Residual basal areas of hardwoods within group openings are 5 to 10 f&acre. Pines outside group openings were

21
iiQa8F9

;!z3

:;:y:= y::::::::: 0

$$$g;

::::::::::::

::::::::::::

:*,

Iii Wfa85zY30‘...‘

.

.::. ‘,‘.._ 0

:.:.:.

:::

:::

22
thinned to a basal area of 70 to 80 ft*/acre. No hardwoods were harvested or removed outside group openings. Site

preparation and release from woody competition will be done within group openings only, using manual techniques as

needed.

(6) Fine group seledion (P-GS, not split)-The same as (5) except that no hardwoods were left within group openings.

Even-aged Metho&.-The following partial cutting methods, listed in increasing order of harvesting intensity and/or site

disturbance, were imposed to establish and maintain even-aged pine-hardwood stands:

(1) Pine/hardwuod shelterwood (PI-I-SW, not split)-A total of 20 to 40 of the largest pines and hardwoods per acre (30

to 40 ff/acre of basal area of which 5 to 15 ft%cre are in hardwoods) were retained; all other pines and hardwoods

were harvested or removed. Site preparation and release from woody competition will be applied uniformly over the

site as 8 manual treatment if needed.

(2) Pine/hardwood shelterwoud (PEGSW, split)-The same as (1) except that the harvested area was subdivided (split) to

allow comparison of various combinations of site preparation and release treatments (see Vegetation Management

section that follows).

(3) Fine shelterwoud (P-SW, split)-A total of 20 to 40 of the largest pines per acre (30 to 40 f&acre of basal area) were

&tained; all other pines and hardwoods were harvested or removed except those needed to meet den-tree and mast-

’ production requirements (2 to 5 f&acre of hardwoods). The harvested area was subdivided to allow comparison of

various combinations of site preparation and release treatments (see Vegetation Management section that follows).

(4) Pine/hardwood seed-tree (PI-I-ST, split)-A total of 10 to 15 of the largest pines and hardwoods per acre (10 to 20

ft%cre of basal area of which 5 to 15 ft’/acre are in hardwoods) were retained; all other pines and hardwoods were

harvested or removed. The harvested area was subdivided to allow comparison of various combinations of site

preparation and release treatments (see Vegetation Management section that follows).

(5) Pine seed-tree (P-ST, split)-A total of 10 to 15 of the largest pines per acre (10 to 20 ff/acre of basal area) were

retained; all other pines and hardwoods were harvested or removed except those needed to meet den-tree and msstproduction requirements (2 to 5 ft%cre of hardwoods).

The retained trees for all shelterwood and seed-tree cutting methods will be left a minimum of 10 years or indefinitely if

reproduction develops at an acceptable rate (at least 6 inches of annual height growth) (Chapman 1945).

ControLs.-The control treatments include: (1) an unmanaged stand condition in which the existing stand is not subject

to reproduction cutting; and (2) a clearcut and plant treatment. The unmanaged control will anchor one end of a continuum

in that it represents minimum human-induced disturbance. The clearcut control will anchor the other extreme as the most

intensive, and possibly the most site disturbing, of the reproduction cutting methods. The following is a description of these

two treatments:

(1) Unmanaged control (UC, not split)-No harvesting will be done. No other stand management will be done except to

provide protection from severe loss to wildfire or insects.

(2) Clearcut control (CC, not split)-All pines and hardwoods were harvested or removed except 2 to 5 ftz of basal area

per acre of hardwoods retained as den trees and mast producers. Site preparation will be done by injecting all ttees that

were not harvested or not planned for retention with Garlon@ 3A at rates not to exceed 1 .O lb/acre of active ingredient.

The site will be mechanically ripped on lo-foot centers to a depth of 6 to 8 inches, and genetically improved shortleaf

pine seedlings will be hand planted at 8-foot intervals within the rips. Release from woody competition, if needed, will

be done using spot treatment of selected stems with Garlon@ 4E applied manually from backpack sprayers at ra@ not

to exceed 1.0 lb/acre of active ingredient.

23
Vegetation Management

Site preparation and release treatments to be tested and evaluated in the subdivided (split) stands include:

(1) No site pmparation, no release.

(2) No site preparation, mamral or herbicide release.

(3) Manual site preparation, manual or herbicide release.

(4) Herbicide site preparation, manual or herbicide release.

Manual site prepamtion will involve chainsaw felling all unwanted stems 2 inches in d.b.h. and larger. Herbicide site

preparation will be done by either injecting or chain saw felling and stump treating unwanted stems 2 inches in d.b.h. and

larger with G&on 3A at rates not to exceed 1.0 lb/acre of active ingredient. These treatments will be implemented during

the 1993-94 dormant season.

A need for release will be assessed of&r two growing seasons following the establishment of pine reproduction. Where

manual release is needed, it will be done using chain saws or power brush saws. Where herbicide release is needed, it will

be done using injection or cut stump spraying of Garlon 3A and/or directed foliar spray of Garlon 4E at rates not to exceed

1.0 lb/acre of active ingredient using backpack sprayers. only stems adversely affecting development of desired pines and

hardwoods will be treated.

The regeneration objective for the even-aged systems is to have 300 pine and 300 hardwood seedlings and saplings per

acre that are free-to-grow 3 to 5 years after the regeneration harvest. For the uneven-aged systems, the objective is to have

100 pine and 100 hardwood seedlings and saplings per acre that are free-to-grow 3 to 5 years after the harvest.

Expe rim e ntal Design

The 13 harvesting treatments (11 partial cutting methods plus an unmanaged control and a clearcut control) were

replicated 4 times in a random&d complete block design. Thus, a total of 52 stands are being used in the study (13 stands

in each of 4 blocks). Blocks correspond to the four ecoregions and sub-ecoregions described earlier.

A subset of 28 stands (4 replications of 7 of the treatments-LISTS, PH-STS, PH-GS, PGS, PH-SW, UC, CC) will

be treated in a similar manner regarding the harvest cutting, site preparation, and release treatments. The homogeneous

conditions of these stands are needed for some monitoring and evaluation activities, particularly migrant and resident birds.

Another subset of 24 stands (4 replications of 6 of the treatments-PH-STS, P-STS, PH-SW, P-SW, PH-ST, P-ST) will

be subdivided into 4 almost equal lo-acre compartments used to test and compare the site preparation and release treatments.

For this subset of tmatments and stands, a split-plot randomized complete block design will be used. Statistical analyses that

are appropriate for these experimental designs include analysis of variance at the stand level and regression analysis at the

plot level.

Stand Selection and Randomization

The target population for the study included all mixed shortleaf pine-hardwood stands in the Guachita and Oxark National

Forests that were candidates for reproduction cutting and met the following criteria:

1. Tree age: 70+ years.

2. Stand area: >35 acres.

3. Aspect: south- or west-facing.

4. Pine basal area: 60 to 110 ft%cre.

5. Hardwood basal area: 20 to 50 ft2/acre.

To optimize operational logistics in conducting research measurements, a representative subpopulation of candidate stands

was randomly selected from the target population. The subpopulation was selected from four randomly located strips, each

a township (6 miles) wide. Two of the strips were oriented nor&-south, and two were oriented east-west (fig. 3). These

strips were randomly selected from contiguous four-township-wide swathsrunning north-south and east-west that included:

(1) the four ecoregions and sub-ecoregions identified in the Guachita Mountains; and (2) most of the main population of

candidate stands. Thirteen stands were then randomly selected from the candidate stands occurring in each of the four blocks

(fig. 3), and treatments were randomly assigned to the stands.

