United States

Department of

Agriculture

Forest Service

Southern

Research Station

General Technical

Report SRS–70

Comprehensive Regional Resource

Assessments and Multipurpose Uses of

Forest Inventory and Analysis Data,

1976 to 2001: A Review

Victor A. Rudis
The Author

October 2003

Southern Research Station

P.O. Box 2680

Asheville, NC 28802

Victor A. Rudis, Research Forester, U.S. Department of Agriculture,

Forest Service, Southern Research Station, 201 Lincoln Green,

Starkville, MS 39759.

For more information regarding the FIA Program, contact the following:

National

FIA National Program Leader

USDA Forest Service, 1NW

201 14th St., SW

Washington, DC 20090-6090

Northeast

Program Manager, FIA

USDA Forest Service

Northeastern Research Station

11 Campus Blvd., Suite 200

Newtown Square, PA 19073

North Central

Program Manager, FIA

USDA Forest Service

North Central Research Station

1992 Folwell Ave.

St. Paul, MN 55108

South (includes Puerto Rico and

 Atlantic territories)

Project Leader, FIA

USDA Forest Service

Southern Research Station

4700 Old Kingston Pike

Knoxville, TN 37919

Rocky Mountain

Program Manager, FIA

USDA Forest Service

Rocky Mountain Research Station

507 25th St.

Ogden, UT 84401

Pacific Northwest (includes Alaska, Hawaii,

 and Pacific territories)

Program Manager, FIA

USDA Forest Service

Pacific Northwest Research Station

620 SW Main, Suite 400

Portland, OR 98205

Statistical Techniques

Project Leader, FIA

USDA Forest Service

Rocky Mountain Research Station

2150 Centre Ave., Bldg. A

Fort Collins, CO 80526-1891

Or visit the FIA Web site at:

http://www.fia.fs.fed.us

Cover:

Depending upon one’s disciplinary perspective, the image on the cover may depict forest products, services, or

intangible values. Inventoried elements in the scene could include information about air quality, human uses, tree

volume, the owner’s intentions, the forest’s proximity to water, and temporal trends, with some data having

multipurpose uses in a comprehensive forest resource assessment.
i

Table of Contents

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Problem and Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Results and Synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

A Growing and Diversifying User Audience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Early Progress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Approaches to Comprehensive Assessments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Progress Toward Multipurpose Utility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

References by Selected Subjects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Air pollution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Biomass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

Dead wood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

Esthetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Geographic context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Nearby nonforest influences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

Owner attitudes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

Range . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

Recreation opportunity and remote and roadless areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

Tropical inventories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

Water quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

Vegetative habitat typing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

Wildlife . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90

Other FIA-Associated Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98

Web Sites with FIA-Associated Data Uses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128

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1

Comprehensive Regional Resource

Assessments and Multipurpose Uses of

Forest Inventory and Analysis Data, 1976

to 2001: A Review

Victor A. Rudis

Abstract

Reported is a compilation of over 1,400 literature citations and a review of

selected subjects that constitute an integrated knowledge base for

comprehensive forest resource assessments with regional, field samplebased forest inventory data. The focus of the report is on nontraditional

and novel technical uses tied to the U.S. Department of Agriculture, Forest

Service, Forest Inventory and Analysis (FIA) field surveys published or in

press between 1976 and July 2001. Briefly noted are pioneering studies

that link FIA data with air pollution, biomass, dead wood, esthetics,

geographic context (geographic information systems and satellite remote

sensing), nearby nonforest influences (operability, roads), owner attitudes,

range (agroforestry and livestock use), recreation, tropical inventories,

water quality (soils and hydrology), vegetative habitat typing, and

wildlife. All known M.S. theses and Ph.D. dissertations associated with

FIA data since 1976 are included, regardless of subject matter. Also

incorporated are citations of collected works concerning integrated

assessments and multidisciplinary surveys and representative citations

associated with economics, global climate change, remote sensing,

sampling designs, tropical forest resources, and traditional timber resource

assessments. The literature review suggests assessments are

“comprehensive” for issues in selected regions and chosen resources.

Multidiscipline involvement, multipurpose uses of nontraditional data,

and analysis of resources other than timber are variable. Nontraditional

measurements and models, with some exceptions, have been provincially,

rather than nationally, applicable and not well coordinated among regions.

Recommended are ways to accelerate progress toward comprehensive

assessments and cost-effective multipurpose uses.

Keywords: Bibliography, ecological inventories, forest inventory,

hydrology, interdisciplinary studies, integrated assessments, monitoring,

natural resource planning, range, recreation, timber, water, wildlife

habitat.

Introduction

The scope of land-management-planning issues has

widened and the process of measuring and assessing

forest resources has grown increasingly complex.

Traditional timber-oriented inventories no longer are

sufficient to assess timber supplies or monitor forest

resources (Wikstrom and Alston 1985). There is

widespread perception that current efforts and

capabilities for monitoring America’s forest resources are

failing to meet increasingly complex and large-scale

needs (Peterson and others 1999). The expanding role of

forests and public involvement in forestry today elicit

differing concerns, measurement priorities, and

sometimes opposing opinions about land use, forest

resources, and the attributes to be measured.

Inventories of standing timber are common benchmarks

by which many forest industries and natural resource

agencies determine forest-resource supplies, but an

underlying assumption is that timber inventory data

include all of the needed information. That this

assumption is wrong is illustrated by the lack of maturetree harvests near urban areas on nonindustrial private

land and court injunctions against timber sales on

National Forest System land.

Measurement of forest resources is not just an inventory

of a forest’s biological characteristics, but the evaluation

of their value relative to all of society’s needs. Scientific

measurement of timber and other forest products is more

precise than measurement of the less tangible values and

services that forests provide. Comprehensive, multidisciplinary assessments that address contemporary forest

resource issues require useful analyses of forest

inventory data.

To be comprehensive, regional forest-resource

inventories must not only account for forest land use and

timber production, but also for land and water (hereafter

earth) cover, other land uses, other resources, and their
2

interactions. Long-term and global planning must also

consider the effects of acid deposition, carbon

sequestration, and climate change; and must anticipate

changes in the role of forests as producers of products,

services, and intangible values. Such assessments would

seem to require the impossible—consideration of all

associated resources and the social, spatial, and temporal

dynamics taking place among them. Interdisciplinary

inventories are frontiers in which multidisciplinary

approaches advance towards comprehensive assessment.

However, an integrated inventory may not be possible for

all resources (Bastedo and Theberge 1983). Assessments

must at least incorporate scientific data and analyses

from other disciplinary perspectives—often assembled

with dissimilar research techniques or collected at very

different levels of precision.

A standard system for collecting, storing, and analyzing

such information commonly is required, but usually is

lacking (Jensen and others 1999). Many scientists and

assessment teams familiar with studies within their own

disciplines often ignore the work of other disciplines.

Interdisciplinary analysis is uncommon because the

interdisciplinary infrastructure—funding, information,

and social networks—may not always exist. Rarely are

there agencies, journals, or organized stakeholders, much

less scientific societies, devoted to the task.

Interdisciplinary assessments often are plagued by the

inordinate amount of time required to communicate

among authors with differing disciplinary perspectives

using analyses performed at inconsistent scales of data

resolution.

This report considers a corpus of material from a variety

of natural resource disciplines and perspectives in a

searchable database, assembled for studying the ways

that forest inventory data are used. Knowledge of the

corpus is crucial in optimally selecting measurement

standards, identification of knowledge gaps, and the

developing comprehensive assessments.

Federal, State, and local public agencies, large landholding commercial firms, and some nongovernmental

organizations (NGOs), conduct resource inventories to

obtain information and make decisions about forests. The

author used the systematic field, sample-based forest

survey conducted by the U.S. Department of Agriculture,

Forest Service (USDA FS), Forest Inventory and

Analysis (FIA) program as an example. This sciencebased, broad-region survey program, one of the oldest of

its kind still used, began in the 1930s in response to

concerns about dwindling timber supplies on private land

in the United States. Responsibility for assessing current

conditions and trends in both public and private forests

rests with the USDA FS; and the FIA program is its

research-based tool. Scientific, sample-based inventories

began with the passage of the McSweeney-McNary

Forest Research Act of 1928. Later, passage of the Forest

and Rangeland Renewable Resources Planning Act of

1974 (P.L. 93-378 [88 Stat. 476]) and associated laws in

1978 (P.L. 95-307 [92 Stat. 353]) shifted inventory and

monitoring efforts of the USDA FS from documenting

commodity outputs towards a more comprehensive

assessment of forest resources that also included water,

range, recreation, timber, and wildlife values. The Forest

Ecosystem and Atmospheric Pollution Research Act of

1988 added monitoring to account for ecological effects

associated with air pollution. Cooperative agreements

with eastern national forests and later legislation

(Agricultural Research, Extension, and Education

Reform Act of 1998) broadened the USDA FS FIA

program to include status-and-health surveys on all

public land, including western national forests and

designated wilderness areas.

Owing to differing resources and stakeholders, there is

some regional variation in the manuals of procedures for

field data collection assembled by FIA staffs (U.S.

Department of Agriculture, Forest Service 2001b, 2001c,

2001d). Nevertheless, a core set of attributes and

procedures always has conformed to one set of

measurement standards for national reporting. Between

the late 1970s and mid-1990s, some FIA staffs started

developing comprehensive assessments, often

independently, by supplementing traditional timber

measurements with procedures drawn from other natural

resource disciplines, measures relevant to other natural

resource assessments, and an inventory of attributes with

multipurpose interest; e.g., in Alaska,1

 Intermountain

1 U.S. Department of Agriculture, Forest Service. 1995. Field procedures

for the southeast Alaska inventory. [Various pages in separate sections].

On file with: USDA Forest Service, Pacific Northwest Research Station,

FIA Unit, 3301 C Street, Suite 200, Anchorage, AK 99503-3954.
3

West,2 North Central,3 Northeastern,4 Pacific Northwest,5

and Southern (Kentucky,6 Midsouth,7 and Southeast8)

United States, and Puerto Rico.9

 In some instances, FIA

staffs also assembled relational databases containing the

added attributes with traditional timber data to facilitate

extramural analyses and modeling with resource

objectives other than timber; e.g., in the north-central

region for total biomass appraisals (Hahn and Hansen

1985) and the southern (Midsouth10 and Southeast11)

region for a variety of range, recreation, water, and

wildlife habitat assessments.

Individuals from agencies, disciplines, and regions often

differ in their need for information from forest

inventories and assessments. In developing nationally

standardized inventories and comprehensive assessments,

decision makers seek consensus among stakeholders

from a variety of disciplinary interests and resource

regions, e.g., cooperators and partners from State

agencies, other Federal agencies, forest industry, and

universities, along with concerned individuals.

Stakeholders today also include groups like The Nature

Conservancy, The Wilderness Society, the U.S.

Environmental Protection Agency, the U.S. Department

of the Interior Fish and Wildlife Service, and USDA

Natural Resource Conservation Service (NRCS), as well

as those focused only on timber resources. Individuals in

such disparate disciplines need a common understanding

of past and present measurements and knowledge of

others’ concerns about associated resources. Integrated

knowledge is essential to optimize the selection of

common attributes and standardize procedures for costefficient data collection, storage, management, and

analysis.

Stakeholders often question the usefulness of

observations, measurements, and techniques not directly

tied to their interests. Field data collectors may ask:

“Why are we measuring this?”, “Who is going to use

it?”, and “How important is it?” For resource inventory

administrators, analysts, and data-acquisition specialists,

which additional measures will truly be useful once

collected, and which now recorded should be dropped

are routine concerns at State, regional, and national

meetings. Questions about forest resource issues posed

by local public-interest groups occupy center stage from

time to time, engendering a scramble for the appropriate

inventory or analysis technique. Published studies—

scattered among libraries of disparate disciplines,

agencies, and regions—already address many such

questions. A citation database is one means of informing

these and other groups, finding relevant reports for

particular issues, discovering already tried sampling and

assessment efforts, and promoting new ways to analyze,

describe, and integrate the data with other information.

