Trees At Work:

United States Department of Agriculture

Forest Service

Southern Research Station

General Technical Report SRS-226

November 2017

Economic Accounting for Forest 

Ecosystem Services in the U.S. South

Erin O. Sills, Susan E. Moore, Frederick W. Cubbage, Kelley D. McCarter, 

Thomas P. Holmes, and D. Evan Mercer 
Editors

Erin O. Sills, Professor, Department of Forestry and Environmental 

Resources, College of Natural Resources, North Carolina State 

University, 3110 Jordan Hall, Campus Box 8008, Raleigh, NC 

27695- 8008; Susan E. Moore, Associate Extension Professor (retired), 

Department of Forestry and Environmental Resources, College of 

Natural Resources, North Carolina State University, 4223 Jordan 

Hall Addition, Campus Box 8008, Raleigh, NC 27695- 8008; 

Frederick W. Cubbage, Professor, Department of Forestry and 

Environmental Resources, College of Natural Resources, North Carolina 

State University, 3118B Jordan Hall, Campus Box 8008, Raleigh, NC 

27695-8008; Kelley D. McCarter, Program Coordinator, Department of 

Forestry and Environmental Resources, College of Natural Resources, 

North Carolina State University, 4221 Jordan Hall Addition, Campus 

Box 8008, Raleigh, NC 27695-8008; Thomas P. Holmes, Research 

Forester, U.S. Department of Agriculture, Forest Service, Southern 

Research Station, P.O. Box 12254, Research Triangle Park, NC 27709; 

and D. Evan Mercer, Research Economist (retired), U.S. Department of 

Agriculture, Forest Service, Southern Research Station, P.O. Box 12254, 

Research Triangle Park, NC 27709.

Cover photo

by Edmund Garman, https://www.flickr.com/photos/3cl/14930524212

Disclaimer

The use of trade, firm, or model names in this publication is 

for reader information and does not imply endorsement by the 

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

November 2017

Southern Research Station

200 W.T. Weaver Blvd.

Asheville, NC 28804

www.srs.fs.usda.gov
Trees At Work:

Economic Accounting for 

Forest Ecosystem Services

in the U.S. South

Erin O. Sills, Susan E. Moore, Frederick W. Cubbage, 

Kelley D. McCarter, Thomas P. Holmes, and D. Evan Mercer 
ii

Chapter Authors

Chapter 1, Introduction

Erin O. Sills, Professor, Department of Forestry and Environmental Resources, North Carolina State University, 

3110 Jordan Hall, Raleigh, NC 27695-8008

R. David Simpson, Principal, RDS Analytics, LLC., 2435 Shenandoah Street, Vienna, VA 22180

D. Evan Mercer, Research Economist (retired), USDA Forest Service, Southern Research Station, 3041 Cornwallis 

Road, P.O. Box 12254, Research Triangle Park, NC 27709

Chapter 2, Forest Ecosystem Services: Cultural Values

Melissa M. Kreye, Post-Doctoral Researcher, School of Forest Resources and Conservation, University of Florida, 

Newins-Ziegler Hall, Gainesville, FL 32611

Damian C. Adams, Associate Professor, Natural Resource Economics and Policy, University of Florida, 

Newins- Ziegler Hall, Gainesville, FL, 32611

Ramesh Ghimire, Spatial Economics Research Scientist, Atlanta Regional Commission, 40 Courtland Street NE, 

Atlanta, GA 30309

Wayde Morse, Associate Professor, School of Forestry and Wildlife Sciences, Auburn University, 3229 Forestry and 

Wildlife Sciences Bldg., Auburn, AL 36849

Taylor V. Stein, Professor, School of Forest Resources and Conservation, University of Florida, P.O. Box 110410, 

Gainesville, FL 32611

J.M. Bowker, Research Social Scientist, USDA Forest Service, Southern Research Station, 320 Green St., Athens, 

GA 30602

Chapter 3, Forest Ecosystem Services: Water Resources

Thomas P. Holmes, Research Forester, USDA Forest Service, Southern Research Station, 3041 Cornwallis Road, 

P.O. Box 12254, Research Triangle Park, NC 27709

James Vose, Research Ecologist, USDA Forest Service, Southern Research Station, Center for Integrated Forest 

Science, North Carolina State University, Department of Forestry and Environmental Resources, Raleigh, NC 27695

Travis Warziniack, Research Economist, USDA Forest Service, Rocky Mountain Research Station, 240 West 

Prospect Road, Fort Collins, Colorado 80526

Bill Holman, North Carolina State Director, The Conservation Fund, 410 Market St., P.O. Box 271, Chapel Hill, 

NC 27516
Trees At Work: Economic Accounting for Forest Ecosystem Services iii in the U.S. South

Chapter 4, Forest Ecosystem Services: Carbon and Air Quality

David J. Nowak, Senior Scientist/i-Tree Team Leader, USDA Forest Service, Forest Inventory and Analysis, 5 Moon 

Library, SUNY-ESF, Syracuse, NY 13210

Neelam C. Poudyal, Associate Professor of Natural Resource Policy and Human Dimensions, Department of 

Forestry, Wildlife, & Fisheries, University of Tennessee, 274 Ellington Plant Science Bldg., Knoxville, TN 37996

Steven G. McNulty, Director, USDA Southeast Regional Climate Hub, 920 Main Campus Drive, Venture Center 2, 

Suite 300, Raleigh, NC 27606

Chapter 5, Forest Ecosystem Services: Provisioning of Non-Timber Forest Products

James L. Chamberlain, Research Forest Products Technologist, USDA Forest Service, Southern Research Station, 

FIA, 1710 Research Center Drive, Blacksburg, VA 24060

Gregory E. Frey, Research Forester, USDA Forest Service, Southern Research Station, 3041 Cornwallis Road, 

P.O. Box 12254, Research Triangle Park, NC 27709

C. Denise Ingram, Consultant, P.O. Box 2326, North Wilkesboro, NC 28659

Michael G. Jacobson, Professor of Forest Resources, Pennsylvania State University, 309 Forest Resources Building, 

University Park, PA 16802

Cara Meghan Starbuck Downes, Research Economist, USDA Forest Service, Southern Research Station, 

3041 Cornwallis Road, P.O. Box 12254, Research Triangle Park, NC 27709

Chapter 6, Conclusion

Erin O. Sills, Professor, Department of Forestry and Environmental Resources, North Carolina State University, 

3110 Jordan Hall, Raleigh, NC 27695-8008 

R. David Simpson, Principal, RDS Analytics, LLC., 2435 Shenandoah Street, Vienna, VA 22180

D. Evan Mercer, Research Economist (retired), USDA Forest Service, Southern Research Station, 3041 Cornwallis 

Road, P.O. Box 12254, Research Triangle Park, NC 27709

Chapter Authors, cont.
iv

Acknowledgments

Darrel Pendris, Forest Stewardship Council, Culpeper, VA

Dru Preston, Georgia Forestry Commission, Dry Branch, GA

William Pryor, Georgia Forestry Commission, Claxton, GA

Bettina Ring, Virginia Department of Forestry

Mike Santucci, Virginia Department of Forestry, 

Charlottesville, VA

Hughes Simpson, Texas Forest Service, Lufkin, TX

Edie Sonne Hall, Weyerhaeuser Company, Federal Way, WA

Nancy Stairs, NC Forest Service, Raleigh, NC

John Sunday, Georgia Forestry Commission, Thomson, GA

Jack Swanner, NC Forestry Association, Raleigh, NC

Jeff Vincent, Duke University, Durham, NC

Stewart West, Kentucky Division of Forestry, Frankfort, KY

Steve Whitfield, NC Woodlands, Raleigh, NC

Risher Willard, Georgia Forestry Commission, Claxton, GA

We also received helpful feedback from the participants and 

audience of a special session on “Matching the means to the ends: 

choosing appropriate methods for valuation of forest ecosystem 

services” at the Annual Meeting of the International Society of 

Forest Resource Economics. Raleigh NC, April 2016.

Alicia Raimondi, Simon Hall, and Connor Rice served as 

graduate research assistants for the project, including reviewing 

relevant literature, in 2014-2016. They were graduate students in 

the Department of Forestry and Environmental Resources, North 

Carolina State University, Raleigh, NC 27695-8008.

Other graduate students and staff members served as facilitators 

and note-takers during the many planning and stakeholder 

meetings in 2014-2016:

Micheala Foster, Natasha James, Grizel Gonzalez-Jeuck, 

Kelley McCarter, Mark Megalos, Christopher Serenari, and 

Addie L. Thornton, Department of Forestry and Environmental 

Resources, North Carolina State University, Raleigh, NC 

27695- 8008

The editors are grateful for the expert formatting and editorial 

assistance of Leslie Byrd of Adesso Design, Apex, NC, and 

Lane Eskew, Fort Collins, CO.

T

he research leading to this publication included two 

stakeholder meetings (in addition to multiple meetings of 

the expert panels). The project coordinators cast a wide 

net to obtain a diversity of perspectives on ecosystem services 

from forests in the Southeastern United States. The stakeholder 

meetings provided important context on how ecosystem services 

are defined, understood, and valued in the region. The editors 

wish to acknowledge the essential role of these participants in the 

research process leading to this publication.

Stakeholder Meeting Attendees and 

Expert Panel Contributors, 2014-2016

Tim Adams, SC Forestry Commission, Columbia, SC

Clayton Altizer, NC Forest Service, Raleigh, NC

Charlie Becker, Virginia Department of Forestry, 

Charlottesville, VA

Rebecca Benner, The Nature Conservancy, Durham, NC

Caitlin Burke, Conservation Trust for North Carolina, 

Raleigh, NC

Janet Cakir, South Atlantic LCC, Chapel Hill, NC

Sam Cook, Center for Heirs’ Property Preservation, 

Charleston, SC

Tony Doster, Resource Management Service, LLC, 

Wilmington, NC

Patrick Glass, Arkansas Forestry Commission, Little Rock, AR

Jim Hancock, Mississippi Forestry Commission, Jackson, MS

Dylan Jenkins, Finite Carbon, Wayne, PA

Dan Len, USDA Forest Service, Atlanta, GA

Kerry Livengood, Tennessee Division of Forestry, Nashville, TN

Luanne Lohr, USDA Forest Service, Washington, DC

Larry Lowe, Kentucky Division of Forestry, Frankfort, KY

Will McDowell, Environmental Defense Fund, Raleigh, NC

Brian Murray, Duke University, Durham, NC

Barry New, NC Forest Service, Raleigh, NC

Herb Nicholson, SC Forestry Commission, Columbia, SC

Jarek Nowak, Florida Forest Service, Tallahassee, FL

Wib Owen, Southern Group of State Foresters, Garner, NC

Rusty Painter, Conservation Trust for North Carolina, 

Raleigh, NC
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South v

Southern forests provide a variety of critical ecosystem services, from 

purification of water and air to recreational opportunities for millions of 

people. Because many of these services are public goods with no observable 

market value, they are not fully accounted for in land use and policy decisions. 

There have been several efforts to remedy this by estimating the total value 

of forests in different States, with each effort including different bundles 

of ecosystem services and using different valuation methodologies. In this 

guide, we propose a more consistent and theoretically sound approach to 

1) quantifying annual flows of ecosystem services, 2) developing a spatial 

catalog of the marginal values of changes in those flows, and 3) accounting for 

the total value of ecosystem services lost or gained as a result of changes in 

forest ecosystems. Four chapters—on cultural services, watershed services, air 

quality and carbon, and provisioning of non-timber forest products—provide 

guidance on best practices for quantifying and estimating the values of these 

services as provided by forests. Expert panels were convened to write each 

chapter. The guide as a whole was developed with input from the Southern 

Group of State Foresters and stakeholder meetings held in 2014 and 2015.

Keywords: ecosystem services, non-market valuation, green accounting, 

southern forests, non-timber forest products, watershed services, air quality, 

cultural services.

Abstract
vi

Table of Contents

Chapter Authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .ii

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

Chapter 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Antecedents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Previous Assessments in the U.S. South . . . . . . . . . . . . . . . . . . . 2

Motivations for Quantifying the Value of FES in the U.S. South . . . . . . 3

Economic Accounts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Incorporating FES into Accounts . . . . . . . . . . . . . . . . . . . . . . . 5

Structure of the GTR . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Appendix 1.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Chapter 2. Forest Ecosystem Services: Cultural Values . . . . . . . . 11

What Are Cultural Services? . . . . . . . . . . . . . . . . . . . . . . . . 11

Connecting Cultural Ecosystem Services with the Ecosystem Services 

Valuation Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12

Valuation Methodologies . . . . . . . . . . . . . . . . . . . . . . . . . . .17

Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .26

Appendix 2.1 Recreation and tourism values of forests in the

Southeast region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Chapter 3. Forest Ecosystem Services: Water Resources . . . . . . . . 31

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .31

Ecosystem Service Assessments of Water Resources from 

Forest Landscapes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33

Economic Valuation of Water Resource Ecosystem Services . . . . . . . . 38

Guidelines for Estimating the Ecosystem Service Values of Water 

Resources from Forest Landscapes . . . . . . . . . . . . . . . . . . . . . .41

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .45
Trees At Work: Economic Accounting for Forest Ecosystem Services vii in the U.S. South

Chapter 4. Forest Ecosystem Services: Carbon and Air Quality . . . . .49

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .49

Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .49

Biophysical Quantification of Ecosystem Services . . . . . . . . . . . . . .54

Economic Valuation of Ecosystem Services . . . . . . . . . . . . . . . . . 55

Improving Future Valuation . . . . . . . . . . . . . . . . . . . . . . . . . .58

Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . .60

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61

Chapter 5. Forest Ecosystem Services: Provisioning of 

Non-Timber Forest Products . . . . . . . . . . . . . . . . . . . . . . . . .65

Introduction and Background . . . . . . . . . . . . . . . . . . . . . . . . .65

Identification and Selection of NTFPs for Valuation . . . . . . . . . . . . .69

Quantification of NTFP Provisioning Services . . . . . . . . . . . . . . . .74

Valuation of Marginal Changes in NTFP Provisioning Service . . . . . . . 81

Estimation of Production Costs . . . . . . . . . . . . . . . . . . . . . . . .85

Scaling Up/Aggregating . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .87

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .87

Appendix 5.1 Summary of select valuation studies of NTFPs in 

the U.S. South and around the world . . . . . . . . . . . . . . . . . . . . .90

Appendix 5.2 FIA Forest Groups and Associated Tree Species . . . . . . . 92

Appendix 5.3 Summary of Data Sources . . . . . . . . . . . . . . . . . . .93

Chapter 6. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

Principles of Economic Accounting for Ecosystem Services . . . . . . . . .95

Recommended Structure for Assessment of Forest Ecosystem Services . . .96

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

Table of Contents, cont.

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 1

Chapter 1

Introduction

Erin O. Sills, R. David Simpson, D. Evan Mercer

ecosystem services, we suggest consulting a recent state of the 

science review provided by the Northern Research Station, U.S. 

Forest Service (Binder and others 2017).

ANTECEDENTS

Interest in the economic value of changes to natural ecosystems 

has a long history, beginning in the 1960s (e.g., Clawson 1959, 

Krutilla 1967) and blossoming in the 1980s and ’90s (Banzhaff 

2010, Liu and others 2010). The 21st century has brought 

exponential growth in scientific publications on ecosystem or 

ecological services (Fisher and others 2009). One catalyst for 

this growth was a controversial article in the journal Nature by 

Costanza and others (1997), which has been cited over 15,000 

times according to Google Scholar. Using benefit transfer 

techniques (often improperly [Plummer 2009]), Costanza 

and others (1997) estimated the world’s ecosystem services 

to be worth $33 trillion, $15 trillion more than Gross World 

Product in 1997. A 1998 special issue of Ecological Economics

contained eight stinging commentaries on Costanza and others 

(1997), while a 1998 column in Nature (vol. 395, page 430) 

called the article a “box office success ... panned by the critics” 

and “a political document ... of no use for policy analysis or 

implementation.” Costanza and others (2014) conceded that 

the article was “clearly an awareness-raising exercise with no 

specific policy or decision in mind,” and it certainly did raise 

awareness both of the value of ecosystem services and of the 

potential pitfalls in attempting to estimate total values.

In fact, the use of ecosystem service values in policy and 

management decisionmaking has been limited (Adamowicz 

2004, Liu and others 2010, Laurans and others 2013, Rogers 

2015). Laurans and others (2013: 241) concluded that the value 

of ecosystem services typically “receives no more than a cursory 

reference in the form of an expected, proposed or desired use,” 

while Liu and others (2010: 73) state that “the contribution of 

ecosystem service valuation to ecosystem management has 

not been as large as hoped nor as clear as imagined.” Recent 

Federal policy initiatives, however, have generated new interest 

MOTIVATION

Given the economic importance of wood products in the 

U.S. South, the value of southern forests as timberlands is 

well known and acknowledged in State policy decisions. 

However, timber represents only part of the value of forests, and 

forestry leaders are increasingly interested in quantifying the full 

value of the South’s forests, i.e., the value of all final ecosystem 

services produced by forests, including cultural (non-tangible) 

benefits, regulation of environmental quality, and provision 

of services (timber and non-timber goods). Recent efforts to 

quantify forest ecosystem services (FES) at the State level have 

considered different sub-sets of these services and employed 

different methodologies (Escobido and Timilsina 2012, Moore 

and others 2011, Paul 2011, H. Simpson and others 2013), which 

have limited the credibility of the results, the utility of cross-state 

comparisons, and the ability to report regional values. To address 

these issues, this guide describes best practices for quantifying 

four categories of FES (cultural services, regulation of water 

quantity and quality, regulation of air quality, and provisioning 

of non-timber goods) and a framework for estimating the total 

value of gains or losses due to changes in FES. While these four 

categories of services have been identified as the most important 

to stakeholders in the forestry sector in the Southern States, they 

are not comprehensive, e.g. pollination services are excluded 

here but discussed elsewhere (Iovanna 2017). In this introductory 

chapter, we explain the increasing interest in ecosystem services, 

discuss the motivations for valuation of FES in particular, and 

place this work in the context of economic accounting.

The primary intended audience for this report is State forestry 

officials charged with requesting, selecting, guiding, and 

evaluating the results of FES assessments in their states. We 

assume prior knowledge only of introductory micro-economics 

or forest economics. Thus, this report is not intended as a 

comprehensive guide to actually carrying out an assessment, but 

rather to obtaining an assessment that is methodologically sound 

and policy relevant. For readers who are interested in expanding 

their understanding of approaches used to assess and value forest 
Table 1.1—Previous assessments of forest ecosystem services in Florida, 

Georgia, Virginia, and Texas

Florida

(Escobedo and 

Timilsina 2012)

Georgia

(Moore and 

others 2011)

Virginia

(Paul 2011)

Texas

(Simpson and 

others 2013)

Value 

estimate

 $2.07 billion 

($151/acre/year)

$37.7 billion 

($1,709/acre/year)

 $15.3 billion 

($880/acre/year)

$92.9 billion/year 

($1,489/acre/year)

Scope FSP lands Private forests All forests All forests 

Services 

valued

Water, carbon, 

timber, habitat

Water, climate, 

habitat, pollination

Water, carbon, 

forest products, 

habitat, recreation

Watershed 

regulation, climate, 

biodiversity, 

cultural values

FSP = Forest Stewardship Program.

2 Chapter 1. Introduction

in using estimated values of ecosystem services as inputs to 

policy and management decisions (Richardson and others 2015). 

For example:

● In 2011, a report by the President’s Council of Advisors on 

Science and Technology (PCAST 2011) recommended:

○ establishing a Quadrennial Ecosystems Services Trends 

(QuEST) Assessment and

○ requiring Federal agencies to include valuation of impacts 

on ecosystem services in planning and management 

decisions.

● The U.S. Forest Service 2012 Planning Rule requires 

evaluation of ecosystem services associated with alternatives 

for managing the National Forests (USFS 2015).

● In 2013, the White House released “Principles and 

Requirements for Federal Investments in Water Resources” 

(CEQ 2013), requiring Federal agencies to use an ecosystem 

services approach to evaluate Federal investments in 

water resources.

● In 2015, the Council on Environmental Quality issued 

a memorandum directing all Executive Departments 

and Agencies to document how they would incorporate 

ecosystem services in their activities (CEQ 2015).

Most of these Federal guidelines call for agencies to consider 

how policy, management, and investment decisions affect 

flows of ecosystem services, quantified in terms of the value of 

those changes.

There is also increasing interest in mainstreaming ecosystem 

service valuation into accounts, or “green accounting.” Progress 

has been made both internationally, e.g., by the G8 (TEEB 

2015), the European Union (Brower and others 2013), and 

multilateral organizations (WAVES 2015), as well as at the State 

level, e.g., by the Ecosystems Services Working Group (ESWG) 

in Maryland (USDA 2015) and as reflected in adoption of the 

Genuine Progress Indicator by 20 States (Ceroni 2014). These 

efforts typically estimate total values of ecosystem services based 

on existing valuation literature.

PREVIOUS ASSESSMENTS IN THE U.S. SOUTH

Four Southern States have recently completed assessments of 

ecosystem services and FES in particular. The scope and findings 

varied from State to State, as summarized in table 1.1 and 

described in more detail below.

Following a scoping study by the Virginia Department of 

Forestry in 2006, the Piedmont Environmental Council funded 

a Yale University study to estimate the value of all ecosystems 

in Virginia. Annual ecosystem service benefits from Virginia’s 

forests were estimated to be $15.3 billion ($880/acre/year), as 

reported in table 2 of Paul (2011). Choosing a narrower scope, 

the Florida Forest Service commissioned the University of 

Florida to quantify the most important values generated by 

forest lands enrolled in the Florida Forest Stewardship Program. 

The present value of the ecosystem services from the 437,800 

enrolled acres was estimated to be $2.07 billion ($5,030 per 

acre or $151/acre/year at the assumed 3-percent discount rate) 

(Escobedo and Timilsina 2012). Funded by the Georgia Forestry 

Association, the University of Georgia assessed the value of 

all private forest lands in Georgia, resulting in an estimated 

annual value of $37.7 billion ($1,709/acre/year) (Moore and 

others 2011). The most recent effort, commissioned, funded, 

and implemented (with collaborators) by the Texas A&M Forest 

Service, found Texas’ forest ecosystem services to be worth 

$92.9 billion/year ($1,489/acre/year) (Simpson and others 2013). 

The wide range in the estimated annual value of ecosystem 

services generated by an average acre of forest land (from $151/

acre/year in Florida to $1,709/acre/year in Georgia) reflects both 

methodological differences and differences in the value of forests 

across the four States.
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 3

One reason for the wide range in values is the different scopes 

of the studies. For example, the Florida study focused on the 

value of “the components of forests that are directly enjoyed, 

consumed, or used to produce specific, measurable human 

benefits,” while the Georgia study used the more general concept 

of “ecosystem services as the things nature provides that are of 

direct benefit to humans.” The authors of each State study made 

different choices about which services to include; for example, 

only Florida and Virginia included timber, and only Georgia and 

Virginia included pollination services. Most critically for the 

total value estimates, only Texas and Georgia included estimates 

of the non-use value of forests (e.g., aesthetic and cultural 

benefits). However, all studies estimated the value of forests 

for protecting water quality, regulating water flow, regulating 

climate change via carbon sequestration, and providing wildlife 

habitat or biodiversity. Water (including both quality and quantity 

dimensions) is a key component of the total value in all States: 

66 percent in Florida, 54 percent in Georgia, at least a third in 

Virginia (varying by forest type), and 14 percent in Texas. This is 

consistent with findings from the stakeholder workshop described 

below, in which participants identified water as the most 

important ecosystem service to include in valuation studies.

The four studies varied in their methods. Although all used 

benefit transfer (or “value transfer”) (Richardson and others 

2015), the Virginia study only transferred values from published 

revealed preference studies, while the other studies drew on 

a much broader literature. All of the studies transferred “unit 

values” for some services, multiplying the value (or average 

value) per acre reported in the literature by the number of acres 

of a given forest type. They varied in how far they were willing 

to extrapolate values from the literature to different forest types 

and different locations. For the Florida study, the researchers 

estimated meta-regressions to obtain values of water and habitat 

adjusted to conditions in Florida. The Florida study also used 

the spatial modeling tool InVEST (Integrated Valuation of 

Environmental Services and Tradeoffs) for water, nutrients, and 

timber. In Georgia and Texas, original stated preference surveys 

were conducted to estimate non-use values.

The studies also reflect different approaches to disaggregating 

forests in order to calculate values. In Georgia, researchers 

divided private forests into categories based on forest type, 

riparian status, rare species abundance, scenic visibility, public 

land buffer, development class, and geographic region. They 

then transferred values per acre of each ecosystem service from 

the literature for each category of forest. The other State studies 

differentiated per acre values differently for each ecosystem 

service, e.g., using FIA (Forest Inventory and Analysis) forest 

types for carbon, watersheds or proximity to water for watershed 

services, and broad regions for other services. In some cases, 

researchers assumed that the supply of ecosystem services 

varies across regions, whereas in other cases, the demand 

was also assumed to vary. For example, the Florida and Texas 

studies estimated watershed and cultural values by multiplying 

household willingness-to-pay (WTP) by the number of 

households living in each region.

MOTIVATIONS FOR QUANTIFYING THE 

VALUE OF FES IN THE U.S. SOUTH

Often referred to as the “wood basket” of the world, the U.S. 

South produces over 18 percent of the world’s pulpwood and 

7 percent of industrial roundwood, generating more than $230 

billion in traditional economic output and $48 billion in wages 

for almost 1.1 million people (SGSF 2013). Southern forests also 

provide regulatory and cultural ecosystem services, including air 

and water purification, climate regulation, wildlife habitat, and 

recreational opportunities. Rapid population growth throughout 

the South is driving land use changes that put forests at risk, 

while simultaneously increasing the number of people in the 

region who value FES. The Forest Service, U.S. Department of 

Agriculture, forecasts that 23 million acres of forest land will 

be converted to other uses by 2060 (Wear and Greis 2013). This 

conundrum of simultaneously increasing threats and values 

makes it essential to quantify changes in FES in order to better 

manage change in the forest sector.

To identify the specific motivations and goals for valuation of 

FES in the Southern States, we reviewed the reports summarized 

in the previous section and convened a meeting in February 2014 

with 38 stakeholders from Federal (3 participants) and State (15) 

government, NGOs (12), private industry (4), and academia (4) in 

10 Southern States. Most (90 percent) participants had more than 

10 years of experience in natural resources fields.

The stakeholders all agreed that one key purpose for valuing 

FES is to increase awareness of the importance of southern 

forests and the consequences of forest loss. Some hoped that 

reporting a single (large) dollar value for all FES in a State 

would catch the attention of the public and policymakers, thus 

replicating the global influence of the Costanza and others (1997) 

study at the State level. As noted above, there are concerns 

about the theoretical validity of this approach and its utility to 

decisionmakers. In the following section, we therefore review 

the theoretical basis and mechanics of constructing economic 

accounts. This leads us to suggest that this objective can best be 

met by quantifying each FES in physical units, such as percent of 

drinking water that flows through forests or number of recreation 

user days in forests, while using valuation to understand changes 

in FES.
4 Chapter 1. Introduction

Other goals expressed by stakeholders require understanding how 

values vary across space and time in order to manage change, 

specifically by:

1. Improving policy, land use planning, and decisionmaking by 

quantifying the value of forests relative to other land uses 

and identifying which forests are most important for which 

ecosystem services;

2. Catalyzing and supporting the creation of ecosystem service 

markets by estimating the values of those services; and

3. Reducing the inherent bias of valuing forests (and setting 

policy) only for commercial forest products rather than by 

assessing the value of all benefits from all forests.

Of course, each stakeholder group has its own particular 

concerns. State forestry agencies need to evaluate forest 

conservation programs. For example, the USDA Forest 

Stewardship Program (FSP) provides funding to States to help 

landowners plan and sustainably manage millions of acres of 

forest land for timber, wildlife habitat, watershed protection, 

recreation, and other ecosystem services. One goal of a Florida 

State assessment of FES was to quantify the value of ecosystem 

services provided by properties enrolled in the FSP. State forestry 

agencies also must respond to the natural disasters that regularly 

affect southern forests, including hurricanes, floods, tornadoes, 

ice storms, drought, and wildfires. The resulting timber losses 

are well-documented, but methods are needed to quickly and 

accurately estimate losses of other FES, to help make the case 

for public assistance for recovery efforts in forests that are not 

actively managed for timber.

Although decisionmakers in State government have been the 

primary target audience for FES assessments, conservation 

organizations and private landowners also find them important. 

For example, conservation organizations can use the results to 

direct resources toward properties with high ecosystem service 

values, while private landowners can use the results to report how 

their land management affects FES and to guide their transactions 

in ecosystem service markets (cf., Kareiva and others 2015). 

Thus, most stakeholder goals require understanding the value 

of changes in FES resulting from marginal losses or gains of 

particular types of forest in particular regions.

ECONOMIC ACCOUNTS

Given that all stakeholders expressed interest in an accounting 

of the total value of FES in their States, we review here how 

standard economic accounts are constructed and interpreted, as 

well as the challenges of expanding these accounts to include 

FES. An accounting total is generally considered to be a “bottom 

line” measure that summarizes overall performance in a single 

monetary figure such as gross national product or income, which 

represents what economists call “utility,” or, more broadly, 

“welfare.” This figure is obtained by: 1) assembling data on 

quantities of “goods and services”; 2) assembling data on the 

value society attaches to these goods and services, as measured 

by “prices”; and 3) multiplying the quantity by the price for every 

good and service and summing over all goods and services.

Assuming that the quantities and values of all final goods and 

services have been identified and summed, the next question is 

how to interpret the results. Economic accounts are typically 

more useful as measures of changes from one year to the next 

than of any absolute level of well-being. For example, if the 

national product increased by $300 billion from one year to 

another, one might conclude that the country is collectively $300 

billion (about $1,000 per person) richer than the year before. On 

the other hand, the national income of the United States is about 

$17 trillion per year. There is no reasonable basis for saying that 

we are, collectively, $17 trillion, or about $53,000 per person, 

better off than we would be if we produced and consumed 

literally nothing. Would the average American accept $53,000 to 

do without literally everything for a year? Likewise, we might 

identify increases or decreases in the acres of different forest 

types in a State and multiply these by per-hectare values of FES. 

However, even with good estimates of the per-hectare values, we 

could not use this procedure to calculate a figure that accurately 

reflects the consequences of the complete elimination of all 

forests in the State, i.e., the total value of all of those forests.