24
Arkansas River

El ::;:j:;:;:;:; OZARK NATIONAL FOREST l PHASE II STANDS

I

~~~~ OUACHITA NATIONAL FOREST ::::::::::::.:::.:.:.:.:.:

Figure 3. -Phase II study area illustrating stand location within township-wide corridors and blocks.
Sampling Scheme-Permanent and Temporary Plots

A typical 35 to 40-acre stand is illustrated in figure 4A. Stands usually include one or more ephemeral streams

surrounded by a streamside protection xone in which there will be no harvesting and no vegetation management.

Stands were stratified into lower, middle, and upper slope positions (fig. 4A). Soil moisture and productivity generally

decrease from the lower to the upper slope position. Also, plant species composition generally changes along this elevation

gradient. Some stands were also subdivided into quarters of approximately equal areas, arranged perpendicular to the

elevation gradient as described earlier (fig. 4A).

A series of both permanent and temporary sample plots and transects were established in the stands to evaluate preharvest

conditions and to monitor changes after treatment. An example of the typical layout is shown in figure 4B for the stands

that are being used by all research groups. Some plots and transects were randomly located within the stand, whereas others

were located systematically. Some sample plots were installed in a nested sample design in which several research groups

collect and share data, other sample plots were established for specific monitoring activities.

Research Groups and Monitoring Activities

The research team is organ&d around six disciplines and seven research groups. The disciplines and research groups

associated with the Phase II research program and their monitoring and evaluation activities are as follows:

l’lanl Communities.-Includes 16 team members from the Silviculture, Plant Diversity, and Wildlife Research Groups.

1. Seed production

2. Seedbed conditions

3. Pine/hardwood regeneration and development

4. Overstory stand development

5. Vegetation management (competition control)

6. Plant diversity

W ildlife Communities.-Includes seven team members from the Wildlife Research Group.

1. smal1mammals

2. Flying squirrels

3. Neotropical migratory and resident birds

4. General habitat conditions

Arth ropod and Microbial Com m unities.-Includes nine teun members from the Arthropod and Microbial Research

1.

2.

3.

4.

Group.

Arthropods

Cone and seed insects

Southern pine beetle hazard ratings

Crown health of overstory hardwoods

W ate r, Soils, and Cdtum l Resources.-Includes 10 team members from the Water Quality, Soils, and Cultural

1.

2.

3.

4.

5.

6.

7.

Resources Research Group.

Water chemistry of ephemeral streams

Herbicide movement in stream water

Stream channel morphology of ephemeral streams

Woody debris in ephemeral streams

Soil disturbance associated with logging

Nutrient cycling

Impacts of harvesting activities on cultural resources

26
Plots and Transects

@ Silviculture, plant diversity, wildlife :;..>::::... :. . . .

:.q. Wildlffe, plant dlverslty

GJ Birds, visual quality

:p.:w, $A.,.:~$ .<.+ ..: $+ Cultural resources

0 Soils, nutrient cycling ~1Stream mor,phology,

Soil disturbance from harvesting

water chemistry A

Figure 4. - A typical 35 to 4O -ucre stand @A) stratifie d by slope osition and subdivide d

into q uarte rs , and (8) illustrate s the num be r and d& dk ution of pe rm ane nt and

te m porary sam ple plots e nd transe cts .

27
Scenic Qual@.-Includes six team members from the Visual Quality/Recreation Research Group.

1. Visual impacts of recently cut stands

2. Customers survey of scenic preferences

3. Effects of hardwood retention, season, and physiography on perceived scenic beauty

4. Contingent valuntion and acceptance of alternative harvest regimes

H arvesting and Management Economics.- Includes six team members from the Harvesting and Management Economics

Research Group.

1. Harvesting economics

2. Management costs associated with various reproduction cutting methods

3. People and natural resource relationships

LITERATURE CITATIONS

Chapman, H.H. 1945. The effect of overhead shade on the survival of loblolly pine seedlings. Ecology. 26: 274-282.

Clingenpeel, J. Allen; Co&ran, Betty G. 1992. Using physical, chemical and biological indicators to assess water

quality on the Ouachita National Forest utilizing basin area stream survey methods. In: Proceedings Arkansas Academy

of Science. 45: 33-35.

Giese, J.; Keith, B.; Maner, M. [and others]. 1987. Physical, chemical, and biological characteristics of leastdisturbed

reference streams in Arkansas’ ecotegions: Data analysis. Little Rock, AR: State of Arkansas, Department of Pollution

Control and Ecology. 148 p. Vol. 2.

Graney, David L. 1992. Site index relationships for shortleaf pine. In: Brissette, John C.; Bamett, James P., camp.

Proceedings of the shortleaf pine regeneration workshop; 1991 October 29-31; Little Rock, AR. Gen. Tech. Rep. SO-90.

New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station: 142-157.

Skiles, Albert. 1981. Arkansas climate atlas. Little Rock, AR: Arkansas Energy Office; Arkansas Industrial Development

Commission. 93 p.

U.S. Department of Agriculture, Forest Service. 1990. Amended land and resource management plan-Ouachita

National Forest. Hot Springs, AR: U.S. Department of Agriculture, Forest Service, Southern Region: Vol. 1.

28
Midstory and Overstory Plants in Mature Pine/Hardwood Stands

of the Ouachita/Ozark National Forests’

James M. Guldin, James B. Baker, and Michael G. Shelton’* 3

ABSTRACT

The Phase II silviculture research was established using 728 plots, 14 in each of the

52 stands in the study. Twelve of the fourteen plots were located within the area of

the stand where reproduction cutting will occur; two were placed within ephemeral

stream protection zones. Each plot contains four nested subplots monitored by the

silviculture research group (overstory and midstory) and the understory plant research

group (shrubs and ground cover). The average stand in the study has a south-facing

aspect of 180.3”, occupies midslope position on an 11 percent slope, and has 91

percent cover. The mean site index of the average stand is 62.2 ft (base 50), derived

from mean tree height of 70.4 ft and mean tree age of 64.5 years. The average

stand has 323.2 trees per acre and a basal area of 129.5 ft’/acre (trees 3.6 inches in

d.b.h. and larger). Conifers, primarily shortleaf pine (Pinw ech inatu Mill.),

comprise 51.1 percent of the trees and 73.5 percent of the basal area. Conifer

importance values exceed 50 percent from the 7- to g-inch size class through the 22-

to 24-inch size class, reaching a maximum of 90 percent in the 13- to 15-inch size

class. The importance value of hardwoods exceeds that of conifers in the 4- to 6-

inch size class and in the 25- to 28-inch and >28-inch diameter classes. Tests for

differences in means by block and future treatment reveal significant though

ecologically marginal differences for nearly all variables. These differences reflect

a high degree of variability among plots, an attribute that will be useful in subsequent

analyses.

INTRODUCTION

The goal of ecosystem management research in the Ouachita Mountains is to provide scientific support for implementing

a new philosophy of sustainable ecosystem management on Federal lands. In this Phase II research program, silviculture

is the common element that unites several different research groups, to broaden the collective understanding of alternative

reproduction cutting methods and their multiple resource characteristics, implications, and effects. Silviculture has

traditionally been viewed as a timber management activity. But in this research project, it assumes a more holistic role-as

the fundamental means to affect the biotic influence of diverse vegetation components in order to promote the desired future

condition of individual stands.

In this study, the silviculture research objectives are driven by the desire for mixed pine-hardwood regeneration and

retention. There is not enough information on mixed-species regeneration ecology and developmental dynamics to be able

to manage mixed pine-hardwood stands effectively in either even-aged or uneven-aged stands (Cooper 1989, Farrar and

others 1989). The Phase II study design (Baker, this volume) provides an opportunity to quantify the effects of a mixedspecies overstory on regeneration, understory vegetation, and overstory growth and yield. A key element of this is how site

preparation and release can be modified to be less intensive yet successful in establishing pine and hardwood regeneration.

Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

Research forest ecologist and Silviculture Group Leader, USDA Forest Service, Southern Forest Experiment Station, Hot

Springs, AR 71902; Principal Silviculturist and Team Leader, USDA Forest Service, Southern Forest Experiment Station,

Monticello, AR 71656; Silviculturist, USDA Forest Service, Southern Forest Experiment Station, Monticello, AR 71656,

respectively.

The authors would like to acknowledge the efforts of the field crews-Leif Anderson, Doyle Cain, Gary Sanchez, Linda

Smith, Saul Sema, Lisa Washington, Tommy Norton, and Chris Pope-in conducting the fieldwork for this research.

29
The goal of the silviculture research group is to provide on-the-ground research support, monitoring, and evaluation of

traditional and nontraditional reproduction cuttiqg methods. The term “traditional” refers to partial cutting methods (seedtree, shelterwood, group selection, and single-tree selection) in which the residual overstory is composed primarily of

shortleaf pine (Pinus echinata Mill.) and in which intensive competition control measures are applied. The term

“nontraditional” refers to modifications of the partial cutting methods (seed-tree, shelterwood, group selection, and single-tree

selection) in which both pines and hardwoods are retained in the residual overstory. Despite these traditional and

nontraditional labels, the research support for these partial cutting methods, applied to shortleaf pine in the Interior

Highlands, is virtually nonexistent.

The management and research questions that guide the silvicultural component of this research have been summariz.ed

as follows4:

(1) Can nontraditional pine-hardwood reproduction cutting methods successfully regenerate pine-hardwood mixtures?

(2) What combination of pine and hardwood residual basal areas allows for establishment and development of pine

and hardwood seedlings and advancti regeneration?

(3) Will the natural regeneration systems result in mixed pine/hardwood stands that reflect current species

compositions and stand structures?

These translate into a specific study objective for the silviculture research group-to quantify the establishment and

development of seedlings and sprouts of both pines and hardwoods under an array of reproduction cutting methods, site

preparation treatments, and release treatments.

Included in the silviculture research are several studies whose pretreatment status is not summarized in this paper. A

study of seed production will monitor seedfall through several years after reproduction cutting; a subset of this study will

investigate differences in genetic diversity in several Phase II stands. ’ Post-treatment analyses of the site preparation and

release elements of the study will be conducted within a split-plot framework to assess low-impact methods of site preparation

and release:, 7 Ecophysiological measurements to quantify stand microclimatology will also be taken through several early

posttreatment growing seasons.*

METHODS

Stand selection and treatment assignment

Methods for stand selection have been described in detail elsewhere’ (Baker, this volume). The end result of the process

was the inclusion of 52 stands in the study, 13 in each of 4 ecoregional blocks (north, south, east, and west, related to

geological substrate). Treatments were assigned randomly to the stands’ (Baker, this volume) (table 1).

Baker, James B. 1991. Study plan: New perspectives research on the Ouachita/Ozark National Forests. Study Plan

FS-SO-410681 (Problem 3). On file, Southern Forest Experiment Station, USDA Forest Service, Monticello, AR.

71656.

This research is being coordinated by Dr. Robert Wittwer, Department of Forestry, Oklahoma State University,

Stillwater, OK 74078.

Assistance in this component of the study will be provided by Dr. Jim Miller, Principal silviculturist, USDA Forest

Service, Southern Forest Experiment Station, Auburn, AL 36849.

Guldin, James M.; and others. 1993. New perspectives / ecosystem management research on the Ouachita/Ozark

National Forests: Phase II-Silviculture research. Study plan RWU-4110, FS-SO-4106-81 (Problem 3), Southern Forest

Experiment Station, USDA Forest Service, Monticello, AR.

This component of the study will occur with the cooperation of Dr. Jim Bamett, Principal ecophysiologist, USDA Forest

Service, Southern Forest Experiment Station, Pineville, LA 71360.

30
Table 1. - Traditional at&non-traditional reproduction cutting methoak assigned as Phase Iltreatments, with corresponding

posttreatment residual basal area targets. The designation “split” indicates the stand will be included in the

split-plot site preparation and release study; the designation “not split n indicates the stand will not be included

in the split-plot study

_______ _______.____ Reproductioncutting meho& ______ _____________ ---- Residual basal area per acre ---

Treatments Code shortleaf pine hardwoods

I. Controls

Unmanaged control, not split

Clearcutting, not split

II. Even-aged methods

Seed-tree, pine, split

Seed-tree, pine-hardwood, split

Shelterwood, pine, split

Shelterwood, pine-hardwood, not split

Shelterwood, pine-hardwood, split

III Uneven-aged methods

Group selection, pine, not split *

Group selection, pine-hardwood, not split t

Single-tree selection, pine only, split

Single-tree selection, pine-hardwood, not split

Single-tree selection, pine-hardwood, split

Single-tree selection, low impact, split

UC

CCNS

same as

pretreatment

0

STP

STPH

SWP

SWW

SWPH

20

IO

40

30

30

GSP 50

GSPH 50

STSP 60

STSW 50

STSH 50

STSL 60

ft’lac

same a*

pretreatment

O-5

O-5

IO

O-5

IO

IO

IO

IO

O-5

10

10

IO

*No trees retained in groups; pines and hardwoods retained between groups.

THardwoods retained within groups; pines and hardwoods retained between groups.

Study plot installation

Within any given stand, plot locations were influenced by plans to quarter the stands for the split-plot study, which

dictated that a subset of plots must fall within each quarter of each stand. Since three plots generate the minimum number

from which statistical inferences may be collectively drawn, three plots were placed in each quarter of the stand. In order

to standardize plot installation across all 52 stands, each stand was so quartered.

On a stand map, each stand was subdivided into quarters of approximately equal area, arranged perpendicular to the

elevation gradient. Each quarter of the stand was then subdivided into thirds along the elevation gradient. One study plot

was then randomly located within each 1/12th of the stand, with the provision that no plot center was placed within 75 fi

of the border of the stand or any included streamside zones. Plot centers were established by compass and pacing with

azimuth and distance scaled from the stand map.

The silviculture research group and understory plant research group cooperated in establishing the pattern for nested

subplots. Four layers of vegetation were sampled. The overstory layer and midstory layer were measured by the silviculture

research group, and the shrub layer and ground cover layer were measured by the understory plant research group.

Successively lower layers were sampled with subplots of decreasing size (table 2). The subplot installation was arranged

such that the sample plot for each successively lower vegetation layer was nested within the subplot used to sample the nexthigher layer (fig. 1).

Overstory woody species (9.6 inches in diameter at breast height (d.b.h.) and larger) were sampled by species and 0. linch d.b.h. units using variable-radius plots established with a basal area factor (BAF) 5 f&acre prism. This sample scheme

was selected rather than 0.2-acre fixed-radius plots because field trials demonstrated that large trees just beyond the 0.2-acre

plot radius exert an ecological influence on plants near plot center, whereas small overstory trees near the outer perimeter

of the 0.2-acre plot do not. When using a prism with BAF 5, a tree 20 inches in d.b.h. has a horizontal limiting distance

of 77.78 ft-which is approximately equal to the height of the tree and represents the marginal degree of overstory influence

on subplot ecology (Pickett and White 1985).

31
Table 2.- Nested subplot elements, dimensions, and vegetation to be sampled in each element by type, size, and research

group responsible

Plot size

0.001 acre

Plot dimension8

Square

6.6 tt by 6.6 A

Number Vegetation sampled Vegetation

of plots (research group) dimensions

4 Herbaceous plants (understory all nonwoody

plant)

Woody vegetation all woody stems

(silviculture) ht<4.5 ft, d.b.h.iO.5 inches

0.001 acre Circular

3.72 fi radius

Woody vegetation all woody sterna

(silviculture) ht ( 4.5 A, d.b.h. i 0.5 inches

0.004 acre Square

13.2 A by 13.2 tt

Woody and nonwoody

understory

(understory plant)

all woody stems

0.6 inches i d.b.h. i 3.5 inches

‘0.1 acre

Variable

Circular

37.24 ft radius

Variable radiur

BAP 5.0 ft’lacre

1 Woody midstory all woody stems

(silviculture) 3.6 incher I d.b.h. i 9.5 inches

1 Woody overatory all woody stema

(silvicultufe) d.b.h. L 9.6 inches

,.----.,

/ \

/ \

/ \

/

I’I

I

I

I

\

\

\

\

\

\

/

\

/

‘.

--_--

/’

Figure l.- Overview of nested subplot sample plot configuration. The dashed lines represent the BAF Sftz/acre variable

radius plot, for overstory sampling. The large circle (solid line) represents the 0. l-acre fued radius plot, for

midstory sampling. The two rectangles (solid line) represent the shrub layer sample plots; each rectangle

consists of two 0.004-acre square subplots. The four small squares and two small circles (solid line) within the

large circle represent square and circular milacres, respectively. Plot dimensions are listed in Table 2.

32
Midstory trees (3.6 inches in d.b.h. to 9.5 inches in d.b.h., inclusive) were tallied by l-inch classes and species using

a 0. l-acre fixed-radius (37.24 ft) subplot. A plot of this size captures the ecologically significant elements of the midstory

that affect plants near plot center. In addition, with a prism of BAF 5, the limiting distance to sample a 9.6 inch tree is

37.33 ft, whereas that to sample a 9.5 inch tree is 36.94 ft. This clean break in subsampling enhanced the sample design-all

overstory trees 9.6 inches in d.b.h. and larger within the 0. l-acre midstory plot radius will be “in” the prism sample of the

overstory, and no midstory trees 9.5 inches in d.b.h. and smaller can be sampled beyond the fixed radius of 37.24 ft.

The pattern and configuration of shrub and regeneration subplots are as follows. All plants having a d.b.h. of 0.6

inches to 3.5 inches inclusive were sampled on four square subplots, each of which is 13.2 ft square with an area of 0.004

acre. Placing two of these shrub plots adjacent to one another essentially creates two 0.00%acre square subplots (fig. 1).

Nested within these plots are four O.OOl-acre square subplots, within which all herbaceous vegetation and all woody

regeneration from 0.25 ft tall to 5 0.5 inches in d.b.h. were sampled. Two additional milacre plots were established to

supplement the postharvest inventory of woody regeneration. Results from the pretreatment sampling of the shrub and ground

cover Iayers are presented elsewhere in this symposium (Foti and Devall, this volume). Results from analysis of the full

spectrum of vegetation, from ground layer to overstory, are also presented elsewhere in this symposium (Foti and Guldin,

this volume).

Site variables

The site conditions at each plot were recorded using plot center as the primary reference point. Slope percentage and

aspect of plot orientation were measured using a hand-held clinometer and compass to the nearest 1 percent and 1 degree,

respectively. Slope position was recorded on ;I scale of 1 to 5 for ridgetop, upper slope, midslope, lower slope, and

floodplain, respectively. On each plot, two dominant or upper codominant shortleaf pine trees were measured for both total

height (ft) and ring count at 4 ft; three years were added to each ring count, and site index was determined for each tree

from Graney and Burlchart (1992). The average site index was then determined by arithmetic average of the two site index

values. A qualitative judgment of site quality, subjectively made in the woods based on vegetation, physiographic, and

edaphic factors, was assigned at each plot using a scale of 1 to 4 (poor, medium, good, and excellent, respectively).

Microtopography, defined as the topographic variation across the entire plot, was rated using a scale of 1 to 3 (convex, level,

and concave, respectively); microtopographic severity was scaled from 1 to 3 (mild, moderate, and severe, respectively).

Microrelief, defined as the topographic variation within a plot, was rated as either 1 or 2 (pit-and-mound, and smooth,

respectively); microrelief severity was scaled from 1 to 3 (mild, moderate, and severe, respectively).

Stands were identified by treatment and block through the analysis. Stand locations were quantified by plotting the center

of each stand on a US Geological Survey topographic quad (1:24000), and reading Universal Transverse Mercator values

for latitude (UTM North, meters) and longitude (UTM East, meters).

Data Analysis

Initial data summaries were conducted for trees per acre and basal area per acre in a 3 by 3 contingency table. The xaxis was subdivided as midstory, overstory, and both layers; the y-axis was subdivided as conifer, hardwood, and all

species. More detailed summaries were prepard using a matrix of 25 rows and 10 columns representing species by size

classes, respectively, as follows. The 25 species <consist of 23 individual species, 1 “other” category, and an all-species total

(table 3); the 10 size classes represent eight 3-inch classes, a final class for all trees larger than any of the previous classes,

and a total (table 4).

Summary tables of trees per acre and basal area per acre were calculated by stand, based on averages of the 14 plots.

Relative density was calculated for each species by size class as the quotient of trees per acre in the given species by size

class divided by the total number of trees across all species in the given size class; similarly, relative dominance was

calculated as the quotient of basal area per acre in the given species by size class divided by the total number of trees across

all species in the given size class. Importance values were then derived for each species by size class as the average of

relative density and relative dominance.

The tinal analytical step in this pretreatment analysis was to test for differences in means by block and future treatment.

Tests for normality indicated that most variables were not normally distributed; as a result, nonparametric analysis of

variance (SAS Institute Inc. 1990) was used to test the null hypothesis of no difference among means for site and summary

mensurational data. Statistical significance of results would imply differences among plot means for the site and

mensurational variables. Given that plots were imposed in a stratified manner, one would expect plot differences to be

detected using this analysis. Future attempts to use regression analysis will be enhanced if this test is significant.

33
Table 3.-Species present in the analysis

Species

Code Common name and scientific name

JUNVIR Eastern rrd cedar, Juniperus virginiana L.

PINECH Shortleaf pine, Pinus cchinata Mill.

AMEARB Serviceberry, Amelanchier arborea (Michx. f.) Fem.

ACERUB Red maple, Acer rubrum L.

CARCAR American hornbeam, Carpinus caroliniana Walt.

CARCOR Bittemut hickory, Carya cord@& (Wangenh.) K.Koch

CARTOM Mockemut hickory, Carya tomentosa (Pair.) Nutt.

CARTEX Black hickory, Carya Mana Buckl.

CORFLO Flowering dogwood, Comusflorida L.

FRAAME White ash, Fraxinus americana L.

LIQSTY Sweetgum, Liqukfambar styracifluo L.

NYSSYL Black gum, Nyssa sylvatica Marsh.

OSTVIR Eastern hophornbeam, Osrrya virginiana (Mill.) K. Koch

PRUSER Black cherry, Prunus serotina Elwh.

QUEALB White oak, Quercus alba L.

QUEFAL Southern red oak, Quercus falcata Michx. var. falcata

QUEMAR Blackjack oak, Qucrcus marilandica Muenchh.

QUERUB Northern red oak, Quercus rubra L.

QUESTE Post oak, Quercus srellata Wangenh.

QUEVEL Black oak, Quercus velutina Lam.

ULMALA Winged elm, U1mu.r alata Michx.

ULMAME American elm, Vbnus americana L.

ULMRUB Slippery elm, Vbnus rubra Muhl.

GGGSSS Other species (grouped for Lhis analysis)

TOTAL All species

Table 4.- Size classes and inclusive size class endpoints

used in this analysis

Diameter class Specific size

(inches) (inches in d.b.h.)

04-06 3.6 - 6.5

07-09 6.6 - 9.5

10-12 9.6 - 12.5

13-15 12.6 - 15.5

16-18 15.6 - 18.5

19-21 18.6 - 21.5

22-24 21.6 - 24.5

25-27 24.6 - 27.5

2a+ 27.6 and larger

TOTAL 3.6 and larger

RESULTS

The Average Mature Pine/Hardwood Stand On South-Facing Slopes

of the Ouachita/Ozark National Forests

Descriptive summary statistics for all 52 stands in the Phase II study (including mean, standard deviation, and

minimum/maximum) are presented in table 5. The “average stand” in the study is a south-facing stand with 11 percent slope,

occupies a midslope position on the hillside, and has 91 percent cover. Based on UTM coordinates, the geographic center

of the 52-plot data base is located about 5 miles north of the Big Brushy campground in the Oden Ranger District-not

unexpected, since that district contains the largest number of stands (11 of 52) in the study. Average site quality was judged

to be halfway between medium and good, and average site index for shortleaf pine (base 50) is 62.2 ft. Microsite topography

was judged more level than convex, and moderately so; microtopographic relief was judged more smooth than pit-andmound, though only from mild to moderate.

Statistics for the “average stand” mensurational summary variables, also based on all 52 stands in the study, are

presented in table 5. The average stand has 323.2 trees per acre in trees > 3.6 inches in d.b.h., of which 51.1 percent is

conifer and 48.9 percent hardwood. However, of the 129.5 ft’lacre of basal area in the average stand, 73.5 percent is

conifer and 26.5 percent hardwood. It follows that the average conifer is larger than the average hardwood; the quadratic

mean diameter (the diameter of the tree of average basal area) for conifers is 10.45 inches, whereas that for hardwoods is

6.28 inches.

Examination of variable statistics for the 72%plot data base, rather than as summarized stand data, gives a better

indication of plot variability. Although statistics for variables based on the pIot-based observations result in the same sample

means as those for the 52-stand data base, the sample standard deviations, maxima and minima are larger, larger and smaller,

respectively, for the 728-plot data base. Histogra.ms of site variables across all plots reveal that in most cases, sample means

and modes are similar, but that in all cases a wide spectrum of variation is included in the data base (Appendix, figs. AlAlO).

34
Table 5.- Sample minimum, maximum, mean, and standard deviation for site and mensurational summary variables based

on stand averages in the S2-stand data base. Stand averages for all except UlM (Universal Transverse

Mercator) variables based on I4-plot summaries. TPA - trees per acre; BA - basal area, j? per acre ; QD -

quadratic mean diameter (diameter of the tree of average basal area), inches

Variable Minimum Maximum Mean

Standard

Deviation

I. Site variables

UTM - North (m) 31803700.00 3936200.00 3844196.15 25115.13

UTM - East (m) 335100.00 463400.00 426144.23 33664.42

Azimuth Orientation (deg) 115.14 280.64 180.31 38.86

Slope percent 4.21 25.36 11.62 4.83

Slope position * 2.36 3.71 3.12 0.31

Percent Cover 82.37 95.57 91.01 3.17

Microtopography t 1.36 2.57 1.88 0.28

Microtopographic severity $ 1.00 1.93 1.41 0.22

Microrelief J 1.36 2.00 1.84 0.17

Microrelief severity $ 1.00 2.00 1.50 0.24

Tree Height 57.75 80.07 70.38 5.20

\ Tree Age 51.64 85.75 64.49 5.92

Site Index 49.59 70.73 62.23 4.35

Site Quality 1 1.79 3.14 2.51 0.30

II. Mensurational variables

TPA, conifer midstory 8.57 181.43 81.50 38.72

TPA, conifer overstory 44.13 108.31 83.55 13.31

TPA, all conifers 56.27 283 .OO 165.05 44.80

TPA, hardwood midstory 24.29 217.86 145.76 38.91

TPA, hardwood overstory 1.38 38.36 12.40 8.55

TPA, all hardwoods 27.76 243.29 158.16 41.92

TPA, all midstory 136.43 355.00 227.25 45.14

TPA, all overstory 71.67 126.52 95.95 12.29

TPA, all trees 203.52 455.19 323.21 48.25

BA, conifer midstory 2.11 46.89 18.20 9.00

BA, conifer overstory 45.71 97.14 77.02 10.65

BA, all conifers 50.12 121.17 95.22 14.31

BA, hardwood midstory 5.00 35.52 23.43 6.45

BA, hardwood overstory 1.07 41.07 10.86 7.86

BA, all hardwoods 8.21 67.13 34.29 11.92

BA, all midstory 24.77 74.90 41.63 9.38

BA, all overstory 62.50 111.07 87.88 10.15

BA, all trees 98.36 155.26 129.51 13.76

QD, conifer midstory 4.35 7.36 6.10 0.61

QD, conifer overstory 11.39 14.65 13.07 0.72

QD, all conifers 9.06 13.97 10.74 0.97

QD, hardwood midstory 4.25 5.86 5.31 0.31

QD, hardwood overstory 2.62 13.85 9.35 2.94

QD, all hardwoods 5.25 8.32 6.22 0.63

QD, all midstory 5.03 6.71 5.77 0.27

QD, all overstory 11.34 14.31 13.05 0.62

QD, all trees 7.74 9.68 8.69 0.47

+ Index: 1 - ridgetop; 2 slope; 3 midslope; 4 - upper - - lower slope; 5 - floodplain

t Index: 1 - convex; 2 - level; 3 - concave.

$ Index: 1 - mild; 2 - moderate; 3 - severe.

0 Index: 1 - pit-and-mound; 2 - smooth.

( Index: 1 - poor; 2 - medium; 3 - good; 4 - excellent.

35
Tree density

The average stand shows a bimodal distribution of trees per acre in the coniferous component, with peaks in the 4- to

6-inch class and the lo- to 1Zinch cla.cs (fig. 2). Hardwoods as a group show a continuous exponential decline in density

with increasing diameter. Shortleaf pine is the most numerous tree in the average stand, followed by post oak, white oak,

black hickory, mockemut hickory, and winged elm (fig. 3).

0

Conifers q

Hardwoods

4-6 7-9 lo-12 13-15 16-18 19-21 22-24 25-27 28+

D.b.h . class (inch e s )

Figure 2.-Trees per acre in the average stand, by conifers and hardwoods.-#-

Shortleaf pine

-APost oak

-0

White oak

ABlack hickory

*

Mockernut hickory

43

i

Winged elm

4-6 7-9 IO-12 1315 16-18 19-21 22-24 25-27 2%

D.b.h . class (inch e s )

Figure 3.-Trees per acre in the average stand--six most numerous species.

36
Th e m ost num e rous species in th e ove rstory are sh ortle af pine, post oak , and w h ite oak ; no oth e r species in th e ave rage

stand exceeds one ove rstory tree pe r acre (table 6). Sh ortleaf pine dom inates th e ove rstory w ith 51.4 pe rcent of its stem s

in th e ove rstory laye r; no oth e r species h as m ore th an 20 pe rcent of its stem s in th e ove rstory, alth ough south e rn red oak ,

slippery elm , sw e etgum , north e rn red oak , post oak , and black ch e rry all exceed 10 pe rcent (table 6).

Sh ortleaf pine is also th e m ost num e rous species in th e m idstory (78.8 stem s/acre), follow ed by post oak , w h ite oak ,

black h ick ory, and m ock em ut h ick ory (table 6), all of w h ich exceed 10 stem s per acre. H ow eve r, w h en considering th e

percentage of ove rstory occupancy by species, a h andful of species exists only as m idstory trees in th e ave rage stand-nam ely

se rvicebe rry, h oph om beam , bittem ut h ick ory, flow e ring dogw ood , w h ite ash , and Am e rican h ornbeam (table 6).

Basal area

Th e conife rs in th e ave rage stand h ave a norm al or “bell-sh aped” distribution of basal area pe r acre, w ith peak s in th e

lo- to ‘15~ inch classes (fig.4). H ardw oods sh ow a continuous exponential decline in basal area as size class increases.

Sh ortleaf pine accounts for 9 4.7 ft’/acre in th e ave rage stand , or 73 pe rcent of total basal area (table 7). Post oak and w h ite

oak account for 10.5 ft’/acre (8.1 pe rcent) and 8.9 ft’/acre (6.8 pe rcent), respectively; no oth e r species exceeds 3.0 ft2/acre.

Basal are a data also reve al th e degree of ove rstory dom inance by sh ortle af pine. O f th e 87.9 ft2/acre in ove rstory basal

area, sh ortleaf pine accounts for 76.9 ft2/acre or 87.5 pe rcent (table 7). Post oak and w h ite oak com prise 4.0 ft2/acre (4.6

percent) and 3.0 ft’/acre (3.4 pe rcent) of ove rstory basal area, respectively; no oth e r species in th e ave rage stand exceeds

1.0 ft2/acre of basal area in th e ove rstory (table 7).

Th ough it does not dom inate th e m idstory as it does th e ove rstory, sh ortleaf pine noneth eless accounts for th e largest

percentage of m idstory basal area pe r acre in th e ave rage stand , h aving 17.8 ft2/acre (table 7) or 42.6 pe rcent. It is follow e d

by post oak , w h ite oak , and black h ick ory, w h ich h ave 6.4 ft2/acre (15.4 pe rcent), 5.9 ft2/acre (14.2 pe rcent), and 2.1

ft2/acre (5.1 pe rcent), respectively, in m idstory basal area. No oth e r species exceeds 2.0 ft2/acre in th e m idstory (table 7).

Table 6.- Trees per acre in the average stand, by species and j-inch diameter classes. 131e midstory includes all trees with

3.6 inches to 9.5 inches in d. 6. h.; rhe overstory includes all trees 9.6 inches in d. b. h. and larger

--- Midstory --- ____________________________ @erstory ___--_-_--_.--..._.-.---.--- Midstory O ve rstory Pe rce n t

Spe cies * 4-6 7-9 10-12 13-15 16-18 19 -21 22-24 25-27 28+ Subtotal Subtotal Total O ve rstory

_______________________________________ Trees per ac,.e ________________________-_-____________________________________________________________ --Pe rce n t--

JUNVIR 2.267 0.714 0.188 0.000 ‘0.004 0.000 0.000 0.000 0.000 2.9 81 0.19 2 3.173 6.05

PINECH 45.39 8 33.380 43.9 27 28.861 8.9 38 1.421 0.179 0.007 0.000 78.778 83.334 162.112 51.41

AMEAR B 0.275 0.027 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.302 0.000 0.302 0.00

ACERUB 2.843 0.288 0.036 0.000 0.000 0.003 0.000 0.000 0.00 0 3.132 0.038 3.170 1.21

CARCAR 0.041 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.041 0.000 0.041 0.00

CARCOR 0.055 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.055 0.000 0.055 0.00

CARTOM 10.01 4 1.758 0.405 0.042 0.014 0.000 0.000 0.000 0.000 11.772 0.461 12.233 3.76

CARTEX 13.008 1.827 0.325 0.065 0.032 0.006 0.000 0.000 0.000 14.835 0.429 15.265 2.81

CO R FLO 2.9 12 0.027 0.000 0.000 0.000 0.000 0.000 0.000 0.000 2.9 40 0.000 2.9 40 0.00

FRAAME 0.316 0.110 0.000 0.000 0.000 0.000 O.OCKl 0.000 0.000 0.426 0.000 0.426 0.00

LIQSTY 2.006 0.742 0.358 0.122 0.032 0.012 0.005 0.000 0.000 2.747 0.529 3.276 16.13

NYSSYL 4.080 0.440 0.068 0.048 0.039 0.023 0.017 0.002 0.000 4.519 0.19 6 4.715 4.16

OSTVIR 0.412 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.00 0 0.412 0.000 0.412 0.00

PRUSER 0.288 0.09 6 0.039 0.000 0.004 0.000 0.000 0.000 0.00 0 0.385 0.043 0.428 10.10

QUEA LB 24.561 8.39 3 2.240 0.640 0.305 0.132 0.039 0.004 0.003 32.9 53 3.363 36.316 9 .26

QUEFAL 2.472 1.223 0.567 0.240 0.09 1 0.018 0.005 0.000 0.000 3.69 5 0.9 21 4.616 19 .9 5

QUEMAR 6.03 0 0.852 0.214 0.068 0.005 0.000 0.000 0.000 0.000 6.882 0.286 7.168 3.9 9

QUERUB 2.651 1.360 0.333 0.143 0.071 0.006 0.000 0.002 0.003 4.011 0.557 4.568 12.20

QUESTE 33.18 7 7.349 2.838 1.220 0.355 0.105 0.037 0.004 0.002 40.536 4.561 45.09 7 10.11

QUENIG 4.643 1.841 0.382 0.177 0.081 0.03 1 0.002 0.000 0.003 6.483 0.675 7.159 9 .44

U LM A LA 7.720 0.9 34 0.152 0.042 0.000 0.000 0.000 0.000 0.000 8.654 0.19 4 8.848 2.19

U LMAME 0.15 1 0.055 0.011 0.000 0.000 0.000 0.000 0.000 0.000 0.206 0.011 0.217 5.16

U LMRU B 0.069 0.027 0.022 0.000 0.000 0.000 0.000 0.000 0.000 0.09 6 0.022 0.118 18.71

GGGSSS 0.59 1 0.069 0.061 0.039 0.009 0.000 0.003 0.000 0.001 0.659 0.114 0.773 14.71

TO T 165.9 89 61.511 52.168 31.706 9 .9 79 1.757 0.287 0.019 0.011 227.500 9 5.9 28 323.428 29 .66

Conife rs 47.665 34.09 4 44.115 28.861 8.9 42 I.421 0.179 0.007 0.000 81.759 83.526 165.285 50.53

H ardw oods 118.324 27.418 8.053 2.845 1.037 0.336 0.107 0.011 0.011 145.742 12.402 158.143 7.84

x Spe cies codes are defined in Table 3.

37
q

Conifer

liiiiil

Hardwood

:.:

+ +

:. ISI I

I I I I

4-6 7-9 10-12 13-15 16-18 19-21 22-24 25-27 28+

:.L

::::

D.b.h . class (inch e s )

Figure k--Basal area per acre in the average stand, by conifers and hardwoods.

Table 7.- Basal area per acre in the average stand, by species code and 3-inch diameter classes. The midstory includes

all trees 3.6 inches to 9.5 inches in d. b.h.; the overstory includes all trees 9.6 inches in d.b.h. and larger

--- Midstory --- ____ ________ __ _______ __ _____ Ove rstory ___.-________-_______----___ Midstory Ove rstory Pe rce n t

Spe cies X 4-6 7-9 10-12 13-15 16-18 19 -21 22-24 25-27 28+ Subtotal Subtotal Total O ve rstory

______________________________----____ Trees oe r acre ____________________________-___.-_______~__________-______~~______________.~_______~ --Pe rcent--

JUNVIR 0.283 0.239 0.110 0.000 m o.OO7 0.000 0.000 0.000 0.000 0.522 0.117 0.639 18.27

PINECH 6.088 11.678 29 .512 30.268 13.59 9 2.9 81 0.501 0.027 0.000 17.765 76.889 9 4.654 81.23

ACERUB 0.342 0.09 0 0.021 0.000 0.000 0.007 0.000 0.000 o.OO+ l 0.431 0.027 0.459 5.9 9

AMEARB 0.028 0.008 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.036 0.000 0.036 0.00

CARCAR 0.004 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.004 0.000 0.004 0.00

CARCOR 0.006 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.00 0 0.006 0.000 0.006 0.00

CARTEX 1.518 0.59 6 0.206 0.069 0.048 0.014 0.000 0.000 0.00 0 2.114 0.336 2.451 13.73

CARTOM 1.242 0.560 0.254 0.041 0.021 0.000 0.000 0.000 0.000 1.802 0.316 2.118 14.9 1

CO R FLO 0.29 2 0.010 0.000 0.000 0.000 0.000 0.000 0.000 0.00 0 0.301 0.000 0.301 0.00

FRAAME 0.036 0.032 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.068 0.000 0.068 0.00

LIQSTY 0.255 0.235 0.240 0.124 0.048 0.027 0.014 0.000 0.00 0 0.49 1 0.453 0.9 44 48.02

NYSSYL 0.488 0.137 0.041 0.048 0.062 0.048 0.048 0.007 0.00 0 0.625 0.254 0.879 28.89

OSTVIR 0.042 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.00 0 0.042 0.000 0.042 0.00

PRUSER 0.033 0.033 0.027 0.000 0.007 0.000 0.000 0.000 0.000 0.066 0.034 0.100 34.29

QUEALB 3.155 2.753 1.408 0.666 0.467 0.282 0.110 0.014 0.014 5.9 08 2.9 60 8.869 33.37

QUEFAL 0.329 0.404 0.371 0.254 0.144 0.041 0.014 0.000 0.000 0.733 0.824 1.557 52.9 3

QUEMAR 0.743 0.269 0.130 0.069 0.007 0.000 0.000 0.000 0.000 1.012 0.206 1.218 16.9 0

QUERUB 0.342 0.436 0.220 0.151 0.110 0.014 0.000 0.007 0.014 0.778 0.515 1.29 3 39 .83

QUESTE 4.063 2.383 1.834 1.284 0.542 0.227 0.103 0.014 0.007 6.446 4.011 10.457 38.36

QUEVEL 0.59 8 0.612 0.254 0.185 0.124 0.069 0.007 0.000 0.014 1.210 0.652 1.862 35.03

U LM A LA 0.9 07 0.303 0.09 6 0.041 0.000 0.000 0.000 0.000 0.000 1.210 0.137 1.347 10.19

U LMAME 0.015 0.023 0.007 0.000 0.000 0.000 0.000 0.000 0.00 0 0.038 0.007 0.045 15.18

U LMRU B 0.010 0.011 0.014 0.000 0.000 0.000 0.000 0.000 0.000 0.021 0.014 0.035 39 .15

GGGSSS 0.067 0.023 0.041 0.041 0.014 0.000 0.007 0.000 0.007 0.09 0 0.110 0.200 54.9 3

TO TALS 20.887 20.835 34.787 33.242 15.19 9 3.709 0.803 0.069 0.055 41.722 87.864 129 .586 67.80

Conife rs 6.3708 11.9 17 29 .622 30.268 13.606 2.9 808 0.5013 0.0275 0 18.288 77.005 9 5.29 3 80.81

H ardw oods 14.516 8.9 184 5.1642 2.9 735 1.59 3 0.7278 0.3021 0.0412 0.0549 23.434 10.857 34.29 3 31.66

x Spe cies codes are defined in Table 3.

38
Importance Values

Considering all size classes in the average stand, the importance value of conifers is greater than that of hardwoods (table

8). This is primarily due to conifer dominance in the overstory, where their importance value is roughly seven times greater

than that of the hardwoods. In the midstory, the hardwood importance value exceeds that of conifers, due to high hardwood

densities in the midstory.

Table 8.- Importance values in the average stand, by species and 3” diameter classes. The midstory includes all trees 3.4

inches to 9.5 inches in d. b. h., the overstory includes all trees 9.6 inches in d. 6. h. and larger

--- Midstory --- -______----------_.___-__--- Ove rstory ---_____.---------_ ---__- Midstory Ove rstory

Spe cies X 4-6 l- 9 10-12 13-15 16-18 19 -21 22-24 25-2 7 28+ Subtotal Subtotal Total

t JUNVIR 1.36 1.15 0.34 0.00 0.04 0.00

PINECH 28.25 55.16 84.52 9 1.04 89 .52 80.62

ACERUB 0.9 0 0.24 0.03 0.00 0.00 0.09

AMEAR B 0.9 2 0.25 0.03 0.00 0.00 0.08

CARCAR 0.02 0.00 0.00 0.00 0.00 0.00

CARCOR 0.03 0.00 0.00 0.00 0.00 0.00

CARTEX 6.65 2.86 0.68 0.17 0.23 0.19

CARTOM 6.89 2.83 0.68 0.16 0.23 0.18

CO R FLO 1.58 0.05 0.00 0.00 0.00 0.00

FRAAME 0.18 0.17 0.00 0.00 0.00 0.00

LIQSTY 1.22 1.17 0.69 0.38 0.32 0.71

NYSSYL 2.40 0.69 0.12 0.15 0.40 1.29

OSTVLR 0.22 0.00 0.00 0.00 0.00 0.00

PRUSER 0.17 0.16 0.08 0.00 0.04 0.00

QUEALB 14.9 5 13.43 4.17 2.01 3.06 7.55

QUEFAL 1.53 1.9 6 1.08 0.76 0.9 3 1.07

QUEMAR 3.60 1.34 0.39 0.21 0.05 0.00

QUERU B 1.62 2.15 0.64 0.45 0.72 0.35

QUESTE 19 .72 11.69 5.36 3.86 3.56 6.05

QUEVEL 2.83 2.9 1 0.73 0.56 0.81 1.81

U LM A LA 4.50 1.49 0.28 0.13 0.00 0.00

U LMAME 0.08 0.10 0.02 0.00 0.00 0.00

U LMRU B 0.05 0.05 0.04 0.00 0.00 0.00

GGGSSS 0.34 0.11 0.12 0.12 0.09 0.00

TO TALS 100.0 100.0 100.0 lOO.(l 100.0 100.0

0.00 0.00 0.00

62.46 39 .74 0.02

0.00 0.00 0.00

0.00 0.00 0.00

0.00 0.00 0.00

0.00 0.00 0.00

0.00 0.00 0.00

0.00 0.00 0.00

0.00 0.00 0.00

0.00 0.00 0.00

I .69 0.00 0.00

5.89 10.49 0.00

0.00 0.00 0.00

0.00 0.00 0.00

13.72 19 .54 25.19

1.71 0.00 0.00

0.00 0.00 0.00

0.00 9 .67 24.68

12.85 20.56 13.47

0.80 0.00 23.9 2

0.00 0.00 0.00

0.00 0.00 0.00

0.00 0.00 0.00

0.87 0.00 12.72

100.0 100.0 100.0

1.28

38.60

0.58

0.73

0.01

0.02

5.12

5.42

1.01

0.17

1.19

1.74

0.14

0.16

14.32

1.69

2.73

1.81

16.63

2.87

3.35

0.09

0.05

0.25

100.0

0.17 0.74

87.19 6158

0.02 0.22

0.02 0.50

0.00 0.01

0.00 0.01

0.43 2.84

0.40 3.18

0.00 0.57

0.00 0.09

0.53 0.87

0.25 1.07

0.00 0.08

0.04 0.10

3.44 9 .04

0.9 5 1.31

0.27 1.58

0.58 1.21

4.66 11.01

0.72 1.83

0.18 1.89

0.01 0.05

0.02 0.03

0.12 0.20

100.0 loo.0

Conife rs 29 .61 56.31 84.86 9 1.04 89 .56 80.62 62.46 39 .74 0.02 39 .88 87.357 6232

H ardw oods 70.39 43.69 15.14 8.9 6 10.44 19 .38 37.54 60.26 9 9 .9 8 60.12 12.642 37.68

______ _.__ ___________ ____ _________ _____ Treesperacre_____________ -__._ ________ -_____________ ___________.__-___________________-____

r Spe cies codes are defined in Table 3.

When considering the importance value of conifers and hardwoods in 3-inch size classes, an interesting pattern emerges

(fig. 5). In the 4- to 6-inch class, the hardwood group has a larger importance value than the conifers, again because of the

many hardwood stems in the 4- to 6-inch class. From the 7- to g-inch class through the 22- to 24-inch class, the conifer

group has greater importance values than the hardwoods; this difference is especially prominent from the lo- to 1Zinch class

to the 19- to 21-inch class. However, in the two largest classes, hardwood importance values again exceed those of the

coniferous group.

Analysis of Variance

Nonparametric analysis of variance using plot averages resulted in significant differences among site and mensurational

data. The assumption of equality among means by future treatment was rejected (at P> 0.05) for nearly all site and

mensurational summary variables (table 9), using the Kruskal-Wallis test statistic. Only three variables did not show

significant difference among means by future tratment-trees per acre in the conifer midstory, quadratic mean diameter of

the conifer midstory, and quadratic mean diameter of the hardwood overstory. The reason these variables should exhibit

a lack of mean difference is not readily apparent. Despite the statistical significance of these tests of mean difference by

39
20

0 t

4-6 7 - 9 , IO-12 ' 13-15 ' 16-18 19-21 '22-24 '2527 ' 28+

D.b.h . class (inch e s )

Conifers

iiif

Hardwoods

Figure 5.4mportance values in the average stand, by con@ers and hardwoo&

future treatment for most variables, the values of the means do not show great variation. For example, consider the total

trees per acre and basal area per acre for all trees 3.6 inches and larger. Means by future treatment vary from 286 to 377

trees per acre, and from 122 to 147 ft2 per acre, respectively. Similarly, means by future treatment for site index vary from

58.8 to 65.1 ft, and means for percent cover vary from 89.2 to 93.5 percent.

The assumption of equality among means by physiographic block was also rejected for most site and mensuration

variables (table 10). The only site variables in which one fails to reject the hypothesis of mean equality by future treatment

are microtopography and microrelief, indications that within-plot surface variation is minimal. Several of the mensuration

summary variables-trees per acre of the conifer overstory and all overstory, basal area per acre of the conifer overstory

and all overstory, and several of the quadratic mean diameter measurements-exhibit no statistically significant difference

among ecoregional blocks means when evaluatecl at P>O.O5.

DISCUSSION AND CONCLUSIONS

The average stand in this study had residual basal areas slightly higher than anticipated, with hardwood midstory basal

areas also higher than anticipated. The stand was slightly younger than anticipated, as well. These observations are

consistent with the impression in the woods that the dominant and codominant pines in these stands have rather small crowns

and a relative absence of cones. It follows that relying on these trees to produce seed following reproduction cutting in the

summer of 1993, while not quite a leap of faith, is nonetheless a rather large step. Future work might focus productively

on securing mixed-species advance growth se\.eral years prior to reproduction cutting, perhaps through late-rotation

preparatory cutting coupled with pre-cut site preparation such as prescribed fire. The silvicultural hoops through which the

forester must jump are fewer, larger, and less flammable if advance growth of the desired mixture of species existed prior

to reproduction cutting.

The reverse J-shaped diameter distribution of the average stand, especially in the hardwood component, might lead some

to label these stands as uneven-aged. However, this is discounted on multiple grounds. First, the curve is a mixture of all

species; such interpretations are best made for individual species. Second, such interpretations are dubious at best without

examining the submerchantable component; the l- to 3-inch hardwood component has a large number of stems per acre,

but that the conifer component does not (Foti and Devall, this volume). Third, a pilot study of age distributions suggests

that there are very few trees of any species 3.6 inches and larger that are less than 50 years old; this suggests that the

smaller hardwoods are a long-suppressed element similar in age to the overstory, rather than a vigorous younger component.

This reverse J-shaped diameter distribution is better explained based on varying growth rates both within and between these

hardwood species, related to both shade tolerance and to the exclusion of fire for the past 6 decades.

40
Table 9.- Means by future treatment for site and mensuration summary variables, based on plot averages (n =56). The null

hypothesis of equality among means is rejected at indicated levels of Kruskal-WallisX2 test statistic. Codes

for silvicultural system are defined in Table 1; TPA - trees per acre; BA - basal area, ftz per acre ; QD -

quadratic mean diameter (diameter ‘7f the tree of average basal area), inches

Variable

-- Controls - -----Even-aged pattial cutting m e th ods----- --Uneven-aged partial cutting m e th ods----- K W

U C CCNS STP STPH SW P SW PH SWW GSP GSPH STSP STSH STSW STSL P> p

I. Site variables

Azim uth (deg) 179 .30 161.9 8 169 .25 176.GS 181.84 184.61 1.80.21 184.87 209 .29 153.00 154.45 19 6.48 212.75 0.0001

Slope pe rcent 8.50 14.82 10.66 9 .GO 12.86 18.5 5 12.04 11.61 12.45 12.46 10.9 3 7.09 10.13 0.0001

Slope position + 3.29 2.63 3.13 3.29 3.14 2.89 3.25 3.27 3.20 2.9 6 3.05 3.34 3.13 0.0001

Pe rcent Cove r 9 0.07 9 0.9 4 9 1.31 9 2.33 9 0.70 8 9 .23 9 0.14 9 2.74 89 .53 9 1.71 9 0.18 9 0.69 9 3.51 0.0001

Microtopograph y t 1.77 1.71 2.11 1.86 1.89 1.9 5 1.68 2.07 1.66 1.9 3 2.04 1.77 1.9 5 0.0483

Microtopograph ic seve rity $ 1.21 1.61 1.30 1.30 1.45 1.38 1.57 1.38 1.55 1.29 1.38 1.43 1.43 0.0034

Microre lief !j 1.82 1.80 1.9 1 1.80 1.73 1.9 6 1.9 3 1.9 3 1.68 1.88 1.84 1.84 1.86 0.0009

Microre lief seve rity $ 1.41 1.64 1.29 1.63 1.54 1.61 1.55 1.50 1.48 1.45 1.34 1.55 1.55 0.0024

Tree H eigh t 76.13 67.82 71.26 70. 9 6 72.76 64.65 73.32 72.88 69 .67 71.12 66.89 68.74 68.79 0.0001

Tree Age 69 .32 67.46 65.18 62.17 63.73 5 9 .63 69 .28 65.79 65.03 61.89 62.39 64.67 61.80 0.0001

Site Index 65.06 58.84 62.33 63. 9 8 64.57 5 9 .22 62.88 64.01 61.56 63.9 3 60.04 60.50 62.07 0.0001

Site \ Quality ( 2.73 2.11 2.55 2.54 2.55 2.50 2.50 2.70 2.27 2.80 2.48 2.50 2.38 0.0001

II. Mensurational variables

TPA, conife r m idstory 7 9 .64 70.71 86.25 101. 9 6 77.32 9 6.43 53.3 9 83.57 70.54 86.61 83.57 68.21 101.25 0.0828

TPA, conife r ove rstory 78.6 9 83.07 7 9 .58 9 6 . 9 1 81.0 9 86.43 9 0.65 85.83 70.088 86.84 83.23 76.40 87.40 0.0124

TPA, all conife rs 158.33 153.78 165.83 19 8.88 158.41 182.86 144.04 169 .40 140.62 173.45 166.80 144.61 188.65 0.0248

TPA, h ardw ood m idstory 138.75 127.86 161.43 165.18 154.46 9 7.32 132.68 153.39 161.61 146.9 6 152.32 149 .82 153.04 0.0001

TPA, h ardw ood ove rstory 9 .83 13.16 11.08 13.38 9 .62 12.14 9 .72 14.06 14.71 18.77 8.45 15.38 10. 9 2 0.0187

TPA, all h ardw oods 148.58 141.02 172.51 178.55 164.09 109 .46 142.40 167.46 176.32 165.73 160.77 165.20 163.9 5 0.0001

TPA, all m idstory 218.39 19 8.57 247.68 267.14 231.79 19 3.75 186.07 236.9 6 232.14 233.57 235.89 218.04 254.29 0.0001

TPA, all ove rstory 88.51 9 6.23 9 0.66 110.2 9 9 0.71 9 8.57 100.37 9 9 . 8 9 84.80 105.61 9 1.68 9 1.78 9 8.31 0.0009

TPA, all trees 306.9 0 29 4.80 338.34 377.43 322.50 29 2.32 286.44 336.86 316.9 4 339 .18 327.57 309 .82 352.60 0.0001

BA, conife r m idstory 18.00 16.00 20. 9 6 24.35 16.5 9 22.01 11.30 20.00 16.04 18.88 17.33 15.2 9 1 9 . 8 9 0.0165

BA, conife r ove rstory 81.52 75.36 75.09 84.64 75.54 69 .02 89 .82 77.9 5 67.05 77.50 74.73 71.88 81.16 0.0013

BA, all conife rs 9 9 .52 9 1.36 9 6.05 108. 99 9 2.13 9 1.03 101.13 9 7 . 9 4 83.0 9 9 6.38 9 2.06 87.16 101.05 0.0086

BA, h ardw ood m idstory 22.74 22.35 24. 9 1 26.30 24.42 15. 9 1 20. 9 3 25.48 26.14 22.78 22.62 24.48 25.54 0.0011

BA, h ardw ood ove rstory 8.04 10. 9 8 9 .73 11.79 8.57 10.89 8.84 11.52 14.64 16.34 7.32 13.21 9 .29 0.0122

BA, all h ardw oods 30.77 33.34 34.64 38.C9 33.00 26.80 2 9 .77 37.00 40.7 9 3 9 .12 2 9 . 9 5 37.6 9 34.83 0.001 8

BA, all m idstory 40.74 38.36 45.87 50.65 41.01 37.9 2 32.24 45.48 42.18 41.66 39 .9 5 39 .76 45.43 0.0001

BA, all ove rstory 89 .55 86.34 84.82 9 6.43 84.11 79 .9 1 9 8.66 89 .46 81.70 9 3.84 82.05 85.09 9 0.45 0.0010

BA, all trees 130.29 124.70 130.69 147.08 125.12 117.83 130.9 0 134.9 4 123.88 135.50 122.00 124.85 135.88 0.0001

QD, conife r m idstory 5.86 6.32 5.9 0 6.48 5.9 6 6.16 5.9 6 6.18 5.9 6 6.22 6.11 6.01 6.18 0.4838

QD, conife r ove rstory 13. 9 2 13.10 13.0 9 12.51 13.29 12.20 13.37 12.89 13.51 12.70 13.09 12.89 13.19 0.0001

QD, all conife rs 11.30 10.70 10.9 3 10.51 10.84 10.06 11.54 10.77 11.19 10.39 10.32 0.54 10.5 9 O.oool

QD, h ardw ood m idstory 5.42 5.59 5.26 5.35 5.34 4.9 1 5.27 5.32 5.42 5.29 5.17 5.24 5.50 0.0109

QD, h ardw ood ove rstory 8.1 9 10.87 9 .88 12.03 9 .18 8.16 8.02 10.00 8.67 9 .71 7.42 9 .76 9 .64 0.0563

QD, all h ardw oods 6.02 6.58 5.9 5 6.34 6.06 6.42 6.10 6.35 6.41 6.48 5.68 6.16 6.37 0.0003

QD, all m idstory 5.79 5.9 0 5.72 5.87 5.66 6.06 5.57 5.9 0 5.79 5.71 5.54 5.72 5.76 0.0001

QD, all ove rstory 13.70 12.9 4 12.9 6 12.69 13.22 12.24 13.48 12.9 2 13.37 12.87 12.99 13.15 13.12 0.0001

QD, all trees 8.9 2 8.87 8.51 8.53 8.56 8.76 9 .23 8.62 8.65 8.63 8.38 8.72 8.53 0.0014

* Index: 1 - ridge top; 2 s - uppelopr e ; 3 -m idslope ; 4 - low e r slope ; 5 - floodplain.

t Index: I - conve x; 2 - le ve l; 3 - con cave .

$ Index: 1 - m ild; 2 m od e rate ; 3 - se ve re .

5 Index: 1 - pit-and-m ound; 2 - sm ooth .

(I Index: 1 - poor; 2 - me dium ; 3 - good; 4 - e xce lle n t.

41
Tab le lo.- Means by block for site and mensuration summary variables, based on plot averages (n=182). The null

hypothesis of equality among means is rejected at indicated levels of Kruskal-Wallisy test statistic. Codes

for silvicultural system are defined in Table 1; TPA - trees per acre; BA - basal area, j? per acre ; QD -

quadratic mean diameter (diameter of the tree of average basal area), inches

Variable

East

Block

North

Block

sout h

Block

west

Block

KW

P>Xj

I. Site variables

Azimuth (deg) 198.64 170.88 166.79 184.95 O.ooal

Slope percent 9.74 15.06 12.32 9.37 O.oool

Slope position * 3.19 2.93 3.20 3.15 0.0005

Percent Cover 90.43 91.93 91.00 90.67 0.0456

Microtopography t 1.85 1.93 1.75 1.97 0.0556

Microtopographic severity $ 1.32 1.52 1.45 1.33 0.0041

Microreliee 1.86 1.84 1.81 1.87 0.4110

Microrelief severity $ 1.52 1.64 1.41 1.45 0.0003

Tree Height 70.82 70.04 73.60 67.07 0.0001

Tree Age 65.31 65.42 62.70 64.51 0.0110

Site Index 62.23 61.50 65.82 59.36 0.0001

Site Quality ( 2.52 2.37 2.70 2.44 0.0001

II. Mensurational variables

TPA, conifer midstory 79.73 75.06 68.79 102.42 0.0015

TPA, conifer overstory 87.66 81.64 79.04 85.86 0.0688

TPA, all conifers 167.39 156.70 147.83 188.28 0.0008

TPA, hardwood midstory 145.88 134.29 159.73 143.13 0.0064

TPA, hardwood overstory 10.87 12.31 15.73 10.70 0.0442

TPA, all hardwoods 156.75 146.60 175.45 153.83 0.0011

TPA, a11 midstory 225.60 209.34 228.52 245.55 0.0005

TPA, all overstory 98.53 93.95 94.77 96.56 0.4810

TPA, all trees 324.14 303.29 323.29 342.11 0.0005

BA, conifer midstory 19.14 15.64 15.80 22.22 0.0006

BA, conifer overstory 77.31 76.73 74.42 79.62 0.4863

BA, all conifers 96.45 92.37 90.23 101.84 0.0102

BA, hardwood midstory 23.60 21.10 26.15 22.88 0.0011

BA, hardwood overstory 9.01 11.18 13.63 9.62 0.0246

BA, all hardwoods 32.61 32.28 39.78 32.49 0.0001

BA, all midstory 42.54 36.74 41.95 45.10 0.0001

BA, all overstory 86.32 87.91 88.05 89.23 0.8162

BA, all trees 129.06 124.65 130.00 134.33 0.0043

QD, conifer midstory 6.41 5.74 6.04 6.21 0.0025

QD, conifer overstory 12.i 1 13.20 13.15 13.23 0.0002

QD, all conifers 10.59 10.90 10.91 10.57 0.0407

QD, hardwood midstory 5.28 5.26 5.45 5.26 0.0622

QD, hardwood overstory 8.56 8.97 9.73 9.93 0.0605

QD, all hardwoods 6.C2 6.28 6.37 6.23 0.0847

QD, all midstory 5.84 5.64 5.78 5.81 0.0058

QD, all overstory 12.66 13.23 13.16 13.15 0.0001

QD, all trees 8.67 8.8 2 8.68 8.59 0.2758

* Index: 1 - ridgetop; 2 slope; 3 midslope; 4 - upper - - lower slope; 5 - floodplain

t Index: 1 - convex; 2 - level; 3 - concave.

$ Index: I - mild; 2 - moderate; 3 - se’tiere.

3 Index: 1 - pit-and-mound; 2 smooth.

( Index: 1 - poor; 2 - medium; 3 - good; 4 - excellent.

42
The importance value graphs depict unexpected trends as well. The high importance values for very small and very

large hardwoods, coupled with the very prominent difference in importance value between conifers and hardwoods in the

lo- to 24-inch overstory classes, are interesting. The prominence of the hardwood midstory can be attributed to the ongoing

successional development of shade-tolerant hardwoods, which is made possible by the alteration of disturbance through fire

prevention. The prominence of the 25 to 27-inch and 2 28-inch hardwoods may be due to a long-standing philosophy for

their retention for wildlife and other non-timber benefits. Conversely, the nontimber benefits of large pines have been less

appreciated, especially when considered relative to their timber value. Finally, in the lo- to 24-&h size classes, the

prominent difference in importance values between pines and the hardwood species might reflect the relative rates of growth,

but could also be explained by the long history of midstory hardwood control efforts conducted by the Ouachita NF over

the past decades, especially on sites such as these south-facing slopes that have been traditionally managed for pine. These

data suggest a three-step hypothesis toward restoration of natural ecological processes. These steps would include restoration

of light surface disturbances, cessation of efforts to eliminate smaller overstory hardwoods, and allowing some proportion

of overstory pines and hardwoods to grow beyond 24 inches in diameter.

The analysis of variance indicates that for most of the mensuration and site variables, differences exist among means

by both ecophysiographic block and future treatment. This is somewhat unexpected, since stands were selected according

to preestablished criteria, treatments were assigned randomly, and plot stratification was conducted systematically. But in

a larger sense this is surprising. The results illustrate that even fairly narrowly-defined pine-hardwood stands on south-facing

slopes in the Ouachita Mountains are, in fact, inherently variable. It lends credence to the assumption that the plots

encompass a full range of conditions likely to be encountered on these south- and southwest-facing mixed-species stands.

However, the observation that statistically significant differences may exist should be interpreted in light of the

ecological meaning behind the magnitude of the differences. For example, some variables, such as trees per acre for all trees

3.6 inches and larger, show rather large variation, which might be expected to be of significance ecologically and

silviculturally. Others, such as site index or percent cover, show little variation despite the statistical significance of the

difference among mean values by future treatment; the ecological importance of these significant differences is likely to be

minimal.

The presence of significant differences before treatment indicates that some adjustments in the analysis will be required

as comparisons are drawn between pre-treatment and posttreatment conditions. Analysis of variance is not likely to be the

best method of data analysis in light of preexisting differences, unless transformation of the data can reduce that variation.

On the other hand, the variation inherent in the data, especially at the level of the individual plot, is evident. Regression

analysis of stand development under block and future treatment effects at the plot level should be fruitful, in that models will

be applicable over a wide range of conditions.

LITERATURE CITED

Baker, James B. 1994. Stand-level ecosystem management research-an overview. In: Baker, J.B., camp. Symposium

on ecosystem management research in the Ouachita Mountains: pretreatment conditions and preliminary findings; 1993

October 26-27; New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station.

Cooper, A.W. 1989. Ecology of the pine-hardwood type. In: Waldrop, Thomas A., ed. Proceedings of pine-hardwood

mixture: a symposium on management and ecology of the type; 1989 April 18-19; Atlanta, GA. Gen. Tech. Rep. SE58. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station: 3-8.

Farrar, R.M., Jr.; Murphy, P-A.; Leduc, D.J. 1989. Volume growth of pine and hardwood in uneven-aged loblolly pineupland hardwood mixtures. In: Waldrop, Thomas A., ed. Proceedings of pine-hardwood mixture: a symposium on

management and ecology of the type; 1989 April 18-19; Atlanta, GA. Gen. Tech. Rep. SE-58. Asheville, NC: U.S.

Department of Agriculture, Forest Service, Southeastern Forest Experiment Station: 173-179.

Foti, T.L.; Devall, M. 1994. Pretreatment conditions in mature pine/hardwood stands on south-facing slopes of the

Ouachita/Ozark National Forests: ground layer and shrub layer. In: Baker, J.B., camp. Symposium on ecosystem

management research in the Ouachita Mountains: pretreatment conditions and preliminary findings; 1993 October 26-27;

New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station.

Foti, T.L., and J.M. Guldin. 1993. Pretreatment conditions in mature pine/hardwood stands on south-facing slopes of the

Ouachita/Ozark National Forests: multivariate analysis of ground layer, shrub layer, midstory, and overstory. In:

Baker, J.B., camp. Symposium on ecosystem management research in the Ouachita Mountains: pretreatment conditions

and preliminary findings; 1993 October 26-27; New Orleans, LA: U.S. Department of Agriculture, Forest Service,

43
Graney, D.; Burkhart, H.L. 1973. An equation to predict shortleaf pine site index in the Interior Highlands. Res. Paper

SO-85. New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station: 12 p.

Pickett, S.T.A.; White, P.S. 1985. The ecology of natural disturbance and patch dynamics. New York: Academic Press.

SAS Institute Inc. 1990. SAS Language: Reference, Version 6, First Edition. Cary, NC: SAS Instutite Inc. 1,042 p.

44
Figure A 1.-Distribution of azimuth orientation by plot.

160 , 1........1

Azimuth (degrees)

APPENDIX

’ 360

300

250

50

0

.~.‘,‘,‘_‘.‘_‘.’

.~.~.~.~_~_~_~_~

_‘_‘_~.‘_‘.‘.‘.’

_~_‘_~.~_‘_‘.~.’

- :..:..........

X= 91 01 percent

.~.~.~,~.~,~.~.~ .'_'_'.'.'.'.'.' _~_._~.~.~...... ::............ ::: .::::

(64.58-100.00) .~.~...~.~_~_~_~ _~_~.'.'.'.'.'.' ,~.'.'.'.'.'.'~ .~.~_~,~.~.~.'.~ . . . . . . . . . . . . . . . . . . . .~.~.~,~.'.~_~_~ .~.~_~.~_'.~_~_~ .~.~.~,~.','.~_~ _~_'.','.'.~.'.~ :.':,~:::: .._._._..._~_~. _~_~_~_~.'_~_~I ::::;::. .'.'.','.'.~.~.~ ::..:;::. .~.~.~,~_~.~.~_~ .._._._..._._._ .._._._._~_~.~_~ :::::::. :::::::: :::::::. _~_'.'.~.'.'.'.~ .._.:......... . _.::.......... :.>>>>>:.: :::::::::::::::: ,.i_.::...._ ::..:........ _..._._.,...... :::........: ,.~_._..._~_~. _~_'_~.~_~.~.'.' . . . . . .._..._~_._ .~.~.~.~.~.~.~_~ ..~_~.~.~.~.~. .-.'.-.'.'.'.'.' .~.~.~_~.~.~.~, _'_'_'.'_'.'.'.~ ,......-,~.~.~_ ::::_ ::: :::::\<:.::>~ . . . . . . . . . ..."'Z ..~.~.~

,~.~.~.~.~.~_~. :.:,::.:,I.:.: :::::::y:>:: y::::::::::::::: ,.,.,.~,.,,_._ ,.,.,.,.;_._... :::::::. .'.'.~.~.'.~.'.' .~.~.~.~.~.'_~_ .'.'.~.'.'.'.'.~ :::::::. :::::.:.:.: :::::::. ::::. .:.:_:_:.:.:.. ::: '.'.'.'.. .~.~.~.~.'.~_~_' .'_~_~.'.'.'.'. .~.'.'.'.'.'.'.' ,~.~.~.~.~.~_~. :.':,'.'::: :::::::. .'.'.'.'.'.'.'.~ .._-_~_~,~,~,~. ::::_ ::: ..:..,.:..,.. .P.............. .~.~.~.~.~_'.~_ .'.'.'.'.'.'.'.' :::::::. .~.'.'.'.'.'.'.' :::::::;:::::: ::::::.::::::::: . . . . . . . . .._.... . ..~.~,~,~.~_~.~ ::::::::::::::: :.,.,~,...,.,._.,. .','. ::: ::::::::::::::: ,~.~.~,~.~_'.~_ _'.'.'.~.'.~.~.' .~_~_~.~,~,~.~. _~_'_~.~.'.'.'.' ;;;;,.;_., ,.___.,.,.,,,._ __,.,.,.;;;,. .'.'.'.'.'.'.'. I ..,.,...,._._._ .:.:.:,:,:,:.:_: :::::::::::;:: I I I I I 1

< 65 70 75 80 85 90 95 100

Cove r (pe rce nt)

Figure A2.-Distribution of percentage cover by plot.

4 5
:.:.:.:.:.: r-l :::::. :::::. :::::. :::::.

x= ‘11.62 percent

(O.O- 50.0)

:::::: ::..::: ..::::: L

.~_~.~_‘_‘_’

_~.~_~.‘.‘.’

_~_‘.‘.‘_‘_’

::::::

_~_~.~_~_~_’

_~_~_~_~.‘.’

I I I I

-ii%? ' 11-15 ' 16-20 ' 21-25 ' 26-30 31-35 36-40 41-45 46-50

Slope (pe rce nt)

Figure A3.-Distribution of slope percentage by plot.

Ridge top

Uppe r s lope

Mids lope

Low e r s lope

Floodplain

200 300

Plots (num be r)

Figure A4.-Distribution of slope position by plot.

46
s e ve re

Figure AS.-Distribution of microtopography by plot.

Figure A6.-Distrib tution of microrelief by plot.

300

250

200

100

50

pit and m ound

47
200 ,

0 !

I

I I

40 45 50 55

175

i

x- 70.4ft

(39.593)

150

c

Q) *^_

Height (fl)

Figure Al.-Distribution of tree height by plot.

(345126.5)

Age (years)

Figure A8.-Distribution of tree age by plot.

48
250

x= 62.23

(42.6-84.45)

I I I I I I I I

45 50 55 60 65 70 75 80 85

Site Index (fl, base 50)

Figure A9.-Distribution of site index by plot.

Poor

Medium

Good

Excellent

~:::.

. . .

::::_

::::.

::::.

::::.

::::.

::::.

;:::.

::::.

I I I

1 I

I

I

I

I

I

0 100 200 300 400

Plots (number)

Figure AlO.-Distribution of site qunlity by plot.

49
Herbaceous Plant Biodiversity of Stands

in the Ouachita and Ozark National Forests’

Thomas Foti and Margaret S. Devall’

ABSTRACT

Pretreatment data on herb and shrub communities of 20 shortleaf pine-dominated stands in

the Ouachita and Ozark-St. Francis National forests are presented. These data will become

the baseline used to determine the impact of various silvicultural systems on plant diversity

as a part of a larger Ecosystem Management research effort. This effort will compare an

array of traditional and nontraditional even-aged and uneven-aged natural reproduction cutting

methods as alternatives to clearcutting and planting. In this pretreatment study, 582 species

were recorded in the stands during three sample periods in 1992 with 76 percent of the total

occurring during the summer and 21 percent only occurring during that sampling period. Fall

and spring sample periods had fewer total species and fewer unique species. Half the species

occurred in three or fewer stands whereas more than half the cover is provided by species that

occurred in all stands. These stands, within a narrow range of site, composition and structure

conditions, were relatively diverse and contained 40 percent of the species found in the region

but had few regionally rare species.

INTRODUCTION

Conservation of biological diversity has become an issue of public concern regarding the changes in biodiversity and their

effects on human life. Since adoption of the National Forest Management Act of 1976, the USDA Forest Service has been

mandated to consider impacts of its actions on diversity. increasing awareness of this issue has augmented USDA Forest Service

emphasis on preserving biodiversity and on devising acceptable management techniques to maintain and promote biodiversity in

national forests. Because traditional management activities in national forests have become controversial in recent years, and

because an increase and change in demands are being placed on the forests, new approaches to forest management are being

evaluated - most recently under the defining concept “Ecosystem Management.” Ecosystem Management provides a unique

challenge and opportunity in managing complex values and issues such as biodiversity as well as traditional products such as

timber, water, game and nongame wildlife, and fish, recreation, and minerals.

Ecosystem Management research in the Ouachita and Ozark National Forests attempts to objectively begin determining tht:

impacts of alternative management techniques in order to facilitate informed decisionmaking. This study of understory vegetation

and flora as a part of the overall research program will characterize and compare herbaceous plant diversity of stands before and

after a variety of traditional and nontraditional even-aged and uneven-aged reproduction cutting methods in order to detemline the

impact of the cutting methods and silvicultural systems on plant biodiversity.

Diversity can be used as an indicator of the “health” of ecosystems ( Magurran 1988). But biodiversity is a complicated and

challenging issue comprised of, and influenced by, many factors. Herbaceous plants appear to be good indicators of forest diversity

and the effect of silvicultural treatment on the environmental quality of the forest. One reason for this is that, in temperate forests,

there are typically many more species in the forest understory than in the overstory. They are distributed in relationship to both

intrinsic physical site conditions and conditions modified by the overstory (Causten 1988). With individualistic species response

(Whittaker 1956), understory communities comprise a broad suite of indicators of site and overstoryiunderstory relationships. In

addition, it is possible to characterize the understory flora (at least the vascular species component) in its entirety because these

species are persistent, detectable and identifiable by field biologists. Persistence throughout a season allows relatively few samples

taken within a year to be used to characterize the flora, wtile pelsistence or stability from year to year allows one year’s sampling

to serve as an adequate characterization of the site’s flora. Detectability is important in allowing species to be located in one site

visit regardless of time of day or length of time spent sampling. Identifiability results from distinct field characteristics and training

of botanists to identify many vascular plant taxa. These characteristics of the vascular flora of temperate forests contrast with those

of the fauna of these forests in that the fauna may be ephemeral (migratory species may change population levels on an hourly or

1 Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

2 Chief of Research, Arkansas Natural Heritage Commission, Little Rock, AR 72701; Ecologist, USFS Southern Forest

Experiment Station, New Orleans, LA 70113, respectively.

50
daily basis), undetectable (many are nocturnal or spend much of their life cycle below ground), or unidentifiable (most zoologists

are specialized on fairly narrow taxa).

For these reasons, the flora was addressed in this study not only as a taxonomic unit of importance in these stands, but also

as a unit that is especially useful for addressing questions of stand diversity. The objective here is to describe pretreatment

conditions on herb and shrub communities within 20 stands in the Ouachita and Ozark-St. Francis National Forests.

METHODS

The research stands used in this study are 14-16 ha, located on slopes of 5 to 20 percent facing south, southeast or southwest,

and are more than 70 years old. The stands contain 13.8 to 22.9 m*/ha basal area (BA) of merchantable pine and 1.15 to 6.9 m’/ha

of merchantable hardwoods (> 9.0 cm d.b.h.). Stands represent the typical sites managed for timber production on the Ouachita

and Ozark-St. Francis National Forests. For a detailed description of the study areas, stand selection and treatments, etc., see

Baker (1994). Data were collected on all vascular and some nonvascular herbaceous-layer (< 1 m tall) and shrub layer (1 m tall

to 9 cm d.b.h.) plants; midstory and overstory data collection was done by the silvicultural team. Understory plant data were

collected on stands representing four replications of each of the five projected treatments. Treatments are clearcut, shelterwood,

group selection, single tree selection, and control. Data on herbaceous-layer plants were collected during spring (6 weeks from

the beginning of March to mid April), summer (10 weeks from the beginning of May to mid July), and fall (10 weeks from the

beginning of August to mid October). Data on shrubs and saplings < 8.9 cm d.b.h. and all vines were collected once during the

summer period. Although the contract botanists used in this project were skilled at identification of most of the vascular plants

of the region, skills were enhanced through a workshop organized by Dr. Lynn Thompson, University of Arkansas at Monticello

(4 days), to familiarize scientists with techniques for censusing, collecting and identifying ferns and bryophytes so that ferns could

be identified accurately as to species and some mosses and liverworts (as well as some lichens) could be identified to genus or

species. The workshop was conducted by Dr. James Peck of the University of Arkansas at Little Rock and by Dr. Paul Redfearn,

Emeritus Professor of Southwest Missouri State University at Springfield.

Because funding was limited, full pretreatment biodiversity data were collected on only 20 of the 52 stands. More funding

became available, and summer season data were collected on the other 32 stands. Spring, summer, and fall pretreatment data for

the original 20 stands are presented and analyzed here.

On entry to each stand by the botany team, a general reconnaissance was made, and a species list was composed for the stand.

A directed search was made for rare plant species. Two specimens of each species encountered in the study were collected and

will be deposited in a regional herbarium.

The team then sampled flora along transects to assess overall composition of herbaceous-layer flora. A botanist walked along

one side of the transect, noting all species within a strip 2 m wide. These 5 to 7 transects in each of the 20 stands were established

by the wikllife group (see Thill, Tappe and Koerth 1994 for a more detailed description of transects). The transects exclude a 50-m

buffer along the outer boundary of each stand, but otherwise cross all microsites on the stand, including greenbelts. The minimum

distance between transects is 30 m, and the maximum distance is 100 m. Measurements made on transects were cover class by

species.

The most intensive sampling was done within fourteen macroplots which were installed in each stand by the silviculture group.

These macroplots were each 8 m x 16 m (see Guldin and others [ 19941 for a more detailed description of macroplots. At the ends

of each macroplot are two rectangular plots 8 m X 4m = 32 m’. These plots are used for sampling shrub-layer vegetation. There

are four 2 m x 2 m “milacre” microplots per macroplot, two in each of the shrub plots (see Guldin and others [ 19941 for plot

layout). Stem counts by species and diameter class were made on all woody plants taller than 1 m and smaller in d.b.h. than 9

cm in the shrub plots. Size-class d.b.h’s were <2.5 cm; 2.5 to 6.25 cm; and 6.26 to 8.9 cm. The percentage of cover of all plants

< 1 m tall and all herbaceous species regardless of size were estimated by species on the milacre plots (Mueller-Dombois and

Ellenberg 1974). Whereas the dimensions of the plots in this study were set to meet specific needs, the overall layout and sampling

strategy were similar to others previously described (The Nature Conservancy 1988; Ahnendinger 1988). Two macroplots are

located in greenbelt areas (unharvested streamside zones) within each stand, whereas the others were placed within the portion of

the stand where management was to take place.

The cover values from the four microplots within each macroplot were averaged to give a macroplot percent-cover value for

each species. Each species recorded within a macroplot but not measured in a microplot, was arbitrarily given a cover value of

0.01 percent on the plot. Species values for each of the 14 macroplots within each stand were averaged to give a stand mean value

for stand-based analysis, and individual macroplot data were recorded for plot-based analysis. Any species recorded on a transect

or general walk-through of the stand was arbitrarily given a cover value of 0.001 percent in the stand analysis. These values for

species not encountered on the microplots were included in order to ensure that all species encountered in the stands could be

included in all diversity analyses.

Data from the two shrub plots in each macroplot were averaged to provide a macroplot density by species and size class.

Relative frequency of occurrence in macroplots within a stand and relative density and basal area across size classes were averaged

to produce a single importance value for each species in each stand.

Only stand-based analyses are presented here. Plot-based analysis will be undertaken after all data are entered and audited.

51
For this preliminary analysis, species number and mean percent cover were determined for each stand by season and over three

seasons for each stand. Several measures of diversity were computed for each stand, and lists of species from the stands were

compared with those from the region. Also, the intluence of season on species recorded was examined. The latter was done in

order to determine seasonal sampling needs for future years; if three-season sampling is not required, personnel time and expense

could be reduced.

Nomenclature follows Smith (1988).

RESULTS AND DISCUSSION

Total Species

A total of 582 species were recorded in the 20 stands (table 1). This compares with approximately 1,450 species listed for

the westernOuachita Mountain counties of Arkansas by Smith (1988).

Of the 90 species tracked as being rare or otherwise of special concern by the Arkansas Natural Heritage Commission in the

Ouacbita region, one was recorded in the stands, Tradescantia ozarkana. In addition, Penstemon and Antennaria cobea neglecta

were recorded but appear to be misidentifications. Several additional records could be range extensions or new state records if

verified; specimens are being checked.

Table 1. - Species and cove r categories used in understory/sh rub data collection; nearest occurrence of

\ out- of- range species sh ow n in parentheses

Acalyph a sp.

Acalyph a gracilens

Ace r rubrum

Ace r sacch arum

Aesculus sp

Aesculus & bra

Agave virginica

Agrim onia parvtflora

Agrim onia sp

Agrim onia pubescens

Agrim onia rostellata

Agrostis sp.

Agrostis alba = A. gigantea

Allium sp.

Allium canadense

Allium stellatum

Amaryllis family

Am brosia sp.

Am brosia arfim isitfolia

Am brosia bidentata

Am elanch ier arborea

Andropogon sp.

Andropogon elliottii = A. gyrans

Andropogon gerardii

Andropogon virginicus

Anem one sp.

Anem onelia th alictroides = 7h alictrum th alictroides

Antennaria sp.

Antennaria neglecta (mis id?)

Antennaria platagintfolia

Apiaceae

Aplecrum h y em ale

Arabis sp.

Arabia spinosa

Aristida sp.

Aristida dich otom a

Arisiida purpurascens

Aristoloch ia reticulata

Aristolorh ia serpentaria

Asclepias sp.

A.tc1epia.c quadr~ folia

Asclepias tuberosa

As-cleptas l,ariegata

Asclepias viridis

Asim ina triloba

Asplenium sp.

Asplenium platyneuron

Aste r sp.

Aste r drum m ondii = A. corai’folius

Aste r lineanfolius

Aste r novae-angliae

Aste r parviceps (mis id? - Ozarks)

Aste r patens

Aste r subulatus

Asteraceae

Ath yrium filix-fem ina

Aureolaria sp.

Aureolaria gram byora

Avena sativa

Bacopa acum inata

Baptisia sp.

Baptisia leucoph aea = B. bracteaia

Baptisia nuttalliana

Baptisia sph aerocarpon

Bare mineral soil

Bare rock

Berchem ia scandens

Bidens sp.

Bidens polylepis = B. aristosa

Bignonia capreolata

Boltonia di& sa

Botrich ium sp.

Borrych ium bitem atum

Bortych ium dissecturn

Brassica family

Bum elia lanuginosa

Gtcaiia plantaginea

Callicarpa am e ricana

Callirh oe sp.

Calopogon tuberosus

Cam ps0 radicans

Cardam ine concatenata = D e ntaria laciniata

Cardam ine pensylvanica

Care* sp.

Carex caroliniana

Carex ceph aioph ora

52
Table I. - Species and cove r categories used in understory/sh rub data collection; nearest occurrence of

out- of- range species sh ow n in parentheses (continued)

Carex com planala

Carex,flaccospe rm a

Cflrex jrank ii

Care.l- h irsurella = C. com planata var. h irsura

Carex m uh lenbergii

Care.r relroflexa

Carex um b ellala

Carpinus caroliana

Carya sp.

Carya illinoensis

Carya la& niosa

Carya ovala

Carya tom enlosa

Cassia fasciculara = Ch am aecrisla fasciculala

Cassia‘iricrilans = Ch aem icrista niclilans

Caslanea oz ark e nsis = C. pum ila var. oz ark e nsl

Ceanolh us am e ricanu.s

Ceanoth us h e rbaceus

Celri.5 laevigala

Celris occidenralis

C‘e rrirosem a ~ irginianum

Ceph alarrlh us 0ccidenlali.c

Ce rci.s canadensls

Chantrel (mushroom)

C‘h trsm arr/h ium sp.

Ch asm anrh iunr laf~ folirtnr

Ch asm anlh iunr larunr

Ch a.tm arnh ium sessih f7orum

Cicula m aculala

Cinium sp.

Cirsrum alrissrm um

Cir.siunr rarolinianum

Cirsium h orruiulum

Clada.clrus lurea = C. k e nruck e a

Cladonia sp. (lichen)

Cladonra cri.trarella (lichen)

Cladonia suh renuis (lichen)

Clnyronia vrrginiana

Cliloria m ariana

Corcu1u.s carolinu.7

Corrvov111v1c.c sp.

Conyza canaderr.ti.s

Corallorh iz a odonm rh iz a

Co re0p.c i.5 s p

Core0p.ri.s grandiflora

Coreopsis palm ala

Coreop.ris puhescens

Coreopsis rinrloria

Coreosi.s 1ripleri.s

Cornus drum m ondii

Cornus ,florida

Cornus fire rnina

Cra1aegu.c sp.

Cralaegus crus-galli

Cralaegus m ar.th allii

Cru1aegu.s pruinosa

Cratae gus .spath uh ra

Cra1aegu.s viriok

Crolon sp.

Crolorr capila1u.r

Crolonoppsit elliplica

C‘urula origanoides

Cynoglo.w nr sp.

C~~~ rrogloc.sunr vrrginianuni

Cyperu.c sp.

Cyperus e ryfh rorh iz ot

D aclylis glom e rala

D anth onia spicata

D aucu.r sp.

D am -us carola

D e lph inium carolinianum

Desm odium sp.

Desm odium glulinosum

Desmodium h um ifusum (Missouri)

Desm odium m arilandicum

Desm odium nudiflorum

Desm odium och roleucum (M is souri)

Desm odium paniculalum

Desm odium pauciflorum

Desm odium rigidum = D . obrusum

Desm odium rotundifolium

Desm odium virk h jlorum

D icentra cucullaria

D ich ondra repens var. carolinensis

D iclipte ra brach iala

D ioscorea sp.

D ioscorea villosa

D iospyrus virginiana

D odecath e on m eadia

Ech inacea sp.

Ech inacea pallida

Erh inacea purpurea

Eleoch aris sp.

Eleph antopw lom enlosa

E1ym u.s sp.

h ’lym us canadensis

Blym us glaucus

Elym us riparius

Elymus villosus

Elym us virginicus

Equiselum sp.

Erech rires h ieracnfolia

Erianrh us conform s

Erigeron annuus

Erige ron strigosus

Erigonum sp.

Eryngium yuccifolium

Euonymous sp.

Euonymus am e ricanus

Euonym us atropurpureus

Euparorium sp.

Euparorium album

h upalorium coeleslinum

Eupalorium perfoliatum

h upatorium ronm difloium var. pubescens

Eupatorium serolinum

Euph orbia sp.

Euph orbia corollala

Fernmoss

Fe.rruca elatior = F. arund inacea

Foliose lichen

1:ragaria virginiana

Fraxinus sp.

Fraxinus am e ricana

Fraxinus pennsylvanica

Galacrira volubilis = G. regularis

Galium sp.

Galium ark ansanurn

Galium circaezans

Galium obru.r.rum

(Talium pilosum

Caliunr rin crorium

53
Table 1. - Species and cove r categories used in understory/sh rub data collection; nearest occurrence of

out- of- range species sh ow n in parentheses (continue d)

Galium trifrorum

Geranium m aculatum

Gerardia sp. = Agaiinis sp.

Geum sp.

Geum canadense

Gillenia sp. = Porte ranth us sp.

Gillenia .rtipulata = Porte ranth us stipu1atu.r

Gnaph alium sp.

Gnaph e lium obtusifolium

Gnaph e lium purpureum

H edyotis sp. ’

H edyotis crassifalia

H edyotis longifolia

H edyotis m inim a (Missouri)

lledyotis nigricans

H edyotis purpurea

Helenium flexuosum

H elenium nudiflorum = H . ,flexuosum ?

JIelianth us sp.

Jielianth us ongustijolius

JJelianth us divuricatus

H elianth us h irsutus

H elianth us m icroceph alus

H ete roth e ca gram inifolia

H ete roth e ca pilosa = Ch rysopsis pilosa

H euchem am e rirana

Heuchera americanu

Hieraciunr sp.

FIieracium gronovii

H ydrororyle sp.

H ypericum sp.

JJypericum h ypericoides

H ypericum m utilum

Ilypericum perj?orfltum

H ypericum spath ulatum = H . proltj?cum

H ypericum .rtuns

H ypo.ris h irsuta

l1e.r decidua

1le.x opaca

Jlex vom itoria

Jm patiens sp.

Im patiens capen7i.r

lndigofe ra m iniata

Ipom ea sp.

Iris sp.

Iris cristata

.Juncus sp.

Juncus baltirus

Juncus @usus

.Juncus .secundus

.Jurrcus tenuis

Juniperus virginiana

Kick sia elutine

Krigin sp.

Krigin ctnnd elion

Kuh nia euputorioides = Brick e llia eupatorig

Lahiatae

Juctuca sp.

Lacluca jloridana

I*lctucaJloridana w r. lillo.ta

I*lctucrt h irsuta

Iam ium sp.

Jxrh e a tenuifolia

Lem nn sp.

Lespedeza sp.

Lespedezu cuneata

vi& s

Lecpedez rt h irta

Lespedeza inte rm edia

Lespedeza procum bens

IAspedezrc repens

Lespedeza striula

Lespedezu .rruevei

Lespedezn violureu

Lespedezu virginira

Leurobryum sp. (moss)

Liatri.s sp.

Liatris a.rpera

Liatris elegari.7

Liatris pycnostach ya

Liatris squarro.~ a

Lichen

Ligustrum .tinen.re

Ligustrum vulgare

Lindera benzoin

Linum m edium

Linum virginianurn (Louisiana)

Liq uidam bur .rtyracQluu

Litter

Lobelia sp.

Lobelia puberula

Lobelia .spirata

Lonire ru sp.

Lonice ra ulh o (Oklahoma)

Lonice ra japonicu

Lorinserin (W oodw ardiu) areolata

Ludw igiu crlrern~ folia

Luz ula bulbosa

Lycopodium sp.

Lysim uch ia sp.

Lysim arh ilirr riliuta

Lysim arh iu q uudrijolin

Mateleu sp.

Melica mutica

Mimulus alatus

Mitchella repens

Monarda sp.

Monarda$.~ tulosa

M ona& russeliana

M ona& .stipitatoglandulosa

Monotropa h ypopith ys

M onotropa unifrora

Morus rubra

Moss

M uh lenbergia sp.

M uh lenbergiu rapillaris

M uh lenh e rgiu sobolife ra

Mushrooms

M yrira re rife ra

Nyssa aq uatirn

Nyssa sylvatira

O enoth e ru ~ fruitirosa

Onorlea .serrsibilis

Open water

Oph ioglossum petiolatum

O puntia com pressa = 0. h um @sa

O.sm urrdu sp.

O stvu virginiflna

Oxalis strirta

0.xali.s violncea

Punirum sp.

Panicum nrirulure = P. angusrifolium

Panicum 0nrep.r

54
Table 1. - Species and cove r categories used in understoryk h rub data collection; nearest occurrence of

out- of- range species sh ow n in parentheses (continued)

Panicum h ick nellii = P. linear~ folium

Panicum h oscii

Panicum com m ufatunr

Panicum dich otom t~ orum

Panicunr dich otom unl

Panicum h ians

Panicum lat{folium

Panicunr laxtjlorum

Panicum lineart~ olium

Panicum obtusum

Patti& ph iladelph icunr

Panicum polyanthes

Panicunr sph aerorarpon

Panicunr villosissim um

Parth e nium h ispidum = P. integr(folium v. h ispidum

Parth e nium integrtfolium

Parth e nium sp.

Parth e nocissus q uinq uefolia

Parth e nocissus vitaceae

Paspalum floridanum

Passtjlora lutea

Pedicularis canadensis

Penstem ort sp.

Penstem on ark ansanus

Penstem on cobea (mis id?)

Penstem on digitalis

Penslem on pallidus

Petalostem on sp.

Ph lox sp.

Ph lox pilosa

Ph oradendron serotinum

Ph yllanth us sp.

Ph yllanth us polygonoides

Ph ysalis sp.

Ph ysostegia virginiana

Ph ytolacca am e ricana

Pinus ech inata

Piatanth e ra cilian’s

Platanth e ra lace ra

P& anus occidentalis

Pluch e a cam ph orata

Poa sp.

Podoph yllum peltatum

Polygala sp.

Polygala ve rticillata

Polygonum sp.

Polygonum h ydropipe roides

Polygortum punctatum

Polypodium sp.

Polypodium polypodioides

Polystich um sp.

Polystich um acrostich oides

Polytrich um sp.

Potentilla sp.

Potentilia recta

Prenanthes altissim a

Prunella vulgaris

Prw rus sp.

Prunus am e ricana

Prmu.7 m esicana

Pruttus s erotina

P.soralea sp.

Psoralea psoralioides

Pte ridium sp.

Pte ridium aq uilinum

Pycnnnthem um sp

Pycnanthem um albescens

Pycnanthem um tenuifolium

Pycnanthem um virginianurn

Quercus sp.

Quercus alba

Quercus falcata

Quercus im bricaria

Quercus m arilandica

Quercus nigra

Quercus ph e llos

Quercus prinoides

Quercus rubra

Quercus sh um ardii

Quercus stellata

Quercus velutina

R atibida pinnata

R h am nus caroliniana

R h ododendron prinoph yllum

R h us arom atica

R h us copallina

R h us glabra

R h ynch osia latifolia

R h yncospora sp.

R obinia pseudo-acacia

R osa sp.

R osa Carolina

R osa setigera

Rubus sp.

Rubus trivialis

R udbeck ia sp.

R udbeck ia fulgida

R udbeck ia gratub~ ora

R uabeck ia h irta

R udbeck ia triloba

R uellia h um ilis

R uellia sp.

R uellia pedunculata

R uellia strepens

Sabatia angularis

Salix sp.

Salvia az urae

Salvia lyrata

Sam bucus canadensis

Sanicula canadensis

Sanicula gregaria = S. odoram

Sassafras albidum

Satureja sp.

Sch iz ach yrium scoparium = Andropogon scopan’us

Sch rank ia nutlallii

Scitpus atrovirens

Scle ria sp.

Scle ria ciliala

Scle ria oliganth a

Scle ria triglom e rata

Scutellaria sp.

Scutelh w ia elliplica

Scutellaria ovata

Senecio sp.

Senecio obovatus

Senecio tom entosus

Silene virginica

Silph ium sp.

Silph ium laciniatum

Sisyrinch ium sp.

Sisirinch ium angustifolium

Sisyrinch ium cam pestre

55
Table 1. - Species and cover categories used in understory/sh rub d ata collection; nearest occurre nce of

out-of-range species sh ow n in parenth eses (continued)

Sm itacina racem osa = M aianthem um paniculatum

sm ilax sp.

Smilar aun’culata

Sm ile r bona-no*

Sm ilax glauca

Sm ilax h e rbacea

sm ih lx pum ila

Sm ilax rotundifolia

Solanum sp.

So&urn caroh nense

Solidago sp.

Solidago canadensis

Solidago leptoceph ala = Euch am ia leptoceph ala

Solidago odora

Solidago rugosa

Solidago ultn~ olia

Sorgh um h alepense

Sph agnum sp. (moss)

Spilanthes am e ricana = Acm ella oppositifolia

Spiranthes sp.

Spiranthes cem ua

Spiranthes ovalis

Spiranthes cuberosa

Sporobolus sp.

Sporobolus asper

Stach ys sp.

Stipa sp.

Stipa avenacea

Stipa spartea (Missouri)

Scroph ostyles sp.

Stroph ostyles leiospenna

Stylosanthes sp.

Stylosanches btpora

Sym ph oricarpos orbiculatus

Taraxacum oJicinale

Teph rosia virginiana

T7telespenna~ lijolium

Tilia am en’cana

Tipularia discolor

Toxicodendron sp.

Toxicodendron radicans

Tracelospennum dtrorm e

Tradescantia sp.

Tradesrantia oh iensis

Tradescantia oz ark ana

Tn’dens flaw s

Trt~ olium sp.

Tnifolium h ybridum

Trtyolium repens

Triodanis biflora = T. pe rfoliata var. btpora

Triodanis perfoliata

Ulm us sp.

Ulm us alata

Ulm us rubra

Unidentified

Unidentified Gramineae

Unidentified gymnosperm

Unidentified Laminaceae

Unidentified monocot

Unidified Leguminosae

Umula sp. (fungus)

Urn& a crate rium (fungus)

Vaccinium arboreum

Vaccinium pallidurn

Vaccinium sp.

Vaccinium scam ineum

Ve rbena canaafensis = Glanaitlaria canadensis

Ve rbena sp.

Ve rbesina altem ifolia

Ve rbesina h e lianth oides

Ve rbesina virginica

Vem onia lette rm anii

Vem onia sp.

Ve ronica sp.

Ve ronicasttum virginicum

Viburnum sp.

Viburnum r@dulum

Vicia sp.

Vicia caroliniana

Vicia villosa

Viola sp.

Viola palm ata

Viola pedata

Viola prim ulifolia

Viola pubescens

Viola sagittata

Viola sororia

Viola striata

Viola viarum

Vicis sp.

Vitis aestivalis

Vitis rotundifolia

W oodsia sp.

W oodsia obcusa

Yucca sp.

Z izia apte ra

Z iz ia aurea

56
Seasonal Influence

Data were collected in three seasons to capture ephemeral species. The periods were March-April, June-July, and SeptemberOctober. There is a seasonal influence; in no single season was as much as 80 percent of the total flora recorded (table 2). The

summer sample was most comprehensive, with 76 percent of the total flora. At the other extreme, the spring sample included only

44 percent. Each season contributed species not found in any other season, with 21 percent of the total occurring only in the

summer; each of the other seasons contributed only about half as many (table 2). When considered as season pairs, summer/fall

and summer/spring each produced approximately 90 percent of the total, whereas spring/fall produced about 10 percent fewer

species (table 2).

Table 2. - Total species per season, total species encounte red in each pair

of seasons, and species occurring uniq uely in only one season.

Single Season Totals (Percent)

Spring Summer Fall

Total Spp. 256 (44) 443 (76) 368 (63)

Unique Spp. 60 (10) 123 (21) 72 (13)

Season Pairs Num. Spp. (Percent)

Spring/Summer

Summer/Fall

Spring/Fall

510 (88)

522 (90)

459 (79)

From this analysis it appears that three season sampling is necessary to assess plant biodiversity because at a maximum, only

76 percent of the species recorded in this study occurred in any one sample season, If only one season of sampling were possible,

it should be summer, with fall as a second choice and spring as the last choice. With two samples, one in summer and one in either

spring or fall will increase the species encountered to about 90 percent.

Stand Analysis Of Ground Cover Species

Species per stand ranged from 123 to 238 with a mean of 176 (table 3). Total area1 ground cover of each stand in percent (sum

of individual species values) ranged from 12.78 to 32.37 with a mean of 21.08 percent.

Diversity of the stands was investigated using H’, the Shannon Diversity Index. This index is based on information theory,

with larger values equal to greater uncertainty about the identity of a species drawn at random from the population. It has a

minimum value of zero if only one species is present and a maximum value of

H(max) = In (S)

where: S = number of species. It achieves the maximum value when ah species have equal abundance. Jn the stands in this study

H’ ranged from 1.94 to 3.78 with a mean of 3.19 (table 3).

Because the maximum value of the Shannon index varies with the number of species per stand and the number of species per

stand in our study varies, it is useful to use the ratio

J’ = H’/H(max).

This ratio varies from 0 to 1. It measures the relative evenness or diversity. hi our stands it ranged from 0.403 to 0.739 (40

percent to 74 percent of maximum evenness) with a mean of 0.618 (62 percent of maximum) (table 3).

5 7
Table 3. - Stand sum m uries offoristic dutu. SP is num b er of

species per stand, CV is totul percent cove r (sum of

individual species v& es), H ’ is the Sh annon Dive rsity Index and 1’ is H ’/H (nuu).

STAND SP CV H ’ J’

2310 19 1 20.08 3.09 0.588

2701 19 9 14.45 3.32 0.628

3551 206 12.78 3.67 0.688

4618 203 15.9 7 3.44 0.648

6206 143 16.67 3.38 0.680

7010 175 16.51 3.07 0.59 4

24817 152 32.16 3.35 0.668

28411 178 32.37 3.37 0.650

45712 171 14.55 3.78 0.739

45816 176 18.86 3.67 0.711

60505 206 20.03 2.81 0.529

609 09 238 28.26 3.56 0.651

83301 147 25.28 3.20 0.642

89 607 140 29 .53 2.52 0.509

106715 123 21.77 1.9 4 0.403

1119 51 208 23.60 3.23 0.605

112411 19 5 27.62 2.9 8 0.565

129 202 145 14.56 3.66 0.735

1649 13 19 3 19 .18 3.35 0.636

165805 138 17.35 2.41 0.488

LOW 123 12.78 1.9 4 0.403

H IGH 238 32.37 3.78 0.739

MEAN 176 21.08 3.19 0.618

S.D. 29 .87 06.04 0.45 0.084

Measures of species abundance are contrasted in figures 1 and 2. Ove r h alf th e species recorded in this study occur in ouly

1, 2, or 3 stands (fig. 1). However, over half the area1 cover (13 percent out of the 2lpercent average) is provided by the species

that occur in all 20 stands (fig. 2). In contrast to the analysis of seasonal sampling needs, relatively few samples are required to

characterize those species that exert community control through cover, biomass, competition, etc., because over half of the total

cover measured in this study was produced by species that occurred in all stands.

This preliminary analysis of the understory plant communities of these stands demonstrates that south-facing, pinedominated

stands in the Ouachita Mountains are moderately diverse in that they contain 40 percent of the species found in the region as a

whole and have a relatively even proportion of the species that occur there. However, they have few regionally rare species.

ACKNOWLEDGMENTS

Field work on this project was done by contract botanists John Logan, Newell McCarty, Larry Magrath, Seth Barnes, aud

Jimmy Baker, along with USDA Forest Service Southern Forest Experiment Station botanist Alton Martin. The high quality of

their work was responsible for the success of this project.

58
mlrnoI

7 9 11 13 15 17 19

Stands per Species

Figure I. - Num b er of species occurring in a specified num b er of stands.

2 --

1-t

Ol 3

1 I1-rI I, -II t

9 II 13 15 17 19

Species by Frequency of Occurrence

Figure 2. - Ave rage percent cove r of all stands contributed by species th at occurred in a specified num b er of stands. Ave rage

percent cove r of all stands (sum of ind ividual species values) is 21 pe rcent.

59
LITERATURE CITATIONS

Almendinger, John C. 1988. A handbook for collecting releve data in Minnesota. Minneapolis, MN: Department of Natural

Resources, Minnesota Natural Heritage Program.

Baker, James B. 1994. An overview of stand-level ecosystem management in the Ouachita/Ozark National Forests. In: Baker,

James B. 1994. Proceedings of a symposium on ecosystem management research in the Ouachita Mountains: pretreannent

conditions and preliminary findings. New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest

Expperiment Station.

Causten, D.R. 1988. Introduction to vegetation analysis. London: Unwin Hyman. 342 p.

Gukhn, James. M.; Baker, J.B.; Shelton, M.S.; 1994. Pretreatment conditions in mature pine/hardwood stands on south-facing

slopes of the Ouachita National Forests: midstory and overstory plants. In: Baker, James B. 1994. Proceedings of a

symposium on ecosystem management research in the Onachita Mountains: pretreatment conditions and preliminary findings.

New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Expperiment Station.

Magurran, A.E. 1988. Ecological diversity and its measurement. Princeton NJ: Princeton University Press. 67 p.

Mueller-Dombois, D.; Ellenberg, H. 1974. Aims and methods of vegetation ecology. New York: John Wiley and Sons. 547 p.

The Nature Conservancy. 1988. Community Survey Handbook. Arlington, VA: The Nature Conservancy.

Smith E.B. 1988. Atlas and Annotated List of the Vascular Plants of Arkansas. Fayetteville, AR: Privately published. 489 p.

Thill, Ronald E.; Tappe, Philip A.; Koerth, Nancy E. 1994. Wildlife habitat conditions in mature pine-hardwood stands in the

Ouachita/Ozark National Forests. In: Baker, James B. 1994. Proceedings of a symposium on ecosystem management

research in the Ouachita Mountains: pretreatment conditions and preliminary findings. New Orleans, LA: U.S. Department

of Agriculture, Forest Service, Southern Forest Expperiment Station.

Whittaker, R. H.. 1956. Vegetation of the Great Smoky Mountains. Ecol. Mon. 26(l): l-80.

60
Multivariate Analysis of the Ground Cover Layer, Shrub Layer, Midstory, and Overstory

of the Ouachita/Ozark National Forests’

Thomas L. Foti and James M. Guldin%’

ABSTRACT

Data from nested samples of ground cover, shrub, midstory, and overstory vegetation were

used to study the floristic composition and structure in stands on south- and southwest-facing

slopes in the Ouachita Mountains. Preliminary analyses reduced the data set to 162 species

(109 ground cover, 32 shrub, 15 midstory, and 6 overstory species variables) and 20 site

variables from 20 stands. Correlation analysis, principal components analysis, and

regression analysis were used to identify major species associations and site relationships.

Three species associations were identified from the correlation analysis-one characterized