2 U.S. Department of Agriculture, Forest Service. 1994. Utah forest survey

field procedures, 1994-1995. 232 p. On file with: USDA Forest Service,

Rocky Mountain Research Station, Interior West FIA Unit, 507 25th

Street, Ogden, UT 84401.

3 U.S. Department of Agriculture, Forest Service. 1996. North central

region inventory and analysis field instructions—Illinois and Indiana.

87 p. + appendix. On file with: USDA Forest Service, North Central

Research Station, FIA Unit, 1992 Folwell Avenue, St. Paul, MN 55108.

4

 U.S. Department of Agriculture, Forest Service. 1996. Field instructions

for the fifth inventories of New Hampshire and Vermont. 90 p. + appendix.

On file with: USDA Forest Service, Northeastern Research Station, FIA

Unit, 11 Campus Blvd, Suite 200, Newtown Square, PA 19073.

5

 U.S. Department of Agriculture, Forest Service. 1995. Field instructions

for the inventory of western Oregon 1995-1997. 224 p. On file with:

USDA Forest Service, Pacific Northwest Research Station, FIA Unit, 620

SW Main, Suite 400, Portland, OR 97205.

6

 U.S. Department of Agriculture, Forest Service. 1986. Field instructions

for the fourth inventory of Kentucky 1986–1987. 97 p. + appendix. On

file with: USDA Forest Service, Southern Research Station, FIA Unit,

4700 Old Kingston Pike, Knoxville, TN 37919.

7 U.S. Department of Agriculture, Forest Service. 1994. Forest survey

inventory work plan: Arkansas 1994–1995. 61 p. + appendices. [Appendix

B: Other forest resources work plan, 1994-1995. 19 p. http://

www.srs.fs.usda.gov/pubs/viewpub.jsp?index=502 (Date accessed: June

2003)]. On file with: USDA Forest Service, Southern Research Station,

FIA Unit, 4700 Old Kingston Pike, Knoxville, TN 37919.

8 U.S. Department of Agriculture, Forest Service. 1991. Field instructions

for the Southeast. [Various pages]. On file with: USDA Forest Service,

Southern Research Station, FIA Unit, 4700 Old Kingston Pike, Knoxville,

TN 37919.

9 U.S. Department of Agriculture, Forest Service. 1991. Forest survey

inventory work plan: Puerto Rico 1990. 38 p. + appendix. On file with:

USDA Forest Service, Southern Research Station, FIA Unit, 4700 Old

Kingston Pike, Knoxville, TN 37919.

10 U.S. Department of Agriculture, Forest Service. 1996. Interactive data

access user manual: forest inventory and analysis: forest resource data for

Midsouth States. Version 6.1. [Various pages]. On file with: USDA Forest

Service, Southern Research Station, FIA Unit, 4700 Old Kingston Pike,

Knoxville, TN 37919.

11 U.S. Department of Agriculture, Forest Service. 1984. A user’s guide to

forest information retrieval (FIR): forest inventory and analysis. 93 p. On

file with: USDA Forest Service, Southern Research Station, FIA Unit,

4700 Old Kingston Pike, Knoxville, TN 37919.
4

Background

Monitoring of earth cover for forest resources with

sample observations began in the 1930s (Frayer and

Furnival 2000). The USDA FS established the Forest

Survey program to conduct such surveys on all private

land and most non-Federal public land. From the

beginning, the audience for these data included natural

resource planning agencies of the Federal Government,

State forestry agencies, and their supporters. Authors of

the first nationwide inventory titled their document

“Timber Resources for America’s Future” (U.S.

Department of Agriculture, Forest Service 1958).

Satisfying the need for standardized timber statistics

remained a primary driver of the inventory program in

both the early 1970s (U.S. Department of Agriculture,

Forest Service 1973), and the late 1970s (U.S.

Department of Agriculture, Forest Service 1977).

Even as they were begun, however, these timber-oriented

inventories addressed other interests. Integration of data

about forest types with earth-cover information occurred

in map form—an effort that necessitated incorporation of

nonforest landmarks. Ownership, volume, and other

attributes of forest land later appeared in map form,

along with tabular statistics, e.g., for Mississippi

(Sternitzke 1962). Descriptive distribution maps of tree

species on forest land have appeared for economically

important species, e.g., hickory (Cruikshank and

McCormack 1956). An early research use included

comparisons of surveyed tree-species distributions with

tree pollen from pond sediments, which were useful in

gauging long-term species shifts and the ecological

processes that gave rise to them (Webb 1974).

In the late 1950s and early 1960s, the American Forestry

Association (AFA) sponsored three efforts to assemble

examples of what today might be termed a

comprehensive assessment. Analysts combined into

book-length volumes, FIA data on forest-land area, land

cover, forest ownership, available literature, and other

economic and demographic information. Included were

forest-type maps, tabular summary statistics of forest

area, an analysis of issues, and a discussion of other

resources. Using data for California (Dana and Krueger

1958), one set of topics focused on private land

intermingled with public land. Using data for Minnesota

(Dana and others 1960), another focused on formerly

tax-delinquent local public land. Using data for North

Carolina (Pomeroy and Yoho 1964), the third effort

focused on small, nonindustrial private holdings. A

central concern that emerged from the three reports—and

other owner studies of the period (Moyer and Daugherty

1976)—was that the intentions of private nonindustrial

owners regarding forest-land use were critical to

adequately assessing timber supplies.

Early documents that linked forest inventories to other

resource evaluations concerned deer browse (Moore and

others 1960, Ripley and McClure 1963). By the mid1970s, many felt that combining the effort to directly

inventory timber attributes with information about other

resource attributes made sense—even among those

concerned only with timber resource supplies (Southern

Research Planning Committee 1974). Scientists from the

USDA FS with cooperators at research institutions,

modified inventory procedures for FIA data collection

and analysis to better address associated issues

surrounding timber supplies, such as ownership studies

(Kingsley 1975), field estimates of potential productivity

from noncommercial species (MacLean and Bolsinger

1973), and potential range on forest land (Pearson and

Sternitzke 1974). In a 1975 meeting scheduled to discuss

the 1976 survey of South Carolina, organizers from the

State and the USDA FS expanded “the ongoing timberoriented forest survey into a more complete . . .

inventory” (McClure 1979). Initial findings appeared in

“Multiresource Inventories—A New Concept for Forest

Survey” (McClure and others 1979).

Reflecting shifting interests, the program changed names

a few times—the Renewable Resources Evaluation

(RRE) program in the late 1970s, and since the mid1980s—the FIA program. In the past, FIA units

coordinated with the National Forest System, the Bureau

of Land Management, and other landholding Federal

agencies, as well as States, to compile inventory

information for all domestic forest land. Today FIA is

responsible for surveys on all land. Through cooperative

arrangements, many of the smaller Federal land parcels,

Federal land in Alaska, and all National Forest System

land are surveyed using the same FIA sampling scheme.

In the 1990s, concerns about air pollution effects on

forest ecosystems fostered the development of an FIAaffiliated program known as “Forest Health Monitoring”

or FHM (Bones 1993). The program began in the Eastern

United States (Bechtold and others 1992, Bones 1993,
5

Brooks and others 1991) and spread to the West

(O’Laughlin 1994). The program includes growingseason measurements; pilot testing of a variety of

indicators, e.g., understory vegetation structure; and

collection of a wider array of information, e.g., tree

crown condition and soils. Recent FHM reports use FIA

data to establish the context for findings rather than

making resource assessments, but commonly focus on

damage and mortality to trees from pests and air

pollution. FHM used a sampling scheme, and for some

regions used locations that differed from the FIA

program until about 1996. FIA and FHM programs now

are merged. FHM conducts more detailed measurements

than FIA and does most sampling during the growing

season on a subset of FIA plots. FHM publishes State,

regional, and national reports, with the most recent

regional reports available for the Northeast (McWilliams

and others 1997), South (Burkman and others 1998), and

West (Rogers and others 2001).

Forest inventory priorities and the issues addressed in

assessments have shifted over the years. In the past

decade, increasing awareness of global forestry issues

has broadened the scope of data needed to include

criteria and indicators for the conservation and

sustainable management of forests (Smith 1999). Nations

made commitments to provide such information that

meets agreed-upon global reporting protocols (Smith

1999). These indicators will shape both the selection and

standardization of future attributes for the FIA program,

as well as the analysis of existing forest resource data.

Despite many changes, FIA data and inventories

generally are not widely perceived to address issues other

than those that relate strictly to timberland and timber

resources. A common assumption is that the U.S. Census

of Agriculture provides a definitive estimate for area of

cropland and pastureland, and that NRCS surveys

provide definitive nonforest resource estimates.

Acceptance of this belief is reflected in the presentation

of land-use area estimates. In the first table of many

USDA FS FIA resource bulletins (e.g., Alerich 1990),

FIA inserts U.S. Census of Agriculture area estimates of

cropland and pastureland for nonforest land.

Monitoring the associated attributes of forest ecosystems

remains a critical component of the FIA survey effort.

Most FIA resource status reports include species,

damage, stand structure, and human influence

measurements as important indicators; estimates of

disturbance, growth, removals, mortality, succession, and

erosion as important processes; and amenities, range,

recreation, timber, water quality and wildlife habitat as

important resources. Due to differing measures and

regional interests, the reports vary in their coverage.

Beginning in 1999, a committee composed largely of

Forest Service FIA staff agreed to a core set of these

attributes to serve as the standard set of nontraditional

measures nationwide. To what extent the analysis of

these indicators, processes, and resources will be

featured in future resource status reports has not yet been

determined.

Problem and Objectives

Cross-disciplinary surveys often share some data,

informal infrastructure, development concepts, and

stakeholders. However, such surveys often have

restricted administrative support among natural resource

agencies and professional research societies. Akin to

trans-boundary efforts among sovereign nations, crossdisciplinary surveys have no common sources of

financial support, and few communication vehicles, such

as journals and terminology, that mean the same to all

involved. The lack of a formal administrative

infrastructure extends to information management, which

includes cataloging, storage, and delivery of data and

associated documents.

Before the widespread use of Internet technologies,

display and storage of paper copies on central library

shelves increased the likelihood that a report would

receive attention by a diverse audience. For years, USDA

FS Research Stations have published paper copies of

FIA-associated documents. They commonly are

delivered free of charge to interested individuals and

libraries,12 some of which are forestry department

libraries. Central libraries that were part of the Federal

12 Each USDA FS Research Station publishes and distributes a list of

recent Station publications and reprints of selected articles published

elsewhere by Forest Service scientists. Some Stations also send all of their

publications to those libraries that request them. Periodically, the Stations

also ask recipients to formally resubscribe or renew their stated interest in

receiving the list or paper copies of documents.
6

Depository Library (FDL) program13 relied, in part, on

the FDL for collection, cataloging, and delivery of all

USDA documents. With few exceptions, however, FDL

policy since 1981 has been to distribute documents only

on microfiche.

Cataloging by subject, as well as discipline, and

inclusion of abstracts or other extensive indexing also

increases the likelihood of a readership broader than the

traditional forestry discipline. In practice, indexing varies

widely among forestry schools. While many university

libraries index Research Station serial publications as

individual books, others catalog them by series number

only, rather than by author, keyword, title, or subject.

Still other libraries and their patrons rely on

bibliographic services attuned to government documents,

such as AGRICOLA. By contrast, a nongovernment

journal’s publisher or professional society often

extensively indexes articles and books of serial

publications every few years.

Today, online catalogs and searches of most university

libraries as well as specialized for-profit bibliography

services and several nonprofit collections, are available

to anyone with a modem and a personal computer. Many

newer publications are now available on the Web.