Thus, we focus on changes in accounting totals, considering what 

they reveal about changes in well-being. Economists assume 

that people make decisions in order to maximize their utility,1 or 

the net benefits (welfare) they receive as a consequence of their 

consumption choices. As shown mathematically in Appendix 1.1, 

the change in an individual’s welfare from one period to the 

next is just the change in the quantity of each good and service 

consumed by the individual, multiplied by its price, and summed 

over all goods and services. Thus, the change in the accounting 

total is the dollar value of the change in total welfare.

Next, we consider how to aggregate changes in individual welfare 

over the entire population. The simple answer is to add together 

the changes in aggregate consumption of each good weighted 

by its price. While this procedure is straightforward and often 

used, it has some fundamental problems. When we add up the 

changes in expenditures over all individuals, and call it a change 

in aggregate welfare, we are implicitly assuming that everybody 

has identical reactions to changes in their income (i.e., everyone 

has the same marginal utility of income). While unverifiable 

1

 Or more accurately, people make decisions as if they were maximizing utility. 

According to a standard economic proof, if people prefer some alternatives over 

others in a consistent way, they behave as if their preferences were determined by 

a “utility function.”
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 5

empirically (since utility cannot be observed or measured), it is 

reasonable to assume that a $1,000 increase in annual income 

would be much more important and valuable to someone with 

an annual income of $20,000 compared to someone with an 

annual income of $200,000. The only theoretical justification 

for adding up changes in individuals’ expenditures to get some 

notion of the welfare of the population as a whole is the idea 

of “potential compensation.” The “potential compensation” (or 

“Kaldor-Hicks”) criterion holds that if the sum of accounting 

gains is positive, there is—at least in theory—a way to assure that 

everyone is made better off by redistributing the monetary gains 

(Johansson 1993). In practice, changes that increase the overall 

value of FES may have negative effects on the welfare of some 

groups even while they have positive effects on the welfare of 

other groups.

INCORPORATING FES INTO ACCOUNTS

While accounting appears to be a straightforward exercise, 

incorporating FES presents several complications. First, many 

goods and services that contribute to our well-being do not 

have prices that can be observed from transactions in markets. 

There are two likely reasons why we cannot observe prices for 

these ecosystem goods and services. One is entirely mundane, 

but always worth considering. We do not observe prices for 

things that are not worth much. This is a proposition that may 

seem at once counterintuitive and commonsensical. It may seem 

counterintuitive when applied to the goods and services nature 

provides, because goods and services such as fresh water and 

flood protection are essential to human life. However, common 

sense suggests that when small changes in the amounts of goods 

and services make no difference, they are not valuable. Things 

command high prices when a little more of them contribute 

substantially to our welfare, and this, in turn, happens when the 

things in question are in short supply relative to their demand. 

Fresh water is essential to life, but it is not very valuable when 

and where there is plenty of water available relative to the 

number of people who benefit from it.

The other possible explanation for the lack of observable prices 

is that the good or service in question is “public” in some or all 

aspects. A public good is one that is non-rival and non-exclusive. 

Non-rival means that when one person benefits from the good, it 

does not diminish the benefits for others. A good is non-exclusive 

when there is no feasible way to prevent others from benefiting 

from it. In this case, the value of an additional unit of the good is 

the sum of its value to all individuals who benefit from it. These 

characteristics of public goods undermine the functioning of 

private markets because the prices of any transactions in markets 

for public goods understate their value. There may not even be 

any transactions, if no one pays to provide something that confers 

a relatively small benefit to each of a relatively large number 

of people.

Non-market valuation techniques have been developed to 

estimate “prices” for goods and services that are valuable 

but not traded in markets. The following chapters discuss the 

most commonly used and appropriate techniques for different 

categories of FES. However, it is important to recognize that the 

prices determined through these techniques are highly context 

dependent. Real estate agents sometimes say that three things 

determine the price of a property: location, location, and location. 

Because a home is fixed on the landscape, much of its value is 

determined by its proximity to places of work, shopping venues, 

and attractive natural features. Likewise, the value of attractive 

natural features depends crucially on the number of people who 

can access them. Moreover, the values of ostensibly similar 

ecological features may vary tremendously depending on how 

much is available, now and in the future or under alternative 

policy scenarios. Market prices reflect this variation for most 

goods that are bought and sold in markets; the challenge is 

obtaining “prices” that reflect the local supply and demand for 

ecosystem services that are not traded in markets.

A second complication with accounting in general, and especially 

in accounting for ecosystem services, is that not all ecosystem 

goods and services are things we enjoy directly (sometimes called 

final goods and services or benefit relevant indicators) (Olander 

and others 2015). Some, called intermediate goods and services, 

are inputs required to produce final goods and services. Further, 

many of these inputs could be considered investments made 

today in order to produce final goods and services in the future. 

And furthermore, some of these capital investments may be for 

the purpose of averting or restoring damages.

The final challenge that we consider here is valuing 

investments—giving up some consumption now in order to 

enhance consumption possibilities later. Suppose that we define 

units so that, by giving up one “apple” now, we can acquire 

one unit of “capital.” Let’s suppose that “capital” can be used 

to enhance our future consumption of “bananas.” So, what is 

the worth of the extra unit of capital we would get by foregoing 

consumption of an apple? It consists of the products of three 

things, which are first multiplied together, and then summed over 

the life of the capital investment:

● The utility derived from the additional banana 

consumption, times

● The extra banana production, afforded by the additional 

capital investment, times

● A discount factor that expresses the value of foregoing 

current consumption to increase consumption in the future.

If a consumer were to decide to eat an extra apple this year, 

we would multiply that apple by its price and add it to all the 

other consumption changes, weighted by their prices, in order to 
6 Chapter 1. Introduction

estimate the change in welfare. If the consumer forgoes eating an 

apple in order to grow more bananas, though, she is showing that 

she regards that investment (or input) to be at least as valuable 

for her overall welfare as immediate consumption of an apple. 

Hence, it is reasonable to add to the ledger of changes in welfare 

the net present value of investment.2 Assuming that consumers 

and investors made this calculation in deciding how much to 

invest, we can simply record the dollar value of investment as a 

measure of its contribution to well-being.

The calculation of this value is more daunting when considering 

investments in the production of public goods. Investments and 

disinvestments in forests may not be made optimally when, for 

example, a landowner plants trees that store carbon or protect 

downstream water quality. In this case, we should still record 

the value of the investment, but we must now estimate values 

for the public goods of carbon storage and water quality. This 

requires understanding the “extent of the market,” or the size of 

the population that benefits from these goods. Further, we must 

calculate these values over the life of the investment. This means, 

in particular, we must project the marginal value of the public 

good, the investment’s contribution to the provision of that public 

good, and the discount factor to be employed, over the time 

horizon of the investment.

Finally, we note that many of the effects of (dis)investments in 

natural capital are eventually reflected in traditional economic 

accounts. For example, if clearing forests increases the 

probability of floods, the damage will eventually be reflected 

in lost assets or reduced agricultural yields. Thus, part of the 

motivation for green accounting is to attribute a portion of 

changes in gross domestic product (or other summary figures) to 

changes in natural capital. Another motivation is to project the 

effects of current (dis)investments in natural capital on future 

well-being. Finally, clearly some (dis)investments in natural 

capital affect well-being directly and thus are additional to 

standard economic accounts. To obtain a comprehensive measure 

of long-term economic performance, we would need to account 

for all of these future returns to investments.

STRUCTURE OF THE GTR

The following four chapters on cultural (chapter 2), regulating 

(chapters 3 and 4), and provisioning (chapter 5) services 

exemplify the different approaches and different levels of 

information found in the literature. Non-market valuation 

methods can be categorized as either stated preference, meaning 

that they are based on surveys that elicit people’s values, or 

revealed preference, meaning that they infer values from prices 

in related markets. The chapter on cultural ecosystem services 

2

 The modifier “net” before value is important. It is certainly possible to 

make disinvestments. One way to do this would be by failing to keep up with 

depreciation. Another is by liquefying capital assets, including natural capital such 

as forests.

describes both stated and revealed preference methods that 

can be used to estimate the value of these services in particular 

contexts and for particular populations. The chapter on water 

services gives greater emphasis to revealed preference methods. 

The chapter on air quality emphasizes benefit transfer approaches 

embedded in accounting frameworks for urban forests and 

for climate change mitigation. The next chapter discusses 

provisioning of non-timber forest products (NTFPs). Once 

harvested, NTFPs are private (rather than public) goods, but there 

are still significant challenges in quantifying harvest and deriving 

the associated value of the forest provisioning service.

These chapters lay the groundwork for the concluding chapter 

to discuss aggregation of such highly variable information 

(across services, forests, and people) and potential pitfalls or 

red flags involved in doing this. While the four chapters on 

different categories of ecosystem services describe options for 

estimating the marginal values of those services, the final chapter 

considers how to aggregate those marginal values in order to 

track changes in value over time and project changes in value 

as a result of policy alternatives. This should be considered both 

when planning and when reviewing results of an assessment (e.g., 

when writing terms of reference or assessing deliverables). The 

concluding chapter argues that FES assessments should account 

for total flows of ecosystem services from forests (in physical 

units), but should quantify the marginal value (in dollar terms) of 

the most likely changes in forest cover. This approach will help 

steer FES assessments around the numerous possible pitfalls of 

green accounting. 

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8 Chapter 1. Introduction

Appendix 1.1

use a basic result from economic theory. The trick is to divide 

all the terms in the expression above by one of the marginal 

utilities—say, for convenience, the marginal utility of apples:

 

... A B A N A dU MU = dA+ MU MU dB + + MU MU dN.

 (1.3)

The fundamental result from theory is that the ratio of the 

marginal utilities of any two goods a consumer buys is equal to 

the ratio of the prices she pays for them; that is,

 B B

A A

MU p

MU p = , (1.4)

and so forth, for all other goods the consumer buys (recalling 

that we only have prices for goods that are bought and sold). The 

argument that this condition holds is a staple of basic economics 

textbooks and involves a proof by contradiction. If this condition 

did not hold, the consumer could buy more of the good that 

provides her with more marginal utility per dollar spent and less 

of that which provides less, and achieve higher overall welfare 

for the same monetary expenditure, contradicting the assumption 

that her choices are optimal.

So, 

... A B A N A dU MU = dA+ p p dB + + p p dN (1.5)

or

... A A A B N p dU MU = + p dA p dB + + p dN. (1.6)

T

o show that changes in accounting totals are indicative of 

changes in well-being, we consider how well-being can 

be expressed in terms of dollars-and-cents figures. First, 

consider an individual who buys apples and bananas and carrots 

and a host of other goods numerous enough to go through the 

alphabet many times over. Her utility, as a function of the number 

of apples, bananas, carrots, and so on, that she enjoys could be 

expressed as

 U x x x A B N ( ) , ,..., , (1.1)

where N is now not the 14th letter of the alphabet, but rather, the 

very, very large number of different goods and services we enjoy. 

This expression can be decomposed to write changes in utility 

from one year to the next as follows:

... A B N dU = + MU dA MU dB + + MU dN . (1.2)1

In this expression, dU is the difference between the overall level 

of utility a consumer experienced this year compared to last year, 

i.e., her change in well-being. It can be decomposed into MUA, 

the marginal utility she gets from consuming an extra apple, times 

dA, the number of apples she consumes this year over and above 

the number she consumed last year, plus the same calculation for 

bananas, and so on through all the things she consumes.

While we could measure changes in the quantities of things a 

person consumes between one year and the next, we cannot 

measure the extra utility she realizes from consuming a bit more 

of something (the MU’s). We can, though, do a simple trick and 

1

 In mathematical jargon, expression is a first-order approximation to a 

change in utility. A second (or still higher)-order approximation might be more 

accurate, especially when the period-on-period changes in quantities are larger, 

as would likely be the case when the “periods” under consideration are longer. 

A more accurate approximation would involve the definition of many more 

terms, however, and would require empirical estimates of own- and cross-price 

elasticities of demand, which would be a daunting exercise.
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 9

The right-hand side of expression 1.5 consists entirely of 

things we can observe: the prices of goods and changes in their 

quantities. To interpret the left-hand side, we need to apply a 

corollary to the result from consumer theory we just considered. 

Recall expression, which characterizes the conditions under 

which a consumer is maximizing her utility given the constraint 

that she cannot spend more money than her income allows. We 

can express it equivalently as

... A B C N

A B C N

MU MU MU MU

p p p p = = = =

.

(1.7)

The intuition for this condition is that if the consumer got more 

additional utility for the last dollar she spent on apples than she 

did for the last dollar she spent on bananas, she could reallocate 

her expenditures from bananas to apples and be better off overall. 

So, if her choices are optimal, she must get the same marginal 

utility per dollar spent on all goods. That means all the ratios in 

expression measure the same thing: the additional utility realized 

from an additional dollar of expenditure. The ratios are all equal 

to the marginal utility of income: the increase in welfare due to 

an additional dollar of income.

If we denote the marginal utility of income as MU

y

, we now can 

write expression (1.6) as

... y A B N dU MU = + p dA p dB + + p dN . (1.8)

The left-hand side of this equation is now the dollar value of the 

change in utility, since units of utility (the dU) are divided by 

utility per dollar spent (MU

y

).

To recap: we asked how we might represent a change in an 

individual’s welfare from one period to the next. We started by 

decomposing it into changes in how much of each thing she 

consumes, multiplied by the price of each thing. We then rewrote 

this as the dollar value of the change in welfare, or change in 

utility, showing that it is the sum of the prices of goods multiplied 

by the changes in their quantities, which is just the change in the 

accounting total. 

Appendix 1.1 cont.

Figure 2.1—Relationship between forests and society that give rise to cultural ecosystem services and perceived 

benefits provided by forest lands.

Perceived Benefits

(e.g., meaningful symbols of patriotism)

Forest Components

(e.g., wildlife habitat)

Society’s Values

(e.g., patriotism)

Final Cultural Services

(e.g., conservation of wildlife)

Customs and 

Beliefs

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 11

WHAT ARE CULTURAL SERVICES?

How we define “culture” and societal well-being related 

to culture depends heavily on who is looking at it, but 

culture can be generally described as “the customs and 

beliefs of a particular group of people that are used to express 

their collectively held values” (Soulbury Commission 2012). 

In the context of forests, culturally derived norms, beliefs, 

and values help drive preferences for forested landscapes and 

forest-based benefits such as diversity and identity, justice, 

education, freedom, and spirituality (Farber and others 2002, 

Fisher and others 2009, Kellert 1996). Environmental policies 

and responsible forest management can enhance how forests 

help give rise to and support cultural ecosystem service values. 

Likewise, human components (e.g., customs and beliefs) 

determine how forests are to be culturally valued (fig. 2.1). This 

is somewhat different when compared to other types of services 

(e.g., regulating services) because human culture plays a central 

role in determining how people interact with forests and perceive 

their associated benefits. In other words, human culture gives 

important meanings to forests that are recognized as valuable, but 

the forests themselves do not inherently possess these meanings. 

Table 2.1 offers a topology of cultural ecosystem services and 

associated ecosystem and human components. However, our 

understanding of the many factors that give rise to cultural 

ecosystem services is still a matter of ongoing investigation.

There is good reason for investigating the cultural ecosystem 

service values associated with forests: they are critical to our 

understanding of the value of forest land and the benefits of 

forest conservation. The U.S. South is expected to lose 30-43 

million forest acres to urbanization between 1997 and 2060 

(Wear and Greis 2002), and structural changes in southeastern 

ecosystems are expected to impact the provision of a wide 

range of cultural ecosystem service benefits (Bowker and others 

2013). Concurrently, social trends also suggest that youth are 

spending less time outdoors compared to previous generations 

(Louv 2008). This means that the customs and beliefs held by 

future generations and how future generations value forests will 

likely be different compared to previous generations. To help 

maintain the forest estate, we may need to actively cultivate 

cultural ecosystem service values through outreach programs 

that encourage different population groups (i.e., younger and 

non-white populations) to take up new recreational activities 

(Poudyal and others 2008). Providing tangible experiences can 

Chapter 2

Forest Ecosystem Services:

Cultural Values

Melissa M. Kreye, Damian C. Adams, Ramesh Ghimire, 

Wayde Morse, Taylor Stein, J.M. Bowker
Table 2.1—Typology of the components that give rise to cultural 

ecosystem services 

Components 

intrinsic to 

visitors/users

Components 

intrinsic 

to the site

Potential 

benefits

Cultural 

ecosystem 

services

Social capital

Skills

Knowledge

Values

Beliefs

Historic features

Biodiversity

Wildlife

Management

Structure 

Stories

Practices

Artworks

Health and well-being

Social contacts

Personal pride

Education

Inspiration

Spiritual well-being

Cultural identity

Cultural heritage

Spiritual services

Inspirational services

Aesthetic services

Recreation/Tourism

Sources: de Groot and others (2005); Tabbush (2010).

12 Chapter 2. Forest Ecosystem Services: Cultural Values

help individuals gain a sense of place and an appreciation of the 

services provided by forests. Those who gain a sense of place are 

also more likely to perceive that they have attained the benefits 

they desire and will want to visit forests again in the future (Kil 

and others 2012).

While the importance of cultural ecosystem services has been 

recognized within land management and policy decisions, many 

services are not yet adequately defined, quantified, or integrated 

within the ecosystem services framework (Daniel and others 

2012). This is largely because attempts to quantify these values 

require: 1) an understanding of how ecosystem components and 

associated artifacts (e.g., historic sites) interact with important 

human components (e.g., customs, beliefs), and 2) the suitability 

of the quantitative and valuation methods used to measure 

these interactions (de Groot and others 2005). Experts in most 

social science disciplines, such as anthropology, sociology, 

and psychology, are trained to address the first requirement, 

and economists are involved to address the second component. 

Notably, the valuation approaches used by economists tend to 

offer incomplete and lower bound estimates of ecosystem service 

values. Moreover, economists tend to use market data that is 

readily available but poorly suited to the task, particularly when 

public goods and externalities are involved (Costanza and others 

1997). There is a need for decisionmakers to better understand 

the methods available to estimate non-market values for 

ecosystem services and the challenges associated with using these 

methods to understand tradeoffs in cultural ecosystem services.

The goal of this chapter is to provide an overview of how 

valuation methods can be used and applied within a cultural 

ecosystem services context. The first part will focus on different 

types of values (use and non-use values) and the ways cultural 

ecosystem services may be integrated within the ecosystem 

services framework. Second, we will examine the policy context 

and purpose for producing economic estimates of ecosystem 

services value. Third is a non-technical description of important 

theoretical frameworks and challenges associated with economic 

estimation efforts. Finally, we will provide readers with a nontechnical description of commonly used non-market valuation 

methods and benefit transfer and will discuss these approaches 

within a cultural ecosystem services context. Consistent with the 

theme of this book, we will focus on the Southeastern United 

States; however, the overall concept of cultural ecosystems 

services, and the methods used to identify and measure the 

economic value of these services, are applicable well beyond 

this region.

CONNECTING CULTURAL ECOSYSTEM 

SERVICES WITH THE ECOSYSTEM 

SERVICES VALUATION FRAMEWORK

Cultural Ecosystem Services 

and Use Values

The cultural aspects of a society are often expressed through the 

activities, practices, skills, and events that occur in the forest, 

or that involve artifacts that originated from the forest (Tabbush 

2010). These activities may involve the consumptive use of 

forests (e.g., mushroom picking) as well as non-consumptive 

uses (e.g., hiking). To help readers understand use values in 

the context of cultural ecosystem services, this section will 

provide an in-depth discussion about recreational and aesthetic 

experiences, also known as amenity services (de Groot and 

others 2005). Since amenity services are often associated with 

public lands, the last part of this section will describe some of 

the cultural ecosystem services also associated with private 

forest lands.

The benefits of engaging in outdoor recreation activities on 

forest lands have long been important to people in the southeast 

region of the United States (Ownby 2014). Today, millions of 

people participate in non-consumptive recreational activities such 

as walking, hiking, camping, birdwatching, wildlife viewing, 
Intermediate Components/Services

Motivation and 

Preference Activity

Desired Experience: 

aesthetics, spirituality, 

physical health

Final Service:

Managerial Setting Social Setting

water body, fish, visual scenery

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 13

and other such pursuits in forests every year (Cordell 2008). 

Southeastern forests are also habitat for many game animals 

and fish sought by consumptive recreationists, such as hunters 

and anglers, and serve as the source of rivers and streams used 

for recreational activities. It is unsurprising that the value 

of recreation in the southeast region has been the subject of 

numerous economic studies (see Appendix 2.1). The number of 

visitors to southeastern forests is expected to rise over time along 

with demand for different recreational activities (Bowker and 

others 2013).

Several authors have suggested that for accounting purposes, 

recreation (e.g., angling) should be thought of as a benefit that 

arises from the joint use of other ecosystem services (e.g., 

clean water) and conventional goods and services (e.g., fishing 

equipment) (Boyd and Banzhaf 2007, Fisher and others 2009). 

There is a long history of research on the components of and 

benefits from a recreation experience (Driver and others 1991, 

Manfredo and Driver 1996, Manfredo and others 1983, Manning 

1999). In the recreation literature, the recreation experience 

is most often understood from the psychological perspective. 

Consequently, individuals who participate in outdoor recreation 

do so with the expectation that the recreation activity, done in a 

particular setting, will result in certain beneficial psychological 

and physiological outcomes (Manfredo and Driver 1996, 

Stein and others 2003). This is commonly referred to as the 

experiential or behavioral model of recreation where the 

outcomes of recreation rather than the activities themselves are 

deemed to be the benefits (Driver and others 1991). Interestingly, 

the majority of the benefits categorized as cultural ecosystem 

services by most authors (MEA 2003, DeGroot and others 2005) 

are tied to outdoor recreation (see table 2.2 in chapter 2 Moore 

and Driver 2005).

The key aspects of setting in the recreation experience model 

are defined as the physical setting (e.g., level of remoteness), the 

social setting (e.g., level of crowding), and managerial setting 

(e.g., level of management restrictions and facilities) (Driver and 

others 1987). Settings are expected to influence the activities 

that can be performed in any given location and the benefits 

that recreationists might expect to obtain (Pierskalla and others 

2004). We have taken the outdoor recreation experience model 

and ungrouped the three setting attributes so that we can begin 

to elaborate on the physical setting (Morse 2010) (fig. 2.2). 

Presented this way, the biophysical setting is considered to be but 

one aspect of the recreation setting. Furthermore, the physical 

setting is more than simply a level of remoteness, but also a 

combination of geophysical, biological, and vegetative attributes 

that are spatially explicit (Morse and others 2009). It is this 

ecological portion of the physical recreation setting that is the 

final service (the forest, the water body, and the fish) recognized 

by Boyd and Banzhaf (2007), or the result of indirect and final 

structural and functional services of Fisher and others (2009).

By conceptualizing the recreation experience model in 

this way, we can identify clearly the contribution of the 

ecosystem as a critical aspect of the recreation setting. It also 

demonstrates that the ecosystem is but one of the attributes 

that combine to form a recreation opportunity setting, or the 

amenity service. Using recreation theory, we can also identify 

the many benefits (psychological, physiological, etc.) that 

are accrued from recreation experiences. Finally, the model 

clarifies the subjectivity of an experience (essential for cultural 

ecosystem services) that is dependent on how different 

individuals’ motivations and expectations regarding their 

experience and desired outcomes can influence their value of the 

recreation experience.

Figure 2.2—Integrating recreation theory with ecosystem services.
Table 2.2—A topology of non-use values

Option value Bequest value Existence value Altruistic value

The value of maintaining 

an asset or resource to 

have the possibility that it 

may someday be used.

The value of maintaining 

or preserving an asset or 

resource so that it is available 

for future generations.

The benefit people receive 

from knowing that a particular 

environmental resource, 

organism or thing exists.

The value of maintaining an 

asset or resource that is not 

used by the individual, so that 

others may make use of it.

Source: Dietz (2015).

14 Chapter 2. Forest Ecosystem Services: Cultural Values

Public lands are often recognized as being central to the provision 

of cultural and amenity ecosystem services; however, private 

forest lands also play an important but less well understood 

role. In the southeastern region of the United States, the value of 

recreation on private lands is most often associated with lease and 

fee hunting (Mozumder and others 2007). Willingness to pay for 

hunting leases in Alabama was found to be steadily increasing 

and was last valued at $1.29 per acre per hunter (Zhang and 

others 2004). Willingness to pay for fall and spring turkey hunting 

permits in Mississippi has been valued at $11.00 and $36.25, 

respectively (Brunke and others 2006). The value of the hunting 

leases can depend on a number of factors such as alternative 

hunting access options, hunter perception of crowding on public 

lands, availability of game species on leased lands, and duration 

of the lease agreement (Munn and others 2011).

Even when the public is not able to access private lands, certain 

benefits may still be provided in the form of spillover effects 

(Blitzer and others 2012). Private lands offer green landscapes 

and positive aesthetic experiences for neighbors and others in the 

community (Luttik 2000). Moore and others (2011) estimated 

total aesthetic value of Georgia’s private forests to the residents 

of Georgia at $11.2 billion per year. Haefele and others (1991) 

found people were willing to pay $100 per year and $21 per year, 

respectively, for protecting high-elevation spruce-fir forests in the 

southern Appalachian Mountains from exotic insect infestations 

and air pollution damages. With continued forest fragmentation 

and a loss of forest cover, demand for green spaces can be 

expected to increase in the Southeastern United States (Griffith 

and others 2003).

Similar to aesthetic benefits, how land is managed can serve as 

salient symbols on the landscape, expressing important cultural 

priorities and values (Allison 1996, Sorice and others 2012). 

For example, planting even-aged pine stands can be seen as an 

homage to the South’s longstanding history in producing forest 

products (Zhang and Polyakov 2010), or more simply the virtue 

of productivity. Likewise, prescribed burning can help express 

the value of living in harmony with nature or the importance of 

maintaining certain management traditions (Putz 2003). The act 

of owning forest land also helps people express important ideals 

about identity, individualism, a sense of duty (toward nature or 

society) and skepticism about State control (Brook and others 

2003, Burton 2004). Maintaining the ability for self-determination 

has important psychological benefits and can enhance perceptions 

of personal well-being (Ryan and Deci 2000). Those who help 

shape the landscape may also have a greater sense of place and 

assign a higher value to the cultural benefits associated with 

private lands (Kil and others 2012).

Due to changing cultural values and perceptions, there is an 

increasing tendency to create landscapes with high amenity 

values (for aesthetic and recreational use, for example) at 

the expense of traditional landscapes with high cultural and 

spiritual ecosystem service values, and to disregard those with 

traditional knowledge about forest management (de Groot and 

others 2005). When changes are made to the landscape, either 

through market forces or government interventions, this can be 

perceived as a threat to certain cultural ecosystem service values 

and the psychological well-being of forest owners (Kreye and 

others 2016). Government interventions that seek to improve 

public welfare through the management of private forest lands 

should also recognize the cultural ecosystem service values and 

traditional knowledge associated with maintaining private lands. 

Policy efforts that recognize the unique benefits associated with 

maintaining private forest lands can help improve the quality 

of human life within rural communities while simultaneously 

achieving forest conservation and sustainable use goals (de Groot 

and others 2005).

Cultural Ecosystem Services 

and Non-use Values

Some of the cultural ecosystem services provided by forests 

do not have to be used for the benefits to be recognized or 

considered valuable. Non-use (or passive use) values are ideals 

that serve as a guiding principle in how people make decisions 

about the environment and are an expression of important cultural 

values (Dietz 2015). Understanding people’s attitudes (positive 

or negative) toward different types of non-use values can 

improve our understanding of public priorities for less tangible 

cultural ecosystem services. Table 2.2 provides a list of the 

non-use values most often recognized in the research literature 

(Dietz 2015).

Bequest value, or beliefs about the importance of passing 

ecosystems on to future generations in good condition, relates to 

the heritage services provided by conserved or restored forests 

(Broadbent and others 2015). What separates bequest value from 

a general concern about environmental integrity or altruistic 
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 15

value is the additional desire that a specific group (i.e., future 

generations) be given the opportunity to benefit from forests 

(Walsh and others 1984). In the southeastern United States, 

longleaf pine (Pinus palustris) ecosystems, and associated 

wildlife such as the gopher tortoise (Gopherus polyphemus), 

are considered by many to be part of the cultural heritage of 

the region. However, less than 6 percent of the original extent 

of longleaf pine ecosystems remains in the South (Guldin and 

others 2016). Participants in advocacy organizations, such as the 

Longleaf Alliance, recognize the bequest value associated with 

these ecosystems and seek to promote longleaf pine restoration 

on public and private lands.

Society’s beliefs about the treatment of non-humans and 

ecosystems are an important part of the spiritual and cultural 

identity ecosystem services provided by forests (Davidson 

2013, de Groot and others 2005). Some people psychologically 

benefit from knowing that a certain organism exists, because 

the organism is an important symbol within their community 

or personal life (de Groot and others 2005). Some also believe 

we have an ethical responsibility as a society to protect the 

integrity of ecosystems (Pienaar and others 2013). To illustrate, 

households in South Carolina were found to have a willingness to 

pay of $10.64 annually for the benefits associated with protecting 

the endangered red-cockaded woodpecker (Leuconotopicus 

borealis) (Loomis and White 1996). Research has also found 

that people in the United States, including the Southeast, tend to 

have biocentric attitudes toward forests (i.e., a concern about the 

well-being of all organisms) (Kreye and others 2014, Pienaar and 

others 2013).

The beliefs people hold about how ecosystem services should be 

distributed to society (e.g., government interventions, markets) 

can also contribute to the cultural identity and heritage ecosystem 

services associated with forests in the Southeastern United 

States (Johnson and Duke 2007, Kreye and others 2016, Poudyal 

and others 2015). Beliefs about government control over the 

distribution of services can impact the perceived legitimacy and 

public acceptance of environmental policy decisions (Petersmann 

2004) as well as estimates of willingness to pay for ecosystem 

service provision used in decisionmaking (Kreye and others 

2014, 2016b). Most government approaches to ecosystem service 

distribution involve the permanent modification of private 

property rights (e.g., land acquisition, conservation easements). 