by shortleaf pine (Pinus echinara Mill.), another by mesic oak species such as white oak

(Quercus alba L.), and a third by xeric oak species such as post oak (Q. stellara Wang.).

Principal components analysis of the 162-variable data set resulted in a geographic

interpretation of the pattern of stand composition. Regression of the first 3 principal

component axes resulting from the 162-variable data set versus site variables produced the

better geographic explanation, whereas regression of the principal component axes from the

21-variable midstory and overstory data set versus the 162~species data set gave the better

interpretation of vegetation. Although stand-based comparisons are used in this initial

exploration, plot-level studies hold even more promise because the stands are not uniform

expanses of a single slope, aspect, and community. These analyses could be made more

interesting through addition of data from other groups.

INTRODUCTION

Most of the studies presented in this symposium concentrate on a single taxonomic, structural, or functional component

presented at the stand-level scale. Though this approach has been effective at this scale, patterns at wider scales may be

missed. Combining data among groups offers the opportunity to address larger landscape scale issues immediately.

One intent of the present paper is to explore patterns that result when stands are considered samples of a set of related

communities or site types occurring over a large geographic area. This type of analysis has particular merit in this research,

given that the stands included in the study were selected randomly within the following set of narrow constraints: (1) stands

were limited to pine and pine-hardwood stands on south- to southwest-facing slopes, (2) stands had to meet preestablished

age and basal area criteria, and (3) future treatments were blocked geographically.

This paper also represents the first effort to aggregate several of the taxonomic and structural elements being otherwise

treated in separate studies by distinct research groups. Because of the physical and computational logistics involved in

combining data, and because much of the data from individual studies are not yet in final form, this study has concentrated

on merging the ground cover and shrub layer data with the midstory and overstory data. Data were combined for the 20

stands in which 3-season ground cover and shrub estimates were taken (Foti and Devall 1994). This represents the first fruit

of efforts between the silviculture group and understory vegetation group that began with the development of a nested sample

procedure designed expressly to enable such comparisons (Guldin and others 1994).

The goal of this paper is to explore the interrelationships of the ground cover, shrub, midstory, and overstory vegetation

elements, in order to develop a conceptual model of floristic composition and structure of the forest plant community found

on south- and southwest-facing slopes in the Ouachita Mountains.

I Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1994.

2 Chief of research, Arkansas Natural Heritage Commission, Little Rock, AR, 72201; Research forest ecologist and

Silviculture Group leader, USDA Forest Service, Southern Forest Experiment Station, Hot Springs, AR, 71902.

3 The authors extend their thanks to Dr. A.A. Karlin, Department of Biology, University of Arkansas at Little Rock, Little

Rock AR, without whose generous and altruistic support this paper would not have been possible.

61
METHODS

Development of the Data Set

Data were obtained and summarized as described in Foti and Devall (1994) and Guldin and others (1994). Canopy

layers included in this analysis are as defined in those papers, and include the ground cover layer, the shrub layer, the

midstory layer, and the overstory layer.

The overstory and midstory data were combined with shrub and ground cover data additively by layer, in the following

manner. In the ground cover layer, percent cover was determined for each species, based on averaging the spring, summer,

and fall measurement percent cover estimates for each species across all stands (Foti and Devall 1994). These estimates were

then directly applied as input to the analysis, so that the variables for the ground-cover species are based on percent cover.

In the shrub layer, importance values for each species were calculated based on relative density (based on number of stems

per acre) ‘and relative dominance (by percent cover) during each sample season; the final importance value was derived as

the average of the importance values for all three sample seasons. In the midstory and overstory layers, the importance value

for each species was calculated as the average of relative density (based on number of stems per acre) and relative dominance

(based on basal area per acre) across all twenty “non-split” stands (Guldin and others 1994). The variables for the shrub,

midstory, and overstory layers, then, are the importance values for each species by layer. In this manner, a total of 699

species variables were included in the preliminary analysis-579 in the ground cover layer, 81 in the shrub layer, 24 in the

midstory layer, and 15 in the overstory layer.

The size of this data base is at the least ungainly, and leads to an unacceptable ratio between observations and variables

for the multivariate analysis. Memory limitations in PC-SAS dictated the need for alternative analytical tools, so the data

were installed on a VAX minicomputer at the Eiology Department of the University of Arkansas at Little Rock and the

analysis was continued there. Despite the shift to the larger computer, the 699-variable data set generated a correlation

matrix that exceeded the available memory allocation, locked up the computer, and led to an acquaintance with a graduate

student with system privileges. Therefore, for both theoretical and practical reasons, it was decided to edit the data so that

only a subset of the 699 species variables were retained for analysis.

Editing the data proceeded as follows. Of the 579 ground cover layer species, over 100 were recorded as having only

a trace occurrence; other species had trace values in the other layers as well. While important in a larger analysis, trace

occurrences confound attempts to make sense of the larger patterns in the data base because of the inherent lack of ecological

distance between species with trace values relative to that between common species.

The number of species in the analysis was arbitrarily reduced based on the summed percent cover or importance value

across all 20 stands. Thresholds of percent cover or importance value were subjectively established by layer. In the ground

cover layer, species were retained if their average percent cover per stand exceeded 0.02 percent; this resulted in including

109 of the 579 species (19 percent) in this analysis. In the shrub, midstory, and overstory layers, species were retained if

their average importance value exceeded 0.5 on a 0 to 100 scale; this resulted in retaining 32 (40 percent) of the shrub

species, 15 (62 percent) of the midstory species, and 6 (40 percent) of the overstory species. The final data base upon which

this analysis is based thus includes 162 species variables. See appendix table 1 for variable codes, scientific names (including

authorities), families, and common names by vegetation layer.

The site variables obtained by the silviculture group and the understory biodiversity group were also merged (Guldin

and others 1994, Foti and Devall 1994). These SeNed as input establishing the average condition for the stands in the study,

associated with values for the species (appendix table 2). As a result, we were able to explore the relationships of the 162-

species data base in relation to the 20-variable site parameter data base.

Statistical Analysis

Relationships between the vegetation data and the site data were studied using correlation analyses, principal components

analyses, and regression analyses.

Correlations were developed between the midstory and overstory against all 162 species. Supplemental correlations

between species of interest in the shrub and ground cover layers were also conducted. This approach should provide insight

into composition of plant communities or species assemblages within them. In order to concentrate attention on patterns

rather than the erroneous occasional “statistically significant” relationships that are to be expected in any large correlation

analysis, only those significant relationships that occurred consistently among a set of variables were sought.

Determination of patterns among the data was done as follows. First, significant correlations among overstory and

midstory variables were identified. Then, the correlations between these correlated overstory and midstory variables and

the all-layer list were examined to determine whether two species significantly correlated (either positively or negatively)

with each other were also correlated with a third species in the all-layer list. In this way, only those species showing

consistent patterns of correlations were identified.

62
Principal components analysis (PCA) was conducted to analyze patterns of stand association based on vegetation. With

this technique, assuming II variables, stands are ordered along a series of n axes called principal components (PCs), in which

the first axis accounts for the largest proportion of variation in the data, and subsequent axes account for orthogonal

relationships from the previous axis (SAS Institute 1990). Two arrangements of the data were analyzed using this

method-first, all canopy layers (162 species variables), and second, only the overstory and midstory layers (21 species

variables). Results from the PCA are generated as scores for each stand along each principal component axis.

These scores were used as dependent variables in either stepwise or MAXR regression analysis (SAS Institute 1990) as

follows. The first three PC axes resulting from the 162-species data set and the 21-species data set were regressed against

2 sets of independent variables -- the 162-species data set and the 20-variable data set of site parameters. The purpose of

these regressions was to elucidate information regarding the relationships of the PC axes with the species and site data.

In combination, these complementary and interrelated analyses were used explore the ecological relationships in the data.

The combinations of insights resulting from the analyses presented here provide evidence of community floristics and the

arrangement of stands relative to the prevailing patterns in vegetation and site variables.

RESULTS

Correlation Analysis

One set of overstory and midstory species variables showing consistent patterns of correlations are the pines and oaks.

Overstory shortleaf pine is positively correlated with midstory shortleaf pine; these form one species association. These two

are negatively correlated with overstory white oak, northern red oak, and water oak, and with midstory northern red oak;

the oaks form a second association. In order to examine relationships between these species and other species variables from

the all-layer list, any species included in the analysis were required to share significant correlations with five of these six

midstory and overstory species.

Nine of the 162 species were significantly correlated with at least 5 of these 6 overstory and midstory species (table 1).

In each case the ground cover species are positively correlated with the oaks and negatively correlated with pine. The ground

cover variables are northern red oak, flowering dogwood, panic grass, tick trefoil, dittany, Aristolochia serpentaria, Galium

sp., total moss cover and total unidentified grass cover.

Table 1. - Correlation matrix of overstory and midstory species variables showing consistent signtftcant correlations vs. each

other and other species variables. Species codes are defined in appendix table 1. Codes ending in 4 indicate

overstory, 3 indicate midstory, 2 indicate shrub layer, and those without a number are ground cover. lhe

direction of the correlation is shown as positive (+) or negative (-)

Oth e r

_____________________________ Ove rstory and m idstory species variables + _______-__________~ _

species

variables * QUEALB4 QUERUB4 QUENIG4 QUERUB3 PINECH 4 PINECH 3

QUERU B + + + +

PANBOS + + + +

MOSS + + + +

DESNUD + + + +

GALSPP “.s. + + +

GRASS “.s. + + +

CO R FLO + + + +

CUNOR I + + + + n.s.

ARISER + + + +

l Spe cies variables defined in appendix table 1.

A third set of related species emerged using this analysis. Overstory post oak was not significantly correlated with most

of the species presented in table 1, but was positively correlated with midstory post oak. These were found to be positively

correlated with five ground-cover species and two shrub-layer species, and negatively correlated with three midstory species

(table 2). In each case these species had the same relationship (positive or negative) with both overstory and midstory post

oak. The midstory associates were white oak, water oak and blackgum; shrub layer associates are blackjack oak and winged

elm, and ground cover species were bird’s_foot violet, phlox, Coreopsispalmata and poverty oatgrass. Unidentified ground

cover layer oak species were also positively correlated.

6 3
Table 2.- Correlation matrix of species variables showing consistent correlations vs. each other and other species variables.

Species codes are defined in appendix table 1. Codes ending in 4 indicate overstory, 3 indicate midrtory, 2

indicate shrub layer, and those without a number are ground cover. i’he direction of the correlation is shown

as positive (+) or negative (-)

Other

species

variables *

Overstory and midstory species variables +

QUESTM QUBSTU

QUENIGJ

QUEALBJ

NYSSYL3

QUEMAR2 + +

ULMALAZ + +

VIOPED + +

PHLPIL + +

CORPAL + +

DANSPI + +

QUESPP + +

+ Species variables defined in appendix table 1.

Principal components analysis

In order to interpret the results of the PCA, it is helpful to have an understanding of the orientation of the 20 stands in

the data base. The most easily visualized pattern is the geographic location of the stands. Thus, for purposes of comparison,

stands were plotted according to their Universal Transverse Mercator (UTM) coordinates for latitude and longitude (fig. 1).

Figure l.-

3’goo’ooo I---- Mag46

Mag70

3.880.000 t

E

Q

2 3.860.000

z

s

g

2 3.&40,000

zz

5

3,820,OOO

3.800.000

Cho Pot Mena

62 1292 833

CSP

284 Fou458

Fowl57

Jes605

Oden Jes609

1067

Kia Mena

248 896

OdenIl

Oden1124

Worn1 658

Worn1649

Cad35

Cad23

340,000 360,300 380,000 4Gu ,000 420 ,OW 440,000 460 ,M30 480,ooo

UTM East longitude, m

Geographic distribution of 20 stands in the study, based on Cartesian plot of Universal Transverse Mercator

coordinates. Stands identified by compartment number and ranger district acronym, as follows: Cad-Caddo

RLI; Cho-Choctaw RLI; CSp-Cold Springs RD; Fou-Fourche RD; Jes-Jessieville RLI; Kia-Kiamichi RLI;

Mag-Mt. Magazine RLI; Mena-Mena RLI; Oden-Oden RLI; Worn-Womble RD.

64
Th e PCA of th e 21-variable ove rstory and m idstory laye rs resulted in th e first th ree PC axes explaining 56.1 pe rcent

of th e variation in th e d ata set. Graph s of PC axes 1 and 2, and axes 1 and 3, are presented in figures 2a and 2b,

respectively. Th ese graph s reveal no obvious relationsh ip w ith th e geograph ic location of stands (fig. 1). Th e Mag46 stand ,

th e north e rnm ost stand in th e data set, is found at one e nd of PC axes 1 and 2, but th e arrangem ents of th e oth e r stands on

th e axes appear to be influenced by factors oth e r th an geograph ic association.

Figure 2.- Principal components (PCs) analysis of 20 stana? in the study based on overstory and midrtory vegetation layers

only. Standr identified as in figure 1. a. Principal component axis I versus principal component axis 2. b.

Principal component axis 1 versus principal component axis 3.

a.

2 -- l

Oden1067 Worn1 658

Jes605 Cad27 Kia248

Cad35

c.lo Mag70 Odenl119

5 .Jes609 ruz7 Mena

: Cho62 Worn1649

_2 _.Potl 2g2 OdenIl

-4 -- Mag46

-6 I 1 I I

b. 4

2

-4 -2 0 &is 4 6 8

PC 1

Oden CSp284

Cad27

00 -Mena

Fou Mena $ _;;;,‘,“2 45 8 Oder 1067

Kia248

x-2 --

Jes605

Cad35’

Worn1 658

Mag46

-6 I I 1 I

-4 -2 0 2 4 6 8

PC Axis 1

65
The PCA of all canopy layers resulted in the first three PC axes explaining 39.0 percent of the variation in the data set.

Graphs of PC axes 1 and 2, and axes 1 and 3, are presented in figures 3a and 3b, respectively. These graphs relate more

easily to geographic position (fig. 1). For example, the easternmost stands (Caddo, Jessieville, and Fourche) lie in the (-,-)

quadrant of the plot of PC axes 1 and 2, the westernmost stands (Choctaw and Poteau) lie in the (+ ,-) quadrant, and most

of the centrally-located stands are found in the positive half of PC axis 2. The third PC axis adds little to the interpretation.

Figure 3. - Principal components (PCs) analysis of 20 star& in the study based on all vegetation layers (162 species).

Stat& identified as infigure 1. a. Principal component axis I versus principal component axis 2. b. Principal

component axis 1 versus principal component axis 3.

a. 10

CSp284

El --

6 --

Mag46 Mena Oden

896 1124

4 "Odenlll9 Kia248 Mena

N I--

Worn1 649 I

.v, Worn

&! o--CadCad27-- 1658

Mag70

kf _2 __ 23 Cad35

Fou457

-4 -- Fowl58

Oden1067

-6 -- Jes609

Pot1 292

Cho62

a --

Jes605

-10 -' ; , I i i II II II 10 II

-6 -4 -2 0 2 4 6 a 10 12

PC Axis 1

b.

Oden

1124

Mena

-6 -4 -2 0

;c Awls41

6 8 10 12

66
Regression Analysis

The first set of regression analyses were conducted to relate the PCA axis scores with the site data, to study underlying

site relationships.

For the overstory-midstory PCA, stepwise regression analysis produced a four-variable model for PC axis 1, a threevariable model for PC axis 2, and a two-variable model for PC axis 3 (table 3). In each model, variables related to site

quality are significant and carry positive influence. It was previously noted that slope percent, site quality, and site index

differ by block in the full 52-stand data set (Guldin and others 1994), with higher slope percent in the north and south blocks,

and higher site index and site quality in the south and east block plots. These PC models may therefore reflect a previouslyobserved block effect.

Table 3.- Results porn SAS stepwise regression analysis to regress principal components vs. measured site variables.

Results indicate the site variables within each layer most related to the principal components. All variables in

the model are sign@icant at the 0.05 level

Dependent

variable

Principal components derived from

overstory and midstory cover canopy

layers only

Principal components derived from

overstory, midstory, shrub, and ground

cover canopy layers

A. PC Axis 1 Y = -24.13355 Y = -23.88073

i- 0.02538 l AZDEG - 3.36549 * SQ

-I- 0.23268 * SLPCT + 6.01906 * MRT

-I- 0.27543 * COVER - 0.0000876 + UTMET

i- 2.41958 l SQ + 0.52080 + LlTrER

R2 = 80.9 percent R2 = 80.0 percent

P(>F) = 0.0005 P(>F) = 0.0001

B. PC Axis 2

C. PC Axis 3

Y = -4.50040

i- 0.18096 * SLPfl

-I- 0.17256 * SX

- 5.51607 MSS *

R2 = 55.7 percent

P(>F) = 0.0039

Y = -89.97034

+ 3.86398 * SLOPOS

+ 0.59229 l COVER

+ 0.32468 HGT l

+ 0.45057 * ROCK

R2 = 85.0 percent

P(>F) = 0.0001

Y = -6.39313

+ 2.70794 * SQ

- 22.00791 * WATER

R2 = 46.3 percent

P(>F) = 0.0051

Y = -15.74287

+ 11.49851 * MRT

- 3.79540 SOIL +

- 0.70772 ROCK *

R2 = 62.2 percent

P(>F) = 0.0011

For the all-layer PCA, stepwise regression analysis produced a four-variable model for PC axis 1, a four-variable model

for PC axis 2, and a three-variable model for PC axis 3 (table 4). The prominence of UTMET in axis 1 of the overstorymidstory PCA is consistent with the geographic relationships for the all-layer PCA presented in figure 2. The second PC

axis presents a positive relationship with variables that relate to high site productivity (more protected slope position, higher

percent cover, and greater height), but these are at odds with an increasing percentage of rock.

In the second set of regression analyses, the search for community relationships centered on models of the PC axes with

species variables. In the all-layer PCA, regression of the first two axes against the 162-species all-layer data set resulted

in models that contained no midstory or overstory species (table 4). The first axis model includes positive association for

both shrub and ground cover layers of oaks, tick trefoil species, and negative association for greenbrier. The second includes

mockemut hickory (+) and birds-foot violet (-) in the ground cover layer, and winged elm and red maple (both +) in the

shrub layer. The only midstory and overstory species that appear in the regression occur in PC axis 3, with the inclusion

of midstory water oak.

6 7
Table 4.- Results from SAS MAXR regression analysis to regress overstory-midstory principal component axes and all-layer

principal component axes versus all-layer (162) species variables. Results indicate the species within each layer

most related to the principal components. All variables in the model are significant at the 0.05 level

Dependent Principal components derived from overstory and

variable midstory canopy layers.

Principal components derived from overstory,

midstory, shrub, and ground cover canopy layers.

A. PC Axis 1 Y = -3.68050

+ 3.09191 * DESSPP

+ 7.19833 + QUESPP

- 1.56719 * ShdIBON

+ 0.34208 + QUESPP2

R2 = 90.0 percent

P(>F) = 0.0001

B.PCAxis Y = -4.03727

+ 9.10940 * CARYTOM

- 34.48905 * VIOPED

+ 0.61293 l ACERUB

+ 0.28104 * ULMALA2

C.PCAxis3

R2 = 95.6 percent

P(>F) = 0.0001

Y = -2.12705

+ 78.97042 + LACSPP

+ 18.30949+ PRUSER

- 3.44123 + VACARB

- 0.32088 + QUENIG3

R2 = 96.9 percent

P(>F) = 0.0001

Y = -2.91119

+ 0.22715 + LIQSTY3

+ 0.04172 * QUEALB3

+ 0.28522 * QUEALB4

+ 0.48832 * QUENIG4

R2 = 96.0 percent

P(>F) = 0.0001

Y = -9.21345

+ 3.37593 * EUOAME

+ 9.01782 + NYSSYL

- 4.68207 * ULMALA

+ 0.09783 * PINECH4

R2 = 92.0 percent

P(>F) = 0.0001

Y = -0.32304

+ 18.81324 + VIOSAG

+ 16.41026 l VFAES

- 0.09227 +I QUEMAR3

- 0.23826 * QUERUB3

R2 = 89.1 percent

P(>F) = 0.0001

Conversely, in the overstory-midstory PCA, regression of the three PC axes against the 162-species all-layer

data set resulted in midstory and overstory species included in each axis model. Regression against PC axis 1

resulted in positive association with midstory sweetgum, midstory and overstory white oak, and overstory water oak.

This suggests a gradient in relation to site quality, in that these species are typically associated with lower slopes

and protected topographic settings. Regression against PC axis 2 resulted in a model having positive association

with overstory shortleaf pine, in addition to three ground cover species. Regression against PC axis 3 led to a

model in which two ground cover species have positive association and two midstory oaks-southern red and

blackjack-have negative association.

DISCUSSION AND CONCLUSIONS

It appears that three sets of associated species have been defined through the correlation analysis-one

characterized by shortleaf pine, another by mesic oak species, and a third by xeric oaks.

In the mesic oak association, the overstory and midstory oak species discussed here are typical of dry-mesic

to mesic sites in the Ouachitas, although water oak has not received much attention in the literature on Ouachita

Mountain plant communities. Most of the associated ground cover species present are typical of dry-mesic to mesic

communities as well. High moss cover is consistent with this community, whereas the appropriateness of high total

unidentified grass cover and high cover of Valium sp. is unclear.

In the pine association, the consistent negative correlations between shortleaf pine and other species may be a

characteristic of pine-dominated communities, or it may be an artifact of the stand-selection criteria. This may be

68
an association in which the pines reflect disturbance, with the species that then become established in conjunction

with the pines reflecting the shift toward later successional stages.

The third species association is consistent with communities in the Ouachita Mountains characteristic of dry to

xeric sites: an open forest or woodland dominated by post oak in the overstory. In this analysis, post oak is typical

in the midstory with shrub layer associates blackjack oak and winged elm, and a ground cover layer with bird’s_foot

violet, phlox, Coreopsis palmata and poverty oatgrass. Midstory white oak, water oak, and blackgum are

characteristic of dry-mesic to mesic communities, so their negative association with post oak in this species

association is ecologically consistent.

From the PCA graphs, it appears that a more geographically lucid interpretation of the stand pattern results

from adding the shrub and ground cover layers to the principal component analysis. One explanation for this is that

the lower canopy layers add valuable ecological information, even on these south- and southwest-facing pine and

pine-hardwood stands, that aid in stand classification. This might also be influenced by past species-specific

manipulations in the overstory and midstory, such as hardwood control or selective harvest of pines, which could

alter the relative proportions of these species in a stand for decades after the treatment was imposed.

Overall, the regression models most easily explained are the all-layer PCA versus site variables, which gave

the better geographic explanation, and the midstory-overstory PCA versus the full-canopy species data set, which

gave the better interpretation in light of the correlation analysis. Both of these analyses have as their core a

relationship to site quality, either expressed as site variables or species variables in the regression models.

However, the assumption that geographic pattern represents ecological pattern is not necessarily valid, especially

in light of the varying disturbance history that one would expect in these stands.

In regard to subsequent analyses, it will be interesting to stratify the data base in ecologically meaningful ways.

For example, analysis of each vegetation layer or specific combinations may allow us to better understand interlayer

and intralayer relationships. Grouping plots by strata of similar attributes may also elucidate meaningful

relationships. Effective groupings could be made using the ecological classification schemes under development in

the National Forest System or by use of LANDSAT imagery or digitized aerial photo imagery.

Although stand-based comparisons are used in this initial exploration, plot-level studies potentially hold even

more promise because variance between plots is greater than that between stands (Guldin and others 1994). The

stands are not uniform expanses of a single slope, aspect, and community. Indeed, plot-based analysis may allow

the development of a plant community/ecological site classification which describes the community variation on

south-facing slopes in the Ouachitas and extrapolates to other site types as well.

Finally, we would like to extend an invitation to other groups to join us in the multivariate compilation. We

especially would solicit the involvement of other groups that have characterized variables across either the 20-stand

data base, the 52-stand data base, or the 72%plot data base. For example, we suspect it would be easy to append

forest floor and soil disturbance variables, small mammals, birds, and wildlife habitat data. But there may also be

opportunities for others with a more limited plot- or stand-based data set as well, depending on the nature of the

data and the scope of the analysis that would result.

LITERATURE CITED

Foti, T.L.; Devall, M. 1994. Pretreatment conditions in mature pine-hardwood stands on south-facing slopes of

the Ouachita/Ozark National Forests: ground layer and shrub layer. In: Baker, J.B., camp. Proceedings of

the symposium on ecosystem management research in the Ouachita Mountains: pretreatment conditions and

preliminary findings; 1993 October 26-27; Hot Springs, AR. Gen.Tech. Rep. SO-xx. New Orleans, LA: U.S.

Department of Agriculture, Forest Service, Southern Forest Experiment Station..

Guldin, James M.; Baker, James B.; Shelton, Michael G. 1994. Midstory and overstory plants in mature pinehardwood stands of the Ouachita/Ozark National Forests. In: Baker, J.B., camp. Proceedings of the

symposium on ecosystem management research in the Ouachita Mountains: pretreatment conditions and

preliminary findings; 1993 October 26-27; Hot Springs, AR. Gen.Tech. Rep. SO-xx. New Orleans, LA: U.S.

Department of Agriculture, Forest Service, Southern Forest Experiment Station..

SAS Institute, Inc. 1990. SAS/STAT user’s guide, version 6, fourth edition, vol. 2. Cary, NC: SAS Institute, Inc.

Smith, Edwin B. 1988. An atlas and annotated list of the vascular plants of Arkansas. 2d ed. Fayetteville, AR:

Bound xerographic text. 489 p.

69
A PPEND IX -

Appendix Tab le l.- Species included in the analysis presented in this paper. Scientific and common names follow Smith

(1988)

Variable

Code Scientific names

A. Ground cover layer

Family Common name

ACERUB

AMEARB

ANDSPP

ANTPLA

ARIDIC

ARIPUR ’

ARISPP

ASPPLA

ASTNOV

ASTSPP ’

BAPLEU

BERSCA

CARCAR

CARXCOM

CARXFLA

CARXSPP

CARYSPP

CARYTOM

CHALAT

CHALAX

CHASES

CLIMAR

CORFLO

CUNORI

DANSPI

DESNUD

DESROT

DESSPP

ELETOM

EUOAME

EUPCOR

FERNMOSS

FUNGI

GALCIR

HELDIV

HELHIR

HIEGRO

IRICRI

JUNVIR

LACSPP

LESPRO

LESREP

LESSPP

LESVIO

LEUSPP

LIAASP

LICHEN

LIQSTY

LONJAP

MlTREP

MONFIS

MONRUS

MONSPP

MOSS

NYSSYL

OSTVIR

OXASTR

Acer rubrum L.

Amelanchier arborea (Michx. f.) Fem.

Andropogon spp .

Anfennoria pluntaginifilia (L.) Richards

Aristida dichotoma Michx.

Aristida putpurascens Poir.

Aristida spp.

Asplenium platyneuron (L.) Oakes ex D.C. Eat.

Aster novae-angliae L.

Aster spp.

Baptisia leucantha T. & G.

Berchemia scundens (Hill) K. Koch

Carpinus caroliniana Walt.

Curer complanata Torr. and Hook.

Carex$accosperma Dewey

Carex spp.

Carya spp.

Curya tomentosa (Pair.) Nutt.

Chasmanthium larifolium (Michx.) Yates

Chasmanthium larum (L.) Yates

Chusmanthium sessilzjlorum (Pair.) Yates

Clitoris mariana L.

Comus jlorida L.

Cunila origanoides (L.) Britt.

Danthonio spicuta (L.) Beauv. ex Roem.& Schult.

Desmodium nudi~orum (L.) DC.

Desmodium rotundt~olium DC.

Desmodium spp .

Elephantopus tomentosus L.

Euonymus americanus L.

Euphorbin corollata L.

Various fern and moss spp.

Various fungi

Galium circaezans Michx.

Helianthus divaricatus L.

Helianthus hirsutus Raf.

Hieracium gronovii L.

Iris cristata Ait.

Juniperus virginiana L.

Lacruca spp .

Lespedeza procumbens Michx.

Lespedezn repens (L.) Bart.

Lespedeza spp

Lespedeza tiolncea (L..) Pers.

Leucobryum spp .

Liatris aspera Michx.

Various lichen spp.

Liquidambar styraciflua L.

Lonicera japonica Thunb.

Mitchella repent L.

Monardajstulosa L.

Monarda russeliana Nutt. ex Sims

Monarda spp.

Various moss spp.

Nyssa sylvah’cn_Marsh.

Ostrya virginiana_(P. Mill.) K. Koch

Oxalis stn’cta L.

Aceraceae

Rosaceae

Gramineae

Compositae

Gramineae

Gramineae

Gramineae

Polypodiaceae

Compositae

Compositae

Leguminosae

Rhamnaceae

Betulaceae

Cyperaceae

Cyperaceae

Cyperaceae

Juglandaceae

Juglandaceae

Gramineae

Gramineae

Gramineae

Leguminosae

Cornaceae

Labiatae

Gramineae

Leguminosae

Leguminosae

Leguminosae

Compositae

Celastraceae

Euphorbiaceae

Red maple

Serviceberry

Bluestem grasses

Pussy’s toes

Church-mouse three-awn

Arrowfeather three-awn

Three-awn spp.

Ebony spleenwort

Aster

Asters

White wild indigo

Rattan vine

American hornbeam

Sedge

Sedge

Sedge

Hickories

Mockemut hickory

Inland sea oats

Butterfly pea

Flowering dogwood

Dittany

Poverty oatgrass

Tick trefoil

Tick trefoil

Tick trefoil

Tobacco-weed

Strawberry bush

Flowering spurge

Rubiaceae

Compositae

Compositae

Compositae

Iridaceae

Cupressaceae

Compositae

Leguminosae

Leguminosae

Leguminosae

Leguminosae

Compositae

Wild licorice

Sunflower

Sunflower

Hawkweed

Crested iris

Eastern red cedar

Wild lettuce

Trailing bush clover

Creeping bush clover

Clovers

Prairie clover

Mosses

Blazing star

Hamamelidaceae Sweetgum

Caprifoliaceae Japanese honeysuckle

Rubiaceae Partridge beny

Labiatae Wild bergamot

Labiatae Horsemint

Labiatae Mints

Nyssaceae

Betulaceae

Oxalidaceae

Blackgum

Hophombeam

Yellow wood sorrel

70
Appendix Tab le l:- Species included in the analysis presented in this paper. ScientljTc and common names follow Smith

(1988) (continued)

Variable

Code Scientific name Family Common name

A. Ground cover layer, cont’d.

OXAVIO

PANBOS

PANDIC

PANDICF

PANSPP

PARINT

PARQUI

PHLPIL

PHLSPP

PINECH

POLSPP

POLYMOSS

PRUAME

PRUSER

PTEAQU

QUEALB

QUEFAL

QUEMAR

QUENIG

QUEPHE

QUERUB

QUESPP

QUESTE

QUEVEL

RUBSPP

SANCAN

SCHSCO

SCLCIL

SCLOLI

SCLSPP

SCLTRI

SMIBON

SMIGLA

SMIROT

SOLISP

SOLULM

SPHSPP

TEPVIR

TOXRAD

TOXSPP

TRACDIF

ULMALA

UNKNOWN

VACARB

VACPAL

VACSTA

VIBRUF

VIOPED

VIOSAG

VITAES

VITROT

ZIZAUR

Oxalis w’olacea L.

Panicum boscii Poir.

Panicum dichotomum L.

Panicum dichotom~$omm Michx.

Panicum spp.

Parlhenium inle grifoiium L.

Parthenocissus quinquefolia (L.) Planchon

Phlox pilosa L.

Phlox spp.

Pinus cchinata Mill.

Polygala a**.

Polystichum spp .

Prunus americana Marsh.

Prunus serotina Ehrh .

Pteridium aquilinum (L..) Kuhn in Decken

Quercus alba L.

Quercus falcata Michx.

Quercus man’landica Muench.

Quercus nigra L.

Quercus phellos L.

Quercus rubra L.

Quercus app.

Quercus stellara Wang.

Quercus velutina Lam.

Rubus spp.

Sanicula canadensis L.

Schizachyrium scopatium (Michx.) Nash

var. divergens Gould

Scleria ciliata Michx.

Scleria oligantha Michx.

Scleria app.

Sckria triglomerata Michx.

Smiler bona-nox L.

Smilax glauca Walt.

Smilax rotundvolia L.

solidago app.

Solidago ulm~folia Muhl.

Sphenopholis app.

Tephrosia virginiana (L.) Pera.

Toxicodendron radicans (L.) Kuntze

Toxicodendron spp .

Trachelospennum diflonne (Walt.) Gray

Ulmus alara Michx.

Unknown app.

Vaccinium arboreum Marsh.

Vaccinium pallidum Ait.

Vaccinium sramineum L.

Viburnum rufidulum Raf.

Viola pedata L.

Viola saginara Ait.

Vitis aestivalis Michx.

Vitis rotund~folia Michx.

ziu’a aurea (L.) Koch

Oxalidaceae Violet wood sorrel

Gramineae Pa&urn grass

Gramineae Panicum grass

Gcamineae Fall panic grass

Gcamineae Panic gcasaes

Compoaitae Wild quinine

Vitaceae Virginia creeper

Polemoniaceae Phlox

Polemoniaceae Phloxes

Pinaceae Shortleaf pine

Roaaceae

Roaaceae

Polypodiaceae

Fagaceae

Fagaceae

Fagaceae

Fagaceae

Fagaceae

Fagaceae

Fagaceae

Fagaceae

Fagaceae

Roaaceae

Umbelliferae

Gcamineae

Cypemceae

Cyperaceae

Cyperaceae

Cyperacee

Liliaceae

Liliiceae

Liliiceae

Compoaitae

Compoaitae

Gramineae

Leguminoaae

Anacacdiaceae

Anacardiaceae

Apocynaceae

Ulmaceae

Ericaceae

Ericaceae

Ericaceae

Caprifoliaceae

Violaceae

Violaceae

Vitaceae

Vitaceae

Umbelliferae

Wild plum

Black cherry

Bracken fern

White oak

Southern ted oak

Blackjack oak

Water oak

Willow oak

Northern red oak

Oaka

Post oak

Black oak

Blackberries

Black snakeroot

Blueatem graaa

Nut rush

Nut tush

Nut tuaher

Tall nut grass

Greenbtier

Gceenhtier

Greenbtier

Goldenrod

Elm-leaf goldenrod

Wedgeacales

Goat’s Rue

Poison ivy

Poison ivy-oak

Climbing dogbane

Winged elm

Tree huckleberry

Low-bush huckleberry

Gooaebetry

Ruaty blackhaw

Bird’a-foot violet

Arrow-leaved violet

Summer grape

Muacadine grape

Golden Alexandera

71
Appendix Table l:- Species included in the analysis presented in this paper. Scientific and common names follow Smith

(1988) (continued)

Variable

Code Scientific name Family Common name

B. Shrub layer

ACERUB Acer rubrum L.

AMEARBZ Amelanchier arborea (Michx. f.) Fem.

BERSCA2 Berchemia scandens (Hill) K. Koch

cARcAR Carpinus caroliniana Walt.

CARYOVA2 Carya ovara (P.MiIl.) K.Koch

CARYTOMZ Carya tomentosa (Pair.) Nun.

CORFLOZ ’ Comusjkwida L.

CRASPP2 Cralaegus spp.

FRAPEN2 Fraxinus penn.$vanica Marsh.

JUNVIR2 Juniperur virginiana L.

LIQSTY2 ’ Liquidambar styracz@ua L.

NYSSYLZ Nyssa sylvan’ca Marsh.

osTVIR2 Osrrya virginiana Q. Mill.) K. Koch

PARQU12 Panhenocissus quinquefolia (L.) Planchon

PINECHZ pinus echinara Mill.

PRUAME2 Prunus ameticana Marsh.

PRUSER2 Prunus serotina Ehrh.

QUEALBZ Quercus alba L.

QUEFAL2 Quercus falcata Michx.

QUEMARZ Quercus man’landica Muench.

QUERUBZ Quercus rubra L.

QUESPP2 Quercus spp.

QUESTE2 Quercus stellata Wang.

QUEVELZ Quercus velutina Lam.

SMIBONZ Smiler bona-nar L.

SMIGLA2 Smiler glauca Walt.

SMlROT2 Smiler romndifolia L.

TOXRADZ Toxicodendron radicans (L.) Kuntze

ULMALA2 Ulmus alara Michx.

VACARB2 Vaccinium arboreum Marsh.

VIBRUFZ Viburnum ruJ7dulum Raf.

VII-ROT2 Viris rorundifolia Michx.

C. Midstory layer

ACERUB

CARYTOM3

cARYTEx3

CORFL03

JUNVIR3

LIQSTYJ

NYSSYL3

PINECH3

QUEALB3

QUEFAL3

QUEMAR3

QUENIG3

QUERUB3

QUESTU

ULMALA3

Acer rubrum L.

Carya tomentosa (Pair.) Nutt.

Catya aexana Buckl.

Comus@ida L.

Junipems virginiana L.

Liquidambar styraciflua L.

Nyssa sylvan’ca Marsh.

Pinus echinata Mill.

Quercus alba L.

Quercur falcara Michx.

Quercus man’landica Muench.

Quercus nigra L.

Quercus rubra L.

Quercus stellara Wang.

Ulmus alata Michx.

D. Overstory layer

LIQSTY4

PINECH4

QUEALB4

QUESTM

QUENIG4

QUERUB4

Liquidambar styraci$ua L.

Pinus echinata Mill.

Quercus alba L.

Quercus stellata Wang.

Quercus nigra L.

Quercus rubra L.

Aceraceae

Rosaceae

Rhamnaceae

Betulaceae

Juglandaceae

Juglandaceae

Comaceae

Rosaceae

Oleaceae

Cupressaceae

Hamamelidaceae

Nyssaceae

Betulaceae

Vitaceae

Pinaceae

Rosaceae

Rosaceae

Fagaceae

Fagaceae

Fagaceae

Fagaceae

Fagaceae

Fagaceae

Fagaceae

Liliaceae

Liliaceae

Liliaceae

Anacardiaceae

Ulmaceae

Ericaceae

Caprifoliaceae

Vitaceae

Aceraceae

Juglandaceae

Juglandaceae

Comaceae

Cupresaaceae

Hamamelidaceae

Nyssaceae

Pinaceae

Fagaceae

Fagaceae

Fagaceae

Fagaceae

Fagaceae

Fagaceae

Ulmaceae

Hamamelidaceae

Pinaceae

Fagaceae

Fagaceae

Fagaceae

Fagaceae

Red maple

Serviceberry

Rattan vine

American hornbeam

Shagbark hickory

Mockemut hickory

Flowering dogwood

Hawthorn

Green ash

Eastern redcedar

Sweetgum

Blackgum

Hophombeam

Virginia creeper

Shortleaf pine

Wild plum

Black cherry

White oak

Southern red oak

Blackjack oak

Northern red oak

Oaks

Post oak

Black oak

Greenbrier

Greenbrier

Greenbrier

Poison ivy

Winged elm

Tree huckleberry

Rusty blackhaw

Muscadine grape

Red maple

Mockemut hickory

Black hickory

Flowering dogwood

Eastern redcedar

Sweetgum

Blat kgum

Shortleaf pine

White oak

Southern red oak

Blackjack oak

Water oak

Northern red oak

Post oak

Winged elm

Sweetgum

Shortleaf pine

White oak

Post oak

Water oak

Northern red oak

72
Appendix Table 2.- Site variables included in the analysispresented in thispaper (GuMin and others 1994, Foti andDeval1

1994)

Variable code Variable

BKNO

TRTNO

AZDEG

SLPCX

SLOPOS

COVER

HGT

AGE

s x

Block number

Treatment number

Azimuth, degrees

Slope percent

Slope position

Percent cover

Height, ft

Age, years

Site index, A (base 50)

SQ

MST

MSS

MRT

MRS

UTMN

UTMNT

UTME

UTMET

Ll’l-l-ER

SOIL

WATER

ROCK

Site quality

Microsite topography

Microsite severity

Microrelief topography

Microrelief severity

Universal Transverse Mercator - North, m

UTMN Transformed (3,800,ooO - UTMN), m

Universal Transverse Mercator - East, m

UTME Transformed (340,ooO - UTME), m

Percent coverage of litter

Percent of exposed mineral soil

Percent coverage by water

Percent coverage of rock

73
Small Mammal Communities of Mature Pine-Hardwood

Stands in the Ouachita Mountains’

Philip A. Tappe, Ronald E. Thill, Joseph J. Krystofik, and Gary A. Heidt’

ABSTRACT

A study was conducted on the Ouachita and Ozark National Forests in Arkansas to evaluate

the effects of alternative pine-hardwood reproduction cutting methods on small mammal

abundance and diversity. Pretreatment characteristics of small mammal communities on 20

late-rotation mixed pine-hardwood stands in four physiographic zones of the Ouachita

Mountain region of Arkansas are presented. Each physiographic zone (block) contained one

replication of five treatments (four future treatments and an untreated control). The most

commonly captured small mammal species were Peromyscus spp., Blarina carolinensis, and

Ochrotomys nuttafli. Capture success varied between years but most likely reflected changes

in probabilities of capture of individual animals and not fluctuations in community

composition. Small mammal species richness, diversity, evenness, and relative abundance

did not differ between physiographic zones or future treatments.

INTRODUCTION

There is currently a paucity of information concerning the implications of even- and uneven-aged mixed pine-hardwood

management for small mammals. In extensive literature searches on the topic of silvicultural effects on wildlife habitat (covering

the years 1953 through 1990) Harlow and Van Lear (1981, 1987) and NCASI (1993) did not cite a single paper specifically

addressing the effects of reproduction cutting methods in mixed pine-hardwood stands on small mammal communities. Coupled

with increasing concerns over the impacts of silvicultural practices on wildlife, research on the effects of alternative silvicultural

practices is particularly warranted for small mammal communities. Small mammals are the primary prey base for many

mammalian and avian predators. Mycophagous species facilitate dispersal of fungal spores that form root-inhabiting

ecotomycorrhizae required by most higher plants for adequate nutrient procurement, enhanced water absorption, and protection

Tom root pathogens (Maser and others 1978). Consumption of pine seeds by some species may adversely affect regeneration

success (Pank 1974, Smith and Aldous 1947). In addition, fossorial species may significantly influence hydrological processes

on forested watersheds (Ursic and Esher 1988).

The objective of this study is to evaluate the effects of alternative pine-hardwood reproduction cutting methods on small

mammal abundance and diversity. Pretreatment characteristics of small mammal communities in late-rotation stands in the

Ouachita Mountain region of Arkansas are presented in this paper.

METHODS

Study Areas and Treatments

Twenty late-rotation mixed pine-hardwood stands in four physiographic zones of the Ouachita Mountain region were selected

for study. These stands are located in the Ouachita National Forest and Ozark-St. Francis National Forest and are characterized

by: size ranges from 14.2 to 16.2 ha; predominantly south, southeast, or southwest aspects; and slopes of 5 to 20 percent.

Locations and habitat characteristics of the stands are described by Thill and others (1994).

Four replications of five treatments, blocked by physiographic zone, were randomly assigned to 20 stands. These treatments

consist of an untreated control and four reproduction cutting methods: clearcut, shelterwood, group selection, and single-tree

’ Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

2 Assistant professor, School of Forest Resources, University of Arkansas at Monticello, Monticello, AR 7 1656; supervisory

research wildlife biologist, Southern Forest Experiment Station, Nacogdoches, TX 75962; research specialist, School of

Forest Resources, University of Arkansas at Monticello, Monticello, AR 7 1656; professor, Department of Biology,

University of Arkansas at Little Rock, Little Rock, AR 72204; respectively.

74
selection. All silvicultural treatments, except for the clearcut, provide for the retention of overstory hardwoods. These treatments

were implemented in the summer of 1993. For a detailed description of treatments and physiographic zones, see Baker (1994).

Small Mammal Surveys

Small mammals were trapped prior to treatment installation during December of 1991 and 1992 using Sherman livetraps (7.62

cm by 8.89 cm by 22.86 cm). These traps are of sufficient size to capture eastern woodrats (Neotomaj7o~idanu), flying squirrels

(Glaucomys vofuns), and smaller mammals. Eighty trap stations per stand were located at 15-m intervals along permanent

transects established for small mammal trapping, habitat sampling, and biodiversity surveys. To ensure adequate coverage of

each study area, each stand was subdivided into 50-m wide, parallel bands. One randomly selected transect was located within

each band so that no transect was closer than 30 m from another transect. The number of transects and their lengths varied by

stand size and shape. To minimize potential edge influences, no traps were placed closer than 50 m from the stand boundaries.

A more detailed description of transect establishment is given by Thill and others (1994). In 199 1, one trap was placed at each

station. Sampling effort was increased to two traps per station in 1992 to ensure ample opportunities for multiple captures per

trap station.

Traps were baited with commercial horse and mule feed and checked for 10 consecutive days. A wad of cotton was placed

in each trap for nesting material to minimize trap mortality. Captured mammals were marked and released at the site of capture

after recording species, sex (when possible), and location (station number) of capture. A tally was also kept on the number of

empty/sprung traps so that total available trap nights could be computed. Because of insufficient discriminating physical

characteristics available from field observations, animals of the genus Peromyscus (including P. leucopus, P. gossypinus, P.

municulutus, and P. uttwuteri) were not identified to the species level.

Data Analyses

A number of diversity measures were computed for each stand. These included species richness (i.e., the number of species

encountered), Shannon’s diversity index (Shannon and Weaver 1963), and species evenness (i.e., the distribution of individuals

among species). In addition, an index of relative species abundance was obtained by computing small mammal captures per 100

trap nights, excluding recaptures and after correcting for sprung/empty traps. Though sampling intensity was doubled in 1992,

very few multiple captures occurred. Thus, to ensure that data were comparable between years, 1992 trap nights were based on

the number of trap stations as opposed to the number of individual traps. Diversity, evenness, richness, and relative abundance

of small mammals were compared by year using Wilcoxon matched-pairs signed-ranks tests and by physiographic zone and

future treatment using one-way analysis of variance (ANOVA) and Tukey’s HSD. In addition, small mammal community

composition was evaluated among physiographic zones and among future treatments using Sorensen’s Similarity Index (MuellerDombois and Ellenberg 1974). This index is computed as: SI = 2OOC/(A + B), where A = the number of species in zone or

treatment A, B = the number of species in zone or treatment B, and C = the number of species that areas A and B have in common.

Similarity can range from 0 percent (no species in common) to 100 percent (identical species composition). So that community

composition could be readily compared between any two blocks or treatments, an index value was computed for each

combination of both physiographic zones (6 combinations) and future treatments (10 combinations).

RESULTS

After correcting for sprung traps and differential sampling intensity, 2 1,165 trap nights were accumulated over 2 years across

all stands. A total of 502 small mammals of 10 species were captured (table 1). Trapping success across years was 2.37 new

captures per 100 trap nights. The most commonly captured species were Peromyscus spp., Blurinu curolinensis, and Ochrotomys

nuttulli, comprising 94 percent of all animals captured (table 1).

Differences by Year

Capture success was different between 1991 and 1992. Total captures varied significantly between years (Z = -3.6773, P

<O.OOl), and numbers of individuals within the species were different for the three most commonly caught species (table 1). New

captures per 100 trap nights also differed between years for the three most commonly captured species (table 1): Peromyscus spp.

(Z = -2.6880, P = 0.007) Blurinu curolinensis (Z = -2.7253, P = 0.006), and Ochrotomys nuttulli (Z = -3.0 102, P = 0.003).

Because of these differences in capture success, measures of diversity also differed between years. Species richness among

stands differed by year (Z= -2.1993, P = 0.028), averaging 3.35 (SE = 0.24) for 1991 and 2.55 (SE = 0.20) for 1992.

Species diversity also differed by year (Z = -2.3 146, P = 0.021), averaging 0.90 (SE = 0.08) for 1991 and 0.71 (SE = 0.07) for

1992. However, species evenness did not differ between years (Z = -0.8213, P = 0.412), averaging 0.73 (SE = 0.06) for 1991

and 0.75 (SE = 0.06) for 1992.

75
Table 1- Species, numbers of captured individuals, and relative abundance (new captures per 100 trap nights) of small mammals captured by year in

Ecosystem Management research stands in the Ouachita Mountains of Arkansas

Species

Peromyscus spp.*

Blarina carolinensis

Ochrotomys nuttalli

Neotomajloridana

Reithrodontomys filvescens

Glaucomys volans

1991 1992

Total

Captures/l 00 Captures/l00 captures/l00

Captures trap nights Captures trap nights Total captures trap nights

170 1.62 84 0.79 254 1.20

127 1.21 31 0.29 158 0.75

51 0.49 9 0.08 60 0.28

8 0.08 5 0.05 13 0.06

5 0.05 1 0.01 6 0.03

3 0.03 2 0.02 5 0.02

Microtuspinetorum 2 0.02 1 0.01 3 0.01

Orzomys palustris 1 0.01 0 0.00 1 co.01

Sigmodonihispidus 1 0.01 0 0.00 1 co.01

h4us nhsculus 0 0.00 1 0.01 1 co.01

Total 368 3.51

*Includes P. leucopus, P. gossypinus, P. maniculatus, and P. attwateri.

134 1.26 502 2.37

Because habitat characteristics did not change appreciably between years, differences in relative abundance and diversity were

probably related to differences in the inherent probabilities of capture of individual animals and not to yearly fluctuations in the

actual abundance and/or composition of small mammal species. Species that were captured only 1 year were likely present both

years, but their populations may have been so low that capture was unlikely given our sampling intensity. When richness,

diversity, and evenness values were computed for pooled 1991 and 1992 data, mean values across all stands were 3.70 (SE =

0.21) for species richness, 0.98 (SE = 0.07) for species diversity, and 0.75 for species evenness.

Differences by Physiographic Zones

Physiographic zones were compared for each year and for pooled data across years. In 199 1, 1992, and 199 l-92 combined,

no differences between zones were found for relative abundance, richness, diversity, or evenness (tables 2,3). Likewise, few

habitat parameters were significantly different by physiographic zone (Thill and others 1994). Small mammal community

similarity between physiographic zones ranged from 6 1.5 percent to 87.5 percent (table 4), and averaged 74.1 percent. However,

Peromyscus spp., Blarina carolinensis, and Ochrotomys nuttalk were present in all zones. Because all other species comprised

only 6 percent of the animals captured, these areas may be more similar than indicated by Sorensen’s index.

Differences by Future Treatments

Groups of stands targeted for future treatments were also compared for each year and for pooled data across years. In 199 1

and 1991-92, no differences between future treatments were found for relative abundance, richness, diversity, or evenness (Tables

5 and 6). In 1992, there were no differences between future treatments for relative abundance, richness, or diversity; however,

the mean evenness value for the group of stands to receive the shelterwood treatment differed from all other groups of stands

except the control group (tables 5, 6). Likewise, only one of 69 habitat parameters (volume of down pine logs, decay class 3)

differed significantly among future treatments (Thill and others 1994). Small mammal community similarity between future

treatments ranged from 57.1 percent to 92.3 percent (table 4) and averaged 78.5 percent. Similar to physiographic zones,

Peromyscus spp., Blarina carolinensis, and Ochrotomys nuttalli were present in all treatment areas. In addition, the next most

abundant species, Neotomajloridana (table l), was also present in all treatment areas. Thus, these areas may also be more similar

in small mammal composition than indicated by Sorensen’s index.

76
Table 2- Relative abundance (new captures per 100 trap nights) of small mammals and the three most commonly captured species (xi SE) in Ecosystem

Management research start& in the Ouachita Mountains of Arkansas byphysiographic zone, 1991-92

Species Year

North

Zone

F P

South East West

All species 1991 3.21 f 1.13 3.21 l 1.23 4.88 f 0.91 2.15 f 1.35 0.637 0.60

1992 1.29 f 0.44 1.11 *0.22 1.46 f 0.47 1.15*0.36 0.173 0.91

Pooled 2.25 l 0.66 2.19 f 0.69 3.17 f 0.75 1.95 f 0.71 0.584 0.63

Peromyscus spp.* 1991 2.01 f 0.80 1.99 f 1.32 1.46 f 0.37 0.98 f 0.47 0.351 0.79

1992 0.88 f 0.33 0.63 l 0.15 0.93 f 0.39 0.69 f 0.24 0.245 0.86

Pooled 1.45 f 0.45 1.31 f 0.67 1.19iO.27 0.84 f 0.26 0.346 0.79

Blarina carolinensis 1991 0.30 l 0.09 0.75 f 0.27 2.53 l 1.03 1.35 f 1.68 2.193 0.13

1992 0.22 f 0.09 0.29 f 0.09 0.34 f 0.21 0.30 f 0.10 0.306 0.82

Pooled 0.26 f 0.06 0.52 f 0.15 1.44 f 0.61 0.83 f 0.40 1.847 0.16

Ochrotomys nuttalli 1991 0.72 f 0.29 0.34 f 0.17

1992 0.07 f 0.07 0.04 f 0.04

Pooled 0.40*0.18 0.19*0.10

*One-way ANOVA F-value.

‘Probability associated with one-way ANOVA F-value.

*Includes P. leucopus, P. gossypinus, P. maniculatus, and P. attwateri.

0.81 f 0.33 0.08 f 0.05 2.022 0.15

0.15 f 0.09 0.08 f 0.05 0.514 0.68

0.48 f 0.20 0.08*0.11 1.695 0.19

Table 3- Species richness, diversity, and evenness (xi SE) in Ecosystem Management research stands in the Ouachita Mountains of Arkansas by

physiographic zone, 1991-92

Variable

Richness

Year

1991

1992

Pooled

North

3.20 f 0.20

2.20 f 0.37

3.60 f 0.24

Zone

F+ pt

south East West

3.40 l 0.51 3.20 f 0.21 3.60 f 0.87 0.133 0.94

2.80 f 0.37 2.60 f 0.40 2.60 f 0.5 1 0.362 0.78

3.83 f 0.48 3.40 f 0.25 4.00 f 0.63 0.346 0.79

Diversity* 1991 0.88 f 0.10 0.94 l 0.20 0.88 f 0.12 0.89 f 0.23 0.028 0.99

1992 0.55 f 0.17 0.84 f 0.13 0.76 l 0.09 0.70 l 0.19 0.694 0.57

Pooled 0.96 l 0.14 1.02 f 0.21 0.89kO.13 1.06 f 0.05 0.214 0.89

Evenness 1991 0.77 f 0.09

1992 0.61 f 0.17

Pooled 0.74 f 0.09

*One-way ANOVA F-value.

‘Probability associated with one-way ANOVA F-value.

*Shannon’s diversity index (Shannon and Weaver 1963)

0.76 f 0.12 0.76 f 0.09 0.65*0.17 0.210 0.89

0.84 f 0.04 0.87 f 0.07 0.67 f 0.17 0.936 0.45

0.72 f 0.13 0.73 f 0.08 0.81 f 0.05 0.173 0.91

77
Table 4- Sorensen’s similarity indices (Mueller-Dombois and Ellenberg 1974) for small mammal communities

in Ecosystem Management research stands in the Ouachita Mountains of Arkansas by future treatments

and physiographic zones. 1991-92

Analysis

Future treatments

Comparison

Clearcut-single tree selection

Clearcut-shelterwood

Control-single tree selection

Control-shelterwood

Single tree selection-shelterwood

Control-clearcut

Group selection-clearcut

Group selection-single tree selection

Group selection-shelterwood

Group selection-control

Similarity index

(percent)

92.3

90.9

85.7

83.3

83.3

76.9

76.9

71.4

66.7

57.1

Physiographic zones South-West 87.5

North-East 80.0

North-South 76.9

North-West 76.9

South-East 61.5

East-West’ 61.5

DISCUSSION

Small mammals play an important role in several ecological processes of forested communities and can be greatly influenced

by forest management activities. To effectively evaluate the impacts of imposing specific treatments on forest stands,

pretreatment conditions relative to small mammal abundance and community composition should be as similar as possible. In

this study, no differences were found in small mammal relative abundance, richness, diversity, or evenness by physiographic

region, and with only one exception, no differences were found in these same parameters by future treatment. Thus, future

analyses of posttreatment data should not be confounded by pretreatment differences in respect to small mammal community

composition and stand location (physiographic zone).

Though differences in trap types and trapping methodologies prevent direct comparisons with other studies, all stands sampled

in this study appeared to be characterized by a relatively low density and diversity of small mammals. Several studies have

shown that small mammal abundance and diversity is influenced by successional vegetation patterns and structural habitat

characteristics (Goodwin and Hungerford 1979; Kirkland 1977, 1990; McComb and Noble 1980; Mengak and others 1989a,

1989b). In general, early successional seres are characterized by higher small mammal abundance and diversity than later seres,

as well as differences in species composition.

Small mammal abundance, diversity, and species composition is often positively related to understory cover and down woody

material. Stands in this study generally had very little down woody material (averaging 3.3 percent ground coverage), and the

percentage of cover was low (averaging 0.3 to 2.3 percent) for woody plants, forbs, and graminoids (Thill and others 1994).

Numerical and compositional responses of small mammals following treatments will most likely reflect associated increases in

the above habitat parameters. The magnitude and temporal characteristics of these responses will probably vary by treatment,

and total numbers of some species may increase substantially. Though increasing sampling intensity during pretreatment trapping

did not increase trapping success, retaining two traps per station will probably be necessary to sample increased small mammal

populations following certain treatments.

The three most commonly captured species in this study represented three different trophic groups: insectivores (Blarina

curolinensis), granivores (Ochrotomys nuttulli), and omnivores (Peromyscus spp.). If sufficient numbers of additional species

78
Table 5- Relative abundance (captures per 100 trap nights) of small mammals and the three most commonly captured species (x* SE) in Ecosystem

Management research stands in the Ouachita Mountains of Arkansas byfiture treatment, 1991-92

Treatment

Species Year

Clearcut

Single-tree Group F P

Shelterwood selection selection Control

All species

Peromyscus spp?

Blarina carolinensis

Ochrotomys nuttalli 1991

1991

1992

Pooled

1991

1992

Pooled

1991

1992

Pooled

1992

I .06 f 0.23

0.6O*O.ll

0.83 f 0.15

0.55 f 0.16

0.37 l 0.13

0.46 f 0.10

0.46 f 0.12

0.18 f 0.07

0.32 f 0.08

0.23 f 0.18

0.00 f 0.00

3.90 f 1.62

1.30 f 0.67

2.60 f 0.95

2.57 f I.61

0.88 f 0.50

I .73 f 0.84

0.74 f 0.37

0.19 f 0.08

0.46 l 0.21

0.48 f 0.36

0.14*0.09

0.31 f 0.18

4.77 f 1.22

1.65*0.31

3.21 f 0.83

I .45 f 0.62

1.04 f 0.29

I .25 f 0.32

2.16* 1.08

0.28 f 0.12

1.22 l 0.62

0.67 f 0.3 I

0.14 f 0.09

0.41 f 0.18

3.54 f I.54

1.39 f 0.35

2.47 f 0.84

2.06 f 1.00

0.78 f 0.29

1.42 f 0.54

0.47 f 0.18

0.42 f 0.09

0.45 f 0.10

0.72 f 0.42

0.10 l 0.10

0.41 f 0.23

4.36 f 0.88 1.437 0.27

1.31 f 0.35 0.95 1 0.46

2.83 f 0.73 1.475 0.23

I.41 * 0.32 0.704 0.60

0.84 f 0.28 0.614 0.66

1.13*0.23 0.942 0.45

2.32 f 1.22 1.508 0.25

0.38*O.ll I .280 0.32

1.35 f 0.68 1.298 0.29

0.33 l 0.15 0.486 0.75

0.05 f 0.05 0.676 0.62

Pooled 0.12 f 0.09 0.19 f 0.09 0.629 0.65

*One-way ANOVA F-value.

+Probability associated with one-way ANOVA F-value.

Qrcludes P. leucopus, P. gossypinus, P. maniculatus, and P. attwateri.

Table 6- Species richness, diversity, and evenness 6 f SE) in Ecosystem Management research stanak in the Ouachita Mountains of Arkansas byfuture

treatment, 1991-92

Treatment

Variable

Richness

Year

1991

1992

Pooled

Clearcut Shelterwood

3.25 l 0.25 2.75 f 0.25

2.00 f 0.00 2.50 f 0.87

3.25 l 0.25 3.40 f 0.40

Single-tree

selection

3.50 l 0.50

3.00 l 0.41

4.25 f 0.48

Group

selection

3.00 f 0.71

2.75 f 0.25

3.50 f 0.29

F1 P

Control

4.25 l 0.75 1.152 0.37

2.50 f 0.29 0.647 0.64

4.25 f 0.75 1.062 0.41

Diversity’ 1991 1.03 f 0.06 0.82 f 0.21 0.97 l 0.06 0.76 f 0.26 0.93 f 0.26 0.328 0.89

1992 0.62 l 0.04 0.48 f 0.28 0.88 f 0.10 0.86 f 0.12 0.73 f 0.14 1.167 0.36

Pooled 1.04*0.1l 0.90 f 0.22 1.13 f 0.12 0.99 l 0.07 0.87 f 0.23 0.360 0.83

Evenness 1991 0.88 f 0.03 0.77*0.17 0.81 f 0.08 0.59 l 0.20 0.62iO.11

1992 0.89 f 0.06 A 0.34 f 0.20 B 0.84 f 0.05 A 0.86 f 0.06 A 0.80 f 0.10 AB

Pooled 0.88 f 0.04 0.70 f 0.16 0.79 f 0.05 0.80 f 0.04 0.59 f 0.10

*One-way ANOVA F-value. Means within rows followed by unlike letters are statistically different (P < 0.05).

‘Probability associated with one-way ANOVA F-value.

*Shannon’s diversity index (Shannon and Weaver 1963).

0.875 0.50

4.212 0.02

1.196 0.35

79
are captured during posttreatment sampling, changes in community structure relative to trophic groups will be of interest,

particularly in respect to fungi- and seed-consuming species due to their potential effects on natural regeneration.

ACKNOWLEDGMENTS

We gratefully acknowledge the assistance of the many people who participated in small mammal trapping, including USDA

Forest Service Ouachita and Ozark National Forest district personnel, University of Arkansas at Little Rock biology students,

J.F. Taulman, and R.W. Perry. We also thank B.R. Lockhart and R.A. Williams for reviewing an earlier draft of this manuscript.

LITERATURE CITED

Baker, J.B. 1994. An overview of stand-level ecosystem management research in the Ouachita/Ozark National Forests. In:

Proceedings of the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment Conditions

and Preliminary Findings. 1993. October 26-27: Hot Springs, AR. Gen. Tech. Rep. New Orleans LA: U.S. Department of

Agriculture, Forest Service, Southern Forest Experiment Station.

Goodwin, John G., Jr.; Hungerford, C. Roger. 1979. Rodent population densities and food habits in Arizona ponderosa pine

forests. Res. Pap. RM-214. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and

Range Experiment Station. 12 p.

Hat-low, Richard F.; Van Lear, David H. 1981. Silvicultural effects on wildlife habitat in the South (an annotated bibliography):

1953-1979. Tech. Pap. 14. Clemson, SC: Clemson University Department of Forestry. 30 p.

Hat-low, Richard F.; Van Lear, David H. 1987. Silvicultural effects on wildlife habitat in the South (an annotated bibliography):

1980-1985. Tech. Pap. 17. Clemson, SC: Clemson University Department of Forestry. 42 p.

Kirkland, Gordon L., Jr. 1977. Responses of small mammals to the clearcutting of northern Appalachian forest. Journal of

Mammalogy 58: 600-609.

Kirkland, Gordon L., Jr. 1990. Patterns of initial small mammal community change after clearcutting of temperate North

American forests. Oikos. 59(3): 3 13-320.

Maser, Chris; Anderson, Ralph G.; Cromack, Kermit, Jr. [and others]. 1979. Dead and down woody material. In: Thomas, Jack

Ward, tech ed. Wildlife habitats in managed forests: the Blue Mountains of Oregon and Washington. Agric. Handb. 553.

Washington, DC: U.S. Department of Agriculture: 78-95. Chapter 6. In cooperation with: The Wildlife Management Institute;

U.S. Department of the Interior, Bureau of Land Management.

McComb, W.C.; Noble, R.E. 1980. Small mammal and bird use of some unmanaged and managed forest stands in the mid-South.

In: Proceedings of the 34th Annual Conference of the Southeastern Association of Fish and Wildlife Agencies. 482-49 1.

Mengak, Michael T.; Guynn, David C., Jr.; Van Lear, David H. 1989a. Ecological implications of loblolly pine regeneration for

small mammal communities. Forest Science 35(2): 503-514.

Mengak, Michael T.; Van Lear, David H.; Guynn, David C., Jr. 1989b. Impacts of loblolly pine regeneration on selected wildlife

habitat components. In: Miller, J.H., camp. Proceedings of the 5th biennial southern silvicultural research conference. Gen.

Tech. Rep. SO-74. New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station:

612-618.

National Council of the Paper Industry for Air and Stream Improvement, Inc. 1993. Forestry, wildlife, and habitat in the East

(an annotated bibliography), 1986-1990. In: Sweeny, S.R.; Wigley, T.B., camps. Tech. Bull. 651. 3 17 p.

Pank, L.F. 1974. A bibliography on seed-eating mammals and birds that affect forest regeneration. Spec. 174. U.S. Department

of the Interior, Fish and Wildlife Service. 28 p.

Mueller-Dombois, D.; Ellenberg, H. 1974. Aims and methods of vegetation ecology. New York: John Wiley and Sons.

80
Smith, C.F.; Aldous, S.E. 1947. The influence of mammals and birds in retarding artificial and natural regeneration of coniferous

forests of the United States. Journal of Forestry. 45: 361-369.

Shannon, C.E.; Weaver, W. 1963. The mathematical theory of communication. Urbana, IL: University of Illinois Press. 177 p.

Thill, R.E.; Tappe, P.A.; Koerth, N.E. 1994. Wildlife habitat conditions in mature pine-hardwood stands in the Ouachita/Ozark

National Forests. In: Proceedings of the Symposium on Ecosystem Management Research in the Ouachita Mountains:

Pretreatment Conditions and Preliminary Findings. 1993. October 26-27: Hot Springs, AR. Gen. Tech. Rep. New Orleans

LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station.

Ursic, S.J.; Esher, R.J. 1988. Influence of small mammals on stormflow responses of pine-covered catchments. Water Resources

Bulletin. 24: 133-139.

81
Southern Flying Squirrels in Mature Pine/Hardwood

Stands in the Ouachita and Ozark National

Forests of Arkansas’

James F. Taulman and Ronald E. Thill’

ABSTRACT

The southern flying squirrel (Glaucomys volans) was chosen as a representative forest-dependent mammal for

examination in this study imposing a variety of habitat-altering management techniques. Considering its habitat

requirements, the flying squirrel should be very responsive to changes in forest structure, density of cavity trees, and

availability of hard mast, Goals of this research on the mature pine-hardwood forest type were to gather baseline

data on flying squirrel population demographics, including reproductive success; to identify any habitat features

influencing squirrel habitat use; to investigate any differences in groups of stands according to future treatment type

or replicated group; and to identify ectoparasites associated with flying squirrels.

During fall 1992,630 nest boxes were constructed and installed on 21 mature stands comprising 3 replications

of 6 different proposed cutting treatments plus 3 controls. Boxes were checked once each in January, February, and

March 1993. Ninety-one adult and 27 juvenile squirrels were marked on 16 stands; five stands yielded no squirrels.

The mean number of marked squirrels per stand was 5.6, and density averaged 0.37 per ha. The mean weight of

nomnatemal adult squirrels was 67.45 g, and monthly mean weights did not differ from that value throughout the

sampling period. Twenty-three maternity boxes had a mean of 1.96 squirrels per litter. Young were born between

February 8 and March 13. Thirty-four non-maternity boxes contained a mean of 2.8 adults per box. Two maternal

females shared nest boxes with other adults. A maximum of six squirrels was found in one box. Fifty-four nests

(constructed predominately of shredded eastern redcedar [Juniperus virgin ian a L.] bark) were collected and dried,

yielding 6 families of ectoparasites after a partial analysis.

Slope was negatively correlated with numbers of marked squirrels across all stands. Numbers of pines in the

lower midstory diameter class (8.9 to 16.6 cm in d.b.h.) were negatively correlated with the numbers of marked

squirrels and significantly fewer in macroplots containing nests compared with macroplots across all stands. Habitat

variables did not differ between stands grouped by .future treatment, and only azimuth differed between stands

grouped by replicated subset.

INTRODUCTION

Growing public awareness of, and concern over, habitat destruction and species declines and extinctions worldwide

has resulted in a shift to a more ecological approach to management of national forests in the United States. The U. S.

Department of Agriculture, Forest Service has initiated a large-scale, replicated, interdisciplinary study in Arkansas to

compare ecological and financial aspects of several silvicultural treatments as alternatives to clearcutting. While population

responses of birds and mammals to even-aged harvesting techniques (primarily clearcutting) have been investigated (Harlow

and Van Lear 1987, Smith and Petit 1988), little is known of the effect of uneven-aged silviculture on forest wildlife (Thill

and others 1992).

The Ecosystem Management Research Program of the USDA Forest Service includes a research venture in which

alternative silvicultural practices are being evaluated under rigorous scientific scrutiny. In Arkansas, researchers with the

USDA Forest Service, Southern Forest Experiment Station and the Ouachita and Ozark National Forests are cooperating

to meet the Ecosystem Management goals through a three-phase approach. Under Phase II of this project, an array of 12

Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

Wildlife Biologist, USDA Forest Service, Southern Forest Experiment Station, P.O. Box 1270, Hot Springs, AR 71902.

(Present address: Department of Biological Sciences, University of Arkansas, Fayetteville, AR 72701); and Supervisory

Research Wildlife Biologist, USDA Forest Service, Southern Forest Experiment Station, Wildlife Habitat and Silviculture

Lab, P.O. Box 7600 SFA Station, Nacogdoches, TX 75962, respectively.

82
partial cutting treatments ranging from pine-hardwood single-tree selection to clearcut, plus an uncut control, were replicated

in four forest zones. Stands were selected for the study from a pool that conformed to a range of criteria (see Baker 1994).

Seven research groups will monitor various economic and ecological parameters before and after treatment at the stand level

to provide data on the relative merits and ecological effects of each cutting method. Pretreatment data were collected on

the replicated Phase II stands during 1992 and the spring of 1993. All experimental stands were harvested during the

summer of 1993.

This study design affords the opportunity to monitor populations of a forest-dependent mammal in a concurrent

comparison of matched groups of control and experimental stands both before and after harvest, as suggested by Eberhardt

(1976), thus eliminating the problem of unknown environmental factors, such as weather, causing observed changes in

experimental variables (Eberhardt and Thomas 1991). This report presents pretreatment results from the first year of a

3-year study of flying squirrel demographics and habitat features on a subset of 21 mature stands within this larger study.

Flying squirrels are common inhabitants of pine-hardwood forests in the Southern United States (Goertz and others

1975). Because G. voluns glides as a primary means of escape and travel, habitat needs include trees of considerable height

and a relatively open midstory (Bendel and Gates 1987). High-use areas also have been found to be characterized by a

fairly dense understory shrub layer (0.5 to 3.0 m in height) in both flying squirrels (Bendel and Gates 1987, Jordan 1948,

Sonenshine and Levy 1981) and gray squirrels (Sciurus carolinensis) (Fischer and Holler 1991). The shrub layer provides

foraging cover and soft mast during summer before acorns and hickory nuts are available (Sonenshine and Levy 1981).

Southern flying squirrels are omnivorous (Harlow and Doyle 1990) but rely heavily on hard mast (seeds, hickory nuts, and

acorns) throughout the year (Braun 1988, Sawyer and Rose 1985, Sealander and Heidt 1990, Sollberger 1943). Hard mast

provides an energy-rich storable food source that minimizes foraging trips during winter (Weigl 1978).

Because flying squirrels move inefficiently in cleared areas within forests, Bendel and Gates (1987) emphasized the

importance of forest structure to squirrel escape behavior. They suggested that clearings more than 75 m wide may be the

limit of a successful glide and, therefore, may be avoided by flying squirrels. If that is true, clearcuts may be effective

barriers to dispersal and movement. Knowledge of the amount of structural alteration that a flying squirrel population will

tolerate in a mixed pine-hardwood ecosystem may provide implications for the overall suitability of the stand for other

species of mammals, particularly gray squirrels and fox squirrels (S. nige r), which consume similar foods and are also tree

nesters (Fischer and Holler 1991, Kantola and Humphrey 1990, Sealander and Heidt 1990).

Plying squirrels form nesting aggregations during winter that reduce metabolic stresses associated with thermoregulation

(Stapp and others 1991). The size of aggregations is inversely correlated with ambient temperatures (Goertz and others

1975; Muul 1968, 1974; Sawyer and Rose 1985). Since flying squirrels do not excavate their own tree cavities, den trees

and snags are critical habitat components (Bendel and Gates 1987, Doby 1984, Gilmore and Gates 1985, Loeb 1993, Muul

1974, Sawyer and Rose 1985, Weigl 1978). The scarcity of suitable nest sites has been suggested as a possible cause for

increased interspecific aggression between flying squirrels and other cavity-nesting species such as gray squirrels (Doby

1984), red squirrels (Z ’m iasciurus hudsonicus)(Muul1968), and woodpeckers (Conner and Rudolph 1989, Stabb and others

1989). The conflict between flying squirrels and red-cockaded woodpeckers (Picoides borealis, RCW) over available

cavities is apparently severe because both species prefer cavities with small entrances (Loeb 1993). Where they occur

together, flying squirrel use of RCW cavities has reached levels of 21 percent (Loeb 1993) and 25 percent (Dennis 1971).

Questions addressed in this first year’s research were: (1) What are the population dynamics of flying squirrels in the

mature habitat type represented by this group of study areas?, (2) In what densities do squirrels occur on these stands?, (3)

What is the reproductive rate of local populations of flying squirrels?, (4) Do any forest habitat variables of interest differ

with respect to future treatment group or by replicated subset?, (5) Do any of these habitat variables appear to be critical

to squirrel nest-site selection?, and (6) What ectoparasites am associated with flying squirrels in this habitat type?

METHODS

Study Area Layout

Three replications of seven treatments (control, pine-hardwood single-tree selection, pine single-tree selection,

pine-hardwood shelterwood, pine shelterwood, pine-hardwood seed tree, and pine seed tree) were selected for this study (fig.

1). During September 1992, 630 nest boxes (30 boxes per stand on 21 stands) were installed at a height of 3 to 4 m on

trees scheduled to be retained after cutting. Box trees were selected to form a grid with 60-m spacing between trees and

rows. A 60-m buffer zone was retained around the outside of the grid to approximate one-half the mean maximum distance

moved (MMDM) and to allow for density estimation from grid captures using the stand area without creating an inflationary

bias (Wilson and Anderson 1985). Where habitat macroplots (see explanation below) were available, a box was placed on

83
Fort Smith

160 0

5

014 0

Hot Springs

Figure LApproximate locations of the 21 experimental stands in the Ouachita

mountains of western Arkansas. &and numbers correspond to treatment

numbers in Table 1. Stands in the same replicated treatment group denoted

by sin&r icons, i.e. hatched circle, filled diamond, or open circle.

84
a tree within the plot. That tree was then substituted for the nearest gridpoint tree. Only habitat plots inside a 60-m buffer

zone from the stand boundary were used. Of the 14 macroplots in each stand, a mean of 8.4 plots per stand (SE = 0.40)

contain box trees. Figure 2 shows a typical stand layout and distribution of box trees,

Habitat Measurements

Fourteen habitat macroplots were established in each stand, 12 in the treatment area and 2 in greenbelt (uncut strips

along ephemeral creek channels). Each macroplot consists of an 11.3-m-radius (0.04 ha) circle containing 2 nested 4 by

8 m (0.006 ha) rectangular subplots. Pretreatment measurements were taken on all woody vegetation within 294 macroplots

across 21 stands from July to December 1992 (Guldin and others, 1994). Squirrel boxes were located on trees in 169 of

these macroplots. The 14 macroplots per stand (0.6 ha per stand) proved to be an inadequate area to accurately account

for snag density. Therefore, additional snag data collected on the 9 stands comprising the future control, PH/STS, and

PH/SW treatments were used in the analysis. Snags were talhed along parallel 15-m wide strips averaging 1,328 m through

each stand and covering an average 2.0 ha per stand. In additian, estimates of horizontal vegetative density were made on

the same 9 stands at 30 random points along the 15-m wide strips. The percentage of horizontal foliage cover on a

0.5-m-square checkerboard was estimated from 15 m away at elevations of 0.25, 1.0, and 2.0 m.

In order to investigate the effect of adjacent habitat condition on squirrel populations in study areas, vegetative types

at the four cardinal directions from each study area were characterized as (1) mature pine-hardwood forest, (2) immature

plantation (~20 years since harvest), or (3) pasture. Ground reconnaissance and low-level aerial photographs were used to

determine adjacent habitat characteristics. Using the combined categories for the four adjacent habitats, each stand was

given a rank from 1 to 12 based on the similarity of the surrounding areas to the mature stand type (1 = most similar. 12

= most different).

Nest Box Monitoring

Nest boxes were checked during January, February, and March 1993. All adult squirrels captured were marked with

two numbered metal ear tags, weighed, sexed, examined for reproductive condition, and released at the point of capture.

Because of their small size, juveniles less than 5 weeks old were returned to the nest untagged. We did not toe clip young

for identification because the magnitude of any possible resulting reduction in fitness was unknown. A tissue sample was

collected from each squirrel and stored in 95 percent ethanol to permit later genetic evaluation of kinship between nestmates.

When possible, fresh fecal samples were collected. After the third survey in March, entrance holes were covered, and any

nests present were removed. Mothers with young under 8 weeks of age were returned to the nest; those boxes were closed

in April and the remaining nests were collected. Boxes will remain closed for 7 months to minimize the effect of artificial

nesting habitat on squirrel use of experimental stands.

Data Analysis

The Kruskal-WaIlis one-way ANOVA was used to analyze habitat variables and numbers of marked squirrels on each

of the 21 mature stands in subsets grouped by future treatment (3 stands each) and by 7-treatment replicated sets. The

Mann-Whitney U test was used to compare means of habitat variables for stands with and without squirrels. The

Mann-Whimey U test was also used to test for mean variable differences between macroplots in which squirrels nested and

macroplots across all stands. Habitat variables on stands with and without squirrels were subjected to logistic regression.

Spearman rank-order correlations were calculated for all variable means across the 21 stands. Adjacent habitat rankings

were compared with numbers of marked squirrels on study areas using Spearman rank-order correlation. All statistical tests

were performed using CSS:Statistica (Statsoft ~1991).

RESULTS AND DISCUSSION

Abundance and Nest Box Use

One hundred and eighteen squirrels (91 adults, 27 juveniles) were captured and marked on 16 stands; 16 additional

juveniles observed when too young to mark, were subsequently moved by their mothers and not seen again. Five stands

yielded no squirrels (table 1). Squirrels constructed nests in 56 boxes on 16 stands (X = 3.5 nests per stand, SE = 0.89).

Excluding maternal nests, thirty-four boxes with nests were occupied by adult squirrels when checked, yielding a total of

85
EPHEMERAL -_

50 m

-

Figure 2.-Typical stand kyout showing 60 x 60-m grid with 30 numbered trees

containing squirrel nest boxes. Encircled numbers indicate a box tree in

an 11.3 m-radius habitat macroplot.

86
96 squirrels (X = 2.8 adults per box, SE = 0.237). A maximum of six squirrels was found in one box. While no

completely formed nests were found on the five stands without squirrels, one to five boxes on four of the stands showed

evidence of squirrel presence such as balls of shredded eastern redcedar or acorn and hickory nut hulls. One hundred and

forty-three boxes showed signs of squirrel use (1.57 boxes per adult squirrel). Fifty-six contained platform or chamber nests,

22 held incompleted nests, and 65 contained acorn and/or hickory nut hulls and had evidently been use d as feeding stations.

Increasing box use on study areas was positively correlated with the numbers of marked adult squirrels (rs = 0.74,

P = 0.0001, N = 21). There were 1.62 adult squirrels marked per observed nest.

Weights of adult males and nonmaternal females averaged 67.45 g (SE = 0.85, N = 86) and monthly mean weights

did not vary significantly over the sampling period, whether compared as a combined group (fig. 3) or separately (table 2).

Weights of maternal females averaged 86.96 g (SE = 1.14, N = 48) and also did not vary over the sampling period when

monthly means were compared to the mean weights of all maternal squirrels (Chi-square = 0.148, P = 0.98, Table 2). The

mean weight of maternal females actually increased about 4 g in April over the weight in January, indicating that nursing

females were generally able to maintain body mass throughout the nursing period.

Of the flying squirrels captured and marked in 1993, 11 percent were marked in January, 40 percent in February, and

47 percent in March. The 27 young were added to the population during February and March, but 40 and 35 new adults,

respectively, were also marked during those months. While only 12 maternity boxes were left open after March, 3

additional new adults (2 percent of the total marked) were observed and marked when those boxes were closed in April,

Because substantial numbers of new squirrels appeared during the second and third surveys, the total number of marked

squirrels is considered a conservative population estimator, probably underestimating the local population of squirrels using

each stand, particularly considering that 18 young squirrels and several adult escapees were observed but not marked. The

total number of marked squirrels may, in this case, be the best local population estimate.3 The “Jolly” open population

estimator (Pollock and others 1990) was not applicable to these data because of the small number of sampling occasions.

The number of marked squirrels and stand area were used to calculate squirrel density (Table 1). Nineteen squirrels

were recaptured in boxes different from those in which they were originally observed. The mean maximum distance moved

(MMDM) was 105 m (SE = 12.55, N = 19). The buffer zone of 60 m around the grid of box trees within the stand

boundary very closely approximated one-half the MMDM, a compensator for edge effect suggested by Wilson and Anderson

(1985). Though the density of flying squirrels on this set of similar stands (Z = 0.37 per ha, SE = 0.10, N = 21) might

seem low compared to those ranging from 1.1 to 12.0 per ha reported elsewhere (Burt 1940, Jordan 1948, Muul 1968,

Sollberger 1943, Stojeba 1978), no studies have investigated flying squirrel population density and abundance in habitats

closely matching conditions present in this study. Apparently, the structure of the stands under investigation here

(predominately pine with scattered hardwood on upland south slopes) constitutes a minimal level of one or more critical

habitat features required by southern flying squirrels. Indeed, this may also be the case for other small mammals as well.

In a separate study of small mammals on 9 of these and 11 other similar stands (20 total), Tappe and others (1994) trapped

each stand for a mean of 524 adjusted trap nights (TN, subtracting snapped empty traps) in 1991 and 1,068 adjusted TN

in 1992. In 1991, only three species of small mammals were captured in mean frequencies higher than one individual per

stand (O&j/ha). One of those, Pe rom yscus spp., included P. leucopus, P. gossypinus, P. m uniculatus, and P. attw ateri

lumped together because of the diiculty in field identification. Mean numbers of each species captured per stand across

the 20 trap@ stands w e re Pe rom yscus spp. 8.5 (SE = 2.15), O ch rotom ys nuttalli 2.6 (SE = 0.67), and Blarina carolinensis

6.4 (SE = 1.85). In 1992, only two species were captured in greater mean densities than one per stand: Pe rom yscus spp.

4.8 (SE = 0.91), and B. carolinensis 1.6 (SE = 0.23). Considering these results, the mean of 5.6 flying squirrels per stand

observed in this study suggests that flying squirrels occur in these stands in frequencies compamble to the most numerous

forest-floor small mammals, or at least that nest boxes capture flying squirrels at rates similar to the sampling of forest-floor

small mammals using Sherman live traps.

In 8 instances, females moved from boxes that they had occupied alone or shared with other squirrels to establish a

maternity box. Mean dispersal distance was 92.5 m (SE = 14.36, N = 8). In one other instance, a female remained in the

box she had previously shared with other adults after the other squirrels moved out. In addition to females dispersing to

establish a maternity box, 11 other adults were recaptured in boxes other than those in which they were frost observed.

Mean distance for those movements was 115 m (SE = 19.09). Thirty-one adults were recaptured once, 7 others were

captured twice. On two occasions during the survey period, groups of six and five squirrels, respectively, having shared

boxes for 1 to 2 months, vacated them. Some were recaptured in other boxes; others were not seen again. The nesting

material in both abandoned boxes was wet, muddied, and compacted. Squirrels which were not recaptured in other boxes

presumably relocated to natural cavities. Madden (1974), Muul(1968), and Stojeba (1978) concluded that southern flying

3 Hines, J.E. 1993. U.S. Fish and Wildlife Service. Personal communication with author dated October 1, 1993.

87
squirrels in New York, Michigan, and Arkansas, respectively, vacated nests that had become dirty and flea infested.

While it might be argued that nest-box-use data reported here could have resulted from immigration of squirrels onto

the experimental stands during the survey period, the following evidence suggests that the new squirrels observed during

each survey period were probably either residents on experimental stands or were squirrels whose home ranges overlapped

the study areas:

(1) The fact that squirrels found boxes indicates that the home ranges of captured squirrels at least overlapped onto

experimental stands.

(2) Doby (1984) considered the fact that southern flying squirrels in hardwood forests of North Carolina used nest

boxes “almost immediately” after installation as evidence supporting the hypothesis that nesting cavities were in

short supply due to intense competition with gray squirrels. Only 11 percent of the total number of squirrels

marked in this study were captured during the first survey in January, two months after boxes had been installed.

Squirrels first seen during the second and third surveys may have started the winter in established cavities and

t selected boxes after the first nests became soiled.

(3) A Spearman rank-or&r correlation test of the relationship between the number of marked squirrels on a study area

and the increasing dissimilarity of the surrounding habitat to the mature forest type yielded a weak positive

:correlation (r, = 0.382, P = 0.088, N = 21). Stands with less suitable surrounding squirrel habitat (pasture or

\ young plantation) seemed to have larger squirrel populations. Just the opposite would presumably be the case

were squirrels immigrating onto study areas from surrounding stands.

(4) The dynamics of flying squirrel cavity use apparently include multiple refugia throughout the home range to which

squirrels can flee for protection or which can serve as auxiliary nesting sites (Fridell and Litvaitis 1991, Gilmore

and Gates 1985, Heidt 1977, Muul 1968, Stone 1993). In this study, released squirrels often glided directly to

den trees or snags and entered cavities, corroborating the supposition of preexisting natural refugia which were

augmented by nest boxes. Mull (1968) observed individual flying squirrels enter as many as 9 different natural

cavities when pursued through their home ranges. The rather low box use frequency of 1.57 boxes per adult

squirrel reported here would also suggest that other natural refugia were avaiable to squirrels on these study areas.

A similar defensive strategy is employed by hoary marmots (Marmota caligata), the largest North American

ground squirrel. Hoary marmots maintain many auxiliary burrows throughout their home range which are used

as refugia for marmots foraging nearby. Tauhnan (1990) found that one group, ranging from 7 to 12 marmots,

defended a territory of 12 ha in Washington on which they maintained 71 burrows, only 4 of which were used

for sleeping. Foraging marmots ran to the nearest burrow when alarmed or threatened.

Since flying squirrels often nest on the periphery of their home ranges (Bendel and Gates 1987; Stone 1993), nest

boxes may allow squirrels to use part of a harvested study area for nesting, even though they might forage predominantly

in uncut greenbelt areas or in adjacent stands. Telemetry data on collared squirrels gathered during the summers of 1994

and 1995, when boxes will be closed, will answer questions about squirrel range and habitat use on control and treated

stands without any possible bias from additional artificial nesting habitat.

Reproductive Demographics

Twenty-three boxes were used as maternity nests. A total of 45 young were observed (K = 1.96 per litter, SE = 0.117,

N = 23). The sex ratio of young (218 to 20?) was not significantly different from the sex ratio of adults (403 to 519) (2

x 2 contingency table test, Chi-square = 1.24, P = 0.27). Young were marked and released from 14 of those nests after

reaching at least 8 weeks of age: mothers and young vacated 8 others before the young were old enough to mark.

Using the weight and length data for young flying squirrels from birth through 1 year reported by Linzey and Linzey

(1979), birth dates for each of the 23 litters were estimated (fig. 4). Several of the litters were discovered only 1 or 2 days

after birth. Birth dates tanged from February 8 to March 13 (X = February 25). Allowing for a 40&y gestation period

(Sollberger 1943), the corresponding range of days during which conception occurred was between December 30 and

February 1. These conception dates largely agree with other reports that have indicated dates of conception for flying

squirmls during late January and early February in Arkansas (Heidt 1977, Stojeba 1978, Stone 1993) and northern Louisiana

(Goertz and others 1975). Gihnore and Gates (1985) recorded conception dates in southern flying squirrels ranging from

88
Table I.-Sum m ary of flying squirrels m arked d uring spring 19 9 3 in nest boxes on the 21 experim ental stands

grouped accord ing to the 7f& re treatm ents in the Oaach ifa M ountains of Ark ansas

Tre atmen t Adults young Total Stand Squirrel

cate gory’ m ark e d Gende r m ark e d Gende r m ark e d are a (h a)+ density (#/h a)

1 cant 5

2 cant 6

3 cant 8

4 PH ISTS 3

5 PH lSTS 16

6 PH lSTS 1

I PISTS 3

8 PJSTS 10

9 PISTS 0

10 PH /SW 0

11 PH lSW 6

12 PH ISW 0

13 P/SW 3

14 PISW 2

15 P/SW 1

16 PH /ST 0

17 PH lST 20

18 PH /ST 0

19 P/ST 2

20 P/ST 1

21 P/ST 4

TOTALS 9 1

Id 49

26 4Q

46 49

2d 1Q

9 6 79

19

16 29

7d 3Q

3d 39

26 l?

29

1Q

88 129

2Q

1Q

16 39

403 519

7

3

3

0

3

0

0

2

0

0

2

0

0

2

0

0

4

0

0

1

0

27

36 44

26 19

39

id 29

16 1Q

Id 19

Id’1Q

49

Id

148 13Q

12 14.9 0.81

9 16.0 0.56

11 15.8 0.70

3 16.1 0.19

19 14.9 1.28

1 15.0 0.07

3 16.0 0.19

12 15.6 0.77

0 13.3 0

0 15.4 0

8 17.0 0.47

0 16.0 0

3 15.2 0.20

4 16.5 0.24

1 14.9 0.07

0 16.0 0

24 14.5 1.66

0 15.5 0

2 14.5 0.14

2 16.6 0.12

4 15.0 0.27

118 2 = 15.5 ‘;I = 0.37

SE = 0.19 SE = 0.10

t Future tre atmen t groups: Cont - control, PH lSTS - pine-bardw oodh ingh re e sele ction, P/STS - pine/sin@

tree sele ction, PH /SW - pinebardw oodh b elte rw ood, P/SW - pine/sh e lte rw ood, PH lST - pioebardw oodlseedtre e, P/ST - pinelseedtre e.

? Stand boundaries dete rm ined by ground trave rse ; m apping and subsequent calculation of stand area perform e d

using Gene ric Cadd 6.0 (Autodesk Retail Products ~ 19 9 2).

89
8 0

60.

40

20

0

T-F

T

t

7 5 29 17 43 18 7 8

JAN FEB MAR APR

Figure 3.-Mean weights(Z * 1 SE) for maternal females and other adult males and females

during each month of the sampling pe riod, January - April, 1993. Numbers below

bars indicate numbers of squirrels used to calculate mean. M % F = all males and

nonmaternal females combined, MAT-F = maternal females. Means for neither

category were different across months (M & F chi-square = 1.01, P = 0.80, d.f =

3; MAT-F chi-square = 0.148, P = 0.98, d.f = 3).

90
Table 2.-Adah m ean w eigh ts (g) of sexaally active and inactive m ales and pregnant and nonpregnant fem ales during the sam pling periad,

January IO April, 1993. Ch anges in proportions for each group across m onth s w e re investigated w & h the ch i-square test, using

m ean w eigh t for sexually active and inactive m ales and nonm ate rnal fem ales com bined as the e xpected w eigh t for th ose th re e

groups, and the me an for m ate rnal fem ales as the e xpected w eigh t for th at group

Gender

S& Y

active FebrWUy MaI-& April

Meall

weight

Comb Chimean#

square Prob.

Male 00 63.00

(1.0 )’

2p

Male Ye 80.60 71.83 69.80

(2.75) (2.82) (1.18)

5 6 10

Female no 0

Female yes

64.44 65.39 63.67 64.81 67.45

(1.89) (2.11) (1.86) (1.29) (0.85)

9 18 3 32 86

65.50 67.00 68.33 66.47 67.45

(2.62) (1.61) (1.20) (1.36) (0.85)

14 15 3 32 86

87.12 85.06 91.00 86.96

(1.79) (1.78) (3.56) (1.14)

17 18 8 48

68.00

1

72.73 67.45

(1.42) (0.85)

22 86

0.705 P = 0.87

2.93’ P = 0.40

0.07’ P = 0.96

0.15s P = 0.98

l Standard error of mean.

t Numbe r of squirrels used to calculate mean.

* Mean of weights of all sexually active and inactive males and nonmaternal females used as expected v&e to calculate chi-sqm for

each of those groups.

5 Tbree degrees of freedom.

II Two degrees of freedom.

9 1
late February through early March in Maryland. Linzey and Linzey (1979) reported mating dates from mid-July through

early January in southern Alabama.

Four different adult females, two of them maternal, were observed nesting with other adults. One lactating female and

two young were captured together in a box with two adult males in February. In March, the female and males were

recaptured, but the young were not present. Another maternal nest contained an additional adult female. That litter was

apparently successful, as the maternal female, the second female, and the two 9-week-old juveniles were released and the

box closed in April. These are apparently the first records of nest-sharing by maternal southern flying squirrels. Bendel

and Gates (1987) found that the core activity areas of adult female home flying squirrels in Maryland did not overlap and

that adult females did not share dens with other adults. Of four adult females (three of them maternal) tracked in New

Hampshire by Fridell and Litvaitis (1991), core activity areas of two overlapped by 50 percent, though none shared nesting

sites. Stapp (1991) also reported solitary nesting in captive maternal females following parturition. Mull (1968) Sollberger

(1943), and Stone (1993) reported overlap of home ranges and sharing of nest boxes between adults, with the exception of

brood nest defense by maternal females. Sollberger (1943) found that females with pups would kill strange adult males

introduced into the cage.

Ecological Relationships

Descriptive statistics on numbers of flying squirrels and on habitat variables used in analysis of stand relationships are

given in Table 3. Table 4 shows means for several habitat variables and numbers of marked squirrels by stands grouped

according to future treatment. Mean totals across all 21 stands are given for each variable. Results of the Km&al-Wallis

one-way ANOVA show no differences in the means of any variables across the seven future treatment groups (table 4).

Comparing means of all variables across replicated zones showed that only azimuth differed between groups of stands (table

5). The Mann-Whitney U test comparing means of habitat variables between stands inhabited by squirrels and those without

showed no differences between the two groups for any variable.Based on logistic regression, none of the habitat variables

were significantly associated with squirrel presence or absence.

Stem counts of upper and lower midstory hardwoods (16.7 - 24.2 cm in d.b.h. and 8.9 - 16.6 cm in d.b.h., respectively)

tended to increase with increasing squirrel density (rs = 0.39, P = 0.08, N = 21; and r, = 0.37, P = 0.09, N = 21,

respectively). Basal area of overstory hardwoods (oaks and hickories 2 24.3 cm in d.b.h.) was not correlated with squirrel

numbers (r. = -0.16, P = 0.50, N = 21). Hard mast production was not directly measured on these study areas, and it is

possible that differences in mast crop success across experimental stands were partially responsible for the observed