Indexing also has improved, and electronic searches of

an entire document may be conducted online.

Given all of the above, there is an obvious gap in

cataloging, indexing, and distributing information to

diverse audiences. This is especially true of older

documents. My objective is to assemble and index the

literature associated with FIA data from an array of

natural resource disciplines, technical user groups,

scholarly peer-reviewed journals, and online electronic

sources. The citation database indexes reports from

individual disciplines, forms a knowledge base for

referencing associated efforts, and provides a tracking

process to monitor technical advances. As a reference

repository, the citation database fosters integration of an

evolving knowledge system for data collection,

modeling, monitoring, and analysis, as well as the crossdisciplinary dissemination of findings.

This report focuses on nontraditional and novel technical

uses tied to the USDA FS FIA field surveys that were

published between 1976 and July 2001. Studies that

reported using FIA data were included if associated with

hydrology, ownership, range, recreation, or wildlife

habitat. Also included are citations of collected works

concerning integrated assessments and multi-disciplinary

surveys; representative citations associated with air

pollution, economics, global climate change, remote

sensing, sampling designs, tropical forest resources, and

traditional timber resource assessments; and all known

M.S. theses and Ph.D. dissertations since 1976. Briefly

noted are pioneering studies to analyze data from

inventories of air pollution, biomass, dead wood,

esthetics, geographic information science, operability,

ownership, range and livestock use, recreation, satellite

remote sensing, water, tropical forest resources,

vegetative habitat, and wildlife habitat.

Methods

The first citation database was Rudis’ (1991) “Wildlife

Habitat, Range, Recreation, Hydrology, and Related

Research Using Forest Inventory and Analysis Surveys:

A 12-Year Compendium,” which covered the period

1979 to 1990 for the coterminous United States. I revised

the database and expanded the years of the compendium

to include the period 1976 through July 2001. Revisions

included citations of all known M.S. theses and Ph.D.

dissertations associated with FIA data since 1976,

regardless of topic, citations of collected works and

selected documents concerning integrated assessments

and multi-disciplinary FIA surveys prior to 1976, FIA

surveys in the tropical United States, and representative

citations associated with timber resource assessments. I

assembled all citations in Endnote 4.0 software (ISI

Research Soft 2000) to form a fully searchable citation

database.

13 The Federal Depository Library (FDL) program is a centralized library

service that makes available publications produced by Federal agencies.

Unlike the Research Stations, the FDL program serves both libraries and

Federal agencies by not requiring periodic resubscription, production,

delivery, and selection of specific documents. Instead, the FDL program

provides all Research Station publications. Beginning in 1977, however,

the FDL started using microfiche as an alternative to paper distribution.

Inch-thick technical documents, for example, were reduced to a millimeter

in size, which saved considerable delivery and storage costs. Since 1981,

FDL has stopped sending paper copies of selected documents and

replaced them almost exclusively with microfiche, except for color-based

publications. Today, Web-accessible documentation has increased, but the

policy for tangible documentation remains in microfiche.
7

Queries of other electronic databases for 1976 through

July 2001 used the following keywords: forest inventory,

multipurpose, and surveys; multiresource and surveys;

regional and forest and surveys, forest and service and

surveys; land and resource and survey; land use; FIA and

forest; forest and inventory. Chief search engines used

were AGRICOLA, dissertation abstracts, USDA FS

Research Station publication databases, and recent issues

of journals with online search capabilities. Other

electronic searches used keywords: land use; FIA and

forest; forest and inventory. The other electronic searches

included Scirus “http://www.scirus.com” an Internet

search engine focused on scientific information, and a

variety of Web search engines (primarily AltaVista,

Google, and Netscape).

As in Rudis (1991), other professionals (scientists within

the USDA FS FIA program, NGOs, and professors at

universities) known to use FIA data for nontraditional

purposes provided their lists of publications. Sources

included conference proceedings associated with

contributions already known to contain presentations by

these professionals. I also included Web-based technical

publications but not newspapers and nontechnical articles

in popular news magazines.

The citation database includes abstracts where available,

and annotations of selected recent publications

(particularly those concerned with timber resources) to

reference information reflecting their multidisciplinary,

multipurpose, nontraditional, and novel analyses or data

uses. Citations concerned with traditional timber

resource statistics and analysis are included but are not

inclusive of all such reports. Within-State USDA FS

Resource Bulletins that consist chiefly of traditional

tabular statistics are excluded.

For several reasons, key references between 1976 and

1978 are listed primarily as collected works, e.g.,

conference proceedings and bibliographies, rather than as

citations from individual authors. A bibliography of

multiresource and integrated inventory studies already is

available for the period 1978 and earlier (Lund and

McNutt 1979). The Lund and McNutt (1979)

bibliography also contains many citations for inventories

conducted by other U.S. agencies and foreign countries,

as well as a wider diversity of inventory citations—with

annotations. In addition, online search capabilities and

access to hardbound materials were more limited before

the widespread use of computers.

Results and Synthesis

There were over 1,425 citations published or in press

between 1976 and July 2001. What follows is an

overview of studies for the period, early progress for

selected subjects, approaches to comprehensive

assessments, progress toward multipurpose utility, and a

synthesis. An appendix lists citations by selected

subjects.

The number of entries grew between 1979 and 2000,

with a slight decline in the early 1990s (fig. 1). Increases

in the past 5 years are likely due to sponsorship of

aggregate studies associated with a decennial assessment

required under the Resources Planning Act (RPA). Other

likely causes are wider dissemination and Internet

Figure 1—Average frequency of articles associated with forest inventory and analysis data uses, 1979 to 2000.

Annual — — —

3-year
8

documentation of the traditional forest inventory data in

the East (Hansen and others 1992) and West

(Woudenberg and Farrenkopf 1995), other advances in

Geographic Information System (GIS) software, and the

growing demand for more comprehensive regional

assessments. Since publication of the eastwide manual

(Hansen and others 1992), citations have more than

doubled.

A Growing and Diversifying User Audience

Strategically important components of a comprehensive

survey require information from and involvement by

other agencies and disciplines, a broad constituency, and

informed stakeholders. Because laws mandate

comprehensive assessments, there is a need for

information about timber, other resources, and other

forest attributes. The range of data and analyses and the

potential audience for these data—both inside and

outside the USDA FS—has greatly expanded. Data

dissemination and involvement across disciplines at the

technical level, and across agency jurisdictional

boundaries at the administrative level, are not yet well

coordinated.

At the national level, forest-land assessments continue a

long tradition of service to the timber resource

community (U.S. Department of Agriculture, Forest

Service 1981, 1982, 1989, 2001a). Analysts have

addressed information needed by increasingly wider

audiences, with larger sections devoted to other resources

and other associated issues. An array of natural resource

disciplines is involved in preparing reports to address

allied issues. FIA data are important in many such

studies (Flather and others 1999; Joyce and Birdsey

2000; Mitchell 2000; Smith and Sheffield 2001; U.S.

Department of Agriculture, Forest Service 2001a).

The primary users of data and analytical reports before

1979 were national, State, and county forestry agencies,

forest industry representatives, and forest industry

consultants. At the State level, many FIA forest inventory

resource bulletins focus on data standardized to address

timber resource interests, such as traditional statistics

(timberland area, growing-stock volume, sawtimber and

poletimber-sized stands, and trends in growth, removals,

and mortality). Few consultants, managers, planners, or

researchers are willing to sift through data and analyses

laden with resource assumptions other than their own.

Nor are they likely to spend much time expressing crossdisciplinary data needs relevant to other resources,

agencies, or issues.

Some resource user groups have documented inventory

data needs and the types of analysis desired with regard

to nontraditional attributes such as human influences,

range, recreation, wildlife habitat, and water quality. In

the 1980s, such reports appeared in selected proceedings

(Barnard and others 1985, Chalk and others 1984, Irland

Group 1989, Lewis 1988, Porter and others 1983, Shands

1985). Recent reports have documented additional needs

for timber (Irland Group 1989, Minnesota Department of

Administration Management Analysis Division 1997,

Tarbet and Cashwell 1990), wildlife habitat ( Brooks

1990; Brooks and Barnard 1984; Morrison and Marcot

1995; U.S. Department of Agriculture, Forest Service

1992), and ecological information in general (Rudis and

others 1995). Two national blue ribbon panels,

representing Federal and State agencies, forest industry,

universities, and NGOs—made specific

recommendations about the FIA program (American

Forest & Paper Association 1998, American Forest

Council 1992). Multidisciplinary regional assessments,

such as those for the Pacific Northwest (Haynes and

Perez 2000), also noted data gaps and listed

recommendations for regional surveys.

State and local users make their special data needs

known through individual FIA units, but public records

of informal inquiries are not maintained. Forest

industries use FIA data extensively to model current and

projected wood supplies, to support investment analysis

and to assess regulatory impacts on wood supplies, e.g.,

coastal zone, riparian, and endangered species habitat

restrictions (Lord 2000). These groups and individuals

often ask for general stand characteristics, including tree

species and ownership information that is already

available in standard format from the FIA Web site http://

fia.fs.fed.us. Occasionally articles are published that

detail recommendations on selected nontraditional

attributes, e.g., for input into the State of California’s

wildlife habitat modeling efforts (Noon 1984), but such

documentation is rare or incomplete. Timber resource

interests note the need for more, better, and faster

information. Better information includes geographic

context attributes to assess urban impacts and timber

availability, and vegetative habitat typing to model future

wood productivity (Lord 2000). Occasional users of FIA
9

Figure 2—Average frequency of articles in journals associated with forest inventory and analysis data uses, 1979 to 2000.

Figure 3—Annual frequency of unique journals with articles associated with forest inventory and analysis data uses, 1979 to 2000.

statistics include individuals in disciplines other than

timber management, such as forest hydrologists,

recreation specialists, and managers in State-level natural

heritage and wildlife agencies and conservation groups.

These and other occasional users have expressed interest

in these and other nontraditional data, as well as other

novel data uses (Blackmon 2001); although they may be

unaware of some elements, or have limited financial

opportunity to analyze fully the nonstandard information.

Other evidence for the wider array of scientific interests

comes from reports in nontraditional journals. Threefourths of the articles come from conference

proceedings, regional assessments, and individual USDA

FS Research Station reports. The number of journal

articles has been increasing since the mid-1980s (fig. 2),

as has the number of outlets. Articles have appeared in

no fewer than nine different journals every year since

1986 (fig. 3).

Common outlets for much traditional FIA-related

research are Canadian Journal of Forest Research, Forest

Products Journal, Forest Science, and Journal of Forestry.

There is a much more diverse audience today. In 2000,

subjects included a wide range of biology, ecology, and

economic issues, as represented by the articles’ journal

titles. Such titles are: American Journal of Agricultural

Economics (Prestemon and Holmes 2000), Forest

Annual — — —

3-year
10

Ecology and Management (Borges and Hoganson 2000,

Gill and others 2000a, Lund and Iremonger 2000), Forest

Policy and Economics (Raunikar and others 2000),

Global Ecology and Biogeography (Phillips and others

2000), Journal of Biogeography (Buergi and others

2000), Journal of Forest Economics (Scarpa and others

2000), Native Plants Journal (Outcalt 2000), Southern

Journal of Applied Forestry (Cubbage and others 2000,

Huebschmann and others 2000, Prestemon and Pye

2000), American Midland Naturalist (Zhang 2000),

Transactions of the North American Wildlife and Natural

Resources Conference (Schmidt 2000), Western Journal

of Applied Forestry (Chojnacky and Dick 2000), and

World Resources Review (McNulty and others 2000).