Government entities may also use laws and regulations to oversee 

the fair distribution of cultural benefits, such as access to outdoor 

recreation and other resource amenities by minority groups 

(Floyd and Johnson 2002, Johnson and others 1998). However, 

for some goods and services, government involvement may be 

considered cumbersome or less effective compared to free market 

approaches. Government involvement in service provision may 

also involve certain tradeoffs, such as the psychological benefit of 

being assured that resources will be protected into the future (e.g., 

option value) but the loss of the psychological benefits associated 

with maintaining private lands (e.g., self-determination). Recent 

research has found public values for forest-based services in 

Florida and Georgia are indeed influenced by the policy processes 

(e.g., conservation easements) and the institutions (e.g., State 

agency) used to bring about the services (Kreye and others 2016, 

Poudyal and others 2015). While a broader body of social science 

research has recognized the relationship between social trust and 

ecosystem management, this relationship is rarely incorporated 

into valuation efforts and is not well understood as a contributor 

to cultural ecosystem services (Kreye and others 2014).

Why Assess the Economic Value 

of Cultural Ecosystem Services?

Given the difficulties in defining and quantifying certain 

cultural ecosystem services, one may question the rationale 

behind attempts to estimate economic values for these services. 

Some advocate that multi-criterion and deliberative evaluation 

procedures be used instead of strict economic strategies to 

clarify tradeoffs and synergies involving cultural ecosystem 

services (Daniel and others 2012). Moreover, some argue that 

traditional market approaches are inappropriate for identifying 

and measuring cultural ecosystem services (Kumar and Kumar 

2008, Peterson and others 2009). Still, we see evidence every 

day of people expressing important cultural values through 

consumer and market behaviors (e.g., visiting National 

Parks, buying organic food), but this can only occur when 

markets exist that allow people to express these values. The 

metric that can best express changes in human well-being for 

decisionmaking purposes often depends on the policy context and 

stakeholder needs.

In most policy contexts, the need to obtain economic values 

can arise when (1) there is a need to justify management costs 

for current levels of service provision, or (2) when a common 

metric (i.e., dollar) is needed to assess tradeoffs in welfare across 

dissimilar services (e.g., clean water benefits versus agricultural 

goods). In the first case, a single value estimate may be all that 

is needed for use in a cost-benefit analysis. In the second case, 

each policy alternative may need to account for other associated 

factors such as the number of people impacted by a change in 

service provision and the distribution of benefits over time.

Economic values are also central to helping advance marketbased approaches (i.e., payments for ecosystem services) to 

ecosystem service provision. In the past, the valuation of cultural 

ecosystem services, primarily recreation, has been limited to 

public lands. Increased population growth and demand for 

forest-related benefits in the Southeastern United States has 

now compelled decisionmakers to also understand the full value 

of private lands. Traditionally, the value of private forest lands 

has been associated with agricultural productivity (i.e., timber) 

and landowners receive little or no external reward for securing 

services that help provide cultural benefits. As such, ecosystem 

services with either off-site or non-use values are likely to be 

undersupplied by private forest landowners because it is difficult 

for them to capture those values. Helping landowners diversify 

income by offering a variety of nature-based activities that 
16 Chapter 2. Forest Ecosystem Services: Cultural Values

capitalize on cultural ecosystem services could play an important 

role in encouraging private landowners to maintain recreational 

benefits and culturally valuable ecosystem services. Key to 

this approach is understanding public willingness to pay (i.e., 

demand) for cultural ecosystem service provision and landowner 

willingness to accept compensation (i.e., price) for providing 

cultural ecosystem services.

Economic Concepts and 

Theoretical Assumptions

Economic theory attempts to describe the values people hold 

for different goods and services under different contexts (e.g., 

a change in quality, the availability of substitutes) and when 

choices are constrained by cost (e.g., income). Because of these 

constraints, monetary values do not represent the inherent value 

of an ecosystem, only its value in relationship to other levels of 

provision or other goods (Kallis and others 2013). It is assumed 

that the benefits derived from cultural ecosystem services provide 

the individual with some utility or measure of satisfaction. 

Random utility theory states that the level of utility associated 

with a good or service will vary randomly across a population 

(Train 1998). It is also assumed that measured estimates of 

willingness to pay (WTP) are an appropriate representation of 

individual utility. Therefore, the most commonly accepted and 

applied metrics for valuing cultural services are individuals’ 

maximum WTP in dollars for ecosystem service provision. 

In some cases, economists may also choose to measure the 

minimum willingness to accept (WTA) to forego the provision of 

a good or service (Brown 2007).

The difference between what a consumer is willing to pay and 

what they actually paid for a good (i.e., its price) is known as 

consumer surplus. In cases where market prices do not exist, but 

goods or services have recognized value, individual consumer 

demand is represented by WTP. When consumer surplus is 

aggregated across a population, an estimate of the welfare gain to 

consumers of that good or service is obtained. The analogue for 

producers is known as producer surplus and is typically thought 

of as profit—the difference between the price and the cost of 

providing the service (i.e., supply curve). Producer surplus can 

help describe how producer welfare can be improved through 

the development of missing markets. Market-based solutions 

to welfare—or ecosystem service—distribution are considered 

efficient when supply equals demand. Change in consumer and 

producer surplus is the measurement that economists provide to 

policymakers to help describe how public welfare is impacted by 

changes in ecosystem service provision (Brown 2007).

To facilitate a successful market transaction, it is important that 

goods and services embody certain characteristics (Brown 2007). 

One important characteristic is the ability to be rivalrous, or when 

the good is consumed by one person it prevents simultaneous 

consumption of the good by others (e.g., timber). Another 

characteristic is the ability to exclude or prevent people who 

have not paid for a good or service from having access to it 

(e.g., fee-based access to a State park). Goods and services that 

have a direct use value and are rival and/or excludable tend to be 

already traded in a market setting. However, use values are only 

part of the total economic value (TEV) associated with a good or 

service. Non-use values are also considered important because of 

how these values relate to important beliefs and ideologies that 

help drive consumer behaviors and preferences for less tangible 

cultural ecosystem services. Non-use values may also constitute 

an important part of the total value associated with certain forests, 

such as wilderness preserves (Loomis and Richardson 2000, 

Walsh and Loomis 1989).

When attempting to link land management decisions with 

certain cultural ecosystem service values, it is useful to employ 

Lanscaster’s theory of values, which postulates that the utility we 

expect from a good or service is dependent on the characteristics, 

or bundle of attributes, that make up the good or service 

(Lancaster 1966). This is to say, consumers decide which services 

(or goods) are preferable by examining the attributes or features 

that make up the service, along with the price of the service 

and the income they have available to spend on it. Advanced 

valuation approaches, such as an attribute-based choice 

experiment and hedonic methods, are often structured around 

this theory. The advantage of this approach is that both attributes 

on the landscape—created through management actions—and 

attributes describing cultural components can be linked with 

changes in benefits or utility. Attributes on the landscape may 

include forest plant diversity and structure, trails and historic 

sites, and spatial relationships among important features (e.g., 

distance between historic sites). Attributes that describe important 

cultural components may include the customs of service users 

(e.g., level of hiking activity) and/or beliefs that people hold 

about service outcomes (e.g., health benefits, importance of 

passing forests to future generations). Unfortunately, attributes 

that describe the human components of cultural services are less 

often examined or understood in a valuation context, more of 

which will be discussed later on in the chapter.

The theoretical frameworks and assumptions presented above 

also come with some important limitations. One limitation is that 

WTP estimates are a meaningful proxy of utility only for those 

who have a sufficient amount of disposable income. This means 

that valuation efforts may not be appropriate for addressing 

environmental justice concerns in poor communities. Another 

limitation is the occurrence of lexicographic preferences or 

when a person is unwilling to forego a good in exchange for any 

other amount of another good based on ethical reasons. There 

is also the assumption that people, as consumers, are primarily 

interested in maximizing their utility and make decisions outside 

of social contexts. In reality, some people are willing to be losers 

at times (e.g., pay higher taxes) if they believe that this will help 

society or their community as a whole succeed. Similarly, some 

landowners may be motivated by personal ethics (e.g., being a 

good land steward) to assume the costs of conservation and are 

unwilling to accept financial incentives for providing certain 

cultural ecosystem services.
2

Number of visits per year (quantity)

Demand curve

Cost of travel (price)

$25.00

$5.00

5

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 17

The theoretical issues described above illustrate the difficulty 

of understanding human behaviors toward the environment 

using a strictly economic approach. Still, valuation methods are 

continually being improved and offer a useful way of comparing 

tradeoffs in utility associated with ecosystem service provision. 

For example, non-market valuation approaches have been the 

subject of investigation in 130 countries for over 50 years and 

have resulted in over 7,500 published research papers (Carson 

2012). It is our recommendation that those who plan to employ 

valuation methods consider how the associated assumptions may 

impact their efforts to produce useable estimates of economic 

value within a given policy situation. In some policy contexts, 

non-monetary metrics or a mixed methods approach (i.e., using 

both quantitative and qualitative methods) can instead be used to 

understand policy impacts and inform decisionmaking.

VALUATION METHODOLOGIES

This section of the chapter provides a general description of 

the non-market valuation methods currently used to generate 

estimates of economic value. Revealed preference methods, 

such as travel cost and hedonic pricing, rely on data from actual 

spending choices or behaviors to infer underlying relative utilities 

for non-market goods and services. Stated preference methods 

use hypothetical market contexts to quantify non-market values 

(e.g., by asking respondents to state their maximum WTP or 

WTA) for a non-market good or service (e.g., using a survey 

approach). We also provide a comparison of the outcomes of an 

economic impact analysis with non-market valuation methods so 

that readers can better distinguish between the approaches.

Limitations of an Economic 

Impact Analysis

Economic impact analysis is a quantitative approach often used 

by government agencies to justify management or program 

costs. This approach focuses on policy driven changes on the 

landscape which result in changes in business revenue, business 

profits, personal wages, and/or jobs. For example, recreation on 

Federal lands contributes about $13.6 billion to the Nation’s gross 

domestic product each year and supports approximately 205,000 

jobs, many of which are located in rural areas (Weldon 2014). 

The total economic impact of hunting activities, wildlife viewing, 

and recreation in the southern Appalachian region was estimated 

at $594 million, $407 million, and $6 billion, respectively, 

in 1996 (Barnhill 1999). It is also reported that expenditures 

made on wildlife related recreations (e.g., fishing, hunting, and 

wildlife-watching) generated 0.7 percent of regional employment 

and gross output in the Southeastern United States (Munn and 

others 2010).

Clearly, public demand for cultural ecosystem service provision 

has an important economic impact on surrounding communities. 

However, these types of economic metrics (i.e., jobs created, 

revenue earned) do not offer a suitable description of consumer or 

producer surplus necessary for describing changes in utility for a 

given service. Moreover, economic impact estimates are based on 

existing market values for a limited number of services and fail to 

describe the value associated with related non-market goods and 

services. To use economic estimates within an ecosystem services 

framework, at a minimum the estimates need to be comparable 

across services and describe consumer surplus for both market 

and non-market values.

Revealed Preference Methods 

Travel cost methods—Travel cost methods are primarily used to 

estimate the value of recreation offered at a specific site (e.g., a 

State park). Economists assume that the economic cost necessary 

to reach a recreational site, such as travel expenses and associated 

user fees (e.g., entrance fees), is an estimate of user WTP for 

recreation. In other words, it is assumed that people perceive 

and respond to changes in travel costs and amenity qualities the 

same way that they would respond to changes in market price 

and qualities of purchased goods. The values generated using this 

method can allow decisionmakers to compare estimated benefits 

with the costs of maintaining the site for visitors (Parsons 2003).

A simple zonal travel cost method can be applied by collecting 

information from visitors about the number of visits and their 

travel distance to the site. Because travel costs tend to increase 

with distance, researchers are able to construct a demand curve 

by calculating the number of visits purchased at different prices 

or travel costs (fig. 2.3). Consumer surplus for users is then 

estimated by quantifying the area above the price line and below 

the demand curve.

Figure 2.3—Example of a demand curve based on the cost of travel 

(purchase price) and number of visits to the site (quantity).
18 Chapter 2. Forest Ecosystem Services: Cultural Values

The merits of the travel cost method are that it is often relatively 

inexpensive to apply and uncontroversial because it is based 

on standard economic techniques for measuring value. The 

challenge with using the simple zonal approach is accurately 

estimating the travel costs of visitors. Transportation costs often 

include gas prices and—if traveling a long distance—possibly 

food and hotel accommodations. The value of the visitor’s time 

is sometimes also considered by including estimates of wages 

lost while traveling and visiting the site. These average costs are 

included in the travel cost calculation as average distances, gas 

prices, and proportion of wage values (e.g., Amoako-Tuffour and 

Martinez-Espiñeira 2012). A potential source of error in the value 

estimates occurs when cost information is not collected directly 

from the visitor, but instead is approximated by the researcher. 

Error can also be associated with the assumption that the visitor’s 

sole purpose for the trip was to recreate at that site. Similarly, the 

availability of substitutes and their effect on preferences are also 

not usually considered (Randall 1994).

By focusing only on costs, this simple valuation method tends 

to provide an incomplete understanding of the associated 

benefits. Many natural areas offer multiple activities (hiking and 

boating), which a given visitor, based on their customs, may or 

may not use. Linking travel costs with specific psychological 

or physiological benefits is also difficult unless additional data 

are collected to better understand how users perceive their 

experiences. It is also important to consider that the simple travel 

cost approach only provides values associated with current benefit 

levels, not changes in benefits levels, which would be more useful 

for planning. Finally, travel costs can only examine the use values 

associated with the park and not the non-use values. In short, 

simple travel cost estimates provide an incomplete understanding 

of consumer surplus and potential tradeoffs in social welfare 

associated with different management outcomes.

The simple zonal travel cost method could be improved by 

using an individual travel cost or hybrid travel cost/contingent 

valuation approach with a more detailed survey of visitors’ 

characteristics and expected benefits (Armbrecht 2014, Cameron 

1992, Randall 1994). Survey questions can pertain not only to 

individual travel costs but the purpose of the visit (e.g., hiking 

and/or fishing) and how changes in benefit levels or costs may 

impact visitor behaviors. For example, a recent study used the 

individual travel cost method to compare the value of non-trail 

backpacking activity with trail backpacking activity at Allegheny 

National Forest (Cho and others 2014). In another study, a series 

of questions describing different activities and benefit levels was 

used to cluster visitors into user groups, such as “backcountry 

enthusiasts,” “do it all adventurists,” “windshield tourists,” and 

a “creature comfort” group (Benson and others 2014). In these 

cases, the data collected not only provided park managers with 

estimates of economic value, but also a better understanding 

of how management funds should be distributed to maintain 

certain benefits.

Even with advanced sampling and analysis methods, the travel 

cost approach may not always be appropriate for estimating the 

value of cultural ecosystem services in all policy contexts. When 

the focus is on private or local forests, the travel cost approach 

to valuation is more likely to result in the underestimation of 

consumer surplus. To build a demand function, the resource 

needs to be far enough away to have an effect on the income of 

visitors, which may not be the case for local visitors. Also, those 

who live nearby may place a relatively higher cultural ecosystem 

service value on local resources due to place attachment (Kil 

and others 2012). This may be a particular concern in the rural 

Southeast where there are fewer acres of public lands per capita, 

compared to the West, and recreational activity on private lands is 

poorly or infrequently documented.

Hedonic pricing—The hedonic pricing method takes advantage 

of the fact that sometimes non-market values for cultural benefits 

such as aesthetics, recreation, and other environmental amenities 

(e.g., clean air and water) are embodied in the price of other 

goods and services and can therefore be derived (Dietz 2016). 

This method is most effective when there has been a distinct 

change in environmental quality that has impacted the quality 

or satisfaction associated with a related good. For example, 

it is assumed that home buyers select houses based on their 

preferences for different attributes of the house including location 

(e.g., distance to parks and schools), features (e.g., number of 

bedrooms/bathrooms), and surrounding environment (e.g., air and 

water quality). After controlling for variation in price, location, 

and house features, it is assumed that the remaining difference in 

home prices is related to a difference in environmental quality. 

The implicit price estimates are then used to estimate inverse 

demand functions or marginal WTP.

How hedonic values are used in a policy context depends on 

how the associated environmental benefits are perceived. Values 

associated with green space and aesthetic amenities can be used 

to justify changes to zoning laws and other regulations that help 

control urban sprawl and land use change (Gibbons and others 

2014). Values associated with increases in pollution or a decline 

in health benefits can be used to justify costs associated with 

remediation or health care provision. Hedonic models have long 

been used by the Environmental Protection Agency to derive 

the value of living in neighborhoods with high or low levels of 

air quality (Smith and Huang 1995). A few studies have also 

estimated the economic value of trees or forests on property price 

in the Southeastern United States (table 2.3). Using the hedonic 

property price models, Anderson and Cordell (1988) analyzed 

the economic value of urban trees and found certain trees were 

associated with a 3.5-4.5 percent increase in homes sales price. 

Likewise, Mansfield and others (2005) found proximity to forest 

types and proportion of parcel that was forested increased home 

sales prices in Research Triangle, North Carolina.

Hedonic modeling uses regression analysis to determine 

how changes in the attributes of the good, the users, and the 

environment (i.e., independent variables) are correlated with 
Table 2.3—Economic value of forests in the Southeast region

Study Measurement used Location Method Results

Anderson and 

Cordell (1988)

Number of large, small, pine, 

and hardwood trees in front 

yards of residential single 

family properties

Athens, GA Hedonic 

property price

Trees were found to be 

associated with a 3.5%–4.5% 

increase in homes sales price

Mansfield and 

others (2005)

Percentage of residential 

single family parcel that was 

forested, acres of forest on a 

parcel, percentage of forested 

land within 400-m, 800-m, 

and 1,600-m buffers around 

parcel, distances to private 

and institutional forests

Research 

Triangle NC

Hedonic 

property price

Proximity to both forest types 

and proportion of parcel that was 

forested increased home sales 

prices; increasing forest cover 

on parcel by 10% adds less than 

$800 to home sales prices while 

adjacency to private forests add 

more than $8000

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 19

changes in price. Market data for housing is often secured 

from the property appraiser’s or tax offices. Measured changes 

in environmental quality (e.g., water pH, turbidity) can be 

secured from the State or Federal agencies responsible for 

monitoring those changes. Census data is often used to describe 

relevant changes in social components such as demographic 

characteristics, annual household income, and employment. 

Sometimes, it may be necessary to use GIS spatial software to 

map the location of the house relative to the site where the service 

(or disservice) originates (e.g., a nature park or an industrial 

park). Because changes in environment quality and the housing 

market can be masked by other influences on the market, large 

amounts of data often needed for analysis and estimates depend 

heavily on model specification (Lipton and others 1995).

The main strength of the hedonic approach is that, as a revealed 

preference method, the non-market value estimates are 

derived from actual choices and reflect the cultural customs of 

homebuyers. Property markets have been found to be relatively 

efficient in responding to information and property records can be 

reliable in reporting market transactions. Still, outside influences 

like taxes, interest rates, or housing market bubbles can affect 

housing prices, masking the influence of the environmental 

amenities. There are also limitations to the hedonic method in 

regard to informing policy. Researchers can only examine the 

environmental qualities that are directly associated with the good 

(e.g., housing) and apply these values to policy contexts with a 

similar physical setting. For example, the value of wildlife habitat 

provided by trees on a parcel of land in a neighborhood may not 

be comparable to the value associated with habitat located in 

large, unbroken parcels of forest (Willis and Benson 1988).

Hedonic pricing also provides a limited understanding of the 

expected benefits, which is important for characterizing the 

cultural ecosystem service values associated with forests. It is 

assumed that potential homeowners are aware of the surrounding 

environmental conditions and will make their selection based 

on how it will enhance their quality of life or reduce discomfort 

or effort (Dietz 2015). Moreover, hedonic pricing can only 

suggest the presence of certain self-enhancement benefits (e.g., 

self-seeking analysis of costs and benefits) and not the selftranscendent attitudes (e.g., altruistic and biocentric attitudes) 

often associated with non-use values and benefits (e.g., existence 

value) (Dietz 2015). Similar to travel cost methods, hedonic 

pricing can only account for certain use values, and therefore it 

can describe only part of the total economic value of a good or 

service. One way to improve the hedonic approach is to use it in 

combination with stated preference methods. Using a combined 

methods approach, Johnston and others (2001) found that the 

optimal scale and design of population growth management 

policies depended upon many factors, including the distribution 

of benefits and costs among heterogeneous groups.

Revealed preference methods are often preferred by economists 

because the observations included in the analysis are based on 

actual market data. However, to improve our understanding 

of cultural ecosystem service values, there is a need to better 

measure and quantify certain human components (i.e., beliefs and 

perceived benefits) that market behaviors alone cannot describe, 

and relate these measurements to changes in forest management. 

Given the flexibility, stated preference methods may instead 

provide the appropriate tools needed to meet this challenge.

Stated Preference Methods

Stated preference methods estimate non-market values by 

querying individuals on their WTP for improvements (or 

willingness to accept payment for losses) to an environmental 

good or service using choice trials and surveys. These WTP 

estimates can then be used to estimate consumer surplus and 

associated demand curves. These methods include several 

approaches (e.g., contingent valuation, contingent ranking and 

rating, contingent behavior, choice experiments, and paired 

comparisons) that construct hypothetical markets for ecosystem 

services and observe study participant behavior to infer their 

preferences and subsequent economic value.
Table 2.4—Main forms of contingent valuation

Open-ended 

question Iterative bidding Payment card

Dichotomous 

choice/discrete 

choice

Double-bounded 

dichotomous 

choice

Respondents are 

directly asked 

their maximum 

willingness to pay.

Respondents are 

asked whether they 

are willing to pay 

a certain amount 

and then extra or 

reduced increments 

(bids) until their 

maximum WTP is 

reached.

Respondents are 

given a card that 

contains several 

payment bids and 

they choose one.

Known as the 

referenda model, 

respondents are 

asked if they 

support a change 

in environmental 

quality given a 

specific additional 

payment.

Similar to 

dichotomous choice, 

but then depending 

on whether they 

responded, 

respondents are 

asked if they are 

willing to pay a 

slightly higher or 

lower amount.

Source: Morrison and others (1997).

WTP = willingness to pay.

20 Chapter 2. Forest Ecosystem Services: Cultural Values

Given their reliance on practitioner-defined hypothetical market 

contexts, stated preference methods can be applied in virtually 

unlimited ways to inform a diversity of policy decisions (Bennett 

2011). However, an important concern associated with this 

method is that valuation estimates are vulnerable to several 

biases. For example, with hypothetical bias, respondents may 

consider their responses to be less consequential (and therefore 

respond differently) than if they had to actually pay. Response 

bias can occur if the people who answered the survey are not 

representative of the larger population. Strategies for dealing 

with bias concerns have been the subject of ongoing research 

since the early 1990s when it was recommended that stated 

preference methods be used to inform natural resource damage 

assessments in U.S. Federal courts (Arrow and others 1993, 

Carson and others 2003). Since that time, stated preference 

methods have been improved and are shown to provide valid, 

useful, and scientifically defensible value estimates (Haab and 

others 2013). Indeed, for services that lack markets altogether, 

stated preference methods are the only adequate link to the 

economic value and public preferences for these services. 

Stated preference approaches also offer a way to link valuation 

estimates to perceived (versus actual) benefits, which are critical 

for understanding how various groups in society may value 

cultural ecosystem services differently and the role of education 

and knowledge in enhancing perceived benefits.

Since surveys are the primary mode of data collection, survey 

design and associated data analysis are critical considerations for 

appropriately assessing the value of cultural ecosystem services. 

Researchers often use interviews and focus groups to inform 

a more thorough survey and as part of quantitative or mixed 

methods research approach. The data that is collected is then used 

to parameterize a hypothesized utility function and the design 

of the WTP questions. A typical utility function assumes that 

the utility associated with a good or service is impacted by the 

attributes that make up the service, the unique preferences of the 

respondent for that service, and the cost or price of the service. 

Ultimately, the data collection tool should contain opportunities 

to observe respondents’ preferences to descriptions of the 

hypothetical changes to an ecosystem service and associated 

prices. Information on respondent characteristics are later 

integrated into analysis as additional explanatory variables.

When setting up a stated preference study to examine cultural 

ecosystem service values, it is important to determine which 

data types will best deliver the desired information for the given 

policy context (Carson and others 1994). Below we describe 

the two most commonly applied stated preference methods: 

contingent valuation and choice modeling. As described in the 

sections above, these procedures can also be combined with 

revealed preferences methods to meet certain data objectives.

Contingent valuation—In a contingent valuation question, the 

respondent is presented with two alternatives—a status quo, with 

respect to the current provision level of one or more ecosystem 

services—and the policy alternative with a specified payment 

vehicle (e.g., tax) and dollar amount. This method initially 

utilized simple question formats, such as open-ended questions 

(e.g., fill in the blank) or bidding procedures to elicit WTP 

values (table 2.4). In the more commonly applied referendum 

approach, the investigator presents a single offer and records 

the participant’s “yes” or “no” response. These responses are 

typically analyzed with dichotomous choice models (logit or 

probit) from which a welfare measure can be derived (table 2.4). 

The contingent valuation approach has some practical limitations 

in describing important tradeoffs; therefore, this approach may 

be suitable in contexts where decisionmakers need to understand 

the welfare associated with a single policy or a policy that has 

already been implemented. To understand tradeoffs in relative 

utility and WTP among different services or service levels, 

for planning purposes, a choice experiment approach may be 

more suitable.

Choice modeling—Choice modeling methods, or choice 

experiments, arose from conjoint-analysis procedures and have 

been employed in the marketing, transportation, and psychology 
Table 2.5—Survey items describing attributes of a forestwater protection program

Attribute 

category Attribute levels

Item 

code

Non-use 

benefits

Ensure clean water in the future (option value)

Ensure all people benefit (altruistic value)

Pass along to grandchildren (bequest value)

Maintain an unpolluted ecosystem 

(existence value)

1

2

3

4

Use benefits Recreation

Groundwater recharge (drinking water)

Commercial fisheries

Storm protection

5

6

7

8

How the 

program 

will be 

implemented

Purchase private forest land

Conservation easement

Technical assistance for landowners

Financial assistance for landowners

9

10

11

12

Who will 

implement 

the program

Federal agency

State agency

County government

Private non-profit organization

13

14

15

16

Proposed 

monthly 

utility tax 

payment

$0.50/month

$1.00/month

$3.00/month

$5.00/month

17

18

19

20

Source: Kreye and others (2016b).

Water-Forest Protection Program A

Purchase private forest land

Implemented by a State agency

Ensures clean water in the future

Provides recreational benefits (e.g., swimming)

Funded via a utility tax of $0.50/month ($6.00 annually)

Would you vote to accept Program A (all characteristics)?

Yes

No

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 21

literature for some time. In this approach, respondents are 

asked to choose from a selection of alternative bundles 

of attributes, which is more comparable to an actual 

market setting where tradeoffs are assessed and decisions 

are made (Adamowicz and others 1998). Rather than 

being questioned about a single event in detail, subjects 

are questioned about a sample of events drawn from a 

universe of possible alternatives. It is assumed that the 

order of preferences (A over B; B over C) for different 

services (or levels) generated using this approach is 

related to the respondent’s latent scale of utility (Boyle 

1990). Compared to contingent valuation, the choice 

experiment approach offers a richer description of the 

attribute tradeoffs individuals are willing to make and the 

estimated WTP values generally have smaller variances 

relative to the mean (Adamowicz and others 1998).

The effect of changing the level of a single attribute 

is known as a main effect. To understand main effects 

on the WTP decision, a main effects orthogonal array 

can be used to design a series of choice sets (Street and 

others 2005). To illustrate this procedure, a list of key 

attributes describing a forest-water protection program 

was developed through a series of interviews with the 

members of the public and experts in the field (see 

table 2.5; Kreye and others 2016b). Attributes of the 

clean water service provided by forests, including use and 

non-use values, were arranged into 16 different choices 

sets, each containing one attribute level from every 

attribute category.

Latent utility for ecosystem service attribute levels can 

be measured using several different methods (Carson and 

others 1994). In a dichotomous choice question format, 

the respondent is able to accept or reject the ecosystem 

service bundle or outcome described in each choice set 

(but without a specific reference to the status quo, as with 

contingent valuation) (fig. 2.4). This approach is similar 

to how consumers make decisions, which are often binary 

(e.g., category or brand decision, buy now or wait, etc.), 

and binary decisions are often consistent with economic 

demand theory. To produce a direct measure of relative 

utility for each attribute level, a ranking procedure may 

be used. In best-worst scaling, the respondent is asked 

to indicate which attribute is the “best” and which is 

the “worst” within each choice set (Louviere and Islam 

2008). A novel approach to survey design is to combine 

ranking and dichotomous choice methodologies in the 

same choice experiment question to generate both direct 

and indirect estimates of utility and allow for internal 

validation procedures (Kreye and others 2016b, Soto and Figure 2.4—Example of a dichotomous choice experiment question presented in a 

valuation survey.
Table 2.6—Dichotomous choice model using random effects logistic regression to 

estimate household willingness to pay (WTP) for a forest-water protection program 

in Florida

Variable Coefficient S.E. p>Z

Δ in 

monthly 

WTPa

Mean 

annual 

WTP

Payment -0.5070 0.3200 0.0000 $29.64

Ensure all people benefit -0.1640 0.0840 0.0490 -$0.81

Ensure clean water in the future 0.2300 0.0990 0.0210 $1.13

Groundwater recharge (drinking water) -0.3880 0.0820 0.0000 -$1.89

Conservation easement 0.3670 0.1000 0.0000 $1.78

Technical assistance for landowners -0.2370 0.0850 0.0050 -$1.15

Private non-profit organization 0.3380 0.0990 0.0010 $1.78

County government -0.2190 0.0830 0.0080 -$1.08

Weight 1.1970 0.3150 0.0000

Constant -0.9610 1.7760 0.0000

Adapted from Kreye and others (2016b).

Number of observations = 4,140. 

a Difference from mean monthly WTP estimate of $2.47 (2014 dollars).

22 Chapter 2. Forest Ecosystem Services: Cultural Values

others 2013, 2016). Other methods that measure latent utility 

using a choice modeling approach include: ranking alternatives 

in order of preference, series of paired comparisons, bundle 

selection (i.e., pick some number of the best alternatives), 

judgmental ratings, and fixed-sum allocation tasks (Carson and 

others 1994).