differences in squirrel population numbers. The average slope on each stand was negatively correlated with the number

of marked squirrels (r. = -0.480, P = 0.028, N = 21). The prevailing percentage slope of stands with squirrels (N = 16)

tended to be lower than on stands without squirrels (N = 5) (U = 16.5, P = 0.052). Slope was again somewhat flatter in

macroplots with nests (N = 12) compared with average slope of each stand across all areas (N = 21) (U = 76.5, P = 0.064).

These results suggest a tendency for squirrel numbers to increase on a stand as average slope decreases.

Weigl and others (1989) found that food supply was the most critical factor limiting the distribution of fox squirrels

in North Carolina. Where food resources declined below a certain level, fox squirrels “disappeared,” regardless of the

presence of other ecological necessities. Food resources may play an equally vital role in the use of habitat by southern

flying squirrels.* While harvesting operations and other logistical limitations precluded hard mast surveys on pretreatment

stands, mast surveys will be conducted during fall 1994 and 1995. Data on acorn and hickory nut production will provide

an additional variable with which to better understand squirrel habitat use during 1995 and 1996.

Mean stem counts of lower midstory pines were negatively correlated with numbers of marked squirrels

(rs = -0.442, P = 0.045, N = 21), suggesting that stands with lower numbers of smaller pines and a relatively more open

lower midstory canopy tended to have more squirrels. Comparing habitat means from plots across all stands (N = 21) with

only macroplots that contained boxes with nests (N = 12) indicated that fewer pines in the lower midstory class (8.9 to 16.6

cm d.b.h.) were found in plots containing squirrel nests (U = 66, P = 0.024). Squirrel numbers tended to increase as snag

densities increased (rs = 0.57, P = 0.10, N = 9). Horizontal foliage density was not correlated with numbers of marked

squirrels across the 9 sampled stands at any of the three vertical strata.

These results partially corroborate the findings of Bendel and Gates (1987) that flying squirrel habitat should include

trees of considerable height and a relatively open midstory. The trend toward higher density of snags as squirrel population

increases is consistent with the results of Bendel and Gates (1987), Doby (1984), Gilmore and Gates (1985), Muul(1974)

Sawyer and Rose (1985), and Weigl (1978). While other reports have not investigated the influence of slope on squirrel

’ Weigl, P.D. 1993. Wake Forest University. Personal communication with author dated October 21, 1993.

92
o-- c

1

I --- u

__._____---__----_----0 1

__ *__----------__--- c 1 .Fl __ .__----------___~-__~_~____-______--!~

__ .____---_-----__---_c_(_____-----__---0

-- *-----_---____~____ ~----_----___-_-_-~-t-i? c-n

l __--___---__------_~_+---~

a__---__----_----___O I

~--------___--_____o~---~_~

l --------- ---____--~-t--__-fl

~----__---____-____~-1,

*___--___-----_----

~___~~___~~~~~~~~~~~_~

----------=

~_---~-----___--___~“~

l ----------__---___vj--------___--C]

.----_---____--_____O_~

*--------- _--------bAl-___-----_____c]

t-------

------------0

*-------_--_____---C-‘-i?

*-----___----___---o-t---17

*-------- --_____---*_--------_____--_

*_-------------_--_ (--t_-L$

I

I JAN I FEB I MAR I APR

Figure 4.-Estimated dates of conception, birth, and weaning for each of 23 flying

squirrel litters found in nest boxes during 1993. Vertical marks indicate

dates on which litters were actually observed and handled. Length,

weight, and general appearance were used to estimate birth dates

according to the growth tables of Linzey and Linzey (1979). Conception

dates were estimated at 40 days prior to birth, and dates for weaning were

estimated at 6 weeks after birth (Sollberger 1943). Format offigure after

Weigl and others (1989). Black circles represent estimated conception

dates, open circles represent birth dates, and open squares represent

estimated weaning dams at 6 weeks after birth.

93
Table 3.-Descriptive statides for flying squirrel numbers and habitat variables across 21 mature stands

Variable’ Mean SE Minimum Maximum

Marked

squirrels 5.62 1.46 0 24.0

slope 10.63 0.87 6.0 19.20

Azimuth 184.0 7.94 128.0 256.0

BA pine 80.48 1.89 67.50 97.86

BA hardwood 11.56 1.42 1.07 31.10

PINECTLG 3.62 0.50 0.80 10.21

PINRCTSM 4.26 0.51 0.71 10.50

HDWDCTLG 2.75 0.19 1.00 4.29

HDWDCTSM 12.0 0.66 6.50 17.64

TRREHTMN 22.09 0.36 19.30 24.70

TREEAGMN 62.84 1.29 55.0 84.10

l Variable descriptors: Habitat means based on measurements taken at 14 - 0.04 ha macroplots per stand. BA

pine - basal area of pine trees 2 24.3 cm in d.b.h.. BA hardwood - basal area of hardwood trees 2 24.3 cm

in d.b.h., PINECTLG -mean numbers of pine stems 16.7 - 24.2 cm in d.b.h. in macroplots. PINECTSM - mean

numbers of pine stems 8.9 -16.6 cm in d.b.h. iu macroplots, HDWDCTLG - mean numbers of hardwood stems

16.7 - 24.2 cm in d.b.h. in macroplots, HDWDCTSM - mean hardwood stems 8.9 - 16.6 cm in d.b.h. in

macroplots, slope - mean of 14 measurements per stand taken in degrees at the center of each macroplot,

azimuth - measured in degrees simibuly to slope, TRREHTMN - mean height (m) of dominant pines across

aif stands (one in each of 14 macroplots per stand), TREEAGMN - mean age of dominant pines (one in each

macroplot).

94
Table L-Me ans and standard errors for num b ers of frying squirrels and h abital variables grouped by J& tare treatm ents (th ree stands

each ). Krusk al- W allis one-w ay ANOVA rest.& w ith P-level sh ow n at righ t

Future tre atmen t groups (Th re e stands per group)’

H abitat 1 2 3 4 5 6 7

t

Krusk al-W aIIis H ,

variables C O N T PH lSTS PlSTS PH lSW P/SW PH lST P/ST d.f. = 6, N = 21 Probability*

Mark e d

squirrels

Slope

Azimuth

BA pine

BA h ardw ood

PINECTLG

PINFXTSM

H DW DCTLG

H DW DCTSM

TREEH TMN

TREEAGMN

10.7§

0.89 1

7.7 5.0 2.7 2.7 8.0 2.7

5.70 3.61 2.67 0.88 8.0 0.67

7.1 8.0 12.9 10.8 11.3 11.9 12.4

1.03 1.57 2.38 2.75 1.26 2.69 3.46

183 201 148 19 7 19 6 19 3 168

22.11 21.05 12.44 30.50 15.10 21.38 24.66

86.1 75.1 76.2 9 1.4 77.8 83.0 73.7

6.61 3.82 2.01 3.27 1.77 5.84 3.26

8.2 13.2 19 .2 10.8 9 .5 11.9 8.1

3.21 4.03 6.05 2.32 4.29 2.44 2.21

2.7 2.9 3.6 2.7 3.2 5.0 5.2

I.51 0.46 1.28 0.33 1.04 1.52 2.52

4.0 4.1 4.7 3.1 4.5 4.2 5.3

1.08 1.62 2.9 5 1.25 1.41 0.52 0.72

2.6 2.9 2.7 2.8 3.0 3.0 2.3

0.53 0.69 0.71 0.58 0.41 0.53 0.66

11.3 10.9 12.1 10.2 14.4 12.4 12.8

1.67 3.44 2.64 0.55 0.12 0.77 1.53

23.4 21.1 21.8 23.3 22.3 21.0 21.7

0.50 1.77 0.78 0.35 1.38 0.23 0.29

63.7 62.5 59 .7 69 .2 61.3 61.3 62.2

2.15 0.70 2.49 7.59 3.58 2.12 1.63

4.88 0.56

7.16 0.31

6.50 0.37

7.77 0.26

5.38 0.50

3.02 0.81

2.21 0.9 0

1.32 0.9 7

4.71 0.58

7.11 0.31

2.78 0.84

t Future tre atmen t groups detined in table 1.

t H abitat variable descriptors given in table 3.

* A probability le ve l less th an 0.05 indicate s th at at le ast one of the tre atmen t group m e ans diffe rs signi& antIy from the oth e rs.

8 Meall

B Standard error

95
Table S.--Means and standard errors for num b ers of flying squirrels and h abital variables for stands grouped

by replicated zone (seven each ). Krusk al-W allis one-w ay ANOVA results and P-value sh ow n at righ t’

Habitat

variables i

Replicated treatment groups

KruskaLWallis H

1 2 3 d.f. = 2, N = 21 Probability

Marlred

sqUirrels

' slope

AZkUUtb

BA pine

BA hardwood

PINECTLG

PINECTSM

H DW DCTLG

H DW DCTSM

TREEH TMN

TREEAGMN

12.89

1.50

181.0 A

13.67

81.79

2.94

12.90

1.26

3.51

0.84

4.06

0.54

2.57

0.37

12.36

1.16

21.47

0.61

65.91

3.16

6.71

3.16

9.10

1.39

211.7 A

10.57

80.10

3.77

8.9 2

1.44

4.48

1.13

5.06

1.19

2.79

0.36

11.43

1.25

21.70

0.60

62.74

1.71

5.71

2.70

9 .9 3

1.42

159.3 B

10.04

79 .54

3.52

12.86

3.86

2.86

0.54

3.66

0.84

2.9 0

0.31

12.21

1.18

23.11

0.53

59 .86

0.9 0

0.14

3.99

7.04

0.64

2.75

0.79

0.83

0.21

0.36

0.9 3

0.14

0.03

0.73

0.25

0.67

0.66

0.9 0

0.84

* Group means followed by unlike letters are signScantly different (P < 0.05).

t Variable descriptors defkd in table 3.

5 Standard error

96
habitat suitability, the indication of a possible trend in these results toward squirrels occupying flatter stands or portions of

stands may reflect a greater mast production in wetter areas or the difficulty of squirrels foraging on the ground effectively

and safely in steeper terrain.

Fifty-four nests were collected. Nesting material consisted almost entirely of shredded eastern redcedar bark. Most

nests filled the box and contained a central chamber; a few were platforms in which nesting material filled about one-third

of the box. Occasionally oak leaves and twigs lined the bottom of the box. All collected nests were dried using the Berlese

apparatus and invertebrates were preserved in 75 percent alcohol. Preliminary analysis of 23 nests (43 percent) yielded

invertebrates representing 4 classes, including 29 families from 11 orders of insects and 10 families of mites and ticks from

2 orders of arachnids (table 6). Six of the families identified are ectoparasites of flying squirrels: Ceratophyllidae (fleas);

Glycyphagidae, Trombiculidae, Laelapidae, and Macronyssidae (mites); and Ixodidae (ticks). No vertebrates other than

flying squirrels were found in nest boxes. Flying squirrel nests clearly support a diverse and extensive invertebrate fauna.

Changes in the kinds and relative abundances of ectoparasites in nests on harvested stands compared with those in nests

on control and pretreatment stands may help to elicidate any differences in environmental stress on local populations of

squirrels.

Human activities, such as logging or livestock grazing, can cause habitat fragmentation and other changes on a time

scale that precludes the adaptive modification of predator-avoidance behaviors in prey species. The alteration of critical

habitat features required for camouflage or preferred nesting sites, for example, may give a predator an advantage that can

lead to the decimation of an affected bird population (Martin 1993). While this study will concentrate on responses of

southern flying squirrels to habitat manipulations, it must be acknowledged that any changes that affect the predator-prey

interactions of squirrels with owls, for example (see Rosenberg and Anthony 1992), may play a significant, though unknown,

part in observed differences in squirrel population dynamics and habitat use.

Future Research Activities

The next phase of this study will attempt to ascertain responses of local populations of flying squirrels to the cutting

treatments imposed during summer 1993, and to evaluate squirrel use of those areas that they continue to inhabit. Winter

nest box monitoring will continue, and squirrels will be tracked by radio telemetry on selected control and harvested stands

during the summers of 1994 and 1995. Four questions will be addressed:

(1) Are there differences in the demographics of flying squirrel populations on experimental stands before and after

treatment?

(2) Are there differences in squirrel population densities on stands before and after treatment?

(3) How do home range sizes and core activity areas vary between control stands and altered stands?

(4) Are there apparent differences in habitat use patterns among the treated and control stands?

Based on the resource-dispersion hypothesis (Macdonald 1983), we expect that squirrel ranges may be larger where

the density of limiting resources such as mast-producing trees and cavity trees is reduced. This hypothesis is supported by

the results of Geffen and others (1992) in which home range of Blanford’s foxes (Vulpes cuna) were found to be enlarged

where favored creek bed habitats were widely dispersed.

Squirrels that remain on or return to treated stands will probably concentrate their activity in the more productive uncut

greenbelt areas along ephemeral creeks, as suggested by the “ideal free distribution” theory of Fretwell and Lucas (1970).

The decrease in resource levels on manipulated stands combined with the already low density of squirrels on uncut stands

should permit a more unequivocal evaluation of habitat-use patterns through radio telemetry than would be possible were

squirrels abundant (Rosenzweig 1985). Single-tree selection methods will likely produce the smallest changes in population

parameters. Nixon and others (1980) found that selective cutting of forests in Illinois had no apparent effect on resident

fox or gray squirrel populations.

ACKNOWLEDGMENTS

We appreciate the reviews of an earlier draft of this document by KG. Smith and P.D. Weigl. K.G. Smith, SD.

Grump, B.D. Pounds, N. McCarty, C. Hill, and B. Vaught provided essential field assistance. Logistical support for field

assistants were provided by the USDA Forest Service Caddo district headquarters of the Ouachita National Forest, under

the direction of J.S. Watson and B. Cochran. The initial support of J.B. Baker of the USDA Forest Service, Southern Forest

97
Table 6.-lnvertebmtes collected from squirrel nests, with probable ecological associations (Borror and DeLong 1964, Kmntz 1978). Generic and

specifw names provided when known

Cl&W Order Family Ecological Association

Insecta Isoptera

Epbemeroptera

Collembola

Psocoptera

Homoptera

Lepidoptera

Orthoptera

Coleoptera

Siphonaptera CeratophyBidae

Diptera Cecidomyiidae

Psychodidae

Phoridae

Asilidae

Sciaridae

Hymenoptera

Arachnida Acarifonnes

Parasitiformes

Diplopoda

Nematoda

Kalotennitidae

Baetidae

Poduridae

Emtomobryidae

Liposcelidae

PseudocaeciBidae

Cicadellidae

Pyralidae

B1attidae

Gryllidae

Carahidae

Histeridae

Staphylinidae

Sylvanidae

Helodidae

Braconidae

Pteromalidae

Mymaridae

Sphecidae

Formicidae

Apidae

Vespidae

Cynipidae

BdeBidae

Chelytidae

Glycyphagidae

Oribatidae

EpBohmauniidae

Pyemotidae

Trombicnlidae

Ixodidae

Macronyssidae

LaelPpidae

Termites, damp wood

Small mayfly, larva

Springtail, found in decaying vegetation

Springtatl, found in decaying vegetation

Liposcelis spp., fungus feeders, common in wood structures

La&es&a spp., found in straw and plant matter

Leaf hopper, plant feeders

Snout moth, found in shelters, grass feeders

Roach, found in shelters, diet varied

Cricket

Ground beetle, Cafusomu spp., larvae predatory on other invertebrates

Hister beelle, predaceous on other insects in decaying organic matter

Rove beetle, predaceous on insects in decaying vegetation

Oryzaephifus spp., sawtooth grain beetle

Found in damp rotting litter or tree cavities

Diamanus spp., Urchopeas spp., rodent ectopasasites, known disease vector*

Resin midge, Retinodiplosis resinicoloides, associated with tree resin

Psychmia spp., found in decaying vegetation

Humpbacked By, found in decaying vegetation

Robber flies, predatory on other insects

Fungus gnat, found in decaying plant matter

Parasitic on other insects

Parasitic on other insects

Parasitic on other insects

Trypoxylon spp., organ pipe mud dauber

Ant, Mynnica spp.

Bumble bee, Rombus spp.

Paper wasp, Polistes spp., construct nests in sheltered sites

Gall wasp, parasites on fly pupa

Parasitic on other invettebrates

Free-living predator on insects, may cause mange in mammals

Glycyphagus spp., parasitic mite*

Cepheus spp., Cam6es spp., found in leaf litter

Epilohmannia spp., found in decaying vegetation

Found in decaying vegetation

Chigger, Trombicula spp., parasite on mammals*

Tick, Lodes scapularis, parasitic on mammals*

Macronyssus spp., mammal parasite, disease vector*

Androlaelaps spp., Hirstionyssus spp., Hypoaspis spp., parasites found on

skin and fur of mammals, known transmitter of disease in m-ah*

Millipede, found in decaying plant matter

Free Bving larva

l Known m-al ectoparasites

98
Experiment Station, in the planning phase of the study is greatly appreciated. D. Harris (Womble district headquarters of

the Ouachita National Forest) and R. Grounds (Ouachita National Forest Headquarters) provided vehicles needed during

nest box installation. J.G. Guldin of the USDA Forest Service, Southern Forest Experiment Station, and T. Foti of the

Arkansas National Heritage Commission graciously shared habitat data collected by the silviculture and biodiversity research

groups, respectively. J. Singleton of the University of Arkansas at Fayetteville provided invaluable assistance with

identification of invertebrates. In addition to funding provided through the USDA Forest Service, Southern Forest

Experiment Station, this research was also supported by a grant from the Theodore Roosevelt Memorial Fund of the

American Museum of Natural History and a University of Arkansas Doctoral Fellowship.

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102
Breeding Birds of Late-Rotation Pine-Hardwood Stands:

Community Characteristics and Similarity to Other Regional Pine Forests’

Daniel R. Petit, Lisa J. Petit, Thomas E. Martin, Ronald E. Thill, and James F. Taulmar?

ABSTRACT

The relative abundances of bird species and the ecological characteristics of the overall

avian community were quantified within 20 late-rotation pine-hardwood sites in the

Ouachita and Ozark National Forests in Arkansas and Oklahoma during 1992 and 1993.

In addition, similarities in species composition and guild representation were compared

with those of forest types in other areas of the Southeastern United States to assess the

possible extent of generalizations to be made from this Ecosystem Management research.

A total of 55 bird species was recorded within survey plots during 1992 and 1993, but

only 10 species accounted for more than 80 percent of all individuals detected. Pine

warblers comprised approximately 40 percent of all individuals. Rank abundances of the

55 species were relatively consistent between years, especially for the most common

species. Numbers of species and individuals detected during point count surveys were

different between 1992 and 1993, although some of that discrepancy may be due to

interobserver variation. No significant differences were detected in bird species richness,

abundance, or diversity among the four geographic zones or among future harvesting

treatments. Bird communities were dominated by species that nest and forage in the

canopy. Similarity was relatively low between bird assemblages characterized on the

Ouachita Mountain sites and assemblages in other studies. Representation of nesting and

foraging guilds, however, was more closely aligned with guild structure found in other

forests. ln general, results from Ecosystem Management Research should be most

applicable to loblolly-shortleaf pine and oak-hickory forest types in the Southeast.

INTRODUCTION

The Ecosystem Management Research Program of the USDA Forest Service was designed to assess the effects of

traditional and nontraditional cutting and regeneration techniques on the flora, fauna, ecosystem function, and esthetic and

cultural properties of our national forests as well as the economic costs associated with each harvesting program. The

philosophy behind the ecosystem-level approach to managing federal lands is based on the perception that to serve the longterm, multiple interests of society, preservation of biodiversity and sustainability of natural resources must be viewed in a

holistic fashion (Salwasser 1991, 1992). This “new perspective” suggests that neither societal (monetary and cultural)

considerations nor ecosystem integrity (including sustainability) can be viewed independently of the other, and that

management units must be viewed simply as components within the scope of larger-scale watershed processes and functions.

The interactions of these complex, and often controversial, issues (e.g., Frissell and others 1992) are being investigated in

a series of demonstration projects within National Forests.

Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

Research Associate, Cooperative Fish and Wildlife Research Unit, University of Arkansas at Fayetteville; Currently

Research Fellow, Smithsonian Environmental Research Center, Edgewater, MD 21037; Research Associate, Cooperative

Fish and WildlifeResearch Unit, University of Arkansas at Fayetteville; Currently Research WildlifeBiologist, Smithsonian

Migratory Bird Center, National Zoological Park, Washington, DC 20008; Assistant Leader, Cooperative Fish and Wildlife

Research Unit, University of Arkansas at Fayetteville; Currently Assistant Leader, National Biological Survey, Cooperative

Wildlife Research Unit, University of Montana at Missoula, 59812; Wildlife Biologist, USDA Forest Service, Southern

Forest Experiment Station, Nacogdoches, TX 75962; Wildlife Biologist, USDA Forest Service, Southern Forest Experiment

Station, Hot Springs, AR. Currently Ph.D. Candidate, University of Arkansas at Fayetteville, 72701.

103
Ecosystem Management Research in the Ouachita and Ozark National Forests in western Arkansas and eastern

Oklahoma is comprised of three phases: Phase I provided a demonstration of the logistical aspects and feasibility of different

harvesting treatments. Phase II and Phase III are designed to assess the economic effectiveness of different harvesting

treatments as well as treatment effects on the biological, chemical, physical, and esthetic properties of pine-hardwood

ecosystems at the stand and watershed levels, respectively (Baker, this volume).

Natural pine forests and pine plantations often support fewer species of birds compared with mature deciduous stands

in the Southeastern United States (Hamel 1992, Smith and Petit 1988). Mixed pine-hardwood forests, on the other hand,

often equal or exceed pure hardwood forest types in species richness (Dickson and others 1980, Hamel 1992, Meyers and

Johnson 1978). Yet, both pine and mixed-pine forest types represent critical habitats for economically and socially important

game birds, declining neotropical migratory bird populations, and threatened/endangered species (Evans 1978, Hamel 1992,

Jackson 1988). The value of pine-associated habitats to bird and wildlife populations, coupled with increasing demands on

these lands for timber production and urban development (Jackson 1988, Knight 1987), has created an urgency among

wildlife biologists to better understand bird-habitat relationships and the impact of different management practices on bird

populations in the Southeast (Childers and others 1986, Harris and others 1974, Johnson 1987, Noble and Hamilton 1975).

Critical in this research is documentation of bird species that are associated with mature, naturally regenerated pine forests,

“controls” against which to compare different stand ages and management techniques.

This report summarizes information on the relative abundances and community characteristics of breeding birds

associated with late-rotational pine-hardwood forests before stand-level ecosystem management harvesting treatments were

applied (Phase II). Bird assemblages occupying these sites were compared with assemblages inhabiting mature pine and pinehardwood stands in other areas of the Southeastern United States. The degree of similarity among the different regional bird

communities allowed projection of the generality of the harvesting treatments on Southeastern pine/pine-hardwood bird

communities.

METHODS

Study Sites

In 1991, nine late-rotation pine-hardwood stands were selected in the Ouachita (7) and Ozark (2) National Forests of

northwestern Arkansas (table 1) to establish bird and vegetation sampling protocols to be used once Phase II treatment plots

were selected (see below). (At that time, these sites were targeted to represent pretreatment controls. However, timing of

Phase II timber harvesting allowed pretreatment data to be collected within the actual 20 Phase II sites. Consequently, these

nine sites provided only supplemental information on late-rotation pine-hardwood bird assemblages.) South-facing slopes

(including southeast and southwest) predominated on most sites. Stands had not been harvested for 75 to 90 years, and pine

and hardwood basal areas averaged approximately 7.7 m2Jha (range: 7.0 to 8.1 m2/ha) and 3.8 m21ha (range: 2.5 to 4.3

m2/ha), respectively. Canopies were largely closed (Percent canopy cover, mean = 84 percent; range = 79 to 88 percent,

N = 9), with mean canopy heights between 15 and 23 m (overall mean = 18 m). Most sites had well-developed

understories and midstories comprised mainly of Vaccinium corymbosurn L., Cornus jlorida L., h’yssa sylvatica Marsh.,

Quercus marilandica Muenchh., and Q. stellata Wangenh. Quercus velutina Lam., Q. rubra L., Carya spp., and Pinus

echinata Mill. were the primary overstory trees. All sites encompassed 16 to 25 ha.

In 1992 and 1993, bird surveys were conducted on 20 additional sites on which 5 different Phase II harvesting

treatments were to be applied during summer and autumn 1993. All stands had predominantly south-facing aspects (including

southwest and southeast) with slopes that ranged between 0 to 15 percent. Stand age (> 70 years), vegetative structure (mean

canopy cover = 82 percent, range = 78 to 87 percent; mean canopy height = 17 m, range = 15 to 20 m), and tree species

composition were similar to the late-rotational tracts studied in 1991 (Thill and others [this volume] provide additional details

of sites used in 1992 and 1993). The 20 Phase II sites were loosely grouped (based upon possible edaphic and climatic

differences [Baker, this volume]) into four geographic zones (five stands per zone) primarily in the Ouachita National Forest

in Arkansas and Oklahoma, but several sites were located in the southernmost district of the Ozark National Forest (table

1). Each group of five sites included one replicate of each of the four harvesting treatments (clearcutting, shelterwood, group

selection, and single tree selection) that were to be performed in 1993, in addition to an untreated control site (Thill and

others, this volume). All sites were 14 to 16 ha.

104
Table 1 .- Locations of late-rom’on pine-hanhood stat& studied in 1991-93 in the Ouachita and Ozark

National Forests in Arkansas and Oklahoma

Year

National

Forest Zone’ Compattment Stand

1991 Ozark 2 25

Ozark 2 16

Guachita 1601 11

Guachita 1610 11

Guachita 1614 24

Guachita 603 17

Guachita 1457 ACEF’

Guachita 473 11

Chtachita 462 11

1992-93 Guachita

Guachita

Ozark

Ozark

Guachita

Guachita

Guachita

Chtachita

Guachita

Guachita

Guachita

Guachita

Guachita

Guachita

Guachita

Guachita

Guachita

Ouachita

Guachita

North 458 16

North 457 12

North 46 18

Noah 70 10

North 284 11

East 1067 15

East 1119 21

East 1124 11

East 609 9

East 605 5

south 1658 5

south 27 1

south 35 42

south 1649 13

south 23 10

West 1292 2

West 833 1

West 62 6

West 248 17

West 896 7

l Geographic zone used in the Ecosystem Management experimental design. No designation of zone is

appropriate for preliminary data collected on the nine sites in 199 1.

’ Alum Creek Experimental Forest.

Bird Surveys

Bird abundance was estimated in five or six (depending on size of the site) 40-m radius (0.5 ha) circular plots spaced

evenly over each site. Bird survey plots (hereafter “plots”) were usually more than 150 m apart, but size or shape of some

stands permitted only 130 to 150 m of separation. Plots were more than 90 m away from edges (e.g., roads, younger

successional growth, different forest types). On 3 different days (= 3 visits) between 5 to 24 May 1991, 28 April to 2 June

1992 (75 percent of surveys completed before 15 May), and 1 to 14 May 1993, all birds seen or heard within plots on each

site were recorded. Ten minutes were spent at each plot. Individuals detected beyond 40 m, but within the site boundaries

were also noted. Birds seen flying or soaring above canopy trees and species that do not breed in the region (transients) were

excluded. Surveys were conducted between 06:OO and 12%) (> 90 percent were completed before 11:OO) on days without

strong winds or prolonged precipitation. (On several days, surveys were continued when light rainfall began after initiation

of bird counts on a site.) Bird surveys were conducted by four observers in 1991, three in 1992, and three in 1993. Only

one observer (Taulman) surveyed birds during all 3 years. With the exception of Taulman, the bird censusers in 1992 were

different from those in 1993.

105
Guild Analysis

Species were grouped into the following foraging and nesting guilds to examine the relative contributions of these

groups to the overall bird community inhabiting late-rotation pine-hardwood stands: (1) open-cup, canopy ( > 3 m); (2) opencup, shrub (< 3 m); (3) ground; (4) cavity; and (5) other (e.g., rock faces). Foragingjtrophic guilds were based on breeding

season diets/foraging tactics and designated as either: (1) foliage-gleaning insectivore, canopy ( > 3 m); (2) foliage-gleaning

insectivore, shrub (< 3 m); (3) ground-foraging insectivore; (4) aerial flycatcher; (5) bark insectivore; (6) carnivore; (7)

granivore; (8) nectarivore; and (9) omnivore. Classifications were based upon Ehrlich and others (1988) and Hamel (1992).

Breeding bird community composition on sites in the Ouachita and Ozark National Forests was compared with that of

12 other studies conducted within mature ( > 40 years) pine-associated forest types in the Southeastern United States. Raptors

and waterbirds were not included in this analysis because populations are not easily quantified using fixed-radius point counts

(e.g., raptors); presence of a species on a given site may be highly dependent upon water (e.g., waterfowl); and many studies

reported only terrestrial landbirds. Similarity in bird community composition was calculated by Sorensen’s Index (SI):

2OOC/(A + B), where A = number of species in forest type A, B = number of species in forest type B, and C = number

of species shared between two forests (Mueller-Dombois and Ellenberg 1974). Sorensen’s Index can range from 0 percent

(no species in common) to 100 percent (identical species composition).

Similarity indices may not accurately reflect the actual overlap in species composition in two areas because species

assemblages quantified at local levels may be strongly influenced by the intensity of sampling (e.g., number of sites, number

of years), Hamel (1992) presented complete bird species lists for different forest types in the Southeastern United States.

Those data were used to provide some indication of the “potential” similarity in bird community composition between mature

mixed-pine hardwood stands (forest type represented by Ouachita and Ozark National Forest research) and six other forest

types in the Southeast: loblolly-shortleafpine (Pinus taeda L.-P.e ch inafa), Virginia-pitch pine (P.virginiana Mill. -P. rigida

L.), longleaf-slash pine (P. pah .w is Mill.-P. ellioffii Engelm.), sandhills longleaf pine, longleaf pine-scrub oak (Quercus

spp.), and oak-hickory (Curya spp.). Similarity indices were calculated as described above.

Data Analysis

The bird survey technique allowed calculation of an index of density for each species rather than a measure of absolute

density. Relative abundance of each species on a site was presented as the average number of individuals detected per survey

point (based upon three visits). Species richness was based upon: (1) only those individuals detected within survey plots on

each of the 20 sites (S,>; and (2) all species detected on the site, i.e., both within and outside survey plots (S,). The

Shannon-Weiner diversity index (H’) was calculated as H’ = - C p, In pl, where p, was the proportion of all individuals

detected that were represented by species i (Pielou 1969). Data from 1992 and 1993 were analyzed separately because of

between-year differences in species richness and abundance (see below). Comparisons of bird community metrics (i.e.,

abundance, diversity, richness) across future treatments and geographic zones were made with two-way analysis of variance

(ANOVA). only the main effects model for each bird community metric was re ported here because no interactions existed

among the factors (Neter and Wasserman 1974, p. 582). Other statistical tests are included in the text. Differences were

considered to be significant if P 50.05.

RESULTS

Adequacy of Bird Sampling Effort

Thoroughness of bird surveys is difficult to assess without extraordinary effort (e.g., by spot-mapping) to determine

all species breeding on sites and their relative densities. However, when estimating species richness, for example, adequate

sampling intensity can be achieved when species-effort curves become asymptotic. Bird surveys in 1991 demonstrated that,

on average, one visit to a site (cumulative sum from all plots on a site during a given day) detected nearly three-fourths of

the species, and that two visits registered more than 90 percent of the species recorded within survey plots after three visits.

Data from 1992 and 1993 revealed species-effort curves similar to those found in 1991, especially for results after two visits

(fig. 1).

106
I

+ I’

I

I

I

I

I

I

I

I

I

I

I

Figure l.- Effect of number of visits on estimates of species tichness

during 1991-93. Squares npresenl the mean percentage of

species detected apCr one and two visits compared with the

wtal number of species wconied a&r thne visits (N = 9

sires in 1991, and 2Osites in 1992 and 1993). Vertical bars

fvptvsent one slanakRid&a&t.

I

t i

I

t

I

I

I

I

I

I

I

I

I

I

I

I

I

5 0

t

rs = 0.6 0

P /8

.I . n \ 8

i

3

\

.

3 0 i l

. .

2 .

I . .

. .

RANK IN 1993

Figure 2.- Relaiionship (Speatman’s correlation coegfcent) between

rank-o&r abundance of 55 species observed in 1992 and/or

1993. Numbers within graph represent multiple points.

Bird Community Characteristics

Specks Richness, Abundance, and Diversity

Few of the 55 species detected within Ouachita and Ozark survey plots in 1992 and 1993 were common (table 2). Pine

warblers (scientific names are listed in table 2) and red-eyed vireos comprised half of all individuals detected within plots;

10 species accounted for 82 percent of the 2,248 individuals counted in 1992 and 1993. The rank-order of abundance of

these 55 species was generally stable between years (Spearman’s rank correlation coefficient; r, = 0.60, df = 53, P

<O.OOl), although abundances of relatively rare species were much less consistent (fig. 2). Hence, when the 29 rarest

(ranked higher than median rank) species were removed from the analysis (including those that were recorded in only one

year), the relationship became stronger (r, = 0.77, df = 24, P <O.OOl).

Relative abundance was compared between years for each of the 11 species that comprised more than 2 percent of the

bird community in 1992-93. When analyzed within regions; only 4 of the 44 comparisons (11 species x 4 regions) showed

significant differences (pine warbler, north; scarlet tanager, south; worm-eating warbler, south and west). Over all 20 sites,

only these 3 species showed significant (paired r-tests; P ~0.05) between-year variation.

107
Table 2.- Relative abundances @ercentage of total) of bird species recorded within 4&m radius circularplots

in 159 2 and 19 9 3. Species are arranged according to their rank abundance (in parentheses) in

1992. In cases of ties, average ranks were assigned to species

Common name

Pine warbler

Rai-eyedvirco

stmuner tanager

Black-ard-white warbler

Ovenbird

Scarlet tanager

Carolina chickadee

Tufted titmouse

Blue jay

Carolina -

Pileated woodpecker

Brown-hutdd cowbird

American crow

Blue-gmy gnatcatcher

Great created flycatcher

Imfigo bunting

Acadian flycatcher

Northern cardinal

Hairy woodpecker

Worm-eating watbler

chuck-will’s widow

Whitabrcaated nuthatch

Yellow-billed cuckoo

M ourning dove

Red-bellied woodpecker

wood thrush

Downy woodpecker

Raatem wood-pewee

Kentucky warbler

Barred owl

Northern flicker

Gray catbird

Prairie warbler

Rufousaided towhee

Yellow-throatedvireo

Broad-wingedhawk

Great-homed owl

Northernbobwhite

American goldfinch

American redstatt

Black-billed cuckoo

Brown-he&d nuthatch

Chipping sparrow

common grackle

Cooper’s hawk

Hoeded warbler

Louisiana waterthrush

Northern panda

Red-shouldered hawk

Ruby-throataihummingbitd

Swainson’s warbler

Cedar waxwing

Red-headed woodpecker

White-eyed vireo

Yellow-throated warbler

Wild turkey

Red-tailed hawk

Belted kingfisher

Yellow-breasted chat

Scientific name

Dendmica pinus

Vireo olivaceus

FSranga mbm

Mniotilta vatia

Seiurw aumcapillus

Pimnga ol+acea

Patus camlinensis

Panu bicolor

Cyanocitta c&rata

lhymthonu ludoticutntu

D tyocopuspileatur

Molothms ater

Corvus bnachyrhynchos

Polioptila caendea

Myiamhus ctinitus

Passetina cyanea

Rmpidonar virescenr

Caniinaliscaniinalis

Picoides villosuc

Helmithcms vemdvoms

Capn%u&u camlinensis

Sitta camlinensis

coccyzus amelicanw

Zenaida macmum

Melaneipu camlintu

tfylocichla mustelina

Picoides pubescens

Contopus tirens

Opomndsfonnosus

Sttix van’s

Colaptes auratus

Dumetclla carolinensis

Dendmica discolor

Pipilo erythmphthalmus

Vireojlavtfmns

Buteo platyprenu

Bubo virginianus

Colinus virginianus

Caniuelisttistis

Selophaga rutin’lla

Coccyucs erythmpthalnw

Sitla prcsilla

Spizellapasserina

Quiscaltuquiscula

Accipiter coopen’i

Wilsonia ciltina

Seiurus motacilla

Parula ameticana

Buteo lineatus

Amhilochus colubris

Limnothlypis swaimonii

Bombycilla cedrotum

Melanerpes erythmcephalur

Vireo griseur

Dendmica dotninica

Meleagtis gallopavo

Buteo jamaicemis

Megaceryle olcyon

Icten’a virens

Percentape of total (mnk)

1992

40.1 (1)

12.9 (2)

5.8 (3)

4.6 (4)

4.5 (5)

4.4 (6)

4.1 (7)

3.4 (8)

2.5 (9)

2.1 (10)

I.8 (11)

I.6 (12)

1.6 (13)

1.5 (14)

1.4 (15)

1.2 (16)

1.1 (17)

0.8 (18)

0.7 (19)

0.5 (20.5)

0.5 (20.5)

0.4 (22.5)

0.4 (22.5)

0.3 (25)

0.3 (25)

0.3 (25)

0.2 (28)

0.2 (28)

0.2 (28)

0.1 (32.5)

0.1 (32.5)

0.1 (32.5)

0.1 (32.5)

0.1 (32.5)

0.1 (32.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

0.0 (45.5)

+’

_t

199 3

35.2 (1)

11.9 (2)

7.2 (3)

6.9 (4)

4.5 (6)

0.8 (16)

4.8 (5)

2.7 (s)

2.4 (9)

1.9 (13)

2.1 (12)

0.1 (42)

1.2 (15)

2.3 (10.5)

1.8 (14)

2.3 (10.5)

0.7 (17.5)

0.1 (42)

0.1 (42)

4.2 (7)

0.0 (52)

0.5 (21)

0.0 (52)

0.0 (52)

0.2 (3 1)

0.6 (19.5)

0.7 (17.5)

0.0 (52)

0.6 (19.5)

0.1 (42)

0.0 (52)

0.1 (42)

0.0 (52)

0.0 (52)

0.4 (22.5)

0.2 (3 I)

0.1 (42)

0.1 (42)

0.2 (3 1)

0.1 (42)

0.1 (42)

0.1 (42)

0.2 (3 1)

0.3 (25)

0.4 (22.5)

0.2 (3 1)

0.2 (3 1)

0.2 (3 1)

0.2 (3 I)

0.2 (31)

0.3 (25)

0.3 (25)

0.1 (42)

0.1 (42)

0.1 (42)

+

+

+

+

s Detected on sites, but only outsideof bird survey plots.

t Not detected on sites in 1992.

108
Thirty-seven percent more species were recorded within plots in 1993 (S, [Total] = 48) than in 1992 (S,, [Total] = 35).

On average, the number of species recorded within survey plots per site in 1993 (mean S,, = 13.40, SD = 3.07, N = 20)

exceeded that of 1992 (mean S_,, = 12.35, SD = 2.41) by one, but this difference was not significant (paired f-test; c = 1.60,

P = 0.12). Likewise, when all species detected on sites were considered (i.e., both within and beyond survey plot

boundaries), more species were documented in 1993 (S, [Total] = 57) than in 1992 (41). On average, approximately 4 more

species were recorded on each site in 1993 (mean S, = 22.70, SD = 2.96, N = 20) than in 1992 (mean S, = 18.10, SD

= 2.99; paired t-test, t = 8.93, P <O.OOl). In contrast to species richness, relative abundance of birds within survey plots

was significantly greater (t = 3.54, P = 0.002) in 1992 (number of individuals pe r survey point; mean = 3.63, SD = 0.56,

N = 20) than in 1993 (mean = 3.04, SD = 0.63). Species diversity (H’) at the site level averaged 1.92 (SD = 0.28) in

1992 and 2.04 (0.35) in 1993 (paired t-test; t = 1.66, df = 18, P = 0.11). (Annual differences in bird species richness,

abundance, and diversity were corroborated with ANOVA -- see Methods).

, Discrepancies in bird community metrics between years could reflect either real differences in bird community

characteristics or interobserver variation. Some insight into these alternatives can be obtained by comparing results of the

only observer to survey birds in both 1992 and 1993 (Taulman). The number of individuals per survey point declined 16

percent between years for both the overall results (see abovej and when analyses were restricted to the single observer,

although the latter difference was not significant @aired f-test; t = 1.67, P = 0.11). Species richness also did not differ

between years at either the plot or site level for the single observer (S,, t = 0.91, P = 0.37; S,, t = 1.23, P = 0.23).

These results suggest that, although bird abundance may have been lower in 1993 compared with 1992, observer variation

was partly responsible for the recorded differences in species richness during that same period.

Nesting and Foraging Guilds

Canopy nesters comprised approximately two-thirds of the individuals recorded in both 1992 and 1993. The high

densities of two canopy-nesters, pine warbler and red-eyed vireo, accounted largely for that domination (fig. 3a). At the

species level, canopy-nesters still were the best represented nesting guild, but cavity-, shrub-, and ground-nesters also

contributed substantially to species richness (fig. 3b). Shrub-nesters represented approximately 18 percent of the species

detected but only 3 percent of the individuals. Representation of nesting guilds within the community did not vary

significantly between years (log-likelihood ratio test; G = 0.72, df = 4, P = 0.95).

60

!? I8 40 30

:

0 $

3 20

a

20

10

s 0

CANOPY CAVITY GROUND SHRUB OTHER 0

CANOPY CAVITY GROUND SHRUB OTHER

NESTING GUILD NESTING GUILD

Figure 3.- Represtnmion of different nesting guilds on late-rotation pine-hardwood site s in 1992 and 1993. Bars represent the percentage of (A)

individuals and (B) species that comprised each of the Jve guilds. Nesting guilds are open-cup, canopy (CANOPY); tree cavity (CAvm);

ground; open-cup, shrub layer (SHRUB); and other.

109
Canopy foliage-gleaning insectivores, of which pine warblers and red-eyed vireos were the most abundant, accounted

for approximately two-thirds of the individuals detected, but only one-fourth of the species (fig. 4a). No other foraging guild

comprised more than 11 percent of the individuals detected in either year. When species were equally weighted (i.e., no

measure of abundance), however, bark-, ground-, and shrub-foraging insectivores, in addition to canopy foragers, were

comparable in their representation (fig. 4b). Carnivores were represented by 3 percent and 10 percent of the species in 1992

and 1993, respectively, although less than 1 percent of the individuals detected each year were raptors. Granivorous and

nectarivorous species were scarce on Ecosystem Management sites. No significant shifts occurred between years in the

relative structure of trophic guilds (G = 3.69, df = 6, P = 0.72).

Differences Among Geographic Zones

No significant differences existed in bird species richness (5, [1992]: F = 0.77; df = 3, 12; P = 0.53; S, [1993]: F

= 0.95, P = 0.45; S, [1992]: F = 0.45, P = 0.72; s, [1993]: F = 2.13, P = 0.15), relative abundance (1992: F = 0.10,

P = 0.96; 1993: F = 3.31, P = 0.06), or species diversity (1992: F = 1.03, P = 0.41; 1993: F = 0.62, P = 0.62) among

the four’geographic zones in either year (fig. 5).

Differences Among Future Treatments

No significant differences were detected in bird species richness (S, [1992]: F = 0.18; df = 3, 12; P = 0.94; Sp [ 19931:

F = 0.16, P = 0.96; S, [1992]: F = 0.83, P = 0.53; 5, [1993]: F = 1.26, P = 0.34), relative abundance (1992: F = 0.21,

P = 0.93; 1993: F = 1.43, P = 0.28), or species diversity (1992: F = 0.17, P = 0.95; 1993: F = 0.49, P = 0.75) among

the five future harvesting treatments in either year (fig. 6).

Similarity to Other Southeastern Forest Types

The overall bird community (terrestrial landbirds only) recorded on Ecosystem Management Research sites was

compared to bird communities from 12 other studies conducted within pine and mixed pine-hardwood forests of the

Southeast. In general, similarity indices (SI) were relatively low (mean = 55 percent, range = 36 to 78 percent) and showed

no clear relationship with forest type, number of sites sampled, or geographic proximity to the Ouachita and Ozark National

Forests (table 3). However, SI was highly correlated with total number of bird species recorded in each of the studies (r

= 0.87, P <O.Ol).

Analysis of “potential” similarity in bird communities using Hamel’s (1992) data showed that the pool of species in

mixed pine-hardwood forests in the Southeastern United States was most similar to those of loblolly-shortleaf (SI = 78

percent) and oak-hickory (SI = 85 percent) forest types. Bird communities in forests dominated by slash, Virginia, pitch,

and/or longleaf pines showed less similarity (mean = 62 percent, range = 57 to 67 percent, N = 4) to communities

occupying mixed pine-hardwood forests, the pine component of which is usually loblolly or shortleaf. Percent similarity

was significantly correlated with the hypothetical number of species occurring in each of the six forest types (t = 0.89, P

<O.Ol). Furthermore, the ratio of SI to SI, (the maximum value possible given the number of species occurring in each

of two forest types) ranged between 0.85 and 0.98 for the six forest types, suggesting that the less speciose bird communities

(all but oak-hickory) were nearly perfect subsets of that found in mixed-pine hardwood forests, and that the mixed pinehardwood bird community was a subset of the oak-hickory bird community.

Nesting and foraging guild composition of the Ecosystem Management sites in the Ouachitas and Ozarks was comparable

to that of other sites and forest types in the Southeastern United States, but only when species were equally weighted (fig.

7). When species were weighted by relative abundance, canopy insectivores and canopy nesters clearly dominated the guild

structure on the Guachita/Ozark sites (see figs. 3 and 4) whereas guild representation did not change appreciably in the other

areas.

110
801 I - I

301

25

80

5 20

i!i 40 i? 15

5 E

0, a 10

20

5

0

CAN BAR GRD BHB AIR OMN CAR GRA NEC

0

FORAGING GUILD FORAGING GUILD

Figure 4.- RepresenMon of d@rent foraging guilds on kUe-rotation pine-haniwood sites in 1992 and 199.3. Bars represent the petVentage of (A)

individuals and (B) species that comptised each of the nine guilds. Fomging gtdids an? foliage-gkaning inSeCtivOn. canopy (CAN); bad

insectivon (BAR); gtvund insectivon (GRD); fOtiage-gkaning insectivon, shrub kayer (MB); aetial insectivon (AIR); omtdvon (OMh%

cau’vore (CAR); granivore (GRA); and nectativon (NRC).

H1992

q ll993

NORTH SOUTH EAST WEST

I 3.0

C I

I

0.5

0.c

NORTH SOUTH EAST WEST

ZONE ZONE

NORTH SOUTH EAST WEST

NORTH SOUTH EAST WEST

Figure 5 .- Comparison of bini community menics acmss diflerent geographic zones in late-rotation pine-hardwood stands in 1992 and 1993. Bars

represent the mean value (vem’cal lines equal I SD) acrossjve sites for (A) species richness within bitd survey plots. (B) species rkhness on

entire s&e, (C) number of individuak detected per 40-m radius plot per survey, and (0) Shannon-Weiner diversity index (H’).

111
v- co cc OR SH S T

5

4

3

2

1

0

co CC OR SH ST

FUTURE TREATMENT

CC GR SH ST

FUTURE TREATMENT

Figure 6.- Comparison of bini communhy metrics on late-rotation pine-handwoods stands that will be subjected to dtrerentsilticultural treatments. Bars

npresent the mean value (+ 1 SD) actoss five sites for (A) species richness within bird survey plots, (R) species tichtuss on et&e site, (C)

number of individuals detected per 40-m radius plot per survey, and (D) Shannon- Weiner diversity index (II’). CO = control, CC = clearcut,

GR = group selection, SH = shelterwood, and ST = single-tree selection.

40

It 30

8

fj 2c

a

1c

r3’

CANOPY CAVITY GROUND SHRUB OTHER

NESTING GUILD

I

I

I

tt

A

*

*

It

*

*

CAN BAR GRD SHB AIR OMN GRA NEC

FORAGING GUILD

Figure I .- Comparison of the distribution of different avian (A) nesting and (B) foraging guilds in mature pine-hardwood stands in the Ouachita and Ozark

National Forests (stars) and pine forests in other locations in the Southeastern United States. Figures are based upon the number of species

comprising each guild. Hotizontal bars represent the mean value calculated from I2 dtyerent studies (table 31, thick bars equal + 1 SD, and

thin vem’cal lines represent the range of values. Nesting guilds are open-cup, canopy (CANOPY); tree cavity (CAVITY)); ground; open-cup,

shrub layer (SHRUB); and other. Foraging guilds are foliage-gleaning insectivore, canopy (CAN); bark insectivore (BAR); ground insectivore

(GRD): foliage-gleaning insectivore, shrub layer (SHB); aerial insectivore (AIR); omnivore (OMN); granivore (GRA); and nectarivore (NRC).

112
Table 3 .- Sorensen’s Index (Sl) of bird community similatity between late-rotation, pine-hardwood stands in

the Ouuchita and Ozark National Forests and other pine-associated forest types and areas in the

Sourhcasrem United States

Forest tvne Location

Number

site of s SI Author

Longleaf-slash pine

Longleaf pine

Slash pine

Loblolly pine

Loblolly pine

Loblolly-shortleaf pine

Mixed pine-hardwood

Pitch pine

Pitch pine-oak

Mixed pine-hardwood

Loblolly-shortleaf pine

Mixed pine-hardwood

Multiple States

Florida

Florida

Virginia

Louisiana

Texas

Texas

New Jersey

Virginia

Louisians

Multiple States

Multiple States

3 36

3 39

3 39

3 48

I 53

I 53

I 53

6 53

. I 65

I 73

ca 5 75

4 78

Dickson and others 1980

Repenning and Labisky 1985

Repenning and Labisky 1985

Childers and others 1986

Noble and Hamilton 1975

Dickson and Segelquist 1979

Dickson and Segelquist 1979

Kerlinger 1983

Conner and others 1979

Noble and Hamilton 1975

Dickson and others 1980

Dickson and others 1980

DISCUSSION

Fixed-radius point counts appeared to be an appropriate means for estimating relative bird abunda;lce in mature pinehardwood forests. Three visits to each site were probably sufficient to detect nearly all species that would be recorded within

survey plots with a moderate increase in effort (perhaps, five visits), because in all 3 years detection of new species slowed

dramatically after the second visit (fig. 1). Similarly, Twedt and others (1993) conducted unlimited-distance point counts

in Mississippi Alluvial Plain forests and found that the number ofspecies recorded after four visits did not differ signiticantly

from the number detected after five visits. In the Ouachita and Ozarks, however, 30 to 40 percent of the total number of

species recorded on a site were not detected within survey plots. Thus, by restricting survey plots to 0.5 ha, relative

abundances of many species that occurred on each site were underestimated. Those species that were not detected within

plots were extremely rare (each species comprised < 1 percent of the total individuals), often being detected on only one

occasion. This rarity is evident in that, over three visits, rate of accumulation of species on the entire site (A’,) closely

paralleled that found for species detected only within survey plots. Because these unlimited-distance counts covered a much

larger area than the 40-m fixed-radius survey plots, a more rapid rate of species accumulation should have been exhibited

if most species were at least moderately common (and detectable). Unlimiteddistance counts, as used in this study, will

improve estimates of species richness compared to fixed-radius plots, although estimates of relative abundance may be more

tenuous. Therefore, to maximize the information gained from general bird surveys in forests, wildlife biologists should

incorporate both fixed-radius and unlimited-radius methods into survey protocols (Petit and others, in press).

The ramifications of underestimation of rare species are probably not significant in the scope of this research.Difficulty

in quantifying abundance of rare species is common to all bird survey techniques (Ralph and Scott 1981). Furthermore,

underestimation of abundance of rare species within fixed-radius plots should not hinder assessment of Ecosystem

Management harvesting treatments, particularly if those rare species become more abundant after treatments are applied

because of changes in successional stage or vegetative structure. In addition, although all species were not detected by the

fixed-radius bird sampling technique, limited resources necessitated examination of relative differences among treatments.

Thus, harvesting treatments that result in increases in abundance of species should be (statistically) detectable even though

some of those species were underestimated during pretreatment surveys. In addition, several of those rare species (e.g.,

owls, hawks, and some woodpeckers) characteristically occupy large (> 10 ha) breeding territories, such that any survey

technique focussed on stand-level populations would detect relatively few individuals. For those species, the effects of

harvesting and management practices on breeding ecology might be most effectively assessed during the watershed-level

manipulations of Phase III Ecosystem Management Research.

113
Not surprisingly, pine warblers were the most abundant bird species occupying mature mixed pine-hardwood stands of

western Arkansas and eastern Oklahoma. Pine warblers reach their greatest densities in pine and mixed-pine forests of the

Southeastern United States including the Ozark-Ouachita physiographic stratum (Hamel 1992, Robbins and others 1986).

Although high relative abundances of breeding pine warblers have been reported by others (e.g., 30 percent of all individuals

[Land and others 19891, 18 percent [Noble and Hamilton 19751, 14 percent [Conner and others 19791, 13 percent [Dickson

and Segelquist 19791, and 10 percent [Kerlinger 1983]), our results suggest that pine warblers may comprise one-third or

more of the total individuals in mature pine-hardwood forests in the Ozark and Ouachib plateaus. Caution must be used

in interpreting our measure of abundance, however, because our survey technique does not fully account for variation in

detectabilities among species. Nevertheless, such domination by a single species indicates that estimates of overall densities

of birds in these pine-hardwood forests may be primarily influenced by the abundance of pine warblers. Summaries of bird

population data from pine-hardwood stands may need to be more detailed than simple measures of overall density and

richness, because numerical domination by one or a few species could cause those quantitative measures to be misleading.

Rather, inferences about the bird community as a whole need to consider such characteristics as sex ratios, reproductive

output, and the distribution of individuals and species among ecological guilds.

Red-eyed vireo was the only other species to comprise more than 10 percent of the individuals. Based on breeding

densities, pine-hardwood forests apparently are not optimal habitats for red-eyed vireos (e.g., Hamel 1992), but they will

occupy a wide range of pine-associated habitats depending on the extent of deciduous canopy and tmderstory trees (Hamel

1992). Local population densities of pine warblers and red-eyed vireos apparently are correlated to similar habitat features,

but in opposite ways. Pine warblers respond positively to increased pine composition, whereas red-eyed vireos would decline

under those conditions (Hamel 1992, Johnston and Odum 1956). Hence, the mixed-tree species composition found on the

Ouachita and Ozark stands allowed both species to persist in relatively high numbers.

Individuals that build open-cup nests in the canopy contributed most to guild membership largely because of the

abundance of pine warblers and red-eyed vireos. At the species level, nesting guilds were much more evenly distributed.

A similar pattern was revealed for foraging/trophic guilds; that is, canopy insectivores, such as red-eyed vireos and pine

warblers, comprised the majority of individuals detected. Discounting relative abundance, species that forage from bark,

canopy foliage, shrub foliage, and the ground were well represented. These results suggest that management or harvesting

methods that alter basal area, leaf litter characteristics, or foliage density at canopy/subcanopy or shrub levels may have

negative repercussions on many forest species that require those resources for nesting and foraging (see L. J. Petit and

others, this volume).

Comparison of bird community composition of mixed pine-hardwoods in the Ouachita Mountains with other pineassociated forests throughout the Southeastern United States suggests that application of results from Ecosystem Management

Research in Arkansas and Oklahoma may not be highly useful in predicting community-level responses in other National

Forests in the region. This was not surprising given differences in species ranges and abundances across the Southeast. Yet,

even representation of foraging and nesting guilds varied substantially among sites and forest types (although Ouachita/Ozark

sites were closely aligned with general trends throughout the region). In addition, Ecosystem Management Research

described in this paper incorporated only a portion of the microclimatic and vegetative variability found in pine-hardwood

stands in this region because only south-facing aspects were considered.These restrictions, although necessary in this highly

controlled experiment, may further hinder generalizations to other areas within the Southeastern United States.

Based upon Hamel’s (1992) compilation of potential bird communities, USDA Ecosystem Management Research in

Arkansas and Oklahoma should be most applicable to loblolly-shortleafand oak-hickory forest types in the Southeast region.

Nevertheless, predicting bird community- or guild-level responses to harvesting treatments still may be difficult in many

locations, or for some foraging and nesting guilds. That uncertainty could create a dilemma for forest managers. For

example, forest managers often attempt to maintain or enhance local diversity of species on lands under their jurisdiction

(Thomas and Salwasser 1989). If the current Ouachita Ecosystem Management Research suggests that a certain timber

harvesting treatment should be applied to increase diversity, should that recommendation be followed even though bird

species composition in the two areas are not highly similar? Thus, caution must be used when applying Ecosystem

Management Research results to predict changes in species diversity or richness at other sites.

However, community-wide predictions in other areas still may be possible because nearly all species found in

Southeastern pine forests also were recorded in the Ouachita Mountains. Similarities between the bird communities in mixed

pine-hardwood forest and the other six major forest types (Hamel 1992) were positively correlated with species richness in

the latter group. This indicates that the bird communities in the five types of pine forest were subsets of the bird community

characteristic of mixed pine-hardwoods, which itself was a subset of that in oak-hickory forest. Thus, although results of

this study will be most valuable for predicting bird responses to harvesting treatments on a species-by-species basis, forest

managers in other National Forests also may be able to develop community-wide predictions from this Ecosystem

Management Research.

114
ACKNOW LEDGEMENTS

D. Petit’s participation in this research was partially supported by a grant from the U.S. EPA’s Environmental Monitoring

and Assessment Program to T. Martin. J. Adams, H. Powell, and J. Williamson assisted with bird surveys. H. Free&en,

G. Hartman, and V. Weindel of the Ozark National Forest graciously provided technical assistance in location of sites during

1991. K. Petit offered helpful comments on a preliminary draft.

LITERATURE CITED

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in the Virginia Piedmont. Journal of Wildlife Management. 50(3): 406-413.

Conner, Richard N.; Via, Jerry W.; Prather, Irvine D. 1979. Effects of pine-oak clearcutting on winter and breeding birds

in southwestern Virginia. Wilson Bulletin. 91(2): 310-316.

Dickson, James G.; Segelquist, Charles A. 1979. Breeding bird populations in pine and pine-hardwood forests in Texas.

Journal of Wildlife Management. 43(2): 549-555.

Dickson, James G.; Conner, Richard N.; Williamson, J. Howard. 1980. Relative abundances of breeding birds in forest

stands in the Southeast. Southern Journal of Applied Forestry. 4(2): 174-179.

Ehrlich, Paul R.; Dobkin, David S.; Wheye, Darryl. 1988. The birder’s handbook: a field guide to the natural history of

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M., tech. coord. Management of southern forests for nongame birds: proceedings of the workshop. Gen. Tech. Rep. SE14. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station: 76-89.

Frissell, Christopher A.; Nawa, Richard K.; Noss, Reed. 1992. Is there any conservation biology in “New Perspectives?“:

a response to Salwasser. Conservation Biology. 6(3): 461-464.

Hamel, Paul B. 1992. The land manager’s guide to the birds of the South. Chapel Hill, NC: The Nature Conservancy,

Southeastern Region; 437 p.

Harris, Larry D.; White, L. D.; Johnston, J. E.; Milchunas, D. G. 1974, Impact of forest plantations on north Florida

wildlife and habitat. Proceedings of the Southeastern Association of Game and Fish Commissioners. 28: 659-667.

Jackson, Jerome A. 1988. The southeastern pine forest ecosystem and its birds: past, present, and future. In: Jackson,

Jerome A., ed. Bird Conservation 3. Madison, WI: University of Wisconsin Press: 119-159.

Johnson, A. Sydney. 1987. Pine plantations as wildlife habitat: a perspective. In: Dickson, James G; Maughan, 0. E., eds.

Managing southern forests for wildlife and fish. Gen. Tech. Rep. SO-65. New Orleans, LA: U.S. Department of

Agriculture, Forest Service, Southern Forest Experiment Station: 12-18.

Johnston, David W.; Odum, Eugene P. 1956. Breeding bird populations in relation to plant succession on the Piedmont of

Georgia. Ecology. 37(l): 50-62.

Kerlinger, Paul. 1983. Avian community structure along a .successional gradient in the New Jersey pine barrens. Records

of New Jersey Birds. 9(4): 71-78.

Knight, H. A. 1987. The pine decline. Journal of Forestry. 85(l): 25-28.

Land, Darrell; Marion, Wayne R.; O’Meara, Timothy E. 1989. Snag availability and cavity nesting birds in slash pine

plantations. Journal of Wildlife Management. 53(4): 1,165-l) 17 1.

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Meyers, Joseph M.; Johnson, A. Sydney. 1978. Bird communities associated with succession and management of loblollyshortleaf pine forests. In: DeGraaf, Richard M., tech. coord. Management of southern forests for nongame birds:

proceedings of the workshop. Gen. Tech. Rep. SE-14. Asheville, NC: U.S. Department of Agriculture, Forest Service,

Southeastern Forest Experiment Station: 50-65.

Mueller-Dombois, D.; Ellenberg, E. 1974. Aims and methods of vegetation ecology. New York: John Wiley and Sons.

Neter, John; Wasserman, William. 1974. Applied linear statistical models. Homewood, IL: Richard D. Irwin, Inc (p. 582).

842 p.

Noble, Robert E.; Hamilton, Robert B. 1975. Bird populations in even-aged loblolly pine forests of southeastern Louisiana.

Proceedings of the Southeastern Association of Game and Fish Commissioners. 29: 441-450.

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influencing effectiveness and efficiency. In: Ralph, C. John; Sauer, John R.; Droege, Sam, eds. Proceedings of the

symposium on monitoring bird population trends by point counts; November 6-7, 1991, Beltsville, Maryland. Gen. Tech.

Rep. PSW-GTR-OOO. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station.

Pielou, E. C. 1969. An introduction to mathematical ecology. New York: Wiley-Interscience.

Ralph; C. John; Scott, J. Michael, eds. 1981. Estimating numbers of terrestrial birds. Studies in Avian Biology. 6: l-630.

Lawrence, KS: Cooper ornithological Society.

Repenning, Robert W.; Labisky, Ronald F. 1985. Effects of even-age timber management on bird communities of the

longleaf pine forest in northern Florida. Journal of Wildlife Management. 49(4): 1,088-1,098.

Robbins, Chandler S.; Bystrak, Danny; Geissler, Paul H. 1986. The breeding bird survey: its first fifteen ye ars , 1965-1979.

Resour. Publ. 157. Washington, D.C.: U.S. Department of Interior, Fish and Wildlife Service. 196 p.

Salwasser, Hal. 1991. New Perspectives for sustaining diversity in U.S. national forest ecosystems. Conservation Biology.

5(4): 567-569.

Salwasser, Hal. 1992. From New Perspectives to ecosystem management: response to F&sell et al. and Lawrence and

Murphy. Conservation Biology. 6(3): 469-472.

Smith, Kimberly G.; Petit, Daniel R. 1988. Breeding birds and forestry practices in the Ozarks: past, present, and future

relationships. In: Jackson, Jerome A., ed. Bird Conservation 3. Madison, WI: University of Wisconsin Press: 23-49.

Thomas, Jack Ward; Salwasser, Hal. 1989. Bringing conservation biology into a position of influence in natural resource

management. Conservation Biology. 3(l): 123-127.

Twedt, Daniel J.; Smith, Winston P.; Cooper, Robert J.; Ford, Robert P.; Hamel, Paul B.; Wiedenfeld, David A. 1993.

Sampling bird communities in bottomland hardwood forests of the Mississippi Alluvial Valley: number of points visited

versus number of visits to a point. In: Smith, Winston P., ed. Proceedings of the 4th meeting of the Southeast Management

Working Group, Partners in Flight: abstracts; November 12-14, 1992; Memphis, TN. Gen. Tech. Rep. SO-95. New

Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station: 16.

116
Predicting the Effects of Ecosystem Management Harvesting

Treatments on Breeding Birds in Pine-Hardwood Forests’

Lisa J. Petit, Daniel R. Petit, Thomas E. Martin, Ronald E. Thill, and James F. Taulman’

ABSTRACT

Habitat relationships of birds are well known compared to those of other taxa. However,

a nutjor obstacle to developing rigorous management plans for birds is the collation and

transfer of information from widely scattered technical and academic publications to a

form that can be applied directly to the management of species. Recognizing this

dilemma, Hamel (1992) produced a comprehensive summary of bird-habitat relationships

for 23 forest types in the Southeastern United States. The explicit purpose of Hamel’s

summary was to aid land managers in projecting the impacts of silvicultural practices and

management activities on bird populations. Ecosystem Management Research offered a

unique opportunity to develop and test predictions derived from Hamel’s bird-habitat

matrices. Given its probable widespread use by wildlife biologists and land managers,

Hamel’s compilation needs its strengths and weaknesses identified for the future

development of accurate predictive models of wildlife habitat in the Southeastern United

States. Predictions of immediate changes in abundances of species and guilds occupying

late-rotation pine-hardwood stands were developed in this paper for four harvesting

treatments. Clearcutting and shelterwood harvesting were predicted to be more

detrimental to the overall breeding bird community in late-rotation stands than were group

or single-tree selection, although at least several species were predicted to increase in

each silvicultural treatment. Bark, aerial, and canopy insectivores were predicted to

exhibit more substantial declines in populations than carnivores, shrub insectivores, and

ground foragers. In addition, species that place their nests in shrubs were predicted to

undergo fewer declines than species that place nests in the canopy, tree cavities, and on

the ground.

INTRODUCTION

The negative environmental consequences associated with human population growth and economic expansion have

focused much attention on the long-term sustainability of natural resources as well as prompting detailed examination of the

ways in which those resources are managed. For wildlife biologists involved in those issues, the goal is often to develop

predictive algorithms that relate land-use practices or management techniques to the density and viability of wildlife

populations on local (e.g., Vemer and others 1986) and regional (e.g., Joyce and others 1990) scales. Those efforts,

however, are often hindered because of lack of detailed information on the habitat associations, nesting and food

requirements, and life-history traits of most species (DeGraaf 1991, Martin 1992).

Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

Research Associate, Cooperative Fish and Wildlife Research Unit, University of Arkansas at Fayetteville; Currently

Research Wildlife Biologist, Smithsonian Migratory Bird Center, National Zoological Park, Washington, DC 2ooO8;

Research Associate, Cooperative Fish and Wildlife Research Unit, University of Arkansas at Fayetteville; Currently

Research Fellow, Smithsonian Environmental Research Center, Edgewater, MD 21037; Assistant Leader, Cooperative Fish

and Wildlife Research Unit, University of Arkansas at Fayetteville; Currently Assistant Leader, National Biological Survey,

Cooperative Wildlife Research Unit, University of Montana at Missoula, 59812; Wildlife Biologist, USDA Forest Service,

Southern Forest Experiment Station, Nacogdoches, TX 75962; Wildlife Biologist, USDA Forest Service, Southern Forest

Experiment Station, Hot Springs, AR. Currently, Ph.D. Candidate, University of Arkansas at Fayetteville, 72701.

117
Ecology and habitat relationships of North American birds are well known relative to those of other taxa, such as

mammals, amphibians, and reptiles (Capen 1981, DeGraaf 1978, Evans 1978, Evans and Kirkman 1981, Ruggiero and others

1991). Nevertheless, one major obstacle to developing rigorous management plans for birds is the collation and transfer of

information from technical academic publications to a form that can be applied directly to the management of those species.

Recognizing this dilemma, several authors have synthesized large volumes of literature on regional habitat relationships of

birds in attempts to provide comprehensive, yet condensed, summaries to land managers (e.g., Hamel and others 1982,

Vemer and Boss 1980). These summaries have the explicit purpose of guiding land managers in evaluating the projected

impact of different management practices on terrestrial land birds. However, not only are these bird-habitat matrices

incomplete due to a scant primary literature and lack of geographic specificity, but the nonquantitative format might allow

land managers to construct only generalized predictions. For example, extreme types of habitat manipulations (e.g.,

clearcutting) may have predictable outcomes on bird populations, but consequences of more subtle management prescriptions

(e.g., thinning of hardwoods) may be impossible to estimate from bird-habitat matrices or even from existing primary

literature. ‘The potential widespread use of bird-habitat matrices by wildlife and land managers requires that the accuracy

and precision of projections from those summaries be tested before actually being put into field use.

In 1992, Paul Hamel produced the most comprehensive regional summary of bird-habitat relationships ever published

in the United States, a revision of a document completed 10 years earlier (Hamel and others 1982). Hamel’s (1992)

summary of information for 23 forest types in the Southeastern United States provided state-of-the-art guidelines for land

managers in that 13-state region. The guide had two primary uses, one of which was “to aid the manager both in prescribing

treatments aimed at improving avian habitats and in assessing and ameliorating the impacts of other management activities

on bird communities” (Hamel 1992, p. 3). Hamel also stressed that guidelines provided in the manual could be improved

through further testing and supplementation of information.

The USDA Forest Service’s Ecosystem Management Research in the Guachita and Ozark National Forests offers a

unique opportunity to assess the predictability of Hamel’s bird-habitat matrices, as well as to improve upon the information

contained therein. In this paper, Hamel’s bird-habitat matrices were used to project changes in relative population densities

of species and in representation of foraging and nesting guilds that will occur within the first few (1 to 3) years following

different Ecosystem Management harvesting regimes. (Examination of predicted trends with observed outcomes will be

completed after several years of posttreatment data are gathered.) Given the immediate widespread use of Hamel’s landmark

guide by USDA Forest Service personnel, as well as other government and private land managers, identification of strengths

and weaknesses of this compilation is both timely and critical for development of accurate predictive models of wildlife

habitat in the Southeastern United States.

METHODS

Study Sites

Birds were surveyed on 20 of the Ecosystem Management Research stands in the Ozark and Ouachita National Forests

of Arkansas and Oklahoma (Thill and others, this volume). Each 14 to 16 ha site corresponded to an individual USDA

Forest Service compartment and stand and was separated from other sites by more than 5 km. Stands were comprised of

mixed pine-hardwoods that were more than 70 years old. Dominant midstory and overstory tree species included Curya spp.

Pinus echinata Mill., Quercus alba L., Q. marilandica Muenchh., Q. rubra L., Q. stellata Wangenh., and Q. velutina Lam.

Canopies were largely closed and had attained heights of 15-25 m. All sites were positioned on southeast-, south-, or

southwest-facing slopes. Additional details of site and vegetative characteristics can be found in Baker (this volume) and

Thill and others (this volume).

Pretreatment Data: Breeding Bird Communities of Late-Rotation Pine-Hardwood Stands

Bird abundance was quantified in five or six (depending on size and shape of the site) 40-m radius (0.5 ha) circular plots

spaced at greater than 130 m intervals over each site. Between 28 April and 2 June in 1992 and 1993, three visits were made

to each site during which time all birds seen or heard within bird survey plots were recorded. Bird counts lasted 10 minutes

and were conducted between 06:OO and 12:O0. Birds seen outside of survey plots were noted but were not included in this

paper (see D.R. Petit and others [this volume] for additional details).

Fifty-five species were recorded on the 20 sites in 1992 and 1993. Most species were rare, with 82 percent of all

individuals being represented by just 10 species (D.R. Petit and others, this volume). All species were assigned to a nesting

and foraging/trophic guild based upon Hamel (1992) and Ehrlich and others (1988).

118
Ecosystem Management Harvesting Treatments

Four harvesting treatments are to be applied to each of four sites (four additional stands will act as control sites where

no harvesting will be performed). On all sites (except controls), understory hardwoods will be controlled (herbicide or

mechanical methods) when necessary to ensure regeneration of an appropriate pine and hardwood mixture. Treatment

descriptions below are taken from the Ecosystem Management study plan (summarized in Baker [this volume]) and represent

general harvesting goals.

(1) Clearcut -- All pine and hardwoods will be harvested or removed, except for hardwoods in greenbelt buffer strips

along drainages. Altogether, approximately 10 percent of hardwoods will be retained for den-trees and mast production.

(2) Pine/hardwood shelrerwood -- Twenty to forty overstory pines and hardwoods (4 to 5 m2 basal area [BA]) per

hectare (ha) are to be retained throughout the stand (i.e., approximately 70 to 80 percent of merchantable trees harvested).

(3) Pine/hardwood group selection -- All merchantable pines and hardwoods will be harvested within 0.04 to 0.40 ha

group openings. Cutting will be on a lo-year rotation. No hardwoods outside openings will be harvested, but pines in those

areas will be thinned to approximately 7 m2 BA/ha (i.e., approximately 10 to 20 percent of the merchantable pines removed).

(4) Pine/hardwood single-tree selection -- Approximately 40 to 50 percent of overstory pines (5 to 7 n# BAlha retained)

and hardwoods (2 to 4 m* BA/ha retained) will be harvested in the initial thinning. Subsequent, less intensive thinning on

a lo-year cycle will be used to create an uneven-aged forest structure.

Hamel’s Bird-Habitat Matrices and Development of Predictions

Hamel (1992) included in his summarization information on forest types, seral stages, and vertical vegetative layers used

by species during the breeding season. In addition, specific requirements for nesting and foraging and minimum tract sixes

for each species were provided, when known. Bird-habitat matrices primarily consisted of qualitative assessments of whether

a given resource category (e.g., send stage or vegetative layer) was used by each species. With the exception of seral stages

and minimum tract sixes, neither the extent of use of those resources (e.g., weighted use of vegetative layers) nor estimates

of optimal conditions (e.g., percent canopy cover) were given. Predictions developed in this paper were based upon data

from the mixed pine-hardwood forest type. See Hamel (1992) for additional information.

Use of qualitative measures to predict general changes from pretreatment bird population densities is difficult because

of the subjectiveness involved in estimating the magnitude of treatment effects on those populations. The projected relative

changes in seral stage, tree density, vegetative structure, and other environmental features (e.g., leaf litter, fragmentation)

associated with each of the four harvesting treatments (table 1) were estimated through examination of Ecosystem

Management harvesting goals (Baker, this volume) and Phase I summaries of pretreatment and posttreatment stand conditions

(Baker 1992).3 Those changes were compared to key habitat and condition requirements indicated for each bird species by

Hamel (1992), and predictions were generated on whether harvesting treatments would result in changes in relative population

densities. Magnitudes of predicted changes in bird populations were estimated by assigning a score to each environmental

feature within each treatment that would reflect the degree of change in the stand environment from the pretreatment (control)

conditions (table 1). Subtle differences in initial harvesting volumes between group selection and single-tree selection made

differentiation between effects of the two treatments on bird populations particularly difficult.Hence, projections were based

on differences in spatial configurations of habitat alterations in addition to residual pine and hardwood basal area. .

3 Baker, James B. 1992. New Perspectives research on the Ouachita/Ozark National Forests: Phase I -- an unreplicated pilot

test. 10 p. Monticello, AR: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station, Forestry

Sciences Laboratory, Establishment/Progress Report FS-SO-4106-81.

119
Table l.- Changes in envimnmental features associated with dt@erent harvesting treatments. Environmental

vatiabks were tifrom Hamei (1992). Projected estimates represent the relative changes in

extent and/or co&Won compared to pntreatment (control) characteristics. Posttreatment conditions

n$ect stand chamcteristics expected during the initial 1 to 3 year postharvesting period

Harvestine treatment

FmviFonmental variable Clearcut Shelterwood Group selection Single tree

Seral dage

Grasslfolb

Shnrblreedlillg

Saplinglpoletimber

Sawtimber

I3’ I3 11 11

I3 I3 I1 I1

D3 D2 Dl Dl

D3 D2 Dl Dl

Ve ge tative layer

Bare Ed

Lerf liir

Iierbr

Shrubs

Midstory

overaw

11 11 11 I1

D2 D2 Dl Dl

I2 I2 I1 I1

I2 I2 I1 I1

D3 D2 Dl Dl

D3 D2 Dl Dl

Key requirements

Closed canopy D3 D3 D2 D2

t&en canopy 11 I3 I2 I3

Grassy openings I2 I2 13 I2

Bii trees D3 D2 Dl Dl

Snags/cavity trees D3 D2 Dl Dl

Forest continuity D2 D2 D2 Dl

* Letters represent decrease (D) or increase (I) in resource. Numbem represent extent of change: 1 = slight,

2 = moderate, 3 = major.

The algorithm used to project bird population changes was simply the sum of the key individual environmental

components identified for each species (e.g., 13 = +3, D2 = -2). Based upon the distribution of these scores, arbitrary

cutpoints were designated which corresponded to each level of predicted change (e.g., moderate increase). These methods

represent a relatively parsimonious approach that can be updated as knowledge of species and environmental changes

associated with harvesting treatments increased. Predictions were developed only for those species recorded within fixedradius plots. Species detected on the sites, but outside of bird survey plots were excluded because those species were

extremely rare, such that statistical tests aimed at testing the predictions may not be powerful. Bird species not recorded

in late-rotation stands during pretreatment surveys, but known to occur in other seral stages or habitats in the region, also

were not included because of the lack of information about local population levels of those species. For instance, one could

predict that a certain early-successional species, which was not detected during pretreatment surveys, should be present on

clearcut stands. However, if that prediction was not supported by data collected during posttreatment bird surveys, it would

be difficult to conclude that clearcutting had no effect on populations of that species because factors other than habitat

manipulation (e.g., geographic distribution, local abundance) could account for the lack of response.

RESULTS

Based upon information provided by Hamel (1992), harvesting treatments were predicted to have different effects on

the bird species breeding in late-rotation, mixed pine-hardwood forests. Clearcut (CC) and sheltenvood (SH) probably will

have the most dramatic effects on the pretreatment bird communities (table 2; see the companion paper in this volume [D.R.

Petit and others] for scientific names). A total of 52 (88 percent) and 50 (85 percent) of the 59 species detected within tixedradius plots in 1992 and 1993 were expected to exhibit appreciable decreases in population density within 1 to 3 years after

clearcutting and shelterwood cuts, respectively. In contrast, only 38 (64 percent) and 36 (61 percent) of the bird species

were predicted to decline after the group (GR) and single-tree (ST) treatments, respectively. Moreover, the declines under

the latter two harvesting treatments were projected to be much less severe than the former treatments. Overall, population

declines associated with harvesting treatments were predicted to be highest in CC, followed by SH, GR, and ST.

120
Table 2.- pndictrd population twponws by bird species breeding in late-rotation pine-hanfwood stands to harvesting treatments iq the Ouachita and Ozark National Forests

I BLACK-AND-W H ITE W ARBLER

BROAD- /I W INGED H AW K f 1;;

RED-TAILED H AW K

c c - - - - o/- ol_

G S -- -- - O/- .

AMERICAN CROW c 0 -- - I SW AINSON’S W ARBLER

CAROLINA CH ICKADEE H C -- _ _

WILD TURKEY G G

NORTH ERN BOBW H ITE G G

s G - - - o/- O/-

G G - - - o/- o/- I OVENBIRD

GG - - Ol- OlG G - Ol- Ol- o/tMOURNING DOVE C GF

BLACK-BILLED CUCKOO C c

I H OODED W ARBLER

CAROLINA W REN H G - o/- 1 YELLOW -BREASTED CH AT

BLUE-GRAY GNATCATCH ER C C . . .- _ _ I SUMMER TANAGER

W OOD TH RUSH S G --- _ _

- o/-

GRAY CATBIRD S s - Ol- 0lt o/t

CEDAR W AXW I h iGIl- BELTED KINGFISH ER 0 P NG c c - 01. o/t o/t

RED-H EADED W OODPECKER H B W H ITE-NED VIREO s s Ol- o/t t t

RED-BELLIED W OODPECKER 11 YELLOW -TH ROATED VIREO c c I- _ _ O/_ lJ_ H 1 B

RED-EYED VIREO c c I-- - -

- OlNORTH ERN PARUIA c c -m e _ I - Ol- I AMERICAN GOLDFINCH

YELLOW -TH ROATED W ARBLER C C -- ___ _ ^

I

IND~~IGO BUNTING

PINE W ARBLER C C -- __ - o/-

Note: Nesting (N) guilds: C = canopy, S = shrub, G = ground, H = hole (cavity) in tree, 0 = other.

Foraging (Q guilds: CA = carnivore, C = canopy insectivore, S = shrub insectivore, B = bark insectivore, A = aerial insectivore, G = ground, P = piscivon, N = nectarivore, 0 = omnivore.

Harvesting treatments: CC = clearcut, SH = shelterwood, GR = group selection, ST = single-tree selection.

Predicted population responses: ‘+ + ’= major increase, ‘+’ = moderate increase, ‘O/+’ = slight increase, ‘- -’ = major decrease, ‘-’ = moderate decrease, ‘O/-’ = slight decrease.
Harvesting treatments were not predicted to affect all nesting and foraging guilds equally. Bark, aerial, and canopy

insectivores probably will exhibit more declines than carnivores, shrub insectivores, and ground foragers (fig. 1). At least

90 percent of the bark, air, and canopy foragers were predicted to decline under CC and SH treatments compared with 10

to 60 percent of those species after single-tree and group selection cuts. Fewer than 10 percent of the species which are

shrub insectivores, ground foragers, and carnivores were expected to show marked declines after ST and GR cuts. In

contrast, clearcutting was predicted to result in declines for approximately 80 percent of carnivores and ground foragers.

Shelterwood cuts were predicted to be intermediate in their impact on carnivores and ground foragers. Gnly 25 percent and

40 percent of shrub insectivores were predicted to exhibit declines after SH and CC, respectively.

Ecosystem Management harvesting treatments probably will have relatively small initial negative effects on birds that

place their nests in shrubs compared to those species that build nests in tree canopies, on the ground, or in cavities (fig. 2).

The GR and ST harvests may reduce populations of 10 to 40 percent of the species in each of the latter three nesting guilds,

whereas CC and SH methods may result in declines in 75 to 100 percent of the species comprising those guilds.

OTHER

GROUND

g looz

i

CARNIV

$ 80-

n

g 6 0 -

55

k !

BARK

v) 40-

2 AIR

y 20- CANOPY

SHRUB

0

ST GR SH CC

HARVESTING TREATMENT

Elgure l.- meets of Ecosystem Management harvesting trearments on avlan foraging guilds. Symbols

represent the pementage of species in each guild predicted to urhibit substantial declines in

population density. Harvesting treatments: ST = single-tree selectlon; GR = group selection; SH

= shelterwood: CC = clearcur. See text for desctiptions of treatments. Foraging guilds: Canopy

= canopy (>3 m) insectivore; Shrub = shrub (< 3 m) insectivore; Ground = ground insectivore;

BatA = bank insectivore; Air = aerial insectivore; Camiv = carnivore; Other = nectativore,

gmnivore. piscivore, omnivore.

122
8 0

6 0

4 0

2 0

0

ST GR SH cc

HARVESTING TREATMENT

GROUND

SHRUB

Figure 2.- Eflects of Ecosystem Management harvesting treatments on avian nesting guilds. Symbols

represent the penxntage of species in each guild predicted to exhibit substantial declines in

population density. Harvesting treatments: ST = pine/hardwood singk-nve selection; GR =

pineluvdwood group sekcrion; SH = pine/hardwood sheberwood; CC = clearcut. See tit for

desctiptions of treatments. Nesting guilds: Canopy = open-cup, canopy; Shnrb = open-cup,

shrubs; G&y = tree catity; Ground.

DISCUSSION AND CONCLUSIONS

Projected posttreatment habitat characteristics in this study (table 1) were based upon conditions expected within 3yeurr

of harvest because of uncertainty about long-term continuation of bird surveys on these sites. Clearly, however, turnover

in species composition through time occurs after habitat alteration, so that bird community characteristics in any given period

are likely to be different from those during other periods (Johnston and Odum 1956). Thus, predictions of changes in

relative bird densities made in this paper are applicable only during a relatively brief postharvest period. Monitoring bird

populations on these sites over several decades or longer would provide critical information on the long-term impacts of

Ecosystem Management harvesting treatments. In fact, following timber harvesting, ecosystem structure and function may

take a century or more to return to a state similar to preharvest conditions (e.g., DutTy and Meier 1992). Nevertheless,

knowledge of the immediate effects of forest management on wildlife populations is imperative for development of effective

wildlife management plans.

If population projections presented in this paper are accurate, wildlife biologists can expect that foraging and nesting

guilds will be differentially affected by the Ecosystem Management timber harvesting treatments. Predicted decreases in

these guilds are closely related to key ecological requirements that are altered by the various harvesting regimes.Knowledge

of those requirements may allow forest managers to modify harvesting schemes to optimize the tradeoff between retention

of ecological features critical for maintenance of forest bird assemblages and production of timber.

123
Projected changes in bird population and guild densities generally were consistent with changes documented in previous

empirical studies of avian responses to different types of habitat alteration (e.g., Crawford and others 1981, Conner and

others 1979, Medin 1985, Webb and others 1977), as well as with general impressions of the direction and magnitude of

changes baaed upon our knowledge of bird-habitat relationships. This may not seem surprising given the fact that Hamel’s

(1992) bird-habitat matrix was built upon those previous studies, as well as expert opinion. However, although a logical

basis exists for concurrence between the predictions and the data upon which the matrix was constructed, one main purpose

of this exercise was to assess the efficacy of the matrix to produce reasonable predictions of population change without

application of sophisticated mathematical manipulations. Given the qualitative format of Hamel’s (1992) guide, we were

encouraged by the apparently accurate projections of bird population densities. In fact, predictions developed in this paper

appear to provide support for this type of approach in wildlife management. Predictions derived from Hamel’s (1992) work,

whether needing substantial refinement or not, may be the best that land managers have to work with until predictions are

tested and additionalresearch is conducted to evaluate the effects of traditional and nontraditional silvicultural treatments on

bird populations.

ACKNOW LEDGMENTS

D. R. Petit’s participation was partially funded by the U.S. EPA’s Environmental Monitoring and Assessment Program

through a grant to T. E. Martin. T. Bently Wigley made numerous useful comments on the manuscript.

LITERATURE CITED

Capen, David E., ed. 1981. The use of multivariate statistics in studies of wildlife habitat. Gen. Tech. Rep. RM-87. Fort

Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station.

249 p.

Conner, Richard N.; Via, Jerry W.; Prather, Irvine D. 1979. Effects of pine-oak clearcutting on winter and breeding birds

in southwestern Virginia. Wilson Bulletin. 91(2): 301-316.

Crawford, H. S.; Hooper, R. G.; Titterington, R. W. 1981. Songbird population response to silvicultural practices in central

Appalachian hardwoods. Journal of Wildlife Management. 45(3): 680692.

DeGraaf, Richard M., tech. coord. 1978. Proceedings of the workshop on nongame bird habitat management in the

coniferous forests of the western United States. Gen. Tech. Rep. PNW-64. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Forest and Range Experiment Station. 100 p.

DeGraaf, Richard M. 1991. Breeding bird assemblages in managed northern hardwood forests in New England. In: Rodiek,

Jon E.; Bolen, Eric G., eds. Wildlife and habitats in managed landscapes. Washington, DC: Island Press: 155171.

Duffy, David Cameron; Meier, A.J. 1992. Do Appalachian herbaceous understories ever recover from clearcutting?

Conservation Biology. 6(2): 196-201.

Ehrlich, Paul R.; Dobkin, David S.; Wheye, Darryl. 1988. The birder’s handbook: a field guide to the natural history of

North American birds. New York: Simon and Schuster. 785 p.

Evans, Keith E. 1978. Oak-pine and oak-hickory forest bird communities and management options. In: DeGraaf, Richard

M., tech. coord. Proceedings of the workshop on management of southern forests for nongame birds. Gen. Tech. Rep.

SE-14. Asheville, NC: Department of Agriculture, Forest Service, Southeast Forest Experiment Station: 76-89.

Evans, Keith E.; Kirkman, R.A. 1981. Guide to bird habitats of the Ozark Plateau. Gen. Tech. Rep. NC-68. St. Paul, MN:

U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station. 79 p.

Hamel, Paul B.; LeGrand, Harry E., Jr.; Lennartz, Michael R.; Gauthreaux, Jr., Sidney A. 1982. Bird-habitat relationships

on southeastern forest lands. Gen. Tech. Rep. SE-22. Asheville, NC: U.S. Department of Agriculture, Forest Service,

Southeastern Forest Experiment Station. 417 p.

124
Hamel, Paul B. 1992. Land manager’s guide to the birds of the South. Chapel Hill, NC: The Nature Conservancy,

Southeastern Region. 437 p.

Johnston, David W.; Gdum, Eugene P. 1956. Breeding bird populations in relation to plant succession on the Piedmont of

Georgia. Ecology. 37(l): 50-62.

Joyce, Linda A.; Flather, Curtis H.; Flebbe, Patricia A.; Hoekstra, Thomas W.; Ursic, Stan J. 1990. Integrating forage,

wildlife, water, and fish projections with timber projections at the regional level: a case study in southern United States.

Environmental Management. 14(4): 489-500.

Martin, Thomas E. 1992. Breeding productivity considerations: what are the appropriate habitat features for management?

In: Hagan, John M., III; Johnston, David W., eds. Ecology and conservation of neotropical migrant land birds.

Washington, DC: Smithsonian Institution Press: 455-473.

Medin, Dean E. 1985. Breeding bird responses to diameter-cut logging in west-central Idaho. Res. Pap. INT-355. Ogden,

UT: U.S. Department of Agriculture, Forest Service, Intermountain Research Station. 12 p.

Ruggiero, Leonard F.; Aubry, Keith B.; Carey, Andrew B.; Huff, Mark H., tech. coord. 1991. Wildlife and vegetation of

unmanaged Douglas-fir forests. Gen. Tech. Rep. PNW-285. Portland, OR: U.S. Department of Agriculture, Forest

Service, Pacific Northwest Forest and Range Experiment Station. 533 p. /

Vemer, Jared; Boss, A.S. 1980. California wildlife and their habitats: western Sierra Nevada. Gen. Tech. Rep. PSW-37.

Fresno, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Forest and Range Experiment Station.

439 p.

Vemer, Jared; Morrison, Michael L.; Ralph, C. John, eds. 1986. Wildlife 2000: modeling habitat relationships of terrestrial

vertebrates. Madison, WI: University of Wisconsin Press. 470 p.

Webb, William L.; Behrend, Donald F.; Saisom, Boonruang. 1977. Effects of logging on songbird populations in a northern

hardwood forest. Wildlife Monogr. 55. Washington, DC: The Wildlife Society. 35 p.

125
Wildlife Habitat Conditions in Mature Pine-Hardwood Stands in the Ouachita/Ozark National Forests’

Ronald E. Thill, Philip A. Tappe, and Nancy E. Koerth2

ABSTRACT

A long-term, stand-level, interdisciplinary research and demonstration project was

initiated on the Ouachita (ONF) and Ozark-St. Francis National Forests in Arkansas in

1990 to compare the impacts of alternative reproduction cutting methods on commodity

and noncommodity forest resources including wildlife habitat and populations. Habitat

measurement procedures and pretreatment habitat conditions for 20 of the 52 stands

included in this study are summarized here. The wildlife component of this study consists

of a completely randomized block design involving four physiographic zones (blocks),

each containing one replication of five treatments (four future treatments and an untreated,

late-rotation control). Of the 69 habitat parameters analyzed to date, 11 differed significantly (I’~0.05) by physiographic zone, but only 1 differed by future treatment. From

a wildlife standpoint, these late-rotation stands primarily consisted of south-facing,

relatively xeric sites characterized by high canopy coverage, an abundance of mostly small

hardwoods, very limited winter herbage and browse supplies, moderate snag abundance,

and limited amounts of down wood. Most of the hardwoods are too small to produce

much mast, and densities of the larger (~35 cm in d.b.h.) snags are insufficient to

accommodate high populations of several of the larger resident cavity-dependent wildlife

species. Snags and down logs of recent origin were generally scarce. Recent amendment

of the USDA Forest Service ONF Forest Plan should help to ameliorate these conditions.

INTRODUCTION

Even-aged silviculture employing clearcutting, site preparation, and planting of pines has been the primary method of

regeneration on southern national forests for more than 25 years. Although young plantations provide excellent habitat for

many wildlife species, even-aged management on short rotations is generally detrimental to those species that require an

abundance of snags, cavity and den trees, hardwoods, hard mast, large down wood, and other mature-forest features (Thill

1990). The USDA Forest Service has been under increasing pressure to consider alternatives to even-aged management

(especially to clearcutting), such as single-tree and group selection and expanded management for pine-hardwood mixtures.

In response to growing public concern over management of the national forests in Arkansas, a long-term, muitidisciplinary, stand-level research and demonstration project was initiated on the Ouachita and Ozark-St. Francis National Forests

in 1990 to compare alternative reproduction cutting methods relative to their silvicultural feasibility and their impacts on

commodity and noncommodity forest resources (Baker, this volume). Determining the effects of these treatments on wildlife

populations and habitat features is a primary objective of this research.

The objective in this paper is to characterize pretreatment wildlife habitat conditions in 20 stands (table 1) that are being