Others include Annals of Operations Research (King

2000a), Atmospheric Environment (Wiedinmyer and

others 2000), Climate Research (Easterling and others

2000), Computers and Electronics in Agriculture (King

and others 2000, MacLean and others 2000, Shifley and

others 2000), Environmental Modeling and Assessment

(Luxmoore and others 2000), Environmental Monitoring

and Assessment (Mercer and Aruna 2000, Stehman and

others 2000), Remote Sensing of Environment (Gill and

others 2000b), and The Compiler (King 2000b). For the

first half of 2001, other journals included Ecological

Modeling (Bragg 2001), Global Change Biology (Coops

and Waring 2001), Journal of Vegetation Science

(Frescino and others 2001), Land Use Policy (Buergi and

Russell 2001), Wildlife Society Bulletin (Trani and

others 2001), and Woodland Management (Leatherberry

2001b).

Early Progress

This section briefly notes early advances in analytical

techniques, in characterizing other resources and in

addressing such nontraditional subjects as air pollution,

biomass, dead wood, esthetics, geographic context (GIS

and satellite remote sensing), nearby nonforest

influences, operability, owner attitudes, range

(agroforestry, browse, livestock use, and understory

forage), recreation opportunities, tropical inventories,

water quality (erosion, hydrology, soils), vegetative

habitat typing, and wildlife.

Air pollution (including biogenic emissions)—Early

studies associating atmospheric pollution with forest

decline (Brooks 1989, Hornbeck and Smith 1985,

Hornbeck and others 1986) later led to detailed

investigations. The first studies on biogenic emissions

used FIA data as input for modeling air pollution from

trees (Guenther and others 1989).

Biomass—Carbon sequestration and fire-danger rating

models use FIA estimates of vegetation biomass.

Analysts use FIA estimates to calculate potential fuel

supply for wood-fired power plants, and to index foliage

volume for ecological habitat characterization.

Scientists first developed estimates for all tree

components and, later, estimates of vegetation on

nonforest land as well as aboveground woody biomass.

An early county-georeferenced, regional assessment map

included estimates of woody biomass by dominant tree

species (Delcourt and others 1981). In Florida, analysts

quantified biomass from forest inventory data on trees,

understory vegetation, samples of woody vegetation on

nonforest land, and averages from unpublished data

(Cost and McClure 1982). In other regions, scientists

used a more precise accounting approach, e.g., in North

Dakota (Jakes and Smith 1982), including biomass

equations for an array of understory species for NorthCentral States (Smith and Brand 1983). Another modeling effort included understory biomass modeling tied to

overstory estimates in Alabama (Joyce and Baker 1987)

and portions of the interior West (Mitchell and others

1987). A study in Alaska tied understory species and

biomass to vertical vegetative structure (Mead and others

1987, Yarie and Mead 1989). Later, scientists associated

with each of these disparate efforts assembled a U.S.-

wide publication on biomass in timberland (Cost and

others 1990).

Dead wood—The term “dead wood” in this report refers

to rotten and standing dead trees, and coarse woody

debris. Live tree assessments are the main reason for

timber resource assessments, but dead materials play a

vital role not only in salvage logging operations but also

in carbon biomass assessment, fire-danger rating, wildlife habitat assessments (termed snags or dens), and as an

indicator of old-growth conditions. Early studies of

standing dead trees applied standard and nonstandard

FIA attributes to assess snag densities for wildlife habitat

appraisal (McComb and others 1986a, 1986b; O’Brien

and Moisen 1992; Ohmann and Bolsinger 1989; Ohmann

and others 1994; Rudis 1988a, 1988b). One novel, early

application used standing dead trees to predict coarse

woody debris for biodiversity appraisal (McMinn and

Hardt 1996).
11

Esthetics—Esthetics embody amenity valuation, visual

penetration, and scenic beauty. Public interest groups,

e.g., the Wilderness Society (Morton 1994), and users of

public land often are concerned with esthetics and scenic

beauty. Quantitative approaches incorporate FIA tree and

plot information directly as models to link timber with

nontraditional resource values, including scenic beauty

(Buhyoff and others 1986; Rudis and others 1988a,

1988b). When used with timber-based profitmaximization modeling, these and other FIA tree- and

plot-based models help estimate hypothetical amenity

values (opportunity cost of timber revenue foregone).

Geographic context (GIS and satellite remote

sensing)—Maps present basic information for assessing

geographic context (Gedney and VanSickle 1979), and

remote sensing using aerial photography has been an FIA

tool since the program’s inception. GIS applications

began with the assembly of a multi-source database at

the county level. One such database included FIA data

assembled from county statistical reports. Known as the

geoecology database (Olson and others 1980), this firstever multidisciplinary effort spawned research uses

beyond timber inventory, including the mapping of

woody biomass (Delcourt and others 1981) and

coterminous U.S. documentation of natural vegetation

(Klopatek and others 1979).

The use of plot-based FIA information began with the

availability of automated plotting and mapmaking

technologies. An early example using approximate plot

locations was the use of FIA data to illustrate the

distribution of roadless forest areas (Rudis 1986). A

decade later, scientists coupled plot-level GIS links with

U.S. census data and FIA data to quantify forest

resources in urban census tracts (Hershey and Birch

1996), as well as to examine potential timber resource

impacts from urban population proximity (Barlow and

others 1998).

Early use of satellite remote sensing and imaging

technologies with GIS resulted in published statistics and

mapped data for Alaska (LaBau and Winterberger 1988),

Arizona (Born and Pearlberg 1987), Illinois (Iverson and

Risser 1987), and Louisiana (Teuber 1987). Such use

spread throughout the United States in the early 1990s

(Powell and others 1993, Zhu 1994, Zhu and Evans

1994). Progress in remote sensing is covered in more

detail elsewhere (Peterson and others 1999). Early

efforts to examine the nontraditional attributes of forests

included poststratification of FIA plot data with

information from satellite imagery to assess the effects

that streamside management zone regulation would have

on timber supplies (Wu 1994).

Nearby nonforest influences—Proximity to roads,

water, and urban or otherwise developed land, as well as

sites with steep slopes or permanent saturation, may

present economic or environmental barriers to timber

management and harvest operations. FIA reports

occasionally include information on some of these items,

but routine inclusion varies widely throughout the United

States.

In the early 1980s, several statewide assessments

reported tabular information on forest area near nonforest

land. Some of this information also appeared in focused

special reports on adverse site conditions, such as road

proximity and steep slopes (Phillips and Powell 1985), or

to assess forest recreation opportunities (Rudis 1986).

Some used terms like “operability” (Czaplewski and

others 1986, Spencer and others 1986) and “timber

availability” (May and LeDoux 1992), which had a

single-discipline context. Resource- or discipline-neutral

terms such as distance from (proximity to) roads, urban

areas, and water bodies served multipurpose resource

information needs. Urban influence studies in the East

started at the county level (Brooks and Rowntree 1984)

and in the West at the plot level to assess neighborhood

context (Oswald 1986). Methods to identify urbanizing

influences varied considerably, with many of the

approaches using aerial photos, which were closely

dependent on measuring the distance from field plots to

variously defined urban areas. Later efforts involved GIS

(see the section on geographic context for additional

information). An early effort to assess streamside

management zone distances involved coarse-scale

georeferencing of FIA plots (Wu 1994).

Owner attitudes—The USDA Economic Research

Service noted in 1976 that many of the then-current FIA

survey reports for the Northeastern United States said

little about the availability of private timber resources

(Moyer and Daugherty 1976). In some States, the reports

simply reported forest land area and volume in a single

nonindustrial owner class approaching 90 percent of the

sample.
12

Improved estimates pioneered in the Northeast used

owner surveys—questionnaires stratified by the

distribution of FIA forested plots (Kingsley 1975, 1976;

Kingsley and Birch 1977; Kingsley and Finley 1975).

This procedure eventually spread throughout the United

States. For many years, the focus was on an owner’s

primary use or reason for owning land and questions

about short-term harvest intentions. Multiple objectives

and multiple-use benefits were ignored, however. Recent

forest owner surveys have included separate queries

about posting, hunting, and other secondary benefits

(Leatherberry 2001a), and now include questions about

multiple land-use objectives.

There currently are no efforts to use the FIA sample

design to sample rural landowners not associated with

forest land. This exclusion limits some forms of crossdisciplinary analysis and modeling, e.g., land used for

public recreation, and forest-to-nonforest land

conversion. A broader sample that includes owners

associated with all land—not just forested land—could

serve a number of purposes for stakeholders, such as to

identify owner attitudes about reforestation, agroforestry

operations (Christmas trees, nonwood forest products),

and interest in tree cover while meeting desired

agricultural crop, recreation, real estate, or wildlife

objectives.

Range—Range is a term used to describe such land uses

as agroforestry, livestock grazing, and wildlife browse or

understory forage. A pioneering study to tally forage

occurred in association with FIA surveys for southern

pine stands. The survey goal was to assess opportunities

to graze livestock and produce timber (Pearson and

Sternitzke 1974). In some regions, scientists later

developed ways to estimate vegetation structure and

foliar cover by testing models that link FIA overstory

measures with amount of forage (Cost 1984, Joyce and

Baker 1987, Mitchell and others 1987, O’Brien and Van

Hooser 1983, Popham and Baker 1987).

The first publication on livestock grazing statistics for

forest land considering broad regions appeared in FIA

forest resource reports for Alabama (Rudis and others

1984), California (Bartolome and Huntsinger 1986,

Bolsinger 1988), and east Texas (Rudis 1988a). In

Kansas, a special study compared FIA timber resources

in grazed and ungrazed forests (Schmidt and Hansen

1998). Forest land with livestock grazing now appears

standard in characterizing the regional mix of resource

uses (Rudis 1998), and in tracking disturbances of forest

land in the South (Rudis 1998, Schweitzer 2000).

Recreation opportunity and remote and roadless

areas—FIA attributes were associated with recreationuse potential, and with pioneering efforts in South

Carolina (Saunders 1979) and later in Alabama (Rudis

1983). The attributes “distance from roads” and “remote

forests“ continue to be a means of distinguishing

primitive from developed recreational experiences (Rudis

1986). Other photointerpretation has been explored

(Czaplewski and others 1986). Additional techniques

using adjacent townships were incorporated for

Minnesota (Freimund and others 1996, Jaakko Poeyry

Consulting 1993b). FIA staff began measuring forest

fragment size (area or extent of contiguous forest cover)

as a surrogate for estimating eligibility for scaledependent timber management assistance programs

(Wells and others 1974), and later used it as a measure of

remoteness, defacto wilderness, or primitive recreational

opportunity (Rudis 1986).

Tropical inventories—With greater need for both

conservation and multipurpose uses of forests on tropical

islands, managers have special inventory information

needs. Soils, rainfall, moisture, and agroforestry land-use

classes represent critical classification attributes on

tropical islands where there is little forest cover. As in the

continental United States, early forest resource surveys in

Puerto Rico and Hawaii focused on potential timber

products, but rejected an examination by traditional landuse classes. Instead, surveyors subdivided tree cover into

selected agroforestry classes such as coffee shade in

Puerto Rico (Birdsey and Weaver 1982) and primary and

secondary forest in Hawaii (Metcalf and others 1978). A

few years later, FIA used a more holistic approach by

first categorizing earth cover, and then subdividing cover

into eight forest, three agroforest, and eight nonforest

land-use and cover classes. For forest land, divisions in

Pacific ecosystems typically included upland, palm,

swamp, mangrove, atoll, plantation, and dwarf forest

(Cole and others 1987, MacLean and others 1986). As on

the continent, detailed measures were made of potential

timber resources, and most efforts focused on woody

biomass and woody species estimation (MacLean and

others 1988, Petteys and others 1986).

Water quality (hydrology and soils)—Though perhaps

not widely known, FIA staff referenced field-sampled
13

14 U.S. Department of Agriculture, Forest Service. 1982. Field

instructions for the Southeast. 120 p. On file with: USDA Forest

Service, Southern Research Station, FIA Unit, 4700 Old Kingston Pike,

Knoxville, TN 37919.