Data analysis procedures for choice modeling are regressionbased and produce statistically defensible estimates of value 

based on calculated probabilities. The independent variables 

in the model reflect the specified utility function and include 

specific attributes of the service (or multiple services) and of the 

respondent (e.g., demographic characteristics). Depending on 

how the dependent variable is characterized, the data are most 

often fitted to either a multinomial logit or probit model, but 

linear, quadratic, or log response functions may also be chosen 

(Boyle 1990, Johnson 2013). Advanced functional forms of these 

models (i.e., the conditional, random effects or mixed models) 

are largely recognized as being more effective in accounting for 

unobserved random utility or realistic variation in WTP estimates 

(Wooldridge 2013). Table 2.6 describes the outcome of a randomeffects logistic model containing the attributes listed in table 2.5.

The part-worth value, or marginal rate of substitution, for each 

attribute and the expected mean WTP value can be calculated 

using the estimated model coefficients (Hanemann 1984). 

Confidence intervals around mean WTP can be calculated using 

the variance-covariance matrix and a simulation approach 

(Krinsky and Robb 1986). Table 2.7 reports mean WTP estimates 

for some of the non-use values and policy processes found in 

table 2.5 and illustrates how individual WTP for a given policy 

alternative can be extrapolated to a larger population when it is 

multiplied by the number of households at the policy site. The 

estimated total annual value describes potential market demand 

for the associated non-market service.

Stated preference and cultural ecosystem service values—

Stated preference methods are well suited to assess cultural 

ecosystem service values because expected benefits can be part 

of the valuation question, whereas with revealed preference 

methods, expected benefits are often inferred. For example, using 

a choice experiment approach, researchers found that Danish 

recreationists experienced the greatest aesthetic benefits, and 

WTP, in forest stands that contain a mix of conifers and broadleaf 

trees (Nielsen and others 2007). The study presented in table 2.5 

described public values for clean water benefits by including 

descriptions of non-use values and beliefs about the effectiveness 

of certain conservation processes (e.g., conservation easements 

or technical assistance for landowners) as attributes in a choice 

experiment (Kreye and others 2016b).

The stated preference approach can also include metrics that 

describe important attitudes or knowledge as explanatory 

covariates in the predictive model (Manning and others 1999, 

Walsh and others 1990). Attitudes toward the environment, as 

described by the new ecological paradigm scale (i.e., biocentric, 

anthropocentric) have been found to have an important influence 

on WTP behaviors for environmental goods and services (Dunlap 
Table 2.7—Total annual benefits estimated for 50 percent of households for two policy 

alternatives to protect forests and water resources in the State of Florida

Household

Policy alternatives

Monthly 

WTP

Annual 

WTP

Percent of 

households

Number of 

households Annual total

Alternative 1: Ensure clean water 

in the future using conservation 

easements

$5.38 $64.56 50% 3,573,508 $230,705,676

Alternative 2: Ensure all people 

benefit from clean water by offering 

landowners technical assistance

$0.51 $6.12 50% 3,573,508 $21,869,868

Based on Kreye and others (2016b).

WTP = willingness to pay.

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 23

and others 2000, Kreye and others 2016b, Spash and others 

2009). Metrics, such as level of ecological and environmental 

knowledge and level of environmental concern, are also related 

to important attitudes and beliefs that make up cultural values 

and often used by researchers to explain consumer behaviors for 

environmental goods (Mostafa 2007, Nielsen and others 2007).

As a caution, standard descriptions of the population, such as 

demographic characteristics (e.g., age, race, household income, 

employment, place of residence) may offer an incomplete 

description of the human components that make up cultural 

ecosystem service value. Estimates of WTP and attitudes toward 

forest ecosystems have been broadly correlated with demographic 

characteristics (Tarrant and Cordell 2002, Torgler and others 

2008, Vaske and others 2001). However, this pattern may not 

always hold across all populations or be useful in all policy 

contexts. For example, campers and hunters in Canada tend 

to have strong biocentric attitudes, and these attitudes are not 

strongly correlated with the socio-economic characteristics of the 

campers and hunters (McFarland and Boxall 2000).

Valuation studies nearly always include variables describing 

population characteristics but only intermittently include 

variables measuring associated attitudes or psychological 

benefits. This is because these aspects of human behavior are 

usually outside the training of a traditional economist who often 

works with market data. Economists with training in stated 

preference methods and who work in interdisciplinary fields such 

as psychology, marketing, behavioral and ecological economics 

are often better equipped to provide decisionmakers with an 

understanding of the human components that give rise to cultural 

ecosystem services and impact WTP estimates.

Benefit Transfer Method

A benefit transfer is a procedure that transfers existing estimates 

of non-market values to a new study or policy context that differs 

from the original study. Benefit transfer is often used in legal 

proceedings and government policy analysis when there is not 

sufficient time or funds available to develop original benefit 

estimates using primary data specific to the issue at hand (Boyle 

and Bergstrom 1992). Rosenberger and others (2017) describe 

its application to estimating the economic benefits of outdoor 

recreation in the National Forest System. The following sections 

provide a description of common benefit transfer procedures and 

important considerations for using benefit transfer to estimate 

cultural ecosystem service values.

The simplest form of benefit transfer is when the unit value(s) 

is directly transferred from the study site to the policy site with 

only a few minor adjustments (e.g., inflation). An improvement 

on this method is a preference calibration transfer that calibrates 

the preference structure (i.e., utility model) described in the 

original study to match the characteristics of the policy site 

(Smith and others 1999). In cases where there are many studies 

available, a meta-analysis benefit transfer function may be used. 

In a regression-based meta-analysis, the dependent variable is 

the estimated WTP and the information provided in the study 

are the independent variables or factors found to influence WTP 

estimates (e.g., age, income). The entire equation (function) 

is then transferred to the site by adjusting the model to fit the 

policy context or the population affected by the policy. Figure 2.5 

illustrates the general differences between these three benefit 

transfer methods.

Unit value transfer—A direct unit value transfer is one of 

the more commonly used methods to help inform agency 

decisionmaking (Brown and Shi 2014, Gilmore 2014, Kroeger 

2005). This is done by applying a single statistic (usually an 

average from one or more study sites) to the policy site. For 

example, a mean WTP estimate for lake fishing from a single 

study can be transferred to assess the value of fishing on similar 

lakes. In the context of cultural ecosystem service values, 

transferring a simple mean value across relatively similar sites 

may only be appropriate when the benefiting population is 

relatively the same (Bateman and others 2011).
Unit Transfer

Preference Calibration 

Transfer

Function Value 

Transfer (meta-analysis)

Select 

applicable 

mean WTP

Adjust WTP ($) 

for inflation

Adjust WTP ($) 

for inflation

Aggregate WTP

across target 

population

Select study 

most similar to 

policy site

Calibrate original 

preference function 

to match the 

characteristics 

of the policy site

Aggregate WTP

across target 

population

Adjust model 

parameters to 

match policy 

site

Adjust 

WTP ($) 

for inflation

Collect large 

number of 

similar studies

Model key 

parameters 

using 

regression 

analysis

Aggregate 

WTP across 

target 

population

Select study 

most similar to 

policy site

24 Chapter 2. Forest Ecosystem Services: Cultural Values

Preference calibrated benefit transfer—A benefit transfer 

approach known as preference calibration offers an improvement 

over the direct unit value transfer approach by linking the 

fundamental preference structure of individuals with WTP 

estimates. Through an algebraic exercise, the researcher can 

“back out” the parameters of the original function presented 

in a single study; the function is then calibrated and used in a 

new WTP function at the policy site (Smith and others 1999). 

Assuming that the ecosystem characteristics and benefits 

generated at the study and policy sites are similar, this approach 

allows researchers to address variation in preferences based on 

the features in the household budget constraint, such as household 

income, average travel cost, and rent. This approach does require 

researchers to be well founded in utility function theory and have 

advanced algebraic skills. Williamson and others (2007) provides 

an example of how to perform a preference calibration transfer 

for changes in water quality using hedonic property values, travel 

cost, and contingent valuation values.

Benefit transfer meta-analysis—A meta-analysis is a statistical 

method for analyzing results from existing studies with a 

set of related research hypotheses and has widespread use in 

several areas including health sciences, psychology, education, 

marketing, and social sciences (Nelson and Kennedy 2009). In 

economics, meta-analyses are often used to synthesize numerous 

studies that place economic values on environmental goods and 

services (Rosenberger and Loomis 2000). The results of a metaanalysis can be used to predict estimates of value constructs (i.e., 

influential factors, or drivers) while controlling for important 

differences among studies. Given that the sources of variation 

Figure 2.5—Comparison of general benefit transfer methods.

in WTP can occur at both the site and population level, a metaanalysis approach may be preferred to other benefit transfer 

approaches (Rosenberger and Loomis 2000, Walsh and others 

1990). As such, the meta-analysis approach to benefit transfer is 

provided in the next section.

Meta-analysis approach—A meta-analysis is a regression-based 

modeling approach and the studies that are selected and included 

in the analysis formulate WTP using the same methodological 

approach (e.g., contingent valuation) for the same services or 

benefits (e.g., hiking) in the same general type of ecosystem 

(e.g., a forested landscape). Researchers may also consider if 

the studies are conducted within a given region and within a 

designated time frame (e.g., Rosenberger and Loomis 2000). The 

value estimate (WTP) selected from a set of related studies (e.g., 

contingent valuation studies) serves as the dependent variable and 

variables describing study methods, target population, and site 

characteristics serve as the independent variables (Rosenberger 

and Loomis 2000) (fig. 2.6).

Standard error, standard deviation, and sample size are useful 

proxies for study quality and are often used as a weighting 

variable to address sample bias or to reduce the impact of lower 

quality studies on model performance (Nelson and Kennedy 

2009). The data can be fitted to a wide variety of models 

including linear and weighted regression and ordinary least 

squares models. The resulting coefficients are then adjusted to 

meet the characteristics of the policy site and back calculated 

to obtain estimates of WTP (see Johnston and Besedin 2009). 

Confidence intervals can also be calculated using the equations 
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 25

Dependent Variable Independent Variable

Estimated annual 

household 

willingness-to-pay for 

an ecosystem service

Study characteristics:

• Type of valuation method

• Year of study

• Study quality

Socioeconomic characteristics:

• Annual household income

• Age

• Gender

Site characteristics:

• Regional location

• Type of ecosystem service

• Change in ecosystem service

• Policy process

Figure 2.6—Conceptual model of a meta-analysis of valuation studies.

and the statistics commonly reported in regression analysis such 

as the margin of error and standard error. For more examples of 

a meta-analysis benefit transfer of forest values, see Chiabai and 

others (2009), Ding and others (2010), Escobedo and Timilsina 

(2014), Kreye and others (2014), and Zandersen and Tol (2009).

Benefit transfer and cultural ecosystem service values—The 

primary challenge of benefit transfer is the presence of important 

and unaccounted differences between the study site and the 

policy site. Selecting studies that help minimize these differences 

can be particularly challenging in the context of cultural 

ecosystem service values, as many valuation studies often fail 

to appropriately measure important human components (e.g., 

perceived benefits, beliefs) that give rise to cultural ecosystem 

service values. Without an understanding of the underlying 

cultural benefits, or the values associated with different 

benefits, we cannot adequately determine how changes in forest 

management or service provision impact public welfare. Even 

with calibration procedures, transfers across different sites are 

subject to less error than a transfer across populations for a given 

site (Morrison and others 2002). In other words, WTP estimates 

are more often impacted by the characteristics of the population 

valuing the forest, rather than the characteristics of the forest 

itself. As discussed earlier in the chapter, relying on demographic 

data alone to describe perceived benefits may provide an 

incomplete description of important cultural ecosystem service 

values (Bengston 1994). Another challenge is that many benefit 

transfer studies do not account for differences in perceived risk 

and the availability of substitutes across sites, which can also 

impact WTP behaviors and lead to the under or overestimation 

of transfer of values (Batabyal and others 2003, Johnston 2007). 

Until the body of research examining cultural ecosystem services 

can provide a more contextualized description of the human 

components that give rise (e.g., beliefs, attitudes) or reinforce 

(e.g., perceived benefits) cultural ecosystem service values, 

the benefit transfer method will likely remain problematic in 

producing accurate and reliable estimates of value for many types 

of cultural ecosystem services.

CONCLUDING REMARKS

This chapter reviewed ways that human culture gives important 

meaning to forests that society recognizes as valuable. We 

also described commonly used approaches for assessing the 

economic value of cultural ecosystem services and highlighted 

important challenges associated with these valuation methods. 

Clearly, efforts to understand tradeoffs in the provision of cultural 

ecosystem services is a formidable challenge. Despite this, 

integrating cultural ecosystem service values into decisionmaking 

remains a pressing issue. Failing to account for diminished 

cultural services that result from forest management decisions or 

loss of forest lands will likely lead to less effective forest policy 

and reduced social welfare. Future research should work to 

advance valuation methods and approaches while continuing to 

investigate how cultural ecosystem service values are mediated 

by perceptions, customs, and beliefs. Providing decisionmakers 

with improved value estimates can lead to better policy and 

program design and help ensure that society continues to benefit 

from the full spectrum of ecosystem services provided by public 

and private forest lands.
26 Chapter 2. Forest Ecosystem Services: Cultural Values

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Zhang, D.; Polyakov, M. 2010. The geographical distribution of plantation forests 

and land resources potentially available for pine plantations in the U.S. South. 

Biomass and Bioenergy. 34(12): 1643-1654.
Appendix 2.1

Recreation and tourism values of forests in the Southeast region

Study Geographic scope of values Basis for valuation Value estimates

Walsh and Loomis (1989) Virginia Use value of wilderness 

protection (contingent 

valuation)

$12/visitor day

Zhang and others (2004) Alabama Hunters’ WTP (contingent 

valuation)

$1.29 per acre per hunter or 

$23 per acre per hunter

Munn and others (2011) Mississippi Hunters’ WTP (contingent 

valuation)

$0.65 to $6.40 per acre

Brunke and others (2006) Mississippi Hunters’ WTP (contingent 

valuation)

$11 and $36.25 for fall and 

spring turkey hunting permits

Moore and others (2011) Georgia Non-use value of private 

forests

$11.2 billion per year

Haefele and others (1991) Southern Appalachian region* Non-use value (WTP for 

protecting forests)

$100 per year and $21 per year 

for dichotomous choice and 

payment card estimates

Talberth and Moskowitz (1998) Southern Appalachian region Expenditures on hunting 

equipment and trip expenses

$1.3 billion in 1988

Loomis and Rochardson (2000) Southern Appalachian region Consumer surplus of 

recreational fishing

$237 million to $637 million in 

1997

Barnhill (1999) National Forests of the 

Southern Appalachian region

Economic impact of 

recreational fishing

$407 million

Barnhill (1999) National Forests of the 

Southern Appalachian region

Total economic impact of 

hunting and wildlife viewing

$594 million and $407 million, 

respectively, in 1996

Barnhill (1999) National Forests of the 

Southern Appalachian region

Economic impact of recreation 

on the National Forests

$6 billion annually

* The Southern Appalachian region consists of Alabama, Georgia, North Carolina, South Carolina, Tennessee, and Virginia.

30 Chapter 2. Forest Ecosystem Services: Cultural Values
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 31

Chapter 3

Forest Ecosystem Services: 

Water Resources

Thomas P. Holmes, James Vose, Travis Warziniack, Bill Holman

in the valuation process (see fig. 3.1). Recommendations on 

the stages to be followed when conducting ecosystem service 

valuation studies, with special emphasis on scoping and defining 

ecosystem services, is presented in a guidebook especially 

designed for Federal resource managers (Olander and others 

2015). Good summaries of the concepts and methods used to 

integrate economic analyses with ecosystem service assessments 

are also available (e.g., Bateman and others 2011). A great deal 

of information focusing on the economic analyses of ecosystem 

services can be found in the literature on non-market valuation 

(e.g., Champ and others 2003, Freeman and others 2014), and 

specific applications of ecosystem service valuation methods 

to water resources have been published (Birol and others 2006, 

Young and Loomis 2014).

Forests, Water Resource Ecosystem 

Services, and Human Well-Being

In this chapter, we refer to people who benefit from water 

resource ecosystem services as beneficiaries who may be divided 

into two groups.4 First, people who use water resources are 

referred to as ecosystem service users. The benefits derived 

from water use may require capital and labor inputs, such as in 

the provision of drinking water supplies, and maintaining forest 

vegetation can help reduce the cost of inputs in the production 

of these services (e.g., Holmes 1988). The value to beneficiaries 

who use water resources for activities such as fishing or boating 

may also be augmented by enhanced water quality provided by 

forested landscapes (e.g., Johnston and Wainger 2015). Forest 

cover can also protect economic use values by reducing the risk 

of damages from floods and droughts. For example, mangrove 

forests help protect people and structures from flooding 

associated with storm surges (Barbier and others 2013, Das 

and Vincent 2009), and knowledge is increasing regarding the 

4 Many of the water related ecosystem services provided by forest landscapes are 

cultural ecosystem services, which are defined and described in more detail in 

chapter 2. 

INTRODUCTION

S

ince the publication of the Millennium Ecosystem 

Assessment (MEA 2005), awareness has steadily grown 

regarding the importance of maintaining natural capital. 

Forest vegetation is a valuable source of natural capital, and 

the regulation of water quantity and quality is among the most 

important forest ecosystem services in many regions around 

the world. Changes in forest cover alter the provision of water 

resource ecosystem services via influences on precipitation 

regimes, drinking water supply and purification, flood 

control, maintenance of streamflows, provision of recreational 

opportunities, and cooling water for thermoelectric power 

production. In this chapter, we describe how the ecosystem 

service values of water resources from forest landscapes can 

be estimated. Although much of the literature we reference is 

focused on the Southern United States, the concepts and methods 

described here are broadly applicable to other regions.

Information regarding the economic values of ecosystem services 

complements cultural and moral sentiments regarding the value 

of nature. This information can help governments, corporations, 

traditional cultures, and individuals make more informed 

decisions regarding the conservation of natural capital (Daily and 

others 2011).3 In general, ecosystem service valuation studies 

seek to integrate ecosystem service assessments with economic 

analyses, and several stages of analyses need to be integrated 

3

 Although some forested watersheds in the Southern United States are protected 

by local, State, and Federal forest conservation areas (Caldwell and others 2014), 

most forest land is privately owned and subject to market forces that can create 

economic incentives to convert forests to alternate uses (Alig and Plantinga 

2004). Where these pressures exist, compensating private landowners for the 

social values their forests provide to other water users may be an effective way 

to limit land use change and promote forest conservation (Holman and others 

2007). Within the Southern United States, efforts are underway by national, State, 

and local conservation organizations to protect source waters, stream flows, 

and reservoir capacity in forested watersheds such as those located along the 

Mills River (NC), Upper Neuse River (NC), Catawba-Wateree River (NC, SC), 

Savannah River (SC, GA), and their tributaries.
SOCIOECONOMIC DYNAMICS 

(migration, markets, 

natural resources & amenities) 

LAND USE DYNAMICS

(forest, agriculture, developed)

UPSTREAM INPUTS WATER QUALITY/ QUANTITY IMPACTS LAND USE LEGACY

FINAL ECOSYSTEM SERVICES

Economic 

Valuation

Function

Use Values

● Drinking

● Fishing

● Boating

Non-use Values

● Existence

● Bequest

● Option

Ecosystem 

Service 

Production 

Function

Damages Avoided

● Floods

● Drought

32 Chapter 3. Forest Ecosystem Services: Water Resources

impacts of large-scale deforestation and tree die-off on local and 

remote precipitation patterns (Devaraju and others 2015, Stark 

and others 2016).

The second group of beneficiaries from hydrological systems 

includes people who value water resources that they do not 

actually use; this group is referred to as non-users. Non-use 

benefits include the values associated with future water use 

as well as knowledge that specific water resource ecosystem 

services exist. A good example of non-use values of water 

resources is found in a study of the value of wetlands restoration 

in the greater Everglades ecosystem (Milon and Scrogin 2006). 

That study provided estimates of Florida residents’ willingness 

to pay to conserve future water provisioning ecosystem services 

and to protect wildlife species that respondents may never see 

(Milon and Scrogin 2006). More generally, a meta-analysis of 

surface water resource values indicated that non-use values can 

be a substantial component of the total economic value of water 

(Johnston and others 2003).

Economic measures of human well-being (value) rely upon 

the theory of consumer demand. Water supplies from forest 

landscapes contribute to the satisfaction of demands for specific 

ecosystem services (such as water for drinking and recreation). 

Economic valuation of water resources from forest landscapes 

generally requires estimates of the numbers of beneficiaries 

associated with each water resource ecosystem service and the 

per capita value associated with each ecosystem service. Because 

the biophysical characteristics of watersheds are heterogeneous, 

as are the characteristics of beneficiaries, the ecosystem service 

values of water resources from forest landscapes can vary greatly 

across locations and need to be carefully addressed in large-scale 

ecosystem service assessments.

The sustainable production of water resource ecosystem services 

relies upon many primary and secondary processes. These 

processes are called ecosystem service production functions

and the services of the natural environment that directly affect 

human well-being are called final ecosystem services (Bateman 

and others 2011, Boyd and Banzhaff 2007, Brown and others 

2007, Fisher and others 2009, Johnston and Russell 2010).5

That is, final ecosystem services are end products of nature to 

be distinguished from ecological processes and intermediate 

5

 For example, final ecosystem services have been defined as “components of 

nature, directly enjoyed, consumed, or used to yield human well-being” (Boyd 

and Banzhaf 2007).

Figure 3.1— Ecosystem service assessments can be linked with economic valuation functions to measure how changes in forest 

landscapes affect the economic value of water resources.
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 33

ecosystem services on which they depend. By recognizing that 

human values are derived only from final ecosystem services, we 

can avoid the problem of double-counting that would occur if 

primary and intermediate services were valued independently in 

an economic assessment.

Ecosystem services provided by water resources include both 

intermediate and final services, and it is important to understand 

how the economic values of these services can be accounted for. 

Consider the ecosystem services enjoyed by a specific group of 

beneficiaries: trout anglers. In this case, tree cover may enhance 

the value of water resource ecosystem services by cooling and 

purifying cold-water streams, thereby increasing trout abundance 

(Johnston and Wainger 2015). Although water quality also 

influences organisms providing food sources for trout, the food 

web is an intermediate ecosystem service that is not directly 

consumed or used by anglers and should not therefore be valued 

independently. Rather, it supports a final ecosystem service that 

contributes to angler well-being.

Human well-being derived from the consumption of an 

ecosystem service is generally estimated using revealed or 

stated preference methods (Champ and others 2003). Revealed 

preference methods rely upon observations of behavior to 

infer economic value. For example, observations regarding the 

frequency of fishing trips to streams with differing water quality, 

in combination with distances that people travel for fishing 

access, can be used to infer the value of water quality as it relates 

to angling (Huppert 1989, Whitehead 1993). A second example 

of revealed preferences is provided by observations on housing 

prices for homes situated next to lakes with varying water 

quality. When entered into statistical models, these observations 

can reveal the value of water quality to homeowners (Poor and 

others 2001). In contrast, stated preference models rely on survey 

questions to infer values. For example, questions may ask survey 

respondents how much they would be willing to pay (WTP) for 

specific water quality changes (Young and Loomis 2014).

Complex Landscape-Riverscape Systems

Land uses influence water supplies and, in general, managed 

and unmanaged forests supply the cleanest and most stable 

fresh water supplies relative to all other land uses (Jackson 

and others 2004, Jackson and others 2005, Brown and others 

2008).6 However, efforts to quantify the impacts of forests 

on water resource ecosystem services involves disentangling 

the components of landscape-riverscape systems, which 

becomes increasingly complex as the scale of analysis shifts 

from individual, small watersheds to multiple watersheds at 

broad spatial scales. Understanding the influence of land uses 

on hydrologic systems is challenged by a number of factors, 

including: (1) natural gradients (e.g., soil type and typography) 

6

 Point source pollution from small areas of non-forest land uses embedded in 

largely forested watersheds is an obvious exception to this generalization.

are correlated with human gradients (e.g., land uses) across the 

landscape, (2) stream ecosystems respond to land use changes 

at multiple spatial and temporal scales, (3) watershed responses 

to land use change may be nonlinear, and (4) influences from 

current land uses are difficult to isolate from historical land uses 

(Allan 2004). Although advances in GIS and remote sensing 

technology are helping to address these challenges (Johnson and 

Host 2010), scientific knowledge of causal landscape-riverscape 

linkages over broad spatial scales remains at an early stage 

of development.

The key to linking ecosystem service assessments with economic 

values is to assure that final ecosystem services are measured 

using the same indicators that are included in economic valuation 

functions (Boyd and others 2016, Olander and others 2015).7

For example, water quality affects the demand for various 

recreational activities (such as swimming or boating), and 

one indicator of water quality is clarity (or turbidity). In this 

case, turbidity levels might be considered as a final ecosystem 

service linking water supplies from forest landscapes with an 

ecosystem service valuation function. In general, science-based 

metrics that link ecosystem service assessments with economic 

valuation functions will help governments and businesses (such 

as water and electric utilities) understand how forest conservation 

would benefit their constituencies, whether they are taxpayers 

or ratepayers.8

In the following, we first present an overview of the literature 

describing relationships between forest cover and various metrics 

of water resource ecosystem services across different spatial 

scales. Next, we present an overview of economic principles, and 

illustrations from the literature, describing how the economic 

value of water resource ecosystem services can be measured. This 

is followed by a discussion of how forestry agencies might go 

about obtaining ecosystem service values of water resources from 

forest landscapes. This section includes information on available 

data sources and decision support models.

ECOSYSTEM SERVICE ASSESSMENTS OF WATER 

RESOURCES FROM FOREST LANDSCAPES

Forest Impacts on Streamflow, Soil 

Erosion, and Chemical Contamination

From the standpoint of evaluating alternative land covers, the 

impacts of forest cover on the hydrograph (i.e., the temporal 

pattern of streamflow after rainfall events) and baseflows are 

more important than total annual flow because forests typically 

require more water for evapotranspiration (and hence, have lower 

7 The term benefit relevant indicator has been suggested to link outputs from 

ecosystem service assessments with economic values (Olander and others 2015).

8 Within the Southern United States, organizations such as The Conservation 

Fund, The Nature Conservancy, Conservation Trust for North Carolina, and 

the Carolina Mountain Land Conservancy are working with water and electric 

utilities to conserve forests in the region to protect water quality and quantity.
34 Chapter 3. Forest Ecosystem Services: Water Resources

total annual streamflow) than land uses that have less vegetation 

cover to intercept and transpire precipitation inputs (e.g., urban 

areas, annual crops, and so on) (Sun and Lockaby 2012). Forest 

soils act as a buffer against heavy storms, slowing the rise of 

streams and minimizing flood risk. During dry conditions, water 

that has percolated into the forest soil is released gradually for 

streamflow and groundwater discharge. Timber harvest and 

management can have negative impacts on quantity, quality, and 

timing; however, decades of research provide best management 

practices that allow forests to be managed in ways that minimize 

impacts on processes and conditions that protect water resources. 

Examples include riparian buffers, road building and surfacing 

standards, and stream crossing design.

Conversion of forest cover to urban or agricultural uses 

alters hydrology. It often results in enhanced peak flows and 

stormflows, while both enhanced and reduced baseflows 

have been reported (Amatya and others 2008, Boggs and 

Sun 2011, Sun and Lockaby 2012). Such conversions reduce 

evapotranspiration and soil infiltration capacity due to 

compaction and impervious cover such as buildings, roads, and 

parking lots, resulting in greater overland flow (O’Driscoll and 

others 2010). As a result, characteristic changes in hydrology 

following forest conversion include greater annual streamflow 

and higher peak flows (Bosch and Hewlett 1982, Crim 2007, 

de la Crétaz and Barten 2007, Hibbert 1967, McMahon and 

others 2003, Schoonover and others 2006). Decreased infiltration 

lowers groundwater recharge rates; thus, baseflows may be 

reduced (Calhoun and others 2003, Rose and Peters 2001, Wang 

and others 2001). However, reduced evapotranspiration from 

lower forest cover may offset some of the baseflow reduction. 

Changes in hydrologic response depends on the amount (i.e., 

percentage loss of forest cover) and the location (i.e., headwater 

vs. riparian) of conversion.

Forest watersheds typically have lower stream channel erosion 

due to lower stream velocity and peak discharge. In addition, 

forests stabilize soils, so soil erosion and sediment delivery to 

streams can increase following the removal of forest vegetation 

and loss of forest floor and roots (Jackson and others 2004). In 

some stream channels, it can be difficult to differentiate sediment 

contributions from current land use and historical agricultural 

use within the watershed, as the legacy effects of historical land 

use can be observed decades later (Jackson and others 2004). In 

addition to generating sediment export from terrestrial sources, 

hydrologic changes due to current land use conversions have the 

potential to re-suspend legacy sediment that accumulated in the 

stream beds decades ago. Hence, even streams within a heavily 

forested watershed may exhibit degradation due to historical land 

uses (Harding and others 1998). As noted in the introduction, 

these long-term “legacy” effects of land use can constrain the 

ability to correlate existing land use and some water quality 

parameters. However, urban and agricultural watersheds typically 

exhibit stream sediment concentrations that are much higher than 

forested watersheds (Clinton and Vose 2006, Lenat and Crawford 

1994, Paul and Meyer 2001, Schoonover and others 2005). 

A variety of factors determine the differences in erosion rates 

between land uses, but the most important factor is the location 

and severity of disturbance (e.g., amount and location of soil 

disturbance, road density and condition, and stream crossings).

Forested watersheds are also associated with low streamwater 

concentrations of most chemicals (Larsen and others 2013). 

Changes in stream nutrients can be observed at relatively small 

levels of forest loss. For example, increases in stream nutrients 

have been observed at levels of imperviousness as low as 

5 percent (Schoonover and others 2005, Crim 2007). Since most 

forests are deficient in one or more elements, forested systems 

are generally effective in retaining inputs of nutrients in soils and 

biomass. Net export (output in streamflow minus precipitation 

inputs) of macronutrients from undisturbed forested catchments 

is often negative, a scenario that indicates accretion of forest 

biomass (Likens and Bormann 1995, Swank and Douglass 

1977). Non-point source related health risks from urban and 

agricultural land uses include elevated nutrients (e.g., nitrogen 

and phosphorus), fecal coliform, e-coli, metals, pesticides, and 

personal care products (Klapproth and Johnson 2000, Larsen 

and others 2013, Paul and Meyer 2001). Forests also play a 

critical role in enhancing water quality in watersheds with mixed 

land use. Higher quality water draining forested portions of a 

watershed can dilute lower quality water and improve overall 

water quality (Clinton and Vose 2006).