studied under this initiative. Habitat measurements and procedures are described, the 20 stands are characterized, and

differences by physiographic zones and future treatments are presented. Pretreatment bird and small mammal data are

presented in separate papers within this proceedings.

’ Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

2 Supervisory research wildlife biologist, USDA Forest Service, Southern Forest Experiment Station, Nacogdoches, TX

75962; assistant professor, School of Forest Resources, University of Arkansas at Monticello, Monticello, AR 71656;

computer assistant, USDA Forest Service, Southern Forest Experiment Station, Nacogdoches, TX 75962.

126
Table l.-Idenrijicaiion of wildlife research plots by physiographic zone (block), future treatment, district,

compartment, and stand

ID no. Zone Treatment District Compartment Stand

1

2

3

4

5

6

1

8

9

10

11

12

13

14

15

16

17

18

19

20

North

North

North

North

North

East

East

Eat

East

East

south

south

SOUth

SOUth

south

West

west

CI& WUt Fourche 458 16

Shelterwood Fourche 457 12

Group selection Magazine * 46 18

Single-tree selection Magazine * 70 10

Untreated control Cold Springs 284 11

CleaXllt Oden 1067 15

Shelterwood Oden 1119 21

Group selection Oden 1124 11

Single-tree selection Jessieville 609 9

Untreated control Jessieville 605 5

Clearcut Womble 1658 5

Sheltenvood Caddo 27 1

Group selection Caddo 35 42

Single-tree selection Womble 1649 13

Untreated control Caddo 23 10

CleaXtit PO&au 1292 2

Shelterwcod Mena 833 1

Group selection Choctaw 62 6

Single-tree selection Kiarnichi 248 17

Untreated control Mena 896 7

‘Ozark-St. Francis National Forest; all others on the Ouachita National Forest.

SELECTED HABITAT PARAMETERS

For the eventual development of wildlife-habitat relationship models, data were collected on a host of habitat parameters

that are: (a) nondestructive to obtain, (b) relatively easy to collect, and (c) often correlated with and/or useful in predicting

wildlife abundance and diversity (Gysel and Lyon 1980, Hays and others 1981). These parameters are described below.

Overstory Conditions

Characteristics of the forest overstory (e.g., tree density, spacing, and height; species composition; and the number of

vertical layers) greatly influence understory floral composition and production, vertical structural complexity, microclimate,

and a host of other habitat parameters that influence wildlife diversity and abundance. For example, hardwood retention

within pine stands typically improves habitat conditions significantly for a broad range of wildlife species by increasing habitat

and microsite diversity, forage substrate (e.g., bole, bark, leaves, and fruits), vertical structural complexity, dens and cavities,

and/or through the amelioration of microclimatic influences. Forest avifaunal diversity is generally positively correlated with

stand structural complexity (Dickson and Segelquist 1979, MacArthur and MacArthur 1961, Meyers and Johnson 1978), but

dense, multilayered hardwood midstories can drastically limit available forage for vertebrate herbivores (Blair and Brunett

1976, Blair and Feduccia 1977).

Information on sizes, densities, and species composition of hardwoods is useful in predicting hard mast production

(Goodrum and others 1971) and availability of natural cavities (Allen and Corn 1990).

Snags and Stumps

Snags provide foraging substrate, roosting and hiding sites, and cavity sites for numerous vertebrate and invertebrate

species (Thomas and others 1979a). Stumps also provide additional structure, cover, and foraging substrate used by som e

species (Maser and others 1979). Absence of suitable nest sites is often a limiting factor for cavity nesting bids (Thomas

and others 1979a), which comprise an ecologically important component of southeastern forest avifauna. Consequently,

wildlife abundance and diversity can be increased through retention of snags of appropriate sizes. Snag preferences of cavity

127
nesting species are dependent on a number of factors including tree species, diameter, height, and stage of decay (Evans and

Conner 1979, Thomas and others 1979a).

Dow n Wood

Down woody material serves many crucial ecologicai functions, many of which have only recently been appreciated

(Harmon and others 1986, Maser and others 1979). These functions influence floral and fauna1 diversity, site productivity,

nutrient cycling, and soil and sediment transport and storage (Harmon and others 1986). From a wildlife standpoint, these

materials are used as hiding cover, feeding sites, and reproduction sites (Maser and others 1979). For example, many

Pkthodbn salamanders require moist, rotting logs and litter for egg development and adult cutaneous respiration (Stebbins

1966). Down woody material provides an energy/nutrient source and habitat for many bacteria and fungi. Some small

mammals prefer to travel along down logs and branches rather than directly on the ground (Planz and Kirkland 1992).

Capture success for deer mice (Peromyscus maniculutus) was highly correlated with coverage of down logs and stumps per

acre in Arizona ponderosa pine (Pinus ponderosa Dougl. Ex Laws.) forests (Goodwin and Hungerford 1979).

Factors infhtencing animal use of down wood include size (diameter and length), species, decay state, and overall

abundance/distribution of down wood (Harmon and others 1986). Larger down logs provide more cover and generally persist

longer than smaller logs (Maser and others 1979, Maser and Trappe 1984). Transitional stages of decay afford different

habitat features. For example, loose bark provides hiding and thermal cover for small vertebrates. In advanced stages of

decay, small mammals can excavate burrows, which, in turn, may be utilized by amphibians and reptiles (Harmon and others

1986). Over a wide range of forest types and seral stages, Harmon and others (1986) indicated that small mammals that use

down woody materials comprise 70 to 90 percent of the species richness and 75 to 99 percent of the total number of

individuals.

Much less is known regarding herpetofaunal communities and their reliance on down wood.However, Pacific Northwest

reptiles and amphibians that use down wood comprise 93 percent of the species and 99 percent of the individuals (Harmon

and others 1986).

Ground Cover

Rocks and rock piles provide a host of habitat elements (e.g., sunning sites, thermal and hiding cover, and habitat

structure) for smaller organisms including many amphibians, reptiles, and small mammals.

Litter depth influences a number of important biological processes including soil moisture evaporation, water infiltration,

and soil heating and cooling. Litter provides forage and foraging sites, thermal and hiding cover, and can significantly

influence microclimatic conditions for many amphibians and reptiles (Jones 1986), small mammals, and other smaller

organisms. It also provides habitat for invertebrates that serve as food for vertebrates. Litter cover, thickness, and

composition also influence nutrient cycling and soil erosion, which, in turn, influence long-term site productivity. Understory

herbage production is generally inversely related to litter depth (Gaines and others 1954).

Plant Cover

To a large extent, wildlife abundance and diversity are closely related to the abundance, diversity, structure, and

nutritional quality of available herbaceous and woody plants, mainly through their influences on forage availability and cover

conditions. Forage and cover are generally most limiting during late winter; consequently, late-winter measures of these

variables were assumed to be more highly correlated with animal abundance and diversity than growing season measures.

Ocular estimates of percent cover (proportion of an area covered by the vertical projection of plant crowns to the ground

surface) are much less expensive to collect than forage production data and are generally sufficiently correlated with forage

production to derive meaningful inferences (Gysel and Lyon 1980).

Horizontal foliage cover (often referred to as security or hiding cover to distinguish from thermal cover) is a measure

of the concealment that vegetation and other structural features (e.g., rock or down wood) afford an animal from its predators.

Many animals have evolved preferences for certain cover conditions; consequently, cover measurements are often useful in

developing wildlife-habitat relationships (Thomas and others 1979b). Patchiness, a structural habitat measure describing

vegetation distribution in a horizontal plane, can be computed as the variance among horizontal cover estimates for each

vertical layer measured (Anderson and Ohmart 1986). Measures of patchiness, together with vertical structure, are useful in

predicting avian community structure (Rotcnberry and Wiens 1980).

128
METHODS

Study Areas and Treatments

Four replications of twelve silvicultural treatments are currently being implemented on an operational basis in forty-eight

14.2- to 16.2~ha late-rotation stands. Four untreated control stands of this size and type were also established; these plots will

remain untreated (except for insect and fire protection) to provide a minimum management scenario for comparative purposes.

These treatments were randomly assigned to 13 late-rotation stands in each of 4 physiographic zones of the Ouachita National

Forest and 2 southern districts of the Ozark-St. Francis National Forest. Logging was initiated during May 1993 and

completed by the fall of that year.

Because of limited resources, habitat and wildlife responses are being monitored on only four replications of the following

five treatments: untreated control, clearcut, shelterwcod, single-tree selection, and group selection. An overstory hardwood

component (approximately 5 m*/ha) will be maintained in the latter three treatments to enhance wildlife and esthetic values.

All stands selected for this study have a predominantly south, southeast, or southwest aspect and slopes of 5 to 20 percent.

Prior to treatment, selected stands contained 13.8 to 25.3 m2 of merchantable pine basal area (BA) and 4.6 to 11.5 m* of

merchantable hardwood BA (Baker, this volume). Shortleaf pine (Pinus echinutu Mill.), post oak (Quercu(i stellatu

Wangenh.), winged elm (Ulmus al&z Michx.), and blackjack oak (Q. marilundicu Muenchh.) tend to dominate these slopes

(Clapp 1990). On south-facing slopes in the Crystal Mountain area, white oak (Q. albu L.) was dominant on lower slopes,

blackjack oak on middle slopes, and post oak on upper slopes (Mayo and Raines 1986). For a complete description of

climate, geology, treatments, physiographic zones, and stand selection and randomization procedures, see Baker (this volume).

Transects

Permanent transects were established in each of the 20 wildlife research stands for small mammal trapping, habitat

measurements, and bicdi versity surveys. To ensure systematic coverage and adequate spacing between transects for small

mammal trapping, the following procedures were used to establish these transects. An azimuth was selected that roughly

paralleled the elevation contour of the stand. Each stand was then divided into imaginary %-m-wide bands along this selected

azimuth. One transect was then randomly established within each band across the width of the stand, with the limitation that

no two transects could be closer than 30 m apart (fig. 1). Starting 50 m from the stand boundary, unnumbered stake flags

were then placed at 15-m intervals along all transects to within 50 m of the opposite end of each transect. This ensured at

least a 50-m buffer zone around the entire sampling area. Stake flags were then removed in concentric circles from the

outside inward until 100 points remained in each stand, 80 of these points were randomly selected for use as small mammal

trapping stations and associated habitat measurements. The entire transect length is being used for biodiversity surveys by

another research team. Under this arrangement, actual buffer-zone widths varied depending on the size and shape of each

stand. Where sufficient greenbelt areas (buffer strips that will be retained along drainages having a defined channel) were

present, eight (10 percent) of the trap stations were placed in what were presumed to be future greenbelts. Thirty of the

eighty stations were randomly selected to serve as permanent habitat sampling points for monitoring long-term habitat

changes. Data from all 80 stations will eventually he used to develop small mammal habitat relationship models. However,

only 1992 data from the 30 permanent sampling points were used in the analyses presented here.

Habitat Measurements

Habitat measurements at each station were confined to three adjacent 2- by 2-m quadrats (each containing a nested lby l-m quadrat), a 5-m-radius semicircle, and a 15-m-wide belt transect (fig. 2). With the exception of growing season

(June/July 1992) measures of horizontal cover, all measurements were taken during late winter (February and early March)

1992.

Percent coverage of rock, bare ground, and litter were estimated ocularly within the three l- by l-m quadrats. Litter

depth was measured at three points in each l- by l-m quadrat, averaged, and assigned to a 2-m increment class (0.00 to 1.99,

2.00 to 3.99, etc.). Percent coverage of all down wood >2.54 cm in diameter was ocularly estimated within each of the three

2- by 2-m quadrats. Percent coverage of forhs and graminoids (grasses and grasslike plants, collectively) during late winter

was estimated within each l- by l-m quadrat; percent coverage of browse (leaves of evergreen and tardily deciduous woody

plants to a height of 2 m) was estimated within the three 2- by 2-m quadrats. Data collected iu each of the three equal-sized

quadrats were averaged, yielding one value per station.

Dead logs lying within the 5-m-radius semicircle and having an average diameter ~10 cm were measured for volwne,

identified as pine or hardwood, and classified into one of four classes (from least to most decayed): (1) branches and small

129
1 Upslope

Qr=.nbelt Strip

figure L-Layout of sm all m am m al trap stations at 15-m intervals along randomly selected transects within 50-m-wide lx.znak

(dashed lines). A bufer strip of at least 50 m separates sampling points from adjacent stanh .

A

15-m Ship Trmmoct for Snag Survey ___):

S-m-R~dlua Semiclrck tot * Down Wood and Stump Sunny’

i

Figure 2.-Location of nested I- by l-m and 2- by 2-m quadrats, S-m-radius semicircle, and 15-m-w’& strip transects relative

to small mammal trap stations. Trap stations (solid circles) are located at 15-m intends along pe rm anent

transects.

130
twigs still intact; (2) larger branches still intact and often holding the log above ground; (3) lying on the ground but with most

of the length still intact; (4) rotten and soft with much of the length reduced and the bole partly buried in litter.

Data on hardwood densities (means for each species by stand) were furnished by the Silvicultural Research Group.3 One

measurement of pine and hardwood basal area was also taken from the center of each S-m-radius semicircle using a Wfactor

(English) prism; all data were converted to metric values. All snags (standing dead trees 210 cm in d.b.h. and 21 m tall)

were tallied within the &m-wide belt transect (fig. 2) along its entire length (1,365 to 1,425 m depending on stand size and

shape; 2.05 to 2.14 ha/stand) by decay class and measured for d.b.h. Decay classes were modified from Nemo and others

(1985): (1) full height with branches and fine twigs; (2) some major branches remaining, may have lost up to one-half of

upper bole; (3) no major branches remaining, >2 m tall, more than half the upper bole gone or trunk less than half its original

diameter; (4) sapwood gone, ~2 m tall, more decayed than class 3. Snag data presented here were grouped into three diameter

classes based on minimum diameter requirements of primary cavity nesters (Hamel 1992): (1) below minimum size (10.0 to

14.9 cm), (2) adequate for smaller cavity nesters (15.0 to 34.9 cm), and (3) suitable for larger cavity nesters (235.0 cm). All

stumps within the 5-m-radius semicircle having a diameter of 215.2 cm were tallied. Stump and snag data were converted

to densities (number/ha).

t Horizontal foliar cover was estimated using a 0.5- by 0.5-m density board (Nudds 1977). Readings were taken

perpendicular to transect lines across the center of each 2- by 2-m quadrat from a fwed distance of 15 m between the density

board (positioned on the transect side of each quadrat) and the observer. Three vertical readings (density board resting on

the ground and centered at 1 and 2 m) were taken across each quadrat. Readings were averaged, yielding one value per height

per station. The variance among readings for each zone across the 30 stations was computed as a measure of habitat

’ patchiness (Anderson and Ohmart 1986).

Data being collected by several other research teams will eventually be used to complement our habitat data. For

example, the Biodivemity Research Group is collecting foliage cover data by species for herbaceous and woody plants during

summer. Inferences on availability of key wildlife forage species will be based on these data. Data being collected by the

Silvicultural Research Group on hardwood diameters, species, and dominance (canopy position) will be used to compare

relative hard mast production potentials for each of the treatments. These data were not available for inclusion in this report

Avian microhabitat data that are being collected by Petit and others (this volume) on five to six 40-m-radius bird censusing

plots located in each stand will be summarized at a later date.

ANALYSES

Two hypotheses were tested: (1) there were no differences in various habitat parameters among the four physiographic

zones prior to treatment implementation and (2) there were no differences in habitat parameters among stands (grouped by

future treatments) before treatment.

Differences among zones (blocks) and future treatments in horizontal cover, litter depth, grounafoliar cover (rock, bare

ground, litter, down wood, forbs, graminoids, and woody plants), stump density, and basal area of pines and hardwoods were

analyzed in a randomized block design with both experimental error and sampling error (n = 600 [20 experimental units by

30 points] except forb, graminoid, and woody plant cover [n = 597). If the ratio of experimental error to sampling error was

significant (P <0.05), experimental error was used to test for effects of future treatments and zones; if not, sampling error

was used. This ratio was significant in all but two cases: percent bare ground (P = 0.3399) and percent woody cover (I’-

0.5907).

Differences in horizontal patchiness (variance of horizontal cover in each stand), snag density (based on one value per

stand), and hardwood density (obtained as a mean for each stand) data were tested using experimental error. Down log

volume was also analyzed using experimental error because of the high incidence of zeros (81 to 100 percent of values).

Data were examined for normality and homogeneity of variance. For one-way ANOVAs, densities of stumps, snags, and

hardwoods and volume of down logs were rank-transformed and analyzed using Conover and Iman’s (1981) nonparametric

procedure. Percentage data (cover and density board) were arcsine square root-transformed to improve variance homogeneity.

Tukey’s HSD was used for separation of means. All tests were at the 0.05 level of significance.

3 Unpublished data file “T3NS.DAT” on file with USDA Forest Service, Southern Forest Experiment Station, Nacogodoches,

TX 75962.

131
RESULTS

Habitat Characteristics--Study Wide

Descriptive statistics for the various habitat parameters collected on all 20 wildlife stands are shown in table 2. With

the exception of snag densities (which are based on a 1%m-wide by 1,365- to 1,425m-long belt transect through each stand),

each mean is an average across 20 stand means, each of which is based on data from 30 sampling plots.

From an overall wildlife standpoint, these stands are characterized by high canopy coverage, an abundance of mostly

small hardwoods, very limited winter herbage and browse supplies, moderate snag densities (see discussion section), and small

amounts of down woody materials.

Differences by Zones

When habitat parameters were compared among physiographic zones (n = 5 stands/zone), means of only 11 of the 69

variables (tables 3 through 5) were different (P ~0.05). Even among these 11 variables, however, the magnitude of

differences was generally small. Although these data indicate that these stands are relatively uniform across zones, future

statistical tests for some habitat parameters are likely to be more powerful if zones are included as a separate source of

variation

Differences by Future Treatments

only 1 of the 69 variables (volume of down pine logs, decay class 3) differed significantly among future treatments (n

= 4 replications/treatment) (tables 6 through 8). only one additional variable (total volume of down logs, decay class 3) had

a significance level of co.10 (table 8).

DISCUSSION

Within inherent edaphic and climatic limitations, forest management practices in the Ouacbita Mountains are the primary

determinants of wildlife habitat sufficiency. Although snag densities and volume of down wood are partklly a function of

natural disturbance events (lightning, windthrow, wild fire, insects, and disease) and natural decay rates, forest management

activities (such as rotation length, frequency and extent of thinning operations, season and frequency of prescribed burning,

and hardwood control practices) can greatly influence their abundance and availability over time.

The availability of snags in Southeastern and South Central States varies widely by forest type and stand age (McComb

and others 1986); however, the range in densities is much narrower when only pine types are compared (table 9). Due to

differences in diameter classes, data in table 9 are not directly comparable; however, they suggest that snag densities in this

study fall within ranges typical of other regional sites.

The minimum snag requirements for cavity-nesting bird populations that have been developed for different regions vary

widely depending on whether reserve snags are included to account for unsuitable/unused snags and those required as

replacement snags (Carmichael and Guynn 1983, Evans and Conner 1979). Based on the very conservative minimum snag

requirements developed by Carmichael and Guymr (1983), which included no provision for reserves, snag densities in this

study are insufficient to support high populations of cavity nesters that require snags 235 cm in d.b.h.-such as pileated

woodpeckers (Dryocopus pileatus), red-bellied woodpeckers (Meherpes curolinus), red-headed woodpeckers (Meherpes

erythrocephah), or barred owls (Strin varia) (Hamel 1992). Pretreatment bird surveys also support this premise. Compared

with other pine-associated forest types in the Southeast, these 20 stands had comparable numbers of bird species within all

but the cavity nesting guild (Petit and others, this volume). A shortage of suitable cavity trees is most likely the primary

cause for this difference. Furthermore, because few of the snags are of recent origin (decay class 1, tables 4 and 7),

sustainable supplies of snags over time should be of concern.

Given their abundance and insectivorous diet, cavity-nesting birds play an important role in control of forest insect pests.

As primary cavity nesters, woodpeckers create cavities needed by a wide variety of vertebrates and invertebrates.

Consequently, cavity nesters (especially woodpeckers) are of major ecological importance, and their welfare should be a

primary concern under ecosystem management.

The importance of large down woody debris bas not been adequately assessed for southeastern forests. Nevertheless,

based on extensive research in the Pacific Northwest, woody debris is presumably of major ecological significance elsewhere.

Even though trees as small as 10 cm in diameter were included, volume of down wood was low on all sites. Furthermore,

quantities of down logs within decay classes 1 and 2 (recent origin) were much lower than in decay classes 3 and 4 (tables

5 and 8), suggesting that down-log abundance will be even lower as decay classes 3 and 4 disappear. Down logs in decay

132
Table 2.-Descriptive statistics for h abi,m m e asure m ents from wildlife research star& in the Ouuchita

Mountak of Arkansas, 1992

H abitat param e te r M e an

-

Coe f.

SE Minim um Maxim um var. (46)

Basal are a (m 2/h a)

Pin e

H ardw ood

All

17.6 0.9 12.5 24.2 22.4

8.4 0.6 4.3 14.2 33.4

26.0 1.0 18.1 37.1 16.8

H ardw oods (no./h a)

9 .1-24.3 cm d.b.h .

24.4-39 .5 cm d.b.h .

39 .6-54.8 cm d.b.h .

154.9 cm d.b.h .

351.2 18.9 218.9 538.3 24.1

27.1 3.9 5.2 72.7 64.1

3.5 0.9 0.4 18.0 111.9

0.4 0.2 0.0 4.0 205.9

Snags (no& a)+

10.0-14.9 cm d.b.h .

15.0-34.9 cm d.b.h .

~ 35.0 cm d.b.h .

10.1 1.3 0.9 20.6 59 .7

6.7 1.0 1.4 17.8 68.9

0.8 0.2 0.0 2.8 9 5.6

Stum ps (no& a) 101.9

Down w ood volume (m 3/h a)*

Decay class 1

Decay class 2

Decay class 3

Decay class 4

All

0.09 0.1 0.0 0.8 273.6

0.37 0.2 0.0 3.7 238.2

2.70 0.4 0.1 6.3 70.3

3.87 0.6 0.1 11.2 75.1

7.02 0.9 1.6 14.9 58.4

GroondEfoliar cove r (W )

Rock

Bare ground

Litte r

Down w oods

Forbs

Gram inoids

w oody plants

2.2 0.4 0.2 6.8 85.8

1.4 0.2 0.2 4.0 69 .2

9 3.1 0.6 87.7 9 8.1 2.7

3.3 0.2 1.4 5.2 33.9

2.3 0.5 0.6 9 .4 88.2

1.4 0.3 0.1 5.4 9 6.4

0.3 0.1 0.0 1.4 122.5

Litte r de pth (cm ) 2.1

H oriz ontal cove r (%)‘T

0.00-0.50 m

0.75-1.25 m

1.75-2.25 m

53.0 3.1 26.9 86.0 26.5

32.1 2.7 15.8 60.7 37.0

38.7 3.5 21.8 76.8 40.3

H orizontal patch iness

0.00-0.50 m

0.75-1.25 m

1.75-2.25 m

9 76.9 59 .3 546.6 1445.5 27.1

9 11.3 52.8 285.9 1444.8 25.9

9 71.9 52.1 714.4 1364.3 24.0

17.6

0.1

0.0

1.7

339 .5

3.1

77.4

14.9

*Values we re com puted using stand ave rages (n - 20 stands). W ith the e xce ption of snag densities

(de rived from on e strip t-stand), e ach stand ave rage w as based on 30 sam pling points.

+ Totals across pines, h ardw oods, and four decay classes.

sValues are totals for pine and h ardw oods (210 cm ave rage diam e te r); decay class 1 is le ast decayed,

4 is m ost decayed (see te xt).

§All w oody m ate rial 22.54 cm in diam e te r.

nPe rce nt obscurity from 15 m .

133
Table 3.-Habitat ch am cteristics (% k SE) in w ild life research stana!s in the Oumhita Mountains of Arkansas by physiographic zone. 1992

H abitat param e te r F” P+ Wes t North SOUth Eas t

hd -(m2/W

Pine

H ardw ood

All

3.73 0.0331 15.9 AB 0.6 21.2A 2. 0 14.9 B 1. 0 18.5AB 1.8

1.10 0.3768 7.8 0.7 9 .8 1.7 6.8 1.2 9 .0 1.1

12.45 0.0002 23.8AB 0.2 31.OC 1. 6 21.7A 1. 0 27.5BC 1.3

H ardw oods (no& )

9 .1-24.3 cm d.b.h .

O& s

H ick ories

Gth e ts

All ’

0.59 0.6331 287.0 52.6 212.5 18.5 218.5 37.6 206.2 35.8

2.42 0.1038 27.5 2.4 67.1 12.0 68.1 16.9 64.6 18.8

1.05 0.39 71 53.3 21.0 61.4 13.8 9 0.0 21.9 48.7 16.8

0.22 0.8844 367.8 46.4 341.0 30.7 376.7 50.1 319 .5 26.5

24.4-39 .5 cm d.b.h .

Oilk s

H b k ories

oth e rs

All

0.71 0.5619 23.1 5.9 30.5 9 .8 22.0 7.7 14.3 2.0

0.28 0.8361 1.6 1.3 1.7 0.6 1.5 0.9 2.7 1.3

0.66 0.5858 2.8 1.4 3.6 1.6 3.6 1.8 1.1 0.8

0.66 0.589 9 27.5 5.2 35.8 11.1 27.1 9 .2 18.1 3.6

39 .654.8 cm d.b.h .

Oak s

’ H ick ories

oth e rs

All

0.31

0.34

0.85

0.819 9 3.7 1.3 4.5 2.5 2.1 0.8 2.3 0.5

0.79 67 0.1 0.1 0.1 0.1 0.1 0.1 0.0 0.0

0.4865 0.0 0.0 0.7 0.6 0.3 0.3 0.1 0.1

0.9 701 3.8 1.4 5.4 3.2 2.5 0.9 2.4 0.6

154.9 cm d.b.h .

Oak s

H ick ories*

oth e rs

All

0.65 0.59 56

0.24 0.8669

0.62 0.6147

0.2

0.0

0.1

0.3

0.1

0.0

0.1

0.1

0.7 0.6

0.0 0.0

0.2 0.2

0.9 0.8

146.0 50.9

0.3 0.2

0.0 0.0

0.2 0.1

0.5 0.2

Stum p density (no./h s) 2.56 0.09 13 54.3 23.3 69 .6 9 .8 137.5 32.4

Ground/folisr cove r (%)g

Rock

Bsre ground

Litte r

Down w ood

Forbs

Gtam inoids

w oody plants

0.05 0.9 860 2.5 1.2 2.5 1.1 1.8 0.4 2.0 0.7

3.9 8 0.0080 0.7A 0.2 1.5AB 0.2 1.2AB 0.3 2.3B 0.6

2.04 0.149 2 9 4.8 1.1 9 2.4 1.3 9 3.9 1.0 9 1.5 0.8

0.60 0.6223 3.0 0.6 3.0 0.6 3.4 0.4 3.8 0.5

1.47 0.259 3 2.3 0.7 1.3 0.6 3.6 1.5 2.1 0.6

7.63 0.0022 3.OA 0.7 0.3B 0. 2 l.OB 0. 4 1.2AB 0.3

0.64 0.59 18 0.1 0.1 0.3 0.1 0.5 0.3 0.3 0.1

Litte r de pth (cm ) 1.56 0.2387 2.1 0.1 2.2 0.2 2.2 0.1

H oriz ontal cove r (5%)

O.CKl-0.50 m

0.75-l 25 m

1.75-2.25 m

1.15 0.359 0 51.2 1.9 47.3 4.5 50.9 8.6

0.46 0.7174 31.8 1.7 28.7 1.3 37.7 7.5

3.66 0.0351 34.9 A 2.6 32.OAB 4.2 55.6B 9 . 5

H oriz ontal patch iness

0.00-0.50 m

0.75-l .25 m

1.75-2.25 m

3.03 0.059 8 820 49 1200 8 8 844 113 1044 140

2.65 0.0841 856 64 1015 77 721 119 1053 106

2.14 0.1357 886 89 1048 130 825 54 1128 9 5

0.1 0.1

0.0 0.0

0.1 0.1

0.1 0.1

1.9 0.1

62.4 7.6

30.3 7.9

32.4AB 4.6

‘One-way ANOVA F value (stum p and h ardw ood density dsta we re rsnk -trsnsformed ); m e ans w ith in row s followed by unlike le tte rs sre

statistically diffe rent (P eO.05).

tProbsbility associated w ith one-way ANOVA F value.

*All values we re ze ro.

%Vccdy (52 m tall) and h e rbsce ous plant cove r m e asured in late w inte r.

134
Table 4.-Snag densities (no& r; ii + SE) in w ildlife research star& by decay and diam ete r classes and by ph ysiograph ic z ones, 19 9 2*

Diam e te r

class (cm ) F$ Wes t North SOUth East

1 10.0-14.9 13.73 0.0001 2.31AB 0.67 0.19 BC 0.12 3.83A 0.80 o.ooc 0.00

15.0-34.9 7.77 0.0020 0.19 A 0.12 O.oOA 0.00 l.%B 0.73 0.29 A 0.29

> 35.0 0.9 5 0.4386 0.19 0.12 0.09 0.09 0.09 0.09 0.00 0.00

2 10.0-14.9 2.67 0.0824 2.78 0.84 1.14 0.32 2.62 0.82 2.68 0.34

15.0-34.9 1.29 0.3133 1.73 0.43 0.57 0.46 1.59 0.48 1.24 0.45

235.0 0.34 0.79 67 0.19 0.19 0.10 0.10 0.09 0.09 0.00 0.00

3 I 10.0-14.9 1.26 0.3210 2.78 1.12 4.41 1.77 6.64 1.68 4.02 0.74

15.0-34.9 0.9 5 0.439 8 2.21 0.54 2.39 1.23 4.21 1.74 3.06 0.57

> 35.0 2.21 0.1263 0.48 0.15 0.58 0.18 0.19 0.12 0.28 0.19

4 I 10.0-14.9 2.07 0.1440 0.67 0.36 2.11 0.62 1.40 0.51 2.78 0.87

15.0-34.9 5.00 0.0124 O.%AB 0.42 2.38AB 1.21 0.47A 0.21 3.46B 0.9 5

135.0 1.75 0.19 81 0.00 0.00 0.38 0.28 0.00 0.00 0.38 0.24

All 10.0-14.9 0.9 8 0.4260 8.55 2.78 7.86 2.72 14.50 3.17 9.49 1.57

15.0-34.9 1.22 0.3347 5.09 1.05 5.34 2.86 8.23 2.68 8.06 1.24 \ 235.0 1.03 0.4049 0.86 0.28 1.15 0.49 0.38 0.27 0.67 0.19

l Iuch rdes all pines and h ardw oods 110 cm in d.b.h . and ~ 1 m tall.

+ Decay classes described in te xt.

*One-way ANOVA F value; data w e re rank -transformed . Means w ith in row s followed by tm lik e le tte rs ate statistically diffe rent (P <0.05).

SProbability associated w ith one-w ay ANOVA F value on rank -transformed data

135
Table 5.-Volum e of dawn logs (m3/?u; z + SE) in w ildlife research stands by decay ckzss and ph ysiograph ic ZOM. 19 9 2*

ET Class F* fi Wes t North south East

1 Pine 1.00 0.4182 0.00 0.00 0.00 0.00 0.16 0.16 o.co 0.00

H ardw ood 2.66 0.0837 0.00 0.00 0.00 0.00 0.14 0.14 0.00 o.cm

unk now n 1.00 0.4182 0.00 0.00 0.00 0.00 0.04 0.04 0.00 0.00

All 5.9 0 0.0065 O.OOA 0.00 O.OOA 0.00 0.35B 0.18 O.OOA 0.0 0

2 Pin e

H ardw ood

unk nowns

All ’

2%

1.26

0.0635

0.319 9

0.07 0.07 0.00 0.00 0.15 0.07 0.00 0.00

0.29 0.13 0.75 0.75 0.23 0.23 0.00 0.00

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

1.66 0.2157 0.35 0.16 0.75 0.75 0.38 0.29 0.00 0.00

3 Pin e 1.61 0.2257 0.66 0.34 2.16 0.80 2.03 0.67 1.9 3 0.62

H ardw ood 0.88 0.4745 0.42 0.37 2.12 1.07 0.32 0.29 0.9 7 0.57

UtiOWn 1.75 0.19 66 0.13 0.10 0.00 0.00 0.07 0.66 0.00 0.00

All 3.11 0.0558 1.21 0.68 4.27 0.9 3 2.42 0.75 2.9 0 0.57

4 Pin e 3.03 0.059 9 2.24 0.9 2 2.34 1.26 2.08 0.34 6.17 1.46

H ardw ood 1.50 0.2527 0.50 0.50 0.67 0.22 0.12 0.12 0.49 0.43

I.$IlOWIl 8.25 0.0015 0.43A 0.12 O.OOB 0.00 0.44AB 0.28 O.OOB 0.00

All 2.89 0.0677 3.17 1.12 3.01 1.45 2.63 0.42 6.65 1.36

All Pine 1.9 5 0.1628 2.% 1.23 4.50 1.9 6 4.42 0.9 5 8.10 1.83

H ardw ood 0.83 0.49 55 1.21 0.50 3.53 1.86 0.81 0.48 1.45 0.9 8

U n k n ow n 11.45 0.0003 0.56A 0.15 O.OOB O.CKl OSSA 0.37 O.OOB 0.00

Au 1.39 0.2808 4.73 1.66 8.03 2.41 5.78 1.12 9 .55 1.63

*lnchdes all logs w ith an ave rage diam e te r of > lO cm .

+ Decay classes described in te xt.

*One-way ANOVA F value; data w e re rank -transform e d. Means w itbin row s followed by unlik e le tte rs are statistically diffe rent (P cO.05).

& obability associated w ith one-way ANOVA F value on rank -transform e d data

1AU values we re z e ro.

136
Table 6.-Habitat characterictics (z * SE) in wildliifc research stands in the Ouachita Mountains of Arkansas by fictrcre treatment, 1992

H abitat param e te r

Single - tre e Group

fl P+ Clearcut Sh e lte rw ood sele ction s e le ction Con trol

Basal are a (m ’/h a)

Pin e

H ardw ood

All

H ardw oods (no& a)

9.1-24.3 cm db.h .

Oak s

H ick ories

Oth e rs

All

’ 24.4-39 .5 cm d.b.h .

Oak s

H ick ories

oth e rs

All

39 654.8 cm db.h .

Oak s

H ick ories

Gth e ts

All

~ 54.9 cm d.b.h .

Oak s

H ick ories*

oth e rs

All

Stum p density (no./h a) 0.61 0.6647 104.0 39 .6 163.4 58.8

Ground/foliar cove r (X)§

Rock

Bare gnnm d

Litte r

Dow n w ood

For&

Gram inoids

w oody plants

0.41 0.79 7 5 2.7 0.8 1.7 0.4 1.5 0.7 2.2 1.5 2.8 1.2

1.41 0.2304 0.8 0.2 1.2 0.2 1.4 0.3 1.8 0.6 1.9 0.5

1.08 0.39 9 2 9 3.6 1.5 9 4.2 0.4 9 3.9 0.8 9 3.2 2.2 9 0.8 0.3

0.74 0.579 9 3.1 0.7 3.0 0.2 3.4 0.5 2.9 0.8 4.0 0.5

0.52 0.7238 1.7 0.5 2.1 1.0 1.6 0.6 2.6 0.7 3.6 2.0

0.47 0.754 1 0.7 0.4 1.6 0.8 1.7 0.6 1.9 1.2 1.1 0.2

0.9 0 0.4608 0.1 0.0 0.3 0.1 0.4 0.2 0.2 0.1 0.6 0.4

Litte r de pth (cm ) 0.40 0.8048 2.1 0.1 2.0 0.1 2.1 0.1

H orim ntal cove r (W )

0.00-0.50 m

0.75-1.25 m

1.75-2.25 m

0.77 0.559 7 42.1 5.7 54.2 1.2 55.3 11.1

0.79 0.5514 25.4 5.4 29 .7 0.7 39 .2 7.2

0.56 0.69 67 31.2 5.0 39 .7 3.8 46.9 8.3

H orizartal patch iness

0.00-0.50 m

0.75-1.25 m

1.75-2.25 m

0.45 0.7706 17.5 1.4 18.1 1.8 18.2 2.9 15.3 0.5 19 .0 2.9

0.40 0.8032 7.2 0.8 8.1 1.5 7.8 1.5 9 .6 1.8 8.9 1.6

0.28 0.8859 24.8 1.4 26.2 2.0 26.0 1.5 25.0 1.4 27.9 4.2

0.70 0.6069 254.2 34.4 177.4 36.0 232.1 56.6 278.0 52.2 213.6 32.5

1.06 0.408 2 33.1 8.5 79 .4 23.5 63.5 19 .3 67.5 14.7 40.6 9 .2

1.16 0.3686 28.7 2.8 71.0 15.7 74.6 31.9 53.8 15.3 88.7 23.1

0.64 0.6418 315.9 33.9 327.8 20.2 370.2 77.6 39 9 .3 30.4 342.9 36.8

0.84 0.5220 27.5 6.5 16.4 4.6 27.3 8.0 25.4 13.3 15.6 5.1

0.04 0.9 9 65 1.5 0.9 2.3 1.4 2.0 1.6 2.3 1.4 1.2 0.5

1.03 0.4228 0.8 0.5 2.4 0.9 4.2 2.2 1.4 1.1 5.1 2.0

0.48 0.749 9 29 .8 6.6 21.0 5.8 33.6 9 .5 29 .1 14.9 22.0 6.9

0.36 0.8320 2.3 1.0 2-8 1.5 3.4 1.1 5.2 3.1 2.1 0.4

0.50 0.7328 0.2 0.2 0.0 0.0 0.1 0.1 0.2 0.2 0.0 0.0

1.05 0.4143 0.0 0.0 0.1 0.1 0.5 0.3 0.7 0.7 0.0 0.0

0.67 0.6218 2.5 1.1 2.9 1.5 4.0 1.1 6.1 4.0 2.1 0.4

1.10

0.52 0.725 8

0.60 0.6682

0.42 0.79 20 9 23 128 1131 124 9 19 19 0 9 20 69 9 9 1 166

0.69 0.6080 841 187 863 108 1083 155 9 25 51 844 32

1.24 0.3349 9 72 113 1083 121 1113 144 858 117 833 53

0.39 42 0.2

0.0

0.1

0.3

0.1

0.0

0.1

0.2

0.1 0.1

0.0 0.0

0.0 0.0

0.1 6.1

0.3 0.2

0.0 0.0

0.1 0.1

0.4 0.2

9 9 .7 45.4

1.0 0.7

0.0 0.0

0.2 0.2

1.2 1.0

0.1 0.1

0.0 0.0

0.2 0.1

0.3 0.2

61.5 20.3 80.6 19 .8

2.3 0.3

54.3 8.7

34.8 7.1

40.9 12.2

2.2 0.2

59 .0 5.0

31.5 7.4

34.8 9 .0

‘One-way ANOVA F value (stum p and h ardw ood density data w e re rank -transform e d); m e ans w ith in row s followed by unlike le tte rs are

statistically diffe rent (P eO.05).

+ Probability associated w ith one-w ay ANOVA F value.

*All values w e re z e ro.

%ody (~ 2 m tall) and h e rbace ous plant cove r m e asured in late w inte r.

137
Table ‘I.-Snag densities (no&; x * SE) in wildlfe research s&z&s by &cay and damefer &uses and by future treatments, 1992*

Diameter

class (cm) Ft fi Ckarcut Sh e lte rw ood

Single-tree

sele ction

GYP

sele ction Con trol

1 10.0-14.9 0.20 0.9353 2.25 1.33 1.28 1.28 1.30 0.80 1.89 1.07 1.19 0.74

15.0-34.9 0.15 0.9 58 9 0.35 0.22 0.23 0.23 0.9 4 0.9 4 1.06 0. 9 0 0.48 0.34

z 35.0 1.09 0.39 8 5 0.12 0.12 0.00 0.00 0.12 0.12 0.24 0.14 0.00 0.00

2 10.0-14.9 0.88 0.5006 2.61 0.49 1.40 0.43 1.79 0.63 2.85 0.77 2.88 1.18

15.0-34.9 0.25 0.9 060 1.30 0.76 1.17 0.40 1.55 0.56 1.56 0.64 0.84 0.37

zz35.0 1.56 0.2359 0.00 0.00 0.23 0.23 0.24 0.14 0.00 0.00 0.00 0.00

3 10.0-14.9 1.78 0.1863 4.86 1.38 1.75 0.88 3.54 1.9 6 6.87 1.61 5.31 1.45

15.0-34.9 0.9 2 0.4804 2.49 0.9 2 1.63 0.73 4.38 2.18 4.16 1.06 2.16 0.57

X35.0 0.76 0.5647 0.36 0.23 0.35 0.22 0.48 0.00 0.60 0.23 0.12 0.12

4 10.@14.9 0 . 9 2 0.476 1 1.42 0.46 0.9 4 0.51 1.19 0.49 2.37 1.14 2.78 0.86

15.0-34.9 0 . 9 0 0.489 6 2.14 0.89 0.47 0.27 1.44 0.44 2.74 1.56 2.30 1.44

235.0 1.20 0.3516 0.24 0.24 0.00 0.00 0.12 0.12 0.59 0.36 0.00 0.00

All lO.Sl4.9 1.43 0.2725 11.14 3.47 5.37 2.23 7.82 3.08 13.99 2.71 12.16 2.76

15.0-34.9 1.69 0.2047 6.29 1.50 3.50 1.04 8.30 3.34 9 .52 2.37 5.79 2.48

;35.0 2.17 0.1221 0.72 0.24 0.58 0.35 0.9 6 0.28 1.43 0.51 0.12 0.12

*Includes all pines and h ardw oods ~ 10 cm in d.b.h . and > l m tall.

tDecay classes described in te xt.

*One-way ANOVA F value; data w e re rank -transform e d.

~ Probability associated w ith one-way ANOVA F value on rank -transform e d data

138
Table 8.-Volume of &mm logs (m3/ha; j; + SE) in wildlife research stands by &cay class andfirhuc treatments, 1992’

ck arcut Sh e lte rw ood

Single-tre e Group

s e le ction s e le ction Control

1 pine 1.00 0.4380 0.00 0.00

H ardw ood 0.75 0.5725 0.00 0.00

Unk nown 1.00 0.4380 0.00 o.co

All 0.50 0.7328 0.00 0.00

2 Pin e 0.26

H ardw ocd 0.52

Unk nowns

_ All 0.31

3 Pin e 3.26 0.0411 1.47A 0.70 0.76A 0.31 1.74AB 0.29 0.78A 0.42 3.72B 0.68

H ardw ood 1.52 0.2472 0.12 0.09 0.35 0.35 1.50 0.85 1.9 7 1.33 0.84 0.48

uIlk now tl 0.88 0.5005 0.00 0.00 0.13 0.13 0.00 0.00 0.08 0.08 0.04 0.03

Ah 2.61 0.0775 1.59 0.72 1.23 0.23 3.24 0.9 1 2.84 1.23 4.59 0.61

4 Pin e 1.42 0.2758 3.67 2.52 2.9 9 1.40 1.9 2 0.84 2.01 0.21 5.46 0.9 3

H ardw ood 0.44 0.7766 0.10 0.10 0.67 0.61 0.73 0.52 0.38 0.21 0.33 0.33

unk nown 0.55 0.7039 0.42 0.24 0.11 0.11 0.03 0.03 0.44 0.32 0.09 0.09

All 1.02 0.429 4 4.19 2.34 3.76 1.59 2.68 1.26 2.83 0.45 5.88 1.16

All Pin e 2.27 0.10% 5.14 3.11 3.9 9 1.15 3.75 0.9 7 2.84 0.63 9 .26 1.12

H ardw ood 1.15 0.3704 0.40 0.23 1.02 0.61 2.77 1.06 3.29 2.43 1.27 0.73

unk nown 0.30 0.8709 0.42 0.24 0.24 0.24 0.03 0.03 0.57 0.45 0.13 0.12

All 1.14 0.3755 5.9 5 2.81 5.25 1.51 6.55 1.81 6.70 2.1 10.66 1.56

0.89 75

0.7258

0.869 1

0.00 0.00

0.18 0.18

0.00 0.00

0.18 0.18

0.20 0.20 0.00 0.00

0.01 0.01 0.17 0.17

0.00 0.00 0.00 0.00

0.21 0.21 0.17 0.17

0.05 0.05 0.10 0.10

0.00 0.00 0.36 0.27

0.00 0.00 0.00 0.W

0.05 0.05 0.46 0.36

0.00 0.00

0.00 0.00

0.05 0.05

0.05 0.05

0.00 0.00

0.00 0.00

0.00 0.00

0.00 0.00

0.05 0.05 0.08 0.08

0.9 3 0.9 3 0.10 0.10

0.00 0.00 0.00 0.00

0.9 8 0.9 2 0.18 0.18

*Includes all logs w ith an ave rage diam e te r of 210 cm .

+ Decay classes described in te xt.

*One-way ANOVA F value; data w e re rank -transfotm e d. M e ans w ith in row s followed by unlike le tte n are statistically diffe rent

(P co.05).

%robability associated w ith one-way ANOVA F value oo rank -trausfonued data

nAllvalues we re z e ro.

139
Table 9.-Compurative snag densities for pine forest types of the Southeastern United States*

state

(WoN Forest type

Diameter

C1liS.S

Snag

density Reference

south csro1ina

(Upper Piedmont)

Texas+

(eastern forests)

Louisiana+

(Statewide)

Arkansas

(this study)

Mississippi~

(down)

FlOridi

(Statewide)

south Carolina Pine and pine-hardwood 12.7-35.6 3.0 Harlow and

(Coastal Plain) mix 238.1 0.5 Guynn 1983

Pine-hardwood

Loblolly-sho rtleaf

Loblolly-sho akaf

Shortleaf pine-hardwood

Pine-hardwood zz10.0 6.4

L& iolly pine 112.7 5.4

_____fJm_____

10.140.0 30.1

240.1 0.8

12.7-32.8 12.1

233.0 1.5

12.7-32.8 9.5

233.0 1.3

1X0-34.9 6.7

235.0 0.8

no&a

Carmichael and

Guynn 1983

Rudis 1988a

Rudis 1988b

This study

McComb

1979

McComb and

others 1986

*Data adapted from references shown.

ktk~~ include salvable and nonsalvable dead trees.

*Region unknown; cited by McComb and others 1986.

140
class 1 were absent in three of the physiographic zones, nor were any in decay class 2 found in east zone stands (table 5).

Production of hard mast (acorns and nuts) is dependent on many factors including density and species of mast-producing

trees, site quality, tree age, canopy position, and canopy form. Reliable estimates of mast production are costly to obtain and

were not attempted in this study. However, based on hardwood-stocking information and available literature, several general

statements can be made regarding hard-mast availability.

Given their relatively young age (average of 65 years for all 52 stands) and low site indices (Guldin and others, this

volume), these stands would not be expected to have an abundance of mature, large hardwoods regardless of past management

practices. On a density basis, hardwoods 29.1 cm in d.b.h. comprise 51 percent (mean across 20 stands) of the trees in these

stands, and hard mast producing species (oaks and hickories) comprise a majority of the hardwoods (table 3). However, most

of the oaks and hickories are too small to produce much mast. Based on research from eastern Texas, oaks less than about

25.4 cm in d.b.h. produce little or no mast (Goodrum and others 1971).

In managed forests, sufficient supplies of critical habitat features (like large snags and den trees) must be achieved

through intentional actions. Recent changes in management on the Ouachita National Forest reflect a more socially acceptable

and ecologically sensitive management approach. For example, Amendment 12 (approved July 22, 1993) to the Forest Plan

for the Ouachita National Forest will, among other things, ensure retention of additional hardwoods in pine management types.

Where seed tree and shelterwood regeneration systems are to be employed, this amendment also requires that a mixed

overstory (21.15 m* of hardwood and 2.30 to 3.44 m* of pine BA/ha) be retained indefinitely to enhance structural diversity,

visual quality, and ecological complexity. Longer retention of more pines and hardwoods will eventually result in additional

larger snags and down logs and greater hard mast supplies. This should improve wildlife abundance and species richness,

especially for cavity nesters and bark-gleaning bids (Stribling and others 1990).

’Low densities of small mammals captured on these sites (Tappe and others, this volume) are most likely due to a

combination of factors including limited winter forage and down wood. All of the reproduction cutting methods being tested

should increase forage availability, amounts of down wood, and cover for a number of years, and total numbers of small

mammals should increase markedly. Responses of seed-eating species will be of special interest under those management

systems dependent on natural regeneration.

Greenbelt strips along ephemeral drainages comprise a significant amount of area within these and similar stands and

afford an excellent opportunity to increase habitat features that are in short supply witbin the surrounding stand. Management

of these strips should be designed to increase supplies of snags, large down wood, hard mast, and den trees.

ACKNOWLED&IENTS

We gratefully acknowledge L.D. Hedrick, W.F. Pell, and R.M. Devall for reviewing an earlier draft of this manuscript.

We also thank J.F. Taulman, R.W. Perry, and J.J. Krystofik for collecting the data and reviewing the ftrst draft. Over-story

data were provided by J.M. Guldin.

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eds. Inventory and monitoring of wildlife habitat. Denver, CO: U.S. Department of Interior, Bureau of Land Management

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Ecology. 57( 1): 18-32.

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Wildlife Management. 41(4): 677-684.

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Carolina. In: Davis, Jerry W.; Goodwin, Gregory A.; Ockenfels, Richard A., tech. coo&. Snag habitat management:

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of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station: 107-110.

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Fayetteville, AR: University of Arkansas. 119 p. M.S. thesis.

141
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American Statistician. 35(3): 124-133.

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of north central and northeastern forests for nongame birds: workshop proceedings; 1979 January 23-25; Minneapolis, MN.

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Ecology: 35( 1): 59-62.

Goodrum, P.D.; Reid, V.H.; Boyd, C.E. 1971. Acorn yields, characteristics, and management criteria of oaks for wildlife.

JournaI, of Wildlife Management. 35(3): 520-532.

Goodwin, John G., Jr.; Hungerford, C. Roger. 1979. Rodent population densities and food habits in Arizona ponderosa pine

forests. Res. Pap. RM-214. Fort CoIIins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and

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Advances in Ecological Research. 15: 133-302.

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DC: U.S. Department of the Interior, Fish and Wildlife Service, Office of Biological Services. 111 p.

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Service Center: 267-290. Chapter 14.

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553. Washington, DC: U.S. Department of Agriculture: 78-95. Chapter 6. In cooperation with: The Wildlife Management

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Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Forest and Range Experiment Station.

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Mayo, Derwood C.; Raines, P.L. 1986. Woody vegetation of the Crystal Mountains region. Proceedings Arkansas Academy

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microclimatic characteristics. Baton Rouge, LA: Louisiana State University. 228 p. Ph.D. dissertation.

142
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sufficient for average populations of primary cavity-nesters? Wildlife Society Bulletin. 14(l): 40-48.

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I43
Arthropod Biodiversity-Sampling Protocol Development’

C. E. Carlton, J. Bollinger, and L. C. Thompson’

ABSTRACT

To assess the effectiveness of a variety of sampling methods and determine optimal

sampling intervals for arthropod biodiversity studies in the Ouachita National Forest, a

preliminary survey was conducted on four pine-hardwood sites during the 1993 field

season. Study sites represented a range of disturbance levels from different management

practices and included a control site of undisturbed old-growth forest. Sampling methods

included pitfall traps, Berlese sifting, flight intercept/malaise traps, and unbaited Lindgren

traps. Preliminary results demonstrate methods of presenting biodiversity data and

prioritizing data analysis to address specific concerns. A point-in-time comparison of 5 1

beetle families captured in flight intercept and malaise traps illustrates the differential

effectiveness of the two techniques in sampling broadly defined habitat/functional groups.

An analysis of 28 species of pselaphid beetles collected during a 2-month period

demonstrates the value of high levels of taxonomic precision when small subsets of

diversity data are selected for study. New distribution records and other novel findings

<

for the Ouachita National Forest are presented as an annotated checklist of species.

Finally, recommendations are provided for conducting arthropod biodiversity studies as

a component of long-term ecosystem management.

INTRODUCTION

Identifying links between species, keystone species, and food-web properties are essential elements needed to relate the

richness of functional species groups to the larger species networks (Solbrig 1991). This is especially important because

human-caused disturbances are quickly fragmenting the ranges of many species of organisms (Barbault and Hochberg 1992).

Thus, the dynamics of fragmented populations need to be understood in relation to landscape ecology so that relevant

management solutions may be taken to conserve biodiversity and prevent extinctions.

Collins and Thomas (1989) provided a series of compelling articles dealing with the relationships between insect diversity

studies and the conservation of habitats. A prevailing theme among these discussions is that arthropods represent a vast and

underutilized resource in planning, implementing, and monitoring conservation programs. However, arthropods remain

largely ignored in most large scale treatments of regional biodiversity. For example, Martin and others’ (1993) treatment

of the biodiversity of upland habitats in the Southeastern United States is excellent with regard to plant and vertebrate

communities, but a brief perusal of the volume reveals only 59 references to arthropods (common and scientific names). This

dearth of information reflects the general lack of broad-based arthropod diversity studies even though arthropods can

comprise more than 60 percent of the species and are an integral functional component of virtually all terrestrial communities

(Wilson 1988).

Arthropod biodiversity research has the potential to be complex and expensive because arthropods live on or with all

plants and animals, are associated with most nonliving substrates in a community, and are inherently challenging to study

due to their small sizes and often cryptic habits. Thus, determining which taxa and habitats to sample and how to sample

them is a crucial undertaking.

During the 1993 field season a study was conducted on four stands in the Ouachita National Forest to meet the following

objectives: (1) test various collecting protocols to establish each technique’s usefulness and optimal sampling interval and

(2) make preliminary assessments of the value of specific taxa as biological indicators. The sampling protocols tested are

described, selected results (primarily to demonstrate data recording methods) are presented, and recommendations regarding

the design and implementation of arthropod diversity studies in long term ecosystem management in the Ouachita National

Forest are offered here.

’ Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment Conditions

and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

’ Department of Entomology, University of Arkansas, Fayetteville, AR 72701; Department of Biology, Arkansas State

University, State University, AR 72467; Department of Forestry Resources, University of Arkansas at Monticello,

Monticello, AR 71655, respectively.

144
METHODS

Study Sites

Four sites were sampled (fig. 1); three representing a range of habitat disturbance and one undisturbed control stand.

We had originally envisioned using three New Perspectives Phase I treatment sites, but one of them, a clearcut, was

eliminated for logistical reasons. A nearby early succession sapling stand (site 1, compartment 1646) was chosen in its place

to represent a high level of disturbance. Two intermediate levels of disturbance were represented by a group selection stand

with overstory hardwoods retained in openings (site 2, compartment 143 1, stand 19) and a shelterwood with pines retained

(site 3, compartment 1641, stand 17). The unmanaged control was an old-growth pine-hardwood stand located within Crystal

Mountain Scenic Area (site 4, compartment 1635).

Collecting Techniques

The arthropod faunas of the study sites were sampled continuously using three trapping methods; pitfall, flight

intercept/malaise, and Lindgren. All traps were unbaited and were therefore presumed to be non attractive (but see flight

intercept protocol recommendation below). Continuously operating traps were supplemented by weekly substrate sampling

and visual censuses. A baited survey for the endangered American burying beetle was also conducted. Weekly ultraviolet

light trapping was abandoned due to equipment problems.

\ Pitfall traps (10 per site at 10-m intervals) consisted of 0.5-l plastic cups sunk into the ground with the rims flush with

the surface. Each trap was covered by a small wooden rain shield, which also functioned as a shelter for surface-active

organisms. A 1: 1 mixture of ethylene glycol and saturated saline solution with a small amount of liquid soap was used as

a preservative. Arthropods were removed by straining the preservative through “no-see-em” netting mesh sewn onto an

aquarium net frame.

3 Shelterwood

2

\

Grou\p se’ect

0

0

l v

/

ARKAN

4 Control

1 Sapling stand

Figure 1 .-Arthropod biodiversity sampling sites during 1993 protocol testing.

Combination malaise/flight intercept traps were set in pairs at each site at least 20 m apart. The flight intercept

component of all but two traps consisted of a 3-m trough cut from 18-cm sewer pipe sealed at the ends (original design by

K. Stephan) and located beneath the center vane of the malaise canopy. The flight intercept component of the remaining two

traps consisted of a 3-m row of disposable aluminum meatloaf pans. Flight intercept traps were filled with saturated soapy

saline solution as a preservative. The collecting heads of the malaise components of the traps were filled with ethylene glycol

early in the study. Ethyl alcohol (95%) was used late in the study.

145
Unbaited 12-unit Lindgren traps (Pherotech, Inc., Delta, British Columbia), two per site, were used as midstory flight

intercept traps. Traps were hung from branches approximately 7 m above the ground on all but the sapling site (site l),

where they were hung 3 m high. Traps were lowered and raised during servicing by strings tied at ground level. Ethylene

glycol was used as a preservative.

A Berlese sample was taken at each site when continuously operated traps were serviced. Leaf litter, rotting logs and

stumps, and flood debris were sifted through 0.7-cm mesh screen until approximately 3 kg of material were obtained.

Arthropods were extracted from these samples using Berlese funnels equipped with incandescent lights.

The presence or absence of two species of insects, the American burying beetle (Coleoptera: Silphidae: Nicroph orus

am e ricanus) and the Diana fritillary (Lepidoptera: Nymphalidae: Speyeria d iana), was of particular interest during the study.

The American burying beetle is protected by the Endangered Species Act of the United States; the beetle occurs in nearby

counties in eastern Oklahoma and western Arkansas (Raithel 1991). For the American burying beetle survey, the preservative

was removed from the pitfall traps and replaced with well-rotted chicken gizzard bait. Trapping was conducted on two

consecutive nights, and captured silphids were collected the following mornings.

The Diana fritillary was listed as a candidate for protection under the Endangered Species Act (Anon. 1991) and is

known to occur near the study area in Logan County, Arkansas. The Diana fritillary was surveyed by visual censuses of

the study sites and surrounding areas during service visits.

Sampling Durations and Service Intervals

Sampling was initiated in late April and continuously operated traps were serviced at weekly intervals during May and

June. Weekly Berlese samples were also collected during this period. In early July, flight intercept trapping and Berlese

sampling were terminated, and service intervals for malaise, pitfall, and Lindgren traps were decreased to every other week

during the remainder of the study (terminated in late September). The American burying beetle survey was conducted during

2-3 June.

RESULTS AND DISCUSSION

Although this study was conducted as a preliminary investigation to test sampling protocols, it generated an impressive

volume of specimens and numbers of taxa. Insect activity was most intense and sampling most thorough during May and

June. A conservative estimate of the number of specimens .collected from each site during this period is 3,000 per week; for

four sites during the 8-week period the figure approaches 100,000. Although the last half of the survey may have been

affected by a moderate drought and heat wave, the project resulted in the collection of a total of more than 150,000

specimens for the season.

Selected Coleoptera Data

A point-in-time compilation of beetle family abundances and approximate numbers of species collected in flight intercept

traps on 25 May is shown in table 1. For comparison, captures from the malaise traps for the same date are given in table

2. These data demonstrate differences in the effectiveness of flight intercept versus malaise trapping as passive methods for

sampling aboveground and forest substrate-inhabiting Coleoptera. Flight intercept traps are effective for most Coleoptera

(1,033 specimens in 46 families) but are less effective than malaise traps in sampling aboveground herbivores such as

Chrysomelidae and Cerambycidae. By contrast, malaise traps provide much poorer sample diversity (696 specimens in 41

families). When trap catches are broken down according to broadly defined habitat and functional group categories, it is

evident that the low diversity of malaise trap catches is due.in part to their ineffectiveness in capturing substrate-inhabiting

forms (table 3). The difference in effectiveness may be the result of differential geotaxis of substrate-inhabiting versus

aboveground-inhabiting insects when encountering obstacles. Beetles in the first group tend to drop (positive geotaxis); those

in the latter are about equally likely to drop or crawl up (negative geotaxis).

146
Table 1 .-Coleopte ra fam ily abundances and species diversiiy from Jigh t inte rcept sam ples on a single sam ple date,

25 May 19 9 3. D ata are expressed as num b ers of specim ens/num b ers of species

Family Site 1

(sapling)

Site 2 Site 3

(group select) (sheltetwood)

Site 4

(control)

Aderidae 01 0

Alleculidae o/o

Anobiidae 11 1

Biphyllidae o/o

Bostrichidae 01 0

Buprestidae 21 2

Cantharidae 01 0

Catabidae 010

Chtysomelidae 614

Ciidae 11 1

Coccinellidae 212

Colydiidae 010

Corylophidae Ol 0

Cryptophagidae o/o

Cucujidae II 1

Curculionidae ll 1

Dermestidae 010

Elateridae o/ 0

Endomychidae 010

Erotylidae 51 1

Eucinetidae o/o

Histeridae 010

Hydrophilidae Ol 0

Lagriidae o/o

Lampyridae 010

Lathridiidae o/o

Leiodidae 713

Melandryidae 01 0

Melyridae 11 1

Mordellidae 010

Mycetophagidae o/o

Mycteridae 010

Nitidulidae 5l3

Phalacridae o/o

Phengodidae 010

Pselaphidae 3217

Ptiliidae o/o

Scaphidiidae 010

Scarabaeidae 6l 5

Scirtidae II 1

Scolytidae 4l 2

Scydmaenidae 61 4

Sphindidae 2l 1

Staphylinidae 1418

Throscidae II 1

(Unknown) Ol 0

II 3 ll 1 Ol 0

01 0 010 41 1

31 1 II 1 21 1

ll 1 o/o 010

3l 2 010 01 0

ll 1 010 01 0

21 2 II 1 101 1

ll 1 21 2 ll 1

2315 8l 2 01 0

ll 1 o/o o/o

21 2 21 1 01 0

313 010 010

71 3 II 1 Ol 0

81 1 21 1 o/o

Of 0 o/o or 0

8l 7 514 II 1

212 o/o 010

212 1013 613

41 1 2l 1 ll 1

31 2 21 2 II 1

1/ 1 II 1 o/o

281 3 11 1 01 0

31 2 2412 8/3

010 o/o 11 1

Ol 0 ll 1 01 0

61 1 II 1 Ol 0

231 8 1518 2217

01 0 Ol 0 ll 1

o/o 01 0 010

212 o/o o/o

61 1 010 010

010 010 51 1

71 4 lO/ 2 I/ 1

II 1 II 1 01 0

01 0 31 1 Ol 0

221 7 413 5317

66llO 6l 4 8l 4

212 212 010

010 2814 010

01 0 010 010

7114 291 5 7l 5

13l6 51 3 914

312 ll 1 21 1

112132 54118 86119

221 3 21 1 010

01 0 II 1 71 1

46 families total 102147 4691129 226190 236165

147
Table 2.-Coleopte ra fam ily abundances and species diversity from flight inte rcept sam ples on a single sam ple date,

25 M ay 19 9 3. D ata are expressed as num b ers of specim ens/num b ers of species

Family Site 1

@aelk )

Site 2 Site 3

(group select) (shelterwood)

Site 4

(control)

Aderidae 11 1 lll2 21 1 I/ 1

Alleculidae 11 1 Ol 0 6l 1 321 1

Anobiidae 010 61 1 41 2 21 1

, Apionidae 010 010 ll 1 01 0

Buprestidae 51 2 21 2 21 1 II 1

Byrrhidae o/o If 1 010 II 1

Cantharidae 381 3 II 1 at 2 2714

, Carabidae 01 0 01 0 ll 1 21 1

Cerambycidae 01 0 4J 3 01 0 o/o

Chrysomelidae a/ 7 10716 61 4 01 0

Cicindelidae 212 31 1 ll 1 010

Cleridae 11 1 612 010 ll/ 1

Coccinellidae a/ 2 61 1 51 1 ll 1

Corylophidae 010 II 1 II 1 ll 1

Ctyptophagidae 010 ll 1 01 0 21 1

Curculionidae 9/ 4 614 212 o/o

Dermestidae 31 2 010 o/o 01 0

Elateridae 51 3 61 3 16l5 3012

Erotylidae 2912 010 la/2 II 1

Eucinetidae 01 0 Ol 0 II 1 II 1

Hydrophilidae 01 0 010 Ol 0 II 1

Lampyridae II 1 ll 1 9l 1 01 0

Lathridiidae 21 I 5l 1 121 1 11 1

Leiodidae 01 0 II 1 II 1 01 0

Lycidae 11 1 91 4 61 2 ll 1

Melandryidae 010 51 1 010 1512

Melyridae 01 0 II 1 010 010

Mordellidae 11 1 II 2 1012 11 1

Mycetophagidae 010 ll 1 o/o II 1

Nitidulidae 21 1 o/o 21 1 010

Phalacridae 31 1 010 21 1 01 0

Phengodidae 010 12/ 1 51 1 31 1

Pselaphidae 11 1 o/o l/ 1 11 1

Scarabaeidae I/ 4 21 1 11 1 010

Scolytidae Ol 0 11 1 2l 2 21 1

Scraptiidae 11 1 01 0 Ol 0 01 0

Scydmaenidae Ol 0 010 514 01 0

Silphidae ll 1 01 0 01 0 01 0

Sphindidae ll 1 Ol 0 Ol 0 Ol 0

Staphylinidae 9l4 913 616 31 1

Throscidae 010 221 1 1712 241 1

41 families total i 40148 237148 153152 166130

148
Table 3.-Data from Tables I and 2 categorized by h abita@ium ional groups. D ata are expressed as num b er of

specim ens/num b ers of species

Habitat/ Site 1

functional group (sapling)

Site 2

(group select)

Site 3

(shelterwood)

Site 4

(control)

Flight intercept

Substrate

predators

fungi-herbivores

Aboveground

predators

fungi-herbivores

Malaise

Substrate

predators

fungi-herbivores

Aboveground

predators

fungi-herbivores

53115 109/35 41/18 106120

25114 230159 97138 93127

31 3 18/ 5 161 6 61 3

21115 111/28 78/21 31/12

51 3 51 2 1019 61 3

3917 381 8 59114 ll/ 9

121 6 2218 151 8 1212

82130 148124 42/18 79/11

Diversity data expressed at higher taxonomic categories are particularly useful for establishing priorities for more detailed

research aimed at identifying species that are likely to reveal treatment effects of interest to the investigator(s). In this project,

the identity and abundance of pselaphid beetle species collected during an s-week period were determined. The Pselaphidae,

with approximately 9,000 described species (Newton and Chandler 1989) is a taxonomically rich family of predatory beetles.

Pselaphids are ubiquitous inhabitants of forest substrates worldwide. Many species exhibit high levels of microhabitat fidelity

and geographic endemism, and many species are potentially useful as indicators of habitat manipulation and forest quality

(Carlton and Chandler in press; Chandler 1987).

The species richness of pselaphid beetles at the four sites (from combined Berlese and flight-intercept samples) is listed

in table 4. Overall species richness at the four sites is similar for Pselaphidae, though there is considerable variation in

evenness. Evenness is apparently lowest at the undisturbed control site (site 4), but endemism is highest, with four species

that were not collected at either of the other sites (table 5). Only one other species was limited to a single site.

149
Table 4.-Ps elaph id beetle species diversity from Berlese and fligh t inte rcept sam ples 12 M ay-8 July 19 9 3. D ata are

expressed as num b ers of specim ens

Species Site 1

(sapling)

Site 2 Site 3

(group select) (sheltewood)

Site 4

(control)

Arth m ias bulbife r

Batrisodes

denticollis

B. furcatus.

B. globosus

B. sp.

Bibloplectus sp.

Conoplectus

canaliculatus

C. susae

Custotych us sp.

D alm osella tenuis

D ecarth ron sp.

Euplectus duryi

E. jiliform is

E. sp.

Leptoplectus

pertenuis

M e lba parvula

M . sulcatula

M . th oracica

M . sp.

Pilopius sp.

Pycnoplectus

sexualis

P. inte rruptus

P. sp.

Rhe xius sch m im ’

R . substriatus

R . sp.

Tm esiph orus

carinatus

lbesiastes atratus

T. fossulatus

T. pum ilis

T. sp.

Trim iom elba dubia

Trim ioplectus

australis

lyrus sp.

6 I 0 0

0

0

I2

1

2

0

0

10

0

3

117 69 40 425

13 14 6 1

5 5 0 11

2 7 2 1

0 0 0 4

5 4 9 7

0 14 2 2

3 0 0 0

0 0

5 13

0 10

2 9

29 20

1 0

2 0 0 0

3 2 2 0

6 8 3 0

1 2 1 0

3 1 1 0

34 69 47 86

0

0

0

1

0

0

1

0

Table 5.-Summary data from Table 4

Summary

category

Site 1

(sapling)

Site 2

(group select)

Site 3

(shelterwood

Site 4

(control)

All

sites

Total

specimens 225 260 155 562 1232

species 17 19 16 17 28

Unique to site 0 1 0 4 5

150
Annotated Checklist of Selected Species

In addition to the broad questions of ecological interactions and community compositions that are addressed by

biodiversity studies, they also contribute a great deal of information to understanding the biologies and distributions of

individual species. Studies conducted in poorly surveyed regions inevitably produce records of previously unrecorded taxa

or change our perceptions of previously recorded, but poorly understood species. The following entries illustrate the novel

findings from the brief survey that was conducted between May and September 1993:

Coleoptera: Byturidae: Byturus unicolor, site 2 (group select), 25 May, two specimens. This is a new State record for the

species and family.

Coleqptera: Carabidae: Anillinus sp., site 2 (group select), 13 May, two specimens, 3 June, one specimen, site 4 (control),

25 May, one specimen. Several undescribed species were regarded by Carlton and Cox (1990) as potential

biogeographic indicators of relict faunas.

Coleoptera: Endomychidae: M ycetina pulch e lla, all localities, various dates. This is a new State record for the species.

Col&optera: Staphylinidae: M e galopinus sp., site 1 (sapling stand), 9 June, one specimen. This is a new state record for the

genus and subfamily Megalopsidiinae.

Hemiptera: Schizopteridae: Glyp?ocom bus saltutor, site 1 (sapling stand), 25 May, 15 specimens. This species was

presumed rare by Allen and Carlton (1989). The recovery of numerous specimens from an early succession habitat

\ suggests otherwise.

Lepidoptera: Nymphalidae: Speyeria d iana, site 2, 17 June, two males; site 3, 1 July, one male. This species is a candidate

species for threatened/endangered status (Anon. 1991). These are new records for the Ouachita National Forest.

CONCLUSIONS

Constraints

The major constraint to extracting meaningful data from arthropod biodiversity surveys is sorting and counting the

specimens, not collecting them. The taxonomic diversity represented in the samples and the difficulties of identifying many

of the taxa make it obvious that great selectivity must be exercised if data analysis is to be completed in a timely fashion.

The goal of the sampling effort should be to collect enough specimens through the season to adequately sample the

system, but not so many as to render identification and enumeration impractical. The goal of data analysis should be the

identification and enumeration of taxa to the highest level of identification possible, ideally to species. Even if many of the

species cannot be named,it may be possible to sort them to morphospecies. In cases where the precise identification of all

taxa is obviously impractical,priority should be given to taxa for which good identification keys or professional expertise are

available and/or those that are of obvious significance to the theoretical goals of the project.

Recommended Protocol and Survey Schedule

The following protocol was developed with the above constraints in mind and from the information gathered during this

preliminary study. In addition to the sorting/identification bottleneck in data analysis, factors that are considered include the

time required to service traps at each study site, distance between sites and site access, and the effect of service intervals

and different preservatives on specimen preservation.

Pitfall trapping is an effective method of capturing ground-active arthropods. A line of 10 traps is the minimum number

that should be used. An alternative to the use of separate trapping techniques for crawling and flying arthropods is to modify

the flight intercept traps by locating them in a trench with the tops flush with ground level. The trap thus created will serve

as an efficient flight intercept/pitfall combination. Also, non target small animals, such as shrews, mice, and various

amphibians, are more likely to escape from the troughs, with.their slanting sides, than they are from the steep-walled pitfall

cups (not to mention the toxic effects of the ethylene glycol in the latter). The volume of material from the Berlese samples

will depend on the number of funnels available to process the samples and frequency of sampling. Small samples can be

processed more thoroughly, but infrequent sampling intervals argue for larger samples, provided they do not sit around the

laboratory long enough to dry out prior to processing. Seasonality is not pronounced in most substrate species in the Southern

United States, so a monthly sampling frequency is probably adequate for annual surveys.

The combination flight intercept/malaise trap is the most important device for sampling flying insect diversity. The use

of a non-toxic preservative in the flight intercept portion such as saturated saline (NaCl) is necessary to prevent accidental

poisoning of animals and local contamination of the ground during spills and rain overflow. One-week service intervals are

too lengthy and should be reduced to no more than 3 days. Longer intervals not only affect the quality of preservation of

151
the specimens, but also bias the trap catch by attracting large numbers of carrion feeders to the slightly decayed insects. This

need for a short service interval affects the schedule of the entire sampling program, which is discussed below. A further

advantage of short service intervals is that it becomes unnecessary to use ethylene glycol in the collecting heads of the

malaise canopies. Ethyl alcohol (95%) gives much cleaner samples and is less troublesome to deal with during servicing.

Two traps per site, spaced at least 25 m apart and oriented at 90” angles to each other, are adequate.

The use of unbaited Lindgren traps as elevated flight intercept traps is a practical approach if used in sufficient numbers

and run contiuously. Numbers of insects produced weekly by a single trap are not impressive, but the diversity represented

is good, and, more importantly, there appears to be very little overlap in faunal compositions from the Lindgren traps and

the ground-based flight intercept/malaise traps. Five traps per site, perhaps raised to varying heights in the midstory and

canopy are recommended. Longer sampling intervals are allowed by the use of ethylene glycol in the collecting cups. Little

danger exists in using this chemical in the Lindgren traps because they are elevated and access to the collecting cups is

limited. ’

Timer-operated ultraviolet (UV) light traps have been used effectively by other investigators, but they proved consistently

unreliable during the course of this study. Certainly all remotely operated equipment should be rigorously tested prior to

being put to use. Since UV light trapping is strongly affected by weather, the phases of the moon, and other variables,

comparisons can only be made between study sites sampled simultaneously. Also, if Lepidoptera are being inventoried, they

should be hand collected at the light traps. Ideally, microlepidoptera must be mounted immediately following collection.

To adequately assess changes in the diversity patterns of arthropod faunas at several study sites and avoid the quagmire

of overcolIecting, a monthly sampling cycle is recommended. For 1 week during each month of the insect flight season

(MarchlNovember), the pitfall/flight intercept/malaise traps should be operated. The investigator should remain in the area

and visit each study site at 2- or 3-day intervals during the week. These traps should be deactivated at the end of the sample

week and reactivated 3 weeks later.

One large-volume Berlese sample should be collected at each site during the sample week. Berlese samples should be

collected at monthly intervals during winter as well. Substrate arthropod diversity is as high during these months as during

periods of surface and flight activity.

Light trapping should be conducted at some point in the week when weather conditions are optimal and reasonably

consistant at all sites. Large, powerful lights, such as mercury vapor lights, are not recommended because they will pull

insects from beyond the study areas.

Because of the low-volume recovery of unbaited Lindgren traps, they should be operated continously throughout the

collecting season. The degree of precision desired by the investigator in tracking seasonal activity patterns will determine

whether they need to be serviced between normal sampling weeks.

In summary, the scale of effort expended on the field portion of arthropod diversity research in long-term ecosystem

studies should be based on the availability of technical and professional personnel to process samples, rough sort taxa, and

conduct the laborious process of species identification, rather than the collector’s enthusiasm for collecting, though this is

a useful adjunct. Such a reality-based collecting protocol allows for a high degree of standardization among field sites,

provides sufficient time for sorting samples with even modest committment of personnel, and ensures that rapid, meaningful,

and statistically robust results will be generated by the project.

LITERATURE CITED

Allen, Robert T.; Carlton, C.E. 1989. New records of Ceratocombidae and Schizopteridae from Arkansas (Heteroptera:

Dipsocoromorpha). Journal of the Kansas Entomological Society. 62: 125- 126.

Anonymous. 1991. Proposed rules. Federal Register. 56 (225): 58,853.

Barbault, R.; Hochberg, M.E. 1992. Population and community level approaches to studying biodiversity in international

research programs. Acta Oecologia. 13: 137-146.

Carlton, Christopher E.; Chandler, Donald S. [In press]. Revision of the Nearctic genus Pseudactium (Coleoptera:

Pselaphidae). Coleopterists Bulletin.

Carlton, C.E.; Cox, Randel T. 1990. A new species of Arianops from central Arkansas and biogeographic implications of

the Interior Highlands Arianops species (Coleoptera: Pselaphidae). Coleopterists Bulletin. 44: 365-371.

Chandler, Donald S. 1987. Species richness and abundance of Pselaphidae (Coleoptera) in old-growth and 40-year-old

forests in New Hampshire. Canadian Journal of Zoology. 65: 608-615.

152
Collins, N.M.; Thomas, J.A., eds. 1989. The conservation of insects and their habitats.: New York, Academic Press.

Martin, William. C.; Boyce, Stephen G.; Echtemacht, Arthur C., eds. 1993. Biodiversity of the Southeastern United States.

Upland Terrestrial Communities. New York, John Wiley and Sons, Inc.

Newton, Alfred F., Jr.; Chandler, Donald S. 1989. World catalog of the genera of Pselaphidae (Coleoptera). Fieldiana

(Zoology) New Series. 53: l-93, + iv.

Raithel, Christopher. 1991. American burying beetle (iVicrqhonts americanus) recovery plan. Newton Comer, MA: U.S.

Department of Interior, Fish and Wildlife Service.

Solbrig, 0. T. 1991. The origin and function of biodiversity. Environment. 33: 16-20, 34-38.

Wilson, Edward O., ed. 1988. Biodiversity. Washington, DC: National Academy of Science Press.

153
Seed, Cone, Regeneration, and Defoliating Insects

in Forest Ecosystem Management’

Alex Mangini, Chris Carlton, Roger W. Perry, and James Hanula’

ABSTRACT

As part of the Phase II Ecosystem Management Research conducted on the Ouachita and Ozark

National Forests, the Arthropod and Microbial Communities Study Group completed two studies

in 1992: a survey of regeneration and defoliating insects and a study of seed bug damage to

shortleaf pine (Pinus echinatu Mill.) seeds. Pitfall traps collected two species of pine regeneration

, weevils, ffyiobius pales (Herbst) and Pachylobius picivorus (Germar). The primary defoliators

were katydids (Pterophyllu sp.). A total of 92 shortleaf pine seeds were collected from 22 stands.

Of the seeds collected, 40 were viable, 41 were empty, and 11 were damaged by seed bugs,

Leptogfossus corculus (Say) and Tetyra bipunctatu (Herrich-Schaffer). Studies initiated in 1993

include the effect of single-tree selection on insect infestation rates of white oak (Quercus alba L.)

acorns and the impact of coneworm and seed bug infestations on shortleaf pine seed yields in

Phase II stands.

INTRODUCTION

The Ecosystem Management Research on the Ouachita and Ozark National Forests is an ambitious program to assess

several silvicultural harvesting treatments. The goal is to determine the effects of the various harvesting methods on all

aspects of forest biology and use. The research included a study group originally known as the Insect and Disease Study

Group. During the past 2 years, as the group developed its research plans, it became apparent that the scope of the research

would include far more than insect pests and diseases. Consequently, the group renamed itself as the Arthropod and

Microbial Communities Study Group. This new name more accurately describes the broad and complex aspect of ecosystem

management that the group has undertaken.

Insects are major components of all forest ecosystems. Many of the pioneering studies of insect population dynamics

have concerned themselves with forest insects, for exaniple, epidemic outbreaks of the spruce budworm (Morris 1963).

Many forest insect species can undergo phenomenal population changes from generation to generation or from season to

season. It is not uncommon to see tenfold increases in population numbers for several generations followed by precipitous

declines over the following generations (Varley and others 1973). However, the real importance of insects in forest

ecosystems is due to the immense diversity of insect species and the role insects play in forest food webs, energy transfer,

pollination of plants, and decomposition processes (Wilson 1992).

This paper will be concerned with the insects that make their living in or on seeds, cones, and seedlings. Additionally, a

survey of defoliators will be discussed. The more general surveys of insect biodiversity are discussed separately (Carlton

and others 1994).

Entomological Background

Forest insects represent a wide array of species in all insect orders. A good general discussion of forest insects is given

by Drooz (1985). Insects that may play an important role in shaping forest communities are those that infest the seeds or

fruits of trees or seedlings. Both groups of insects may play ,a” important role in forest community dynamics.

Caterpillars of the genus Dioryctria attack and kill cones of conifers throughout the Northern Hemisphere. Commonly

called coneworms, the adults are small, gray or brown-orange moths with crossbands on the forewings. Four sympatric

species infest pines in the South: the southern pine coneworm, D. amatellu (Hulst); the blister coneworm, D. clurioralis

(Walker); the webbing coneworm, D. disclusa Heinrich; and the loblolly pine coneworm, D. merkeli Mutuura and Monroe.

Larval feeding destroys conelets and cones, making coneworms major pests in southern pine seed production areas (Ebel and

others 1980).

I Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

Z Entomologist, USDA Forest Service, Forest Health, Region 8, Pineville, LA 71360; Research associate, Department of

Entomology, University of Arkansas, Fayetteville, AR 72701; Wildlife biologist, USDA Forest Service, Southern Forest

Experiment Station, Hot Springs, AR 7 1902; Research entomologist, USDA Forest Service, Southeastern Forest Experiment

Station, Athens GA 30602, respectively.

154
In the South, two species of seed bugs significantly reduce pine seed yields: the leaffooted pine seed bug, Leptoglossus

corculus (Say), and the shieldbacked pine seed bug, Tetyra bipunctutu (Herrich-Schaffer). Both feed by inserting their

piercing-sucking mouthparts into the cones or conelets and sucking out the nutritious contents of the developing seeds.

Consequently, mature seeds appear normal but fail to germinate (Ebel and others 1980).

Hardwood seeds are subject to predation by a number of insects as well. Insects infesting acorns are of special concern

because oaks (Quercus spp.) make up a significant proportion of the hardwood component of southern forests and acorns are

an important source of food for a wide variety of wildlife species.

A great deal of work has been done on estimating the mast production of hardwoods, especially the oaks ( Bonner 1992,

Downs and McQuilken 1944, Sharp 1958, Sork and others 1993, Tryon and Carve11 1962). Several studies indicate that

acorn production varies from year to year and from tree to tree in a given year (Christisen and Kearby 1984, Sharp 1958,

Sork and others 1993). Consequently, loss of acorns to insects can be serious in years of poor acorn production. In one

study, insects were responsible for the loss of 30 percent of the acorn crop (Tryon and Carve11 1962).

Several species of weevils in the genera Curculio and Conotracheles reduce oak mast (Christisen and Kearby 1984,

Myers 1978). Species in both genera have similar life histories; adults lay eggs in the developing nuts, and the resulting

larvae feed on the contents of the seed, destroying it. Larvae leave the nut and pupate in the soil. Other insect species

infesting acorns are the acorn moth, Valentinia glandulella (Riley), and the filbertworm, Melissopus latiferreanus

(Walsingham). With these two species, as with the weevils, the immature stages feed within and destroy the nut (Myers

1978).

\ Regeneration insects are those that feed on seedlings and young trees. One of the primary hardwood regeneration

insects is the twig girdler, Oncideres cingulutu (Say). This species attacks most of the major hardwood species in the Eastern

and Southern States including oaks, hickories, and elms. The adults feed on the tender bark of small trees sometimes causing

heavy damage (Drooz 1985). Several weevils cause damage to young pine trees and seedlings. Two species of primary

importance in the South are the pales weevil, Hylobius pales (Herbst), and the pitcheating weevil, Pachylobius picivorus

(Germar). These weevils feed on the stems of small pines frequently killing them. Damage can be extensive in young

plantations and Christmas tree farms (Hunt and Raffa 1989, Rieske and Raffa 1993). These weevils breed in recently cut

stumps and stump roots and build up substantial populations after logging (Drooz 1985). Consequently, they may affect

natural regeneration following silvicultural treatments.

Studies Completed or Initiated

Regeneration Insects and Defoliators - 1992 Survey

The objective of this study was to survey Phase II control stands for pine regeneration weevils, defoliators and the twig

girdler. This survey was conducted in 1992 to determine the potential effects of insects on regeneration in the Phase II

treatment stands.

Seed Bug Damage to Shortleaf Pine Seeds - Phase I

This study consisted of a radiographic analysis of pine seeds collected in the Ouachita National Forest as part of the

Phase I research in 1992. The objectives were to obtain an estimate of damage to seeds of shortleaf pine, Pinus echinatu

Mill., caused by seed bugs and to compare radiographic analysis with the “cut test” as methods for the determination of

shortleaf pine seed viability.

Acorn Insects

This study was initiated in September 1993 to determine the effects of the Phase II single-tree selection treatment on the

rate of insect infestation in white oak (Quercus alba L.) acorns. A second objective will be to determine the effects of

canopy conditions or gaps on the rate of insect infestation in acorns.

Coneworm/Seed Bug Damage to Shortleaf Pine Seeds - Phase II

This study was initiated in October 1993 to survey coneworm and seed bug damage on shortleaf pines in or near selected

Phase II stands in the Ouachita National Forest. A second objective will be to determine the extent of seed bug damage to

shortleaf pine seeds collected from seedtraps placed in the Phase II treatment stands.

155
METHODS

Regeneration Insects and Defoliators - 1992 Survey

Pine Regeneration Weevil Survey

Turpentine/ethanol-baited pitfall traps described by Hunt and Raffa (1989) were used to collect pine regeneration

insects. Traps were modified slightly by suspending the bait vials from the lids using soft wire harnesses held in place by

passing the ends through holes in the lids and bending the ends outward. At each of the 4 study sites, 20 traps were placed at

approximately 6-m intervals and checked, cleaned, and rebaited weekly.

Weevils were kept live in cardboard mailing tubes or individually in small petri dishes for 5 days after collection to

check for parasitoid emergence. The weevils were then killed and preserved in 70 percent ethanol. Subsequently, they were

dried, identified, and sexed. Voucher specimens were pinned and deposited in the University of Arkansas Arthropod

Museum.

Defoliatoi Survey

Frass traps identical to those described by Haack and Blank (1991) were used with slight modification. Twenty-four

traps, divided equally between pine and hardwood canopies in groups of four, were placed at each site. Collections w ere

made weekly. Frass collections were combined for pine and hardwood samples for each site each week. The material was

air-dried for several days; then, no&ass debris was separated by hand and discarded. Frass was weighed to 0.1 mg, sorted,

and identified.

Mercury-vapor Light Traps

Mercury-vapor light traps were used to survey for twig girdlers although all insects captured in the traps were sorted

and identified. Light traps were rotated among the four sample sites during weekly trap runs if the weather was satisfactory.

Insects were collected into soapy water screened by 6.35 mm wire mesh to exclude large moths.

Study Sites

The study sites used control stands established for the Phase II research on the Ouachita and Ozark National Forests

(Baker 1993). Study-site numbers and locations were: Site 1 - Yell County, 4.8 km northeast of Blue Ball; Site 2 - Yell

County, 4.8 km northeast of Aly; Site 3 - Montgomery County, 12.8 km northeast of Glenwood; Site 4 - Polk County, 16 km

west of Mena.

Seed Bug Damage to Shortleaf Pine Seeds - Phase I

In 1992, seed traps were placed in six randomly selected plots per stand in 22 of the 25 Phase I pilot study stands

(clear-cut stands were excluded). At each plot, seed traps were placed at a distance of 6.7 m along azimuths of 0”, 120”, and

240” from the plot center. Seeds were collected twice per seedfall season (early December and late February/early March).

Seeds from all the traps in one plot were cornposited into one sample. Consequently, each stand produced six cornposited

samples. Seed samples were cleaned, sorted, and tallied.’ The seed samples were collected primarily to estimate

regeneration potential but also provided information on seed bug damage. Traditionally, seed bug damage is determined by

examination of radiographs (X-rays) of seeds (Bramlett and others 1977). Radiography allows determination of seed

viability, i.e. full (healthy), empty (aborted seeds or “pops”), or insect damaged. As part of the survey of seeds collected

from the Phase I plots, we compared the radiographic method of seed analysis with the “cut test” method of testing seed

viability. The cut test involves slicing the seed open with a knife to examine the condition of the seed contents.

3 Guldin, James M.; Shelton, Michael G.; Wittwer, Robert F. [and others]. 1993. Study plan: New Perspectives/Ecosystem

Management research on the Ouachita/Ozark National Forests: Phase II - Silviculture Research. 67~. Monticello, AR:

Southern Forest Experiment Station, Forestry Sciences Laboratory, administrative report 4 110 FS-SO-4 106-8 1 (problem 3).

156
Acorn Insects

A control4 and a single-tree selection treatment in the Phase II south zone, and a control and a single-tree selection in the

Phase II north zone (Baker 1994) of the Ouachita Mountains (Ouachita and Ozark National Forests) were selected to

determine insect infestation of acorns. All stands were primarily pine with a 60-80 year old hardwood component and were

previously unmanaged.

Twenty-five acorn traps consisting of a metal trash can with a 0.325-m diameter opening and a chicken-wire mesh top

were placed in each area. Each trap was placed under a separate tree unless 25 trees were not available, then several traps

were placed under a single tree. Trees were selected on the basis of acorn production determined by ground observations.

Only white oaks were selected due to their abundance in all stands. Traps were placed under the canopy of the tree midway

between the trunk and the canopy edge and in random orientation to the trunk. Trees used in single-tree selection stands were

located outside green belts and trees had been removed from at least one side of the canopy. Codominant trees were selected

because of their overall abundance in all areas and tendency to produce more acorns than subdominants and because

dominant oaks were rare or nonexistent in several stands. Acorn production in each tree was estimated visually from the

ground and recorded as low, medium, or high.

Samples will be collected every 2 weeks. For each sampling, traps will be checked and the acorns removed and placed

in labeled paper bags. Acorns will also be collected from the ground in a 1.0-m radius around the traps. Acorns collected

from the ground will be kept separately from trap-collected acorns. Differences in insect infestation rates between the

ground and trap-collected acorns will be determined, as well as infestation rates.

\ Basal areas of pines and hardwoods surrounding the selected trees will be estimated using a IO-basal area factor (BAF);

and canopy height of trees will be estimated using a metric clinometer to determine if infestation rates are related to canopy

conditions surrounding individual sample trees.

Coneworm/Seed Bug Damage to Shortleaf Pine Seeds - Phase II

The 10 wildlife/biodiversity stands in the Phase II south and east zones will be used for this study (Baker 1993). At each

stand, at least 25 mature, unopened cones of shortleaf pine will be collected. Trees that are readily accessible will be

sampled by one of two methods. When possible, an aerial lift truck belonging to the Ouachita Seed Orchard will be used to

get to the tops of the trees where most cones are located. The cones will be pulled by hand or clipped with pruning shears.

Based on the total number of shortleaf pines remaining in the stands, it may be necessary to collect from trees near, rather

than within, the stands. When access by the aerial lift truck is not possible, cones will be collected by shooting cone-bearing

branches from the tops of the trees with a 22-caliber rifle. Cones will be examined in the field for coneworm damage and

other damage.

Following field examination,cones will be returned to the Stuart Seed Orchard in the Catahoula Ranger District of the

Kisatchie National Forest, Pollock, LA,where they will be air-dried in open sheds for several weeks and then oven dried for

24 hr to open the cones. Seeds will be extracted, dewinged,and radiographed to determine the proportion damaged by seed

bugs. Estimates of seed bug damage in seeds collected will be compared with damage to shortleaf pine seeds collected

during the 1993-94 season from the seed traps placed in Phase II stands.

RESULTS AND DISCUSSION

Regeneration Insects and Defoliators - 1992 Survey

Pine Regeneration Weevil Survey

A total of 467 regeneration weevils were collected from the baited pitfall traps; 116 pales weevil (52 males, 64 females)

and 35 1 pitcheating weevil (137 males, 2 14 females). Some seasonal differences in weevil numbers were obvious including

a dramatic decline in weevil abundance in late August. Although only two species of Hylobiini were collected during this

survey, the possibility that other species are present cannot be discounted because distributional information is incomplete

for this area.

Other insects attracted to the turpentine/ethanol bait included several Drosophila spp., two specimens representing two

genera of Scolytidae, and large numbers of a single species of carpophiline Nitidulidae. Ground-dwelling arthropods that

entered the traps included carabid beetles (mainly Evarthrus spp.), centipedes, spiders, and crickets.

4 This control was not the previously established Phase II control stand. This new control stand was established near the

single-tree selection stand in order to more closely match stand and edaphic conditions.

157
On 20 July 1992, 15 hymenopterous parasitoid larvae emerged from a female P. picivorus. Unfortunately, all died

before pupation. These larvae were likely the braconid Microctonus pachylobii (Rieske and others 1989). No additional

parasitoids were recovered during the survey.

Baited pitfall traps proved excellent for the two weevils of primary concern. Given the effectiveness of the technique,

adequate sampling could probably be achieved using lines of 10 traps per site rather than 20, especially if the treatments are

replicated at least 3 times. If 10 traps are used, they could be spaced further apart reducing the time spent at each site and

lessening the possibility that the traps themselves might reduce local weevil populations. Since live insects are involved, the

weekly sampling schedule is desirable. Specimens should be kept alive between sample runs to monitor for parasitoid

emergence because this may be an important density-dependent control for weevil populations.

Defoliator Survey

Both pine and hardwood fiass samples were dominated by orthopteran frass, mainly from tettigoniids. Katydids

(Pterophyllu sp.), as large nymphs in July and as adults in August and September, were present in large numbers at all sites.

Second in abundance was a mixture of fine powdery frass and minute pellets.The powdery material was likely derived from

orthopteran pellets. A distant third in abundance was caterpillar frass. There were no obvious qualitative differences

between pine and hardwood samples.

Cross-contamination was a serious problem of this method of estimating relative defoliator abundance. It was difficult

to set up the traps in locations where drift from nontarget trees did not contaminate the samples. Deciduous frass samples

contained pine needles, and all the pine samples contained deciduous tree leaves. The pine samples also contained

substantial amounts of katydid f&s, which evidently drifted into the pine fiass traps. In a number of cases, katydids were

actually resting inside the pine frass traps. This is obviously a potential source of sample bias. The problem of

contamination from nontarget canopies will probably continue in the relatively closed canopies of the control plots but might

be reduced in treatment plots where trees are removed. To be more meaningful, deciduous trees should be sampled by

species or genera. However, in addition to the detailed sorting of the frass samples this will dramatically increase time and

personnel requirements.

Mercury-vapor Light Traps

Although no twig girdlers were collected during the’light-trap survey period, the occurrence of girdlers in northwest

Arkansas in October suggests that a brief period of sampling at the sites during this time might yield results.

Seed Bug Damage to Shortleaf Pine Seeds - Phase I

A total of 92 shortleaf pine seeds were collected from the seed traps in the 22 Phase I stands. This may seem to be a

small number of seeds; however, it must be remembered that the seed traps represent only a very small percentage of area in

which seeds are dispersed. Seeds were not expected to be collected in large numbers. Of the seeds collected, 40 were viable

(full), 4 1 were empty (pops) and 11 were classified as damaged (due to feeding by seed bugs).

Comparison of the two methods for determining seed viability-radiographic examination and the cut test-revealed that

the two methods yielded very similar results. Only two seeds were classified differently by the two methods. However, the

cut method does not provide information on the causes of seed damage.

Acorn Insects

Traps were placed in the study plots in late September 1993. At this time, two collections have been made. However,

inspection of the acorns for insect damage has not been completed.

Coneworms/Seed Bugs - Shortleaf Pine - Phase II

Cones will be collected during the week of 24 October 1993 so no data are presently available.

CONCLUSIONS

The frass sampling for defoliating insects was discontinued because of cross contamination between the pine and

hardwood traps and because it required large amounts of time and manpower to be done correctly. The pitfall traps will be

continued as a part of the arthropod biodiversity studies rather than as part of the seed, cone, and regeneration studies. The

158
collection of acorns in the single-tree selection stands and controls will be supplemented by acorns collected in seedfall traps

placed in all Phase II stands by the silviculture study group. All acorns collected will be inspected for insect damage.

Additionally, the shortleaf seeds collected in the seedfall traps will be radiographed for seed bug damage. It is hoped that

these collections and analyses can be conducted for the next several years in order to establish a detailed data base on insect

influences on natural forest regeneration.

159
LITERATURE CITATIONS

Baker, James. 1994. Overview of Phase 11 Stand-level Research. In: Pretreatment conditions and preliminary findings:

Proceedings of the symposium on ecosystem management research in the Ouachita Mountains; 1993 October 26-27; Hot

Springs, AR. New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station.

Bonner, F.T. 1992. Hardwood seed. In: Proceedings of the Southern Forest Nursery Association Conference; 1992 July

20-23; Callaway Gardens, Pine Mountain, GA. [place of publication unknown]: 67-90.

Bramlett, D.L.; DeBarr, G.L.; Yates, H.O., II1 [and others]. 1977. Cone analysis of southern pines - a guidebook. Gen. Tech.

Rep. SE:1 3. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station and

Southeastern Area, State and Private Forestry. 28 p.