15 Personal communication. 2001. Don Faber-Langendoen, Adjunct

Professor and Senior Ecologist, State University of New York, College

of Environmental Science and Forestry, 448 Illick Hall, 1 Forestry

Drive, Syracuse, NY 13210.

locations to sample soils in selected regions. In

cooperation with NRCS, soil measurements were

included in the early 1980s surveys of Alaska (Larson

and Mead 1983), New England (Ferwerda 1982,

Okoye 1997), and Puerto Rico (Weaver and others

1987). In west Oklahoma, NRCS added FIA

measurements to its land and soil surveys (Rosson

1995). In the Lake States for 1980s surveys, special

studies of air pollution included soil information

(David and others 1988). In connection with a

statewide forest hydrology study for South Carolina

(Dissmeyer 1979), FIA inventory procedures included

measurements of soil-associated attributes such as

erosion potential, litter depth, and soil texture. Several

of the soil-associated attributes were included in the

1976 survey of South Carolina and—with some

variation—continued for a number of years in other

Southeastern States14.

Vegetative habitat typing—Occurrence of a species at

a particular location suggests conditions suited to its

growth. Similarly, a group of overstory tree species at a

given location helps categorize its forest community

type and potential wood productivity. Occurrences of

nontree species also serve the same role, but reports

that document use of these data in FIA surveys have

been sporadic. In the West, nontree species accounted

for, and continue to reflect, potential timber (site)

productivity when no trees are present (MacLean and

Bolsinger 1973). In Utah, FIA field crews classify

vegetative habitat class at sampled locations by both

predominant overstory and understory plant species

(O’Brien 1999). For Wisconsin, a similar approach

recently was used in that State’s most recent forest

survey (Kotar 1999, Kotar and others 1999).

A pilot study begun in the Great Lakes area was

scheduled to formally classify dominant tree overstory,

tree sapling, and site-condition data into ecological

productivity classes15 (personal communication,

Don Faber-Langendoen, State University of New York,

College of Environmental Science and Forestry, November

2001). The long-term goal is to integrate FIA timber-based

forest types with an interagency and NGO-sponsored

ecological classification scheme, known collectively as the

U.S. National Vegetation Classification System (Grossman

and others 1998, Weakley and others 1998).

Wildlife—Early efforts to assess wildlife habitat incorporated a deer browse inventory around 1960. This

pioneering cross-disciplinary research thrust began with

pilot testing (Ehrenreich and Murphy 1962, Moore and

others 1960), and then was followed by regional estimation

of deer browse for north Georgia (Ripley and McClure

1963). A decade later, FIA surveys used browse inventories

in New Hampshire (Barnes 1975) and southwest Louisiana

(Pearson and Sternitzke 1976). FIA surveys in the

Southeast also used vegetation structure attributes to assess

the status of wildlife habitat (Cost 1979, Hamel and others

1986). Habitat assessments showed promise for such

forest-dependent species as the red-cockaded woodpecker

(Lennartz and McClure 1979) and woodcock (Cushwa and

others 1977). Later, FIA conducted assessments in other

regions and for other wildlife species, including black bear,

goshawk, and the Mexican spotted owl. Another early

effort used periodic FIA data summaries to prepare

numerical indices for addressing habitat trends as part of

generic bird habitat appraisals (Graber and Graber 1976).

Scientists also developed models to project trends in

wildlife habitat (Boyce and Cost 1978).

Approaches to Comprehensive Assessments

Several approaches may be used in a comprehensive

assessment of forest resources. These range from a description and analysis of forest resources: (1) from a single

disciplinary perspective involving only FIA data-sets and

written with a single objective, e.g., presentation of the

latest survey statistics, or addressing a singular issue, to (2)

a complete synthesis of analyses from an array of disciplinary perspectives, involving both FIA and other datasets, to address a range of natural resource and socioeconomic issues. For ease of discussion and simplicity, I

categorized the approaches first by discipline, second by

data used, and third by purpose of the report. I coded these

approaches as representing single (S) or multiple (M)

perspective(s) or discipline(s), data-set(s), and purpose(s),

and cite an example for each approach in table 1.
14

Table 1—Range of approaches to reporting of FIA survey results by perspective or discipline, data sources used, purpose of the report, and

examples

Perspective Data sources

Type or discipline used Purpose(s) of the report Example reporta

 and reference

SSS Single FIA Information supplied to a single- Forest Resources of Louisiana (Rosson

surveys discipline target audience, with data and others 1988) primarily reported the

from a single source, and presented status and change in timber resources since

for a single purpose—report of new prior FIA surveys.

survey findings

MSS Multi- Largely Examination by a multidisciplinary Patterns and Trends of Early Successional

disciplinary FIA team of a single data source, for a Forests in the Eastern United States

teams surveys single purpose for which the data are (Trani and others 2001) used timberland

appropriate statistics to assess wildlife habitat.

MSM Multiple Largely Information supplied to a broad, Comprehensive Inventory of Utah’s

FIA multidiscipline audience, with data Forest Resources, 1993 (O’Brien 1999)

surveys from a single source, and presented references ecological community types for

for multiple purposes a variety of user information needs.

SSM Single Largely Collection of selected single Majority of Proceedings of the

FIA discipline perspectives about data Symposium on Arkansas Forests: A

surveys from a single source, and presented Conference on the Results of the Recent

for multiple purposes Forest Survey of Arkansas (Guldin 2001)

SMS Single FIA Examination from single discipline Linking STATSGO and FIA Data for

surveys perspectives with data from Spatial Analysis of Land Carbon Densities

and other multiple sources, and presented for (Xu and Pristley 2000)

data a single purpose

sources

MMS Multi- FIA Examination by multiple or cross- Sustainable Forest Management: Policy,

 Type 1— disciplinary surveys disciplinary teams with data from Planning and Practice: Forum Report

 Planning teams and other multiple sources for a single (Great Lakes Forest Alliance 2000)

 reports data purpose

sources

MMS Multi- FIA Examination by multiple or cross- Multidisciplinary research reports from a

 Type 2— disciplinary surveys disciplinary teams with data from generic environmental impact statement

 Research teams and other multiple sources for a single study of timber harvesting and forest

 reports data purpose management in Minnesota (Jaakko Poeyry

sources Consulting, Inc. 1992a, 1992b, 1992c,

1992d, 1992e, 1992f, 1992g, 1993a,

1993b).

SMM Single Array of Collection of selected single Integrated Tools for Natural Resources

data discipline perspectives, with data Inventories in the 21st Century:

sources from multiple sources for multiple Proceedings of the IUFRO Conference

purposes (Hansen and Burk 2000)

MMM Multi- Array of A synthesis of examinations from Summary Technical Report (Pirani and

disciplinary data multiple discipline perspectives, Yaro 1993) for the analysis of selected

synthesis sources using multiple data sets, and serving resources for the New York-New Jersey

multiple purposes Highlands regional study

a In bold if provided.
15

The following are details about each of these approaches:

SSS—Single discipline or perspective, single source

data, and single purpose. Typically, an SSS report

describes findings from the most recent FIA survey.

Objectives selected are those that the FIA data were

initially designed to address. Although additional data

may be available from other sources, findings are often

limited to the single set of data. In other words,

description and analysis are data-driven or issue-driven,

rather than driven by the need to conduct a thorough

assessment from multiple points-of-view. Reports, tables,

charts, and other output match terms understandable to

one discipline and a single target audience. Issues

addressed are about resources of interest to a particular

audience, e.g., timber (Rosson and others 1988) and

wildlife (Brooks and others 1986). Often there is little

incorporation of other perspectives or involvement by

other stakeholders in determination of the analysis

needed or in a review of the manuscript. A literature

search of associated scientific information often is

uncommon in USDA FS resource bulletin series. This

approach yields the lowest form of integration; a single

disciplinary perspective and FIA data-sets determine the

amount and sufficiency of information included in such

reports.

MSS—Multidiscipline team perspective, single source

data, and single purpose. This approach uses FIA data

and involves multiple disciplinary perspectives for a

single purpose. There is limited involvement in the

choice of objectives by other disciplines. Restrictions on

data utility from multidisciplinary teams often rest with

existing definitions and categories of land use and earth

cover. Approaches to estimation of nonforest land area

with trees, reserved land, woodland, and timberland with

and without livestock grazing are inconsistent or

nonexistent for some States, which limits a number of

assessments that cross disciplinary, political, and

resource use boundaries. Historically, problems between

a land-based resource inventory and its utility to address

other needs may revolve around developing a consensus

between land use and land cover (Powell 1982).

Between the 1980s and early 1990s, four of six FIA

survey regions began quantifying land cover in addition

to land-use classes, e.g., separate land uses for pastured

forest land, urban forest land, and nonforest land with

and without trees. Examples included Christmas tree

operations, orchards, pastureland with trees, urban land

with trees. Occasionally, special studies used these

hybrid land cover and land use classes to quantify other

information needs, e.g., urban vegetation (Geron and

others 1995). Detailed land class (nonforest-land uses

such as cropland, pastureland, and water; and hybrid land

cover and land use) estimates appeared in some forest

resource reports, but none appeared nationally in

standardized form.

Broad land-use classes are standardized and have been

used to map the neighborhood context surrounding forest

land (Rudis 2001). However, hybrid and more detailed

earth-cover and land-use classes remain a local option

(U.S. Department of Agriculture, Forest Service 1999a,

2001b, 2001c, 2001d). FIA surveys use different landcover and land-use classes to account for locally

important uses, such as agroforestry production systems

in the tropics (MacLean and others 1986). Elsewhere,

FIA units have established local standards to assess a

broad range of land uses and incorporate land cover

classes desired by other disciplinary perspectives (Rudis

1993).

A study of early successional habitat (Trani and others

2001) is a recent example that addresses a resource other

than timber. Although the team was interdisciplinary, the

available data were restricted to timberland because such

estimates were consistent across the study’s FIA regions

for the particular objective—assessment of the status and

trends in early successional habitat. Timberland formed

98 percent of the forested habitat of concern, so authors

felt that ignoring the other detailed land classes was not

significant.

MSM—Multiple discipline or perspective, single source

data, and multiple purposes. This approach is driven by

the need to assess findings from the most recent survey.

However, unlike SSS or SSM approaches, it includes

other objectives because results serve a varied audience.

In some cases, SSS authors recast FIA data in terms

relevant to other disciplines. It often includes descriptive

analytical reports that feature multiple facets of the data

collected. Some of these include efforts for the North

(Brooks and others 1993), South (Rudis 1998, Rudis

2001), and interior West (O’Brien 1999). Consultation

with other natural resource experts may precede the

design of the report, issues addressed, and attributes

featured.
16

SSM—A collection of single-discipline perspectives,

single source data, and multiple purposes. This approach

takes the form of collected works with multiple

objectives, where individuals with expertise in various

disciplines, e.g., economics, forest hydrology, recreation

and tourism, silviculture, timber products, wildlife, are

invited or assigned to discuss findings directly associated

with results of a recent FIA inventory. In most cases,

participants have raw or preliminary FIA data to examine

prior to the meeting. Recent efforts have included

collected works for meetings associated with the States

of Alabama (Jones 1991), Arkansas (Guldin 2001), New

York (Abrahamson and others 1996), and Oregon

(Lettman 1988).

Such meetings and the reports they generate serve as

communication outlets for managers, NGOs,

practitioners, planners, and others who may not have

stated publicly or published their opinions regarding FIA

data uses or associated data needs. Often, however,

participants are given little time, and little, if any,

additional funding to provide more than a cursory

overview of findings, let alone a comprehensive crossdisciplinary synthesis of the data or even an in-depth

discussion of issues relevant to one discipline.

Nonetheless, the presentations do provide valuable

insight into the perspectives and interests of contributors.