Biophysical Measurements at Stream 

and Watershed Scales

Streamflow and groundwater recharge—As noted above, 

when precipitation exceeds evapotranspiration, excess water is 

available to recharge soil storage, recharge groundwater, and/or 

contribute to streamflow. Regulation of the quantity and timing 

of streamflow and the amount of groundwater recharge are 

important ecosystem services provided by forested watersheds. 

This amount and timing varies from forest to forest and across 

watersheds with different soils, bedrock, topography, land 

uses, and climatic regimes. For example, the amount of water 

consumed by evapotranspiration by forests in the Southern 

United States ranges from 47 to 90 percent of precipitation 

(Vose and others 2015). Hence, it is difficult to generalize the 

quantity of streamflow from the wide diversity of forest types 

and landscapes in the Southern United States; quantification 

requires measurement, modeling, or some combination of the 

two. In addition, small forest stands may be dispersed within a 

matrix of mixed land uses; separating the contribution of forests 

to overall streamflow at larger spatial scales can be a challenge. 

Groundwater recharge is also especially difficult to quantify. The 

best approximation uses an approach that proportions excess 

water based on bedrock geology and soils (Wolock 2003).

Streamflow data are available for only a small sample of forests 

and regions. The most comprehensive dataset for U.S. streams 

is that for the network of stream gauges maintained by the 

United States Geological Survey (USGS) (waterdata.usgs.gov/

nwis/ rt) that includes near real-time estimates of streamflow. 
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 35

Often these gauges are placed on larger streams draining 

mixed land uses, so as noted above, determining the amount of 

streamflow contributed by forests is difficult to quantify. Other 

Federal agencies such as the Forest Service, U.S. Department of 

Agriculture, also monitor forest streamflow (e.g., the Coweeta 

Hydrologic Laboratory; the Santee Experimental Forests) 

on small watersheds, and these data may serve as a good 

approximation of streamflow for similar forest types in the same 

geographic regions and climate regimes. These data also serve an 

important role for testing and validating hydrologic models.

If direct measurements are needed, streamflow can be estimated 

using either permanent or temporary instruments that quantify 

volume (ft3 s-1). Permanent gauges—weirs and flumes—are 

expensive and labor intensive, but they can provide very 

accurate long-term and fine temporal resolution measurements of 

streamflow (water.usgs.gov/edu/measureflow.html). Streamflow 

can also be estimated using measurements of stage height derived 

either manually or with automated sensors. To determine flow 

volume, stage height (i.e., the height of the surface of the stream 

above a given fixed point) is combined with manual measures 

of stream cross-sectional dimensions and velocity to develop 

a rating curve, where volume (ft3 s-1) is estimated from stage 

height (water.usgs.gov/edu/measureflow.html). If measurements 

are long term, have a high temporal frequency, and are taken 

during storms, they can also be used to develop flow regimes 

and storm hydrographs. For example, derived parameters such as 

total annual flow (total water supply), minimum daily flow (water 

supply risk and ecological flows), maximum daily flow (erosion 

and flood risk), and peak flow (flood risk) are all relevant for 

economic valuation.

When direct measurement is not possible or appropriate, models 

can be used to estimate streamflow and groundwater recharge. 

These models range from highly detailed and calibrated process 

models, to simple empirical models. As expected, modeling 

skills, data, and computing requirements vary greatly across 

the full range of modeling approaches. Caldwell and others 

(2015b) provide an excellent summary and review of various 

hydrologic models.

Water quality metrics—Water quality parameters important 

to valuation of water resource ecosystem services include a 

combination of physical, chemical, and biological metrics. 

Because stream nutrients are generally low (especially relative 

to other land uses; Larsen and others 2013) in both managed and 

undisturbed forest watersheds, total suspended solids (TSS) and 

water temperature are among the most important physical water 

quality metrics to monitor in forested watersheds because they 

can be impacted by forestry practices and other disturbances 

(Jackson and others 2004). TSS is a combination of suspended 

sediment and organic matter and is highly correlated with 

turbidity. Where erosion is (or has been) high, TSS is mostly 

comprised of sediment (Reidel and Vose 2002). High TSS 

levels can have a negative impact on aquatic organisms and can 

impact water treatment costs and reservoir storage (Dearmont 

and others 1998, Forster and others 1987, Holmes 1988). TSS 

can be measured directly with grab samples or automated flow 

proportional samplers (e.g., ISCO samplers). The advantage of 

flow proportional samplers is that TSS is sampled across the 

hydrograph and provides a better quantification of TSS due the 

strong relationship between flow and TSS. Some of this variation 

can be captured with frequent grab samples, but this requires 

timing sampling to occur during all stages of the hydrograph. 

In either case, further analyses in the laboratory are required to 

quantify the amount of TSS. Sampling approaches that do not 

require laboratory analyses include in situ optical sensors (e.g., 

YSI data sondes) that can collect data automatically and be linked 

with the hydrograph.

Water temperature can be measured using spot measurements 

with a thermometer or measured and logged continuously with 

a thermometer and data logger. Stream temperature can also be 

predicted from air temperature (which is influenced by forest 

cover), although these relationships are weak in areas where 

groundwater springs contribute substantially to streamflow 

(Caldwell and others 2015). Thermal pollution can have negative 

impacts on aquatic organisms (especially in cold-water streams) 

and contribute to secondary effects such as algal blooms.

Chemical and biological metrics include concentrations of 

chemicals—such as nitrogen, phosphorus, pharmaceuticals, 

pesticides/herbicides, and heavy metals—and biological 

metrics such as fecal coliform and e-coli. High levels of these 

constituents can have direct negative impacts on human health 

(i.e., from direct contact from swimming) and increase costs of 

water treatment (Larsen and others 2013). Streamflow from most 

forested landscapes has very low concentrations of most chemical 

and biological parameters so quantification can be difficult and 

perhaps not necessary in most cases. However, where monitoring 

is required, streamwater can be sampled using grab samples or 

automated flow proportional samplers, by laboratory analysis. 

Because many constituents are highly reactive (i.e., they 

undergo biological transformations while being stored in sample 

containers), there are strict guidelines for sample processing 

and storage. 

Water Resource Ecosystem Services From 

Managed Versus Unmanaged Forests

Considerable information is available on the impacts of forest 

management on streamflow throughout the United States (Brown 

and others 2005, Jones and Post 2004). In general, removal of 

the forest canopy increases streamflow for the first few years, 

but the magnitude, timing, and duration of the response varies 

considerably among ecosystems. Sometimes, streamflow returns 

to pre-harvest levels within 10 to 20 years; whereas other times, 

streamflow remains higher, or can even be lower than pre-harvest 

flow, for several decades after cutting (Jackson and others 2004). 

This wide variation in response patterns is attributable to the 

complex interactions between climate and vegetation; the former 
36 Chapter 3. Forest Ecosystem Services: Water Resources

can vary considerably from dry to wet climatic regimes, and 

the latter can vary in structure and phenology (coniferous vs. 

deciduous forest).

It is further expected that due to demands from a shrinking land 

base and emerging bioenergy markets, management intensity 

will increase on new and established plantations to meet wood 

fiber demands. In the Southern United States, evapotranspiration 

varies considerably among managed and unmanaged forests, 

and among forest types (Vose and others 2015). In general, 

coniferous forests have higher evapotranspiration (and hence 

lower streamflow) than deciduous hardwood forests due to a 

combination of greater interception and transpiration (Ford 

and others 2011). This variation is important for evaluating the 

implications of increasing pine plantation forests or fast growing 

woody species such as Eucalyptus because the magnitude of 

the effects on streamflow depends on the species, forest types, 

or land use being replaced (King and others 2013, Vose and 

others 2015).

Water Resource Ecosystem Services 

From Headwater Forests

Water flows along topographic pathways to form a stream 

network—headwater forests are located at the beginning of the 

stream network (or highest elevation) and typically contain, 

ephemeral and 1st and 2nd order streams. In the Southern United 

States, some of the water that flows into the Piedmont originates 

from the mountainous and heavily forested landscapes of the 

southern Appalachian Mountains. High rainfall, deep soils, forest 

cover, and steep terrain provides a perennial flow of high quality 

water to streams and rivers in the Piedmont and Coastal Plain.

Some of the headwater forests in the South are located on 

National Forest System (NFS) lands, which contribute about 

3.4 percent of the total surface water supply in the South that 

serves some portion of the water supplied to 19 million people 

(Caldwell and others 2014). In comparison, State and private 

forest lands in the South contribute about 32.4 percent of 

southern surface water supplies providing some proportion of 

the water consumed by nearly 50 million people.

Water Resource Ecosystem Services 

From Riparian Forests and Wetlands

Hydrological functions of forested wetlands may include 

flood mitigation or short-term surface water storage; and 

to a lesser extent than forested wetlands in other regions of 

the United States, they abate storm damages and recharge 

groundwater (National Research Council 1995, Walbridge 1993). 

Biogeochemical processes of wetlands include the transformation 

and cycling of elements and retention and removal of dissolved 

substances and thereby the improvement of surface, subsurface, 

and groundwater quality (Blevins 2004, National Research 

Council 1995).

Functions of riparian forests also include hydrological, 

biogeochemical, and habitat aspects. Many studies have shown 

that riparian forests help to stabilize stream banks and also trap 

pollutants such as sediment, nutrients, bacteria, fertilizers, and 

pesticides from runoff (Anderson and Masters 1992, Binkley 

and Brown 1993, de la Crétaz and Barten 2007, Klapproth 

and Johnson 2000, Naiman and others 2005, USDA National 

Agroforestry Center 2008, Vellidis 1999). The hydraulic 

connectivity of riparian zones with streams and uplands, coupled 

with enhanced internal biogeochemical processing and plant 

uptake, make riparian zones effective buffers against high 

levels of dissolved nutrients from uplands and streams, while 

geomorphology and plant structure make them effective at 

trapping sediments (Naiman and others 2005).

However, an intact riparian corridor does not ensure stream 

protection, as this relationship is dependent on several other 

factors including watershed characteristics such as topography, 

hydrology, soils, and vegetation, residence time of pollutants in 

the buffer, depth and variation of water table, upland land use 

practices, and climate (de la Crétaz & Barten 2007, Groffman 

and others 2003, Tomer and others 2005, Walsh and others 2005). 

Use of the riparian corridor also affects the relationship, although 

the impacts of periodic timber harvesting, livestock grazing, and 

recreation are limited if best management practices (BMPs) are 

implemented appropriately (Anderson and Masters 1992).

Quantification of Water Resource Ecosystem 

Services at Multiple-Watershed Scales

Scientific interest in understanding landscape scale relationships 

between land uses and the condition of water supplies has 

intensified during the past few decades. This trend can be 

attributed to the pace and significance of changes occurring in 

land uses and land cover around the world, advancements in 

the concepts and tools used by landscape ecologists, and the 

increasing availability of spatially referenced data on land use/

land cover as well as indicators of stream condition (Allan 2004). 

A common approach is to estimate correlations between land uses 

and indicators of stream quality using statistical methods. Several 

studies of this type have been reported for the Eastern United 

States, all of which show a positive correlation between the 

amount of forest cover and various metrics of water quality.

An early example of this type of analysis conducted in the MidAtlantic region showed that the proportion of stream miles in 

riparian forest cover had a strong negative effect on total nitrogen 

and suspended sediment in streams (Jones and others 2001). A 

second example, using multiple regression analysis of data on 

land use and macroinvertebrate abundance (an indicator of high 

water quality) in North Carolina, highlighted the influence of the 

specific physiographic region on estimated land use/water quality 

relationships (Potter and others 2004). In particular, the authors 

reported that the amount of forest cover in riparian areas was a 

good predictor of macroinvertebrate abundance in the Coastal 
Water quality degradation

Percent impervious

High

Low

Threshold

Overestimate

Actual

Predicted

Underestimate

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 37

Plain region, whereas total watershed forest cover was a better 

predictor of this metric in the Piedmont region. Notably, forest 

cover was not found to be a good predictor of macroinvertebrate 

abundance in the southern Appalachian Mountains. These 

findings indicate the potential danger of transferring research 

results from one physiographic region to another.

It has been noted that the analysis of correlations between 

categories of land use and metrics of water quality are subject 

to some important caveats (Allan 2004). First, the analyses of 

land use-water quality relationships implicitly substitute space 

for time. That is, statistical approaches have typically explained 

variations in water quality across hydrologic units using data 

on the varying proportions of land use within those hydrologic 

units. This approach may obscure important determinants of 

water quality within specific hydrologic units that occur over 

time as land uses within those units change. Therefore, forecasts 

of changes in water quality for specific land units based on 

these sorts of cross-sectional analyses run the risk of omitting 

important influences, such as historical land use practices specific 

to those land units, and may result in biased estimates. Second, 

because categories of land use implicitly sum to 100 percent, 

various measures of land use may provide equally good models. 

For example, an increase in forest cover, as measured across 

land units, implies that other land uses necessarily decrease. 

So, metrics of forest cover may simply be revealing the relative 

prevalence or absence of other land uses. Third, it has been 

shown that spatial correlations among land use variables (for 

Figure 3.2—Landscape-riverscape production of water quality is nonlinear: assuming a linear relationship can result 

in potentially large errors.

example, forest and agricultural lands may tend to occur together) 

can bias the interpretation of estimated parameters (King and 

others 2005).

Fourth, the influences of land uses on water quality are often 

nonlinear and parameters estimated using linear statistical models 

may be biased. For example, water quality generally responds 

nonlinearly to the amount of agricultural land, with streams 

remaining in good condition until the proportion of agricultural 

land within a catchment exceeds 30-50 percent (Allan 2004).

Within urban watersheds, a nonlinear response occurs when 

impervious cover exceeds about 10 percent of land area (Sun and 

Lockaby 2012).

The nonlinear response of water quality to land use demonstrates 

the importance of understanding spatial context in estimating how 

changes in forest cover affect hydrological systems. For example, 

throughout many regions in the Southern United States, forests 

are being converted to developed land uses and the amount of 

impervious cover is increasing. If the existing proportion of forest 

is less than the threshold value at which changes in impervious 

cover begin to substantially impact water quality, conversions 

to impervious cover may have minor impacts on water quality 

(fig. 3.2). In this case, linear estimates of the relationship 

between impervious cover and water quality degradation would 

overestimate the response. Above the threshold, linear estimates 

of the rate of change in water quality with respect to changes in 

impervious cover would underestimate the true relationship.
38 Chapter 3. Forest Ecosystem Services: Water Resources

Lastly, we note that scientific interest in the relationship between 

large-scale tree loss and alterations to the hydrological cycle is 

growing. Major structural changes in forest vegetation due to land 

conversion associated with afforestation, deforestation, forest 

degradation, desertification, and forest die-off are anticipated 

to alter complex, nonlinear feedbacks between land surfaces 

and the climate system in ways that are yet poorly understood 

(Bonan 2008). However, recent macrosystem ecological models 

linking forest losses with atmospheric fluxes indicate that 

changes in albedo and other components of energy balance will 

lead to significant increases/decreases in precipitation at both 

local and remote locations (Devaraju and others 2015). Better 

understanding of large-scale forest-atmospheric couplings is 

needed in an era of rapid and uncertain climate change (Stark and 

others 2016).

ECONOMIC VALUATION OF WATER RESOURCE 

ECOSYSTEM SERVICES

Water resources provide a variety of ecosystem services for both 

instream (e.g., fishing, boating) and diverted (e.g., residential, 

agricultural) uses. Some services conflict with each other, such 

as withdrawal for agricultural irrigation versus maintenance of 

natural flow regimes supporting endangered aquatic organisms. 

Other services are complementary, such as water stored in 

reservoirs for future residential consumption and water resource 

recreation such as swimming and boating. Decisions affecting 

the provision and allocation of water resource ecosystem 

services require measurements of the economic value of water in 

providing alternative benefits (Ward and Michaelson 2002, Young 

and Loomis 2014). Because forest cover influences water quality 

and quantity, land use decisions should consider how alternative 

land uses influence the suite of ecosystem services and values 

provided by water resources.

The concept of economic value often causes confusion in 

decisionmaking. This is because the economic value of a good 

or service often differs from its price. The market-clearing price 

for a given quantity of an ecosystem good or service can provide 

a good approximation of economic value if all of the inputs to 

its production are privately owned and the good is produced in 

a competitive market. This might be the case, for example, for 

bottled water produced from a privately owned spring. However, 

in many instances, hydrologic systems are public goods, not 

privately owned, and may be freely accessed (i.e., zero price). 

In this case, the economic value of water is what beneficiaries 

are willing to pay for it. WTP for public water resources is an 

expression of the demand for water resource ecosystem services 

by beneficiaries.

Valuation of Ecosystem Services: 

Production of Water Supplies

The beneficiaries of public water supplies include residential, 

agricultural, and industrial water users (Young and Loomis 2014). 

In the United States, water prices are often administratively 

determined and do not reflect actual supply and demand 

conditions. Statistical techniques have been frequently used to 

estimate water demand (WTP) functions that reveal the true 

economic value of public water supplies (Ward and Michelsen 

2002).9 In practice, WTP for water typically exceeds the amount 

paid for it, often by very large magnitudes (Olmstead 2010). 

Therefore, administered water prices do not provide reliable 

estimates of this ecosystem service value.

Estimates of the demand for public water supplies can be 

combined with information on the long-run marginal costs 

(LRMCs) of supplying increasing amounts of water to determine 

socially efficient prices for, and social value of, diverted water 

uses. LRMCs of water supply include the costs of collection, 

reservoir storage, treatment, distribution, anticipated future 

capital costs for new facilities, and the opportunity cost of 

water for other potential uses (Olmstead and Stavins 2009). 

Contributions of forest cover to reducing the LRMC of water 

supplies increase the social value of water by lowering the 

socially efficient price.

The ecosystem service value of water quantity can also be 

measured in hydrological systems where water is an input into a 

production process in which changes in water quantity ultimately 

influence productivity. For example, in many regions of the 

United States, water is used to irrigate crops. The economic 

benefits from alternative amounts of water being supplied for 

irrigation purposes can be measured using information on change 

in the value of agricultural crops produced and the change in 

the cost of production (Ward and Michelsen 2002).10 A similar 

approach could be used to measure the economic benefits of 

water supplies to industrial users.

The impact of forest cover on flood risk is a topic of increasing 

concern as more extreme precipitation is expected to accompany 

a warming climate (Donat and others 2016). Economic damage 

assessments from flooding provide estimates of losses sustained 

by a variety of economic sectors including private households, 

industry, agriculture, and infrastructure (Merz and others 2010).11

The greatest challenge in measuring the influence of forest cover 

on flood protection ecosystem services is to understand how 

9 As noted by Ward and Michelsen (2002), this method requires adequate 

variation in administered prices and quantities consumed in order to estimate 

water demand.

10 Economists have shown how preservation of (tropical) forest cover boosts 

agricultural production by increasing baseflow (Pattanayak and Kramer 2001).

11 These estimates typically include the costs of repair and recovery but do 

not consider how much people, or industries, would be willing to pay to avoid 

such damages.
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 39

forests influence water balances during extreme precipitation 

events. Understanding these relationships would allow the 

ecosystem service value of forests on flood risk to be measured 

using estimates of the damage cost avoided.

Valuation of Ecosystem Services: 

Production of Water Quality

Water quality can either be an intermediate input into a final 

ecosystem service or a final ecosystem service by itself. We first 

present an example of water quality as an intermediate input 

before going on to provide examples of water quality as a final 

ecosystem service.

Improvements in fish habitat—Consider an ecosystem service 

causal chain in which water quality influences fish habitat, which 

influences fish mortality and reproduction rates, which influence 

fish abundance, which influences the number of fish caught by 

anglers (Olander and others 2015). Because water quality is an 

intermediate input in the causal chain, the value of water quality 

to a specific class of beneficiaries (i.e., anglers) is estimated 

using information on its contribution to fish abundance and the 

economic value of fish abundance as an input to fishing.

Hundreds of economic studies have been conducted estimating 

anglers’ WTP to catch fish (some studies are for marine and 

others are for freshwater resources). The results of these studies 

are summarized in a meta-analysis that allows WTP values for 

catching a variety of freshwater (bass, muskellunge, pike, trout) 

and anadromous (salmon) fish species to be estimated (Johnston 

and others 2006). An example of how these data can be used to 

estimate the ecosystem service value of riparian reforestation 

along rivers in a watershed in south coastal Maine is provided 

by Johnston and Wainger (2015). By calibrating the relationship 

between riparian tree cover and brook trout abundance, and 

using results from the metaanalysis, the authors concluded that 

each 47 acres of riparian canopy restoration per 1,000 ft2 of river 

would increase the value per angler per fish caught by about 

50 percent. The authors provide a very useful discussion of the 

many assumptions that were necessary to reach this conclusion. 

They also note that other ecosystem service benefits of riparian 

canopy restoration (such as aesthetics) were not estimated.

Water treatment costs—Water quality is an input that is 

combined with capital and labor inputs in the production of 

potable water. Drinking water that meets quality standards is 

valued by consumers and is also required by Federal standards. 

One approach to valuation is to calculate the additional cost 

of assuring that drinking water meets those standards with 

degradation of water quality at water treatment plant intakes. 

Several economic analyses have been conducted to evaluate the 

impact of water quality on the cost of water treatment (Dearmont 

and others 1998, Forster and others 1987, Holmes 1988, Murray 

and Forster 2001). Each study used turbidity (water clarity) as the 

metric of input water quality. In these studies, multiple regression 

analysis was used to isolate the impact of turbidity on water 

treatment cost by controlling for other relevant variables (e.g., 

volume of water treated, wage rates, electricity costs). Although 

the impact of turbidity on water treatment cost varied across 

studies, each study found that increases in turbidity in raw water 

resulted in higher water treatment costs.

Water treatment cost studies have been used to estimate the 

value of specific water quality changes in water basins other than 

those included in the original research studies (Elsin and others 

2010). Using the Neuse River Basin in North Carolina as their 

study area, the authors estimated the net present value of future 

cost reductions to treatment facilities in this basin if specific 

turbidity level reductions were attained.12 Cost reductions 

associated with turbidity reductions in this watershed of 5 to 30 

percent were computed, resulting in cost savings ranging from 

approximately $1 million to $16 million. However, these authors 

did not describe how such reductions in turbidity levels might 

be attained.

Direct linkages between forest cover and water treatment 

costs have been recently explored in two studies. First, a study 

conducted in northeastern France using statistical analyses 

of spatially explicit data concluded that a 1-percent increase 

in regional forest cover (with equal reduction in agricultural 

land) reduced average water supply costs by about 1.3 percent 

(Abildtrup and others 2013). A similar approach was used in a 

study examining the impact of forest cover on water treatment 

costs in Malaysia (Vincent and others 2015). Using data on actual 

treatment costs and GIS data layers on virgin and logged forests, 

the authors found that avoiding conversion of 1-percent of virgin 

forest to non-forest use reduced treatment cost by 0.47 percent, 

and avoiding conversion of 1 percent of logged forest decreased 

treatment cost by 0.31 percent.

Within the United States, a recent study by the American Water 

Works Association (Warziniack and others 2017) surveyed 37 

water utilities in forested ecoregions to assess the impact of land 

use on water treatment costs. The study paired survey data on 

chemical costs for treatment (typically alum or other coagulants, 

polymers, copper sulfate, corrosion control chemicals, and 

disinfection chemicals) with data on water quality at the intakes 

and land use in the watershed. Figure 3.3 shows scatterplots of 

their data. They found that costs increased with both total organic 

carbon (TOC) and turbidity, and that both TOC and turbidity 

decreased with forest cover (the relationship between TOC and 

forest cover was negative but not statistically significant). While 

12 This was accomplished by assuming that the total change in turbidity level 

would take 5 years to accomplish and would be sustained for 25 years.
Log (cost)

Forest (%)

Log (turbidity)

0 .2 .4 .6 .8

2 3 4 5 6 2 3 4 5 6

Log (cost)

Forest (%)

Log (TOC)

0 .2 .4 .6 .8

40 Chapter 3. Forest Ecosystem Services: Water Resources

Figure 3.3— Empirical relationships between percent forest cover, total organic content (TOC), turbidity, and water 

treatment costs (cost) (Warziniak and others 2017).
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 41

the study was able to link forest cover to water quality, and water 

quality to treatment costs, there was too much noise in the data to 

directly link forest cover to treatment costs.

Water resource recreation and non-use values—Within the 

Southern United States, recreational uses of water resources are 

enjoyed by millions of people. About one-third of the population 

in the South, 16 years of age or older, engage either in boating 

or fishing activities and more than one-half engage in outdoor 

swimming (Cordell and others 1999). These usage rates are very 

similar to national averages and provide an indication of the 

importance of protecting water quality in the region and across 

the United States.

Hundreds of economic studies of the value of water quality have 

been conducted in the United States. Factors that influence the 

economic value of water quality have been identified using a 

statistical approach, known as meta-analysis, which summarizes 

the results of many previous studies (Johnston and others 2003, 

2005, 2016; Van Houtven and others 2007). The fundamental 

conclusion of these studies is that the economic value of water 

quality depends on the characteristics of the water bodies 

being studied as well as the characteristics of the population of 

people who use or care about those hydrological systems. For 

example, WTP typically varies with the size of the water quality 

change and average household income.13 Non-use values are 

also consistently found to be an important component of total 

economic value of water quality. However, the non-use values 

for water quality improvements are generally less than the 

use values.

GUIDELINES FOR ESTIMATING THE ECOSYSTEM 

SERVICE VALUES OF WATER RESOURCES 

FROM FOREST LANDSCAPES

The goal of ecosystem service valuation is to link, in a 

meaningful way, ecosystem service production functions (or 

assessments) with economic valuation functions (fig. 3.1). Here 

we describe the general steps to be followed in conducting largescale (e.g., statewide) ecosystem valuation assessments of water 

resources from forest landscapes. The guidelines we present 

are similar to general ecosystem service valuation assessments 

described elsewhere (Johnston and Waigner 2015, Olander and 

others 2015).

Step 1: Scoping

The first step in assessing ecosystem service values of water 

resources from forest landscapes is to identify the objectives of 

the analysis (fig. 3.4) This includes a description of the policy 

13 We note that Johnston and others (2016) found that economic value of water 

quality improvements in the Southeast United States exceeded values in other 

regions, and that a 1-percent increase in water quality increased water values by 

about 0.28 percent. This estimate of elasticity is similar, but smaller than, the 

elasticity estimate (about 0.42) reported for water quality in an earlier metaanalysis (Van Houtven and others 2007).

or management problem facing decisionmakers, consideration 

of the general issues that need to be addressed by analysis, and 

articulation of alternative approaches to providing desired results. 

Examination of trends in forest cover and the condition and use 

of water resources could help identify current and emerging 

problems. Engaging stakeholders at this stage can clarify 

how they would be affected by any potential changes in the 

provision of water resource ecosystem services. The result of the 

scoping phase will include a detailed description of the specific 

hydrological systems to be evaluated, what ecosystem services 

are to be measured and included in an economic assessment, and 

a good understanding of the specific groups of beneficiaries who 

would be impacted by changes in the flows of water resource 

ecosystem services.

Statewide analyses of alterations in water resource ecosystem 

services resulting from changes in forest cover need to identify 

specific locations where forest changes are anticipated to occur, 

perhaps using models of land use change. This element is critical 

in that forest loss (or gain) can have differential impacts on water 

quantity or quality depending upon the existing levels of forest 

cover and the physiographic region (Allan 2004, Boggs and 

others 2015, Sun and Lockaby 2012). This geographic-specific 

information could then be used to help identify the beneficiaries 

of changes in the flow of ecosystem services.

Step 2: Data Collection and Analysis

Once the goals and objectives of an ecosystem service valuation 

assessment have been identified, and the specific ecosystem 

services to be included in the analysis have been selected, the 

next step is to identify information needs. This step will likely 

involve an extensive review of the literature relevant to the 

specific ecosystem services selected. Ultimately, it is necessary 

at this stage to decide whether primary data, secondary data, or 

some combination of both, will be used for analysis. This requires 

decisions to be made on specific modeling approaches that will 

be used.

Primary data collection and analysis—Sophisticated 

measurement tools and modeling approaches are available to 

measure or predict water resource condition for specific forested 

watersheds (as described previously). These approaches are 

often used to assess the success or failure of a land management 

activity in research settings, to measure the effectiveness of 

BMPs, or to identify critical watersheds for conservation 

purposes. There may be some circumstances where direct 

measurements would be useful and a worthwhile investment for 

valuing water supplies from forest landscapes (e.g., comparing 

the relative value of land use choices for a specific watershed). 
Scoping

Identify ecosystem services, beneficiaries, and sites

Collect & analyze primary data

Use decision support models

Make Decisions

Estimate ecosystem service 

production functions

Model(s) of final water 

resource ecosystem services 

from forest landscapes

Model(s) linking water 

resource ecosystem services 

with economic valuation 

functions

Water metrics Land use metrics Revealed or stated 

preferences

Production/

cost functions Damage functions 

Estimate water resource 

valuation functions

Benefit transfers of 

water resource 

economic values 

Geospatial links of 

ecosystem and economic 

valuation models (e.g., 

INVEST, ARIES models)

Computations linking ecosystem service 

and economic valuation functions

Use look-up 

parameters based 

on literature review

Calibrate water 

resource production 

functions 

Water resource 

valuation functions 

(e.g., benefit 

transfers)

Water resource 

production from 

forests 

Yes

Yes

No

No

42 Chapter 3. Forest Ecosystem Services: Water Resources

Figure 3.4—Decision tree for estimating water resource economic values from forest landscapes.
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 43

Similarly, situations may arise where measurement of economic 

values of specific watersheds using revealed or stated preference 

methods would be warranted.

If primary data are to be collected and analyzed to provide a 

large-scale ecosystem valuation assessment, a sampling plan 

must be developed so that experimental results can be generalized 

to sampled populations. Watershed sampling plans should 

recognize and capture the diversity of forest types occurring in 

and across watersheds (such as riparian, plantation, and wetland 

forests) and the protection status of forests (such as public 

forests, private forests, and conservation areas). Economic 

valuation studies of forested watersheds need to consider the 

population of beneficiaries who value water resources (such 

as recreational users, people utilizing public water supplies, 

and people who value the existence of healthy hydrologic 

systems). It is also essential to keep in mind that the ecological 

indicators of inputs to the economic valuation functions (such as 

water clarity or frequency of floods) must be the outputs of the 

ecosystem production function. Without well-specified indicators 

of ecosystem services, it is not possible to estimate the value of 

water supplies provided by forest landscapes.