Carlton, C.E.; Bollinger, J.; Thompson, L.C. 1994. Arthropod biodiversity-sampling protocol development. In: Pretreatment

conditions and preliminary fmdings: Proceedings of the symposium on ecosystem management research in the Ouachita

Mountains; 1993 October 26-27; Hot Springs, AR. New Orleans, LA: U.S. Department of Agriculture, Forest Service,

Southern Forest Experiment Station.

Christ&en, Donald M.; Kearby, William H. 1984. Mast measurement and production in Missouri (with special reference to

acorns). The Missouri Department of Conservation Terrestrial Series No. 13. Missouri Department of Conservation,

Jefferson City, MO. 36 p.

Downs, A.A.; McQuilken, W.E. 1944. Seed production of southern Appalachian oaks. Journal of Forestry. 42: 913-920.

Drooz, Arnold T., ed. 1985. Insects of eastern forests. Misc. Publ. 1426. Washington DC: U.S. Department of Agriculture,

Forest Service. 608 p.

Ebel, Bernard H.; Flavell, Thomas H.; Drake, Loyd E. [and others]. 1980. Seed and cone insects of southern pines. Gen.

Tech. Rep. SE-8. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station.

43 p.

Haack, R.A.; Blank, R.W. 1991. A simple ground-based trap for estimating densities of arboreal leaf-eating insects. Research

Note NC-354. Radnor, PA: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station.

Hunt, D.W.A.; Raffa, K.H. 1989. Attraction of Hylobius radicis and Pachyiobius picivorus (Coleoptera:Curculionidae) to

ethanol and turpentine in pitfall traps. Environmental Entomology. 18(3): 35 l-355.

Morris, R.F. 1963. The dynamics of epidemic spruce budworm populations. Memoirs of the Entomological Society of

Canada. 3 1: l-332.

Myers, Steven A. 1978. Insect impact on acorn production in Missouri. Columbia, MO: University of Missouri-Columbia.

246 p. Ph.D. thesis.

Rieske, L.K.; Hunt, D.W.A.; Raffa, K.F. 1989. Microctonus pachylobii (Hymenoptera:Braconidae) parasitizes Hylobius

weevils in Wisconsin: new host genus and geographic records. Entomological News. 100: 153-154.

Rieske, L.K.; Raffa, K.F. 1993. Potential use of baited pitfall traps in monitoring pine root weevil, Hylobius pales,

Pachylobius piscivorus, and Hylobius radicis (Coleoptera:Curculionidae) populations and infestation levels. Journal of

Economic Entomology. 86(2): 475-485.

Sharp, Ward M. 1958. Evaluating mast yields in the oaks. Bulletin 635. University Park, PA: Pennsylvania State University

College of Agriculture Agricultural Experiment Station. 22 p.

Sork, Victoria L.; Bramble, Judy; Sexton, Owen. 1993. Ecology of mast-fruiting in three species of North American

deciduous oaks. Ecology. 74(2): 528-541.

160
Tryon, E.H.; Carvell, K.L. 1962. Acorn production and damage. Bull. 466T. Morgantown, WV: West Virginia University

Agricultural Experiment Station; 18 p.

Varley, G.C.; Gradwell, G.R.; Hassell, M.P. 1973. Insect population ecology - an analytical approach. Berkeley,CA:

University of California Press. 212 p.

Wilson, Edward 0. 1992. The diversity of life. Cambridge, MA: Belknap Press of Harvard University Press. 424 p.

161
Southern Pine Beetle Risk Ratings’

Peter L. Lorio, Jr.’

ABSTRACT

A preliminary assessment of stand risk rating for the southern pine beetle (SPB), D e ndrocronus

frontalis Zimmermann, indicated that the 52 Phase II research stands range from medium

to high risk. The risk rating considers the relative susceptibility of trees and stands to

attack, the potential for SPB reproduction, and the potential loss of valuable resources.

An abundance of food and habitat, required to produce large SPB populations, is considered

paramount.

INTRODUCTION

The purpose of this paper is to describe the approach taken to assess the risk of loss to the southern pine beetle (SPB),

D e nd rocronus frontalis Zimmermarm, in 52 stands (pretreatment conditions), which are part of the Ecosystem Management

Research Phase II Program, and to present some preliminary results. Factors considered are (1) relative susceptibility or

resistance of stands to beetle attack, (2) the potential for SPB reproduction in those stands, and (3) the potential loss of valuable

resources in the event of successful attacks (Lorio 1978, Lorio and Sommers 1981, Lorio and others 1982). The approach

differs from hazard ratings based solely on the relative susceptibility of trees and stands to SPB attack or the combined considerarion

of tree susceptibility and SPB population level at some point in time (Paine and others 1984). Abundant food and habitat,

required to produce large SPB populations, is considered paramount.

METHODS

As indicated above, the assessment procedure used here includes factors apart from the relative susceptibility of trees

and stands to SPB attack. Also, because detailed plot and stand data were collected in connection with other objectives of

Phase II, those data are used instead of resource data contained in the Continuous Inventory of Stand Conditions (CISC) data

base (Lorio and Sommers 1981, Lorio and others 1982).

The approach involves procedures described in Lorio (1980) in which data are plotted on a stocking chart requiring only

average basal area per acre and number of trees per acre. This is similar to a widely used upland hardwoods chart (Gingrich

1967) to compare existing stand conditions with concepts of understocked, fully stocked, and overstocked stands. For convenience,

the chart used is one developed for loblolly pine, Pinus rueda L., by Westvaco Corporation, which was use d previously for

a similar purpose (Lorio 1980). Any number of other standards, such as Meyer (1942), Schumacher and Coile (1960), and

USDA FS (1976), could be useful for comparisons of actual stand densities with convenient points of reference. On the Westvaco

chart, lOO-percent stocking represents the average condition existing when the maximum number of well-spaced trees of a

given size occupy an acre of land without overcrowding. Full stocking may or may not mean optimum stocking, correct

stocking, or even adequate stocking for any specific product (Lorio 1980).

With the lack of an historical data base for SPB infestations on the Ouachita National Forest, stand densities and stocking

of stands at the points of origin of 217 infestations, which occurred in stands on the Kisatchie National Forest in Louisiana

from June 1975 through June 1977, are presented for comparison with existing stocking in Phase II stands.

RESULTS AND DISCUSSION

Data from two stands included in Phase II research were plotted to illustrate the approach being taken. Data for 14 plots

in stand 5, compartment 1658, are shown in figure 1 (pine and pine plus hardwoods 19.6 inches in d.b.h.) and in figure

2 for trees 13.6 inches in d.b.h. For clarity, only the 50- and lOO-percent stocking lines from the Westvaco stocking chart

are shown. Looking only at the overstory (fig. l), one sees quite a wide range in number of trees per acre, but quite uniform

’ Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

* Principal Research Forester, USDA Forest Service, Southern Forest Experiment Station, Pineville, LA 71360.

162
180

160

140

n

Q)

<‘; 120

(Y

5 100

a.

W

QL 80

a

: 60 v)

a

m

40

20

0

I I I I I

18 16 1 4 1 2

0 50 100 150 200 250

TREES PER ACR E

Figure l.- Stand density ami nkdiw? stocking of trees 2 9.6 inches in d b.h. in I4 plots within stand 5, 

1658, on the Ouachita NationalForest (pine, open circle s; pineplus hardwood,j2led

from Westvaco Corp. stock.@ chart). Here, and in all otherjigures, the labeled,

are quadratic mean diameters, and the dashed lines, labeled 50 and 100, are stocking percentages

extracted from the WesrVaco stocking chart (see L.&o 1980).
I I I I I I I I

I

L;;_.

I

8

164
tree diameters, both for pine only and for pine and hardwood combined, with stocking ranging from low to moderately high.

As expected, when the midstory trees are added to the data, average diameters range widely, generally decreasing, and stocking

levels are shifted upward.

Similar data are shown for stand 1, compartment 833, in figures 3 and 4. In the overstory (fig. 3), there is considerable

variation in stocking and average diameter, but average diameter is considerably larger than that found in stand 5, compartment

1658 (fig. 1). Similar data available for one SPB infestation are also plotted (square symbols). Lightning was apparently

associated with initiation of the infestation, but stocking was at the high end of the range for the sample plots. When data

are plotted for all trees 23.6 inches in d.b.h., several plots exceed lOO-percent stocking, and the range in d.b.h. is greatly

increased.

The average stocking for the 52 stands included in the Phase II study is shown in figure 5, in which, if one considers

only pines, stands do not appear to be excessively stocked. If the hardwood component is included, stocking level shifts toward

and over 100 percent. If hardwoods are ignored, one may get a misleading indication of competition for water, nutrients,

and space in stands typed as pure pine.

Figures 6 and 7 are provided to show the ranges of density and stocking found in 217 SPB-infested stands over a period

of 2 years in the Kisatchie National Forest in Louisiana. In figure 6, considering pines only, most stands exceed the loo-percent

stocking level, but there are many near SO-percent stocked, and more than a few less than 50-percent stocked. When the

hardwood component is added (fig. 7), the great majority of stands fall in the lOOpercent and over range, and the few below

50 percent are in the larger diameter classes.

it would be helpful to have a record of SPB infestations over time in the Guachita National Forest for which data could

be plotted as shown in figures 6 and 7. However, the density and stocking of the 52 Phase II stands shown in figure 5, especially

considering the pine-plus-hardwood data, does indicate a probability of high risk based on comparisons with data for SPB-infestations

on the Kisatchie National Forest (fig. 6 and 7). There are aspects other than assessment of stocking that support the probability.

For example, as stands mature, age and size of mature and overmature trees become increasingly important, and site quality

less so. Stands composed of such trees, but apparently only modestly stocked, may still provide considerable food and habitat

for the SPB. As trees age and their physiological state declines (e.g., root systems no longer meet the demands of crowns

for water and nutrients, and crowns supply less than adequate food to maintain root systems), not only does growth decline,

but secondary metabolism, which includes synthesis of oleoresin, also declines. Consequently, because oleoresin is a major

factor in pine resistance to beetle attack, tree resistance to attack decreases.

The average age of the 52 stands in the Phase II study is 61.5’ years, with a quite narrow distribution. Thirty-one stands

range between ages 60 and 70, and 17 range between 50 and 60, with three stands over age 70 and only one stand under

age 50. A similarly flat distribution exists for site index (height in feet at base age 50 years), which averages 62 and ranges

from 50 to 71. The mature ages of these stands, in spite of low productivity indicated by the site indices, combined with

the densities and stocking indicated in figure 5, suggest that in the absence of silvicultural treatment, SPB could become a

serious problem over the next 5 to 10 years. This would be especially true if these stands are representative of a large proportion

of the surrounding forest areas.

Considerable resource losses can accumulate from small infestations (less than 10 trees) in stands with characteristics

representative of those in the Phase II study, in stands of large, mature trees (Lorio 1984). In addition, such trees are capable

of producing large SPB populations and likely serve as refuges in which SPB reproduce during endemic periods (low populations).

Based on this preliminary assessment of risk rating for the SPB, it appears that the 52 Phase II research stands range

from medium to high risk of losses and production of SPB populations. It is not possible to predict when and where infestations

will occur, and many biological and abiotic factors not considered here may limit the potential for SPB activity in the Ouachita

Mountains.

ACKNOWLEDGMENTS

Sincere appreciation is extended to Tim Mersmann, USDA Forest Service, Guachita National Forest, for guidance, assistance,

and orientation concerning the Ecosystem Management Research Program. James M. Guldin, USDA Forest Service, Southern

Forest Experiment Station, provided guidance and data in the form of computer files for the Phase II research stands without

which even this very preliminary assessment would have been impossible.

165
180

160

140

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40

20

I I I I I I

18 16 14 1 2 1 0

t-b I I I I I I

0

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50 100 150 200 250 300

TREES PER ACRE

Figure 3.- Stand density and relative stocking of trees 2 9.6 inches in d. b. h. in 14 pl&s within stand 1, compartment

833, on the Ouachita National Forest @ine, open circles; pine plus hardwood, filled circles). Note the density

and stoaking (square symbols) at the origin of an SPB infestation.
180 I

1 6 0

z 14 0

k 12 0

E

:: 100

N

a 8 0

a 6 0

3

a 4 0

m

2 0

0 1

0 100 200 3 0 0 4 0 0 5 0 0 6 0 0

I I I I

I

TREES PER ACRE

Figure 4.- Stand &n&y and relative stocking of trees 23.6 inches in d. b. h. in 14 plots within stand 1, compartment

833, on the Ouachita National Forest @ine, open circles; pine plus hardwood, filled circles). Note the dknsity

and stocking (square symbols) at the origin of an SPB i@kstation.
168
0 0

0 00

0 9 08

0 1

l0 I

01 0

0: 0 0

\

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(e-&+4) V3tlV 1VSVEl

169
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170
LITERATURJZ CITATIONS

Gingrich, SF. 1967. Measuring and evaluating stocking and stand density in upland hardwood forests in the central

states. Forest Science. 13: 38-53.

Lorio, P.L., Jr. 1978. Developing stand risk classes for the southern pine beetle. Res. Pap. SO-144. New Orleans, LA:

U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station. 9 p.

Lorio, P.L., Jr. 1980. Loblolly pine stocking levels affect potential for southern pine beetle infestation. Southern Journal

of Applied Forestry. 4: 162-165.

Lorio, P.L., Jr. 1984. Should small infestations of southern pine beetle receive control priority? Southern Journal of

Applied Forestry. 8: 201-204.

Lorio, P.L., Jr.; Mason, G.N.; Autry, G.L. 1982. Stand risk rating for the southern pine beetle: integrating pest

management with forest management. Journal of Forestry. 80: 212-214.

Lorio, P.L., Jr.; Sommers, R.A. 1981. Use of available resource data to rate stands for southern pine beetle risk. In:

Hedden, Roy L.; Barras, Stanley J.; Coster, Jack E., tech. coords. Hazard-rating systems in forest pest management:

\ Proceedings symposium. Gen. Tech. Rep. WO-27. Washington, DC: U.S. Department of Agriculture: 75-78.

Meyer, W.H. 1942. Yield of even-aged stands of loblolly pine in northern Louisiana. Yale University School of Forestry

Bull. 51. New Haven, CT: Yale University School of Forestry. 39 p.

Paine, T.D.; Stephen, F.M.; Taha, H.A. 1984. Conceptual model of infestation probability based on bark beetle

abundance and host tree susceptibility. Environmental Entomology. 13 : 6 19-624.

Schumacher, F.X.; Coile, T.S. 1960. Growth and yields of natural stands of the southern pines. Durham, NC: T. S.

Coile, Inc. 115 p.

U.S. Department of Agriculture. 1976. Volume, yield, and stand tables for second-growth southern pines. Misc. Publ.

WO-50. Washington, DC: U.S. Department of Agriculture. 202 p.

171
Crow n Health of O ve rstory Hardwoods ’

Dale A. Starkey ’

ABSTRACT

Monitoring the health of reserve hardwood trees is being performed as part of

the Ecosystem Management Research Project for shortleaf pine-oak forest types on

the Ouachita and Ozark National Forests in Arkansas. Results will provide

information about the success of retaining such trees and to provide guidelines for

selecting reserve trees in future operational harvests. Reserve trees are mostly 10

to 12 inch d.b.h. codominant and intermediate oaks. A suite of crown measurements

(diameter, live crown ratio, density, dieback, and foliage transparency) is being used

to detect significant changes in reserve tree health over time. Average ratings for

these indicators before harvest appear to be within normal ranges for each species.

Immediately after harvest, 16 to 62 percent of reserve trees had logging injury to the

base, crown, or both. Injury frequency generally increased with the intensity of

harvest cutting. Most injury was judged slight or moderate in severity.

INTRODUCTION

The Ecosystem Management Research Project in the Ouachita Mountains is being conducted to investigate the utility

of a wide range of silvicultural practices in meeting a variety of ecosystem management goals for the Ouachita and Ozark-St.

Francis National Forests. A complete description of the project can be found in Guldin and others (1994) and Baker and

others (1991). In about half of the harvest treatments, overstory and midstory hardwoods are being retained in order to meet

ecosystem management objectives such as improved wildlife habitat, greater biodiversity, reduced visual impact of harvesting,

and perpetuation of the pine-hardwood forest type. These treatments are (and hereafter referred to as): low impact single-tree

selection (LISTS), pine-hardwood single-tree selection (PHSTS), pine-hardwood group selection (PHGS), pine-hardwood

shelterwood (PHSW), pine-hardwood seed-tree (PHST), clearcut (CC), control, i.e. uncut (CONT).

Retained trees generally meet the recently proposed definition of “reserve trees” (Society of American Foresters 1993)

for the clearcutting, seed-tree, shelterwood, or coppice regeneration methods. Reserve trees are defined as pole-sized or

larger and are retained after the regeneration period. Retained trees within groups in the group selection treatments of this

study may also fit the definition of reserve trees because they will be retained after the regeneration period. However, in

the single-tree selection treatments, trees retained in this study cannot truly be considererl reserve trees; they are more

appropriately considered as a normal component of the pine-hardwood forest types being studied in this project. Nonetheless,

it seems expedient when describing this study to use the term “reserve trees” throughout.

The health and longevity of reserve trees are important if ecosystem management objectives are to be realized. In

addition, information about the health and fate of these trees can be used to develop guidelines for the selection of reserve

trees in future operational harvests under an ecosystem management regime. This portion of the ecosystem management

research project was implemented to monitor changes in crown condition and health of hardwood reserve trees.

The major concern for the health and fate of reserve hardwoods is due to oak (Quercus spp.) or hardwood decline

(Starkey and others 1989, Wargo and others 1983). Decline can generally be described as a complex disease syndrome

resulting from the interaction of a variety of host, site, and stand factors with biotic and ahiotic agents and stress factors.

It is expressed by a progressive dieback of the crown from the upper and outer portions downward, usually resulting in

mortality. Manion (1991) describes decline as “an interaction of interchangeable, specifically ordered abiotic and biotic

’ Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment Conditions

and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

’ Plant Pathologist, USDA Forest Service, Southern Region, Forest Health, Pineville, LA 71360.

172
factors to produce a gradual general deterioration,

often ending in death of trees”; decline is depicted

as a spiral of one or more predisposing factors,

followed by one or more inciting factors, which

are then followed by one or more contributing

factors. Figure 1 displays some of the factors that

can be responsible for decline according to their

type* i.e. abiotic, biotic, site/stand, or

anthropogenic. Figure 2 shows these same factors

in categories reflecting the sequence and function

in the decline syndrome of host trees. Most

reports of decline occurrences in the Eastern

United States (Millers and others 1989, Starkey

and ’ others 1989) attribute decline to climatic

events and stand/site factors (predisposing),

defoliation, drought, or frost (inciting); and root

rots and borers (contributing). In the ecosystem

management study stands, the factors most likely

to he operative are stand/site factors

(predisposing), stand disturbance from harvesting

(inciting), and root rot/borers (contributing).

METHODS

The silviculture research plots were used as

the basic sampling units for this part of the study

(Guldin and others 1994). At each of the 14 plots

install4 in each study stand, 3 to 5 of the largest

and nearest hardwoods were identified for

monitoring. These constituted the trees most

likely to be d&gnat& as reserves during marking

and harvesting operations. Preference was given

to trees already marked as reserves, to oaks of any

species, hickories (CLWJW spp.), and finally, other

hardwoods.

Azimuth and distance from plot center were

rtiorded for each tree as well as species and

d.h.h. (diameter at breast height). A suite of

crown measurements was utilized to describe the

current condition (i.e. health) of tree crowns--a

procedure currently being used in the National

Forest Health Monitoring Program (USDA Forest

Service 1992). The suite consists of six

measurements (tahle I), each requiring two crew

members to acquire. Crown diameter was

lllcdSllJld on two axes at 90” to one another by

Abiotic Factors Biotic Factors

Cllmatk trends or past events Borers Drought

Frost \ ~~i??~,

Oak

Decline

Site/stand Factors DenswcumDetltion \

~

physk&glcaiage

I

SolI deptWtexture/fertllHy Anthropogenic Factors

w-s Alr pollution

Topography Stand diaturbancw

Figure l.--Causal factors of oak decline organized by type.

Predisposing Factors

Atr potlution

_

Ctimatlc trends or paat events

Denanv/eonlnetttbfl

Ph y sloiO glcai age

Sdl depth/textura/fertlllty Inciting Factors spedes/genotypes Topography Drought

Defollatlon

1 :: dtsturbanca

Oak r(

Decline

 Contributing Factors

Borers

Canker fungl

Root rot fungl

Figure 2.--Causal factors of oak decline organized by their function

in the decline syndrome.

prolecting the crown perimeter onto the ground. The other five indicators were each visually estimated by two observers

standing on opposite sides of the tree about one-half to one tree length away. Estimates are made by each crew member,

and a concensus or average of both is used as the final estimate.

In addition, a damage coding system (table 2) was used for describing obvious damages due to physical in.jury, insect

or disease problems; particularly those that may not influence the crown indicators described above. Up to three damages

par trtx could he recorded along with the location and probable cause of the damage.

173
Table l.--Crown h e alth indicators for m onitoring reserve h ardw ood trees

Indicator

Crown diameter

Definition and units

Measured on ground in 2 directions at 90” ; in feet to the nearest foot; average of

measurements.

Crown position

Live crown ratio

Crown density

Standard forestry definitions; dominant, codominant, intermediate, or suppressed.

Ratio (in percent) of live crown length to total tree height; visually estimated in S-percent increments.

Estimated percentage of foliage, twigs, branches, and reproductive structures blocking light through the

crown; visually estimated in Spercent increments.

Crown dicback Estimated percentage of recent dieback (tine twigs remaining) in upper and outer portions of the crown compared to entire

crown; visually estimated in S-percent increments.

Foliage transparency Estimated percentage of light being transmitted through the foliated portions of the crown; visually estimated in S-percent

increments.

Table 2--Obvious dam ages recorded for reserve trees selected for m onitoring

Code Definition

Conditions that can occur in multiple locations:

0 0

01

02

03

04

OS

06

07

OX

OY

IO

II

12

None

Dead (describes part of a living tree)

Open wound; (>4.0 square inches, inner wood exposed)

Closed wound; healed, cankers; lesions (inner wood not exposed)

Small holes or pinholes (>0.5 inch diameter; e.g., bark beetle attack/emergence holes)

Broken

Removed; missing (other than defoliation by insects; branches of foliage (i.e. pruning)

Rotten branch stubs; excessive swelling at base of dead branches

Rcsinosis; bleeding

Deformed, twisted, curled (woody stems only)

Galls (abnormal swellings on main stem or branches)

Imhedded foreign objects (nail, fence, etc.)

Other than described above (needs explanation in notes)

Conditions that occur on trunk only:

20 Crook or sweep (severe enough to impede growth or affect survival)

21 Crack of seam

22 Swelling (greater than one-half diameter of tree above the swelling)

23 Leaning (from partial windthrow or root spring)

24 Ahundancr of epicormic branches or water sprouts on trunk or base

174
Table 2--Obvious damages recorded for reserve trees selected for monitoring (continued)

Code Definition

Conditions that occur on branches only:

40 Excessive branching (indicator of past injury such as top kill)

41 Abundance of seeds or cones (may cause dieback)

42, Stunted, dwarfed (woody stems only, short internodes, chlorotic dwarfs)

Conditions that occur on foliage only:

60

61

62 Pale-green foliage ( > 30 percent of the crown with leaves having > 50 percent of foliage affected)

63 Yellow-green foliage ( > 30 percent of the crown with leaves having > 50 percent of foliage affected)

64 Leaves spotted (> 30 percent of the crown with leaves having > 50 percent of foliage affected)

\ 65 Damaged leaves (> 30 percent of the crown with foliage shredded, with holes, or otherwise mechanically damaged)

66 Distorted foliage (>30 percent of the crown with wrinkled, shrivelled, galled, or otherwise distorted leaves)

67 Stunted foliage (>30 percent of the crown with stunted or dwarfed foliage, less than one-half normal size)

Defoliation (from insect feeding)

General discoloration (mixed colors; >30 percent of the crown with leaves having >50 percent of foliage affected; includes

necrotic foliage)

Location codes:

Crown stem (main trunk or bole within the crown)

Upper bole (upper half of the trunk between roots and crown)

Lower bole (lower half of the trunk between roots and crown)

Roots (exposed) and stump (12 inches in height)

Whole trunk (includes codes 1 to 4)

Branches (woody stems other then the main stem)

Buds and shoots (the most recent year’s growth)

Foliage

Whole crown (includes codes 6 to 8)

Probable cause:

100

200

300

400

500

600

700

800

900

999

IllSC%C1

Disease

Fire

Animal

Weather

Plant competition/suppression

Logging and related; human damage

Unknown

True mistletoe

Other than described above; needs explanation in notes

Up to 3 damages can be coded per tree

Crown health and damage data were collected in conjunction with all other silvicultual data collection. Silviculture field

crews were trained to collect crown health and damage data during a l-day session. Classroom training and field practice

were followed by field testing and evaluation in order to meet quality assurance goals (USDA Forest Service 1992). For

all visual crown indicators, a goal of f 10 percent (i.e. two 5 percent classes, see table l), 90 percent of the time, (when

compared to estimates of the trainers) was used. For crown diameter, average diameter was required to be f 10 percent

of the trainers result, 90 percent of the time. For the damage indicator, obvious damage was required to be correctly

recorded 90 percent of the time.

175
Because logging injury was likely to occur on some reserve trees, a survey of a portion of harvest& stands was

conducted soon after logging was completed. Two stands of each treatment were visited, and reserve trees on five to six

plots in the treated area (plots 1 to 12) examined. Logging injury was recorded as either crown or basal, and rated slight,

moderate, or severe (table 3).

Table 3.--Logging damage severity m ting used in posth arvest tree evaluation

Intensity Basal Injury Crown Injury

Sligh t Open wound <20 percent of circumference One broken limb, not the top

Moderate Open wound 20 to 40 percent of circumference Two broken limbs, not the the top

Severe Open wound >40 percent of circumference Three broken limbs, or top broken out

Dead N/A Tree broken off mid-bole or knocked over. Severe enough to preclude any

recovery

Future evaluations of reserve trees are planned 2 and 4 years after harvesting (1995 and 1997) in conjunction with

silviculture plot remeasurements (Guldin and others 1994). Significant changes in tree health should be reflected in large

changes in one or more crown indicators.

RESULTS AND DISCUSSION

The sample population consisted mostly of

oaks (about 84 percent, fig. 3). Hickories and all

other species comprised 8 percent each. The

proportion of oaks, hickories, and other species

varied somewhat among treatments, but the oak

component was always above 75 percent and

populations were quite similar (fig.4). White (Q.

rrlbn L.) and post oak (Q. stellata Wangenh.) were

the most prevalent among oaks in all treatments

(fig. 5), ranging from 62 to 93 percent. Black oak

(Q. velutirla Lam.), southern red oak (Q. falcata

Michx.), northern red oak (Q. rubra L.), and

blackjack oak (Q. marilandica Muenchh.)

comprised I I, 6, 5, and 2 percent, respectively,

overall; in only one treatment was any of these

over 20 percent (group selection, 23 percent for

black oak).

Most trees were in either codominant or

intermediate crown positions (fig. 6; 40 and 54

percent, respectively, overall). Northern red oak

had the highest proportion of dominant trees (9

POStOSkS

32.7%

whItoosks

31.4%

08ks Black oaks

10.9% 9.9%

Figure 3.4am plepopulation of reserve h ardw oods m onitore dfor tre e

h e alth ch anges.

percent) and, along with southern red oak, the highest proportion of codominant trees (58 and 64 percent, respectively).

B/a&jack oak and hickory had the highest proportions of intermediate and suppressed crown classes. Average d.b.h. varied

only slightly among species and ranged from 10 to 12 inches (fig. 7).

176
Crown health indicators varied

somewhat by species but were similar to

those collected in other areas of the South

(Bechtold and others 1992; fig. 8).

Crown diameters averaged 22 to 29 feet,

live crown ratios, 47 to 60 percent,

crown density, 48 to 61 percent, dieback,

2 to 6 percent, and foliage transparency,

12 to 16 percent. Differences between

species are probably not significant in

terms of tree health. They just reflect

species differences.

‘Obvious damage was coded on 80

percent or more of trees of each species

(fig. 9). Trees with two or more

dainages comprised less than 10 percent

of trees of each species except in one

case (post oak). In most cases, damage

was not significantly impacting tree health

at the time of evaluation, but the damage

‘may contribute to decline in tree health in

the future.

100%

80%

60%

40%

20%

0%

MaOthers

rHi&ories

OOaks

LISTS PHSTS PHGS PHSW PHST CC CONT ALL

Harvest Treatments

For code explanations see text In Introduction.

Logging in-jury after harvesting was

common (fig. 10). Overall, 38 percent

of trees had basal damage, crown

damage, or both. Crown damage was the

most prevalent overall, but basal injury

was most prevalent in the shelterwood

and single-tree selection treatments where

the number of reserve hardwoods was

highest. Crown in.jury was usually

judged slight (62 percent; fig. 11) while

basal in.juries were more evenly divided

among slight (42 percent) and moderate

(53 percent). Four percent of crown

in.juries were so severe that form was

totally destroy& or mortality was the

likely result. Logging injury generally

increased in frequency as the intensity of

tree harvest increased (fig. 10).

Figure 4.- -Sam ple population of reserve h ardw ood trees by species and

treatm ent.

@lackja& oak

rN. red oak

OS. red oak

mSlack oak

-Postoak

oWhite oak

These preharvest crown health

measurements and post-harvest logging

injury assessments provide baseline data

to which future crown and tree damage

measurements can be compared. After

all harvest and site-preparation work is

completed, reserve tree conditions will

probably change and then stabilize with

time. Future evaluations of these trees

100%

80%

60%

40%

20%

0%

LISTS PHSTS PHGS PHSW PH.53 CC CONT ALL

Harvest Treatment

For codes explanations see text In Introduction.

Figure S.- -Sam ple population of reserve oak s by species and treatm ent.

will provide valuable information about the contributions of reserve trees to ecosystem management objectives and provide

data for the development of guidelines for selecting reserve trees in future harvests.

177
60% osuppressad

ml-i

mCodominant

40% 0Dominam

Species

WHO-whii oak, PSOqost oak, BLO-black oak, SRO-s. red oak,

NRO- n. red oak, BJO-blackjack oak, HIClhkhy, and OTH-other.

‘igure 6.- - Pe rcentage of reserve h ardw oods by crow n position and species.

.- oWhite oak

-post oak

IEBlack oak

OS. red oak

IN. red oak

mBlackjack oak

aHickory

-Other

Species

_._ ,__., . .

Figure 7.--Ave rage diam ete r at breast h eigh t (d.b.h .) of reserve trees oy speczes.

178
0whne oak

-Post oak

oBiackoak

~rS. redoak

IN. red oak

mBla&jackoak

E43HlCkOrY

mothers

Diameter

met)

Fiat10

(per=w

Transparency

(perf=t)

Crown Indicators (units)

Figure 8.--Ave rage crow n-indicator m tings for reserve h ardw oods by species.

r

20%

I

0%

WHO PSO BLO SRO - NRO BJO HIC OTH

WHO-white oak, PSO=post oak, ELO=Ma& oak, SAO=s. red oak,

NRO-n. red oak, BJO=Mackjack oak, HIC-hiiory, and OTH-other.

dhree

OTWO

lone

Figure 9 .- - Pe rcentage of reserve trees with one, two, or three damages by species.

179
60-

50-

40-

30-

20-

10 -

oLISTS PHSTS PHGS PHSW PHST AU

Harvest Treatment

For codes explanations see text in introduction.

_^ - . ^ .,.* . Fgure lo.--Yroportion of reserve trees wltn toggmg injury by location and treatment.

wm

41.7% WJM

61.8%

,fl-\., ,,/-----~.

,/’

‘.\

,/

‘1 / .\\

Brok e n

3.6% TE!iy.

w.i&

20.0%

BASAL CROWN

Figure Il.--Proportion of reserve trees with logging injury by location and severity.

180
LITERATURE CITED

Baker, J.E. 1991. Study plan: New perspectives research and forest management on the Ouachita/Ozark National Forests.

FS-SO-4106-81. Monticello, AR: U.S. Department of Agriculture, Forest Service, South e rn Forest Experiment Station.

31 p.

Bechtold, William A.; Hoffard, William H.; Anderson, Robert L. 1992. Summary report: Forest health monitoring in the

South, 1991. Gen. Tech. Rep. SE-81. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern

Forest Experiment Station. 40 p.

Guldin, James, M.; Baker, James B.; Shelton, Michael G. 1994. Pretreatment conditions in mature pine/hardwood stands

dn south-facing slopes of the Ouachita/Ozark National Forests: midstory and overstory plants. In: Proceedings of the

Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment Conditions and Preliminary

Findings. 1993 October 26-27; Hot Springs, AR. New OrIeans, LA: U.S. Department of Agriculture, Forest Service,

‘Southern Forest Experiment Station.

Manion, P.D. 1991. Tree disease concepts. Prentice-Hall, Inc. Englewood Cliffs, NJ. 399 p.

Millers, I; Shriner, D.S.; Rizzo, D. 1989. History of hardwood decline in the eastern United States. Gen. Tech. Rep.

’ NE-126. Broomall, PA: U.S. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station; 75

PSociety of American Foresters. 1993. Silviculture Terminology - September 1993. SilvicultureWorkingGroupNewsldter

(D-2). October 1993. Bethesda, MD: Society of American Foresters. 4 p.

Starkey, Dale A.; Oak, Steven W.; Ryan, George W.; and others. 1989. Evaluation of oak decline areas in the South.

Protection Rep. RS-PR17. Atlanta, GA: U.S. Department of Agriculture, Forest Service, Southern Region. 36 p.

USDA Forest Service. 1992. Forest health monitoring field methods guide (eastern guide). Research Triangle Park, NC:

U.S. Department of Agriculture, Forest Service, Forest Health Monitoring Program.

Wargo, P.M.; Houston, D.R.; LeMadeleine, L.A. 1983, Oak decline. Forest Insect and Disease Leaflet 165. Washington,

DC: U.S. Department of Agriculture, Forest Service. 8 p.

181
Woody Debris Dynamics in Zero Order Streams

of the Ouachita National Forest: Preliminary Findings’

Wm. Patrick Fowl&

ABSTRACT

The importance of woody debris within zero order stream channels of the Ouachita

National Forest is unclear. Basic processes of recruitment, occurrence and movement

of woody debris are largely unexplored. The occurrence and abundance of woody debris

dams may prove to be a useful indicator for aquatic macroinvertebrate habitat. If so,

woody debris may be used as an indirect biological indicator for the ephemeral portions

of aquatic ecosystems. This study was conducted to map the location and estimate the

biomass of woody debris in forested ephemeral channels. The effects of reproductive

timber harvest methods on these debris dams are estimated by remeasurement of the

location and biomass of the debris. Ratios of debris dams per 1OOm are determined and

will be compared for untreated and treated drainages. Additionally, the basic processes

of recruitment and movement are examined.

\

INTRODUCTION

Woody debris plays an important role in channel formation and function of aquatic ecosystems (Bilby and Likens 1980,

Galay 1983, Harmon and others 1986, He&e 1985, Keller and Swanson 1979, Potts and Anderson 1990). Some of the

functions of woody debris include instream structure to dissipate flow energy, detain sediment, and provide refugia for fish.

Plus, woody debris is a nutrient source/sink, as well as habitat for benthics.

Knowledge of the function of woody debris in the aquatic ecosystems of southeastern watersheds is lacking (Hedman

and Van Lear 1991). In particular, the functions of woody debris in the aquatic ecosystems of the Arkansas highlands are

largely unexplored. The occurrence and abundance of woody debris dams may prove to be a useful indicator for

macroinvertabrate habitat and therefore useful as an indirect biological indicator for the ephemeral portions of these aquatic

ecosystems.

Additionally, the effects, if any, of forest management activities on this debris have yet to be fully quantified or

understood.’ Traditional methods of studying direct and indirect effects of forest activities upon aquatic ecosystems have

focused on water flow and water chemistry studies. These studies are expensive, require long timespans for results, and

do not allow for assessment of biophysical stream characteristics. Therefore, in this study the use of small woody debris

and detritus to assess potential effects of forest activities on the biological component of streams is examined. Accordingly,

biomass is estimated and locations are mapped for woody debris in forested ephemeral channels. Furthermore, the effect

of reproductive cutting methods on these debris dams will be estimated by remeasurement of the location and biomass of

the debris.

‘Paper presented at the Symposium on Ecosystem Managemnt Research in the Ouachita Mountains:

Pretreatment Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

* Research hydrologist, Oxford Hydrology Laboratory, Oxford, MS 38655, USDA Forest Service,

Southern Station.

3 Studies by Golladay and Webster (1988) and Golladay, Webster, Benfield, and Swank (1992) at Coweeta,

North Carolina showed decreases in organic debris dams after clearcutting .

182
SCOPE

Five reproductive cutting methods and a control are applied to the study areas. They are: clearcut, shelterwood,

seedtree, group selection, single-tree selection, and uncut. These treatments occur on 52 stands of approximately 16ha each.

Ephemeral zero order drains occur within these stands. While small in nature, these streams may reflect direct and indirect

impacts resulting from silvicultural activities.

Objectives

The objectives of the study are:

(1) to describe the natural occurrence of debris dams in small ephemeral channels.

(2) ’ to track the movement of woody debris in small ephemeral channels.

(3) to determine the effects, if any, of various silvicultural treatments on the presence and movement of woody debris

in small ephemeral channels.

Methods

Drainages and local controls within the units were surveyed to identify small woody debris locations and estimate the

amount of woody debris. An arbitrarily selected zero station is established at the beginning of each channel survey. This

station is marked O+OOO. Then the 100-m tape is extended along the thalweg. Each 100 meters a station is designated by

a wooden stake marked with the station number (e.g., 1 +OOO). Each woody debris dam occurrence is flagged, and the

distance to the nearest tenth of a meter is noted on the flagging and recorded on the data form. For example, if a debris

dam occurred at 78.3m the distance of 0+783 is recorded on both the flagging and the data form.

Debris Typing

Next, these debris dams are typed in one of the following categories:

1 = Large woody debris, full

2 = Large woody debris, partial

3 = Small woody debris, full

4 = Small woody debris, partial

5 = Detritus, full

6 = Detritus, partial

7 = Slash, full

8 = Slash, partial

Characteristics of the variuos types of debris dans are: large woody debris is 15 cm or greater in diameter, small woody

debris is less than 15 cm in diameter, detritus is comprised of leaves and needles, and slash is recently deposited tree tops

resulting from blowdown or harvest. If a debris dam occupies 70 percent or more of the channel width, then it is classified

as a full dam. If it occupies less than 70 percent of the channel width, it is classified as a partial dam.

Biomass Estimate

Biomass was determined by adapting Brown’s (1974) techniques for estimating downed woody material to the woody

debris. Biomass is estimated by measuring, to the nearest tenthof a meter, the length of the debris across the channel. The

width of the debris is measured at the midpoint of the debris dam, and the height of the debris is also taken at the midpoint

of the dam but on the downstream side. These measurements are then recorded. Drainages are to be resurveyed annually

for 3 years after the treatment.

PRELIMINARY FINDINGS

Initial measurements were taken in the fall of 1992. The harvesting occurred during the summer of 1993. The first

remeasurements were taken in the fall of 1993. While it is premature to ascertain the effects of forest management activities

upon woody debris, it is possible to characterize debris occurrence on the study sites.

183
The overall distribution of debris dam types is

presemedinFigure1. Ascanbeseeninthis

figure, small woody debris and detritus are 1

more common than either large woody debris

or slash. Preliminary characterization of debris

occurrences is listed in table 1. by drainage,

frequency per lOOm, and estimated biomass

per 1OOm. Twenty-seven xero order drainages

were surveyed. A total length of 8778m of

drainages were surveyed and 2399 debris

dams were counted. Debris-dam frequency

appears to be a relatively consistent parameter.

An average of approximately 26 debris

dams per 1OOm were encountered in zero

order drainages of the study areas. Both the

Cold Water Creek and Gaffords Creek study

areas averaged approximately 30 debris dams

per 1OOm. Both Harvey Creek and the South

Fork of the Guachita River study areas

Frequency of Debris Type

1 .? 3 f 5 6 7 8

Debris Typo

I-LWDFrll Z-LWDPmUml J-SWDFull 1-SWDPdal

5 - Debitus Full f - Detritus Pwthl 7 - Slada Full 8 -Slash Rttial

I

Figure 1. Frequency of Woody Debris Type

Tab16 1. Freliminam charaterization of debris on study sites

Drainage Tributary Lw# Frequency Biomass

number o f m number/lWn m’/l Wm

1035-l Cold Water Creek 300 33 1.2

1035-2 Cold Water Creek 124 39 4.3

1035-3 Cold Water Creek 399 33 4.7

1035-4 Cold Water Creek 341 31 5.0

1035-5 Cold Water Creek 195 28 1.1

1035-6 Cold Water Creek 155 21 1.4

1035-7 Cold Water Creek 668 30 1.7

1035-a Cold Water Creek 274 26 2.0

1035-9 Cold Water Creek 249 24 2.2

1035-10 Cold Water Creek 398 25 3.6

1035-11 Co!d Water Creek 300 31 2.8

1035-12 Cold Water Creek 319 27 2.6

1044-l Gaffords Creek 400 36 2.3

1044-2 Gaffords Creek 254 34 2.1

1044-3 Gaffords Creek 464 28 1.6

1044-4 Gaffords Creek 427 30 1.5

1044-5 Gaffords Creek 407 28 1.7

1044-6 Gaffords Creek 264 23 1.2

1651-I Harvey Creek 119 21 2.4

1651-2 Harvey Creek 317 16 1.2

1651-3 Harvey Creek 291 19 1.3

1651-4 Harvey Creek 241 20 1.3

1651-5 Harvey Creek 488 22 2.5

1658-l Ouachita River’ 247 19

1658-2 Ouachita River 357 20

1658-3 Ouachita River -__ _-

1658-4 Ouachita River 137 23

1658-5 Ouachita River 642 19

2.2

1.2

0.7

2.5

* -The south fork of the Ouachita River.

184
averaged approximately 20 debris dams per 1OOm. Although this is a limited preliminary data set, the differences in

average frequency may imply ecoregional differences in debris occurrence.

CONCLUSION

This study is underway to map the location and estimate the biomass of woody debris in zero order forested ephemeral

channels and to determine the effects, if any, of reproductive timber harvest methods on these debris dams. Preliminary

data indicate a ratio of 26 debris dams per 100 m. Ecoregional differences in debris-dam frequency may occur.

LITERATURE CITED

Bilby, R.E.; Likens. G. 1980. Importance of organic debris dams in the structure and function of stream ecosystems.

Ecology. 61: 1107-1113.

Brown, J.K. 1974. Handbook for inventorying downed woody material. Gen. Tech. Rep. INT-16. Ogden, UT: U.S.

Department of Agriculture, Forest Service, Intermountain Forest and Research Experiment Station. 24~.

Galay, V.J. 1983. Causes of river bed degradation. Water Resources Research. 19(5): 1,057-1,090.

Golladay, S.W.; Webster, J.R. 1988. Effects of clearcut logging on wood breakdown in Appalachian Mountain

Streams. American Midland Naturalist. 119: 143-155.

Golladay, S.W.; Webster, J.R.; Benfield, E.F.; Swank, W.T. 1992. Changes in stream stability following forest clearing

as indicated by storm nutrient budgets. Archiv fur Hydrobiologie. SuppI.-BD. 90: l-33

Harmon, M.E.; Franklin, J.F.; Swanson, F.J.; and others. 1986. Ecology of course woody debris in temperate ecosystems.

Advances in Ecological Research. 15: 133-302.

Hedman, C.W.; Van Lear, D.H. 1991. Ripari;m zone vegetation and large woody debris dynamics: preliminary findings

for the Southern Appalachians. Society of American Foresters National Convention, San Francisco, CA.

Heede, B.H. 1985. Channel adjustments to the removal of log steps: An experiment in a mountain stream. Environmental

Management. g(5): 427-432.

Keller, E. A. ; Swanson, F.J. 1979. Effects of large organic material on channel form and fluvial processes. Earth Surface

Process. 4:361-380.

Potts, D. F.; Anderson, B. K. M. 1990. Organic debris and the management of small stream channels. Western Journal

of Applied Forestry: vol (1): 25-28.

I85
Water Chemistry of Ephemeral Streams’

J.L. Michael, W.P. Fowler, H.L. Gibbs, and J.B. Fischer’

ABSTRACT

Four individual, but related, studies are currently being conducted to determine the

effects of clearcut and seed tree reproduction cutting methods on stream

chemistry, sedimentation, and bedload movement by monitoring herbicide and

nutrient movement in stemflow, overland flow, streamflow, and zonal subsurface

flow. Sediment movement is being quantified for stormflow water samples.

Comparative rates of movement are also being studied for imazapyr, hexazinone,

and triclopyr. Analytical chemistry methods have been developed to permit

detection of triclopyr at 0.5 micrograms per liter (parts per billion, ppb). Freezer

storage studies are underway to demonstrate the suitability of frozen storage of

water samples for herbicide analysis. Studies conducted on the epoxy paint, used

throughout to protect wood and concrete surfaces during study installation, show

a coeluting coextractable compound that interferes with triclopyr analysis. This

compound does not appear after a 2-week curing period for the epoxy paint.

Curing was complete long before triclopyr was applied to the site. Therefore, the

coeluting coextractable compound will not confound any of the triclopyr analyses.

INTRODUCTION

The job of managing and protecting National Forest System land is constantly growing in complexity. Pressures

are increasing for forest lands to produce greater amounts of goods and services while maintaining or enhancing

water quality and site productivity. Accordingly, there is a continuing need to evaluate and monitor the effects

of alternative silvicultural and forest management activities on the forest environment. Evaluating and monitoring

the impacts of these activities on water yield, water quality, ecosystem functioning, and site productivity are

essential to sound forest land management. Research has provided much information, which may be used to

evaluate management activities, but there is little integrated research involving the myriad interactions in the

environment.

Herbicides have been used in forest management with generally good results. The movement of forestry

herbicides offsite and the potential impacts on nontarget organisms or ecosystems are a concern. Several studies

have been summarized that report fate and movement of herbicides from forest sites (Michael and Neary 1990,

1993; Neary and others 1993). None of the reported studies monitored movement of triclopyr from injected sites.

Where injection of other forestry herbicides was the mode of application, peak observed streamflow concentrations

did not exceed 21 micrograms per liter (ppb) (table 1 I. A similar, low-intensity application method known as spot

treatment resulted in a maximum observed concentration of 37 ppb in streamflow (table 1). Neary and others

(1986) point out that sediment is the single greatest nonpoint source pollution problem created by forestry and that

use of herbicides in forestry improves water quality by decreasing sediment loads to levels much lower than

observed with other management tools. Thus, there is the question of ecosystem impacts and the relative

impairment of water quality from herbicide use versus use of other tools in forest management.

Paper presented at the Symposium on Ecosystem Management Research in the Ouachita

Pretreatment Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

Mountains:

Research ecologist, USDA Forest Service, Southern Forest Experiment Station, Auburn, AL 36849; research

hydrologist, USDA Forest Service, Southern Forest Experiment Station, Hot Springs, AR 71902; physical

scientist, USDA Forest Service, Southern Forest Experiment Station, Auburn, AL 36849; chemist, USDA Forest

Service, Southern Forest Experiment Station, Auburn, AL 36849, respectively.

186
Table 1 .-Maximum observedherbicide residues in streamflow from herbicide injection end spot treetments in the Southern United States

Herbicide’ Location

Application

Surface

Method’ Rate* Source’ Water’

Picloram

Picloram

Picloram

Picloram

Picloram

Picloram

Hexazinone

Hex&none

Hexazinone

Hexazinone

Hexazinone

Hexazinone

Georgia

Georgia

Georgia

Kentucky

Kentucky

Tennessee

Arkansas

Alabama

Alabama

Alabama

Georgia

Georgia

INJ 0 . 3

INJ 0.3

INJ 0 . 3

INJ 1.3

INJ 0 . 3

INJ 0 . 6

SPOT 2.0

SPOT 2.9

SPOT 2.9

SPOT 2.9

SPOT 1.6

SPOT 1.6

M ND

M ND

M 6

M 21

M 10

M 4

5 8

M 2 4

M 3 7

M 2 3

M 6

M 9

’ Hexazinone - E.I. duPont deNemours & Company, Wilmington, DE; Picloram - DowElanco,

Indianapolis, IN.

‘Stem injection (INJ), application directly to the ground in a grid network (SPOT).

\ * Active ingredient (ai) applied in kg/ha.

’ Bouchard and others 1985, Michael and Neary 1993.

’ Expressed as MglL, detection limits of analytical method are 1 rg/L.

This study centers on the impacts that changes in ephemeral stream water quality may have on water quality

and quantity at the landscape scale. Specifically, objectives are:

1. Investigate offsite movement of herbicides through water movement:

(a) to estimate total offsite movement of triclopyr injected for operational herbicide application,

(b) to estimate relative importance of different routes of offsite movement of triclopyr applied as single

stem injection for vegetation management (stemflow, overland flow, and zonal subsurface flow); and

(c) to compare relative rate of movement of imazapyr, triclopyr, and hexazinone through subsurface

routes following surface application.

2. Determine the effects of clearcut and seedtree reproduction cutting methods on stream chemistry,

sedimentation, and bedload movement.

METHODS

Study Plans

This study is covered by four study plans. The need for multiple study plans arises from the complexity of each

phase of the research:

FS-SO-4351-92-1 Effects of reproduction cutting methods on streamflow, water quality, soil, and cultural

resource characteristics (Clearcut Study or CCS)

FS-SO-4105-1.25 (FS-SO-4351-93-l) Effects of seed tree cutting and site preparation on streamflow chemistry,

sedimentation, and water yield in the Ouachita Mountains (Seed Tree Study or STS)

FS-SO4105-1.26 Development and validation of an analytical and freezer-storage method for triclopyr in water

samples (Analytical Methods Study or AMS)

FS-SO-4105-1.27 (FS-SO-4351-94-l) Subsurface flow of injected and ground-applied herbicides on a typical

Ouachita National Forest mixed pine/hardwood site (Subsurface Flow Study or SFS)

Sites

A total of six study sites are divided among the four study plans. The sites are typical of the Ouachita National

Forest shortleaf pine/hardwood mixed stands. Topographic relief is variable depending on the length of watershed

under consideration, but slope is typically 10 to 25 percent with loamy surface soils ranging from moderate to well

drained.
The CCS includes four ephemeral watersheds located on the clearcut stands in Compartment (Cpt) 1658 Stand

(St) 05 (Womble Ranger District) and Cpt 458 St 16 (Fourche Ranger District). Each stand includes two small

watersheds. These watersheds were clearcut in July and August 1993.

The STS site is a 32.5-acre watershed on the Alum Creek Experimental Forest. It was harvested in August

1993 by removal of all merchantable stems except 10 to 15 seed trees per acre and approximately 5 ft2/acre of

hardwood basal area.

The SFS site is also located on the A im Creek Experimental Forest. Soils here are shallow to moderately deep

(6 ft), well drained, with slow to moderate permeability. Existing mature pines will not be harvested from this site,

which includes several very small drainages of which two are instrumented. The small drainage to be used in this

study is approximately 0.25 acres.

Instrumentation

All sites include H-flumes of the appropriate size. The CCS sites were instrumented in the fall/winter of 1992.

Control Sections are constructed from plywood and protected from the elements with a coat of epoxy paint. The

output from control sections passes through 2-ft H-flumes. Each control section is covered with a fiberglass roof

extending over the H-flume output. Instrument huts are also constructed of plywood and contain all sampling

instrumentation. Sampling instruments for collection of water samples are Iscoe automatic samplers connected

to lsco flow meters and plotters. Control sections for the STS site and below the SFS site are constructed of

concrete coated with epoxy paint for 4.5~ft and 3-ft H-flumes, respectively.

All sites are, fitted with tipping bucket and weighing bucket rain gauges. The tipping bucket rain gauges are

connected to electronic data loggers, which store precipitation data until it is downloaded and processed by the

Oxford Laboratory.

Sample Handling

All samples are removed on a per-storm basis from the lsco samplers, double labeled with preprinted, stick-on

labels, and stored in freezers at the appropriate work centers. Chest-type freezers are located at each work center

and are for the exclusive storage of these samples. When freezers approach full capacity, a team from the Auburn

Laboratory travels to the work centers in Arkansas carrying empty freezers. Samples are transferred to the empty

freezers and returned to the Auburn Laboratory in a frozen state. All personnel involved in the study have received

training in the collection, labeling, handling, and logging-in of samples, in the programming of lsco sampling device,

and in the maintenance of samplers and rain gauges.

Chemical Analysis

Triclopyr

An analytical method for triclopyr has been developed at the Auburn Laboratory. It is an HPLC method utilizing

UV detection. This method is undergoing final validation. Triclopyr is first extracted and concentrated using solid

phase extraction technology, then cleaned-up and eluted for HPLC analysis. The method is capable of quantitation

at the 0.5 to 1 part per billion level, depending on the initial sample size. A second method for more rapid analysis

is being tested. Utilizing enzyme-linked immunosorbent assay technology, this method (ELISA) permits analysis

of approximately 80 to 100 samples in a day with very good reliability. Some problems with interfering substances

(a problem with all analytical methods) still exist, and solutions are being investigated.

Freezer storage stability studies are being conducted to determine the recovery of triclopyr from samples

fortified with known amounts of triclopyr and stored in the frozen state for up to 1 year. Triclopyr has a water

solubility of 430 parts per million (ppm) at 77 OF. Frozen samples thawed for analysis will be at room temperature

when extracted (approximately 72 OF) and are not expected to contain more than about 0.04 ppm, so solubility

should not be a concern in this study. Any decreased recovery would be attributable to surface sorption on the

container wall or due to hydrolysis.

Studies have been conducted to determine whether any coextractable coeluting substances elute from the

epoxy paint (used throughout these studies), which might interfere with triclopyr analysis. Prior to complete curing,

a single compound appears to elute from the paint, but use of a two-stage gradient mobile phase elution technique

completely separates this compound from triclopyr. Subsequent to curing, which takes about a week, no additional

compounds elute to interfere with the triclopyr analysis. In addition, studies were conducted to determine whether

triclopyr would preferentially sorb onto the epoxy paint surface. No triclopyr sorbtion was detected.

188
Sediment

Aliquots (500 ml) of the water samples collected by lsco automatic samplers are filtered through prewashed,

dried, and weighed Whatmane GF/B glass fiber filters to remove all suspended sediment. Subsequent to filtration,

each filter is again dried to constant weight at 105 OC and then weighed. The difference in weight-suspended

sediment-is related to flow measured with the lsco flow meters to calculate total suspended sediment transported

offsite.

Nutrients

Anions and cations are analyzed using a Dionexe ion chromatograph. Concentrations will be related to storm

flow and treatment. The pli of all samples is also checked and recorded.

Stem Injection

Injection of hardwood stems began during the week of 18 October 1993. Auburn and Oxford Laboratories, as

well as National Forest System personnel, were on site to record the exact amount of triclopyr used on each

watershed. The two watersheds on the Womble were treated 21 October 1993; site 1 received a total of 3,885

ml undiluted Garlono 3A with blue dye added to this mixture; site 2 received 3,610 ml with blue dye added to this

mixture. The Fourche watersheds were treated 22 October 1993; site 3 received 6,630 ml with no dye added,

and site 4 received 5,330 ml with no dye added. And the Alum Creek watershed was treated 23 October 1993;

the total area received 30,530 ml whereas the watershed drainage monitored by the H-flume received 26,280 ml.

Monitoring of offsite movement began with the first precipitation event following the application.

The application method was not a classical injection treatment. Classical injection is application via some

instrument like a tubular type injector (e.g., Jim-Gem” or Cran-jector@ 1. This type of injection equipment ensures

insertion of the herbicide into cuts usually at the rate of 1 or 2 ml per cut. A modification of the injection

technique, which reduces the back strain common with tubular injectors, is the Hypo-Hatchet@ . Hypo-hatchets

are hatchets with narrow bits specially hollowed to allow delivery of the herbicide on impact with the injected

stem. The method used in this study is more aptly described as a hack-and-squirt method. In hack-and-squirt, as

it was used on the Fourche, Womble, and Alum Creek watersheds, a machete, hatchet, or other cutting device was

used to essentially girdle each stem and remove bark, often down to the xylem. A spray bottle was then used to

spray either a steady stream or a spray mist onto each tree around the girdle. During this process, some splashing

was observed, which frequently went directly onto the ground. Because of this, values of offsite movement will

likely be intermediate between the values observed in spot and injection treatments (table 1).

RESULTS AND DISCUSSION

All sites have been completely instrumented except the SFS site. Sampling equipment is present on the SFS

site, but stem collars for the monitoring of stemflow from injected sites have not been installed.

Some baseline sampling has been conducted on these sites. Precipitation data and stream stage data have

been correlated to produce hydrographs indicating stream response to precipitation events of different magnitudes.

Early results produced atypical hydrographs in which flow began and then appeared to remain constant for a long

time, instead of decreasing in an orderly and predictable fashion. The problem was identified and determined to

be the result of incident precipitation received in the flumes. Because H-flumes are designed to have a small dip

at the gauging point, incident precipitation pooled over the pressure transducers used to record stream stage.

Identification of this problem led to covering the entire length of control section and the H-flume to preclude

interception by the control section and the resulting false flow. Subsequent hydrographs have been more typical.

Flow from the Fourche watersheds typically lasts much longer (3 to 5 days) than that observed for the Womble

(1 to 3 days). The STS site on Alum Creek may flow for weeks after a rain event.

Preliminary surveys indicate the Fourche watersheds are approximately 8 and 13 acres while the Womble

watersheds are approximately 3 acres (2.8 and 2.7). The Alum Creek STS is approximately 32.5 acres. The Alum

Creek SFS is approximately 14 acres, with 0.25 acres instrumented for subsurface flow sampling. Additional

surveys will be conducted to more completely identify the area of the treated watersheds.

LITERATURE CITATIONS

Bouchard, D.C.; Lavy, T.L.; Lawson, E.R. 1985. Mobility and persistence of hexazinone in a forested watershed.

Journal of Environmental Quality. 14: 229-233.

189
Michael, Jerry L.; Neary, Daniel G. 1990. Fate and transport of forestry herbicides in the South: research

knowledge and needs. In: Coleman, Sandra S.; Neary, Daniel G., camps., eds. Proceedings of the 6th biennial

southern silvicultural research conference; 1990 October 30-November 1; Memphis, TN. Gen. Tech. Rep. 70.

Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station: 641-649.

Vol. 2.

Michael, J.L.; Neary, D.G. 1993. Herbicide dissipation studies in southern forest ecosystems. Environmental

Toxicology and Chemistry. 12: 405-410.

Neary, D.G.; Bush, P.B.; Michael, J.L. 1986. Herbicides in southern forestry: improving water quality. In:

Proceedings of the 39th annual meeting of the Southern Weed Science Society; 1986 January 20-22; Nashville,

TN. Champaign, IL: Southern Weed Science Society. 39: 335-341.

Neat-y, D.G., Bush, P.B.; Michael, J.L. 1993. Fate, dissipation and environmental effects of pesticides in southern

forests: a review of a decade of research progress. Environmental Toxicology and Chemistry. 12: 41 l-428.

190
Forest Floor Characteristics in Mature Pine-Hardwood Stands

in the Ouachita Mountains*

Michael G. Shelton and Edwin R. Lawson2

ABSTRACT

The forest floor was characterized in 24 mature, shortleaf pine (Pinus echinaru Mill.)-

hardwood stands located in the Ouachita Mountains before implementation of 6

overstory treatments that were replicated 4 times in a randomized complete block

design. Within each stand, five 0. l-m2 samples of the forest floor were collected from

each of three permanent locations representing lower, middle, and upper slope positions.

No significant differences were observed among overstory treatments, topographic

positions, or blocks for any of the forest floor characteristics evaluated. The weight of

the forest floor averaged 19.3 t/ha, and its mean depth was 3.1 cm. Twenty-seven

percent of the total weight was in the litter layer and 73 percent was in the fermentation

layer. The litter layer was composed of nearly equal weights of pine foliage, hardwood

foliage, and woody material. Total weight of the forest floor was positively correlated

with forest floor depth (fit index = 0.34) and percentage of pine foliage in the L layer,

an expression of composition (fit index = 0.18).

Key words: Decomposition, litter production, nutrient cycling, organic matter, forest

soils.

INTRODUCTION

The forest floor is one of the most distinctive features of a forest ecosystem. It consists mainly of shed vegetative parts,

such as leaves, branches, bark, and stems, existing in various stages of decomposition above the soil surface. Although

composed principally of dead organic material, the forest floor also teems with a wide variety of fauna and flora. In fact,

it is one of the richest components of the ecosystem from a biodiversity standpoint (Dickinson and Pugh 1974). The major

compartments for the storage of organic matter and nutrients within forest ecosystems are plant biomass, forest floor, and

soil. The forest floor serves as a bridge between the aboveground biomass and the soil, and it is a crucial component in

nutrient transfer via biogeochemical cycling. Much of the energy and carbon fixed by forests is annually added to the forest

floor through litterfall (Hinesley and others 1991), and a substantial portion of the annual nutrient requirement of forested

ecosystems is supplied by mineralization of organic matter in the forest floor and soil surface (Jorgensen and others 1975,

Switzer and Nelson 1972). The sustained productivity of forests is closely linked with the turnover of shed plant parts,

particularly the nutrient-rich foliage (Witkamp 1971).

Forest floor characteristics are also of considerable interest from a stand-regeneration standpoint because they affect the

seedbed conditions existing after the regeneration cut (Shelton and Wittwer 1992). Pine germination is best on a mineral

soil seedbed. However, the nutritional and protective roles of the forest floor should be fully considered before managers

prescribe site preparation treatments that create favorable seedbed conditions through its destruction (Bengtson 1981, Switzer

and Shelton 1984). Disturbance of the forest floor is also closely linked with water quality (McClurkin and others 1987).

The preharvest character of the forest floor within the study area are described in this paper. Results are restricted to

forest floor physical characteristics because the chemical analyses have not been completed.

’ Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment Conditions

and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

2 Research Forester, USDA Forest Service, Southern Forest Experiment Station, Monticello, AR 71656; Professor, School

of Forest Resources, University of Arkansas, Monticello, AR 71656, respectively.

191
METHODS

Study Area, Treatments, and Sampling Design

Relatively undisturbed, mature, shortleaf pine (Pinus e&in&r Mill.)-hardwood

generally south- facing slopes in the Guachita Mountains of Arkansas and Oklahoma.

area and its vegetation is provided in Baker (1994) and Guldin and others (1994).

stands were selected for study on

A detailed description of the study

Baker (1994) describes the selection criteria for stands and provides an overview of the full array of 13 overstory

treatments. A subset of the full complement of treatments was selected for forest floor and soil sampling because of limited

available resources. The six selected treatments were: clearcut, pine shelterwood, pine-hardwood shelterwood, pine singletree selection, pine-hardwood single-tree selection, and unharvested control. These treatments will provide a broad range

of disturbance effects and also allow evaluating the effects of different levels of hardwood retention. Treatments were

randomly’assigned within each of the four ecoregions that serve as blocks, providing a total of 24 stands. Each 16-ha stand

was subdivided into quarters to facilitate establishing 12 randomly located, permanent subplots that were used for sampling

vegetation. These quarters were oriented perpendicular to the dominant slope within the stand. In stands receiving a uniform

manual site-preparation treatment, one quarter, with its three subplots, was randomly selected for sampling the forest floor

and soils. In stands receiving different site-preparation treatments, forest floor and soil sampling were restricted to the

quarter randomly assigned to the manual site-preparation treatment. This assured that the site-preparation treatment would

be the same in all areas used for sampling the forest floor. Each subplot within a quarter represented either the lower,

middle, or upper topographic positions. In total, 72 subplots were sampled in 24 stands.

Field Sampling

Sampling was conducted during February and March of 1993. Five sampling locations were systematically located 11.4

m from each subplot center. Sampling locations were relocated if abnormal conditions occurred, such as large snrface rocks,

woody debris more than 9 cm in diameter, or previous manmade disturbance (e.g., old roads, etc.). The forest floor was

collected within a 0.1-m* square frame at each sampling location. Two layers or stages of decomposition were recognized:

(1) a litter (L) layer, which included the uppermost, relatively undecomposed material that was mostly deposited in the

autumn pulse of litterfall and (2) a fermentation (F) layer consisting of partially decomposed, older material located between

the soil surface and the L layer. The L and F layers are also referred to as Oi and Oe horizons, respectively. The color,

texture, and level of fragmentation of foliage (especially the hardwoods) were used to define the boundary between the L

and F layers. The boundary between the bottom of the F layer and the soil surface was also based on decomposition stage--

the source of F layer material was apparent, such as a fragment of a pine needle or a piece of bark. By contrast, the soil

surface was either mineral matter or dark, amorphous organic matter, representing the humus (H) layer or the Oa horizon.

A well-defined H layer rarely exists in the forest floors of southern forests because of rapid decomposition rates and

incorporation of organic matter within the soil by fauna (Switzer and others 1979). Thus, any H-layer material present was

included within the surface soil sample. Forest floor depth was evaluated at the midpoint of each side of the sampled area.

Laboratory Procedures

Forest floor samples were dried to a constant weight at 75 “C and weighed. Each L-layer sample was separated into

woody and foliar components. The woody component included branches, bark, small stems, and reproductive material (e.g.,

pine cones). The foliar component of three of the five samples for each subplot was separated into pine and hardwood

foliage and weighed. Thus, the L layer was represented by pine foliage, hardwood foliage, and woody components. The

F layer was not separated because of its high fragmentation.

Forest floor components were composited for a subplot and were ground to pass a 20-mesh sieve. Weight loss on

ignition at 500 “C for 4 hours was determined, and reported weights were for volatile matter. This is a frequently used

approximation of organic matter, although a small error occurs because some nutrients in organic matter are left in the ash.

Ash content was expressed as a percentage of oven-dried weight.

Data Analysis

Forest floor data were analyzed using analysis of variance for a two factorial, randomized complete block design.

Overstory treatment and topographic position were the two factors. Means for ash content of forest floor components were

separated by the Ryan-Einot-Gabriel-Welsch multiple-range test at the 0.05 probability level using the GLM procedure of

SAS Institute (1990). In addition, forest floor weight was regressed with depth and pine percentage in the L layer’s foliage,

192
which is an expression of forest floor composition. The following function, which accommodates

patterns, was used:

Y=b,+b,Xb2

Coefficients were determined by nonlinear, least squares regression, using the MODEL procedure (SAS Institute 1988).

a wide range of data

(1)

Data for regression were the mean values for the 72 subplots. One outlier for forest floor depth was dropped from the data.

RESULTS AND DISCUSSION

Ash Content

i-he forest floor principally consists of shed plant parts in various stages of decomposition. Since deposition mainly

comes from the canopy, the freshest material is in the uppermost portion of the forest floor (the L layer), whereas the oldest

and most highly decomposed material is at the bottom (the F layer). Ash content in the forest floor components reflects the

type’ of material and its stage of decomposition (fig. 1). The fresh material making up the L layer is very low in ash, ranging

from 2 percent in woody material to 6 percent in hardwood foliage. These differences reflect the characteristic chemical

makeup of each type of material since some nutrients in organic matter are left in the ash. For example, Hinesley and others

(1991) found that nutrient concentrations in the litter produced in mature pine-hardwood stands in Mississippi are generally

greatest in the hardwood foliage and least in the woody material.

35 r

L layer

1

F layer Hardwood Pine

COMPONENT

Woody

Figure l.-Ash content in forestfloor components. Bars with differerent letters are significantly different by the Ryan-EinotGabriel-Welsch multiple-range test at the 0.05 probability level.

Ash contents increase as the L-layer material decomposes, and the more highly decomposed F layer averaged 28 percent

ash. This increase principally reflects the mixing of mineral soil within the decomposing material. Shelton (1984), for

example, reported a large increase in mineral matter in decomposing pine stems that was attributed to termite activity.

Mechanisms of mineral matter incorporation include the burrowing and foraging activity of a wide assortment of animals,

such as earthworms (Lofty 1974), arthropods (Edwards 1974), and small mammals (Pritchett and Fisher 1987).

The Typical Ouachita Forest Floor

The L layer of the 24 sampled stands averaged 5.2 t/ha and was composed of approximately equal weights of pine

foliage, hardwood foliage, and woody material (table 1). The woody material was the most highly variable of these

components, with a coefficient of variation (CV) of 44 percent compared to 23 percent for pine foliage and 32 percent for

193
hardwood foliage. The L layer is principally the organic material deposited in the pulse of litter during autumn, and thus,

it approximates annual litter production. For example, the foliar portion of the L layer averaged 3.3 t/ha, which is close

to the 3.6 t/ha/yr of foliar litter collected in similar stand and site conditions in Perry County, Arkansa?. These values for

the Ouachita Mountains are close to the 3.9 t/ha/yr of foliar litter reported by Metz (1952) for similar stand conditions in

the Piedmont of South Carolina. In contrast, Hinesley and others (1991) reported foliar litter was 7.5 t/ha/yr for mature

pine stands growing on average sites in the Coastal Plain of Mississippi.

Table 1 .-Mean forest floor weights of the 24 sampled stands by component

Component Mean

Range

Standard

deviation Minimum Maximum

L layer

Pine foliage

Hardwood foliage

Total foliage

Woody material

Total L layer

F layer

Total forest floor

1.7 0.40 1.1 2.9

1.6 0.51 0.5 2.6

3.3 0.60 2.2 4.9

1.9 0.82 0.8 3.6

5.2 1.20 3.7 7.8

14.1 1.93 10.4 17.6

19.3 2.01 16.2 23.5

The F layer averaged 14.1 t/ha (CV = 14 percent) and accounted for 73 percent of the total forest floor weight. Thus,

the F layer represents the accumulation of several years of litter production. Decomposition rates for the forest floor can

be calculated from the annual litter inputs and the steady state of the forest floor (Olson 1963). Because the L layer

approximates annual litterfall and the F layer approximates the steady state of the forest floor, their ratio is an expression

of decomposition rate. The ratio of the L and F layers averaged 0.37. Similar decomposition rates have been reported for

natural pine stands (Switzer and others 1979) and pine plantations (Shepard 1985) in the Coastal Plain of Mississippi.

The total forest floor averaged 19.3 t/ha, with a CV of 10 percent. The surprisingly narrow range in values (16.2 to

23.5 t/ha) points to the uniform stand and site conditions existing in the stands before implementation of overstory treatments.

Forest floor weights in the Ouachita Mountains are typical of those reported elsewhere in the South and worldwide for a

similar climate and species composition. In a literature review, Vogt and others (1986) reports an average of 20 t/ha for

the warm, temperate coniferous forest type. Crosby (1961) reported that forest floor weights in shortleaf pine stands in the

Ozark Mountains of Missouri varied with stand basal area; values ranged from 23 t/ha for a basal area of 14 n&ha to 30

t/ha for a basal area of 46 m’/ha. Metz (1954) reported that the forest floor of a 40-year old, natural shortleaf pine stand

in the Piedmont of South Carolina weighed 18 t/ha; forest floors for mixed shortleaf pine and hardwoods averaged 12 t/ha.

Forest floor depth is also of interest because it is easily determined in the field and is correlated with weight. Depth

averaged 3.1 cm (standard deviation = 0.51 cm; CV = 17 percent) in the 24 sampled stands and ranged from 2.4 to 4.4

cm. In old-field pine stands on the North Carolina Piedmont, Coile (1940) reported an average depth of 3.8 cm at 20 years,

which increased to 7.1 cm at 80 years. Coile’s depths for mature pine stands are considerably greater than those reported

here for mature pine stands of the Ouachita Mountains or the 3.3 cm reported for similar stand compositions in the Coastal

Plain of both Mississippi (Shelton 1975) and Arkansas (Grano 1949).

Factors Affecting Forest Floor Characteristics

No significant differences were observed among the forest floor weights of assigned overstory treatments, topographic

positions within stands, or blocks (table 2). Similar results, not shown, were observed for depth and weight of L-Iayer

3 Unpublished USDA Forest Service data on file with the Southern Forest Experiment Station, Monticello, AR 71656-3516.

194
components. This was expected because of the random assignment of overstory treatments and selection criteria used to

assure uniform stand conditions before treatment implementation. Apparently, differences in environmental conditions

associated with topographic positions within stands or blocks were too minor to affect forest floor characteristics.

Table 2. -Results of the analysis of variance for forest floor weights

Source

Block

Degrees of

freedom

3

L layer F layer Total

_________________________Me~ square e~or_________________________

1.50 (0.78)’ 6.26 (0.67) 3.96 (0.86)

Overstory treatments 5 3.27 (0.57) 0.83 (1.00) 3.40 (0.96)

Topographic position 2 1.63 (0.68) 10.68 (0.41) 16.64 (0.36)

Treatment x position 10 0.37 (1.00) 8.05 (0.74) 9.12 (0.83)

Error 51 4.18 11.86 16.00

,* The number in parentheses is the probability of F.

Site quality apparently has little influence on forest floor weight within a climatic region and forest type.This is shown

by comparing the values for poor sites in the Ouachita Mountains (this study) to those for better sites in the Coastal Plain

of Mississippi (Switzer and others 1979): values were 19 t/ha for stands on poor sites (pine site index of 18 m at 50 years)

compared to 21 t/ha for stands of a similar composition but on better sites (pine site index of 26 m at 50 years). In addition,

Shepard (1985) found no significant affect of site index on forest floor weights averaging 18 t/ha in a series of loblolly pine

(Pinus taeda L.) plantations with site indices ranging from 15 to 28 m at 25 years. This uniformity in forest floor weights

for a forest type over a wide range of sites undoubtedly reflects the balance between inputs from litter-fall and outputs from

decomposition. Good sites have higher rates of input than poorer sites but also typically have higher rates of decomposition.

These two opposing processes tend to equalize forest floor weights.

Despite little stand-to-stand variability in forest floor weights, some within-stand variation was observed.For example,

total weight of the forest floor increased with an increasing pine composition, as indicated by the following equation:

W = 1.07 f 6.82 Paz0 (2)

df = 69 RMSE = 3.39 fit index = 0.18

where: W = total weight in t/ha and P is the pine percentage in the L layer’s foliage, which is a relative expression of the

forest floor’s species composition. Pine foliage averaged 52 percent of the total foliage weight in the L layer and ranged

from 12 to 87 percent among the 72 subplots. Thus, forest floors in individual subplots varied from nearly all hardwoods

to nearly all shortleaf pine. Weights calculated from equation (2) are 15, 19, and 22 t/ha for forest floors composed of 15,

50, and 85 percent pine, respectively. Switzer and others (1979) reported a similar range in forest floor weights for a series

of stands representing secondary succession in the Coastal Plain of Mississippi. Forest floor weights maximized at 21 t/ha,

whereas pines dominated middle succession and then declined to 14 t/ha as the hardwoods dominated late succession. Such

differences reflect the well-known influence of litter characteristics, particularly lignin content, on decomposition rates (Vogt

and others 1986).

Total weight of the forest floor increased with increasing depth, as indicated by the following equation:

W= 6.54 + 5.75Dnno (3)

df = 68 RMSE = 3.06 fit index = 0.34

where: W = total weight in t/ha and D = depth in cm. Forest floor depth only accounted for 34 percent of the variation

in weight, indicating that numerous other variables affect this relationship. Such variables include the type of material (e.g.,

woody versus foliar) and its stage of decomposition. Variation in microtopography and surface rocks are also sources of

variability. A similar level of fit for the weight to depth relationship of the forest floor was reported in another study

(Shelton 1975).

195
CONCLUSIONS

Th e forest floor is an important component of forest ecosystems; it functions in stand nutrition, biodiversity, water

quality, site protection, soil-water relations, and stand regeneration. Forest floor characteristics depend on a stand’s

disturbance history and the balance between inputs from litterfall and outputs from decomposition. Any factor that affects

either of these two opposing processes, such as the character of the vegetation (age, composition, and density) and the site

(climate, soils, aspect, and topographic position) will be reflected in the accumulation of organic matter in the forest floor.

However, stands evaluated in this study were selected to conform to specific criteria (namely, relatively undisturbed, mature

pine-hardwood stands on generally south-facing slopes). This uniformity in stand conditions was reflected in fairly uniform

forest floor characteristics. Thus, variation observed in this study may not be representative of the entire Ouachita

Mountains. Of the variables evaluated in this study, within-stand variation in vegetative composition had the greatest effect

on forest floor weights. Forest floor weights increased as the pine component increased, a trend that reflects the slower

decomposition rate of pine litter when compared to that of hardwoods. The forest floor’s nutrient status and its role in

nutrient cycling will be reported when chemical analyses are completed.

LITERATURE CITED

Baker, James B. 1994. An overview of stand-level ecosystem management research on the OuachitalOzark National Forests.

In: Proceedings of the symposium on ecosystem management research in the Ouachita Mountains: pretreatment

conditions and preliminary findings; 1993 October 26-27; Hot Springs, AR. Gen. Tech. Rep. New Orleans, LA: U.S.

Department of Agriculture, Forest Service, Southern Forest Experiment Station.

Bengtson, G.W. 1981. Nutrient conservation in forestry: a perspective. Southern Journal of Applied Forestry.

5(2):50-58.

Coile, T.S. 1940. Soil changes associated with loblolly pine succession on abandoned agricultural land of the Piedmont

Plateau. Bull. 5. Durham, NC: Duke University, School of Forestry. 85 p.

Crosby, John S. 1961. Litter and duff fuel in shortleaf pine stands in southeast Missouri. Tech. Pap. 178. Columbus, OH:

U.S. Department of Agriculture, Forest Service, Central States Forest Experiment Station. 10 p.

Dickinson, C.H.; Pugh, G.J.F., eds. 1974. Biology of plant litter decomposition. New York: Academic Press. 775 p. Vol.

2.

Edwards, C.A. 1974. Marcoarthropods. In: Dickinson, C.H.; Pugh, G.J.F., eds. Biology of plant litter decomposition. New

York: Academic Press: 533-554. Vol. 2.

Grano, C.X. 1949. Is litter a barrier to the initial establishment of loblolly and shortleaf pine seedlings? Journal of Forestry.

47: 544-548.

Guldin, James M.; Baker, James B; Shelton, Michael G. 1994. Midstory and overstory plants of mature pine/hardwood

stands on south-facing slopes in the Ouachita/Ozark National Forests. In: Proceedings of the symposium on ecosystem

management research in the Ouachita Mountains: pretreatment conditions and preliminary findings; 1993 October 26-27;

Hot Springs, AR. Gen. Tech. Rep. New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest

Experiment Station.

Hinesley, L.E.; Nelson, L.E.; Switzer, G.L. 1991. Weight and nutrient content of litter during secondary succession on

well-drained uplands of the East Gulf Coastal Plain in Mississippi. Canadian Journal of Forest Research. 21: 848-857.

Jorgensen, J.R.; Wells, C.G.; Metz, L.J. 1975. The nutrient cycle: key

Forestry. 73: 400-403.

Lofty, J.R. 1974. Oligochaetes. In: Dickinson, C.H.; Pugh, G.J.F., eds.

York: Academic Press: 467-488. Vol. 2.

to continuous forest production. Journal of

Biology of plant litter decomposition. New

196
McClurkin, D.C.; Duffy, P.D.; Nelson, N.S. 1987. Changes in forest floor and water quality following thinning and

clearcutting of 20-year-old pine. Journal of Environmental Quality. 16: 237-241.

Metz, Louis J. 1952. Weight and nitrogen and calcium content of the annual litter fall of forests in the South Carolina

Piedmont. Soil Science Society of America Proceedings. 16: 38-41.

Metz, Louis J. 1954. Forest floor in the Piedmont region of South Carolina. Soil Science Society of America Proceedings.

18: 335338.

Olson, Jerry S. 1963. Energy storage and the balance of producers and decomposers in ecological systems. Ecology. 44:

322-331.

Pritchett, William L.; Fisher, Richard L. 1987. Properties and management of forest soils. 2nd ed. New York: John Wiley

and Sons. 494 p.

SAS Institute. 1988. SAS/ETS user’s guide. Version 6, 1st ed. Cary, NC: SAS Institute Inc. 560 p.

SAS Institute. 1990. SAS/STAT user’s guide. GLM-VARCOMP. Version 6, 4th ed. Cary, NC: SAS Institute Inc. 1,686

p. Vol. 2

Shelton, Michael G. 1975. The successional development of the forest floor and vegetation on uplands of the Upper Coastal

Plain of Mississippi. Mississippi State, MS: Mississippi State University. 84 p. M.S. thesis.

Shelton, Michael G. 1984. Effects of the initial spacing of loblolly pine plantations on production and nutrition during

the first 25 years. Mississippi State, MS: Mississippi State University. 161 p. Ph.D. dissertation.

Shelton, Michael G.; Wittwer, Robert F. 1992. Effects of seedbed condition on natural shortleaf pine regeneration. In:

Brissette, John C.; Bamett, James P., camps. Proceedings of the shortleaf pine regeneration workshop; 1991 October

29-31; Little Rock, AR. Gen. Tech. Rep. SO-90. New Orleans, LA: U.S. Department of Agriculture, Forest Service,

Southern Forest Experiment Station: 124-139.

Shepard, James P. 1985. Relationships between nutrient cycling and net primary productivity in loblolly pine plantation

ecosystems of the East Gulf Coastal Plain. Mississippi State, MS: Mississippi State University. 195 p. Ph.D.

dissertation.

Switzer, G.L.; Nelson, L.E. 1972. Nutrient accumulations and cycling in loblolly pine (Pinus raeda) plantation

ecosystems: the first twenty years. Soil Science Society of America Proceedings. 36: 143-147.

Switzer, G. L.; Shelton M.G.; Nelson, L.E. 1979. Successional development of the forest floor and soil surface on

upland sites of the East Gulf Coastal Plain. Ecology. 60: 1162-1171.

Switzer, G.L.; Shelton, M.G. 1984. Maintenance of productivity: some considerations. In: Karr, Bob L.; Baker, James B.;

Monaghan, Tom, eds. Proceedings of the symposium of the loblolly pine ecosystem (West Region); 1984 March 20-22;

Jackson, MS. Mississippi State, MS: Mississippi Cooperative Extension Service: 201-216.

Vogt; K.A.; Grier, C.C.; Vogt, D.J. 1986. Production, turnover, and nutrient dynamics of above- and belowground detritus

of world forests. Advances in Ecological Research. 15: 303-377.

Witkamp, Martin. 1971. Soils as components of ecosystems. Annual Review of Ecology and Systematics. 2: 85-110.

197
New Perspectives In Heritage Resources Management

On The Ouachita National Forest’

Roger E. Colemar?

ABSTRACT

This research project is designed to assess the effects of Forest Service timber

management practices on cultural resources or heritage resource sites. The research was

undertaken in conjunction with Phase II of the ecosystem management project, a replicated

stand-level study that considers the effects that 13 di%rent cutting treatments may have

on multiple forest resources. This two-part research project focuses on the identification

and assessment of heritage resource sites within the 52-stand project area. Following

imposition of the cutting treatments, selected heritage sites will be monitored to assess

relative impacts. These data will be used to select cutting treatments that are sensitive to

heritage resource preservation needs. Furthermore, the avoidance of significant heritage

resources during the experiment will make it possible evaluate the success of this

forest-wide site protection strategy.

INTRODUCTION

The Ecosystem Management research project, formerly called “New Perspectives,” is an experiment in forest management

designed to analyze the effects of timber harvest strategies on an array of forest resources (Baker 1994). Specifically, this discussion

is concerned with the potential effects of timber cutting methods on one particular resource--cultural properties or heritage sites.

Phase II of ecosystem managementresearch is a replicated stand-level study that is being implemented in fifty-two 40-acre stands

in Garland, Montgomery, Polk, Scott, and Yell Counties, Arkansas, and in LeFlore County, Oklahoma. Four replications of thirteen

timber cutting methods have been randomly assigned to these stands, and the treatments are being imposed during the summer and

fall of 1993. Timber harvests have varying potential to impact heritage resources. Generally, in terms of predicted level of effect,

the cutting treatments can be quantified by percentage of ground disturbance sustained and then ranked by relative order of impact.

The resulting scale of effect will be an asset to forest land managers who seek to minimize damage to forest resources caused by timber

harvests.

Whether by natural forces or human alteration of the landscape, the destruction of archeological sites has been a subject of

professional inquiry among archeologists who seek to explicate the processes that affect sites to better interpret the archeological

record. Sites are adversely affected when: (1) horizontal displacement or redeposition of artifacts occur with resulting loss of

contextual information, (2) vertical mixing of site deposits causes loss of temporally sensitive data, and (3) artifact breakage and

deterioration biases composition of the archeological rtird However, the study of site destruction, or site taphonomy, is a “gray-area”

in the archeological literature. Although such studies have been recommended in Arkansas (Padgett 1978 Klinger 1982), none have

been brought to fruition (Harcourt 1993). Ecosystem management, therefore, provides a unique opportunity to study the effects of

timber-cutting practices on heritage resources. In fact, if forest managers are to select harvest options sensitive to the preservation

of heritage resources, this experiment is essential.

Efforts to document preharvest conditions within the ecosystem management study areas as well as the development of strategies

for monitoring and assessing postharvest effects are described here. During the course of this project, the potential effects of other

selected management practices will be examined as well. The suitability of forestwide survey methodology for site identification will

be tested, and the success of site avoidance as a widespread protective measure used during timber harvests will be explored.

These activities are being undertaken in two stages. The first stage was an archeological survey by USDA Forest Service

personnel to ident@ and document heritage resources within the study areas. This effort has been completed. The second, ongoing

stage of analysis--monitoring sites and evaluating postharvest conditions--is being conducted by archeologists of the Arkansas

Archeological Survey under the direction of Dr. Charles Ewen.

’ Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27,1993.

2 Archeologist, USDA Forest Service, Ouachita National Forest, Hot Springs, Arkansas, 7 1902.

198
METHODS

Fieldwork to document preharvest conditions was undertaken by Ouachita National Forest Heritage Resource Technicians

(HRT’s), who are USDA Forest Service personnel trained in the identification and documentation of archeological sites. The HRT’s

follow a standard survey methodology designed by the forest archeologist to maGnize site recognition in forested environments

(Etchieson 1990). An archeological survey is conducted by placing parallel transect lines at 30-m intervals across a project area.

All transects are subjected to intensive investigation. Areas in slopes of 10 percent or less are shovel tested at 30-m intervals. Other

high-site probability areas including benches, terraces, ridgespurs, ridgetops, rock outcrops, alluvial fans, etc., receive additional

emphasis. Such locations, as encountered, are shovel tested. To promote artifact recognition, till from each shovel test is screened

through l/4-inch (0.63~11) mesh hardware cloth, and tests are excavated to a depth of 30 cm or until sterile subsoil is encountered.

When an archeological site is identified, additional shovel testing is conducted to assess the depth of cultural deposits and artifact

content and to establish site boundaries.

Postharvest assessment of heritage sites is currently being conducted under a challenge cost-share agreement with the Ouachita

National Forest by archeologists f?om the Arkansas Archeological %vey (AAS). Survey archeologists shall revisit each of the sample

sites and verify the initial baseline data wllected by Forest Service HRT’s, including definition of site boundaries and depth of cultural

remains. Additional information will be collected, through further shovel testing, for comparison during subsequent postharvest

monitoring. Artifact wncentrations within site boundaries, preharvest site disturbances, and the presence of cultural features will be

recorded. Datum points and permanent camera stations will be established on each site, and these data will be photographically and

planimetrically documented. The survey archeologists shall develop a comprehensive monitoring plan to guide data collection during

postharvest inspections and to assess the degree of horizontal and vertical artifact displacement, artifact breakage and deterioration,

and the destruction of cultural features. The monitoring plan shall be broadly applicable to all Forest Service projects and will be

implemented forestwide. Survey archeologists will conduct the first monitoring inspection to assess the effects of cutting strategies

on the site sample. The results of Phase II monitoring shall be formally reported to the Forest Service by June 15, 1994.

As part of the Phase. II research project, the effectiveness of site-protection measures used during timber harvests will be assessed.

Those archeological sites that are considered potentially eligible for nomination to the National Register of Historic Places shall be