Such forums provide short-term communication within a

cross-disciplinary audience or readership. Occasional,

well-prepared presentations yield credible syntheses of

disparate concepts or a disciplinary analytical process

from two or more disciplines, which foster crossdisciplinary communication.

The ideal situation would involve (1) including

representatives from other disciplines on the inventory

staff, (2) greater participation through funding for

program interests, and (3) direct involvement of Federal,

State, and private groups from a variety of disciplines

(national forest, State forestry, game and fish, conservation commission, timber industry, planning staffs, and

NGOs) in the analysis of collected data. Scientists and

administrators may initiate these approaches, e.g., in the

late 1970s for South Carolina (McClure and others

1979), but fail to establish the needed long-term

infrastructure. Problems common to multidisciplinary

efforts—limited coordination of analysis among

competing agencies and resource interests, incompatible

priorities and perceived responsibilities, and a limited

administrative infrastructure (Rudis 1993)—make such

approaches difficult to maintain.

Since 1999, State forestry agencies have become direct

partners in the data-collection effort, with shared

responsibilities and funding for FIA activities. They have

raised many questions and have served on committees

that determine attributes and procedures. Though the

process is in an early stage of development, the

interagency infrastructure may well alter the degree of

cross-disciplinary involvement and influence by special

interest groups in subsequent analysis.

SMS—Single discipline or perspective, multiple data

sources, and single purpose. This approach commonly

integrates data from other sources to address a single

objective. Information from research journal articles as

well as articles in focused conference proceedings may

be included. These articles combine FIA data with

separate, independent FIA estimates. Typically,

information is required at a scale appropriate to the goal

of the study, e.g., regional habitat estimates of black bear,

red-cockaded woodpecker, and spotted owl; State-level

owner-preference surveys; stand-level scenic beauty; and

county-level U.S. Census surveys. Recent study goals

have included regional biogenic emissions (Wiedinmyer

and others 2000), soils and carbon sequestration (Xu and

Pristley 2000), and satellite image-scaled estimates

combined with forest structure, slope, elevation and

moisture conditions from FIA plot measurements

(Frescino and others 2001).

MMS—Multiple disciplines or perspectives, multiple

data sources, and single purpose. This is a team-based

assessment focused on a particular issue or geographic

region, or both. The team assigns itself one large task.

One or more individuals with perceived expertise in a

particular discipline assume, or are assigned to,

subcategories of the larger task. Tasks are issue-driven

rather than data-driven. Regardless of data that might be

available, team leaders organize analytical steps and

workflow schedules to ensure that the team addresses all

facets of the issue in a timely manner. For a variety of

reasons, not all appropriate FIA data may be used. These

include lack of expertise in applying the data to crossdisciplinary issues; incompatible priorities, perceived

responsibilities, and disciplinary assumptions; and

inconsistencies in measurement and their resolution

across FIA boundaries (Rudis 1993).
17

MMS Type 1—An MMS assessment that closely

resembles a working document for planning and may

include maps, general guidelines, and narrative

statements not rigorously ascribed to a particular

scientific source or research document. The earliest

report of this type grew from desire to obtain a

“comprehensive core of data and analyses to guide policy

making on all ownerships, including Federal, State, and

private lands” by the California Department of Forestry

and Fire Protection. The goal was to develop a “program

to assess and anticipate the changing role of natural

resource lands in the context of the State as a whole”

(Ewing and others 1988). In California, the issue

revolved around the conflict between rangeland and

forest land among public land managers, rural farmers,

and representatives of other private interests.

A committee composed of individuals representing both

private and public agency interest groups initiated a

similar assessment in New Hampshire some years later.

New Hampshire’s issues focused on “forest sustainability and a more ecological approach to forestry . . . the

role of the forest-based economy . . . the relationship

between forests, people and forest industries . . . the

complex task of balancing society’s interests in

preserving public values in forest land . . . and protecting

personal and property rights” (Forest Resources Plan

Steering Committee 1996).

Other such assessments included regional, issue-focused

reports, such as those for the Great Lakes (Great Lakes

Forest Alliance 2000), New York-New Jersey Highlands

(Michaels and others 1992), and Northern Forest Lands

(Harper and others 1990). In all of those assessments,

traditional FIA data provided background material,

typically describing the historic and present-day status of

the timber resource. Nontraditional data served as

supplementary, broad regional estimates of particular

interest. These included general wildlife habitat statistics

for the Northern Forest Lands study (Watson 1994), and

supplementary ownership information for the New YorkNew Jersey Highlands studies (Michaels and others

1992).

MMS Type 2—MMS assessments that resemble

technical research articles, with close attention to

scientific sources of information. Often there is a concern

about a major regional issue such as the perceived

intensification of wood production—the development of

chip mills for processing of low-quality hardwoods,

extensive establishment of pine plantations, or

conversion of oak-pine stands to pure pine. Forecasting

with timber growth models, other resource projection

models, U.S. census statistics, and other economic

indicators are formally associated with ground-based

inventory data when possible to evaluate various facets of

the assessment.

One such case involved the State of Minnesota, which

commissioned a study, now known as a Generic

Environmental Impact Statement (GEIS) (Jaakko Poeyry

Consulting 1994), to investigate timber harvesting and

forest management. This unique effort funded a number

of reports by a private consulting firm. The firm provided

limited release of the documents, distributing them to

State agencies and the public for a nominal cost, then

later released them on the Web. Reports focused on forest

area and owner trends (Jaakko Poeyry Consulting 1992f),

biodiversity (Jaakko Poeyry Consulting 1992a), damage

to trees or forest health (Jaakko Poeyry Consulting

1992c), economics (Jaakko Poeyry Consulting 1992b),

recreation and esthetics (Jaakko Poeyry Consulting

1993b), soils (Jaakko Poeyry Consulting 1992d), timber

resources (Jaakko Poeyry Consulting 1992e), water and

fisheries (Jaakko Poeyry Consulting 1992g), and wildlife

(Jaakko Poeyry Consulting 1993a). A final report

abstracted the results of individual, discipline-specific

studies and synthesized results (Jaakko Poeyry

Consulting 1994). Scientists affiliated with these studies

later reported portions of the results in Ph.D.

dissertations or more widely read outlets, i.e., journal

articles and technical proceedings (Anderson and others

1992, Freimund 1994, Freimund and others 1996, Grigal

and Bates 1997, Kapple 1995, Rose and others 1992).

Other examples include broad regional, multi-year

studies conducted to address regional issues in the

Southern Appalachians (Southern Appalachian Man and

the Biosphere 1996b), Interior Columbia Basin (Quigley

and others 1996), and Ouachita-Ozark Highlands (U.S.

Department of Agriculture, Forest Service 1999b). The

role and contribution of FIA to the assessment varied

with funding and issues endemic to the regions under

study.

The MMS Type 2 assessments often have substantial

funds to support the logistics of data assembly, modeling,

and analysis but often draw upon existing data to make
18

inferences and model associations with other data. FIA

data most often are used to categorize forest area by

ownership and stand-diameter classes on private forest

land. They also provide county level estimates of total

forest land, current timber volume, growth, harvest,

mortality, and susceptibility to tree pests. Issues that

require more than timber production statistics, such as

“biodiversity, soil depletion and productivity, certain

seral stages, and [perceived] loss of . . . nonrenewable

forest resources” (Quigley and others 1996), remain

unresolved.

FIA data that could have been used to resolve some of

the issues, such as detailed traditional and nontraditional

FIA measurements (U.S. Department of Agriculture,

Forest Service 2001c), were not collected in a standard

way across the entire assessment region or were

inadequately developed for scientific analysis. Southern

Appalachian studies referred primarily to specialized

data analyzed by selected disciplines (Herman 1996).

Interior Columbia Basin studies referred only to the

standardized national summary of traditional data

(Powell and others 1993). Other FIA data may have been

included in the assessment database for future research

use, but the final technical assessment contains no

details. In many such cases, available FIA data are

dwarfed by other information already standardized and

readily useable by a variety of disciplines, e.g., in the

West by forest management inventories of the National

Forest System, and in the East by the USDA NRCS

National Resources Inventory (NRI).

SMM—Single discipline or perspective, multiple data

sources, and multiple purposes. This assessment

approach usually uses a narrowly-focused session or

symposium proceedings resulting from conferences

concerned with inventory measurements. Reports

occasionally include journal articles. Annotation of

nontraditional and novel FIA data uses and techniques

prior to 1990 appear in a workshop “Progress with

integrating multiple value objectives into broad-scale

forest inventories,” held in Syracuse, NY, August 2, 1989,

as part of a state-of-the-art conference on forest

inventory methodology (LaBau and Cunia 1990).

Occasionally, there is coordination among participants at

such conferences. Participants involved with FIAassociated data often sponsor sessions or workshops at

many of the larger international conferences. Lately,

biometricians have taken the lead in organizing a formal

symposium series focused just on FIA-associated topics;

and two had been completed as of July 2001—for the

years 1999 (McRoberts and others 2000) and 2000

(Reams and others 2001).

These conferences have documented developments in

measurement tools, statistical analysis techniques, and

data uses. Titles attached to these conferences reflect

their focus: integrated inventories (Lund and others

1978), forest resource inventories (Frayer 1979), wildlife

habitat inventories (Cushwa and others 1979), in-place

resource inventories (Brann and others 1982), renewable

resource inventories (Bell and Atterbury 1983), forest

inventory methodology (LaBau and Cunia 1990), and

global natural resource monitoring and assessments

(Lund and Preto 1990). More recently, one focused on

forest ecosystem resource surveys in North America, and

many topics were relevant to tropical forest assessments

(Aguirre-Bravo and Franco 1999).

Coordinated sessions at larger conferences result in

reports that form substantial bodies of knowledge about

selected issues. The latest major international conference

(Hansen and Burk 2000) used the theme “integrated

inventory tools,” and included sessions on natural

resource inventory design, analysis, and management

applications; measurement consistency issues; data

management; GIS and remote sensing applications;

forest growth model interfaces; and special purpose

inventories and applications.

MMM—Multidisciplinary team(s) or multiple

perspectives, multiple data sources, and multiple

purposes. This assessment approach commonly produces

a report synthesizing several in-depth reports or chapters

with differing perspectives, as well as data examined in

detail by others. It is a summary document representing

highlights of findings, common threads, and concepts. In

its simplest form, such an approach is akin to a synthesis

of papers presented at a conference involving disparate

studies and data-sets. Length and depth may vary from a

brief synthesis, such as an impromptu summation of

presentations, to a more deliberate integration of

disparate concepts. An example of the former was done

for Arkansas (Blackmon 2001) and of the latter for the

New York-New Jersey Highlands (Pirani and Yaro 1993).

Well-funded multidisciplinary teams integrate their

findings more fully, sometimes with additional
19

interdisciplinary analysis, such as is included in the

Northwest Forest plan (Haynes and Perez 2000), the

1989 RPA assessment (U.S. Department of Agriculture,

Forest Service 1990), and the Southern Appalachian

assessment (Southern Appalachian Man and the

Biosphere 1996a).

Progress Toward Multipurpose Utility

Dual and multiple land uses are the norm for most arable

land in the United States. Traditional single-resource

classification simplifies these complexities, making

possible tabular reports and assessments. The estimates

produced yield coarse-scaled resource assessments. Such

estimates are questionable if there are substantial areas

with mixed forest and nonforest-land uses, such as forest

land or significant commercial wood products in

agriculture- or urban-dominated neighborhoods.

The literature review suggests three approaches. The first

is a field method of documenting uses on a sampled plot.

The second method documents a plot’s proximity to

dominating nonforest-land uses. The third method

surveys nonindustrial private owners for information

about their land use and makes assumptions about uses

affiliated with industrial and public ownership. The three

approaches use different scales of measurement; but in

every case, the assessment proceeds following estimation

of the multiple land-use probabilities for a sampled plot

and the resources they represent. Although these

approaches provide credible data for planning at

predefined scales, the accuracy of assigned probabilities,

and analyses at other measurement scales, are of

concern.