Secondary data collection and analysis—The major constraint 

to collecting and analyzing primary data at the statewide level 

is obtaining an adequate research budget, as such studies could 

easily cost hundreds of thousands of dollars. Thus, in most 

situations, large-scale analyses of the ecosystem service values 

of water from forest landscapes will rely upon the collection and 

analysis of secondary data (fig. 3.4).

The simplest approach to the use of secondary data would be 

to conduct a literature review, beginning with the literature 

presented in previous sections of this chapter. The goal of 

the literature review is to identify published scientific studies 

conducted in regions similar in character to the region that is the 

focus of the valuation study (called the policy area). Relevant 

studies can then be used to implement a process known as a 

benefit transfer (Johnston and others 2015, Rosenberger and 

Loomis 2003). The simplest benefit transfer methods apply unit 

values (such as average economic value per unit consumed) from 

an original study site to the policy area under consideration. 

This method ignores differences in characteristics between the 

original study site(s) and the policy site(s), as well as differences 

in the characteristics of beneficiaries and can lead to large errors. 

Consequently, it is not recommended unless no alternatives are 

possible or if the characteristics of the policy site and original 

study site are very similar.

A better approach is to use a function transfer that is based upon 

functions or statistical models developed in original studies 

that define relationships between dependent variables (such as 

WTP for water quality improvements) and a set of explanatory 

variables (such as the characteristics of the hydrologic system 

that was valued and the characteristics of beneficiaries). Function 

transfers are preferable to unit value transfers as they help to 

match the conditions in the original study area to the policy 

area. They require information on the values of the explanatory 

variables in the policy area.

Even more informative than the function transfer approach is to 

use the results of meta-regression analysis, which is a statistical 

model that summarizes the results of numerous original studies. 

Applications of this approach are limited to cases where an 

adequate number of high quality original studies are available to 

estimate a meta-regression model. Fortunately, for the purpose of 

economic valuation of water quality, several meta-analyses have 

already been conducted which may provide usable information 

for policy areas of interest (Johnston and others 2003, 2005, 

2016; Van Houtven and others 2007).

For the purposes of ecosystem service valuation of water supplies 

from forest landscapes, a benefit transfer process could be 

decomposed into the following steps:14

1. Confirm the feasibility of conducting a benefit transfer. This 

methodology depends upon the availability of high quality 

information from primary studies on both the ecological 

production function and the valuation function. If such 

information is not available, then primary data collection 

methods should be considered. Also, primary studies often 

report results for “iconic” sites, such as might be found in a 

National Park or Wilderness Area. If the policy site to which 

values are to be transferred to is more ordinary, then benefit 

transfer may not be appropriate.

2. Confirm that specific ecosystem services and beneficiaries 

are similar. If, for example, an original study provides 

economic values for improvements in water quality to 

recreational users of a reservoir, then using those values 

to describe the benefits of improvements in water quality 

to people who use the reservoir for drinking water would 

probably induce large errors.

3. Evaluate how the effects of changes in forest land use on 

water quality or quantity parameters might be quantified 

using secondary studies. Similar to concerns regarding the 

adequacy of economic value transfer methods, this step 

necessitates the availability of high quality information 

from primary studies linking forest cover with water quality 

or quantity.

4. Assure that the ecosystem service representing the output 

of the hydrological system(s) being evaluated is identical, 

or very similar, to the input(s) included in the economic 

valuation function.

14 The following is largely based upon Johnston and Wainger (2015).
44 Chapter 3. Forest Ecosystem Services: Water Resources

5. Choose the value transfer method and conduct the transfer. 

Decide whether unit values, transfer functions, or the results 

of meta-analyses are to be used both for the ecosystem 

service assessment and for economic valuation.

6. Use the selected methods to compute how historical or 

anticipated changes in forest cover in the policy area 

impact resulting water resource economic values. This step 

necessitates identification of the number of beneficiaries of 

the selected ecosystem services so that economic values can 

be aggregated over that population.

7. Conduct sensitivity analysis. Many assumptions may 

have been made in conducting both the ecosystem service 

assessment (i.e., impact of changing forest cover on 

water quantity and quality) and in economic valuation. 

Repeatedly recalculate ecosystem service values under 

alternative assumptions.

8. Report results. The results of analysis are reported to the 

relevant stakeholders. This could be policymakers, land 

managers, scientists, or the general public. Comparisons 

of management or policy alternatives may be facilitated 

by the use of alternative matrices or maps describing how 

ecosystem service values are impacted under alternative 

scenarios (Olander and others 2015).

Although benefit transfer methods can save costs, and are 

commonly used for ecosystem service valuation, researchers 

should be aware of two potential sources of error that can be 

introduced using this approach (Johnston and Wainger 2015, 

Rosenberger and Stanley 2006). Measurement errors occurring 

in primary studies used for transfer will carry over to transferred 

values, and these errors can be significant. Further, lack of 

similarity between site characteristics, valuation context, and 

human populations at the study sites and policy sites can cause 

generalization errors. Researchers using benefit transfer methods 

for valuing ecosystem services should attempt to minimize these 

errors to the extent possible.

Models and water resource data—In addition to using 

secondary studies to conduct value transfers of ecosystem 

service production and valuation functions, data and models are 

available to assist more complex ecosystem service valuations 

and decisionmaking. The emerging prevalence of spatially 

explicit data and GIS systems has supported the development 

of decision support tools to help agencies understand how 

management directed toward one ecosystem service affects 

other natural resource values (e.g., Bagstad and others 2012). 

The ecosystem service components of these models are typically 

complex and data intensive and require detailed information 

on selected ecosystem processes. In contrast, the economic 

component of these models is typically very simple and relies 

upon unit value transfers of ecosystem service values (Johnston 

and Wainger 2015).

Usually, preserving forests to maintain water quality improves 

other ecosystem services; that is, many ecosystem services are 

complementary to the provision of clean water. Sometimes, 

however, investments in watershed health come at the expense 

other ecosystem services. Grazing cattle, for example, is an 

important economic use on public lands, but it has traditionally 

had negative impacts on water quality.

Decision support tools have been used to understand spatially 

explicit ecosystem service flows and tradeoffs. The most widely 

known model for studying the landscape’s ability to provide 

ecosystem services and for analyzing tradeoffs in management 

activities is InVEST, produced by the Natural Capital Project 

(http://www.naturalcapitalproject.org/invest/). InVEST can be 

run independently, but it is most often used as a plug-in to a GIS 

program (for example, the ArcGIS ArcToolbox environment). 

The model populates predetermined ecological production 

functions with user-provided data to determine economic values 

of ecosystem services. InVEST models have been developed 

that link land use and land cover with water quality and quantity 

(Kareiva and others 2011). Nelson and others (2009), for 

example, use InVEST to evaluate impacts of land use changes 

on water quality, peak storm runoff, soil conservation, carbon 

sequestration, biodiversity, and marketed goods (timber, housing) 

in the Willamette Basin, Oregon. InVEST water quality and 

quantity models may be relatively simple (e.g., using data 

representing annual averages for entire watersheds) or more 

sophisticated (e.g., using measures of daily hydrology and water 

resource infrastructure). In general, the economic valuation 

component of these models is very simple and depends upon 

benefit transfer of unit values.

Balances and tradeoffs between water supplies and carbon 

sequestration can be evaluated using a decision support tool 

(Water Supply Stress Index) developed by the USDA Forest 

Service (http://www.forestthreats.org/research/tools/WaSSI). 

This model can be used to predict how climate, land cover, and 

changes in human populations may impact water availability and 

carbon sequestration at the watershed level. Other models capable 

of showing spatial tradeoffs in ecosystem services include ARIES 

(http://www.ariesonline.org/) and the Forest Ecosystem Services 

Toolkit (FEST) (http://forestecoservices.net/).

The U.S. Environmental Protection Agency has developed a 

public-domain Watershed Management Optimization Support 

Tool to model the effect of management decisions on watersheds. 
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 45

This decision support tool is designed to help local water 

resource managers and planners evaluate the economic costs, 

benefits, and tradeoffs involved with green infrastructure and 

land conservation decisions. The model addresses water flows 

but does not consider water quality. (https://cfpub.epa.gov/si/

si_public_record_report.cfm?dirEntryId=261780).

Agencies may also decide to conduct their own analyses of the 

value of water resource ecosystem services from forests using 

other data available for download. Some of the data sources that 

could be considered include the following:

Forests to Faucets — (http://www.fs.fed.us/ecosystemservices/

FS_Efforts/forests2faucets.shtml). These data are provided 

by the Forest Service and are available for download from 

the Geospatial Data Gateway that includes 12-digit watershed 

boundary (HUC-12) data.15 Within each HUC-12, data are 

provided on a number of variables including: population served 

by surface water intakes, mean annual water supply, percentage 

of forest, percentage of protected forest, percentage of National 

Forest System forest, percentage of private forest, percentage of 

forest highly threatened by insects and disease, percentage highly 

threatened by development, and percentage highly threatened by 

wildland fire.

Safe Drinking Water Information System — (https://www.

epa.gov/waterdata/safe-drinking-water-information-system). 

These data include information on public water systems 

including: water quality violation information for water 

systems, enforcement actions by States, and sampling results for 

unregulated contaminants and for regulated contaminants when 

the monitoring results exceed allowed level.

EnviroAtlas — (https://www.epa.gov/enviroatlas). Data and 

interactive tools are available for understanding the benefits 

that people receive from ecosystem services. Geospatial water 

resource data provided at the HUC-12 level include variables 

such as: agricultural water use, domestic water use, industrial 

water use, number of aquatic animal species, number of aquatic 

plant species, percentage of forest, percentage of forest land in 

buffer, percentage of cropland, percentage developed, percentage 

impervious, stream length, and stream length impairment.

ACKNOWLEDGMENTS

The authors gratefully acknowledge Rob Johnston, Clark 

University, and Pete Caldwell, USDA Forest Service, whose 

comments greatly improved this manuscript.

15 The United States is divided into nested hydrologic units. Each unit is identified 

by a unique Hydrologic Unit Code (HUC), ranging from regions (HUC 2-digit 

codes) to subwatersheds (HUC 12-digit codes). For hydrologic unit maps, see: 

http://water.usgs.gov/GIS/huc.html.

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Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 49

INTRODUCTION

F

orests provide various ecosystem services related to air 

quality that can provide substantial value to society. Through 

tree growth and alteration of their local environment, trees 

and forests both directly and indirectly affect air quality. Though 

forests affect air quality in numerous ways, this chapter will 

focus on five main ecosystem services or disservices related to air 

quality that have the potential to be estimated for forest stands:

(1) Air pollution removal and its effect on air 

pollution concentrations,

(2) Volatile organic compound emissions,

(3) Pollen emissions,

(4) Carbon sequestration, and

(5) Air temperature reduction.

The objectives of this chapter are to:

(1) Provide a background on how forests influence each of the 

above ecosystem services,

(2) Recommend methods on how to quantify the magnitude of 

these ecosystem services, and

(3) Review new approaches in assessing the value associated 

with these ecosystem services.

BACKGROUND

For each of the five air quality ecosystem services, this section 

will provide a brief description of: a) how forests impact the 

service, b) past forest ecosystem service assessments and 

approaches to value the ecosystem service, and c) challenges 

associated with estimating the service and values. However, 

before assessing ecosystem services and values derived from 

a forest, it is critical to assess the forest structure, as structure 

strongly influences the ecosystem services.

Chapter 4

Forest Ecosystem Services: 

Carbon and Air Quality

David J. Nowak, Neelam C. Poudyal, Steve G. McNulty

Assessing Forest Structure and Cover

There are four main steps needed to quantify ecosystem services 

and values from forests:

1. Quantify the forest structural attributes (e.g., number of trees, 

tree cover) that provide the service for the area of interest.

2. Quantify how the structure influences the ecosystem service 

(e.g., tree density, tree sizes, and forest species composition 

are significant drivers of carbon storage).

3. Quantify the impact of the ecosystem service, because it is 

typically the impact of the service on human health or other 

attributes of the environment that provide value to society.

4. Quantify the economic value of the impact of the 

ecosystem service.

In quantifying the forest structure (step 1), there are various substeps that could be followed:

a) Delimit the boundaries of the forest area of interest (study 

area) and determine the area of forest land.

b) Determine the percentage or amount of tree cover within 

the study area. This information can be derived from the 

National Land Cover Database (NLCD) (USGS 2015), but 

the 2001 NLCD data tended to underestimate tree cover 

(Nowak and Greenfield 2010). Cover data can also be 

photo-interpreted (e.g., Nowak and Greenfield 2012) using 

i-Tree Canopy (www.itreetools.org), which allows users 

to easily interpret Google images. However, depending on 

image resolution, all forest areas may not be interpretable. 

Tree cover maps have an inherent error that may or may not 

be known (often photo-interpretation is used to determine 

the map error). NLCD 2001 tree cover layers, on average, 

underestimate tree cover by 9.7 percent nationally, but the 

differences vary by region and land cover class (Nowak and 

Greenfield 2010). These data layers can be adjusted to meet 

photo-interpreted estimates, but there will be errors in the 

locations of adjusted tree cover. High resolution tree cover 
50 Chapter 4. Forest Ecosystem Services: Carbon and Air Quality

layers or data often produce more accurate maps, particularly 

when LIDAR is used, but also have errors that are often hand 

corrected. These hand-corrected data sets can have error rates 

< 5 percent. With photo-interpretation, the cover attributes 

are assumed to be classified without error and standard error 

of the estimates are reduced with increased sample size.

c) Determine the structural characteristics of the forest area 

(e.g., number of trees by species, diameter and condition 

class) by sampling the area of interest. This information 

can often be obtained from USDA Forest Service Forest 

Inventory and Analysis (FIA) data, particularly for rural 

forests. The most important forest structural attributes used 

in assessing forests effects on air quality include total tree 

biomass, tree condition, crown competition, and leaf area 

and leaf biomass by species.

d) If field data are not available, structural characteristics 

can be estimated by extrapolating a regional average of 

characteristics per unit tree cover (e.g., number of trees per 

hectare of tree cover) to tree cover in the area of interest.

Estimates based on measurements in the field assume that plot/

tree data are measured without error and sampled properly 

(e.g., random samples). Estimates from these data have an 

associated estimate of sampling error. When extrapolating 

regional standardized values per unit tree cover to the study area, 

additional uncertainty is added by assuming that the regional 

average applies to the condition of the study area, and there is 

also an additional sampling error in estimating tree cover in the 

study area (which is often quite small and can be calculated).

From these basic forest structural data, estimates of ecosystem 

service flows and values can be derived through process models 

and economic valuation procedures.

Air Pollution Removal and Its Effect 

on Air Pollution Concentrations

Biophysical service—Trees affect air quality through the 

direct removal of air pollutants, by altering local microclimates 

and building energy use, and through the emission of volatile 

organic compounds (VOCs) that can contribute to ozone (O3), 

carbon monoxide (CO), and particulate matter formation (e.g., 

Chameides and others 1988). However, integrative studies have 

revealed that trees, particularly low VOC-emitting species, can 

be a viable strategy to help reduce urban O3 levels (e.g., Taha 

1996). While all plants can impact air quality, trees tend to have 

greater impacts due to their larger leaf surface area. In general, 

the best tree species for improving air quality are species with a 

large healthy leaf surface area, relatively low VOC emissions, 

low maintenance needs, and a long lifespan (are adapted to the 

site conditions). Species that transpire more water will have a 

greater capacity to reduce air temperatures and remove gaseous 

pollutants. Species with more textured or waxy surfaces and 

smaller leaves are generally better at capturing particulate matter. 

In addition, evergreen species offer the ability to capture particles 

year-round.

Trees remove gaseous air pollution primarily by uptake through 

leaf stomata, though some gases are removed by the plant surface 

area. For O3, sulfur dioxide (SO2), and nitrogen dioxide (NO2), 

most of the pollution is removed via leaf stomata. Once inside 

the leaf, gases diffuse into intercellular spaces and react with 

inner-leaf surfaces or may be absorbed by water films to form 

acids (Smith 1989). Trees directly affect particulate matter in 

the atmosphere by emitting particles (e.g., pollen), intercepting 

particles, and resuspending particles captured on the plant 

surface. Some particles can be absorbed into the tree, though 

most intercepted particles are retained on the plant surface. The 

intercepted particles are often resuspended to the atmosphere, 

washed off by rain, or dropped to the ground with leaf and twig 

fall. During dry periods, particles are constantly intercepted 

and resuspended, in part, dependent upon wind speed. The 

accumulation of particles on the leaves can negatively affect 

photosynthesis (e.g., Darley 1971) and therefore potentially 

negatively affect gaseous pollution removal by trees. During 

precipitation, particles can be washed off and either dissolved 

or transferred to the soil. Consequently, vegetation is only a 

temporary retention site for many atmospheric particles, which 

are eventually moved back to the atmosphere or moved to the 

soil. Once in the soil, some chemical elements can be retained for 

substantial periods in slowly decomposable woody debris (Aber 

and Melillo 1982, Bieby and others 2011).

In addition to pollution removal via dry deposition, forests 

also affect local meteorology. Trees influence air temperature, 

radiation absorption and heat storage, wind speed, relative 

humidity, turbulence, surface albedo, surface roughness, and the 

atmospheric mixing-layer height. These effects consequently 

impact emission of pollutants from various sources and the 

concentration of pollutants in the atmosphere. For example, lower 

temperatures will reduce the emission of numerous biogenic and 

anthropogenic VOCs and other temperature-dependent pollutant 

emission sources (Cardelino and Chameides 1990). In addition, 

altering the local environment (e.g., air temperature reduction, 

shade, altered wind speeds) will affect building energy use and 

consequently emissions from power plants. Reductions in wind 

speed can reduce the dispersion of pollutants, which will tend to 

increase local pollutant concentrations as the pollutants are not 

dispersed as much with lower wind speeds. Subsequently, with 

slower winds the volume of the atmosphere where the pollutants 

mix can be reduced. This reduction in the “mixing height” will 

also tend to increase pollutant concentrations as the same amount 

of pollution is now mixed within a smaller volume of air (e.g., 

Nowak and others 2000).

Pollution removal by urban trees in the United States has been 

estimated at 711,000 tonnes (t) per year with average percentage 

air quality improvement in cities during the daytime of the 

season that vegetation is in-leaf typically < 1 percent (Nowak and 

others 2006). A more recent assessment of pollution removal by 

trees across the conterminous United States estimated pollution 

removal at 17.4 million t in 2010 (range: 9.0-23.2 million t) with 
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 51

96 percent of the pollution removal occurring in rural areas. 

This pollution removal also equated to an average air quality 

improvement of < 1 percent (Nowak and others 2014).

There are many factors that determine the ultimate effect of 

trees on air pollution. Integrative studies of tree effects on ozone 

pollution have illustrated how these various factors affect air 

quality. One model simulation illustrated that a 20-percent loss 

in forest cover in the Atlanta area due to urbanization led to a 

14-percent increase in ozone concentrations for a typical summer 

day (Cardelino and Chameides 1990). Although there were fewer 

trees to emit VOCs (chemicals that can contribute to ozone 

formation), an increase in Atlanta’s air temperatures due to the 

increased urban heat island, which occurred concomitantly with 

tree loss, increased VOC emissions from the remaining trees and 

other sources (e.g., automobiles) and altered the chemistry of 

ozone formation (e.g., reaction rates) such that concentrations of 

ozone increased.

Another model simulation of California’s South Coast Air Basin 

suggests that the air quality impacts of increased urban tree cover 

can be either positive or negative with respect to local ozone 

concentrations. However, the net basin-wide effect of increased 

urban vegetation is a decrease in ozone concentrations if the 

additional trees are low VOC emitters (Taha 1996).

Modeling the effects of increased urban tree cover on ozone 

concentrations in several cities from Washington, DC, to central 

Massachusetts revealed that urban trees generally reduce ozone 

concentrations in cities but tend to slightly increase average 

ozone concentrations regionally (Nowak and others 2000). As 

previously explained, the effects of trees on the physical and 

chemical environment demonstrate that trees can cause changes 

in pollution removal rates and meteorology, particularly air 

temperatures, wind fields, and mixing-layer heights, which, in 

turn, affect ozone concentrations. Changes in urban tree species 

composition had no detectable effect on ozone concentrations 

(Nowak and others 2000). Modeling of the New York City 

metropolitan area also reveals that increasing tree cover 

10 percent within urban areas reduced maximum ozone levels by 

about 4 parts per billion (ppb), which was about 37 percent of the 

amount needed for air quality standards attainment (Luley and 

Bond 2002). 

Though reduction in wind speeds can increase local pollution 

concentrations due to reduced dispersion of pollutants and mixing 

height of the atmosphere, altering wind patterns can also have a 

positive effect. Tree canopies can potentially prevent pollution in 

the upper atmosphere from reaching ground-level air space. For 

example, measured differences in ozone concentration between 

above- and below-forest canopies in California’s San Bernardino 

Mountains have exceeded 50 ppb (equivalent to a 40-percent 

improvement below the canopy) (Bytnerowicz and others 1996). 

Under normal daytime conditions, atmospheric turbulence mixes 

the atmosphere such that pollutant concentrations are relatively 

invariant with height. Forest canopies can limit the mixing of 

upper air with ground-level air, leading to significant belowcanopy air quality improvements. Standing in the interior of 

forest stands can offer cleaner air if there are no local ground 

sources of emissions (e.g., from automobiles). Various studies 

have illustrated reduced pollutant concentrations in the interior 

of forest stands compared to outside of the forest stand (e.g., 

Cavanagh and others 2009, Dasch 1987). However, where 

there are numerous pollutant sources below the canopy (e.g., 

automobiles), the forest canopy could increase concentrations by 

minimizing the dispersion of the pollutants away from ground 

level (Gromke and Ruck 2009, Salmond and others 2013, Vos 

and others 2013, Wania and others 2012). This effect could 

be particularly important in areas with heavy tree canopy and 

vehicle traffic.

Economic valuation—The values associated with reduced air 

pollution concentrations are generally related to improved human 

health, improved visibility, and reduced damage to materials, 

plants, and ecosystems. Some studies have used “externality” 

values to estimate the value of pollution removal. For example, 

the value of the 711,000 t removed per year by U.S. urban forests 

was estimated at $3.8 billion using externality values (Nowak 

and others 2006). In this context, “externality” values are the 

estimated cost of pollution to society that is not accounted for 

in the market price of the goods or services that produced the 

pollution. There are a few studies that have linked pollution 

removal and improved health, including one in London where 

a 10 × 10 km grid with 25-percent tree cover was estimated to 

remove 90.4 t of PM10 annually, which equated to the avoidance 

of two deaths and two hospital admissions per year (Tiwary and 

others 2009). In addition, Nowak and others (2013) reported that 

the total amount of PM2.5 removed annually by trees in 10 U.S. 

cities in 2010 varied from 4.7 t in Syracuse to 64.5 t in Atlanta. 

Estimates of the annual monetary value of human health effects 

associated with PM2.5 removal in these same cities (e.g., changes 

in mortality, hospital admissions, respiratory symptoms) ranged 

from $1.1 million in Syracuse to $60.1 million in New York City. 

Mortality avoided was typically around one person per year per 

city, but was as high as 7.6 people per year in New York City. 

Most of the health values came from reduced mortality, which 

was estimated based on the value of a statistical life (e.g., Viscusi 

and Aldy 2003). The human health value of the 17.4 million t of 

air pollution removed by conterminous U.S. forests in 2010 was 

$6.8 billion (Nowak and others 2014). Sixty-seven percent of the 

pollution removal value occurred in urban areas. Health impacts 

included the avoidance of more than 850 deaths and 670,000 

incidences of acute respiratory symptoms. Health valuation 

is based on the U.S. Environmental Protection Agency (EPA) 

BenMAP model procedures that estimate the health impacts 

and monetary value when populations experience changes in air 

quality (Abt Associates 2010, Davidson and others 2007, U.S. 

EPA 2012). The health value varies spatially based on changes 

in pollution concentration and the number and age of people 

receiving that change in concentration.
52 Chapter 4. Forest Ecosystem Services: Carbon and Air Quality

Challenges in estimating air pollution impacts—Computer 

modeling has overcome some of the challenges related to 

quantifying the impacts of trees on air pollution concentrations. 

Though the models can always be improved, the greatest 

challenges are related to quantifying the secondary effects (i.e., 

tree effects on energy use, pollution emission and formation, 

and effects of tree VOC emissions on secondary pollutant 

formation [see below]). Tree effects on ozone concentrations are 

particularly challenging to quantify due the numerous influences 

that trees have on this secondary pollutant. In addition, modeling 

could be refined to explore marginal returns of pollution removal 

to determine potential diminishing returns per unit tree cover with 

additional tree cover.

Volatile Organic Compound Emissions

Biophysical service—Trees can reduce air pollution by changing 

the local microclimate and directly removing pollution, but 

trees can also emit various chemicals that can contribute to air 

pollution, such as volatile organic compounds (e.g., isoprene, 

monoterpenes). These compounds are natural chemicals that 

make up essential oils, resins, and other plant products, and may 

be useful in attracting pollinators or repelling predators (Kramer 

and Kozlowski 1979). Complete oxidation of VOCs ultimately 

produces carbon dioxide, but carbon monoxide is an intermediate 

compound in this process. Oxidation of VOCs is an important 

component of the global carbon monoxide budget (Brasseur and 

Chatfield 1991).

Emissions of VOCs by trees and other sources can also contribute 

to the formation of ozone and secondary aerosols (e.g., Poschl 

2005). Because VOC emissions are temperature dependent 

and trees generally lower air temperatures and remove ozone, 

increased tree cover can lower overall VOC emissions and, 

consequently, ozone levels in urban areas (e.g., Cardelino and 

Chameides 1990, Nowak and others 2000, Taha 1996). VOC 

emissions from urban trees generally are < 10 percent of total 

VOC emissions in urban areas (Nowak 1992). 

VOC emission rates vary by species (e.g., Guenther and others 

1994). Seven tree genera that have the highest standardized 

isoprene emission rate, and therefore the greatest relative 

effect on increasing ozone, are: sweetgum (Liquidambar spp.), 

black gum (Nyssa spp.), sycamore (Platanus spp.), poplar 

(Populus spp.), oak (Quercus spp.), black locust (Robinia

spp.), and willow (Salix spp.). However, due to the high degree 

of uncertainty in atmospheric modeling, results are currently 

inconclusive as to whether these genera will contribute to an 

overall net formation of ozone in cities (i.e., whether ozone 

formation from VOC emissions are greater than ozone removal 

or whether increasing tree cover reduces VOC emissions through 

temperature reduction).

Globally, average emission factors for isoprene are 12.6 mg per 

m2 per hour for broadleaf trees and 2.0 mg per m2 per hour for 

non-broadleaf evergreen trees (Guenther and others 2006). In the 

United States, emission factors for monoterpenes are 449.2 μg 

per m2 per hour for broadleaf trees and 872.6 μg per m2 per hour

for needle leaf trees (Sakulyanontvittaya and others 2008).

Economic valuation—The negative impacts of biogenic VOC 

emissions are often not directly associated with the emissions 

themselves, but rather the formation of secondary chemicals due 

to the VOCs emission (e.g., ozone, carbon monoxide, particulate 

matter). Thus, the valuation of VOC emissions is more dependent 

upon the impacts of the secondary chemicals that the VOCs help 

form (e.g., human health effects). The valuation of VOCs would 

likely best be done by valuing the impacts of the secondary 

pollutants as detailed in the air pollution removal section, 

but instead of the positive effect from pollution removal, the 

valuation would be a negative effect due to pollution formation.

Challenges in estimating the negative impacts of VOC—

Due to the complexity of the atmosphere and chemical reactions, 

it is challenging to quantify the amount of secondary pollutants 

formed due to VOC emissions. To a lesser extent, quantifying 

total VOC emissions from a forest area is also challenging due 

to the number of VOC chemical species emitted. Methods for 

quantification of isoprene, monoterpenes, and some other VOC 

emissions by trees have been extensively addressed (e.g., U.S. 

EPA 2015, Washington State University 2015).

Pollen Emission

Biophysical service—Pollen emission is another air quality issue 

related to forests. While pollen plays an important ecological 

role, it does have the potential to negatively affect humans by 

causing allergic reactions (Puc 2003). While the proximity of 

trees to people is an important factor related to pollen allergies, 

various attributes of the forest influence allergic responses to 

pollen production. These attributes include: a) plant species 

composition, size, and abundance; b) allergenic potential of 

species (i.e., the relative potential of the pollen to cause an 

allergic reaction based on its shape and composition) (e.g., 

Ogren 2002); and c) length of pollination period (Carinanos and 

others 2014). Various studies have analyzed allergic responses to 

common tree species (e.g., Strandhede and others 1984).

Economic valuation—Valuation of the negative impacts of 

forest pollen production is difficult. Several factors need to be 

considered including pollen exposure to humans by species with 

varying levels of allergenicity, quantifying the impact of that 

exposure to human health, and then determining the economic 

cost of the health impacts.

Challenges in estimating the negative impacts of pollen—The 

first challenge in quantifying the forest’s role in pollen formation 

is quantifying the pollen allergenicity of forest trees (e.g., Ogren 

2002), then estimating the exposure of people to the pollen from 

the forest. Further challenges relate to quantifying the health and 

economic impact on the human population that is affected by the 

forest pollen.
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 53

Carbon Sequestration

Biophysical service—Trees, through their growth process, 

remove carbon dioxide from the atmosphere and sequester the 

carbon within their biomass. When a tree dies and the wood is 

allowed to decompose or is burned, most of the stored carbon 

goes back to the atmosphere, though some of the carbon can 

be retained in soils (or wood products). Thus, the net carbon 

storage in a given area with a given tree composition will cycle 

through time as the population of trees grows and declines 

(e.g., through aging and harvest). When forest growth (carbon 

accumulation) is greater than decomposition, net ecosystem 

carbon storage increases.

Human influences on forests (e.g., management) can further 

affect CO2 source/sink dynamics of forests through such factors 

as fossil fuel emissions from machinery used for management 

and harvesting/utilization of biomass (Nowak and others 2002). 

Management choices such as fertilization and rotation length 

also affect carbon dynamics (Johnson 1992, Noormets and 

others 2015). For example, soils are often lacking in nitrogen or 

phosphorus, so the addition of these fertilizers can significantly 

increase tree growth and carbon sequestration (Oren and others 

2001). However, fertilization during a drought period can worsen 

the drought impacts and significantly reduce carbon sequestration 

due to reduced transpiration and canopy conductance per unit 

leaf area, possibly due to structural and physiological changes in 

fine root area or hydrologic conductivity (Ward and others 2015). 