protected during the cutting treatments. Significant sites shall be ff agged and avoided--a Forest Service strategy employed in all timber

harvests. The success of this protective measure will be gauged by the Survey archeologists during Phase II monitoring. Furthermore,

the suitability of the forestwide survey strategy will be tested through the selective resurvey of research stands following the cutting

treatments. At least four clearcut stands will be surveyed, and to avoid bias in site recognition, the resurveys shall not be conducted

by the same personnel.

RESULTS AND DISCUSSION

Documenting Preharvest Conditions

Archeological surveys were conducted sporadically from September 25, 1991, to January 14, 1992, for the proposed Phase II

Research Project (Coleman and others 1992). Fifty timber stands comprising 2,755 acres were archeologically investigated. Only

two unmanaged control units, where archeological sites will not be impacted, were not surveyed. Cumulatively, 1 ,159 hours were

invested in these surveys by 16 HRT’s, resulting in the identification and description of 26 archeological properties. These sites occur

in 16 research stands encompassing the full range of proposed cutting treatments.

Sample Selection

A sample of archeological properties were then selected for monitoring during Phase II of the experiment. Several site types have

little potential to contribute to our understanding of site taphonomy including isolated artifacts, sites without associated cultural

remains (e.g., mineral test pits and agricultural fields), and sites situated within protected riparian zones where timber eutting is not

permitted. Such sites were omitted from the study population. An effort was made in compiling the site sample to include a range

of typical Ouachita Mountain site types and 13 cultural properties were selected for inclusion in Phase II of the experiment (tab. 1).

These include five late 1 9th-and early 20th~century homesteads, a sixth late historic homestead with a prehistoric component, one

whiskey-still site, an historic surface trash midden, a cattle-dipping vat site; and prehistoric lithic scatters. Prehistoric sites include

four lithic workshops for production of stone tools, a butchering station, and one short-term hunting camp.

I99
Table I.--The archeological site sample taken from Phase II stands on Ouachita National Forest

Site number

3MN649

Diic t C!OltlpOIEtlt/~ CtiOll

Historichomestead

3hIN650

34LF796

34LF798

34LF797

3PL.304

3MN652BhIN653

3YE431

3sc312/3sc313

3MN707

3MN708

3MN645

3MN710

Kiam iCh i

KitiCh i

KiaUliCh i

Mau

o&n

odelPoteau

Womble

Womble

Womble

Womble

Plx&tMic/lithic wolkshop

Prehistolic/lithicworkshop

Prch istOli~ th ic W Ork sh Op

pre h istoriJlith ic W Ork sh Op

HistoriHistorilzAl~

HistoriPl&i&ri&c woliahop

HistoliHistori~caitle dipping vat

HiSloCi_

PrehistofiJbutcheringstation

HiiricfhshMidden

Documenting Postharvest Conditions

In a preliminary report on the Arkansas Archeological Survey activities, archeologist James Harcourt concludes that the site

detection skills of the HRTs are “outstanding.” He further notes that Survey archeologists almost always concurred with their tindings

(Harcourt 1993). The combined efforts of USDA Forest Service personnel and the Arkansas Archeological Survey have resulted in

a powerful synthesis of fieldwork and site documentation, leading to Phase II of the ecosystem management project. Postharvest

monitoring, however, has not been undertaken and there are, as yet, no conclusions regarding timber-cutting strategies and their effects

on cultural resources or the viability of Forest Service site-protection measures. Furthermore, selective resurvey of research stands

to determine the effectiveness of Forest Service field methodology has not been initiated. These data, however, are forthcoming. The

survey results will prove to be invaluable to forest planning and will provide new directions to heritage resource management on the

Ouachita National Forest.

FUTURE PERSPECTIVES

An ecosystem is the product of past events including human alteration of the landscape. Humans have a&z&d the environment

in Arkansas for over 10 millenia--perhaps nominally at first, but this is a subject of debate. A popular theory attributes the extinction

of pleistocene megafauna to Paleoindian hunters, and the human role in the frequency of fire is widely acknowledged in other regions.

In the Ouachitas archeologists are just beginning to understand that late-prehistoric Indians altered floodplain ecosystems through

agricultural production, although the effects of novaculite quarrying on the environment have been evident for some time. Some

extensive quarries stretch for miles on mountain ridges where human activity has removed or deflated topsoil, exposing novaculite

rock on the surface. Fire reddened novaculite exposures suggest that prehistoric Indians may have burned these outcrops to facilitate

their mining activities. Generations of such activity could have denuded these ridges of forest vegetation. In any event, drastic

environmental changes have occurred in the past 150 years with widespread commercial logging; various mining booms that have

pitted the landscape in some locations; homesteading with development of pastures and agricultural fields; and finally, by creation

of the Ouachita National Forest in which a period of intensive forest management--notably through tree planting and the supression

of natural fire--was initiated. The magnitude of human alterations, especially those of the Forest Service has resulted in an

anthropogenic forest.

Now, with adoption of the ecosystem management approach, there is an increasing need to study environmental issues in historic

context and to apply the results of these studies to restoration and management of forest ecosystems (Fomey 1993). Heritage resources

contain data sensitive to environmental change, and, with C-l 4 dating, dendrochronology and archeomagnetic dating, these data can

provide a time-sensitive record of forest evolution. The uses of heritage resources in environmental research have been summarized

by Forest Service Archeologist Sandra Fomey who lists some archeological data sets and their potential applications (Fomey 1993).

Fossil pollen and opal phytoliths can reveal plant species composition and, in deeply stratified sites, provide a continuous record of

plant succession and ecosystem change. Zooarcheological or fauna1 data from excavated sites can reveal past species composition

and former abundance of both terrestrial and aquatic species. These data could be decisive in issues concerning endangered species

designation, species reintroduction, and wildlife habitat enhancement.

More recent data sources exist that chronicle historic change in the forest environment and are frequently used by heritage

resource managers. Government land office records, compiled in the 1840’s in west-central Arkansas, contain detailed notes

describing plant communities that surveyors encountered while traversing section lines. These data were graphically depicted in

color-coded maps. Forest Service land acquisition maps from the 1930’s document evidence of human alteration of the environment

200
in that decade including roads, pastures, agricultural fields, and cutover forest land. Another rich source of information yet untapped

by ecosystem researchers are the meteorological records of the U.S. Signal Service Corps. This 176-year-old record collection began

in 18 17 at the observation station at Fort Smith near the northern boundary of the Ouachita National Forest. It presents a daily record

concerning plant species, growing season, precipitation, wind direction, and incidence of fire.

Heritage sites and the data they contain have direct applications to issues of land management and resource planning in the

national forests. Heritage resource managers offer a cultural/historical perspective to Ecosystem Management and integrated

multidisciplinary studies involving heritage resource data are critical to future forest planning.

REFERENCES

Baker, James B. 1994. An overview of stand-level ecosystem management research in the OuachWOzark National Forests. In:

Proceedings of the symposium on ecosystem management research in the Ouachita Mountains: pretreatment conditions and.

preliminary findings; 1993 October 26-27; Hot Springs, AR Gen. Tech. Rep. New Orleans LA: U.S. Department of Agriculture,

Forest Service, Southern Forest Experiment Station.

Coleman Roger E.; Avery, Sherri; Haikey, Larry D. 1992. Cultural resources survey for Phase II New Perspectives research stands,

’ Ouachita National Forest, Montgomery, Garland, Polk, Scott, and Yell Counties, AR, and LeFlore County, OK. Hot Springs,

AR: U.S. Department of Agriculture, Forest Service, Ouachita Cultural Resources Report No. 23. 88 p.

Etchieson, Meeks. 1990. Guidelines for completing cultural resource surveys on the Ouachita National Forest. Hot Springs, AR:

U.S. Department of Agriculture, Forest Service, Ouachita National Forest. 92 p.

Fomey, Sandra Jo. 1993. Heritage Resources:Tools for Ecosystems Management. 26th annual conference of Society for Historical

Archeology, 1993, January 9, Kansas City. Not paged. On file with: U.S. Department of Agriculture, Forest Service, Ouachita

National Forest, Supervisor’s Office, Hot Springs, AR.

Harcourt, James P. 1993. New Perspectives on recent work in the 0uachitas:the Thirteen Sites Project (Draft). Fayetteville, AR:

Arkansas Archeological Survey, Sponsored Research Program. On file with: U.S. Department of Agriculture, Forest Service,

Ouachita National Forest, Supervisor’s Offtce, Hot Springs, AR. 4 p.

Klinger, Timothy C. 1982. Mangmm: mitigation through excavation and preservation. Fayetteville, AR: Arkansas Archeological

Survey Res. Series No. 20. 125 p.

Padgett, T. J. 1978. Blue Mountain Lake: an archeological survey and an experimental study of inundation impacts. Fayetteville, AR:

Arkansas Archeological Survey Res. Series No. 13. 150 p.

201
Esthetics Evaluation’

Victor A. Rudis, James H. Gramann, and Theresa A. Herr&

ABSTRACT

An analysis of summer visual attributes and an overview of ongoing scenic quality

research within selected shortleaf pine (Pinus ech inuru Mill.)-hardwood stands in the

Ouachita and Ozark National forests are presented. Within-stand visual attributes were

reported prior to even-aged stand-level (Phase II) treatment for twelve 40-acre stands in

the north, east, and south regions and for plot-level (pre-Phase I) visual attributes for

twenty OS-acre plots examined two growing seasons after disturbance. No differences

in visual attributes before treatment were apparent between 0.0 to 2.8 feet and 2.9 to 5.5

feet aboveground. From the stand-level study, there were no significant differences

among regions but there were significant differences among stands and sample points.

The plot-level study, a randomized complete block design with four blocks or landform

positions and uneven-aged treatments, revealed differences by distance zone aboveground

for disturbed plots. Greater foliage and twig screening and reduced visual penetration

in lower zone views were associated with increased overstory removal. Visual

penetration was lower and foliage and twig screening was higher in low elevation

landform positions compared with high elevation landform positions. Insight from both

studies suggests that a significant difference between viewing zones in summer may be

suitable as an index of recent stand disturbance.

INTRODUCTION AND OVERVIEW

Public agencies and private owners are increasingly confronted with public reaction to timber harvest and reproduction

cutting activities. One frequent issue revolves around the loss of esthetics caused by disturbances. Maintaining and

enhancing the visual quality of forests are also becoming more important as competing uses for forest land intensify,

particularly on public forest land.

Methods to measure esthetics have been successful in quantifying public perception of a forest’s scenic beauty (Ribe

1989, Rudis and others 1988). Stands with limited screening and limited downed woody material and a moderate amount

of sawtimber-sized trees are rated higher on a scenic beauty rating scale than those with extensive screening, small-diameter

trees, or large amounts of downed woody material.

Many scenic quality studies have suggested silvicultural treatments that alter esthetics, but few have directly tested the

effect of alternative treatments. Few studies have examined treatments over an extended time span, and none are specific

to mixed pine (Pinus spp. L.) and oak (Quercus spp. L.) stands typical of the Ouachita Mountains. Examination of esthetics

before and after treatments are applied can address tradeoffs among alternative silvicultural practices.

Esthetics is defined as an emotional response to an object. This emotional response can be divided into three

measurement categories: the attributes of the object, the viewer, and intervening conditions between the viewer and the

object. Esthetics is commonly quantified by viewers as scenic beauty ratings and standardized with techniques developed

by Daniel and Boster (1976).

The majority of this report focuses on within-stand visual attributes for shortleaf pine (Pinus ech inafu Mill.)-hardwood

stands on the Ouachita and Ozark National Forests (NF) ,(Baker 1994). Other works in progress address a viewer’s

Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

Research forester, USDA Forest Service, Forest Inventory and Analysis Unit, Southern Forest Experiment Station,

Starkville, MS 39759-0906; associate professor, Department of Recreation, Park and Tourism Sciences, Texas A&M

University, College Station, TX 77843-2261; associate professor and head, Department of Recreation and Park

Administration, Arkansas Tech University, Russellville, AR 72801-2222, respectively.

202
background, a viewer’s perception of scenic beauty, and some of the intervening conditions. These are being investigated

in studies by cooperators at Arkansas Tech University, Texas A&M University, and Mississippi State University.

Arkansas Tech’s role, directed by Theresa Herrick, focuses on the viewer (Rudis and others 1991). Herrick reports

on a recreation user survey of scenic preferences in the Ouachita NF (Herrick and Rudis 1994). Work has also begun on

stand-level (Phase II), within-stand scenic beauty estimation of pretreatment conditions prior to even-aged treatment. A

postharvest assessment of seasonal differences in scenic beauty is planned.

Texas A&M University’s role, directed by Jim Gramarm, focuses on the object as perceived by viewers and some of

the varying conditions (Rudis and Gramann 1990). Jim Gramann reports on progress in characterizing within-stand scenic

beauty by season, landform, and treatment (Gramarm and Rudis 1994). Uneven-aged timber management is examined for

OS-acre plots in the Winona Ranger District near Lake Sylvia (Winona plots). Although not reported in this proceedings,

Gramarm and colleagues at Texas A&M have digitized photographs to examine color differences by season (Rudis and others

1991). Color, texture, and shadow effects are likely important in determining scenic beauty from distant views or vistas,

an important component of landscape-scale (Phase III) ecosystem management research.

Mississippi State’s role, directed by Dennis Cengel and Rebecca Ray, has just begun (Rudis and others 1993). Ray has

taken posttreatment “intermediate” views of all 39 north, east, and south Phase II stands. Intermediate views are those

typically seen from a roadside or from stand boundaries. The views encompass 3 control stands and 36 treated stands.

Because views have just been photographed (October 1993), no results are reported in this proceedings. Specific objectives

of this study include determining what constitutes the most visually acceptable harvests. Different groups of viewers will

make assessments of scenic beauty and willingness-to-pay for altered treatments. A subset of views will be prepared as

photographs and shown to loggers to estimate perceived costs. These estimates will be compared with actual cost information

gathered by Kluender and others (1994).

Evaluating Within-Stand Visual Attributes

The proportion of each view within stands was sampled along a 30 degree arc outward to 50 feet (ft). Visual attributes

were divided into visual penetration, foliage and twig screening, tree-bole screening, and nonvegetative screening. Tree-bole

screening is defined as the occupancy of tree trunks at least 5 inches in diameter at breast height (d.b.h.); i.e., at 4.5 ft.

Foliage and twig screening is vegetative screening by tree trunks less than 5 inches d.b.h. and all foliage and twigs.

Nonvegetative screening includes rocks, bare soil, and litter. Visual penetration is the absence of the other three

components, i.e., the “unscreened” portion of the view. Limited screening by foliage and twigs, abundant visual penetration,

and a high density of tree-bole screening is correlated with high scenic beauty ratings in loblolly-shortleaf pine stands (Rudis

and others 1988). The relationship of visual attributes to scenic beauty ratings is also interpretable in psychological terms

(Ruddell and others 1989).

A scaling device called a screenometer was used to estimate the proportion of visual attributes. The screenometer was

modified from that described in Rudis (1985) to include 9 instead of 10 horizontal segments, and two height zones instead

of one. Nine horizontal segments per zone view were used to ease record keeping. Two zone views, a lower zone

approximating 0 .O to 2.8 ft, and an upper zone approximating 2.9 to 5.5 ft above the ground, were etched onto the viewpiece

to increase its resolution for detecting small-scale changes and compare its utility for foliage height-dependent wildlife habitat

assessments.

Analysis of variance, means, and standard errors were calculated from arcsine square root transformation of proportions.

Calculations, analysis of variance, F-tests, and standard errors used the general linear model (GLM) procedure (SAS Institute

Inc. 1990). Means and standard errors were transformed back into proportions for display purposes. For Winona plots,

planned comparisons between means associated with significant sources of variation (P[F] <0.05) were conducted using ttests and the least-squares means option (SAS Institute Inc. 1990).

Phase II Stands

Methods.--Pretreatment conditions for stands to be treated were examined in June 1992. Planned treatments included

clearcut, shelterwood, group selection, and control in north, east, and south regions for a total of 16 stands (table 1).

Screening estimates for each stand were based on 30 observations taken in June 1992. Observations comprised 15 sectors

and 2 zone views per sector. Screening sectors were centered at 30 degree intervals beginning with azimuth 30 degrees.

Sectors were viewed from the center of points coincident with the center of bird census plots (Petit and others 1994). One

screenometer sector was assigned at random to each point; the second sector was 180 degrees in the opposite direction. In

four stands with five points, a third sector was assigned at random. In eight stands with six points, the third sector was

assigned to points 2, 4, and 6.

203
North (Arkansas River Valley ecoregion)

East (upper Ouachita Mountain ecoregion)

South (lower Ouachita Mountain ecoregion)

Clearcut

Shelterwood

Group selection

Control, no treatment

Clearcut

Shelterwood

Group selection

Control, no treatment

Clearcut

Shelterwood

Group selection

Control, no treatment

458 16

457 12

46 18

284 11

1067 15

1119 21

1124 11

605 5

1658 5

27 1

35 42

23 10

Table 1 .-- Re gion, planned treatm ent, and national forest com partm ent and stand num b er exam inedfor w ith in-stand visual attributes, Ouach ita and O m rk

National Forests of Ark ansas

Region* Planned treatment Compartment Stand

* See Baker (1994)

Points were systematically located across the portion of stands to be treated. Because of bird census requirements,

points had to be at least 426 ft (130 m) apart and at least 295 A (90 m) from stand boundaries. Potential stream management

zones (SMZ’s) were retained untreated within several stand boundaries. Points were moved away from potential SMZ’s

when QbviOUs from field observations and topographic maps. Due to these restrictions and the variable shape of stands, there

were five points in four stands and six points in eight stands. Photographs were taken along the same azimuths and points

used to estimate screening. Scenic beauty beauty ratings, at present incomplete, will follow procedures noted elsewhere

(Gramann and Rudis 1994).

Results.--Components of the analysis of variance are contained in tables 2 and 3. Table 3 lists the analysis of variance

for nonvegetative screening by lower zone views, as there was no nonvegetative screening in the upper zone. An F-test

failed to reject the null hypothesis that regional differences existed (P[F] = 0.08) (table 2). Analysis of variance tests

revealed no significant differences by zone (P[F] 20.22). Differences by point were significant. Tests revealed significant

differences among points within stands for all screening categories (P[F] <O.Ol). Differences in variance among stands were

not significant (P[F] 20.19) for tree-bole screening but were significant (P[F] <0.05) for foliage and twig screening and

visual penetration. Variance attributed to the two distance zones was not significant.

Table 2.--Analysis of variance for sum m e r 19 9 2 visual attributes by screenom ete r category, Ph ase II stands

Mean square variance by category

Source

Degrees Tree Foliage Visual

of freedom boles and twigs penetration

Region 2

Stand*region 9

Point*stand*region 56

Pooled mean square 292

combined from below:

(P[FJ 20.22. Denominator is residual mean square)

Zone 1

Zone by region 2

Zone by stand*region 9

Zone by point*stand*region 56

Residual 224

2,057.2 2.551.4 676.8

728.5 2.713.6’ 1,487.1+

485.3’ 1.074.7’ 606.7+

149 .2 219.7 182.7

28.8 0.3 5.1

75.7 283.9 318.8

51.8 116.1 9 2.6

33.3 85.0 85.7

183.3 229 .5 210.1

Total 359

* within each. F-test significantly different: t P <0.05, $ P <O.Ol. Denominator is next lower mean square variance.

204
Screenometer estimates for Phase II stands are illustrated in figures 1, 2, 3 and 4. Differences among several stands

were apparent. Stands to the right have higher foliage and twig screening than those to the left (fig. 2). Among stands,

comparison of confidence intervals for the means among screenometer estimates suggests that there were significant

differences. Actual tests of differences between stands would have to be conducted to assure statistical reliability of apparent

differences.

Table 3 .-- Analysis of variance for sum m e r I992 nonvegetative

screening 0.0 to 2.8ft aboveground, Ph ase II stands

Source

Degrees

of freedom

Mean

square

Region 2 225.8

Stand*region 9 124.6

Point*stand*region 56 103.5’

Residual 112 58.0

Total 179

* = within each. F-test significantly different: t P<O.O5.

Denominator is next lower mean square variance.

Region and planned treatment

Figure 2.-- Foliage and tw ig scre ening 0.0 to 5.5 ji

aboveground, m ean + 2 standard errors, by

region and planned treatm ent, sum m e r 19 9 2

pretreatm ent conditions, Ph ase II stands.

R e gion: N= north , E= east, S= south

Region and planned treatment

Figure 1 .-- Tree-bole scre ening 0.0 to 5.5fr aboveground,

m ean + 2 standard e rrors by region and

planned treatm ent, sum m e r 19 9 2 pretreatm ent

conditions, Ph ase II stands. R e gion: N=

north , E= east, S= south

Figure 3 .--

Region and planned treatment

Visual penetration 0.0 to 5.5 ji aboveground,

m ean + 2 standard errors, by region and

planned treatm ent, sum m e r 19 9 2 pretreatm ent

conditions, Ph ase II stands. R e gion: N=

north , E= east, S= south
From previous scenic beauty research (Ribe 1989) and studies of screening in east Texas pine stands (Ruddell and others

1989, Rudis and others 1988), we anticipate that scenes with a lower proportion of foliage and twig screening and high

proportion of tree-bole screening and visual penetration will receive the highest scenic beauty ratings. Outcome of scenic

beauty ratings is uncertain for stands and scenes where nonvegetative screening is present.

Nonvegetative

!,y!yd Treebole Visual Foliage and twig *“~~~~~gO

r---------- = . .

treatment

Clearcut E

Group N

Control E

Group E

Clearcut S

Control N

Shelter S

Clearcut N

Group S

Shelter E

Shelter N

Control s

percent

*

0 20 40 60 60

Cumulative frequency (percent)

100

Figure 4.-- Cum ulative m ean value of sum m e r 1992 pretreatm ent visual attributes 0.0 to 5.5 ft aboveground by

scre enom ete r category, region and planned treatm ent, Ph ase II stands. R egion: N= north , E= east, S= south

Winona Plots

M e th oak --Visual attribute conditions were examined from an ongoing plot-level study of silvicultural treatments made

in January, 1989. Each plot was a OS-acre square area centered within a 1. l-acre treated area. Visual attribute estimates

were made in 12 directions for each of 20 plots in summer and winter, beginning in summer (September 1990). For

comparison with Phase II estimates, only summer data are discussed and reported here.

Screening estimates were based on 24 summer observations, comprising 12 sectors and 2 zone views. Sectors were

located systematically and centered at intervals beginning with azimuths at 45 degrees from the azimuth of plot comers

toward plot centers. Sectors were viewed from eight points inward toward the plot center: one at each of 4 comers of the

plot and one half-way between each comer. Four sectors were also measured from the center of each plot with azimuths

directed toward plot edges. Eight photographs were taken along the same azimuths as inward views used in scenic beauty

assessments (Gramamr and Rudis 1994).

Four blocks or landform positions with slopes ranging from 10 to 20 percent referred to elevation and slope aspect

(lower north, middle north, upper north, and upper south) and corresponded to a moisture and potential microclimate or siteproductivity gradient. Plots were assigned to treatments following procedures for a randomized complete block design.

There were four plots harvested using uneven-aged guidelines and one unharvested plot (Control) for each landform.

Treatments included alteration of existing stands to 60 square feet (ft2) of pine basal area (BA) per acre and one of the

following: 30 ft2 BA hardwoods (Scatter 30, S30), 15 ft? BA hardwoods in a grouped condition (Group 15, G15), 15 ft2 BA

hardwoods in scattered condition (Scatter 15, S15), and 0 ft2 BA hardwoods (No hwds). Initial BA ranged from 100 to 130

ft2 BA, with the majority of BA in shortleaf pine trees approximately 70 years old. Hardwood BA consisted chiefly of oak

species approximately 50 years old (Shelton and Murphy 1991). Shelton and Murphy (1990, 1991) provide other details on

pretreatment stand conditions.

206
Results. --F-tests for analysis of variance among screenometer estimates revealed significant differences (table 4). Treebole screening was not significantly different by view zone (P[F] 20.4).

Table 44nalysis of variance for sum m e r 19 9 0 visual attributes by screenom ete r category, W inona plots

Mean square variance by category

Degrees Tree Foliage

Source of freedom boles and twigs

Landform 3 42.4 4,200.0*

Treatment 4 1.782.6’ 3,736.8*

Zone 1 77.3 85,218.6$

Zone by treatment 4 19.8 5.850.4’

Experimental design 27 137.4 793.8’

Residual 440 161.3 381.0

-

Total 479

F-test significantly different: t P < 0.05, $ P < 0.01. Denominator is residual sampling variance for the experimental

design and experimental design for other variances.

Visual

penetration

2,902.ot

1,997.O’

68,782.3$

6.297.3’

553.1’

356.8

Tree-bole screening means were significantly different (P 1 t i < 0.05) between substantially undisturbed (Control and

S30) and more disturbed (G15, S 15, and No hwds) plots (fig. 5). Zone differences were significant for foliage and twig

screening (fig. 6) and visual penetration (fig. 7). Differences were largest for foliage and twig screening between untreated

(Control) and disturbed plots in the upper zone, and among substantially undisturbed (Control and S30), somewhat disturbed

(G15 and S 15), and more disturbed (No hwds) plots in the lower zone (fig. 6). The three visual attributes are summarized

in figure 8.

All zones

bc b

t

c

t

t

Distance zone aboveground

100 0.0 to 2.8 ft 2.9 to 5.5 it

90 -- a

3 80-- P

b b

70

--

> tt

t

z 6%

Treatment (sq lt BA hwd retained) Treatment (sq R BA hwd retained)

Figure 5. -- Tree-bole screening 0.0 to 5.5 ft aboveground,

mean +2 standard errors by treatment, summer

1990, Winona plots . Means with the same letter

are not significantly difSerent (P 1 t 1 > 0.05)

Figure 6. -- Foliage and twig screening, mean +2 standard

errors, by treatment and zone (distance

aboveground), summer 1990, Winona plots.

Means with the same letter are not significantly

different (P 1 t i > 0.05)

207
Distance axte aboveground

0.0 tc 2.8 ft 2.9 to 5.5 R

I Treatment (sq R BA hwd retained)

Figure 7.-- Visual penetration, mean +2 standard errors,

by treatment and zone (distance aboveground),

summer 1990, Winona plots. Means with the

same letter are not significantly different

(Pit1 >0.05)

Landform variance was significant for foliage and twig

screening and visual penetration. Differences were largest

between lower and upper Iandform positions (fig. 9). The

experimental design variance was significant. Because

landform interaction was not replicated, statistical

examination of interaction with other sources of variation

was not possible. Mean values among the three visual

attributes varied widely by treatment and landform (fig. 10).

lIeatment

(sq ft BA hwd

retained)

Control

Scatter 30

Group 15

Scatter 15

No hwds 0

Tree-bole Visual

yniW penetration

Figure 9.--

Landform position and elevation (St)

Visual penetration and foliage and twig

screening, mean +2 standard errors, by

landfotm position and elevation, summer 1990,

Winona plots. Within each visual attribute,

means with the same letter are not significantly

different (P 1 t i > 0.05)

Distance zone

Foliage and twig

aboveground

screening

Control

Scatter 30

Group 15

Scatter 15

No hwds 0

20 40 60 60

Cumulative frequency (percent)

2.9 to 5.5 it

Figure 8.-- Cumulative mean value of summer 1990 visual attributes by screenometer and zone (distance aboveground)

category, Winona plots

208
Treatment

(sq ft BA hwd Tree-bo’e

Visual Foliage and twig

ktkned) , =yning penytration screyning Position

Control

sao

G15

515

No hwds

Upper south

Control

530

G15

s15

No hwds

Control

s30

G15

515

No hwis

Middle north

Control

530

G15

515

Lower north

LFiYXlZ~_

20 40 60 80 100

Cumulative frequency (percent)

Figure lo.-- Cumulative mean value of summer 1990 visual attributes by screenometer category, treatment, and landform

position, Winona plots

DISCUSSION AND CONCLUSIONS

No significant vegetative screening and visual penetration differences between upper and lower zones in pretreatment

Phase II stands or Winona control plots were found. Only disturbed plots had significant zonal differences. We hypothesize

that Phase II stand-level treatments will create zonal differences in summer visual attributes. The lack of differences among

zones may be a useful gauge of a stand’s recovery from treatments for comparable pine-hardwood stands in the Ouachita

Mountains. Significant summer visual attribute differences between zones may be indicative of recent disturbance. With

additional study elsewhere, visual attribute zone differences could serve as disturbance detection indices for stands with no

known historical records.

Phase II Stands

Although the pretreatment sample design for Phase II stands considered point location as a random effect, significant

differences in visual attributes were noted among sample points within stands. This finding suggests the need to further

characterize point-location attributes and to consider points as fixed effects after treatments have been applied. Additional

examination of visual attributes and scenic beauty measures by point before and after treatment may reveal significant

differences in the diversity of scenic beauty values within stands.

Nonvegetative screening as a visual attribute may be important in estimating scenic beauty ratings and treatments in

stands with steep terrain. However, previous visual attribute studies either occurred on gentle slopes, flat topography, or

did not separate view zones. Group north, located on one of Arkansas’ highest elevations (Mount Magazine), was one of

the few stands with nonvegetative screening and the only stand examined with > 1 -percent nonvegetative screening. Group

north’s location, steep slopes, limited occurrence of understory foliage and twigs, and lack of obvious evidence of prior

cutting activity (Rudis, personal observation) may make it unique in comparison to other stands in this study.

Winona Plots

Winona plot analysis indicated that foliage and twig screening in the lower zone view increases and visual penetration

decreases with stand disturbance. Two-year old disturbances continued to maintain greater visual penetration above 2.8 ft.

209
The increase in sunlight and subsequent vegetative growth could account for most of the decline in visual penetration in the

lower zone. The potentially drier and less fertile microclimate on higher landform positions may account for reduced foliage

and twig screening and increased visual penetration when compared with lower landform positions.

Having no estimates of visual attributes before disturbance and no replication of landform interaction, we can only

speculate on the landform relationship with treatment. We hypothesize that the favorable microclimate in the middle north

and lower north landform positions enhances the vegetative recovery of recently disturbed forests, resulting in greater foliage

and twig screening than in upper north and upper south positions. In future studies, sampling designs that permit statistical

tests of the relationship among landform, treatment, and zones would be desirable.

From personal observation, some debris and forest floor disturbance from treatment activities were present. Debris

included dead twigs, branches, and tree tops--all of which was included in foliage and twig screening. Scenic beauty ratings

for Winona plots decline with increasing intensity of disturbance (Gramarm and Rudis 1994). We conclude that, two growing

seasons after disturbance, mitigating disturbance impacts on esthetics include removal of debris associated with lower zone

foliage and twig screening.

The choice between retaining 15 ft* of hardwoods scattered (S15) or grouped (G15) is important from a silvicultural

perspective and may be important from an esthetics perspective. From scenic beauty evaluation, G15 yields higher scenic

beauty ratings (Gramann and Rudis 1994). Statistical tests for each of the three visual attributes failed to distinguish

significant differences for foliage and twig screening (P 1 t 1 = 0.38) and visual penetration (P 1 t 1 = 0.63). However, there

was a marginally significant (P} t 1 = 0.07) and higher proportion of tree boles visible in the grouped than in the scattered

treatment. We know that tree-bole screening contributes positively to scenic beauty ratings (Rudis and others 1988), and

conclude that grouping hardwoods has a marginal esthetic advantage. The mechanism remains unclear, however. We

suggest group retention of hardwoods increases the number of views dominated by tree boles, on average, when compared

with views from areas where retention of hardwoods is scattered.

Mitigating silvicultural alternatives might include retaining shade-producing overstory trees to suppress summer growth

of understory foliage, periodic removal of unwanted foliage that screens the view, and removal of downed woody material

from the forest floor. However, downed woody material assessment, examination of visual attributes in other seasons after

plots have recovered from disturbance, and more detailed investigation of landform position are warranted. Such studies

are needed before recommendations can be generalized beyond this initial examination.

ACKNOWLEDGMENTS

We thank Darren Austin and Rhonda Houston for field assistance, the Wildlife Research Group for establishing the bird

census points, Tim Mersmann and Jim Guldin for logistics, and Mike Freed for organizational assistance with Ouachita and

Ozark National Forest stands. For the Winona plots, we thank Mike Shelton and his field crew for study site establishment

and silvicultural details, Ron Thill’s wildlife group for control plots, and Winona Ranger District personnel for logistics.

Mike Shelton and Bernie Parresol provided helpful suggestions in a review draft of this report. Financial support was

provided by the authors’ cooperating institutions and the New Perspectives and Ecosystems Management Research program

administered by Jim Baker.

REFERENCES CITED

Baker, James B. 1994. An overview of stand-level ecosystem management research in the Ouachita/Ozark National

Forests. In: Baker, James B., ed. Ecosystem management research in the Ouachita mountains: pretreatment conditions

and preliminary findings; 1993 October 26-27; Hot Springs, AR. Gen. Tech. Rep. New Orleans, LA: U.S. Department

of Agriculture, Forest Service, Southern Forest Experiment Station.

Daniel, T.C.; Boster, R.C. 1976. Measuring landscape aesthetics: the scenic beauty estimation method.

Res. Pap. RM-167. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and

Range Experiment Station. 66 p.

Gramann, James H. ; Rudis, Victor A. 1994. Effect of hardwood retention, season, and landform on perceived scenic

beauty. In: Baker, James B., ed. Ecosystem management research in the Ouachita mountains: pretreatment conditions

and preliminary findings; 1993 October 26-27; Hot Springs, AR. Gen. Tech. Rep. New Orleans, LA: U.S. Department

of Agriculture, Forest Service, Southern Forest Experiment Station.

210
Herrick, Theresa A.; Rudis, Victor A. 1994. Visitor preference for forest scenery in the Ouachita National Forest.

In: Baker, James B., ed. Ecosystem management research in the Ouachita mountains: pretreatment conditions and

preliminary findings; 1993 October 26-27; Hot Springs, AR. Gen. Tech. Rep. New Orleans, LA: U.S. Department of

Agriculture, Forest Service, Southern Forest Experiment Station.

Kluender, Richard A.; Lortz, David A.; Stokes, Bryce J. 1994. Production time, total costs and residual damage at

varying harvest intensities. In: Baker, James B., ed. Ecosystem management research in the Ouachita mountains:

pretreatment conditions and preliminary findings; 1993 October 26-27; Hot Springs, AR. Gen. Tech. Rep. New Orleans,

LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station.

Petit, Daniel R.; Petit, Lisa J.; Martin, Thomas E.; Thill, Ronald E.; Taulman, James F. 1994. Breeding birds of

late-rotation pine-hardwood stands in Arkansas and Oklahoma: community characteristics and similarity to other regional

pine forests. In: Baker, James B., ed. Ecosystem management research in the Ouachita mountains: pretreatment

conditions and preliminary findings; 1993 October 26-27; Hot Springs, AR. Gen. Tech. Rep. New Orleans, LA: U.S.

Department of Agriculture, Forest Service, Southern Forest Experiment Station.

Ribe, R.G. 1989. The aesthetics of forestry: what has empirical preference research taught us?

Enviromnental Management. 13(l): 55-74.

Ruddell, Edward J.; Gramarm, James H.; Rudis, Victor A.; Westphal, Joanne M. 1989. The psychological utility

’ of visual penetration in forest scenic beauty models. Environment and Behavior. 21(4):393-412.

Rudis, Victor A. 1985. Screenometer: a device for sampling vegetative screening in forested areas.

Canadian Journal of Forest Research. 15: 996-999.

Rudis, Victor A.; Gramann, James H. 1990. Amenity impacts and seasonal dynamics of mixed pine-hardwood stand

management. Study 4810 FS-SO-4801-1-90-31. On file with: Southern Forest Experiment Station, 701 Loyola Avenue,

New Orleans. LA 70113.

Rudis, Victor A.; Gramarm, James H.; Ruddell, Edward J.; Westphal, Joanne M. 1988. Forest inventory

and management-based visual preference models of southern pine stands. Forest Science. 34(4): 846-863.

Rudis, Victor A.; Gramann, James H.; Whisenant, Steven G; Loh, Douglas K. 1991. Amenity impacts and

seasonal dynamics mixed pine-hardwood stand management: visual quality evaluation and modeling of reproduction

cutting methods. Study 4810 FS-SO-4801-1-90-31. Problem 1, addendum B. On file with: Southern Forest Experiment

Station, 701 Loyola Avenue, New Orleans, LA 70113.

Rudis, Victor A.; Herrick, Theresa; Freed, Michael. 1991. Amenity impacts and seasonal dynamics of mixed

pine-hardwood stand management: even-aged stands. Study 4810 FS-SO-4801-90-31. Problem 1, addendum C. On file

with: Southern Forest Experiment Station, 701 Loyola Avenue, New Orleans, LA 70113.

Rudis, Victor A.; Ray, Rebecca J.; Cengel, Dermis J.; Clark, James D.; Watson, William F.; Stokes, Bryce J. 1993.

Visual impact of recently cut stands on intermediate-view forest scenes: a benefit-cost comparison of alternative harvest

regimes. Study 4810 FS-4801-1-93-I. On tile with: Southern Forest Experiment Station, 701 Loyola Avenue, New

Orleans, LA 70113.

SAS Institute Inc. 1990. SASISTAT user’s guide. Version 6, 4th ed. Chapter 24: the GLM procedure.

Cary, NC: SAS Institute, Inc.: 892-996. Vol. 2.

Shelton, Michael G.; Murphy, Paul A. 1990. Uneven-aged management of shortleaf pine in the Ouachita National

Forest: effects of maintaining a hardwood component during conversion from even-aged management. Progress report

4110 FS-SO-4106-63. On file with: Southern Forest Experiment Station, 701 Loyola Avenue, New Orleans, LA 70113.

Shelton, Michael G.; Murphy, Paul A. 1991. Age and size structure of a shortleaf pine-oak stand in the Ouachita

Mountains--implications for uneven-aged management. In: Coleman, Sandra S.; Neary, Daniel G., camps. Proceedings

of the 6th biennial southern silvicultural research conference; 1990 October 30-November 1; Memphis, TN. Asheville,

NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station: 616-629. Vol. 2.

211
Visitor Preference for Forest Scenery in the Ouachita National Forest’

Theresa A. Herrick and Victor A. Rudis?

ABSTRACT

The majority of forest visitors interviewed between June through October 1991 and April

through October 1992 preferred forest scenery that was “undisturbed,” contained a

“variety of natural features, ” or was associated with “natural” or “beauty” descriptions.

Few respondents preferred “younger tree species with open areas. ” Results suggest that

undisturbed conditions are important along with vegetation management to support a

variety of natural features. Slight differences are noted when examining preferences by

respondents’ sex, age class, education level, principal recreation activity, month visited,

and sites where interviewed. The order of questions appeared to affect the respondents’

forest scenery descriptions. Interviews were conducted as part of an onsite survey

involving a larger recreation-user study (CUSTOMER survey) for sites among four

USDA Forest Service Ouachita National Forest ranger districts. Recommendations are

made for using CUSTOMER survey data in future forest scenery preference research.

INTRODUCTION

The U.S. Department of Agriculture, Forest Service (USDA-FS), National Forest System, is charged with managing

it’s nearly 200 million acres of public land under a multiple-use philosophy. Recreation is one of the identified multiple uses.

To adequately plan for recreation, public land managers need data describing the characteristics and preferences of recreating

visitors.

To provide information about recreational use and users of public land, an interagency, multidisciplinary group of

scientists, planners, and policy analysts developed tools and procedures necessary for the task. The result of this effort was

the Public Area Recreation Visitor Survey (PARVS) developed and tested in 1985 by the Outdoor Recreation and Wilderness

Assessment Group (ORWAG) of the USDA-FS Southeastern Forest Experiment Station (Reed and others 1992). Data were

collected on recreation activities, recreation trips, expenditures, demographics, and satisfaction with services and facilities.

PARVS was later modified to obtain information about special issues identified by forest managers and believed to be

important for particular sites. The revised PARV surveys became known as CUSTOMER surveys. CUSTOMER surveys

were conducted for selected Ouachita National Forest sites in 1991 and 1992.

Parallel to CUSTOMER surveys, scientists from the visual quality research group associated with the New Perspectives

(now Ecosystem Management) research team (Rudis and others 1994) began a study of various silvicultural treatments and

their visual impacts. The ORWAG team and the visual quality research group made an effort to coordinate research activities

for CUSTOMER survey sites on the Ouachita National Forest. However, due to budget and interview-time restrictions,

flexibility in the use of additional questions and alternative sampling procedures was limited. As a compromise, two short

questions were added to the special issues section: one ranking preferences for forest descriptions and another describing

preferred forest scenery.

Presented in this report are initial findings of these two questions added to the special issues section. The primary goal

is to describe the scenery preferences of CUSTOMER survey respondents by site and the utility of simplified survey

questions to respondents’ scenic preferences. A secondary goal is to develop likely hypotheses regarding differences in

scenic preferences that vary with forest visitor demographics, principal recreation activity, month of visit, and survey site

location.

’ Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment

Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

’ Associate professor and head, Department of Recreation and Park Administration, Arkansas Tech University, Russellviile,

AR 72801-2222; research forester, Forest Inventory and Analysis Unit, USDA Forest Service, Southern Forest Experiment

Station, Starkville, MS 39759-0906, respectively.

212
SURVEY SITES AND SAMPLING DESIGN

Survey sites were located in four ranger districts in the Ouachita National Forest. During the summer and fall of 1991,

forest visitors were surveyed at 12 locations in or near the Winding Stair National Recreation Area (NRA) within Kiamichi

ranger district in Oklahoma. In 1992, visitors were surveyed in Arkansas at 10 locations: 2 in the Caddo ranger district at

Little Missouri Falls and Albert Pike Recreation Area; 1 in the Mena ranger district at Shady Lake; and 7 in or near Lake

Sylvia on the Winona ranger district. A complete list of locations for both years appears in table 1.

Table 1 .--0uachita National Forest sites and locations w h e re CUSTOMER survey inte rview s w e re conducted in 19 9 1 and 19 9 2

Site, ranger district (RD), time period, and survey locations

Winding Stair National Recreation Area,

June through October 1991

- Equestrian Campground

- Billy Creek

- Winding Stair

- Cedar Lake South

- Cedar Lake North

- Ctdar Lake Shady

- West End Vista

- Emerald Vista

- Kerr

- Horsethief and Ouachita Junction

- Cedar Lake Dam

- Cedar Lake Southshore

Kiamichi RD

Lake Sylvia, Winona RD

April through October 1992

- Lake Sylvia campground

- Lake Sylvia beach and picnic area

- Ouachita National Recreation Trail, trailhead

- Trees of Forest Trail parking lot

- Flatside/Pinnacle Vista parking lot

- Winona Scenic Drive, FS #132

- Lake Winona Road FS #778

Caddo, Caddo RD

June through August 1992

- Little Missouri Falls

- Albert Pike Recreation Area

Mena, Mena RD

June through August 1992

- Shady Lake

Visitors responded to a 20-minute onsite interview that included a special issues section. Nearly all visitors encountered

participated in the survey3. These onsite surveys served as an exit interview of visitors who had completed or nearly

completed their visits. Details on nonscenery questions and other responses from both onsite interviews and a related

followup mail questionnaire are reported elsewhere (Coker and others 1993a, 1993b; Reed and others 1992).

In 1991, the survey instrument was split into two versions. Both versions contained identical demographic and trip

profile sections. One version also contained questions about other onsite activities, contingent valuation, and the National

Satisfaction Index. Another version contained an annual activity profile and the special issues section. An example of the

special issues section for the Winding Stair NRA is found in the Appendix. In 1992, all the survey instruments were the

same, and all onsite surveys contained a special issues section.

Examined in this report are two questions about forest scenery in the special issues section: (1) What type of scenery

do you prefer in a forest environment? and (2) What words would you use to describe your preference in forest scenery?

The two questions were asked in their present order for Winding Stair NRA and Lake Sylvia sites; reverse order was used

for the Caddo and Mena sites.

For the first question, respondents were asked to rank forest descriptions in order of preference from “1” (most

preferred) to “5” (least preferred). Results are reported for the one description comprising the majority of responses that

were most preferred; i.e., ranked “1” or “2” out of 5, for each of the sites surveyed. A second description is listed if one

description did not comprise the majority of responses. Forest descriptions provided were:

_ Undisturbed.

Large mature trees.

-- Trees of mixed sizes and species.

- Younger tree species with open areas.

- Variety of natural features (cliffs, rocks, water, etc.).

’ CUSTOMER survey staff, 1993 pers. comm. to senior author by phone, Athens. GA: USDA-FS, Outdoor Recreation and

Wilderness Assessment Research Unit.

213
For the second question, a content analysis of responses was performed using PROC CONTENT (SAS Institute, Inc. 1989).

Results are reported by survey site for the most frequently used word and word combinations.

RESULTS

Ranked Forest Descriptions and Demographics

Table 2 presents the distribution of forest descriptions by rank for Winding Stair NRA. Most (71 percent) respondents

indicated “variety of natural features” as the preferred forest scenery. The majority of respondents were males (63 percent),

between the ages of 31 and 50 years old (65 percent), and who had completed high school or some college courses (64

percent). The majority were interviewed in July (53 percent) (table 3). Median preferences among demographic classes

were for “variety of natural features” (table 3). Principal recreation activities of respondents were sightseeing (41 percent),

followed by developed camping (25 percent), and other activities (33 percent) (table 4). Differences in preferred scenery

were suggested, with sightseeing respondents preferring “variety of natural features” (77 percent) and developed campers

preferring “undisturbed” scenery (63 percent) (table 4).

Respondent preferences at the Lake Sylvia site differed from those at Winding Stair NRA. The majority preferred

“undisturbed” scenery; “large mature trees” and “trees of mixed sizes and species” were also important (table 5).

Respondents were predominantly males (60 percent), between the ages of 21 to 50 years old (77 percent), and who had

completed high school or some college courses (68 percent). The majority were interviewed in June and July (69 percent)

(table 6). Median preferences among demographic classes were for “undisturbed” scenery and “large mature trees” (table

6). Principal recreation activities among respondents were camping (33 percent) and swimming (24 percent), followed by

18 other activities (43 percent) (table 7). Some variation in preferences existed among recreational activities.

Table 8 presents the distribution of forest descriptions by rank for the Caddo site. The majority (66 percent) of

respondents indicated “undisturbed” as the most preferred forest scenery. The majority of respondents were males (65

percent), between the ages of 3 1 and 50 years old (57 percent), and who had completed high school or some college courses

(65 percent). The majority were interviewed in August (52 percent) (table 9). Median preferences among demographic

classes were for “undisturbed’ scenery. Principal recreation activities among respondents were camping (49 percent) and

sightseeing (22 percent), followed by eight other activities (28 percent) (table 10). Differences in scenery preferences

between “variety of natural features” and “undisturbed” were slight, as both were closely ranked.

Respondent preferences at the Mena site were similar to those for Winding Stair NRA and the Caddo site. The majority

indicated preference for “undisturbed” scenery, with “variety of natural features” competing for second place (table 11).

Respondents were predominantly males (73 percent), between the ages of 31 and 50 years old (65 percent), and who had

completed high school or some college courses (60 percent) (table 12). The majority were interviewed in July (85 percent)

(table 12). Median preferences among age classes and education completed were for “undisturbed,” “variety of natural

features, ” and “trees of mixed sizes and species” (table 12). Principal recreation activities among respondents were camping

(89 percent) and sightseeing (4 percent), followed by five other activities (7 percent) (table 13). The majority of campers

preferred “undisturbed” scenery.

Comparisons of forest scenery preferences among the four sites were made by comparing modal rank; i.e., the rank

associated with the maximum number of respondents. Modal rank for the “undisturbed” forest description is I (most

preferred) for all sites (tables 2, 5, 8, and 11). Comparisons suggest that there are important differences in other preferences

between Lake Sylvia and other sites. “Large mature trees” has a modal rank of 2 for Lake Sylvia and 3 for the other sites.

“Trees of mixed sizes and species” has a modal rank of 2 for Lake Sylvia and 4 for other sites. “Younger tree species with

open areas” has a modal rank of 3 at Lake Sylvia and 5 at other sites. “Variety of natural features” has a modal rank of

4 at Lake Sylvia and 1 at other sites.

Other modal rank comparisons suggest little difference in demographics (tables 3, 6, 9, and 12). A notable difference

exists in principal activities between the variety of activities at Lake Sylvia and the prominence of sightseeing at Winding

Stair NRA when compared with other sites (tables 4, 7, 10, and 13). Data in tables 2, 5, 8, and 11 illustrate a lack of

response for forest descriptions from some forest visitors.

214
Table 2.-- Forest scenery prefe rences by forest description and rank

(I =nw st prefe rre d ) in W ind ing Stair NRA, 19 9 1. sam ple

size = 78

Forest description

Rank Not

1 2 3 4 5 ranked

- - - frequency of responses- - -

Undisturbed 24 18 11 13 9 3

Large mature trees 14 20 26 12 3 3

Trees of mixed sixes

and species 10 14 18 29 4 3

Younger tree species

with openareas 1 1 9 I 51 3

Variety of natural features

(cliffs, rocks, water, etc.) 29 24 9 12 1 3

Table 3 .-- Prefe rred (ranked first or second out offive ) forest descriptions Table 4.-- Prefe rred (ranked first or second out offive ) forest descriptions

for a m ajority of respondents by sex, age, education, and m onth for a m ajority of respondents by principal activity, W inding

of inte rview , W inding Stair NRA, 19 9 1 Stair hRA,19 9 1

Demographic Sample Maioritv preferred Principal Sample Maioritv preferred

categoty size Description Frequency activity size Description Frequency

All respondents 75

Sex

Male

Female

41 Variety of natural features 32

28 Variety of natural features 21

Age class

11-20

21-30

31-40

41-50

51-60

61-70

71-80

3 Undisturbed 3

11 Undisturbed 9

15 Variety of natural features 10

23 Variety of natural features 14

11 Variety of natural features 8

8 Undisturbed 6

4 Undisturbed 4

Education completed

5 8th grade 1

Some high school 3

High school 22

Some college 26

Associate degree 13

Bachelor degree 10

Month of interview

June 22

July 40

August 5

October 8

Variety of natural features

Undisturbed

Large mature trees

Variety of natural features

Variety of natural features

Variety of natural features

Undisturbed, variety of

natural features

Variety of natural features

Variety of natural features

Undisturbed, variety of

natural features

Variety of natural features

53 All respondents 75

Sightseeing 31

Developed camping 19

Horseback riding 11

Day hiking 3

Fishing 3

Backpacking 2

Primitive camping 2

Bicycling 1

Hunting 1

Swimming 1

Wildlife observation 1

1

3

16

18

12

6

16

27

4

6

Variety of natural features

Variety of natural features

Undisturbed

Variety of natural features

Variety of natural features

Large mature trees

Undisturbed

Trees of mixed sixes and species,

variety of natural features

Trees of mixed sixes and species

Large mature trees

Trees of mixed sizes and species

Undisturbed

53

24

12

8

3

3

2

215
Table 5.-- Forest scenery prefe rences by forest description and rank

(I = m ost prefe rred), L.ak e Sylvia, 19 9 2, sam ple size = 283

Forest description

Rank Not

1 2 3 4 5 ranked

Undisturbed

Large mature trees

Trees of mixed sixes

and species

Younger tree species

with open ateas

Variety of natural features

(cliffs, rocks, water, etc.)

- - - frequency of responses- - -

127 26 25 6 81 18

58 78 42 17 70 18

31 94 70 31 39 18

16 43 102 44 60 18

33 24 26 167 15 18

Table 6.-- prefe rred (ranked first or second out offve ) forest descriptions Table 7.-- Prefe rred (ranked first or second out ofjive ) forest descriptions

for a m ajority of respondents by s ex, age, education, and m onth for a m ajori of respondents by principal activiry, Luke Sylvia,

of inte rview , Lake Sylvia, 19 9 2 19 9 2

Demographic Sample Maioritv preferred Principal Sample Maiorih, preferred

categoty size Description Frequency activity size Description Frequency

All respondents 265

&TX

Male 159

Female 106

Age class

1 l-20 11

21-30 49

3140 97

41-50 59

51-60 32

61-70 14

71-80 3

Education completed

5 8th grade 4

Some high school 18

High school 89

Some college 91

Associate degree 38

Bachelor degree 26

Month of interview

April 25

May 32

June 83

July 101

August 18

September 6

Undisturbed 153

Undisturbed 93

Undisturbed 60

Undisturbed

Undisturbed, trees of mixed

sixes and species

Large mature trees

Large mature trees

Undisturbed

Undisturbed

Undisturbed

Trees of mixed sixes and species 3

Undisturbed 11

Undisturbed 16

Undisturbed 18

Large mature trees 12

Undisturbed 16

Undisturbed 14

Large mature trees 20

Large mature trees 46

Undisturbed 61

Undisturbed, large mature trees 10

Undisturbed 5

7

25

57

34

24

9

2

All respondents 265

Camping 87

Swimming 64

Running or jogging 25

Relaxing

Picnicking

Family gathering

Day hiking

Fishing

Backpacking

Sightseeing

Leading a group

Sunbathing

Natnre study

Walking

Berry picking

Getting wood

Horseback riding

Joy riding

20

17

14

7

5

5

1

4

3

2

2

1

1

1

1

Small game hunting 1

Volleyball 1

Undisturbed

Undisturbed, large mature trees

Undisturbed

Undisturbed, trees of mixed

sixes and species

Undisturbed, trees of mixed

sizes and species

Undisturbed, trees of mixed

sixes and species

Trees of mixed sizes and species

Undisturbed

Large mature trees

Undisturbed

Undisturbed

Large mature trees

Large mature trees

Younger tree species with open

areas, undisturbed areas

Large mature trees, younger tree

species with open areas

Large mature trees

Undisturbed

Trees of mixed sixes and species

Undisturbed

Trees of mixed sixes and

species, undisturbed

Large mature trees

153

49

44

15

11

11

9

5

4

3

2

3

3

1

1

1

1

1

1

1

1

216
Table 8.-- Forest scenery prefe rences by forest description and rank

( 1 = m ost prefe rred), Caddo, 19 9 2, sam ple size = 139

Rank Not

Forest description 1 2 3 4 5 ranked

- - - frequency of responses - - -

Undisturbed 63 28 13 24 10 1

Large mature trees 14 44 49 25 5 2

Trees of mixed sizes

and species 12 21 43 52 3 2

Younger tree species

with areas open 0 7 3 16 109 4

Variety of natural features

(cliffs, rocks, water, etc.) 50 33 30 18 8 0

Table 9.-- Prefe rred (ranked first or second out offive ) forest descriptions Table lo.-- Prefe rred (ranked first or second out offive ) forest descriptions

for a m ajority of respondents by sex. age, education, and m onth for a m ajority of respondents by principal activity, Caddo,

of inte rview , Caddo, 19 9 2 19 9 2

Demographic Sample Majorih, preferred Princ,ipal Sample Maioritv preferred

category size Description Frequency activity size Description Frequency

All respondents 139

Sex

Male 90

Female 48

Age class

11-20 6

21-30 21

31-40 47

41-50 32

51-60 13

61-70 15

71-80 2

81-90 I

Education completed

2 8th grade 3

Some high school 11

High school 48

Some college 42

Associate degree 19

Bachelor degree 15

Month of interview

June 6

July 60

August 72

Undisturbed 91 All respondents 139 Undisturbed 91

Undisturbed 63

Variety of natural features 33

Variety of natural features 4

Undisturbed 15

Undisturbed 31

Undisturbed 22

Undisturbed 11

Undisturbed 9

Variety of natural features 1

Younger tree species with open areas 1

Large mature trees, variety

of natural features

Undisturbed

Undisturbed

Undisturbed

Variety of natural features

Variety of natural features

Undisturbed 5

Undisturbed 45

Variety of natural features 47

2

7

32

33

11

12

Camping

Sightseeing

Swimming

Picnicking

Family gathering

Walking

68 Variety of natural features 45

31 Undisturbed, variety of natural features 22

21 Undisturbed 15

9 Variety of natural features 6

3 Variety of natural features 2

2 Variety of natural features,

large mature trees 1

1 Variety of natural features 1

1 Variety of natural features 1

Backpacking

Relaxing

Running or jogging 1 Variety of natural features 1

Fishing 1 Variety of natural features 1

217
Table 1 l.-- Forest scenery prefe rences by forest description and rank

(1 =most prefe rre d ), M e na, 19 9 2, sam ple size=87

Forest description 1

Rank

2 3 4 5

Not

ranked

- - - frequency of responses- - -

Undisturbed 38 13 7 20 7 2

Large mature trees 9 26 33 10 2 I

Trees of mixed sixes

and species 10 21 21 27 1 I

Younger tree species

with areas open 2 1 3 8 65 8

Variety of natural features

(cliffs, rocks, water, etc.) 28 21 16 13 3 6

Table 12.-- Pr@ erre d (ranked first or second out offve ) forest descriptions

for a m ajority of respondents by sex, age, education, and

m onth of inte rview , Mena. 19 9 2

Demographic

category

Sample

size

Maioritv preferred

Description Frequency

All respondents 85 Undisturbed

Sex

Male

Female

62 Undisturbed

23 Undisturbed

Age class

11-20 2

21-30 8

31-40 33

41-50 23

51-60 9

61-70 8

71-80 2

Education completed

5 8th grade 3

Some high school 7

High school 25

Some college 26

Associate degree 18

Bachelor degree 6

Variety of natural features

Variety of natural features

Undisturbed, variety of natural features

Undisturbed, variety of natural features

Undisturbed

Undisturbed, variety of natural features

Undisturbed

Undisturbed

Undisturbed

Trees of mixed sizes and species,

variety of natural features

Undisturbed

Variety of natural features

Undisturbed

Month of interview

June 7

July 12

August 6

Undisturbed 6

Variety of natural features 42

Undisturbed 6

51

38

13

2

6

18

22

7

5

2

3

5

14 .

17

12

5

Table 13 .-- Prefe rred (ranked first or second out ofjive ) forest descriptions

for a m ujoriry of respondents by principal activiry, Mena. 19 9 2

Principal

activity

Sample

size

Maioritv preferred

Description Frequency

Ah respondents 85 Undisturbed 51

Camping 76 Undisturbed 46

Sightseeing 3 Undisturbed, variety of natural features 2

Swimming 2 Undisturbed, variety of natural features 1

Backpacking 1 Variety of natural features 1

Family gathering 1 Undisturbed 1

Picnicking 1 Undisturbed 1

No purpose 1 Variety of natural features 1

218
Content Analysis of Forest Scenery Preferences

Contents of forest scenery preferences described by respondents are reported in table 14. All word and word

combinations comprising 5 percent or more of the responses are listed. Differences by order of the question presented, i.e.,

after and before the question about ranking of supplied forest descriptions, are apparent.

After Ranking Forest Descriptions

(Winding Stair NRA and Lake Sylvia sites).--Words occurring 10 percent or more included “tree,” “natural,”

“undisturbed,” and “variety”--all of which were listed in the previous survey question. Word combinations included “mixed

variety, ” “hills or mountains,” and “large trees.”

Before Ranking Forest Descriptions

(Caddo and Mena sites).--Words occurring 10 percent or more included “beauty,” “natural,” “as is,” “quiet,” and

“trees. ”I “Beauty” and “as is” are difficult to translate into management terms. No word combinations appeared that

represented 10 percent or more of the responses.

Table‘14.-- Fre quently-used w ord or w ord com binations given in answ e r to “W h at w ords w ould you use to describe yourprefe rence in forest scenery?”

by order of q uestion, site, and respondent frequency

Order of question,

site, and number of respondents Word

Frequency

(percent)

word

combinations

Frequency

(percent)

After ranking forest descriptions

Winding Stair NRA,

all respondents=78

Tree 33 (42)

Natural 32 (41)

Undisturbed 21 (27)

Variety 14 (18)

Mixed variety

Hills (and, or) mountains

Large trees

18 (23)

12 (15)

10 (13)

Lake Sylvia,

all respondents = 283

Natural

Undisturbed

Trees

Wild

Variety

Scenic

Mountains

Clean

76 (27)

70 (25)

51 (18)

22 (8)

22 (8)

19 (7)

16 (5)

13 (5)

All water

Hills (and, or) mountains

12 (9)

12 (9)

Before ranking forest descriptions

Caddo, Beauty 82 (59)

all respondents = 140 Natural 71 (51)

As is 20 (14)

Trees 12 (9)

Mountain 11 (8)

Clean 10 (7)

Quiet 9 (6)

All water

Hills (and, or) mountains

12 (9)

12 (9)

Mena,

all respondents = 87

Beauty

Natural

As is

Quiet

Trees

41 (47) All water 7 (8)

40 (46) Hills (and, or) mountains 4 (5)

11 (13)

11 (13)

10 (11)

219
DISCUSSION AND CONCLUSIONS

The questions added to the CUSTOMER survey provide insight into respondents’ preferences for forest scenery and

forest descriptions. The majority of respondents preferred “undisturbed,” “variety of natural features,” “natural,” or

“beauty” forest descriptions. Variation existed in preferences by principal activity, user characteristics, recreation activity,

and sites surveyed. “Younger tree species with open areas” was associated with few activities and few respondent

preferences.

Results are consistent with findings for other recreation area studies in which visitors preferred conditions that were

natural, but parklike, with some vegetation management that limits understory vegetation density (Hammitt 1988, Ulrich

1977). Findings in our study indicate that natural, undisturbed scenes are preferred. Vegetation management also is

important--primarily to maintain a variety of natural features.

It should be emphasized that forest descriptions are not mutually exclusive, as more than one description can be used

for each site. However, the prevalence of high ranks for “undisturbed” and “variety of natural features” and low ranks for

“younger tree species with open areas” suggests a consensus among respondents for the meaning of these phrases.

Notable are majority preferences for “large mature trees” and “trees of mixed sizes and species” for some principal

activity categories at Lake Sylvia. Also, a large proportion of respondents at Lake Sylvia ranked secondary preferences at

odds with the majority at other sites. Reasons for these differences are many, some of which were gleaned from

CUSTOMER survey reports (Coker and others 1993a, 1993b; Reed and others 1992). Lake Sylvia sample locations were

more numerous and diverse, associated with more diverse principal activities, tied to more developed areas, associated with

more out-of-state visitors, and was, perhaps, better known than other sites in the CUSTOMER survey.

Preferred forest descriptions associated with particular recreation activities appear inconsistent among sites. Small sample

size precluded detailed examination by site and activity. Sampling was not designed to compare differences among sites,

as surveys were conducted at different times of the year. Because the primary goal was to describe results by site, it was

decided not to combine the data or categories for this initial examination. For future analyses, combining data from all sites

to provide a larger sample and to conduct additional analyses, such as discrimination and clustering of answers by

respondents and by season, is recommended. Such a study could help researchers better understand differences between Lake

Sylvia visitors and those from other sites and help managers gain insight into different customer market segments for forestselected areas.

The data in these two questions supplement information about visitor preferences but have their limitations. Because

respondents were interviewed at recreation areas, it is suspected that respondents may have been describing scenes in and

around the interview site. The possibility exists that useful analysis of scenery preferences with other CUSTOMER survey

data will provide insight into respondents’ perceptions and related interests. It is recommended that future surveys

incorporate photographs rather than descriptions, that direction regarding scenic-preference rankings depicting forest areas

also include forest management areas outside the interview location, and that future surveys use ratings of scenic preference,

rather than rankings, to improve opportunities for analysis.

Additional research on visitor preferences for forest scenes of pre- and postharvest stand-level (Phase II) treatments is

planned (Baker 1994, Rudis and others 1994). Procedures will involve rating, rather than ranking, forest scenes as depicted

in photographs--a procedure that permits increased statistical analysis and limits potential confounding of scenic preferences

with views during onsite interviews. When combined with stand inventory information, photographs and forest scenery

ratings should provide detailed information about vegetation conditions preferred by visitors.

ACKNOWLEDGMENTS

The authors express appreciation to the ORWAG study team for providing the data for this paper and allowing the

Ecosystem Management visual quality research team to add the two questions about preferred forest scenery to the

CUSTOMER surveys in the Ouachita National Forest. Special thanks to Gwen Hirsch, Mark Young, and Carter Betz for

their help in explaining sampling methodology and data analysis.

LITERATURE CITED

Baker, James B. 1994. An overview of stand-level ecosystem management research in the Ouachita/Ozark National Forests.

In: Baker, James B., ed. Ecosystem management research in the Ouachita Mountains: pretreatment conditions and

preliminary findings: Proceedings of a symposium; 1993 October 26-27; Hot Springs, AR. Gen. Tech. Rep. New

Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station.

220
Coker, Jerry; Crane, Laura; Johnson, Cassandra; Hirsch, Gwen N.; Stueck, Arm; Ryder, Sean; Roberts, Cindy. 1993a.

CUSTOMER final report, Ouachita National Forest: Mena and Caddo Ranger Districts. Athens, GA: Outdoor Recreation

and Wilderness Assessment Group, Southeastern Forest Experiment Station. 170 p.

Coker, Jerry; Crane, Laura; Johnson, Cassandra; Hirsch, Gwen N.; Stueck, Ann; Ryder, Sean; Roberts, Cindy. 1993b.

CUSTOMER final report, Ouachita National Forest: Lake Sylvia recreation area. Athens, GA: Outdoor Recreation and

Wilderness Assessment Group, Southeastern Forest Experiment Station. 189 p.

Hammitt, William E. 1988. Visual and management preference of sightseers. In: Noe, Francis P.; Hammitt, William E.,

eds. Visual preferences of travelers along the Blue Ridge Parkway. Scientific Monogr. Series No. 18. Washington,

DC: U.S. Department of the Interior, National Park Service. 26 p.

Reed, Roger; Coker, Jerry; Hirsch, Gwen N.; Johnson, Cassandra; Ryder, Sean; Whitlock, Kristy. 1992. CUSTOMER final

report: Winding Stair NRA, Ouachita National Forest. Athens, GA: Outdoor Recreation and Wilderness Assessment

Group, Southeastern Forest Experiment Station. 146 p.

Rudis, Victor A.; Gramann, James H.; Herrick, Theresa A. 1994. Esthetics evaluation. In: Baker, James B., ed. Ecosystem

management research in the Ouachita Mountains: pretreatment conditions and preliminary findings: Proceedings of a

symposium; 1993 October 26-27; Hot Springs, AR. Gen. Tech. Rep. New Orleans, LA: U.S. Department of

Agriculture, Forest Service, Southern Forest Experiment Station.

SAS Institute, Inc. 1989. SAS Version 6.07. Cary, NC: SAS Institute, Inc.

Ulrich, Roger S. 1977. Visual landscape preference: a model and application. Man-Environment Systems. 7: 279-293.

APPENDIX

Special Issues Section for Winding Stair National Recreation Area (NRA) CUSTOMER Study

Now, I have a few more questions about your use of this area

INTERVIEWER -- PLEASE TRY TO WRITE WORD FOR WORD THE ANSWERS YOU RECEIVE.

1. Are you aware that this area has been designated a National Recreation Area?

YES (go to 2) NO (go to 3)

2. Does this designation have any effect on your decision to recreate here?

YES NO

3. Are you aware that the road between Mena, AR and Talihena. OK (OK ROUTE 1 - AR ROUTE 88) is a National Scenic Byway?

YES NO

4. Did you pay a user fee to recreate here?

YES NO

5. Are you willing to pay higher fees to recreate at an NRA than at other areas on the National Forest?

YES NO

6. Is there some particular feature of Winding Stair NRA that attracts you here for recreation?

YES (please specify) NO

7. Are there any problems occurring now that may have caused you to have an experience that was not as good as you expected?

YES (please specify) NO

8. What could the Forest Service do to make your recreation experience better?

9. How do you feel about the Forest Service allowing a private individual to operate a concession (such as a small store) inside the NRA?

Good idea Bad idea Other comment

221
10. Would you use this type of service if it were available?

YES NO MAYBE Other comment

11. Would you like to see outfitter/guide services (such as horseback riding with rental horses) available in the NRA?

YES NO

12. What additional facilities would you like to see on or near the NRA?

More campgrounds YES NO

Trails YES NO

Picnic areas YES NO

Visitor center YES NO

Lodge YES NO On NRA

Restaurant YES NO On NRA

Near NRA

Near NRA

13. The Forest Service would like to improve some of the views and vistas along the Talihena Scenic Drive (Skyline Drive).How do you feel about

the removal of a few trees in order to do this?

Check all that apply:

Think it’s a good idea

Don’t like the idea

Vistas ate fine the way they are

Would like to be able to see more as I’m driving

Question.14. FOR TRAIL USERS ONLY:

14. How do you feel about different types of trail users such as horses, hikers, mountain bikes, all terrain vehicles sharing the same trails?

14a. Do any particular uses interfere with your recreation satisfaction?

YES NO

If yes, which ones:

Horses

Hikers

Mountain bikes

All-terrain vehicles

14b. What type of trail user are you on this trip?

14~. Do you ever do more than 1 of the 4 activities mentioned above on these trails?

YES NO

If yes, which ones?

THESE LAST 2 QUESTIONS REFER TO YOUR PREFERENCES IN FOREST SCENERY.

15. What type of scenery do you prefer in a forest environment? Please rank order your preferences by marking ” 1” by the forest type most

preferred, “2” next to the second preference, “3” next to the third preference,“4” next to the fourth preference, and “5” next to the least

preferred.

Undisturbed

Large mature trees

Trees of mixed sizes and species

Younger tree species, with open areas

Variety of natural features (cliffs, rocks, water, etc.)

16. What words would you use to describe your preference in forest scenety?

222
Effects of Hardwood Retention, Season of Year, and Landform on the Perceived Scenic Beauty of

Forest Plots in the Ouachita Mountains’

James H. Gramann and

Victor A. Rudis’

ABSTRACT

Results from a study of the within-stand visual effects of alternative reproduction cutting

methods on 20 experimental plots in the Guachita National Forest are presented.

Treatments varied in their level of hardwood retention from complete suppression of

hardwoods to retention of 30 e/acre of basal area. Using color transparency film, plots

were photo-sampled two growing seasons after treatments were imposed. The color

slides were rated for their scenic beauty by students at Texas A&M University. Results

showed that perceived scenic beauty increased with the level of hardwood retention and

that summer, fall, and spring views were preferred over those taken during the winter.

Ridgetop plots on north-facing slopes were rated as significantly more scenic than plots

on gentle-slope north-facing positions.

INTRODUCTION

The within-stand visual-quality impact of alternative reproduction cutting methods carried out on 20 experimental plots

located in the Guachita National Forest, Arkansas is described in this paper. The plots are installed on the Winona Ranger

District and consist primarily of second-growth shortleaf pine (Pinucr echinatu Mill.) with a hardwood component dominated

by white oak (Quercus alba L.) and lesser amounts of post oak (Q. stellutu Wangenh.), black oak (Q. velutinu Lam.),

blackjack oak (Q. murihdicu Muenchh.), and southern red oak (Q. fukutu Michx.) (Shelton and Murphy 1991). Each plot

consists of a 0.2-ha division within a 0.65ha treated area (fig. 1).

The Winona study area was established during the 1988 to 89 dormant season as a “pie-Phase I” plot-ievel component

of the Guachita/Ozark-St. Francis ecosystem management research program. (Subsequent phases have focused on stand-level

and ecosystem-level analyses.) The Winona plots are oriented along an east-west ridge with elevations ranging from 195

to 240 m above sea level. In aggregate, they represent four replications of four treatments, plus four control plots that were

not treated (plots 17 to 20, fig. 1). In installing the plots, pine basal area was reduced to 60 fi2/acre in all treated stands.

The four experimental treatments included three levels of hardwood retention: a 30 ft2/acre basal area, a 15 ft2/acre basal

area, and total hardwood suppression. The treatment with 15 ft2/acre was implemented so that residual hardwoods were

retained in either a scattered or grouped spatial arrangement (Shelton and Murphy 1991). Because landform position can

affect moisture availability and forest regeneration, the plots were blocked so that each treatment and control is replicated

on four landform positions: a gentle-slope north-facing position, a moderate-slope north-facing position, a ridgetop northfacing position, and a ridgetop south-facing position.

METHODS

All 20 Winona plots were photo-sampled two growing seasons (1.5 years) after treatments were imposed. Photo sampling

took place during each season of the year, beginning in summer 1990 and ending in spring 1991. Views were photographed

with an f-112.8 lens and taken from eight surveyed points on each plot’s perimeter. The direction of the eight perimeter shots

was toward the center of the plot. Ektachrome 35mm color slide film, speed IS0 400, was push-processed to IS0 800 to

compensate for the dimly lit conditions that often characterize within-stand views.

‘Paper presented at the Symposium on Ecosystem Management Research in the Guachita Mountains: Pretreatment Conditions

and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

‘Associate professor, Department of Recreation, Park and Tourism Sciences, Texas A&M University, College Station, TX

77843-2261; research forester, Forest Inventory and Analysis Unit, USDA Forest Service Southern Forest Experiment

Station, Starkville, MS 39759-0906.

223
UNEVEN-AGED

fJjQ&jcjmm “k..,

Figure l.- Winona plot-level study area.

During spring 1992, slides from the Winona plots were rated for their scenic beauty by classes at Texas A&M University.

Rating sessions followed procedures developed by Daniel and Boster (1976). After viewing 10 “warm-up” slides, students

evaluated scenes on a lo-point scale, ranging from u 1,” which meant “very low in scenic beauty” to u 10,” which meant

“very high in scenic beauty. n

Slides used in the rating sessions were selected randomly from the inventory of photos with the constraint that they had

to be of acceptable technical quality and not include obvious distractions that might bias judgments (e.g., spectacular lighting

effects or the presence of human-made objects in the scene). Scenic-beauty judgments were obtained from three undergraduate and one graduate class. The undergraduate classes were in sociology, business administration, and civil engineering. The graduate class was in computer science. Ratings from students majoring in natural resource management fields

were discarded.

Each class rated 100 slides that consisted of 80 unique slides shown only in one rating session and 20 common “baseline”

slides, which were shown in each of the four sessions. Baseline slides were interspersed systematically with the remaining

80 slides so that they appeared as every fifth slide shown. Slides remained on the screen for five seconds. In total, 400

scenic-beauty ratings were obtained that covered 340 views. The 20 baseline slides were rated four times.

Each of the rating sessions replicated a four by five by four factorial design. The three factors were season of the year

(four levels), treatment (i.e., reproduction cutting method-five levels), and landform position (four levels). Treatments were

assigned at random within each landform. The dependent variable was the scenic beauty estimation (SBE) for each slide,

224
which was calculated from the raw scenic-beauty ratings using the BMBATE software (Brown and Daniel 1990). Data were

analyzed using three-way analysis of variance (ANOVA).

Prior to ANOVA, the correlations between the baseline SBE’s from each of the rating sessions were examined to

determine the agreement between rating groups on the scenic beauty of these 20 slides. The Pearson product-moment

correlations ranged from 0.915 to 0.956, with an average correlation of 0.936 for the six pairwise comparisons. This high

level of agreement between groups supports the application of ANOVA to the combined ratings of all four groups of judges.

RESULTS AND DISCUSSION

ANOVA results are shown in table 1. To maintain a balanced design, the 20 baseline slides were excluded from the

analysis, leaving a total sample of 320 slides. ln comparing levels within the three experimental factors, a priori contrasts

were specified between complete hardwood suppression and each of the remaining silvicultural treatments and control

condition, between winter and each of the remaining seasons, and between the gentle-slope north-facing landform and each

of the remaining landform positions. It was hypothesized that plots with complete hardwood suppression would be rated as

significantly less scenic than other plots and that summer, fall, and spring scenes would be judged as more scenic than winter

views. ’ It also was hypothesized that the lower-elevation landform position would be associated with lower scenic-beauty

ratings because the moister conditions that presumably characterized it would produce lusher growth in the understory, which

would create a less open and parklike appearance.

Main Effects

Table 1 shows that the simple main effects of treatment, season, and landform were statistically significant, whereas the

interaction between treatment and season was insignificant. Because landform was not replicated in the study design, the

interaction terms that included this variable were not evaluated. However, the significant effect of the experimental design

suggests that landform may interact with other factors to influence scenic-beauty ratings.

Differences in SBE ratings within factors are graphed in figures 2 to 4. In general, a priori contrasts supported the

hypotheses concerning the relationship between scenic beauty and silvicultural treatments, seasons of the year, and landform

position.

Table l.- Analysis of variance of scenic beauty estimations (N = 320)

Source of variation df

Mean

square

Landform 3 3884.0 3.1+

Treatment 4 17151.0 13.8*

Season 3 122679.5 98X*

Treatment by season 12 1403.0 1.1

Experimental design 57 1242.0 1.4+

Residual 240 871.4 -

Total 319

%e denominator for the F-test is the residual mean square for the experimental design (871.4) and the experimental-design mean square for the

other effects (1242.0).

+p<o.os.

SP<O.Ol.

Treatment

Figure 2 shows that the untreated control plots and those plots retaining 30 p/acre of hardwoods in a scattered pattern

were rated as significantly more scenic than plots with complete hardwood suppression. Leaving 15 @/acre of hardwoods

in a grouped pattern also resulted in significantly higher SBE ratings. However, there was no significant difference between

the plots with complete hardwood control and the 15 e/acre treatment in which hardwoods were left in a scattered configuration. This suggests that retaining residual hardwoods in a grouped pattern, as opposed to a scattered one, may partially

mitigate the negative visual impacts of a reproduction cut that maintains only 15 @/acre of hardwood basal area.

225
I

SEE Mean

40

0

-20

t

-17.02 -16.93

4 o J

I 1 I I I

I r

Control 30 scot- 15 Grouped 15 Scot- No Hardtered tered woods

Treatment

*Differs .from complete hardwood SUPpression at P(t)<0.05.

I

Figure 2.- Main efict of treatment on scenic beauty estimation.

Season

Figure 3 shows that summer views were judged as significantly more scenic than winter views. A priori contrasts

revealed that fall and spring scenes also received significantly higher ratings than winter views.

The preference for summer, fall, and spring scenes over winter views may be related to seasonal color patterns. Color

variation by season is one of the most notable changes in forest vegetation. This variation could have important effects on

human preference for forest scenes, even in landscapes dominated by pine. The exact nature of the relationship between

silvicultural treatment, forest color, and scenic-beauty judgments is worthy of further investigation.

SEE Mean

60

40

20

0

-20

4 0

-60 -50.68

Summer 1990 Fall 1990 Winter 199 1

Season of Year

*Differs from winter at P(t)tO.OOl.

10.03 l

Spring 199 1

,

Figure 3.- Main eflect of season of year on scenic beauty estimation.

Landfonn Position

Figure 4 shows that ridgetop plots on north-facing slopes were rated as significantly more scenic than plots on gentleslope north-facing positions. No other significant differences were found for any of the remaining comparisons with the

gentle-slope north-facing plots.

226
15n

Sf3E Mean

7.12.

-15 ’

I I I I 1

Gentle/ Moderate/ Ridgetop/ Ridgetop/

North North North South

Landform Position

*Differs from gentle-slope north-facing

position at P(t)<O.Ol.

‘igure 4.- Main effect of landform on scenic beauty estimation.

The relatively low scenic-beauty rating for the lower elevation, north-facing position may be caused by variable response

to disturbance. Lower elevation north-facing plots have the highest site index of all the Winona plots (Shelton and Murphy

1991). Thus, compared to other plots, they may have responded more rapidly to disturbance by increased growth of understory foliage and twigs. In summer, low-elevation positions had more foliage and twig screening (Rudis and others 1994).

Previous research in southern pine forests showed that vegetative screening in the understory was negatively related to

perceived scenic beauty (Ruddell and others 1989).

The landform effect on scenic beauty in the Winona plots also may be an artifact of the preparation work done to achieve

hardwood stocking levels appropriate to a treatment. More disturbance may have occurred in the gentle-slope plots than in

the higher-elevation positions. The passage of two growing seasons since treatment may not have been long enough for the

slash left by these disturbances to become visually unobtrusive. While the effect of slash on visual preference in southern

pine forests has not been clearly established (Rudis and others 1988), in other forest types it has been shown to detract from

perceived scenic beauty (Brown and Daniel 1984).

CONCLUSIONS

Of the three factors examined, season of the year exhibited the most significant effect on SBE. This finding is important

in that most forest scenic-beauty models are based on summer data. As demonstrated by this study, such models should not

be generalized uncritically to other seasons of the year.

It seems likely that one source of seasonal differences in scenic-beauty ratings is color variation in forest vegetation.

Visual inspection of the Winona slides indicated that summer views, which were the most preferred, were also characterized

by higher amounts of green than were winter scenes, which were the least preferred. Future research should investigate

more thoroughly the effect of seasonal color change on scenic-beauty ratings as well as the effect of forest management

practices on seasonal color patterns.

Two years after treatment, the level of hardwood retention affected scenic-beauty perceptions in the Winona study area.

Specifically, untreated plots and plots characterized by 30 e/acre basal area in hardwoods were rated as significantly more

scenic than plots with complete hardwood suppression. When remaining hardwoods were left in a grouped pattern rather

than a scattered pattern, the negative visual impact of retaining only 15 e/acre basal area in hardwoods was somewhat

mitigated. Perhaps, this is because hardwoods growing in clusters present a more parklike appearance to observers than do

single trees standing in isolation.

The impact of silvicultural treatment on perceived scenic beauty may change as the Winona plots regenerate. Analyses

based on photo sampling taken only two growing seasons after treatment may not predict scenic-beauty effects five or 10

years after treatment. In particular, the impact of silvicultural treatment may become less noticeable in more mature plots

as trees increase in size. Follow-up analyses of the Winona plots should be carried out to determine the long-term impact

of hardwood management on scenic beauty in this forest type.

It was not possible to reach a firm conclusion regarding the impact of landform position on scenic quality. The landform

effect uncovered in this experiment could be an artifact of differences in disturbance (e.g., downed woody material associated

227
with establishing treatment basal area) and vegetation response to increased sunlight. The experimental design did not permit

an evaluation of the interaction of landform position with either treatment or season. It is possible that the scenic-beauty

effect of hardwood-retention level differs significantly between drier ridgetop plots and moister lower-elevation sites,

especially during the early stages of forest regeneration. These interaction effects also need to be examined in future

research.

LITERATURE CITATIONS

Brown, Thomas C.; Daniel, Terry C. 1984. Modeling forest scenic beauty: concepts and applications to ponderosa pine.

Res. Pap. RM-256. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and

Range Experiment Station. 35 p.

Brown, Thomas C.; Daniel, Terry C. 1990. Scaling of ratings: concepts and methods. Res. Pap. RM-293. Fort Collins, CO:

U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station. 24 p.

Daniel, Terry C.; Boster, R. 1976. Measuring landscape esthetics: the scenic beauty estimation method. Res. Pap. RM-167.

Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment

Station. 66 p.

Ruddell, Edward J.; Gramann, James H.; Rudis, Victor A.; Westphal, Joanne M. 1989. The psychological utility of visual

penetration in near-view forest scenic-beauty models. Environment and Behavior. 21: 393-412.

Rudis, Victor A.; Gramann, James H.; Ruddell, Edward J.; Westphal, Joanne M. 1988. Forest inventory and managementbased visual preference models of southern pine stands. Forest Science. 34: 846-863.

Rudis, Victor A.; Gramann, James H.; Herrick, Theresa. 1994. Esthetic evaluation. In: Baker, James B., ed. Ecosystem

management research in the Guachita Mountains: pretreatment conditions and preliminary findings: Proceedings of a

symposium; 1993 October 26-27; Hot Springs, AR. Gen. Tech. Rep. New Orleans, LA: U.S. Department of Agriculture,

Forest Service, Southern Forest Experiment Station.

Shelton, Michael G.; Murphy, Paul A. 1991. Age and sire structure of a shortleaf pine-oak stand in the Guachita

Mountains-implications for uneven aged management. In: Coleman, S.; Neary, D., camps. eds. Proceedings of the 6th

biennial southern silvicultural research conference; 1990 October 30-November 1; Memphis, TN. Gen. Tech. Rep. SE70. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station: 616629.

Vol. 2.

228
Pmduction Time, Total Costs and Residual Damage

at Varying Hawest Intensities’

Richard A. Kluender, David A. Lortz, and Bryce J. Stokes’

ABSTRACT

Six stands were harvested by either clearcut, shelterwood, or single-tree selection methods. Harvest

productivity was evaluated in 2 consecutive years (1991 and 1992) for each harvesting method. The

&gle-tree selection harvests consisted of thinnings in even-aged stands as an initial basal area

reduction cut required to convert the stand to uneven-aged structure. Harvest intensity (percentage of

basal area removed) ranged from 3 1 to 100.

, The same contractor used two skidders (one grapple, one choker) and production chain saws to

harvest all six tracts. Harvested sites were similar in slope, average diameter at breast height (d.b.h.)

and preharvest number of stems by d.b.h.

In 1991, total felling time (including walk, acquire, fell, and limb-top times) was inversely related to

harvesting intensity. In 1992, total felling time averaged highest under the single-tree selection method

\ and lowest under the shelterwood method. When these averages were adjusted for differences in stand

characteristics, the inverse relationship between total time and percentage of basal area removed at

harvest (harvesting intensity) was present for both years.

In both years, total cycle time (including travel-empty, bunch-building, travel-loaded, and deck

times) was higher, and volume per cycle was lower for the cable skidder than for the grapple skidder.

After adjusting for differences between stands, total cycle time was inversely related to harvest

intensity.

Factors affecting total felling time (in decreasing order of importance) were d.b.h. of harvested stems,

intertree distance, and harvest intensity. Factors affecting total cycle time for skidding (in decreasing

order of importance) were travel distance, skidder type;number of stems per cycle, harvest intensity,

and volume per cycle.

The total percentage of stand area trafficked was lowest for the single-tree stands. The single-tree

selection method (in 1992) had the largest and only significant increase in bulk density in the skid

trails. Residual tree damage (trees/acre) was greater for the single-tree selection method than the

shelterwood method.

INTRODUCI’ION

Recently, comparisons of even-aged and uneven-aged management have attracted increased attention. One aspect of

research includes comparisons of the time required to perform various harvesting operations and their cost. Previous

studies often addressed only a single harvest method, (i.e., clear cutting or single-tree selection), (Kellog and others 1991,

Miller and Sarles 1986) with differences among stands or harvesting crews and equipment confounded with treatment

effects (Bell 1989, Hannah and others 1981, Miller and Smith 1991, Sloan 1991). Studies are needed using the same

equipment and crew to harvest similar stands under prescribed conditions. The results of studies conducted over 2 years

on harvesting time and estimated cost for clear cutting, shelterwood harvesting (two methods used in even-aged

management), and single-tree selection harvest are presented here. Variation among stands, crews, and equipment was

controlled by using the same crew and equipment on all stands and selecting similar stands.

‘Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains:

Pretreatment Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

*Associate professor of forest operations, University of Arkansas at Monticello, Monticello, AR, 7 1656; Research

Specialist, University of Arkansas at Monticello, Monticello, AR, 71656; Project leader, USDA Forest Service,

Southern Forest Experiment Station, Auburn, AL, 36849, respectively.

229
METHODS

Treatment of the Stands

Three harvesting methods were selected to represent a wide range of harvest intensities. Clearcutting and single-tree

selection methods represented extremes in harvest intensity, and shelterwood harvests represented intermediate treatments.

Three stands were harvested by each method in the summer of 1991 and then replicated in 1992. The stands were

located on the Womble Ranger District, Ouachita National Forest west of Hot Springs, AR. Single-tree selection