For example, FIA plot-based indices of livestock grazing

in forested areas corroborate findings from an

examination of the surrounding neighborhood. In the

South, livestock grazing on forest land occurs in a few

ecological provinces, primarily in pasture-dominated

landscapes (Rudis 1998). Grazing on forest land also

occurs in the California Sierra Mountains (Bartolome and

Huntsinger 1986) and in the Intermountain West. The

same is true for forests dominated by urban influences.

Urban uses of forest land are important components in

estimation of resources, particularly in coastal portions of

the United States (Dwyer and others 2000).

Because it takes so long to inventory a region and

monitor changes, past designers of the FIA program are

occasionally fortunate in providing for unanticipated data

needs. For example, Pacific yew, a noncommercial

species, was discovered in the 1980s to have anticancer

properties. Fortuitously, FIA program staff were able to

draw information from an already collected, larger

inventory of otherwise noncommercial species, and to

provide estimates of the range and extent of the Pacific

yew (Bolsinger and Jaramillo 1990).

The historic design of the survey does not always serve

current needs, however. Definitions of forest land

established in earlier decades may not always represent

current uses, such as season-specific grazing on forest

land and urban development within forest landscapes, or

match current measurement technology, e.g., satellite

imagery. On private land, detailed timber information

from FIA surveys may be ancillary to a more widely

encompassing, standardized inventory, e.g., the NRCSNRI. In public-dominated areas of the West, until

recently, the FIA sample design did not extend to

National Forest System land.

Satellite imagery of forest cover types also competes

with traditional FIA field-collected data. The U.S.

Geologic Service’s Land Use and Land Cover, the U.S.

Fish and Wildlife Service’s Gap survey, as well as other

well-funded Federal and State earth-cover inventory

programs, serve broader audiences because the resulting

scale of information products may be closer to perceived

management issues. Many users of FIA data have

questioned the spatial precision and error estimates

associated with the program’s widely spaced samples.

Landsat and other satellite-based inventories may provide

products more suited to the needs of a variety of

disciplines. The advantage of satellite imagery is that (1)

the data management and organization are flexible

enough to accommodate changing needs, e.g., data

categories and elements can be reassembled to suit other

disciplinary assumptions, and (2) the data have logical

spatial and temporal associations with other geographic

information important to a comprehensive assessment.

Nevertheless, advances in GIS technologies have made it

possible to readily visualize FIA data in geographic

context—not only by scientists but also by decisionmakers and advocacy groups in a variety of disciplines.

A decade ago, Rudis (1991) stated that “integration of
20

FIA information with other land use data should provide

users with an improved information database with which

to test hypotheses and become better informed about

regional impacts.” Since that time, spatially oriented data

retrievals, analysis, and linkages with other data-sets

have occurred, and more than 70 citations have

referenced FIA data. Such studies commonly refer to

geography related hypotheses, e.g., about the distribution

of forested ecosystems, their associated characteristics,

habitats for forest-dwelling species, regional ecological

landscape dynamics, land-use practices, and temporal

trends. More than half of these have been published in

just the past five years. Using GIS, links between FIA

data and satellite imagery are also more common in a

number of recent regional modeling efforts, such as

global climate change monitoring and air pollution

assessment.

Synthesis

Given the array of approaches now used, it is safe to say

that the time has arrived for a disciplined, strategic

inventory of associated attributes, and the incorporation

of other relevant data and analysis. However one may

view the inclusion of inventory attributes or analytical

techniques to address a particular issue, it is important to

weigh potential benefits against their potential cost.

The sheer volume of citations in nontraditional subject

areas [air pollution, biomass, dead wood, esthetics,

geographic context (GIS and satellite remote sensing),

nearby nonforest influences, operability, owner attitudes,

range (agroforestry, browse, livestock use, and

understory forage), recreation opportunities, tropical

inventories, water quality (erosion, hydrology, soils),

vegetative habitat typing, and wildlife] is staggering.

Scientists from a wide range of disciplines have

developed analytical techniques, novel measurements,

and models to characterize other resources and address a

variety of issues.

Relating some of these specialized FIA data and analyses

to nationally important, comprehensive assessments

occurs periodically with RPA appraisals. Examples

include biomass (Cost and others 1990) and urban forests

(Dwyer and others 2000). Integration of a unit of timber

with a unit of one or more other resources has yet to be

achieved, however. Efforts to directly link biomass, urban

forests, and other subject areas with timber resource

supplies, forest management, and land-use policies have

been hampered by inconsistencies among data collected

and their sources. Establishment of minimal standards for

a comprehensive as well as cost-effective assessment of

forest resources may be required for State and regional

analyses. Adaptation and refinement of procedures

probably will be necessary if the data are to be used in

future national RPA appraisals.

With the exception of biomass and urban forest

attributes—and perhaps a few others—many field

observations and data uses remain provincially rather

than nationally applicable and poorly coordinated among

regions. Some specialized field observations may not be

cost effective to inventory nationally. These are likely to

remain important in studies for modeling or a regionspecific assessment such as special forest products (e.g.,

bear grass in the Pacific Northwest), invasive species

(e.g., Melaleuca spp., a problematic nonnative invasive in

Florida) and management practices unique to specific

portions of the country. Retention of collective

knowledge about specialized data and the unique

resource uses in an area become problems whenever

decisions are made not to consider them in national

assessments.

Specialized data of the FIA survey appear to have been

fully used when they: (1) are consistent across spatial

and temporal scales important to the geographic region

and questions being addressed; (2) are well-documented

and stored in a form suited to available analytical

techniques, or can be made so in a timely fashion to suit

the timetable of the assessment; (3) lend themselves to

data management and organization that are flexible

enough to accommodate changing needs; (4) can be

reassembled without bias to suit other disciplinary

assumptions; and (5) have logical spatial and temporal

associations with other data important to a

comprehensive assessment, e.g., satellite imagery and

economic and social surveys. More rapid progress

towards comprehensive assessments can be achieved if

all specialized FIA data met these criteria.

If the goal of comprehensive assessment of the forest

resource is to integrate analysis from all relevant

disciplinary and regional perspectives and to synthesize

findings, then the FIA program organization should

reflect those goals at all levels. Convergence of an array

of common attributes and the analysis of protocols of
21

comprehensive assessment will be achieved only by

clarification and refinement of an evolving knowledge

base. Maintenance and support for a central depository of

documented results and use by both data analysts and

designers of data collection procedures may ensure that

progress.

Acknowledgments

Assistance with this report came from many individuals.

I received help from Marie Davis, Assistant Department

Head, InfoSouth, University of Georgia, Athens, GA, for

AGRICOLA citation data searches; LaDonne Delgado,

Coordinator for Government Documents and

Microforms, Mississippi State University, for help with

government documents on microfiche; and staff of the

USDA FS, Southern Research Station, FIA Program with

citation entries. Appreciation for entries is extended to

Mark Hansen and Tom Schmidt at the North Central

Research Station; Bob Brooks, Susan King, Andy Lister,

Will McWilliams, and Rachel Riemann at the

Northeastern Research Station; Ralph Alig, Andrew Gray

and Janet Ohmann at the Pacific Northwest Research

Station; Renee O’Brien at the Rocky Mountain Research

Station; and John Pye at the Southern Research Station.

Scientists at universities and the USDA FS provided

reprints and lists of publications and helped to verify FIA

data uses for some of the publications. Manuscript

reviewers included Roger Lord, Boise Cascade

Corporation; Mark Hansen, USDA FS, North Central

Research Station; and Doug Powell, USDA FS,

Washington Office.

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Appendix

References by Selected Subjects

This section lists the citations of major nontraditional subject areas: air pollution; biomass; dead wood; esthetics;

geographic context (GIS and satellite remote sensing); nearby nonforest influences; operability; owner attitudes; range

(agroforestry, browse, livestock use, and understory forage); recreation opportunities; tropical inventories; water quality

(erosion, hydrology, and soils), vegetative habitat typing; and wildlife. The keyword combinations came from an earlier

examination of unique words in titles published between 1979 and 1990. The list of associated citations is

representative, because not all documents or their abstracts are electronically indexed, nor are some abstracts or full

reports of older publications electronically accessible. Readers may contact the author for lists in subjects other than

those included here.

Air pollution: Citations with “air pollution” or “biogenic emissions” in the title, abstract, or annotation

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asmdnerl/biogen.html. [Date accessed: June 2003].

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experience in New England. In: IUFRO workshop on monitoring air pollution impact on permanent sample plots, data

processing and results interpretation; 1991 September 2–6; Prachatice, Czechoslavakia. Prague, Czechoslovakia:

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Eckhoff, Janet Dawn. 2000. Efficacy of forest health monitoring indicators to evince impacts on a chemically manipulated

watershed. Orono, ME: University of Maine. 318 p. Ph.D. dissertation.

Ediriwickrema, Don Jayantha. 1996. Modeling and analysis of AVHRR data for biogenic emission inventory system (BEIS).

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Water, Soil, and Air Pollution. 31: 425–430.

Kinnee, Ellen; Geron, Chris; Pierce, Thomas. 1997. United States land use inventory for estimating biogenic ozone precursor

emissions. Ecological Applications. 7(1): 46–58.

Lamb, B.; Gay, D.; Westberg, H.; Pierce, T. 1993. A biogenic hydrocarbon emission inventory for the U.S.A. using a simple

forest canopy model. Atmospheric Environment. 27(11): 1673–1690.

Liu, Chiun-Ming. 1988. A decisionmaking framework for assessing atmospheric deposition impacts on regional forest

inventory. Blacksburg, VA: Virginia Polytechnic Institute and State University. 167 p. Ph.D. dissertation.
34

Ohmann, Lewis F.; Shifley, Stephen R. 1989. Relations between forest conditions and atmospheric deposition along the

northwestern Minnesota-to-southeastern Michigan deposition gradient. In: Noble, Reginald D.; Martin, Juri L.; Jensen,

Keith F., eds. Air pollution effects on vegetation including forest ecosystems: Proceedings of the 2d

 US–USSR symposium;

1988 September 13–25; Corvallis, OR, Raleigh, NC, and Gatlinburg, TN. Broomall, PA: U.S. Department of Agriculture,

Forest Service, Northeastern Forest Experiment Station: 225–232.

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inventories of Maine. Durham, NC: Duke University. 267 p. Ph.D. dissertation.

Steinman, James. 1999. Changes in composition of the mixed mesophytic forest: effects of succession and disturbance.

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Wiedinmyer, C.; Strange, I.W.; Estes, M. [and others]. 2000. Biogenic hydrocarbon emission estimates for north central Texas.

Atmospheric Environment. 34: 3419–3435.

Wiedinmyer, Christine; Allen, D.T. 1999. Land use characterization in Texas for use in photochemical models [Abstract]. In:

American Geophysical Union fall meeting: program and abstracts; 1999 December 13–17; San Francisco. Washington, DC:

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Wiedinmyer, Christine; Guenther, Alex; Estes, Mark [and others]. 2001. A land use database and biogenics emissions

inventory for the State of Texas. Atmospheric Environment: Vol. 35(36): 6465–6477.

Zeide, Boris. 1992. Reevaluation of forest inventory data from loblolly pine stands in the Georgia Piedmont and Mountain

areas. In: Flagler, R.B., ed. The response of southern commercial forests to air pollution. Pittsburgh: Transactions of the Air

and Waste Management Association: 17–35.

Biomass: Citations with “biomass” in the title

Brand, Gary J.; Smith, W. Brad. 1985. Evaluating allometric shrub biomass equations fit to generated data. Canadian Journal

of Botany. 63(1): 64–67.