Prescribed burning immediately releases some carbon to the 

atmosphere but can also release nutrients tied up in understory 

vegetation that in turn make the nutrients more available to 

the trees and increase forest growth and carbon sequestration 

(Johnson and others 2014). Both air quality and climate change 

affect tree growth and consequently carbon sequestration by 

forests (Aber and others 1995, Sitch and others 2006). Longer 

growing seasons and increased precipitation are predicted to 

increase southern U.S. pine forest productivity (McNulty and 

others 1996). Through their influence on air temperature, trees 

also affect building energy use and consequently alter carbon 

emissions from sources such as power plants.

Above- and below-ground biomass in all forest land across the 

United States, which includes forest stands within urban areas, 

stored approximately 20.2 billion tonnes of carbon in 2008 

(Heath and others 2011). Factors that influence carbon storage 

and sequestration include tree size, species, tree density, tree 

health, and tree growth rates.

Economic valuation—Current carbon valuation is typically 

based on the social cost of carbon as reported by the Interagency 

Working Group on Social Cost of Carbon or SCC (2013). Social 

cost associated with a pollutant (e.g., CO2) refers to an estimate 

of total (global) economic damage attributable to incremental 

increase in the level of that particular pollutant in a given year. 

The current value (in 2015) is $38 per metric ton of CO2 based 

on a 3-percent discount rate. The cost of carbon emissions 

varies through time. The market price of carbon offset credits on 

commercial and regional trading platforms has also been used to 

represent the value of avoided carbon emissions to landowners 

(Hein 2011). Using the SCC, the total value of avoided damage 

attributable to potential destruction of all forests could be 

obtained by multiplying $38 by the CO2 equivalent of all of 

the carbon stored in forests. On the other hand, if the objective 

is to estimate value of avoided damage attributable to a flow 

(of carbon to atmosphere) rather than stock, the cost could be 

multiplied by the annual rate of carbon sequestration.

Challenges in estimating carbon sequestration—Given 

the amount of forest data related to tree size, density, species 

composition, etc., collected by the Forest Service FIA program 

(USDA Forest Service 2016), the various forest carbon 

calculators (e.g., USDA Forest Service 2015) and carbon 

calculation procedures (Eve and others 2014), this service is 

relatively easy to calculate and value using either the SCC or the 

current price from an offset market.

Air Temperature Reduction

Biophysical service—Air temperature affects human health and 

well-being both directly and indirectly through its influences on 

the environment. These influences include effects on building 

energy use, human comfort and health, evaporative cooling, 

ozone production, and pollutant emissions. Urban areas tend 

to create heat islands that, on average, tend to be warmer than 

surrounding rural areas (e.g., Howard 1818, Oke 1973). Reducing 

air temperatures by a few degrees can have a significant 

economic impact through reduced energy use and improved 

human health.

Heat waves in cities can cause hundreds and sometimes 

thousands of human deaths. More than 700 deaths in Chicago 

were attributed to a heat wave in July 1995 (U.S. EPA 2006). 

Over 30,000 excess deaths were related to the heat waves 

in Western Europe during the summer of 2003 (Golden and 

others 2008). Forests reduce air temperatures mainly through 

transpirational cooling, shading of surfaces, and altering wind 

speeds. While forests can increase air temperature in winter 

relative to open spaces, they tend to reduce average and extreme 

high temperatures during the summer (Boggs and McNulty 2010, 

Karlsson 2000, Spurr and Barnes 1980).

Air temperature affects numerous attributes of the environment. 

It affects other ecosystem services such as evapotranspiration, 

and it also impacts biogenic emissions, anthropogenic emissions, 

and pollution formation. Air temperature also directly affects 

human comfort and human health (e.g., Harlan and others 2014, 

Martens 1997).

Economic valuation—Valuation of the effects of air temperature 

could be done by quantifying the impact of air temperatures on 

energy use and resulting emissions and human morbidity and 

mortality. Once these relationships are determined, the impacts 

could be valued based on energy costs, externality costs of 
54 Chapter 4. Forest Ecosystem Services: Carbon and Air Quality

emissions, and the statistical value of human life. Recent studies 

have used multivariate regression techniques to directly link 

forest coverage with mortality, while controlling for other factors 

that impact human health (e.g., Walton and others 2016).

Challenges in estimating forest impacts on air temperature—

The relationship between forests and air temperature are well 

understood (Huang and others 1987, Kurn and others 1994). 

However, challenges still remain in modeling air temperatures 

and their impacts on other ecosystem services and human health 

and comfort.

BIOPHYSICAL QUANTIFICATION OF 

ECOSYSTEM SERVICES

Three of the five air quality ecosystem services can currently 

be assessed (air pollution removal, VOC emissions, and carbon 

sequestration), while others need more research and development 

(i.e., pollen, air temperature reduction). The following text details 

how these services can or could be assessed.

Air Pollution Removal and Impacts 

on Air Pollution Concentrations

Pollution removal by trees and forests, along with its health 

effects and values, has been estimated for the conterminous 

United States using models that incorporate U.S. hourly 

weather and pollution monitor data, national tree cover maps, 

and U.S. Census data (Nowak and others 2014). These data are 

incorporated within i-Tree Canopy, Design and Landscape to 

allow managers to roughly estimate the quantity and health value 

of air pollution removal by trees and forests.

In addition to pollution removal by trees, various model 

calculations in i-Tree are used to estimate the consequent 

effects on pollution concentrations and human health (e.g., 

Nowak and others 2013). The U.S. EPA BenMAP program was 

used to estimate the incidence of adverse health effects (i.e., 

mortality and morbidity) and associated monetary value that 

result from changes in NO2, O3, PM2.5, and SO2 concentrations 

due to pollution removal by trees. The model estimates assume 

that: a) the measured inputs (meteorology and pollution 

concentrations) represent the conditions in the region around 

the monitors; b) the boundary layer is well mixed; c) input 

variables are correctly measured; d) the dry deposition model 

in i-Tree accurately portrays pollution removal (Hirabayashi 

and others 2011, Morani and others 2014); and e) BenMAP 

accurately estimates and values health effects due to changes in 

pollution concentrations.

Under most situations, atmospheric acid deposition of NOx 

and SOx are below levels that cause reductions in forest health. 

However, a combination of high acidic deposition and/or low soil 

acid buffering capacity can result in forest soils exceeding the 

critical acid load level in places. At this point, the forest soil is 

termed to be “in exceedance” of the critical acid load. The trees 

growing on soils that are in exceedance are much more likely 

to experience reductions in growth and increased risk of early 

mortality. Additionally, excess acids can leach into streams and 

thereby reduce water pH and aquatic biodiversity. Simple mass 

balance equations are typically used to estimate critical acid 

loading and to identify forest areas that are in exceedance of 

their critical acid load. For example, McNulty and others (2007) 

applied this approach to the conterminous United States at a 1-km 

resolution and found that the region with the largest proportion 

of forest area in exceedance of the soils critical acid load was 

the Northeast. Forest harvesting and base cation fertilization 

(e.g., the use of calcium carbonate lime) are two methods used to 

either remove acids from the ecosystem or neutralize acidic soil. 

Through a combination of forest growth and harvest, trees can be 

used to remove excess acid from forest soil, which will improve 

both terrestrial and aquatic ecosystem health.

Volatile Organic Compound Emissions

VOC emissions from forests can be quantified using either 

a) the Biogenic Emissions Inventory System (BEIS) model 

methodology (U.S. EPA 2015), which is also incorporated 

into the i-Tree model (www.itreetools.org), or b) the MEGAN 

Model - Model of Emissions of Gases and Aerosols from Nature 

(Washington State University 2015). Both models estimate VOC 

emissions from trees and forests, making various assumptions 

and using various structural and meteorological inputs. While 

assumptions can always be questioned, these models are likely 

the best available options for estimating plant VOC emissions. 

Neither model estimates the secondary impacts (e.g., ozone 

formation) or the value of changing VOC concentrations. More 

research is needed on these topics.

Pollen Emissions

There are databases on pollen allergenicity of numerous tree 

species and methods to estimate pollen allergenicity index 

for areas with tree cover. For example, the i-Tree model has 

a prototype allergenicity index that could be used to rate 

allergenicity of forests. This module has not been released yet 

and is similar to the index used in Carinanos and others (2014). 

However, these index values have not yet been linked to impacts 

on human health (e.g., allergies). More research is also needed on 

this topic.

The main assumptions of the pollen index approach are that the 

allergenicity ratings of tree species are correct and that pollen 

emissions are related to plant crown/leaf volume or biomass.

Carbon Sequestration

Carbon storage and sequestration by forests can be estimated 

using Forest Service forest carbon calculators (e.g., USDA Forest 

Service 2015), urban forest calculators (e.g., i-Tree), or carbon 

calculation procedures detailed in Eve and others (2014).
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 55

There are various carbon equations used to estimate carbon 

storage by trees, and it is assumed that these equations accurately 

estimate carbon based on the measured structural data (e.g., 

species, diameter, height). Sequestration rates are based on 

estimates of annual tree growth. Although there are limitations, 

the procedures used to estimate carbon stocks and flows are 

pretty well established and accepted.

Air Temperature Reduction

Satellites can be used to measure surface temperatures (e.g., 

NASA 2015, Sobrino and others 2004). For example, land surface 

temperature maps can be downloaded at neo.sci.gsfc.nasa.gov/

view.php?datasetId=MOD11C1_M_LSTDA&date=2015-01-01. 

Various models can also be used to estimate air temperatures 

(e.g., Chen and others 1993, Yang and others 2013). However, 

there are limited procedures or models showing how forests and 

others surfaces affect air temperatures.

Use of land surface temperatures is based on a reasonable 

assumption that these temperatures are related to air 

temperatures. However, while surface temperatures influence 

local air temperatures, they can be quite different from air 

temperatures. Models used to estimate air temperatures make 

various assumptions about the atmosphere and earth surfaces 

to produce reasonable estimates of hourly air temperatures and 

temperature variations, but more research is needed on this topic.

ECONOMIC VALUATION OF ECOSYSTEM SERVICES

Once the flow or provision of the good or service (e.g., carbon, 

air pollution removal) is quantified, various methods of market as 

well as non-market valuation can be applied to characterize their 

value. Since none of these services (perhaps except for carbon 

sequestration) are currently traded in the market, non-market 

valuation methods are used to estimate their values. Methods of 

non-market valuation can be pecuniary or non-pecuniary. We 

focus on pecuniary methods that obtain the money equivalent 

value of a service. There are also non-pecuniary methods for 

characterizing value in other than monetary terms, such as 

number of human lives saved, number of clear days observed etc.

This section introduces market and non-market valuation 

methods that are potentially applicable in valuing one or more air 

quality services (table 4.1), provides guidance on choosing the 

most appropriate method, and discusses important considerations 

in benefit aggregation.

Market Price Method

This method relies on the prevailing price for the service as 

traded in the local market. Since many of the air quality services 

are not currently traded in the market, this method is not 

applicable except in the case of carbon sequestration. Carbon 

offset credits are currently traded in national and international 

cap-and-trade institutions and other “over-the-counter” voluntary 

transactions. Market prices are typically less than the SCC, 

because the transactions are motivated by the expected benefits 

and costs to individual sellers and buyers, reflecting both their 

preferences and the regulatory framework, and hence do not 

necessarily take account of all of the social benefits associated 

with sequestration or reduced emissions. Price of emission 

permits for other kinds of air pollutants (e.g., SO2) represent the 

value of abatement service that forests provide, provided we can 

attribute such service to forests and assuming that the current 

policy regime will continue. However, the market prices of such 

services could be distorted by lack of information and failure 

to capture external benefits of production. Moreover, the price 

of such a permit or offset credit is strongly influenced by the 

regulatory environment (i.e., whether the emitters are subject to 

mandatory regulation to offset their emission).

Contingent Valuation Survey Method

This method relies on asking people to state their willingness 

to pay (WTP) to consume or enjoy the benefit of a given air 

quality service by forests. Once the service provided by forests 

to improve the air quality is defined and quantified, a randomly 

selected sample of potential beneficiaries is asked to express their 

WTP to maintain a specified area of forest for the purpose of 

providing the service. The most common approach is to split the 

sample and ask different groups whether they would be willing 

to pay a specified amount that varies across groups. Typically, 

the WTP estimated at household level is extrapolated to an entire 

population to get the total value of the service attributable to a 

forest area. Dividing the total estimate by total hectares of the 

specified forest could yield value on a per-hectare basis, which 

provides an approximate measure to evaluate the marginal 

impact of forest area change. A similar approach can be taken 

by surveying how much forest landowners are willing to accept 

(WTA) in compensation for delaying or forgoing their harvest 

in favor of air pollution removal or carbon storage. Such an 

agreement would require landowners to forgo all other economic 

interests for a specific period of time, and their stated WTA to 

commit to this agreement is considered a proxy of the production 

cost of air quality. A few studies have applied the contingent 

valuation method to estimate landowners’ WTA and buyers’ 

WTP for carbon services (Poudyal and others 2012, Tsang and 

Burge 2011).

This method assumes that people will do what they say, and it is 

sensitive to how the WTP question is designed and how nonresponses (or refusals) are factored into benefit estimation. The 

questionnaire needs to be very specific in attributing the benefit to 

the forest of interest. It is worth noting that Zhang and Li (2005) 

have argued that the value of a good or service can be more 

accurately approximated by deriving a shadow price from the 

opportunity costs of the resources involved, rather than eliciting 

producers’ WTA. However, caution is required here because the 

full value, as captured by WTA, may be greater than the costs 

of acquisition. Despite the limitations, when there are no prior 
Table 4.1—Summary of applicable valuation methods and example application by forest ecosystem service types

Method Ecosystem service Applicabilitya Example application (where available)

Market priceb Air pollution removal

VOC removal

Pollen emission 

Carbon sequestration Jerath and others (2012), Hein (2011)

Air temperature Pandit and Laband (2010)

Value of statistical life saved Air pollution removal Levinson (2012)

VOC removal

Pollen emission 

Carbon sequestration

Air temperature

Contingent valuation Air pollution removal

VOC removal

Pollen emission 

Carbon sequestration Carlsson and others (2010), Jerath and others (2012)

Air temperature Carlsson and others (2010)

Replacement or substitute cost 

method

Air pollution removal

VOC removal

Pollen emission 

Carbon sequestration Platinga and Miller (1999), Richards and others (1993)

Air temperature

Hedonic method Air pollution removal Luechinger (2009)

VOC removal

Pollen emission 

Carbon sequestration

Air temperature Pandit and Laband (2010)

Damage cost avoidedb Air pollution removal Hein (2011)

VOC removal

Pollen emission 

Carbon sequestration Interagency Working Group on Social Cost of Carbon 

(2013), Jerath and others (2012)

Air temperature

Life satisfaction or happiness method Air pollution removal Levinson (2012), Welsch (2009), Luechinger (2009)

VOC removal

Pollen emission 

Carbon sequestration

Air temperature Rehdanz and Maddison (2005), Levinson (2012)

Benefit transfer Air pollution removal

VOC removal

Pollen emission 

Carbon sequestration Moore and others (2013)

Air temperature

a Applicable to ecosystem service if checked.

b Interrelated, when the damage involves market goods/services.

56 Chapter 4. Forest Ecosystem Services: Carbon and Air Quality
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 57

studies of the value of a good and no related market behaviors 

that indirectly reveal the value, contingent valuation may be the 

only way to obtain an estimate of the value of the service.

Replacement or Substitute Cost Method

This cost-based method relies on the assumption that the value of 

a given ecosystem service provided by forests is equivalent to the 

cost of providing such a service by some alternative or artificial 

means. For example, the value of forest carbon sequestration, 

as typically measured in per metric ton of CO2 sequestered, 

would be estimated as the cost of offsetting equivalent CO2 from 

forest projects such as afforestation (Platinga and Miller 1999) 

or non-forest projects such as methane capture, agriculture soil 

carbon, or renewable energy. Similarly, various kinds of indoor 

ventilation and air purifying or conditioning systems have been 

designed to regulate VOCs in air, and the cost of acquisition 

and operation of such devices could offer a surrogate “price” for 

estimating the value of services like VOC removal by forests.

This method is reliable only if: (1) the service provided by 

forest is the same (in nature and quality) as that provided by 

an alternative project; (2) the alternative is the next least-cost 

means for providing the service; and (3) the benefits of the 

service provided by the alternative project exceed the cost of 

the alternative project (Brown 2017). While air quality and 

carbon-related services provided by forests and alternative 

means are likely to be similar in nature and quality, their level 

of provision and therefore their costs are likely to be determined 

by the regulatory framework, meaning that the benefits do 

not necessarily exceed the costs. While these are significant 

limitations on use of this method to estimate values, it can 

be used to quantify the cost-effectiveness of forests as a way 

to meet externally set standards such as national ambient air 

quality standards.

Hedonic Method

Even though no markets exist to observe financial transactions 

involving forest ecosystem services related to air quality, their 

benefit can be revealed by examining whether and how the 

change in supply of such a service is compounded in a related 

good for which market prices are available. The hedonic method 

is particularly applicable to valuing air pollution removal, due 

to the local nature of the benefits. In the case of air quality or 

volatile organic compounds, the price (or rent) of a residential 

house is a market value that relates directly to the air quality 

in the neighborhood. By regressing prices of properties against 

their structural features and some measure of air quality (e.g., air 

pollutant concentration), one could estimate the implicit value 

of a marginal unit reduction in a pollutant. The implicit marginal 

willingness to pay (WTP) for air quality improvement can be 

obtained from the regression. The value of this service can be 

obtained on a per-hectare basis by multiplying the resulting WTP 

by the rate of pollution removal (amount removed by a hectare 

of forest).

Damage Cost Avoided Method

When a damage can be avoided with a given ecosystem service 

in place, then the avoided cost of the damage is one value of 

that ecosystem service. One measure of the damage cost is the 

amount that society is willing to pay to avoid the damage, and 

thus insurance premiums are sometimes used to estimate the cost. 

In other words, if society incurs a cost to avoid a damage, then 

the worth of an ecosystem service that prevents that damage is at 

least as much as the cost incurred.

The SCC is a type of damage cost avoided, as it involves 

projecting the physical damage (including change in agricultural 

productivity, human health, property damage, etc.) from CO2, 

and then estimating the monetary value of that damage (Pizer and 

others 2014). Avoided damage due to the sequestration (capture 

and long-term storage) of carbon by a forest can be interpreted 

as the value of carbon service for a given forest stand. The 

global SCC is estimated at $38 per metric ton of CO2 based on 

a 3-percent discount rate (Interagency Working Group on Social 

Cost of Carbon 2013).

This method could also be applied to estimate the value of the 

pollen emission disservice. If one knows how the amount of 

pollen emitted per forest area relates to the number of allergyrelated illnesses, then the total public expenditure on allergy 

medications (i.e., cost of illness) could be used to obtain a lower 

bound on the value of the disservice (assuming that the total cost, 

or utility lost, due to allergies is greater than the expenditures).

Value of Statistical Life Saved Method

This method can be considered similar to the method of damage 

cost avoided with particular relevance in human health. It has 

been widely applied in risk and health economics studies (Viscusi 

and Aldy 2003). Forest ecosystem services like reduction in air 

pollution can be linked with positive health outcomes among the 

human population. The assumption here is that people are WTP 

for the marginal reduction in mortality attributable to a change in 

forest cover or condition. The benefit of a marginal reduction in 

mortality is the monetary equivalent of the reduction of mortality 

risk from one to none. For example, if the removal of x metric 

tons of air pollution as a result of expansion of y hectares of 

forest reduces the morality risk by 1 in 1 million for 2 million 

people, the air pollution control service provided by y hectares 

of forest is 2 avoided deaths. Multiplying this value by the 

statistical value of a life saved yields the total value of the service 

attributable to y hectares of forest.The statistical value of life has 

been estimated by contingent valuation and by hedonic wage 

models, in which a regression analysis quantifies the tradeoffs 

people are willing to make between fatality risks and wage rates. 

Federal agencies like the U.S. EPA and U.S. Department of 

Transportation use $7.4 million (mean estimate based on several 

wage-risk studies and contingent valuation survey) (U.S. EPA 

2010) and $9.1 million (based on wage-risk study), respectively, 

(Revez 2014) as the monetary value of avoiding the death of a 

single person.
58 Chapter 4. Forest Ecosystem Services: Carbon and Air Quality

Aggregation

Aggregation involves extrapolating the value of each ecosystem 

service across the entire geographic region of interest (e.g., State) 

or the beneficiary population (e.g., State population). If the value 

is estimated per hectare, simply multiplying the per-hectare value 

by the total area of forest would yield a statewide total value of 

that particular service. Services such as air temperature reduction 

in urban areas are often estimated on a per-household basis rather 

than per hectare of forest. In this case, the per-household value of 

a service could be extrapolated to the total number of households 

that benefit from the service to get a statewide estimate. While 

this approach to aggregation is easy to implement, it is subject to 

a number of caveats.

First, the marginal value of a forest ecosystem service benefit 

can vary (impact of the loss of first hectare vs. the last hectare 

of forest). Unfortunately, there is no general guidance on how 

to incorporate nonlinearity of marginal benefits in valuation. 

Second, since neither the supply (nature of forest) nor the 

demand (preference of beneficiaries) of ecosystem services are 

homogenous across entire States, it is important to stratify the 

State into relatively homogenous regions and to use the most 

appropriate or adjusted value for each region (e.g., Moore and 

others 2013) before summing up regional estimates to get the 

statewide total value. Again, it is difficult to provide guidance 

on exactly how to stratify the State, i.e., how far it must 

be disaggregated.

Finally, the statewide total value of all services can be obtained 

by a sum of the statewide value of each type of service. 

Considering the interrelatedness of production process and 

consumption, it is important to avoid double counting and hence 

overestimating the total benefits. Only services that are mutually 

exclusive should be added. Likewise, it is important to account 

for tradeoffs between services, and at the extreme, to avoid 

summing services that are mutually exclusive (e.g., wilderness 

values and timber production).

IMPROVING FUTURE VALUATION

There is interdependence between forest structure and ecosystem 

services and values. Valuation is dependent upon accurate 

estimates of the magnitude of the service provided; service 

estimates are dependent upon accurate estimates of forest 

structure and how structure affects services. The key starting 

point to valuing services provided by forests is quality data on 

forest structure. Services and values cannot be adequately valued 

without accurate forest data. Combining accurate forest data 

with valid procedures for quantifying ecosystem services will 

lead to reliable estimates of the magnitude of ecosystem services 

provided by the forest. Finally, with accurate estimates of forest 

ecosystem services, values of the services can be estimated using 

valid economic estimates and procedures. Thus, three critical 

elements in sequence are needed to value forest ecosystem 

Life Satisfaction or Happiness Method

The marginal effect of air quality on self-reported life satisfaction 

or happiness can be analyzed to reveal the marginal value of air 

quality, if the income equivalent of changes in life satisfaction or 

happiness can also be estimated. If one could quantify the change 

(better or worse) in carbon storage or air quality attributable 

to change in forest area or condition, this change could be 

linked with some measure of life satisfaction as reported by 

the beneficiaries. The basic assumption of this method is that 

measures of life satisfaction are reliable proxies of people’s 

underlying utility, and the value of an ecosystem service such 

as air pollution removal can be estimated by evaluating how 

people tradeoff between the service and income. For example, 

if a 25-percent increase in carbon sequestration or air pollution 

removal (as a result of expansion of forest area or a similar 

increase in growing stock of an existing forest) increases the life 

satisfaction measure by 1 unit, and it takes a $10,000 increase 

in annual household income to achieve a comparable increase in 

people’s life satisfaction, then this method would conclude that 

the total value of the service provided by the increased forest 

area or improved forest condition to beneficiaries would be 

$10,000 multiplied by the number of beneficiaries. By estimating 

a production function for the service, its value can easily be 

estimated on a per-hectare basis. Luechinger (2009) and Levinson 

(2012) have already applied this method to value reduction in air 

pollution and for changes in air temperature.

Benefit Transfer Method

When there is a budget or time constraint on collecting new 

data, benefit transfer is typically used to quantify the value of 

an ecosystem service. In a unit value benefit transfer, the value 

of a specific service (e.g., carbon sequestration per hectare of 

given forest type) in a given “policy site” is derived from an 

average of such values reported in one or more study areas of 

similar characteristics elsewhere (study sites) (Loomis 1992; 

also discussed in chapters 2 and 3 of this publication). Values 

reported in study sites would be estimated by one of the methods 

described above. These would be per-hectare value of a given 

ecosystem service provided by a given type of forest. The analyst 

would then ‘transfer’ them to the policy site by multiplying the 

average per-hectare value by the total area occupied by that 

type of forest. Many of the recent studies that characterized 

the value of forest ecosystem services in Southern States have 

used this approach (e.g., Moore and others 2013, Simpson and 

others 2013). A key consideration is that the ecological and 

socioeconomic characteristics of the “study site” and “policy 

site” should be as similar as possible because species composition 

(hardwood, softwood), location of forest relative to source of 

pollution, and beneficiaries can make a substantial difference 

in the level of supply and public value of the service. Several 

reports including Troy and others (2006), Liu and others (2010), 

and Costanza and others (2014) provide per-area values of air 

quality related to ecosystem services that may be applicable to 

regions of similar characteristics.
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 59

services: structure – services – values. Errors with precursor 

elements will lead to errors in subsequent estimates (e.g., errors 

in characterization of forest structure will lead to errors in 

estimating services and valuation). All estimates and means of 

estimation can be improved to varying degrees.

Quantifying Forest Structure

Mapping of tree cover from NLCD 30-m resolution data can 

be improved by creating or utilizing high resolution tree cover 

data. These tree cover data are being created in some areas 

at the city or county scale (e.g., www.nrs.fs.fed.us/urban/utc/

status/). Another option for calculating tree cover is to use 

photo-interpretation. With photo-interpretation, one can often get 

tree cover estimates with a standard error of around 1.4 percent 

with 1,000 interpreted points (about one day’s worth of work). 

This accuracy is often better than that produced by cover maps, 

but photo-interpretation does not map specific locations of tree 

cover. There is a free photo-interpretation tool (i-Tree Canopy) 

that provides users an easy means to interpret and analyze tree 

and other cover types using Google maps (www.itreetools.org/

canopy/index.php).

For estimates of local forest structure (e.g., number of trees, 

species composition), FIA collects plot data for forest areas at a 

density of one plot every 2,428 hectares. For small study areas 

(e.g., where sample size does not meet a minimum threshold), 

there are likely not enough plots to make a reasonable estimate of 

forest structure. In this case there are two options:

1) Collect more local data. This can be done using FIA 

procedures with plot intensification or by collecting your 

own data (e.g., using i-Tree Eco),

2) Use FIA plot data from the region to determine the forest 

structural attributes (e.g., number of trees) per unit of tree 

cover within the FIA sampled area, and then apply these 

standard values to the amount of tree cover in the study area. 

Plot data from FIA have been imputed to non-plot areas (e.g., 

Wilson and others 2013). This approach is less accurate, 

but it applies regional average values to local tree cover 

and could illustrate regional differences in forest structure 

and functions.

Air Pollution Removal and Its Effect 

on Air Pollution Concentrations

Forest effects on air pollution concentration have been estimated 

using i-Tree Landscape for urban and rural areas in counties of 

the conterminous United States, with valuation of those effects 

based on health impacts and values from BenMAP. However, 

health values only occur when people live in close enough 

proximity to forests to receive the improved air quality. As there 

are fewer people in rural areas, the health value of the air quality 

improvement decreases substantially from urban to rural areas.

As air quality affects more than human health (e.g., visibility, 

plant health, damage to materials), another approach to valuation 

has been to use “externality values” calculated for each air 

pollutant (e.g., Van Essen and others 2011). An externality value 

is a constant value per ton of pollution removed ($ per t) derived 

from the literature. Externality values should be higher than 

health values as they should include health and other values. 

For example, pollution removal by trees in the conterminous 

United States in 2010 had a health value of $6.8 billion but 

had an externality value estimate of $86 billion (Nowak and 

others 2014).

While methods for modeling pollution removal by trees and 

forests are well developed, further research is needed on 

secondary pollutants that are formed through chemical reactions 

(e.g., ozone), including understanding the role of VOC emissions. 

For all pollutants, secondary effects of trees on pollutant 

emissions (e.g., via altering air temperatures and energy use) 

need to be quantified to provide a more comprehensive analysis 

of forest impacts on air quality.

Volatile Organic Compound Emissions

Though improvement can always be made, the BEIS and 

MEGAN procedures are likely the best available procedures 

to estimate plant VOC emissions. If VOC emissions can be 

converted to tons or concentrations of particulate matter, ozone, 

and carbon monoxide, then valuations can be done similar to 

pollution removal.

Pollen Emissions

Compared to other air quality (dis)services, there is relatively less 

certainty about pollen emissions. Current methods only produce 

a relative index value of pollen for forests but do not estimate 

actual pollen emission by species. Developing emission rates 

for each species by time of year would be helpful in improving 

pollen estimates. To model human health impacts, better 

understanding is needed of how species emissions affect pollen 

concentrations and their specific impact on allergic responses in 

humans. Given current knowledge, relating the relative index 

values to health impacts (e.g., increased allergies) and then health 

values associated with these effects could be used to value the 

impact of pollen emissions.

Carbon Sequestration

Improvement can always be made by developing more and/

or better carbon estimation equations and developing better 

estimates of tree growth. However, the procedures used are pretty 

much the standard in estimating carbon storage and sequestration 

from trees and forests. The current (2015) value of forest carbon 

sequestration is $38 per metric ton of CO2 based on a 3-percent 

discount rate (Interagency Working Group on Social Cost of 

Carbon 2013).
60 Chapter 4. Forest Ecosystem Services: Carbon and Air Quality

Air Temperature Reduction

As air temperatures affect many attributes within forest 

ecosystems (e.g., transpiration, growth, photosynthesis, VOC 

emissions) and have secondary effects that impact air quality 

(e.g., photochemical rates, pollutant emissions), this service 

requires more research to improve model estimates of forest 

effects on air temperatures and associated secondary effects on 

other ecosystem services and air quality.

Changes in air temperature affect human health directly (e.g., 

heat stress) and also affect chemical emissions from numerous 

sources, which can influence human mortality. If these impacts 

can be quantified, then they can be valued either using the 

valuation procedures related to air pollution removal or using the 

statistical value of a life.