harvesting consisted of a light thinning of two even-aged stands. This was an initial basal area reduction cut required to

convert the stands to uneven-aged structure.

There was a small hardwood component in all six stands. The hardwood stems were bypassed by the harvesting crew

to be processed at a later time.

Diameter distribution and average height of the six stands were statistically similar. These stands were typical mature

even-aged stands for the Ouachita National Forest. Table 1 shows the preharvest stand conditions for all

six tracts. The percentage of basal area removed was used as an index of harvesting intensity for each stand.

Table 1. ’ Preharvest stand condition summary for six stands.

1991 1992

Single-tre e

selection

Sheltemood Clearcut Single-tree

Selection

Shelterwood Clearcut

Basal area (ft*) 81 70 81 108 77 69

Harvest (% basal area) 31 57 100 43 71 100

dbh (inches) 10.0 11.4 10.5 10.6 10.5 10.0

Merchantable height (feet) 54 62 53 61 52 57

Size (acres) 52 11 40 40 40 40

Diameter distributions from preharvest cruises were compared using a Kolmogorov-Smimov distribution test to

determine whether they were from the same parent distribution. This test showed all the stands were representative of

the same parent population.

There were differences in the measured average values for each stand. These differences were adjusted for the final

analysis by using global averages (average of all six stand values) into the regression equations. This adjustment

accounted for variation between stands. The effect of harvest intensity was isolated.

Felling

The sawyer felled all marked trees within the stand boundaries according to felling ease and safety. Directional

felling to optimize skidding was not a consideration, nor was it practiced. Hung trees occurred in all three stands. When

trees were hung, the sawyer stopped work while a skidder was used to pull or push the tree to the ground or the sawyer

moved to a new area until the hung tree was brought to the ground by the skidder operator. Trees were processed into

tree-length stems by limbing and topping immediately after felling.

A felling observation was defined as the time required for the sawyer to walk to a tree (walk), clear the brush for a

safe exit path and plumb the tree (acquire), fell the tree (fell), and limb and top the tree (limb and top). Not every

felling cycle was observed. Observed felling cycles were randomly chosen as work progressed through the stand.

Observed cycles did not necessarily mirror the stand’s distribution. Field research team members timed and recorded

each event in the cycle. Delay times (delay) and reasons were recorded. When a tree was limbed and topped so it was

safe to approach, researchers measured the d.b.h. and merchantable length (5inch top) of the felled tree. Individual tree

volumes were calculated by a formula developed by Clark and Saucier (1990). Total time per tree (excluding delays)

was calculated for each observation. Means for walk-time, acquire-time, cut, limb and top-time, and delay-time were

computed by tract and the overall study. Differences in mean times were detected by Tukey’s HSD pair-wise comparison

test at the 0.05 level. Adjusted (for mean tree diameter and inter-tree distance) total-time-per-tree was calculated for the

six harvested stands. Finally, a structural regression was estimated for total felling time with the percentage basal area

harvested, d.b,h., and intertree distance as independent variables.

230
Sk idding

Two 120 horsepower, turbo-charged Caterpillar@ 5 18 skidders3 equipped with 34-inch tires hauled the tree-length

stems on all tracts. One was equipped with a one-cord grapple, the other with a cable skidder with six chokers. The

cable skidder operator hooked his own chokers. Both operators gathered approximately a full load before traveling to the

landing. When skidders arrived at the landing, they dropped (grapple skidder) or unchoked (cable skidder) their load and

pushed the stems into a pile for loading. Skidders incurred delays both at the deck and in the woods. Occasionally, the

two skidders arrived at the deck simultaneously; when this occurred, one skidder waited on the other (productive delay)

to finish dropping its load and piling stems. In-the-woods delays occurred when hung trees needed to be pulled or

pushed down, or when sawyers had not completed their work resulting in no stems to haul. No mechanical delays were

observed for the skidders during the study.

At the deck, hauled stems were measured to obtain d.b.h., top diameter, and length using tree calipers and a logger’s

tape. Applicable volume tables were used to determine individual stem volume (Clark and Saucier 1990). For each

skidder cycle, travel-empty, travel-loaded, acquire (bunch-building), and dispose (deck time), times were recorded.

Skidding distances along haul trails were measured; colored flagging was hung in nonharvested trees at measured

distances from the deck to aid in measurement of exact haul distance.

Total time per haul was calculated for each skidder cycle. Averages for travel-empty, acquire, travel-loaded, and

dispose were computed for each skidder by harvesting method and the overall study. A structural regression equation

was estimated to determine the significance of each of the factors contributing to total time. Results were considered

significant at the 0.05 level.

Posth aw est Dam age Assessm ent

A postharvesting site-damage assessment included area disturbed, residual tree damage, and soil bulk density. A lchain by l-chain grid was established on each of the tracts. At grid intersection points, site disturbance was identified

and classified by disturbance class. Disturbance classes included: (1) undisturbed-untrafficked; (2) disturbed-trafficked,

litter in place; (3) disturbed-trafficked, exposed soil; (4) disturbed-trafficked, exposed soil and or soil depression; (5)

disturbed-slash; (6) disturbed-nonsoil (rock). At every fifth point along grid lines, a l/lo-acre circular plot was installed

in the shelterwood stands and a l/20-acre circular plot was installed in the single-tree stands to assess residual tree

damage. Tree damage was classified as either bark damage, cambium exposed, or wood damage, and the area of damage

was measured. Lengths of primary and secondary skid trails were measured in all six stands. Widths for each trail were

measured at IOO-ft intervals, and average widths were used to calculate the total area in skid trails.

Postharvest soil samples were collected on only the 1992 stands. Samples classified as disturbed were taken in three

primary skid trail ruts in each stand at 100, 300, 500, and 700 ft from the deck. With each disturbed sample, a

corresponding undisturbed sample was taken along a perpendicular line to the trail from the disturbed sample. The

distance from the disturbed sample to the first undisturbed sample was measured. Disturbed and undisturbed samples

were also taken along three secondary trails, 100 ft from their junction with the primary trail.

The samples were weighed wet, dried at 105 “C for 72 hours, and reweighed to obtain dry weight. Bulk density and

percentage of moisture content were then determined for each sample. Bulk density was adjusted for rock content

according to American Society for Testing and Materials Standards (ASTM 1992) for samples with 40 percent or more

of total dry weight in rock.

Stands

RESULTS

The diameter distribution for the three stands harvested in 1992, while not statistically different from the parent

population, averaged slightly higher than the 1991 stands. In the two stands harvested by single-tree selection, the

distribution of removed stems was similar to a mixed thinning with cutting in the 6- to lo- inch classes (low thinning)

and in the 14- to 18- inch classes (thinning from above).

Fe lling

The diameter distributions of harvested stems in the felling study were not statistically different from their parent

stands. Intertree distance was inversely related to harvesting intensity. The sawyer had to walk further to find marked

trees in the single-tree selection stands than in the clearcut stands; walk-time decreased as harvesting intensity increased.

There was no identifiable trend in acquire-time. Felling time was dictated by the d.b.h. of the individual tree. Limb and

top-time was influenced by merchantable height, d.b.h., and harvest intensity. This was attributed to the problem of

’ Use of trade names is for the reader’s information and does not constitute official endorsement by

University of Arkansas or the USDA Forest service to the exclusion of other suitable harvesting machinery.

231

the
working with longer, and wider stems, and working around

unharvested trees. Figure 1 illustrates the average values for ’

each component in the six stands.

The structural regression for the estimation of time to fell U

a tree had an R2 = 0.585. All regression coefficients were “: I

significant at the .Ol level. The structural equation was: N

M1U

Total Time = -0.581 - 0.610 HZ + 0.007 Dist N

”

+ 0.224 d.6.h. z

B ’

where: I

Total Time = sum of time required to walk to, acquire, u

fell, and limb and top a tree in minutes

HI = Harvest intensity (Percentage of basal area

harvested)

Dist = Intertree distance in feet

d.b.h. I= Tree diameter at breast height in inches.

.

“&I aNuB_IIE mWLnB.WwDIHeL77?B.Wam nl?AKwr cLlWQ.cvt. -lm 199, *9% ,991 199l 1991 IWI

Figure 1. Average felling time for an individual tree

broken down by operation components.

Table .2 gives the range of values for harvest intensity, intertree distance, and d.b.h.,which were the significant

indemndent variables. Harvest year was tested as a possible independent variable but was not significant.

Table 2. Summary of the felling data variables used in the felling regression equation.

1991

Harvest (% basal area)

dbh (inches)

Intertree distance (feet)

Single-tree selection

n= 51

max. min. mean

31

19.8 6.4 11.4

408 8 75

Sheltenwod Clearcut

n = 50 n = 61

max. min. mean max. min. mean

57 100

23.6 5.6 11.5 18.7 5.8 11.7

3 122 46 93 7 49

1992

Harvest (% basal area)

dbh (inches)

Intertree distance (feet)

Single-tree selection Shelterwood Clearcut

n= 107 n = 121 n = 141

43 71 100

25.0 10.6 14.8 22.4 6.7 13.6 24.5 8.0 14.4

408 8 75 3 122 46 93 7 49

Application of the regression equation is straightforward. For example, a 3-inch increase in average d.b.h. would

increase total time to process a tree by 0.67 minutes (40 seconds). Examination of the standardized coefficients in the

structural regression equation indicated the most important factors influencing total felling time (in decreasing order of

importance) were d.b.h., intertree distance, and harvest intensity. Figure 2 demonstrates the expected total time per tree

using individual stand averages for d.b.h. and intertree distance. Figure 3 shows the expected total time per tree when

d.b.h. and intertree distance are adjusted to reflect global averages (averaged across all six stands) for d.b.h. and intertree

distance.

Average productivity was calculated using expected time and average stem volume. Productivity was used in

combination with estimated hourly operation costs to derived cost per unit of volume.

Felling cost per unit volume varies directly with productivity. An hourly fixed cost of $0.30, a variable cost of $1.63

per productive hour, and a labor cost of $7.98 per hour were used in calculations. The adjusted (50 percent availability)

232
(Miyata 1980) hourly operating cost under these assumptions would be $9.10 per hour. Hourly cost was combined with

total time estimates (from the regression equation) and volume estimates to derive cost per hundred cubic feet (ccl)

‘t I

Figure 2. Estimated felling time based on indivicual Figure 3. Estimated felling times based on global

stand averages. averages

produced. These were %3.40/ccf and %1.7l/ccf for singletree selection in 1991 and 1992, respectively. For the

shelterwood, they were %2.81/ccf and %2.00/ccf in 1991

and 1992, respectively. Finally, the clearcut \costs were

$2.89/ccf and $1.6l/ccf in 1991 and 1992, respectively.

Figure 4 shows the costs of production for each stand.

These costs are not adjusted to remove differences in

stand characteristics.

Skidding

In 1992, the measured stems were larger than in 199 1.

Skid volumes tended to be higher and cycle times lower

in 1992; thus, overall productivity (volume per unit time)

was higher in 1992. This was particularly true for the

stand harvested with the single-tree selection method in

1992. Skidding productivity was unexpectedly high in

this stand because average stem d.b.h. was larger and

merchantable length was longer than any other stand.

However, when the variation attributable to differences in

skidded volume was removed, the inverse relationship

between cycle time and harvest intensity was again

evident.

Figure 4. Estimated felling cost per 100 cubic feet

Figures 5 and 6 illustrate the average time components for a grapple skidder and a cable skidder cycle, respectively.

There was no clear trend in the travel-empty and travel-loaded time variables. Acquire-time was related negatively to

both average d.b.h. and percentage of basal area removed. It was related positively to, and was strongly influenced by,

the average number of stems per turn. For the grapple skidder, there was no apparent trend in the dispose variable. The

cable skidder did show a positive relationship between number of stems and disposal time.

233
.sNcLE-REE ENUS-- ~lmwooD.mELmwooD now cLaAs*

(PISCIIM -ON ,991 ,992 ,991 ,997.

lsfl ,992

Figure 5. Average time of a grapple skidder cycle

broken down into operation components

Figure 6. Average time of a cable skidder cycle broken

down into operation components

The RZ value for the structural regression estimating skidder-cycle time was 0.461. All coefficients were significant at

the 0.01 level. The equation was:

Total Time = 4.154 - 2.297 HI - 2.087 Skid + 0.003 Distance + 0.497 Stems + 0.022 Volume

where:

Total Time = sum of travel-empty, acquire, travel-loaded and dispose time

HI = Harvest intensity (percentage of basal area harvested)

Skid = 1 if the skidder is a grapple skidder; 0 if the skidder is a cable skidder

Distance = Travel-empty distance (feet) + Travel-loaded distance (feet)

Stems = Average number of stems per turn

Volume = Average volume hauled per turn in cubic feet.

Tables 3 and 4 give the range of values for the independent variables (harvest intensity, skid distance, stems per turn,

and volume per turn) on which this equation was based. The specific year of harvest was tested as a possible variable

and was not significant when combined with the other variables.

Table 3. Summary of the cable skidding data used in the skidding regression equation.

1991

Single-tree selection Shelterwood Clearcut

n=8 n = 35 n = 34

max. min. mean max. min. mean max. min. mean

Harvest (% basal area) 31 57 100

Stems per cycle 7 3 4.1 .5 2 3.7 5 3 3.6

Volume (100 ft’) 84.0 25.8 51.1 105.3 22.1 61.7 137.0 37.2 76.7

Total skid distance (feet) 2849 1300 2355 2436 609 1369 2472 1050 1864

234
Table 3 continued. Summary of the cable skidding data used in the skidding regression equation.

1992

Single-tree selection

n =44

Shelterwood

n = 67

Clearcut

n = 85

max. min. mean max. min. mean max. min. mean

Harvest (% basal area)

Stems cycle per

Volume (100 fl’)

Total skid distance (feet)

43 71 100

5 1 3.0 5 2 3.9 5 2 3.9

180.6 21.5 104.2 122.9 18.7 58.3 140.1 13.6 73.1

3170 237 1279 2738 292 1347 3245 446 1470

Table,4. Summary of the grapple skidding data used in the skidding regression equation

1991

Single-tree selection Shelterwood Clearcut

n = 53 n = 50 n = 65

max. min. mean max. min. mean max. min. mean

Harvest (% basal area) 34 57 100

Stems cycle per 7 1 4.1 8 2 4.2 7 2 4.0

Volume (100 ft3) 161.2 19.1 81.8 153.9 32.2 82.9 180.0 30.1 98.7

Total skid distance (feet) 3315 390 1350 2266 394 1109 2772 524 1325

1992

Single-tree selection Shelterwood Clearcut

n = 59 n = 71 n = 70

Harvest (% basal area) 43 71 100

Stems cycle per 6 2 3.3 14 2 5.6 9 3 5.3

Volume (100 ft’) 189.0 58.3 112.4 176.2 19.5 93.1 157.7 29.9 97.7

Total skid distance (feet) 3444 316 1468 2563 493 1330 2918 361 1484

The equation demonstrates the sensitivity of total time required per cycle to changes in the independent variables. For

example, under the conditions studied, a grapple skidder took approximately 2 minutes and 5 seconds less time per cycle

than the cable skidder. Additionally, loading the skidder to only 60 ft3, rather than fully loading to 100 ft’, will reduce

the total travel time by 0.88 minutes (53 seconds) per haul. The standardized coefficients of the structural regression

analysis showed the most important factors influencing time per cycle (in decreasing order) were total turn distance,

skidder type, stems per turn, percentage of basal area harvested, and average haul volume. Figure 7 shows the estimated

total times using individual stand averages for skid distance, number of stems per turn, and volume for the grapple and

cable skidders. Figure 8 shows the estimated total time per turn when distance, number of stems, and volume are

adjusted to reflect global averages (averaged across all stands).

235
7

Figure 7. Estimated average skidding time for one cycle

based on individual stand characteristics

10

t

0w.A9u81991

.

.

.cmLalvvl

.

.

0-I

.cAmaLvva

.

Figure 8. Estimated average skidding time for one cycle

based on global characteristics.

Skidding cost per unit volume varies with fixed and variable operating cost and productivity. Assumed availability for

the skidders was 67 percent (Miyata 1980). In 1991, total estimated costs ($/ccl) for the cable skidder were $21.77,

$17.06, and $12.50 for the single-tree selection, shelterwood, and clearcut methods, respectively, versus $11.60, $10.70,

and $7.97, respectively, for the grapple skidder. In 1992, total estimated costs ($/ccl) for the cable skidder were $10.40,

$17.57, and $13.12 for the single-tree selection, shelterwood, and clearcut methods, respectively, versus $8.18, $9.20, and

$8.06, respectively, for the grapple skidder. Cable skidder productivity was more sensitive to differences in stem size

than the grapple skidder. Figures 9 and 10 illustrate the costs of production for the grapple and cable skidders,

respectively. All the costs are based on unadjusted time estimates.

12

II

10

0

7

Q w0,vvl

.I

0

.

I

Figure 9. Estimated average grapple skidding costs per

100 cubic feet

Postharvest Damage Assessment

Trees with cambium exposed were considered damaged All cambium exposure was counted, regardless of area. In

1991, Average exposure area was as low as 0.1 ft’ per tree (3.79 inches by 3.79 inches). The 1991 postharvest damage

assessment revealed 16 residual trees per acre damaged from the single-tree selection method (Table 5). There were only

six damaged trees per acre from the shelterwood method. The 1992 postharvest damage assessment revealed that the

single-tree selection method resulted in 10.2 damaged trees per acre. The shelterwood method resulted in 2.5 damaged

0

0 1991 cl .*VVl

.

0

.

0

.

Figure 10. Estimated cable skidding costs per 100 cubic

feet

236
trees per acre. There was a decrease in damage between the 2 years that may have resulted from gaining experience

with the harvesting method. The average number of damaged trees per acre for the 2 years from the single-tree selection

method was 13.1, whereas the shelterwood method averaged only 4.3 damaged trees per acre for the 2 years.

Table 5. Postharvest residual damage assessment for three harvesting methods for 1991 and 1992.

Harvest method

Single-tree selection Shelterwood Clearcut

1991 1992 mean 1991 1992 mean 1991 1992 mean

Tree damage due to cambium

exposure (trees/acre)

Area of cambium exposure

(fir/tree)

Area in skid trails (percent)

Primary

Secondary

Total

Stand disturbance (percent)

Undisturbed

Untraflicked

Disturbed

Litter in place

Soil exposed

Soil exposed/

depression

Slash

Non-soil

16.0 10.2 13.16 6.0 2.5 4.3 na na na

0.4 0.4 0.4a 0.1 0.2 0.2a na na na

2.0 6.6 4.3a 7.0 19.1 l3.0a 7.5 10.1 8.8a

1.6 3.6 2.6 0.6 6.9 3.7a 4.8 7.6 6.2a

3.6 10.2 6.9 7.6 26.0 16.7a 12.3 17.1 15.Oa

48.3 36.6 42.4a 18.0 16.7 17.3b 9.6 11.5 10.5b

22.3 29.2 25.7a 29.2 27.6 28.4a 25.6 23.7 24.6a

5.6 15.1 10.3a 11.2 21.1 16.1a 8.0 16.5 12.2a

9.9 9.2 9.5a 14.6 10.9 12.7a 15.2 14.3 14.7a

13.9 9.1 11.5b 27.0 21.8 24.4ab 40.8 30.2 35.5a

0.0 0.7 0.3a 0.0 1.9 0.9a 0.8 4.3 2.5a

letters indicate groups similar at the 0.05 level in a means separation test using Tukey’s HSD multiple

comparisons test.

Primary and secondary skid trails accounted for 3.6, 7.6, and 12.3 percent of the total area for the single-tree selection,

shelterwood, and clearcut methods, respectively (Table 5). Primary trails were defined as those having branching trails,

whereas secondary trails did not. The 1992 harvests had total skid-trail area of 10.2, 26.0, and 17.7 percent of the total

area for the single-tree selection, shelterwood, and clearcut methods, respectively. The 2-year skid-trail area averages

were 6.9, 16.8, and 15.0 percent of the total area in primary and secondary skid trails for the single-tree selection,

shelterwood, and clearcut methods, respectively.

Table 5 also gives the percentage of each stand in each disturbance class. As harvesting levels increased, so did the

proportion of the total tract trafficked. There was significantly more undisturbed area for the single-tree selection

methods than the other two methods. Combining the area disturbance data for the 2 years shows that the single-tree

selection method left an average of 42.4 percent of the stand undisturbed as compared to 17.3 percent for the

shelterwood method and 10.5 percent for the clearcut method. This results in 144 percent more undisturbed area for the

single-tree selection method compared to the shelterwood method and 300 percent more compared to the clearcut

method. The clearcut method resulted in 163 percent more area with slash than the single-tree selection method and 24

percent more than the shelterwood method. Additionally, the percentage of total area covered by slash increased with

increasing harvest intensity. There were no significant differences among treatments for the amount of area disturbed

(this includes three classes).

237
The single-tree selection method had less area in skid trails and less disturbed area based on total area. This analysis,

however, does not account for quantity of wood harvested. If disturbance is related to wood recovery, the treatment

effects would be more balanced rather than skewed toward lower removal levels.

After testing for the effect of distance from the deck, the soil bulk densities were grouped by treatments. The average

bulk density on primary skid trails was 1.49 g/cm’ for the single-tree selection method, 1.30 g/cm3 for the shelterwood

method, and 1.26 g/cm3 for the clearcut method (Table 6). There was an increase in bulk density for all harvesting

treatment. A paired comparison test showed a significant difference for the single-tree selection method only. Due to

fewer trees removed (high residual stand density) for the single-tree selection method, the skidders were more restricted

in their travel, and, therefore, used the same primary trails more frequently than with the shelterwood and clearcut

methods. This resulted in a higher bulk density for the single-tree selection method due to cumulative traffic impacts.

Table 6. Summary of soil analysis.

Harvest method

Single-tree Selection Sheltenwod Clearcut

Bulk Density (g/cm’)

Undisturbed

Trail

Difference

Prob> ItI

Mean S.D. Mean S.D. Mean S.D.

1.12 0.27 1.22 0.17 1.15 0.21

1.49 0.19 1.30 0.19 1.26 0.27

0.37 0.23 0.08 0.25 0.11 0.37

0.0003 0.2732 0.3017

DISCUSSION

The most important factors in felling time per tree were the d.b.h., the intertree distance, and the harvesting method.

In the analysis of co-variance and the structural regression analysis, harvest intensity acted as a surrogate variable to

collect otherwise unexplained variation in felling time. For felling, the extra time spent finding marked trees, planning

the cut, and working around residual stand components affected production for the single-tree and shelterwood methods.

Skidder productivity was significantly influenced by skidder type, total haul distance, volume per haul, and harvest

method. The harvest intensity variable collected the additional time required to build bunches in a single-tree selection

harvest, and the lower volume per cycle for both skidders.

Estimated skidding productivity increased with the percentage of the stand removed but was also influenced by

differences in average stem size. Felling productivity was more closely related to the d.b.h. of the felled stems. For the

grapple skidder in 1991, a IO-percent increase in harvest intensity resulted in a 30 cf/hr increase in productivity, and a

$0.70 decrease in the cost per ccf produced. The dual benefits of increased productivity and decreasing per-unit cost

associated with increasing harvest intensity substantiate conventional wisdom that clearcutting is a cheaper form of

harvest, is more productive, and hence, more efficiently utilizes logging machinery capital investment. For example, in

this study the average yearly investment (a measure of yearly capital cost) for the grapple skidder is $95,000. Estimated

productivity of this skidder for the single-tree selection harvesting method was 3.21 ccfihr, for the shelterwood method,

4.47 ccflhr, and for the clearcut method, 5.06 ccf/hr. Thus, productivity on the clearcut is 1.58 times that of the singletree method, a 58-percent increase in capital-use efficiency.

The residueal impact analysis identified a significant increase in soil bulk density in the skid trails because of the

concentrated traffic patterns. Residual tree damage was higher for the single-tree selection method than for the

shelterwood method because of the high residual tree density.

Although the lower harvesting intensities had higher costs, higher residual tree damage, and a higher soil bulk density

increase, it had the lowest percentage of total area in skid trails and disturbed area, thus providing a continuous ground

cover. For some forest land managers, the higher cost of the single-tree selection method is compensated by its esthetic

quality, continuous canopy, high percentage of site unaffected by harvest, and improved natural regeneration. The effect

of multiple, closer spaced entries by harvesting equipment into forest stands on some of these qualities is still unknown.

Additionally, the results of the postharvest survey confirm that total ecological disturbance, based on the percentage of

the stand trafficked, is much lower with single-tree selection than with clearcutting.

238
The results of the harvesting study describe relative time and cost of operations for different harvest intensities given a

single operator. The predictive ability of these equations for a broader spectrum of options is yet to be tested. In the

summer of 1993, harvesting operations were observed, and postharvest assessments were performed on six new stands.

The stands included group selection, single-tree selection pine, and single-tree selection pine/hardwood. The operator

and equipment used in the 199 1 and 1992 studies were not used in the 1993 study. The diameter distributions of these

six new stands were statistically similar to the stands from the 1991 and 1992 studies.

The regression equations developed in 1991 and 1992 will be applied to this new data. Additional variables to

account for differences in machinery will be added to the equations. This is the next step in developing reliable

predictive equations.

The controversy between even-aged versus uneven-aged management and their associated silvicultural methods will

continue, especially for public land management. For many proponents of uneven-aged management, harvesting cost and

economic efficiency are a distant third consideration after maintaining stand visual quality and minimizing individual

stand disturbance. Even-aged management advocates champion harvesting and capital efficiency as preeminent concerns.

Two even-aged reproduction methods are compared in this study with a single-tree selection harvest in an initial basal

area reduction cut intended to bring an even-aged stand to uneven-aged structure. Harvesting productivity and cost for

these operations were determined by the pre-harvest stand conditions, average tree size removed and the spatial

distribution of the trees on the site.

239
Litemtule Cited

American Society for Testing and Materials. 1992. Standard practices for correction of unit weight and water content for

soils containing oversized particles. In: ASTM Standards on soil compaction. Standard D 47 18-87. Philadelphia:

American Society for Testing and Materials: 123-124.

Bell, R. D. 1989. Influences of varying stand harvest methods on timber harvesting costs in southwestern Virginia

hardwoods. Blacksburg, VA: Industrial Forestry Operations Program, College of Forestry, Virginia Polytechnic

Institute and State University. 69 p. M.S. thesis.

Clark, A. C.; Saucier, J. R. 1990. Tables for estimating total-tree weights, stem weights and volumes of planted and

natural southern pines in the southeast. Res. pap. 79. Macon, GA: Georgia Forestry Commission, Research Division.

23 p. ,

Hannah, P.; Kiln, M.; Kinnett, D. 198 1. Some impacts of whole-tree harvesting under some different silvicultural

methoLds. Northern Logger and Timber Processing. 29( 11):60-6 1,82,84.

Kellogg, L. D.; Pilkerton, S. J.; Edwards, R. M. 1991. Logging requirements to meet new forestry prescriptions. In:

Proceedings: Council on Forest Engineering 1991 Annual Meeting; July 22-25, 1991; Nanaimo, British Columbia.

Nanaimo, British Columbia: Faculty of Forestry, University of British Columbia with McMillan Bloedel Ltd.: 43-49.

Miller, Gary W.; Sarles, Raymond L. 1986. Costs, yields and revenues associated with thinning and clearcutting sixty

year old cherry-maple stands. Res. pap. NE-582. Brosmall, PA: U. S. Department of Agriculture, Forest Service,

Northeastern Forest Experiment Station. 16 p.

Miller, G. W.; Smith, H. C. 1991. Applying group selection in upland hardwoods. In: Proceedings: Uneven-aged

silviculture of upland hardwood stands workshop. February 25-27, 1991; Blacksburg, VA. Blacksburg, VA:

Industrial Forestry Operations Program, College of Forestry, Virginia Polytechnic Institute and State University,

Cooperative Extension Service. 6 p.

Miyata, E. S. 1980. Determining fixed and operational costs of logging equipment. Gen. tech. rep. NC-55. St. Paul,

MN: U. S. Department of Agriculture, Forest Service, Northcentral Forest Experiment Station. 16 p.

Sloan, H. 1991. Uneven-aged silviculture: impacts on loggers. In: Proceedings, Uneven-aged silviculture of upland

hardwood stands workshop. February 25-27, 1991; Blacksburg, VA. Blacksburg, VA: Industrial Forestry

Operations Program, College of Forestry, Virginia Polytechnic Institute and State University, Cooperative Extension

Service. 4 p.

240
Understanding People and Natural Resource Relationships:

Ouachita National Forest Timber Purchasers

and Changing Timber Harvest Polh$

Christine Overdevest and Donald B.K. English2

AIwrRAcT

Seventeen woods workers addressed the Ouachita National Forest’s 1967

shift from uneven-aged management to even-aged management and the 1988-89

shift to uneven-aged management of the forest. Respondents’ unique views, values,

and stakes are heard, and emergent similarities and differences among them are

analyzed in a qualitative study. While a majority of 17 participants criticized the

Ouachita National Forest’s recent transition to uneven-aged management, other

study participants lauded the Ouachita National Forest’s move to uneven-aged

management. In the following pages, the variety of ways in which the woods

workers perceived and valued the use and management of timber is reported.

Studying perceptions and values regarding timber management aids us in generating

a better understanding of people and natural resource relationships.

Keywords: Harvest method, even-aged management, uneven-aged management,

ecosystem management, loggers.

INTRODUCTION

The Strategy for the 1990’s for USDA Forest Service Research calls for increased understanding of people

and natural resource relationships, increased understandii of how people perceive and value the protection,

management, and use of natural resources (USDA 199Ob), and. studies of rural community residents’ values and ways

of life (USDA 1991). Harvest policy changes on the Ouachita National Forest in southwestern Arkansas and eastern

Oklahoma have affected woods workers and their natural resource relationships. In this study, an attempt is made to

reconstruct the perceived past effects of harvest policy change and to document the anticipated future impacts of

recent policy change on Ouachita National Forest woods workers. The first section of this paper provides

information on Ouachita National Forest harvest policy changes; reviews of previous studies are documented in the

second section. Methods and sampling techniques are described in the third section. The major portion of the paper

presents a summary of 17 in-depth interviews with Ouachita National Forest timber purchasers. The final section

provides discussion and conclusions.

Harvest Policy Changes

Even-aged management is a system of managing timber so that all trees within a particular stand are the

same age class (Horwitz 1974). Certain tree species regenerate better under even-aged conditions, particularly shadeintolerant species. These species include yellow poplar, black walnut, black cherry, and white birch as well as

southern pine and Douglas fir (Horwitz 1974). Harvest methods used to establish and maintain even-aged

management include clearcut, seedtree, and shelterwood.

Uneven-aged management is a system of cutting single trees, or small groups of trees, of varying ages,

leaving others to grow and disperse seeds in the resulting openings (Smith 1986). Harvest methods used to establish

and maintain uneven-aged stands include single tree and group selection.

’ Paper presented at the Symposium on Ecosystem Management Research in the Ouachita

Mountains: Pretreatment Conditions and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

* Social Scientist and Research Social Scientist respectively, USDA Forest Service, Southeastern

Forest Experiment Station, Athens, GA 30602-2044.

241
A Gnning is a preharvest cut used in uneven-aged and even-aged management. Thinning is undertaken to

remove undesirable species and trees in poor health from a growing stand to increase the total yield of high-quality

trees at harvest time in either type of management (Holland and others 1990). The illustrations in figure 1 depict a

harvested area after removal by even-aged and uneven-aged harvest methods.

Single Tree Selection -

Group Selaetkm -

Figure I.-Definition of harvest methods Sowee: U.S. Department of Agriculture. l!BOa.

7

Trees of various sizea, dispersed throughout the forest, are

indiidually selected for cutting Harvest treatments

enhance or maintain the uneven-aged character of the

stand.

Small groups of trees are cut in l/4 to 2 acre sires.

Several cuts are made over a period of 10 years. The first

cut is designed to remove over-mature trees. The second

cut uniformly opens the canopy in order to afford sufficient

light and warmth to stimulate germination, establishment

and survival of the seedlings. Finally, comes one or more

cuttings in which the remaining old treea are removed for

the development of the new stand.

Most trees ate removed in one cut, leaving 12 to 15 wellspaced, seed producing trees over each acre.

Trees larger than 1 to 2 inches in dieter are generally

removed from a specific area at one time. Some trees am

left within the area to address wildlife, soil, water and visual

needs.

242
Harvest Policy Change 1: From Uneven-aged Management to Even-aged Management

The Ouachita National Forest practiced uneven-aged management on its 1.6 million acres of forest land until

1%7. In 1967, it began replacing single-tree selection with clearcutting and seedtree removal. In 1%9, the

multinational Weyerhauser Corporation bought the firm, Die&s Forest Inc. Die&s owned 1.8 miiiion acres of forest

land adjacent to and intermingled with the Ouachita National Forest timberlands and had also practiced uneven-aged

management by single tree selection. When Weyerhauser bought Die&s in 1970, Weyerhauser implemented an evenaged management strategy. Weyerhauser used clearcutting, slash removal, site preparation, and planting of

genetically superior loblolly pine seedlings. Clearcuts were performed on 30-year intervals and the land was

replanted (Smith 1986).

,Thus, the two largest timberland holders in the Ouachita Mountains changed their harvest policy to evenaged management in the late 1960’s. Through 1988, over 250,000 acres of the Ouachita National Forest were

harvested by the even-aged method. According to forest records, no uneven-aged management was used in the

intervening two decades, 1%7 to 1988 (see table 1).

Table 1. - Acres Harvested by Harvest Method, ONF FY 1967 - l!B2*

Uneven-aged management Even-aged management

1%7-1988 0

\

268,762

19881992 1437g 24,045

SOURCE: Ouachita National Forest timber management staff, November l!X!.

*Includes all sales valued greater than $2000 and all permit sales, excluding personal use firewood.

Harvest Policy 2: The Return of Uneven-aged Management on the Ouachita National Forest

In fatal year (FY) 1989, the Ouachita National Forest reintroduced uneven-aged management and

significantly reduced clearcutting in the forest. Planned uneven-aged management sales increased from zero acres

annually to 15,000, and planned annual clearcut sales decreased from 16,000 acres to 5,300 acres (a 67-percent

reduction in clearcutting). A 9-percent reduction in total timber available for sale was planned as well (USDA

1990a). However, due to a variety of factors, inchtding policy changes and appeals on timber sales since 1988,

reduced amounts of timber have been sold. In FY 1991, zero acres timber by the clearcut method and 3,761 acres by

uneven-aged management methods were sold on the Ouachita. In fiscal year 1992, harvesting by uneven-aged

techniques increased to 11,349 acres while the number of clearcut acres remained at zero.

A typical pulpwood operation before 1976 involved no investment beyond a chainsaw and a single-axle truck

(Watson and others 1977). By 1987 in Arkansas, one-quarter of all logging operations were high-production

operations having eight or more employees (27.4 percent), and investments of more than SlOO,ooO were not

uncommon. For example, in 1992, a crew with a feller buncher, grapple skidder, knuckleboom loader, and truck

driver would require a $380,000 to $450,000 equipment investment. In 1987,63 percent of operations in Arkansas

used knuckleboom loaders (at a cost of $90,000 to $110,000); the same percentage used diesel tractor trailers ($70,009

to $100,000); 57 percent used rubber-tired grapple skidders ($85,000 to $95,000) and 26.1 percent used rubber-tired

feller bunchers ($135,000 to $145,000) (Watson and others 1989).

ISSUES RAISED IN OTHER STUDIES

In three recent studies, loggers and other timber industry members were interviewed concerning forestry

activities in their communities. Kusel (1991) interviewed independent and gyppo3 loggers who expressed concern

that national forest policies favored the interests of large-scale forest industry over the interests of independent and

gyppo loggers. More timber was harvested from the two studied national forests in the 1980’s than ever before, but

3 An independent operator who does not purchase timber directly, but generally operates timber

purchased by others.

243
independent and gyppo loggers reported it more difticult to purchase timber because large companies dominated

timber sale contracts (Kusell991). When large companies dominate local timber purchases, Kusel suggests such

companies hold powerful influence over the well-being of independent and gyppo loggers by setting logging rates, and

telling loggers when and how much timber to harvest. Once independent and gyppo loggers are constrained in how

much work they can get and how much they will be paid for it, they perceive a loss of control over their lives,

reducing their sense of social well-being (Kusell991, Fortmann 1991).

Bliss and Flick found that while most timber industry members valued the economic efficiency of businesslike

high volume producers and high volume producers depended on high-volume per acre sales to pay off equipment

debt, truck and chainsaw pulpwood producers highly valued maintenance of subsistence patterns associated with low

volume logging. Access to wood was a main concern for these producers. In the focused interviews, truck and

chainsaw loggers complained about how difficult it was to locate timber because of the competition from mechanized

producers, ‘timber brokers, and mills.

Bliss and Flick concluded that while traditional truck and chainsaw haulers are largely a thing of the past,

low volume operators continue to find a niche in small tracts, salvaging damaged timber or in environmentally

sensitive areas. One of Bliss and Flick’s interviewees described the niche for low-volume producers:

“It is still a need for little producers, because you got somebody who’s got five acres, a little tract of timber

I here around their house, may not be but 50 cords of wood. Big producers, he can’t move all his bii

equipment in, his bull dozer up there to make a road, and his loader, and skidder and all that to cut one day,

you see. So it’s a demand for the little producer, and it always will be” (p. 17).

Fortmann and others (1990) in a study of participants at Redwood Summer4 found that some local timber

industry workers were concerned with potential adverse effects of harvest intensity on forest health. Some timbersector employees concerned about forest health felt the Forest Service and forest industry used inappropriate

practices. One logger complained about the extent of timber harvesting in the area: “If we didn’t have a Sierra Club,

we probably would have no trees up here. People are greedy. The companies would have cut all the trees up here.”

A number of timber industry workers interviewed claimed they hated clearcuts (Fortnuum and others 1990).

Each of these qualitative studies suggests that some timber industry workers have concerns and interests

different from large-scale forest industry. Bliss and Flick found truck and chainsaw loggers that were concerned

about access to timber sales and competition from economically powerful actors. Kusel’s independent and gyppo

loggers feared the domination of timber purchases by forest industry, and Fortmann and others’ “environmentalist

loggers” were concerned about the amount of timber taken from local national forests. These studies suggest that

some members of the timber industry, particularly truck and chainsaw and independent and gyppo loggers, have

experienced the modernization and mechanization of the timber industry as a potential threat to their way of life or

as a perceived threat to forest health.

METHODS

Samples for this study of attitudes toward changing harvest policy were taken from USDA Forest Service

form 2400-17, timber sale proof listings, from the fast quarter of FY 1985 through the fourth quarter of FY 1991.

Such a form is completed for each timber sale valued at over $2,000. Information such as timber purchaser name,

purchase date, size, and minimum bid from each sale were compiled. All purchasers who bought Ouachita National

Forest timber sales contracts, both before and after the implementation of uneven-aged management in FY 1989

were the target sample. Twenty-seven timber purchasers met the target sample criteria; they included 15 product

mills, 6 timber brokers, and 6 loggers in the target sample. Contacts were attempted with all of them. The linal

sample of 17 included 5 of the mills, all 6 of the timber brokers, and all 6 of the loggers. Years of experience in

woods work in the Ouachita Mountains in this final sample ranged from 8 years to 42 years with a mean of 23 years.

4 An environmentalist-sponsored event, protesting the cutting of northern California redwoods.

244
Interviews were conducted in person between December 30,1991, and January 11,1992, at respondents’

homes or businesses. Interviews lasted from 1 to 2.5 hours and were tape-recorded. In the semi-structured

interviews, an interview schedule was used to guide dizussion, and interviewees were encouraged to discuss their

views and perceived experiences related to Ouachita National Forest harvest policies. Semistructured interviews are

approximations of a formal questionnaire and are usually chosen when the researcher wants to develop comparative

data (Fetterman 1989). In this case, wmparisons of respondents’ perceptions of harvest policy were planned.

After wllecting life-history data regarding early experiences in the local timber industry, respondents were

asked about the anticipated impacts and perceived past impacts of harvest policy change. Respondents were asked

questions about what it was like when the Ouachita National Forest switched harvest policies (i.e., “Do you remember

when the Ouachita National Forest started even-aged/uneven-aged management? Describe that time. How did the

change affect you? Was the change for the better?“). While each respondent was asked to restrict their comments to

perceptions of different harvest policies, respondents raised issues of timber availability as well.

Qualitative methods of research differ from quantitative in that quantitative methods are generally used for

quantify&I population parameters, generating statistically valid generalizations about population samples, and for

estimating degrees of confidence associated with research hypotheses. Qualitative research results, on the other hand,

are generally used for discovering unknown relationships between beliefs, attitudes, behavior, and contexts, thus

generating important parameters and hypotheses rather than quantifying and testing them (Bliss and Martin 1989).

Because people may perceive and experience circumstances differently, respondents’ perceptions may not wnform to

“objective” reality, nevertheless understanding them may help researchers, research audiences, and policymakers

understand why members of a particular social group feel and act like they do (Fetterman 1989, Henderson 1991).

For more information about qualitative research see Linwln and Guba (1985).

RESULTS

The Supporters of Even-aged Management

The majority of interviewees (n= 12) highly valued even-aged management for its production efficiency and

its capability to produce high volumes of timber. They think that clearcutting is environmentally feasible and

sustainable. Because of the percieved economic inefficiency of uneven-aged management, the supporters of evenaged management feel that the size and number of timber harvesting operations will decline, and they are wncemed

with the impact of reduced-timber availability. The combination of reduced efficiencies and reduced stumpage has

caused this group apprehension and fear about their current and future dependency on Ouachita National Forest

timber and about the viability of the local economy. The supporters of even-aged management included all 5 mill

buyers, 4 of the 6 timber brokers,and 3 of the 6 loggers.

The Supporters of Uneven-aged Management

The supporters of uneven-aged management (n=5) fondly remembered the forest management that Die&s

and the Ouachita National Forest practiced before 1967. They recalled the high quality of timber and the small

crews of harvesters that were supported by uneven-aged management in the 1960’s. In the 1970’s, when clearcutting

became the dominant harvesting method and timber production increased, these interviewees remembered the

demand for high-production logging. However, it appears that some logging operators resented the changes and felt

that high-production operations were squeezing smaller operations out of their traditional ways of life. Much like the

respondents to Bliss and Flick’s study, these respondents report seeing large mills often outbid everyone else on

desirable high-volume sales. The respondents began to associate clearcutting with both the demise of low-production

logging and to the clearing of the forest. As evidenced in the interviews, they questioned whether even-aged

management would lead to the whole forest beii cut. Today, these interviewees praise the return to uneven-aged

management, because they think uneven-aged management will lead to more low-production loggers and to better

protection of the forest resource. However, they fear the effect of “preservationists” and “environmentalists” on

timber availability because less timber has been available to harvest than planned.

Thus, the interview data suggest that not all members of the timber industry view changing harvest policy in

the same way. In the eyes of uneven-aged management supporters, the intensive timber management of the Ouachita

245
National Forest and surrounding lands practiced in the 1970's and 1980's threatened demise of local forests and thus

their livelihoods. The high volume harvesting is felt to be non-sustainable, and the high production crews are felt to

be stealing jobs from low volume loggers. From the perspective of supporters of even-aged management, the

intensive management of the 1970’s and 1980’s was acceptable, supported their livelihoods,and they fear that the

return to uneven-aged management will negatively affect high volume operations. All interviewees agree that evenaged management favors high production logging, which is felt to be threatened by the return to uneven-aged

management.

In the rest of the paper, the perspectives presented above will be documented through the actual words of

the respondents? Fist the views of the supporters of even-aged management will be presented and the views of

supporters of uneven-aged management follow. Tables 2 and 3 provide descriptive statistics of respondents.

Table 2 - Supporters of Uneven-aged management on the ONF

Y~iUlOCdtilUbCX

industry

Table 3 - Supporters of Even-aged management on the ONF

limber broker 3 35

Tiiber broker 4 26

Logger 4 13

Loggtr 5 31

Timber broker 5 12

Timber broLcr 6 34

Mill buyer 3 18

Mill buyer 4 1s

Mill buyer 5 25

Mill buyer 6 26

8

’ Written permission was obtained from respondents by researchers to include direct quotes in

publication.

246
The Interview Data

The 12 supporters of even-aged management criticized the economic inefficiency of uneven-aged

management, and praised the efficiency of even-aged management, particularly clearcutting. Many noted their

logging and production costs will increase significantly under uneven-aged management.

“On a thinning, just the average thinning sale, you’re going to cut [a logger’s] production down. You’re going

to take off at the least, at the very least 30 to 35 percent of their production (Timber broker 6).”

“It’ll cost 20 to 25 percent more to harvest uneven-aged cuts than it does clean cuts, and that was the, that’s

one of the big things that’s happened to us (Timber broker 4).”

’ “You still got the same amount of labor involved, at the end of the day, and you get half the production

(Logger 6).”

( Because of the reduced efficiencies and profits, timber purchasers emphasii that uneven-aged management

has resulted in higher costs to mills,which they believe will make their products less competitive with products from

other areas and will result in lay-offs for both logging hands and mill workers.

“When you take a local area and change from even-aged management to uneven-aged management, you

increase the logging cost and that is reflected in the total cost of the finished product and then that product

has to go out on the market place and compete with other products from other areas and it’s not possible to

do that; you can’t compete with someone when your cost is more than theirs (Mii buyer 3).”

“You’ve got to have a certain volume per acre before it’s profitable for that [logging] contractor to go out

there.... If he can’t get two loads a day, I end up paying him for that second load because it takes him two

loads to make payments and everything and to show a profit.... It gets to the point where you add the

stumpage and what I paid for the logging and manufacturing costs, I can’t sell it for a profit... (Mill buyer 4)”

“[Under uneven-aged management] all your men that’s working for you that’s paid by the ton - they can’t

make it.... You’ve got hands that you’ve got to lay off on single tree selection... Just strictly going to unevenaged management is - we’d just have to fold up - there’s just no way that we can do it up here (Logger 4).”

Many supporters of even-aged management felt that the size of timber operations will decline, noting that

larger logging operators will have to downsize. It will be difficult to support highly mechanized operations with

uneven-aged management. The following comments were typical:

“The size of them is definitely having to change... I’m not saying a larger contractor can’t work a thhming or

anything - but most of the larger contractors are just locked in with ‘I have to have this amount of volume

per acre before I can make any money... [One large contractor I know’s] got three trucks, three skidders and

a loader and he’s got eight people - three truck drivers, three skidder drivers, and a couple of saw hands and

himself. Well he has to move four loads a day just to pay these guys to be out there and then he has to

move another load to pay the insurance and costs . . . it was narrowing down to where he was going to have

to split his crew, buy another loader and promote him somebody to run one of the crews while he run the

other one. Well he just wasn’t going to do that so he sold out. He was a million dollar operator (Mill buyer

4).”

“In this area, basically all the loggers are equipped the same, some of them just have more, they have the

same types of equipment, some of them just have more than the others. Four-wheel drive skidders and

hydraulic loaders and tree-length operations, basically. We still have a few small shortwood guy who cut with

a chainsaw and load them by hand and haul with small loading each day. There’s very few of the small

equipment operators still left here. I think that the changes that would affect the loggers, if you go down to

uneven-aged management, where you’ve got a smaller clip per acre and smaller sales in an area, the loggers

that have a lot of equipment will be forced to downsize because they can’t move every other day (Mill buyer

3).”

“We have cut back to just two skidders and two trucks... (Logger 4)”

247
Supporters feared that environmental groups will be successful in stopping timber sales, reducing timber

needed to supply mills and sustain logging operations. While respondents were asked to restrict comments to

opinions on even-aged and uneven-aged management on the Ouachita National Forest, they often raised issues of

reduced timber availability.

“Just by a stroke of the pen [a preservation&t] can appeal every sale that comes out of the Ouachita National

Forest. They can lock you out, and the Forest Service has its administrative appeals process which was

created to allow the public to have an input in Forest Service decisions and to appeal any decisions they felt

like were a problem. But these appeals are just automatic appeals. Anything that has to do with even-aged

management, that is not selective cutting [a preservation% can] just automatically appeal. And you can stop

an entire forest, and that has been clearly illustrated here on the Ouachita... Where they have a normal sale

schedule of 175 million feet, they only sold something like 35 million feet (Mill buyer l).”

“Originally the preservationists, is a word I like to use rather than environmentalist, because I consider myself

as much an environmentalist as anybody. The preservationists originally only appealed sales for clear cutting

that were geared toward even-aged management. Or&ally. It seems to be now they appeal everything

. . ..They have had a tremendous number of appeals on the Ouachita which its my understanding has slowed

the process down, even kept a lot of timber off the market. Many millions of board feet that otherwise

would have been sold have been delayed, a lot has been cancelled. The main problem everybody [in the

timber industry] has is they’re not selling anything (Mii buyer !I).”

With the combination of uneven-aged management and reduced timber availability, timber purchasers

expressed concerns about the total economic impact to the area.

There’s three counties right here that really depend on timber and without it, they just don’t know what to

do. Our schools are going to suffer, county roads are going to suffer...1 don’t want to say anything bad about

anybody because they have their points too. And we could all work right here if they’d set down at the table

and be broad-minded about it. They could have what they wanted and we could have what we wanted. I

think everyone involved in the timber should be at a table somewhere giving his point (Timber broker 3).”

“From your loggers out in the woods all the way down to your grocery store in the community, your service

stations, everybody suffers as a result of it. So you can’t say its just the timber industry --that they’re the

only ones, just those old loggers and sawmill people. That’s not all that’s involved - your schools are involved

in it. Your supermarket’s involved in it. Your bank’s involved in it. Your parts store in that town-he’s

selling parts to those loggers - your tire dealership. He’s not going to be able to sell any tires if those

loggers aren’t rolling those trucks and blowing out tires you know (Mii buyer 2).”

“All of Arkansas really is heavily dependent on the forest industry, and a lot of people tend to forget that...1

just want the people of Arkansas to realize how vital it is to the economic well&ii of this state and to

these areas throughout the Ouachita and Ozark Forests, and that they should do everything they can to keep

the programs, support the programs, and support the Forest Service (Mill buyer l).”

To mitigate these negative consequences, even-aged management supporters suggested several courses

including increased volume per acre on single tree selections, maintaining the total sales volume as in the USDA

Forest Service, Ouachita National Forest Plan, and balancing more clearcuts with the uneven-aged management.

“It wouldn’t be (bad) if they’d mark more volume per acre. They still could have uneven-aged management,

still leave a good stand and they could go in there two or three times and thin it (Timber buyer 6).

“As long as they would just sell something close to their sales targets which are part of their forest plans that

they spent many millions of dollars developing, if they’d get even close to those sales targets everybody would

be okay.... (Mii buyer 5)”

“Basically, what the Forest Service has done for the past ten years, from the late seventies to the middle

eighties was a good plan. But as far as coming out with all this uneven-aged management... I just don’t

know... I’d like to see clearcutting put back in places, I believe it’s got it’s place. I just want to make sure

that gets in there, the clearcutting (Logger 4)”

248
On the other hand, a consistent theme in the interviews with supporters of uneven-aged management is that

smaller operators will benefit from uneven-aged management and that uneven-aged management ensures the

protection of the forest resource for future generations while clearcutting threatened demise of the forest. The 5

supporters of uneven-aged management expressed approval of the Ouachita National Forest management for deemphasizing clearcut harvesting and reintroducing uneven-aged management since FY 1989. These respondents see

uneven-aged management as capable of indefinitely sustaining high quality timber harvesting as a natural resource

employment opportuni~, while they see even-aged management, especially clearcutting, as exploiting timber and

curtailing natural resource employment opportunities for themselves and their children.

“I’m glad to see it [clearcutting] stop . . . but it’s something that I thought that ought to be done 20 years ago.

Because I’ve got a grandson and I hope that he never logs but, if he wants to log...in 20 years if we keep

clearcutting what’s he going to haul? (Logger 1)”

“I could say yes I’m 100 percent in favor of the clearcutting . . . But I can say if we do there’ll come a time

when we won’t have anything to do. If you clearcut everythin& you know, you’ve got to wait for it to grow

’ back and that just ain’t going to work (Logger 2).”

Several believed that both Weyerhauser and the Forest Service would run out of timber if they continued

clearcutting at the rate of harvest between 196%1988.

I’d seen that they (Weyerhauser) were going to run out of timber. Anyone with common sense could tell it.

I saw that it would grow, but it had to bc thinned if they were going to grow more volume on those... I

believe that they could have selectively managed it and continued on (Timber broker 2).”

Y’hey almost waited too long to stop clearcutting. That was the statement that I made. They’ve almost got

everything clearcutted in this country...(How do you feel about clearcutting?)..Well I’m not for it. They’re

ruining the timber. Because they’ve got it cut out and it’s not growing back. Of course, Weyerhauser

wouldn’t agree with this but that don’t make any difference - I’ve lived here all my life and I can see. So

long as Dierks lumber and coal company had the company here in Arkansas, they select cut. Well, they had

timber to cut on all the time and when Weyerhauser bought them out they started clear cutting and they

don’t have it any more to cut. The Forest Service done like Weyerhauser - they clear cut a lot - and I wasn’t

for that - but that didn’t make any difference; they did it anyhow. But the way they mark their trees in select

cut why I think they do alright with that. Well of course naturally I think that’s what they’re suppose to do

(Logger 3). ”

Like Bliss and Flick and Kusel’s respondents, several supporters of uneven-aged management felt that a

clearcut policy favored forest industry and large-volume operations and marginalized smaller producers. The laborsaving technologies of the 1970’s and 1980’s increased the overall efficiency of the harvesting process but at the cost

of some traditional rural subsistence occupations.

When they went to clearcutting, the big operations bought all the clearcut timber because it was so much

volume that the smaller loggers couldn’t afford to buy it...1 think that they went astray a little bit on their

clearcutting; and one of the reasons that I think they did was they put too much volume into each sale, and

that if they had kept the volume down for where the smaller, individual loggers could have handled it, it

would have been better (Logger 2).”

“If there’s a million feet of timber, you can’t go buy it. So it is, and I can understand their point about it, it’s

easier for the government to forget coming out here and painting a little old ranger sale. They’ll just run out

there and sell it all in a big sale. But what they was doing - they was starving the little man out. See, they

forced that little man to go to work for the bii man and . ..then the only terms that we had was to get in, was

to get the skidders and stuff and get in and go and play with the bii boys (Logger l).”

“They got these mills they just - the government just got to throwing everything out there for the bii man to

buy so they just choked us out. Our only terms that we had left was to get in then and to get into bii

logging and go a-logging for the bii outfit. Because they went to making these bii old clearcut units, and

these sales was so big that a guy like me couldn’t buy them (Logger l).”

249
Finally, supporters of uneven-aged management sympathized with current high production, me&nized

loggers. The supporters of uneven-aged management felt the high production loggers needed clearcuts in order to

remain profitable and to pay their equipment capital costs. Without clearcuts they will have to downsize. As Bliss

and Flick report, these respondents feel high production loggers need ‘bii volume jobs’ to remain viable.

“True, I hate to see clearcuts stop [because] I got a lot of friends that are still in logging that needs the

clearcuts. I know what it is to owe money. I know what it is to buy this equipment. I’ve been there.... They

really need [clearcuts] to get by because it all comes down again to production. If you can’t get production,

you can’t make it... But people get their operations too bii. With the loggers that’s got the one truck, one

skidder, one loader operation - they’re going to survive (Logger l).”

“Now I can see where some of the bii companies are coming from they got millions of dolIars worth of

machines that just wilI not work in a you know an [uneven-aged] management program. They just won’t

work in it. When you’ve got all kinds of expensive equipment and stufI like that it just won’t- it’s not feasible

to use it. And that’s the reason they’re turning it back to a smaller logger again because he can deal with it

and they can’t. And I think that is the best place for it to be. When the companies - the bii companies get

involved in it it takes a lot of logging really. It takes a lot away from the individuals and you know all of the

loggers, in this area especially, are small operations run by families or one man and he is responsiile for all

of it and he can pretty well take care of it but when you get into a bii company and they contract it out

nobody hadn’t really got anybody to answer to.... And that I think is what thefre running into a lot of times

’ is damaging the forest to where it can’t be repaired if you get people in there that don’t care or you know

just kind of make quick money in it and get out of there (Logger 2).

“Course it’s going to hurt these guys that are rigged up bii who have S4ClO-SsoO,OOO invested. But there’s

just a few of those, there’ll be a lot more employed. But see, a lot of bii ones aren’t going to like that. It’s

going to hurt a few, but when they switched over back in the 70’s, when they switched it hurt a bunch of

people (Timber broker 1).

The supporters of uneven-aged management also prefer uneven-aged management because they think it will

ensure the protection of the forest from overcutting and provide high quality timber.

“I think it was better when they was selective cutting than I do for clearcutting. Because you had a better

grade of lumber, and you wouldn’t run out of timber, and they worked so many more people (Timber broker

l).”

“I think that it’s better for the environment, for the forest, and every&@ to uneven-age manage the

timber... [There] will always be timber there - there will always be a forest there (Logger 2).”

DISCUSSION AND CONCLUSIONS

When the Ouachita National Forest and Weyerhauser switched to even-aged management, the production

efficiency of high volume even-aged management provided the margins needed to support the rational ownership of

expensive mechanized equipment. As mechanized equipment was adopted by several firms within the area, it altered

the general demand for workers with particular skills. SmalI logging companies on the competitive margins were

likely eliminated.

Some small operators survived by cutting smaIl volume sales such as ranger sales or other sales in hard to

get to areas because small operations are more efficient at low volume logging than large heavily-capitalized

operations which need a certain production efficiency to cover the costs of the use of their equipment. As long as

high volume per acre even-aged management dominated harvesting on the national forest, large operations were

supported. Since the return to uneven-aged management, the rational size of operation likely will be smaller than

that supported by an even-aged regime.

Several past studies have shown that some timber purchasers and timber industry members have experienced

the economic rationalization of timber production and harvesting as a threat to their subsistence needs or a threat to

the sustainabiity of the forest; while other industry members praised the economic efficiency and overall social

250
benefit of high production silviculture and harvesting. The researchers point to the importance of understanding

how historical aspects of harvest policy actively structure the rational organization of local timber industry.

Rational economic behavior among firms varies according to the profitability of various employment

strategies under different market conditions (Marchak 1988). Behavior that is rational for a small company operating

on a thin margin with a small capital investment may not be rational for a large company. Similarly, the amount of

capital a large heavily-capitalized firm can invest in technological advancements may not be an option for a small

company. In this study, the different levels of support for even-aged and uneven-aged management may vary with the

rational economic interest at the firm level.

The interview participants suggested that even-aged management benefits high volume timber operations and

marginahxes low volume operations. The even-aged management of the 1970’s and 1980’s was perceived by timber

purchasers to favor the economic well&ii of high production timber operations. Now uneven-aged management is

expected by all to favor smaller operations. Thus, the viability of high and low volume timber operations seem to be

directly related to harvest policy.

Forest managers plan for wildlife values, for recreation values, and for the effects of one resource use on a

another. More should be done to assess the complex human dimensions traded off within resource decisions. In the

case of Quachita National Forest, new management policies will not only affect the overall productivity of the forest

and the overall economic impact on the area, but also the well-b&g and structure of people and natural resource

relationships. An important consideration in implementing new policies is not only the interaction of ecological links

among resource systems but also of ecological links with human systems, including the social structure and welfare of

local timber industry members. In this paper, the researchers attempt to draw greater attention to the need to assess

these human dimension affected by and traded off within resource decisions.

FUTURE DIRECTIONS

It is highly recommended that the Ouachita National Forest take on research that further develops

information on the relationship between forest policy and the wellbeing of different operators. The number and

kind of loggers in the Ouachita area, the number of mills, and their well-beii as defined by both their own values as

well as traditional economic and ecological measures should be tracked through time while controlling for other

variables. In order to develop a policy responsive to the needs of forest-dependent timber purchasers, the Oauchita

National Forest must recogniz the needs and values of different timber industry members. Once the nature of

ecological, economic, and social benefits and tradeoffs of forest management are each better understood, a more

rational accounting of forest management actions and polices may be possible (Brooks and Grant 1992).

LITERATURE CITATIONS

Bliss J.C.; Flick, WA. With a chainsaw and a truck: Lives of Alabama Pulpwood Producers. Unpublished 3-26

Manuscript. Auburn, SC: School of Forestry, Auburn University. 20 p.

Bliss J.C.; Martin, AJ. 1989. Identifying NIPF management motivations with qualitative methods. Forest Science.

35(2): 601622.

Brooks, D J.; Grant, G.E. 1992. New approaches to forest. management. Part 2: Background, science issues, and

research agenda. Journal of Forestry. 90(2): 21-24.

Fetterman, D.M. 1989. Ethnography: step by step. Newbury Park, CA: Sage Publications.

Fortmann, L., Kusel, J. [and others]. 1990. The human costs of the California Forestry Crisis. Unpublished

Manuscript. Berkeley, CA: Department of Forestry and Natural Resources, University of California. 6 p.

Fortmann, L.; Kusel, J. [and others]. 19 9 1. Well&ii in forest-dependent communities. Sacramento, CA: Forest

Publishers, Inc. 245 p. Vol. 1.

251
Henderson, K. 1994. Considerations in using qualitative approaches in studying tourism and natural resources.

AsheviIle, NC: USDA Forest Service, Southeastern Forest Experiment Station: 87-94.

Holland, 1.1.; Rolfe, G.L.; Anderson, DA. 1990. Forests and forestry. DanvilIe, IL: Interstate Publishers, Inc. 476 p.

Horwitz, Eleanor CJ. 19 74.Clearcutting a view from the top. Washington, DC: Acropolis Books Ltd. 179 p.

Ku&, J. 1991. Well-being in forest-dependent communities. Sacramento, CA: Forest and Rangeland Resources

Assessment Program. 130 p. Vol. 2.

Lincoln, Y.S.; Guba, E.G. 1985. Naturalistic inquiry. Beverly Hills, CA: Sage Publications. 416 p.

Marchak, P. 1983. Green Gold: Forest Industry in British Columbia. Vancouver:

Columbia Press. 454 p.

University of ‘British

Smith, ti 1986. Sawmilk The story of cutting the last great virgin forest east of the Rockies. FayettevilIe, AR:

The University of Arkansas Press.

U.S. Department of Agriculture, Forest Service. 1990a. Amended Laud and Resource Management Plan High@&

Okhita National Forest. Hot Springs, AR. 8 p.

U.S. Department of AgicuIture, Forest Service. 1990b. Strategy for the 90’s for USDA Forest Service Research.

wash&ton, DC. 9 p.

U.S. Department of Agriculture. 1991. Enhancing rural America: National research program. Wasbin@on, DC. 16

PWatson W.F.; Kucera, J.M.; Matthes, R.K. 1977. Pulpwood producer census southwest technical division of the

American Pulpwood Association. Mississippi State, MS: U.S. Department of Agriculture, Forest Service,

Misskippi AgriculturaI and Forestry Experiment Station. #I p.

Watson, W.F.; Day, GA.; Altman, Jim [and others]. 1989. 1987 pulpwood logging contractor survey Southwest aud

southeast teclmicaI divisions of the American Pulpwood Association. Misskippi State, MS: U.S.

Department of Agriculture, Forest Service, Mississippi Agricultural and Forestry Experiment Station. 16 p.

252
Management Costs Associated with Various Reproduction Cutting Methods’

Rodney L. Busby and Richard A. Kluende?

ABSTRACT

Management-cost data were gathered for various reproduction cutting methods as part of

the ecosystem management research in the Ouachita Mountains. Costs were gathered on

both traditional and nontraditional reproduction cutting strategies in an attempt to

determine the cost-effectiveness of each management strategy and to estimate the resource

requirements for wide-scale implementation of each method. Preliminary results indicate

that sale preparation costs are higher for low volume-per-acre cutting methods.

INTRODUCTION

Little is known about the costs of implementing the management strategies being tested on the Ozark and Ouachita

National Forests as a part of the ecosystem management research effort. The reproduction techniques are new to the area,

and it is likely that silvicultural, management, and vegetation control costs will differ from current techniques. A study is

currently underway to determine the management costs associated with the new reproduction methods. Data collection is

not complete; however, an update on the methods of research and some preliminary results are provided here.

METHODS

Data were collected using USDA Forest Service operational crews from the Ouachita and Ozark National Forests. Costcollection forms were filled out by crews after management tasks were performed, and the forms were returned to the Forest

Supervisor’s office for editing. Forms were then bundled and shipped to the researchers for data compilation and analysis.

Data recorded for each activity included location, management objective, area, distance from work center, and labor,

equipment, and supplies used. Ouachita and Ozark National Forest personnel provided figures on the volume of pine and

hardwood products harvested from each sale unit where cost data were collected. The location of each management activity

was carefully noted with data collected on Phase II study sites separated from data collected for the same management activity

on non-Phase II tracts. This was done to eliminate bias due to research activities. Some activities may cost more on tracts

that are being actively monitored for several research studies than they would on operational sites, even though operationalsized (40 acres) units were used in the Phase II studies. Costs may also be higher on management activities that are new

and different as each crew must learn the new requirements. Therefore, a large sample size collected over several years

is proposed to deal with the inherent variability of the data collected and the problems associated with collecting data on new

techniques, especially on actively monitored research sites.

Hours of on-site labor for each individual were assignerl by pay grade and entered on the study forms. Labor cost was

estimated by multiplying these labor hours by a standard cost, which included salary and benefits by grade. The assumption

was made that the average employee had been on the job for about 4 years, making the employee a step 4 for pay purposes.

The collection of hours of labor, not labor cost, will allow for easy updating of cost estimates and easy comparisons of data

collected over several years.

Estimates of the supplies needed to accomplish each task, such as paint and ribbons for marking timber, were made on

the cost-collection forms. Supply costs were obtained by multiplying the supplies used by the current unit cost of each item.

I Paper presented at the Symposium on Ecosystem Management Research in the Ouachita Mountains: Pretreatment Conditions

and Preliminary Findings, Hot Springs, AR, October 26-27, 1993.

2 Research forester, USDA Forest Service, Southern Forest Experiment Station, New Orleans, LA 70113 and professor of

forestry, University of Arkansas at Monticello, AR 71656, respectively.

253
Total transportation costs include the actual cost of operating a vehicle plus the lost labor hours spent commuting. These

costs were estimated but were not used in the comparisons.

Timber harvest volume was calculated as the sum of sawlog volume in cubic feet equivalent and pulpwood volume in

cubic foot volume. All costs were reported as cost per one hundred cubic feet (CCF).

Some difficulties were encountered using voluntarily supplied time and cost data. Records were sometimes obviously

incomplete requiring the sample to be discarded, and, in other cases, time may have been incorrectly estimated.

Nevertheless, there were advantages to using this method of data collection. Costs of this method of data collection, although

significant, are far less than fielding a crew of researchers to gather the data. Obtaining precise estimates of new

management activities is not cost-effective because the crews are likely to become more efficient as they practice the

technique. It is better to have a larger sample size, spread out over several years, than to have more precise estimates of

costs on a smaller sample size, given the variability in the data and the problems estimating the costs of new techniques.

Finally, the key advantage is the use of operational Forest Service teams to perform the work. These teams would be

responsible for undertaking the reproductive practices. Therefore, these crews’ costs should be representative of the

implementation cost for these practices.

RESULTS AND CONCLUSION

Preliminary results are presented to show initial trends in the data; more definitive results will be available as sample

size is increased. Results of the comparisons of marking costs are shown in figure 1.

51 - -

td Labor u Supplies

Commercial Single-tree Shelterwood

thinning selection

............... lizzza

Clearcut

Figure I.-Preliminary results of marking costs per CCF in the Ouachita Mountains.

Marking costs per CCF varied with the intensity of timber removals. Gn non-Phase II sites, on-site labor costs were

$3.79/CCF to mark thinning tracts, $1.70/CCF to mark single-tree selection tracts, and $l.O7/CCF to mark shelterwood

tracts. The cost to mark clearcut tracts on the Phase II study site was $0.91/CCF. Thinning and single-tree selection call

for more expertise and judgement than the clearcutting, and thus, more time is spent in marking. Removal volumes are

concentrated for the intensive cutting practices and are dispersed for extensive cutting. Concentration or dispersal of marked

timber is reflected in marking costs with higher concentration of removals yielding lower per-unit-volume marking costs.

Insufficient data points exist to differentiate between marking costs for all practices. For example, differences in

marking cost between pine-single-tree selection and pine-hardwood-single-tree selection cutting strategies were undetectable

at our sample size. Given the variability of the data, it is not certain that cost distinctions can be made from such similar

activities even with larger sample sizes.

254
LIST OF PARTICIPANTS

SYMPOSIUM ON ECOSYSTEM MANAGEMENT RESEARCH IN THE OUACHITA MOUNTAINS

Leif Anderson

USDA Forest Service

P.O . Box 1270

Hot Springs, AR 71901

(501) 623-1538

Steven (Steve) Anderson

0klshon)a state univ.

239 AG Hall, Forestry Dept.

Stillwater, OK 74075

(405) 744-943 1

John Andre

USFS, Ourk National Forest

Rt. 1, Box36

Hector, AR 72843

(501) 284-3150

\

James (Jim) B. Baker

U.S. Forest Service

P.O. Box 3516

Monticello, AR 71655

(501) 367-2109

Bill J. Ballard

Ballard Tree Farms

HC 15, Box 1365

Watson, OK 74943

(405) 244-3406

Mark Baron

Arkansas Game & Fisk Comm.

2 Natural Resources Drive

Little Rock, AR 72205

(501) 2236300

Richard A. Boitnott

International Paper

P.O. Box 30001

Shreveport, LA 71130

(318) 862-9561

Frank Banner

Southern Forest Exp. Stn.

P.O. Box 9%

Starkville, MS 39759

(601) 325-8983

Raymond (Ray) c. Bout2

Ark. Gam e & Fiab Com m .

911 West “B” St.

Russellville, AR 72801

(501) 967-7577

Rodney (Rod) L. Busby

USFS Southern For. Exp. Sta.

701 Loyola Ave., Rm. T-10210

New Orleans, LA 70113

(504) 589-455 1

October 24i-27,1993

Renaldo L. Bush

U.S. Forest Service

P.O. Box 577

Taliiina, OK 74571

(918) 567-2326

Chris Carlton

Univ. of Ark. at Fayetteville

Dept. Entomol., AGRJ 317

Fayetteville, AR 72701

(501) 575-245 1

Mike Cartwright

Arkansas Gam e & Fish Comm.

2 Natural Resnurces Drive

Little Rock, AR 72205

(501) 2236300

Ken Clough

The Nature Conservancy

300 Spring Bldg. #717

Little Rock, AR 72201

(501) 372-2570

Betty G. Cochran

U.S. Forest Service

P.O. Box 369

Glenwood, AR 71943

(501) 356-4186

Malcolm Cockedtam

U.S. Forest Service

P.O. Box 1270

Hot Springs, AR 71901

(501) 321-5284

Roger Coleman

USPS Guachita National Forest

P.O. Box 1270

Hot Springs, AR 71902

(501) 321-5365

Steve Coleman

Boise- Cascade Corp.

P.O. Box 1060

DeRidder, LA 70634

(3 18) 4624056

Michael (Mike) B. Crane

USDA Forest Service

HCR 69, Box 16

Gden, AR 7196 1

(501) 326-4322

Michael H. Crawford

Crawford Law Firm

415 Guachita Ave.

Hot Springs, AR 71901

(501) 321-1982

David Criner

Arkansas Game & Fish Comm.

#2 Natural Resources Dr.

Little Rock, AR 72205

(501) 223-63 15

John (Mike) M. Curtan

U.S. Forest Service

P.O. Box 1270

Hot Springs, AR 71902

(501) 321-5275

Jack P. Davis

U.S. Forest Service

HCR33, Box9D

Hector, AR 72843

(501) 284-3 150

Jerry W. Davis

USDA Forest Service

Box 1270

Hot Springs, AR 71902-1270

(501) 3214201

Margaret S. Devall

Southern Forest Exp . Sta.

701 Loyola Ave., Rm. T-10210

New Orleans, LA 70113

(504) 5894551

David R. Doss

USDA Forest Service

Rt. 1, Box34

Hector, AR 72843

(501) 284-3150

Kathryn L. Duncan

U.S. Forest Service

P.O. Box 369

Glenwood, AR 71943

(501) 3564186

Hugh C. Durham

Jntemationsl Paper

P.O. Box 448

Arkadelphii, AR 71923

(501) 246-5622

Ann M . Early

Ark. Archeological Survey

P.O. Box H-7841 HSU

Arkadelphii, AR 71999-0001

(501) 246-73 11

Cynthia Edwards

Sen. Bumpers’ Staff

700 W. Capitol Ave.

Little Rock, AR 72201

(501) 3246286

255
Kim Fendley

University of ArkanNa

Dept. of Sociology, 211 Old Main

Fayettevilk, AR 72701

(501) 575-3807

James R. FOE

U.S. Folart Service

P.O. Box 369

Gknwood, AR 71943

(501) 3564186

Tom Foti

ArkAnne Natural Heritage Jnventory

suite 1500, Tower Ruibsng

Link Rock, AR 72201

(501) 324-9761

WillLm (Fq) P. Fowkr

USPS Soutbem Fore# Bxp. Sta.

P.O. Box 1270

Hot Splingr, AR 71902

(501) 623-9825

DwapbFra&ill

USDA Forerc Service

HCR 69, Box 16

Oden, AR 71691

(501) 326-4322

Jennk L. Freidhof

&a&&a National Forut

HC 69, Box 16

Oden, AR 71%1

(501) 326-4322

Gary Frost

U.S. Forest Service

Rt. 1, Box36

Hector, AR 72842

(501) 284-3150

Hiitd L. Gibbr

USDA Forest Service

Devau Drive

Auburn University, AL 36849

(205) 826-8700

Jatnea (Jii) H. Gramann

Texar A&M Univemity

Fmncir Hall, Sciencea Dept.

College Station, TX 77843-226 1

(409) 845-4920

David (Dave) L. Granny

U.S. Forest Service

726 west Maple street

Fryetteville, AR 72701

(501) 521-5695

Harold K. Grimm&t

Ark. Natural Heritage Corn.

1500 Tower Bldg., 323 Center St.

Little Rock, AR 72201

(501) x4-9619

John Grinstead

Mark Twain National Forest

P.O. Box FF

Rolk, MS 65401

(3 14) 3648567

James (Jii) M. Guldm

USPS Southern Foreiu Exp. Sta.

P.O. Box 1270

Hot Springs, AR 71902

(501) 623-1174

John Gunter

univ. of Ark. at Montkeuo

School of Forest Resourccr

Monticello, AR 71656

(501) 460-1052

Imy D. Haikey

U.S. Forelt Service

P.O. Box 577

Taliii, OK 74571

(918) 567-2326

David (Dave) A. Hammond

U.S. Fonst Service

P.O. Box 1270

Hot Springs, AR 71902

(501) 3215274

Margaret warge) Harney

U.S. Fish & WIldlife Service

900 Cky street

Vi&burg, MS 39180

(601) 638-1891

Finis L. Harris

U.S. Forest Service

2114 Shreveport Hwy.

Pineville, LA 71360

(318) 442-5124

Rod Hanir

N.P.S.

P.O. Box 1860

Hot Springs, AR 71902

(501) 6243 124

Tom Hamir

Boise Cascade Corp.

P.O. Box 1060

DeRidder, LA 70634

(318) 462-4056

Rooald (Ron) 0. Haugcn

National Forests in Texas

108 April Dr.

Lufkin, TX 75904

(409) 639-8547

John W. Hazel

Nat. Gypsy Moth J3nv. Jmpact Statement

P.O. Box 6775

Radnor, PA 19087

(215) 975-4183

Gemld R. Heath

U.S. Forest Service

P.O. Box 459

Danville, AR 72833

(501) 495-2844

L. D. (Larry) Hcdrick

Ouachita National Fomst

P.O. Box 1270

Hot Springs, AR 71902

(501) 3215270

Car& e Henry

Sen. David Pryor’s Staff

3030 Fed. Bldg.

Little Rock, AR 72201

(501) 324-6336

Therer Herrick

Arkanaar Tech. Univ.

101 wtiimoon

Ruucllvilk, AR 72801

(501) %8Xl386

Nolan Hem

USDA Foment Service, FPM

2500 Shrevepott Hwy.

pincville, LA 71360

(318) 473-7287

Martin High

Tenncasee Valley Authority

P.O. Box 606

Athens, TN 37303

(615) 744-5313

Lisa J. Hlam

OSU Graduate Student

1115 s. Stanley

Stillwatcr, OK 74074

(405) 3776616

Walter (Walt) A. Hough

USDA Forert Service

701 Loyok Ave.

New Orleans, LA 70113

(504) 589-3003

Don D. Hoyle

U.S. Fore& Service

P.O. Box 369

Glenwood, AR 71943

(501) 356-4186

Bill Hubbard

Cooperative Extension Service

Forest Resources Building

Athens, GA 30602

(706) 742-2478

Douglas (Doug) James

University of Arkanna

Dept. of Biological Sciences

Fayetteville, AR 72701

(501) 575-6364

256
N ON Jones

The Nature Consenmncy

320 S. Boston, Suite 1700

Tulsa, OK 74135

(91%) 5851717

Robert (Robby) N. Kitchens

USFS - Region 8

1720 Peachtree Rd.

Atlanta, GA 30367

(404) 3474039

Richard (Dick) A. Kluender

U of A @ Monticello

School of Forest Resources

Monticello, AR 71656

(501) -1949

Jooeph Q=) Kr)r*=

univ. of Ark. at Momkcllo

School of Forest Resources

Monticello, AR 71656

(501) 460-1249

Edwin (Ed) R. Lwson

U of A @ Monticello

School of Forest Resources

Monticello, AR 71656

(501) -1452

Bobby Leonard

Arkanaar Game & Fiab Comm.

2 Natural Resources Drive

Little Rock, AR 72205

(501) 2236300

Franklin (Prank) A. Lewis

USDA Forest Service

Rt. 1, Box36

Hector, AR 72843

(501) 2843150

Marian Lichtler

U.S. Forest Service

HC 64, Box 3467

Heavener, OK 74937

(918) 653-2991

Brian Lockhart

U of A @ Monticello

School of Forest Resources

Monticello, AR 71656

(501) 460-1052

John J_ogan

AR National Heritage Comm.

1500 Tower Bldg.

Little Rock, AR 72201

(501) 3249763

Peter (Pete) L. Lorio

USDA Forest Service

2500 Shreveport Hwy.

Pinevilk, LA 71361-5500

(318) 473-7231

Devid Lortz

U of A @ Monticello

School of Forest Resources

Monticello, AR 71656

(501) 460-1792

Gary S. L&as

USDA Forest Service

P.O. Box 1105

Taliiina, OK 74571

(918) 5673418

Alex Mangini

USDA Forest Service

2500 Shreveport Hwy.

Pineville, LA 71360

(318) 473-7296

Gregg Matbis

Arkansas Game & Fish Comm.

2 Natural Resources Drive

Little Rock, AR 72205

(501) 223-6300

Bob McAnally

Arkansas Game & Fish Comm.

2 Natural Resources Drive

Little Rock, AR 72205

(501) 2236300

Roderick (Rod) McCullough

U.S. Forest Service

P.O. Box 577

Taliiina, OK 74571

(918) 567-2326

John A. McLemore

Ouachita National Forest

P.O. Box 1270

Hot Springs, AR 71913

(501) 321-5223

Tony Melchiors

Weyerhaeuser Company

P.O. Box 1060

Hot Springs, AR 71902

(501) 624-8502

Ralph Meldahl

School of Fotestry

108 M.W. Smith

Auburn University, AL 36849

(205) 844-1060

Ross Melick

Mark Twain National Forest

401 Fairgrounds Rd.

Rolla, MO 65401

(314) 3644621

Tim Mersmann

USDA Forest Service

P.O. Box 1270

Hot Springs, AR 71901

(501) 623-1538

Jerry L. Michael

USDA Forest Service

Devall Dtive

Auburn University, AL 36849

@OS) 826-8700

Ralph F. MuUSDA Forest Service, R-8

1720 Peachtree Rd., NW

Atlanta, GA 30244

(404) 347-7396

Paul A. Murphy

U.S. Forest Service

P.O. Box 3516

Monticello, AR 71655

(501) 367-3464

Joe F. Nix

Ouachita Baptist University

Box 3780

Arkadelphia, AR 71998-0001

(501) 245-5226

Daniel (Dan) L. Nolan

Ouachita National Forest

Box 1270

Hot Springs, AR 71902

(501) 321-5281

Tommy Notton

USDA Forest Service

P.O. Box 1270

Hot Springs, AR 71901

(501) 623-1538

Steve Osborne

Oxark National Forest

Rt. 1, Box36

Hector, AR 72843

(501) 2843150

Christine Overdevest

USDA Forest Setvice

For. Sci. Lab 320, Green St. UGA

Athens, GA 30602

(706) 546-245 1

Bill Paxton

U.S. Forest Service

1039 Hwy. 10N

Perryville, AR 72126

(501) 889-5176

William (Bill) F. Pell

Ouachita National Forest

P.O. Box 1270

Hot Springs, AR 71902

(501) 321-5320

Denise Per&a

Okla. State Univ.

004 Ag Hall

Stillwater, OK 74078

(405) 744-9467

257
Roger W. Perry

USDA Poreat Service

P.O. Box 1270

Hot springs, AR 71902

(501) 623-1538

Deniel (Den) R. Petit

Smithsoman Environ. Rea. Center

P.O. Box 28

Edgewater, MD 21037

(410) 798-4424

Rmeao Reya

USDA Fbrelt Service

1039 Hwy. 1,O N

Perryville, AR 72126

(501) 8895176

Robert (Bob) M. Rhodey

USDA Fomst Sewice

P.O. Box 1279

Mt. View, AR 72560

(501) 269-3228

Lynda L. Richards

Mark Tbain National Forest

401 FairgmundsRd.

Rolh, MO 65401

(314) 341-7433

Rex Roberp

Ark. Game a Fish comm.

2 Netuml Resources Drive

Little Rock, AR 72205

(501) 2234300

Karen Rollet

University of Arkansas

Memonal Hall, Landscape Arch.

Fayetteville, AR 72701

(501) 575-5679

Denny Rowlend

Arkenses Gem & Al Comm.

2 Netuml Resourcer Drive

Little Rock, AR 72205

(501) 2236300

Victor A. Rudis

USDA Foreet Service

P.O. Box 906

Starkville, MS 39759

(601) 324-1611

Gary Senchu

USDA Forest Service

P.O. Box 1270

Hot springs, AR 71901

(501) 623-1538

ley (Scott) Seunden

U.S. Forest Service

P.O. Box 459

Denville, AR 72833

(501) 495-2844

Patricia (Pat) Seay

USPS Kiemichi Rd.

P.O. Box 577

Teliiioe, OK 74571

(918) 567-2326

Saul seme

USDA Forest Service

P.O. Box 1270

Hot springs, AR 71901

(501) 623-1538

Micheel (Mike) 0. Shelton

U.S. Forest Serivce

Box 3516

Monticello, AR 71656

(501) 367-3464

Williim (Bill) M. Shepherd

AR Netual Heritage Comm.

1500 Tower Bldg., 323 Center St.

Little Rock, AR 72201

(501) 324-9613

Allen smith

USDA Fomet Service

1039 Hwy. 10 North

Perryvilie,AR 72126

(501) 889-5176

Kimberly (Kim) Smith

Univenity of Arkansas

Dept. of Biological Sciences

Fayetteville, AR 72701

(501) 575-3251

LindasmiIh

USDA Forest Setvice

P.O. Box 1270

Hot Springa, AR 71901

(501) 623-1538

0. D. Smith

@ark-St. Francis Nat. Forest

10 Stream Rd.

Russellville, AR 72801

(501) 968-3287

Hunter Speed

Guachita National Forest

103 Southern Hills Dr.

Hot Springs, AR 71913

(501) 321-5220

Robert W. Squyrer

U.S. Foreat Service

Rt. 1, Box34

Hector, AR 72843

(501) 284-3150

Richard W. Standage

Guachita National Forest

P.O. Box 1270

Hot Springs, AR 71902

(501) 321-5202

Dale A. Starkey

USDA Forest Service

P.O. Box 5500

Pineville, LA 71361

(3 18) 473-7293

William (Bill) Steenaon

Guachita National Foreat

1039 Hwy. 10 N

Per&Be, AR 72126

(501) 889-5 176

Fred Stephen

univ. of Arkansas

Dept. of Entomnlogy, A-321

FayetteviBe, AR 72701

(501) 575-245 1

Bryce J. Stok es

U.S. Forest Service

Devall Drive

Auburn, AL 36849

(205) 826-8700

Paul V. Tankereley

USDA Forest Service

HCR 69, Box 16

Gden, AR 71961

(501) 326-4322

Philip (Phil) A. Teppe

U of A @ Monticello

School of Forest Resources

Monticello, AR 71656

(501) 460-1352

James (Jim) F. Taulman

Univ. of Ark. at Fayetteville

601 Science/Engineering Bldg.

Fayetteville, AR 72701

(501) 575-3251

Ronald (Ron) E. Thill

Southern Foreat Exp . Stn.

Box 7600 SFA Stn.

Nacogdoches, TX 75962

(409) 569-7981

Patti Turpin

U.S. Forest Service

HCR 69, Box 16

Cklen, AR 71961

(501) 326-4322

Dave Urbston

Arkansas Game & Fish Comm.

2 Natural Resources Drive

Little Rock, AR 72205

(501) 2236300

Craig Uyeda

Arkansas Game & Fisk Comm.

#2 Natural Reeources Dr.

Little Rock, AR 72205

(501) 2236312

258
Brian Wagner

Mr. Game & Pish

P.O. Box 178

Lonoke, AR 72086

(501) 2236385

Willurn (Bill) D. Walker

U.S. Forest Service

105 Chad Drive

Hot Springr, AR 71901

(501) 321-5250

Jan Wallace

City of Hot Springs

236 Davidson Dr.

Hot springs, AR 71901

(501) 262-1519

fir Washington

USDA Forcet Service

P.O. Box 1270

Hot springs, AR 71901

(501) 623-1538

Mikl Widner

Arka- Game & RI Comm.

2 Natural Reeoumer Drive

Little Rock, AR 72205

(501) 223-6300

T. Bently Wigley

NCASI

Dept. of AFW, Clemson Univ.

Clemson, SC 29634-0362

(803) 656-0840

R. Lny Willett

U of A Coop. Extn. Service

P.O. Box 3468

Monticello, AR 71656-3468

(501) 460-1052

Rick Williams

U of A @ Monticello

School of Foreat Reaaurcea

Monticello, AR 71656

(501) 460-1748

Karen W ithemw

Ark. League of Women Votera

2020 W. Third, Suite 501

Little Rock, AR 72205

(501) 376-7760

Ray Yelverton

U.S. Forest Service

P.O. Box 369

Glenwood, AR 71943

(501) 356-4186

Douglas (Doug) Zollner

The Nature Conservancy

300 Spring Bldg. 1717

Little Rock, AR 72201

(501) 372-2750

Frank M. Ye&y

U.S. Foreat Service

P.O. Box 577

Talihina, OK 74571

(9 18) 567-2326

259
Baker, James. camp. 1994. Proceedings of the Symposium on Ecosystem

Management Research in the Ouachita Mountains: Pretreatment Conditions and

Preliminary Findings; 1993 October 26-27; Hot Springs, AR. Gen. Tech. Rep.

SO-112. New Orleans, LA: U.S. Department of Agriculture, Forest Service,

Southern Forest Experiment Station. 259 p.

Introductory and background material and pretreatment conditions and

preliminary findings associated with ecosystem management research in the

Ouachita Mountains is presented in 26 papers. Plant, wildlife, arthropod and

microbial communities, soil, water, scenic, and cultural resources, and

management economics are covered.

Keywords: Diversity, ecosystem components, forest plan, harvesting treatments,

multiresource management, natural regeneration, partial cutting, shortleaf pinehardwood ecosystems, stand-level study.
The use of trade or company names or products or services in this proceedings is for the benefit of the reader.

Such use does not constitute an endorsement or approval of any service or product by the symposium sponsors to

the exclusion of others that may be suitable.

Remarks about pesticides appear in some technical papers contained in this proceedings. Publication of these

statements does not constitute endorsement or recommendation of the mentioned pesticides by the symposium

sponsors, nor does it imply that uses discussed have been registered. Use of most pesticides is regulated by State

and Federal law. Applicable regulations must be obtained from appropriate regulatory agencies.

CAUTION: Pesticides can be injurious to humans, domestic animals, desirable plants, and fish or other wildlife if

they are not handled or applied properly. Use all pesticides selectively and carefully. Follow recommended

practices given on the label for use and disposal of pesticides and pesticide containers.

The United StatesDepartment ofAgriculture (USDA) prohibitsdiscrimination

in its programs on the basis of race, color, national origin, sex, religion, age,

disability, political beliefs, and marital or familial status. (Not all prohibited bases

apply to all programs.) Persons with disabilities who require alternative means for

communication of program information (braille, large print, audiotape, etc.)

should contact the USDA Office of Communications at (202) 720-5881 (voice) or

(202) 720-7808 (TDD).

To file a complaint, write the Secretary of Agriculture, U.S. Department of

Agriculture, Washington, DC 20250, or call (202) 720-7327 (voice) or (202) 720-

1127 (TDD). USDA is an equal employment opportunity employer.

*U.S.GPO:1994-565-016/00013


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Experiment Statlon

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