Brown, S.; Schroeder, P.; Birdsey, R. 1997. Aboveground biomass distribution of U.S. Eastern hardwood forests and the use of

large trees as an indicator of forest development. Forest Ecology and Management. 96(1–2): 37–47.

Brown, S.L.; Schroeder, P.E. 1999. Spatial patterns of aboveground production and mortality of woody biomass for Eastern

U.S. forests. Ecological Applications. 9(3): 968–980.

Brown, Sandra L.; Schroeder, Paul; Kern, Jeffrey S. 1999. Spatial distribution of biomass in forests of the Eastern U.S.A.

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Chojnacky, David C. 1984. Volume and biomass for curlleaf cercocarpus in Nevada. Res. Pap. INT–332. Ogden, UT: U.S.

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Cost, Noel D. 1986. Multiresource inventories: woody biomass in North Carolina. Res. Pap. SE–261. Asheville, NC: U.S.

Department of Agriculture, Forest Service, Southeastern Forest Experiment Station. 36 p.

Cost, Noel D. 1988. Multiresource inventories: woody biomass in Virginia. Res. Pap. SE–269. Asheville, NC: U.S.

Department of Agriculture, Forest Service, Southeastern Forest Experiment Station. 35 p.

Cost, Noel D.; Howard, James O.; Mead, Bert [and others]. 1990. The forest biomass resource of the United States. Gen. Tech.

Rep. WO–57. Washington, DC: U.S. Department of Agriculture, Forest Service. 21 p.

Cost, Noel D.; McClure, Joe P. 1982. Multiresource inventories–forest biomass in Florida. Res. Pap. SE–235. Asheville, NC:

U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station. 24 p.

Cost, Noel D.; McClure, Joe P. 1982. Multiresource inventories: techniques for estimating biomass on a statewide basis. Res.

Pap. SE–228. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station. 31 p.

Cost, Noel D.; McClure, Joe P. 1984. Biomass inventory and assessment in the Southern United States. Biomass. 6: 15–24.
35

Cost, Noel D.; Tansey, John B. 1985. Multiresource inventories: woody biomass in Georgia. Res. Pap. SE–248. Asheville, NC:

U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station. 32 p.

Delcourt, Hazel R.; West, Darrell C.; Delcourt, Paul A. 1981. Forests of the Southeastern United States: quantitative maps for

abovegound woody biomass, carbon, and dominance of major tree taxa. Ecology. 62(4): 879–887.

Frieswyk, Thomas S.; Malley, Anne M. 1986. Biomass statistics for New Hampshire–1983. Resour. Bull. NE–92. Broomall,

PA: U.S. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station. 85 p.

Husain, Syed Arif. 1997. Spatial and dynamic analysis of timber and biomass supply in Minnesota. St. Paul, MN: University

of Minnesota, Department of Applied Economics. 184 p. Ph.D. dissertation.

Jenkins, Jennifer C.; Birdsey, Richard A. 2000. Validation databases for simulation models: aboveground biomass and net

primary productivity (NPP) estimation using eastwide FIA data. In: Hansen, Mark; Burk, Thomas, eds. Integrated tools for

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515–524.

Joyce, Linda A.; Mitchell, John E. 1989. Understory cover/biomass relationships in Alabama forest types. Agroforestry

Systems. 9: 205–210.

Knight, Herbert A.; McClure, Joe P. 1981. Multiresource inventories: forest biomass in South Carolina. Res. Pap. SE–230.

Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station. 22 p.

McClure, Joe P.; Knight, Herbert A. 1984. Empirical yields of timber and forest biomass in the Southeast. Res. Pap. SE–245.

Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station. 75 p.

Mead, B.R. 1992. Methods for describing and comparing biomass distribution among selected Alaska vegetation types. In:

Wood, Geoff; Turner, Brian, eds. Integrating forest information over space and time; 1992 January 13–17; Canberra,

Australia. Canberra, Australia: Anutech, Pty. Ltd.: 358–366.

Mead, Bert; Yarie, John; Herman, David. 1987. Biomass estimates for nontimber vegetation in Tanana River Basin of interior

Alaska. In: Wharton, Eric H.; Cunia, Tiberius, comps. Estimating tree biomass regressions and their error: Proceedings of

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May 26–30; Syracuse, NY. Gen. Tech. Rep. NE–117. Broomall, PA: U.S. Department of Agriculture, Forest Service,

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Mead, Bert R. 1995. Plant biomass in the Tanana River Basin. Res. Pap. PNW–RP–477. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station. 78 p.

Mitchell, J.E.; Bartling, P.N.S.; O’Brien, R.A. 1987. Understory cover-biomass relationships in the front range ponderosa pine

zone. Res. Note RM–471. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Intermountain Research

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Rosson, James F., Jr. 1988. Residual woody biomass on harvested timberland in Mississippi. In: Davids, Robert A.; Watson,

W.F.; Savelle, I. Winston, eds. Proceedings of the ninth annual southern forest biomass workshop; 1987 June 8–11; Biloxi,

MS. Mississippi State, MS: Mississippi State University: 152–162.

Rosson, James F., Jr. 1989. Potential residual biomass in mature pine stands of the Midsouth, U.S.A. Biomass. 20: 145–153.

Rosson, James F., Jr. 1992. The woody biomass resource of major tree taxa for the Midsouth States. Resour. Bull. SO–166.

New Orleans: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station. 52 p.

Rosson, James F., Jr. 1993. The woody biomass resource of Alabama, 1990. Resour. Bull. SO–178. New Orleans: U.S.

Department of Agriculture, Forest Service, Southern Forest Experiment Station. 127 p.

Rosson, James F., Jr. 1993. The woody biomass resource of Arkansas, 1988. Resour. Bull. SO–179. New Orleans: U.S.

Department of Agriculture, Forest Service, Southern Forest Experiment Station. 130 p.

Rosson, James F., Jr. 1993. The woody biomass resource of east Texas, 1992. Resour. Bull. SO–183. New Orleans: U.S.

Department of Agriculture, Forest Service, Southern Forest Experiment Station. 87 p.
36

Rosson, James F., Jr. 1993. The woody biomass resource of Louisiana, 1991. Resour. Bull. SO–181. New Orleans: U.S.

Department of Agriculture, Forest Service, Southern Forest Experiment Station. 114 p.

Rosson, James F., Jr. 1993. The woody biomass resource of Tennessee, 1989. Resour. Bull. SO–182. New Orleans: U.S.

Department of Agriculture, Forest Service, Southern Forest Experiment Station. 129 p.

Rosson, James F., Jr. 1994. The woody biomass resource of east Oklahoma. Resour. Bull. SO–184. New Orleans: U.S.

Department of Agriculture, Forest Service, Southern Forest Experiment Station. 76 p.

Rosson, James F., Jr.; Thomas, Charles E. 1986. The woody biomass resource of Alabama. Res. Pap. SO–228. New Orleans:

U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station. 31 p.

Schroeder, P.; Brown, S.; Mo, J.M. [and others]. 1997. Biomass estimation for temperate broadleaf forests of the United States

using inventory data. Forest Science. 42(3): 424–434.

Smith, W. Brad. 1985. Factors and equations to estimate forest biomass in the north central region. Res. Pap. NC–268. St.

Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station. 6 p.

Smith, W. Brad. 1986. Biomass yields for small trees, shrubs, and herbs in Northern Lake States forests. Res. Pap. NC–277.

St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station. 6 p.

Smith, W. Brad; Brand, Gary J. 1983. Allometric biomass equations for 98 species of herbs, shrubs and small trees. Res. Note

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Wharton, Eric H.; Alerich, C.L.; Drake, D.A. 1997. Estimating total forest biomass in New York, 1993. Resour. Bull. NE–139.

Radnor, PA: U.S. Department of Agriculture, Forest Service, Northeastern Research Station. 48 p.

Wharton, Eric H.; Cunia, Tiberius. 1987. Estimating tree biomass regressions and their error: Proceedings of the workshop on

tree biomass regression functions and their contribution to the error of forest inventory estimates, 1986 May 26–30;

Syracuse, NY. Gen. Tech. Rep. NE–117. Broomall, PA: U.S. Department of Agriculture, Forest Service, Northeastern Forest

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Wharton, Eric H.; Griffith, Douglas M. 1998. Estimating total forest biomass in Maine, 1995. Resour. Bull. NE–142. Radnor,

PA: U.S. Department of Agriculture, Forest Service, Northeastern Research Station. 50 p.

Wheatcraft, Andrew M.; Lewis, David K. 1986. Forest biomass resources of Oklahoma. Bull. B–781. Stillwater, OK:

Oklahoma State University, Agricultural Experiment Station. 45 p.

Yarie, John; Mead, Bert R. 1982. Aboveground tree biomass on productive forest land in Alaska. Res. Pap. PNW–298.

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16 p.

Yarie, John; Mead, Bert R. 1988. Twig and foliar biomass estimation equations for major plant series in the Tanana River

Basin of interior Alaska. Res. Pap. PNW–401. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station. 20 p.

Yarie, John; Mead, Bert R. 1989. Biomass regression equations for determination of vertical structure of major understory

species of southeast Alaska. Northwest Science. 63(5): 221–231.

Biomass: Citations with “biomass” only in the abstract or annotation.

Adamus, Paul; Brandt, Karla. 1990. Wooded wetland vegetation. In: Impacts on quality of inland wetlands of the United

States: a survey of indicators, techniques, and applications of community level biomonitoring data. Rep. EPA/600/3–90/073.

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Other FIA-Associated Literature

This section contains citations not listed elsewhere:

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Web Sites with FIA-Associated Data Uses

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130
Rudis, Victor A. 2003. Comprehensive regional resource assessments and multipurpose uses of forest inventory

and analysis data, 1976 to 2001: a review. Gen. Tech. Rep. SRS–70. Asheville, NC: U.S. Department of

Agriculture, Forest Service, Southern Research Station. 129 p.

Reported is a compilation of over 1,400 literature citations and a review of selected subjects that constitute an

integrated knowledge base for comprehensive forest resource assessments with regional, field sample-based forest

inventory data. The focus of the report is on nontraditional and novel technical uses tied to the U.S. Department

of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) field surveys published or in press between

1976 and July 2001. Briefly noted are pioneering studies that link FIA data with air pollution, biomass, dead

wood, esthetics, geographic context (geographic information systems and satellite remote sensing), nearby

nonforest influences (operability, roads), owner attitudes, range (agroforestry and livestock use), recreation,

tropical inventories, water quality (soils and hydrology), vegetative habitat typing, and wildlife. All known M.S.

theses and Ph.D. dissertations associated with FIA data since 1976 are included, regardless of subject matter. Also

incorporated are citations of collected works concerning integrated assessments and multidisciplinary surveys and

representative citations associated with economics, global climate change, remote sensing, sampling designs,

tropical forest resources, and traditional timber resource assessments. The literature review suggests assessments

are “comprehensive” for issues in selected regions and chosen resources. Multidiscipline involvement,

multipurpose uses of nontraditional data, and analysis of resources other than timber are variable. Nontraditional

measurements and models, with some exceptions, have been provincially, rather than nationally, applicable and

not well coordinated among regions. Recommended are ways to accelerate progress toward comprehensive

assessments and cost-effective multipurpose uses.

Keywords: Bibliography, ecological inventories, forest inventory, hydrology, interdisciplinary studies, integrated

assessments, monitoring, natural resource planning, range, recreation, timber, water, wildlife habitat.
The Forest Service, United States Department of

Agriculture (USDA), is dedicated to the principle of

multiple use management of the Nation’s forest resources

for sustained yields of wood, water, forage, wildlife, and recreation.

Through forestry research, cooperation with the States and private

forest owners, and management of the National Forests and

National Grasslands, it strives—as directed by Congress—to

provide increasingly greater service to a growing Nation.

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