Economic Valuation

Most of the valuation methods presented in this chapter are 

established methods and have been widely used by resource 

economists. A bigger challenge in ecosystem service valuation 

lies in accurately quantifying the benefits. However, a number 

of issues still exist in modeling (users’ preference, demand) and 

benefit aggregation that lead to potential over- or underestimation 

of benefits. Nonetheless, more rigorous methods are evolving 

with advancement in the field of econometrics. On the other 

hand, valuation studies so far have relied on cross-sectional data 

(market or household survey data of one particular point in time), 

but parameters estimated from such models may not be stable 

enough to be useful in forecasting and benefit transfer purposes. 

When the benefit transfer method becomes the only choice in 

valuation, researchers should attempt to get a mean estimate of 

benefits ($/hectare) from as many studies as possible.

Improvements in the valuation approach could also be made 

by integrating economic methods presented here with other 

disciplines such as regional science and public health. For 

example, there currently is no single method accepted as standard 

practice in estimating the value of heat reduction services 

provided by forests. However, the per-person value of human life 

has been estimated by several studies worldwide (Viscusi and 

Aldy 2003), whereas the marginal benefit of increasing forest 

area in reducing heat-related deaths is estimated in regional 

science studies (e.g., Walton and others 2016). Taken together, 

these two estimates (value per life and number of lives saved) 

can be combined to characterize the total value attributable to 

heat reduction services. Considering the dynamics of ecosystem 

service production functions and the complexity of data 

collection and modeling, efficient approaches in ecosystem 

service valuation in the future may have to utilize existing 

information that are valid, reliable, and reasonably accurate for 

the study area.

SUMMARY AND CONCLUSIONS

Forest management and land use decisions in the past have 

rarely acknowledged the value of ecosystem services. This 

omission is largely because our society has taken those services 

for granted. These services could be undersupplied, especially 

in the Southeast, due to a lack of proper incentives to private 

landowners. This chapter reviews published and theoretically 

defensible methods and techniques to quantify and value several 

air quality services of forest ecosystems.

With the market for ecosystem services slowly emerging, it 

is becoming increasingly possible to estimate the value of 

some services (e.g., carbon) based on market price of offset 

credits. On the other hand, most other air quality services are 

currently not traded in the marketplace and require non-market 

valuation methods. Part of the difficulty in monetizing some 

services is quantifying the magnitude or impact of forests on the 

services. Hence, more research is needed to better understand 

the production function of those services, as well as the flow 

of benefits to natural and human systems. There are some 

user-friendly, computer-based tools (e.g., i-Tree) that are at the 

disposal of practitioners to explore and understand the production 

and value of some of the services discussed in this chapter.

Despite the available methods and tools, quantification and 

valuation of many specific services are still challenging because 

of the secondary effects (both in cost and benefit) of some of 

the services. In other words, the interrelation in production 

process of multiple ecosystem services complicates the process 

of characterizing value and aggregating benefits at the forest 

landscape level. For example, management practices that increase 

carbon sequestration will likely impact water flow and quality. 

Thus, when aggregating the values of these services, the analyst 

needs to avoid double counting and hence overestimating the 

total economic value.

While the valuation methods discussed here are standard, 

the procedure to be followed in the quantification of services 

and aggregation of benefits could be specific to the context or 

objective of valuation. For example, if the objective is to estimate 

the value of change in a provision of services as a result of 

proposed policy (e.g., increasing forest area or improving forest 

health), then appropriate caution should be exercised to estimate 

the level of service between two States (say, State A and B) and 

to multiply that by the value of benefit-per-unit evaluated for the 

respective State where possible. The difference of products can 

be interpreted as the public value of the policy.

The methods presented in this chapter do not constitute an 

exclusive list of prescribed methods for quantification and 

valuation of services but are intended to serve as guidelines to 

aid in quantifying forest and environmental resource values. 

Reliability and validity of many of these valuation methods are 
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 61

still being debated. Moreover, as the methodological research in 

ecosystem service continues to grow, several other approaches 

and tools are likely to be tested and proposed in the future.

Each method has its own strengths and limitations and relies on a 

unique set of assumptions regarding the ecological processes that 

produce a service, as well as economic principles of utility and 

welfare. While “benefit transfer” from the existing literature is a 

lower cost option, it is only reliable across areas with identical 

characteristics. In other words, a benefit function developed in a 

study area should only be applied to new areas that fall within the 

range of characteristics of the study area. Hence, the need for a 

new valuation study depends on the uniqueness of the ecological 

and socio-cultural context of the area of interest. Valuation 

methods for these unique cases can be improved through further 

integrated and site-specific research that involves both ecologists 

and economists.

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Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 65

Chapter 5

Forest Ecosystem Services: 

Provisioning of Non-Timber Forest Products

James L. Chamberlain, Gregory E. Frey, C. Denise Ingram, 

Michael G. Jacobson, Cara Meghan Starbuck Downes

INTRODUCTION AND BACKGROUND

T

he purpose of this chapter is to describe approaches to 

calculate a conservative and defensible estimate of the 

marginal value of forests for non-timber forest products 

(NTFPs). “Provisioning” is one of four categories of benefits, or 

services, that ecosystems provide to humans and was described 

by the Millennium Ecosystem Assessment (MEA 2005) as 

“products obtained from ecosystems,” which include food, fuel, 

wood, and fiber, as well as products such as remedies and crafts. 

Clearly, any valuation of ecosystem benefits must include the 

tangible items, or products, that they supply.

There are very few valuation studies of NTFP provisioning. 

The main reason is that NTFPs—which are also called “special 

forest products” in the United States—are typically secondary in 

importance to timber, so they lack the profile and attention wood 

products receive. In the United States, forest valuation is almost 

always based on timber production and a few other items such as 

grazing, minerals, or hunting leases. Timber price and quantity 

data have been tracked for many years and are easily available. 

In contrast, data are available for only a few NTFPs even though 

there is a wide variety of products and markets. Quality data 

related to geographic and temporal distribution of NTFP species 

and their harvests are quite limited.

Most studies of NTFPs report methodological roadblocks in 

getting reliable and accurate values. The basic information 

needed to estimate NTFP values begins with some sort of 

accounting of the flow or stock of the resource. Typically, values 

are estimated based on prices received by harvesters, although 

the contributions that NTFPs make to harvesters’ income, diet, 

and health also represent values to households and communities. 

Non-market valuation based on these types of contributions, 

while not easy, has been used in the absence of market prices.

Ecosystem service valuation studies should use past research 

as a starting point. While a comprehensive literature review is 

beyond the scope of this chapter, appendix 5.1 summarizes select 

valuation studies of NTFPs in the United States and around the 

world. Appendix 5.1 presents studies that may be relevant for an 

analyst attempting to value NTFP provisioning services.

Definitions

NTFPs come from plants (e.g., herbs, lichen, moss, shrubs, trees, 

vines) and fungi (e.g., mushrooms). They include food, medicine, 

decorations, and materials used in fine arts and crafts. Table 5.1 

lists common NTFPs from the U.S. South. These products 

often are collected and consumed for personal and cultural uses 

(Cordell and others 2012, Robbins and others 2008) and provide 

significant economic contributions to users in the United States 

(Alexander and others 2001, Alexander and others 2011).

As the term NTFP specifies, these products are not timber and 

come from forests. This leads to questions about the definitions of 

“timber” and “forest.” This publication considers industrial wood 

chips and poles to be timber products, while wood extracted for 

traditional firewood and artisanal crafts are considered NTFPs. 

Definitions and quantification methods focus on goods produced 

from natural forests (e.g., Adepoju and Salau 2007, Famuyide and 

others 2013, Godoy and Lubowski 1992, Sullivan 2002), but they 

could be used for products grown in plantations solely for their 

non-timber value. Often, products grown in tree plantations or 

cultivated on an industrial scale, such as fruits, nuts, or Christmas 

trees, are not considered NTFPs, yet the valuation methods 

presented are applicable to these products.

Non-biotic products that may come from the forest, such as rocks 

and minerals, are not classified as NTFPs. In some parts of the 

world, animal products such as game meat are considered NTFPs, 

but in the United States, wildlife is generally treated as a separate 

category. We do not deal with animals or animal products here, 

restricting NTFPs to plants and fungi, although many of the same 

principles would apply. For more information on the valuation of 

wildlife for recreation such as hunting, see chapter 2. 

Many past studies on NTFPs report “total market value” or 

“economic value.” Total market value is the total quantity 

harvested or traded in a locality, State, region, or country, 

multiplied by its market price. Economic value refers to the sum 

of the consumer and producer surplus for a good or service. 

While such estimates may provide information about the overall 

importance of NTFPs in a particular economy or policy changes 

that affect the entire source of a product, they are not described 
Product Part of plant Market segment

Virginia snakeroot Root Medicinal

Wild yam Root Medicinal

Black cherry Bark Medicinal

Trillium Whole Plant Medicinal

Autumn olive Fruit Culinary

Pawpaw Fruit Culinary

Black walnut Fruit Culinary

Tulip poplar Bark Decorativea

Persimmon Fruit Culinary

Butternut Bark Medicinal

Eastern red cedar Leaves Medicinal

Witch hazel Bark & Leaves Medicinal

White oak Bark Medicinal

Sassafras Leaves Culinary

Morels Fruiting Body Culinary

Other mushrooms Fruiting Body Culinary

Princess pine Whole Plant Decorative

Spanish moss Whole Plant Decorative

Staggerbush/ 

Crooked-wood 

Branch & 

Stems

Decorative

Blueberries/ 

huckleberries

Fruit Culinary

Blackberries Fruit Culinary

Fraser fir 

transplants

Whole Plant Landscaping, 

Decorativeb

Rhododendron/ 

azalea transplants

Whole Plant Landscaping

Cypress knees Stems Art

Wood for carvings Wood Art

Wood for baskets Wood Art

aTulip poplar bark is used for siding for houses. 

bFraser fir is used extensively for Christmas trees.

66 Chapter 5. Forest Ecosystem Services: Provisioning of Non-Timber Forest Products

in this chapter. Rather than total values over a geographic region, 

this chapter explains how to find the best estimate of per-acre

values resulting from small changes in forest area, or marginal 

value. This type of information is the most relevant for policy 

decisions that affect a limited forested area, as well as for 

tracking changes in the value of provisioning services over time.

Market participants who move NTFPs from forest to the first 

point of sale are generally called “harvesters” (alternatively, 

“collectors,” “pickers,” “gatherers”). They are analogous to 

“loggers” in the timber industry. Harvesters can be an important 

source of information about NTFP activities. They represent 

the primary knowledge base to locate the resource, provide 

extraction rates, and identify what the market wants and what 

prices can be obtained for different qualities of products. They 

observe changes in the forests that they know are critical to 

sustaining their livelihoods as well as the continued existence of 

the NTFP resource. Harvesters are the foundational players that 

initially define the market structure. They gather the products and 

consume, share, or sell the products as raw materials.

“Dealers” can play a key role in setting the prices and value 

received by harvesters of NTFPs. Dealers can be sub-classified 

into “primary buyers” who purchase directly from harvesters, 

consolidate transactions, and sell to regional or national buyers. 

“Secondary buyers” may consolidate transactions and sell to 

national or international buyers, or they may produce a final 

product for retail consumers. “Third buyers” in the market would 

then produce a final product for the retail consumer. The “final 

buyer” in the market chain typically is the retail consumer.

Table 5.1—Major non-timber forest products of the Southern United States

Product Part of plant Market segment

Pine straw Needles Landscaping

Pine cones Cones Decorative

Conifer boughs Boughs Decorative

Sweet grass Stem Art

Sphagnum moss Whole Plant Art

Mistletoe Whole Plant Art

Vines Stem Decorative

Maple syrup Sap Culinary

Ramps Whole Plant Culinary

Fox grapes Fruit Culinary

Galax Leaves Decorative

Moss Whole Plant Decorative

Grape vine Vine Art

Dutchman’s pipe Vine Art

Mountain laurel Whole Plant Landscaping

Winterberry holly Leaves and 

Berries

Decorative

Pitcher plants Whole Plant Decorative

Aletris Root Medicinal

Bethroot Root Medicinal

Black cohosh Root Medicinal

Bloodroot Root Medicinal

Blue cohosh Root Medicinal

False unicorn Root Medicinal

American ginseng Root Medicinal

Goldenseal Leaves & Root Medicinal

Lady’s slipper 

orchid

Root & Whole 

Plant

Medicinal

Saw palmetto Fruit Medicinal

Slippery elm Bark Medicinal
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 67

Greenfield and Davis (2003) found dealers of medicinal forest 

products (e.g., American ginseng), floral products (e.g., galax) 

and edible forest products (e.g., ramps) to operate full time, 

seasonally, and part time depending on the product. Some prices 

are reported daily by the dealers (ginseng) while others are set 

seasonally by buyers (e.g., galax and bloodroot). Blatner and 

Alexander (1998) and Schlosser and Blatner (1995) found that 

data on industries engaged in the marketing, processing, and 

distribution of NTFPs in the Pacific Northwest were limited due 

to the small, informal characteristics of NTFP markets and high 

price variability.

NTFPs can be produced by a continuum of forest management 

intensities. Those for which little or no management occurs are 

“wild-harvested” from natural populations. “Managing wild 

populations” does not mean establishing a species in a forest, 

but it does mean undertaking activities that favor a species or 

individuals over others to increase yield or quality of product. 

Intentionally establishing and maintaining NTFP species within 

a forest is called “forest farming.” Forest farming can take 

numerous approaches, including “wild-simulated,” a low-input 

method of establishing NTFPs with only minimal alterations and 

management, and “woods-cultivated” or “woods-grown,” which 

refers to more intensively established and managed systems.

Conceptual Model

The value of a provisioning ecosystem service is not the same 

as the value of a product. To see this, consider that all NTFPs 

are the result of a combination of production inputs that include 

at least ecosystem functions and human effort. The value of the 

provisioning ecosystem service is most clearly understood to 

be that portion of the products value that is due to ecosystem 

function, that is, the “residual value” after factoring out human 

and other production inputs. We remind the reader that the 

measure of value we demonstrate here is the marginal value. 

Where competitive markets exist, market price is the best starting 

point for determining marginal values.

Smith and others (2010) describe an appraisal system for 

estimating the residual value of NTFPs, based on wholesale 

prices and total harvest cost, which is used by some National 

Forests. An NTFP cost analysis program was initiated by 

Region 6 (Pacific Northwest) of the National Forest System in 

2000 in response to national legislation that required the National 

Forests to charge “fair market value” for harvest permits (Smith 

and others 2010). The tool provides an Excel spreadsheet model 

that uses a residual-value appraisal of permitted products (Smith 

and others 2010, USDA Forest Service 2016). The residual value 

appraisal uses data from interviews with harvesters on delivered 

wholesale market prices for products and all associated harvest 

costs to achieve fair and unbiased base rates or a minimum fee 

for permits. While this tool only includes information related to 

products common in the Pacific Northwest, a similar approach, 

as described in this and following sections, could be used to find 

residual values in other parts of the country.

Timber stumpage—the price per acre of standing trees before 

harvest—roughly corresponds to a provisioning ecosystem 

service marginal value (Alexander and others 2002a). Sometimes, 

harvesters may pay landowners per acre to harvest an NTFP on 

their property, in the same way loggers pay stumpage fees, or 

hunters pay per-acre lease fees, to landowners. If the landowner 

has not invested any time or resources into the production of 

that NTFP, then this per-acre price is the same as the ecosystem 

service marginal value: it is stated on a per-acre basis and already 

has other production inputs factored out. Cases where rights to 

harvest NTFPs are paid on a per-acre basis are relatively rare, but 

this system is used occasionally for a few products such as pine 

straw and saw palmetto. Forest managers of public and private 

lands have many options in deciding how to allocate harvest 

rights for non-timber products (Alexander and Fight 2003).

Cases where no such per-acre transaction occurs and the observed 

price is per unit of harvested product are more common. In such 

cases, the analyst must factor out of the price all human inputs 

including harvest, establishment, and management costs (Godoy 

and others 1993) to obtain an estimate of value for the ecosystem 

function portion of the production inputs. This approach is 

similar to what economists define as net present value (NPV). 

Equation (1) presents the basic NPV formula (see Alexander and 

others 2002a):

 

(1)

where:

NPV = the per-acre net present value over the “rotation” period t, 

on forest land of a given forest type and ownership class

t = the time period of the NTFP production “rotation” (time from 

establishment to final harvest)

ρ = the discount rate

MQi = the quantity of NTFP produced in year i on a marginal 

acre of forest land of a given forest type and ownership class (see 

“Valuation of Marginal Changes in NTFP Provisioning Services” 

later in this chapter)

Pi = the market price or other estimated shadow price per unit 

of NTFP at the first point of sale in year i (see “Estimation of 

Production Costs” later in this chapter)

ECi, MCi, and HCi are the establishment, management, and 

harvest costs per unit in year i (see Scaling Up/ Aggregating” 

later in this chapter).
68 Chapter 5. Forest Ecosystem Services: Provisioning of Non-Timber Forest Products

Typically having an annualized value ($ per acre per year) would 

be preferable. Indeed, much of the present guidance is based on 

the idea of an annual flow of goods and services. In the (relatively 

unusual) case that an NTFP is established, managed, and finally 

harvested at one time (e.g., forest-farmed American ginseng), the 

NPV from equation 1 is first converted to an infinite-horizon soil 

expectation value (SEV) as shown in equation 2, then annualized 

into equivalent annual income (EAI) by multiplying by the 

discount rate (c.f. Alexander and others 2002a) (eq. 3):

 (2)

 (3)

In other cases, NTFPs are harvested from the same plot annually. 

Such might be the case for fruits, or if only a small quantity 

of product (approximately equal to the annual growth of the 

product) is harvested. Perhaps the most common case is wildharvesting, where there are no establishment or management 

costs, so equation 1 simplifies to (c.f. Godoy and others 1993):

 (4)

where MQAn is the marginal annual quantity harvested per acre 

on a sustainable basis. 

If current harvest were so high as to be unsustainable, current 

estimates of value would overstate annual contributions to NPV, 

so estimated NPV should be adjusted down if current harvest 

levels are considered unsustainable. Godoy and others (1993) 

suggest adding a depletion premium to the harvest costs in the 

case of unsustainable harvest. Alternatively, one could adjust 

the marginal annual quantity harvested by the amount of the 

overharvest (Oh):

 (5)

NTFPs are most commonly priced as delivered (to primary 

buyer) or as roadside prices. Since delivered or roadside prices 

are marginal values for a product that has had value added 

through harvest and transport, they are an overestimation of 

the forest’s provisioning service value. In many cases, harvest 

costs are primarily comprised of the opportunity cost of labor. 

If the analyst can reasonably assume that other harvest costs are 

minimal, and if it would be costly to collect the data required 

to adequately estimate those harvest costs, the analyst could 

defensibly argue that harvest costs are virtually zero, simplifying 

equation 1 further to:

 (6)

Unfortunately, since this last equation unambiguously 

overestimates the ecosystem service value (harvest cost must be 

non-zero), it does not meet the principle of finding a conservative 

estimate when uncertainty exists. For this reason, it is a best 

practice to find a reasonable estimate of harvest costs. These can 

be assessed through methods such as interviewing harvesters or 

utilization studies, as described in the “Estimation of Production 

Costs” section.

Challenges

NTFPs are found in most forests but are often neglected and not 

recognized in forest policies or management. One reason for 

this is that very little is known about the production, markets, 

industry, trade, and contributions to society of NTFPs. Realizing 

the actual contribution and value of NTFPs would likely enhance 

their status and generate greater attention in forest policy and 

management decisions. This section discusses the shortcomings 

of available data on the quantities and values of NTFPs in the 

U.S. South.

Valuing the ecosystem service of provisioning NTFPs presents 

numerous challenges compared to valuing the service of 

provisioning timber. First, NTFPs may be traded in formal or 

informal markets or used for personal benefits with no markets 

(McLain and others 2008). For products that are traded in formal 

markets, a convenient starting point for valuation is the market 

price, based on available transaction records and data on price 

and quantity. For NTFPs traded through informal markets, prices 

and quantities may not be tracked or recorded. Informal markets 

are less transparent, and the trade of many NTFPs occurs in the 

transitional region between formal and informal markets. Many 

NTFPs are consumed by harvesters or their family and friends 

with high cultural or recreational values placed on the act of 

collection or consumption. Finding the correct way to estimate 

and add together these values is not easy.

Second, NTFPs may be poached from natural forests or stolen 

from forest farms. Valuable products, such as ginseng, are 

reportedly poached frequently and extensively. Other products 

may be harvested without permits or permission, or out of season. 
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 69

This illegal harvest production is not documented, but it certainly 

has value that affects States’ economies. Law enforcement 

agencies may keep records that could help document the amount 

of NTFPs illegally harvested, yet this represents an unknown 

portion of the total illegal harvest. We do not provide guidance 

here about how to estimate value of poached products, but it is 

clear that when poached NTFPs are excluded from valuation, the 

resulting total values are certainly underestimates.

Third, scalability of research is a challenge. Results of many local 

level studies are not scalable to State, regional, or national levels. 

Findings and recommendations from studies that focus on local 

ecological or sociological systems are difficult, if not impossible, 

to apply to larger geographic areas. This may be because the 

locations chosen for NTFP valuation are not representative of the 

broader region. Survey respondents may be drawn from sampling 

frames that are particular to case study locations and markets, 

making survey results difficult to extrapolate to a State or region. 

Inadequate sampling of plant populations may not provide full 

representation from all forest types. Attaining an accurate sample 

of an entire forest or region may be difficult due to funding or 

accessibility issues.

Geographic variability in the presence and frequency of specific 

NTFPs, even within the same forest type, makes it very difficult 

to impute NTFP values on specific acres. Any particular acre 

might have more or less NTFP quantity than the average. Further, 

even if product is available, its value may be diminished by 

factors that make it less accessible or more costly to harvest. 

These factors are difficult to estimate with existing data.

Fourth, most studies have been one-time efforts and therefore 

do not provide the information required for trend analysis. Most 

NTFP valuations could be considered one-time spot reports that 

become outdated with changing economic conditions. Only a few 

NTFPs, such as American ginseng, are regulated and monitored, 

resulting in time series data. The importance of temporal data is 

that NTFP markets and trade fluctuate with changes in demand 

for “natural” products, as does the biological production cycle 

given external vagaries such as weather. Many NTFPs have only 

had one, if any, formal valuation study and more often than not 

the valuation is many years old (Blatner and Alexander 1998). 

Survey data and value estimates from one point in time do not 

account for variation in supply and demand.

There are numerous challenges with measuring quantities 

and prices received for NTFPs in the forest. Problems with 

quantification relate to both biological and social conditions. 

Many NTFPs are seasonal, so there may be a very short amount 

of time to adequately quantify, interview harvesters, and assess 

product value. Ramps (Allium tricoccum; wild onions) are a good 

example, as they are available for harvest for only a few weeks 

during the year. When interviewing people about how much they 

harvest or what prices they receive, the timing and location of 

interviews are important. During the season, when recollection 

is best, harvesters may not want to be bothered or may be too 

busy to respond to requests for information. If outside the season, 

recollection may be more challenging. NTFP harvesting is a parttime seasonal occupation for many people who combine it with 

other more formal employment. The diversity of NTFP harvesters 

makes it challenging to sort out who is doing what.

The NTFP industry depends a lot on trust, and market participants 

are wary of outside surveys and interviews (Greenfield and Davis 

2003). Harvesters, buyers, and other market players are reluctant 

to provide information especially when they are unsure of how 

it will be used. Harvesters may be reluctant to share information 

if they do not trust the interviewer to protect their knowledge. 

People involved with NTFP markets may be reluctant to provide 

reliable information if they are concerned about the product 

becoming regulated or losing competitive advantage. In addition 

to these factors, survey response rates may be low due to the 

nature of the business.

A partial accounting of harvest volumes can be obtained from 

the permitted harvests on public lands such as National or State 

forests. However, these data often have limitations. The product 

categories of the USDA Forest Service (National Forests) “cutand-sold” reports often are too general to identify species. For 

example, the product code “foliage” is used across all National 

Forests. This code is applied to products sold to the floral 

industry, but there is no way to identify the species harvested.

IDENTIFICATION AND SELECTION OF 

NTFPS FOR VALUATION

Almost any plant or fungi gathered by the occasional forest 

visitor could be classified as a non-timber forest product for 

personal use. NTFPs gathered for personal use may be associated 

with specific market segments (food, medicine, decorations) or 

not (spiritual gain, luxury, subsistence, or recreation) (Emery and 

Pierce 2005). Southern forests also are the source of a plethora 

of medicinal herbs for a multi-billion dollar international market 

that has contributed to the region’s economy since trade began 

with Europe, Asia, and other parts of the United States. Sassafras 

roots, harvested from what is now Martha’s Vineyard, were 

formally traded in the global herbal market as early as the 1600s. 

Other NTFPs also have a long history of trade; for example, the 

longleaf pine forests of the Southern United States were a global 

source of pine resin and associated products from colonial times 

until the early 20th century.
Decision to value NTFPs.

Select NTFPs to analyze.

Form expert panel on NTFPs in State. 

Identify NTFPs of significance to State.

Define forest types and forest ownership classes of 

significance to State.

Criteria and Indicators of importance and 

feasibility of valuation (see section on ‘Criteria for 

Selecting NTFPs for Valuation’ & Table 5.5). 

70 Chapter 5. Forest Ecosystem Services: Provisioning of Non-Timber Forest Products

Today, non-timber products are harvested from the forests of 

every Southern State. Table 5.1 provides examples of common 

non-timber forest products found in the region.

Some forest types, because of their biological diversity, 

have more NTFPs than other forest types. For example, the 

Appalachian hardwood forests are high in diversity and 

have many different medicinal forest products. However, we 

recommend focusing valuation efforts on the NTFPs that are 

most significant to each State. As knowledge and expertise about 

NTFPs increase, and the infrastructure and resources to value 

NTFPs improve, then additional products can be evaluated.

In this section, we discuss key information required to identify 

and select NTFPs for valuation, including commercially and 

non-commercially harvested NTFPs. Major market segments are 

identified to allow for categorizing products by their purpose. 

States also may find it useful to classify and prioritize NTFPs for 

valuation by forest type. Forest ownership is discussed to allow 

for further segmentation of analysis. Finally, we present criteria 

for selection of NTFPs for valuation.

The decision tree in figure 5.1 provides a framework for selecting 

priority NTFPs for valuation.

Without actually knowing the values of NTFPs in the State a 

priori, decisionmakers may need to rely on expert knowledge to 

select priority products for valuation. This can be accomplished 

by convening a diverse group of practitioners, researchers, and 

managers who can provide insights and recommendations. These 

experts may also provide valuable advice toward identifying data 

sources, and, if necessary, sampling and survey methodologies. 

Their knowledge of harvest routines and market structure 

will facilitate the selection of an efficient sampling strategy. 

Discussions should cover non-commercial values, as these may 

tend to be overlooked in comparison with commercial values.

Market Segments of NTFPs

There are many ways to classify non-timber forest products. 

In general, NTFPs can be classified into five broad market 

segments (based on Chamberlain and others 1998): (1) culinary; 

(2) medicinal; (3) decorative; (4) nursery stock and landscaping; 

and 5) fine arts and crafts. Additional categories may evolve as 

knowledge about this industry develops. A brief summary of each 

segments is provided below.

Culinary forest products—Edible forest products include 

berries, nuts, saps, ferns, tubers, and bulbs. In the South, ramps 

are one of the most popular edible forest products found in the 

mountains. Edible fungi, particularly mushrooms, also are welldocumented edible forest products. The geographic distribution 

of edible forest products is dependent on ecological conditions. 

Maple syrup is primarily produced in the Northeastern United 

States, from Ohio to Maine, but production extends south into 

Virginia. Many edible forest products are collected for personal 

consumption, although there are markets also for most products, 

such as the nuts of black walnut (Juglans nigra), which are 

harvested throughout the tree’s natural range (Chamberlain and 

others 1998).

Medicinal forest products—The use and trade of herbal 

medicines derived from forest plants has a long history and may 

constitute the highest valued segment of the NTFP industry. 

The American Herbal Products Association (Dentali and 

Zimmermann 2012) tracks 21 plant species that are used in 

commerce. Table 5.2 summarizes information on 13 that are 

native to eastern hardwood forests. As previously noted, the 

markets for these products vary with changes in demand. Some 

products have increased in volume harvested (black cohosh 

[Actaea racemosa], slippery elm [Ulmus rubra], trillium [Trillium 

erectum]), while others have decreased (saw palmetto [Serenoa 

repens], bloodroot [Sanguinaria canadensis]). The roots of 

American ginseng (Panax quinquefolius) have been harvested 

from eastern hardwood forests for over 250 years. Nineteen 

States are certified by the U.S. Fish and Wildlife Service to export 

wild-harvested ginseng. Of those, seven are located in the South 

(table 5.3). Saw palmetto, which is used to treat benign prostatic 

hyperplasia, is sourced primarily from the pine forests of Florida 

(table 5.4).

Figure 5.1—Decision tree that provides a framework for selecting priority 

NTFPs for valuation.
Table 5.2—Average annual harvest of medicinal forests products tracked by American 

Herbal Products Association and found in southern forests

Latin name Common name Plant part

Average 

annual 

harvesta

2001–2005

Average 

annual 

harvesta

2006–2010

Percent 

change

Actaea racemosa Black cohosh Root 224,072 284,162 26.8%

Aletris farinosa White colicroot Root 1,012 690 -31.9%

Aristolochia serpentaria Virginia snakeroot Root 121 43 -64.2%

Caulophyllum thalictroides Blue cohosh Root 6,651 5,169 -22.3%

Chamaelirium luteum Fairywand Root 4,688 4,541 -3.1%

Cypripedium spp. Lady’s slipper Whole plant 51 48 -4.3%

Dioscorea villosa Wild yam Tuber 33,422 37,692 12.8%

Hydrastis canadensis Goldenseal Root & Leaf 73,619 74,708 1.5%

Panax quinquefolius American ginseng Root 62,294 63,461 2.0%

Sanguinaria canadensis Bloodroot Root 24,823 5,056 -79.6%

Serenoa repens Saw palmetto Fruit 3,293,377 2,432,841 -26.1%

Trillium erectum Red trillium Whole plant 1,099 1,445 31.5%

Ulmus rubra Slippery elm Bark 182,435 304,207 66.7%

aAverage annual wild harvest (pounds dry weight) for 5-year periods.

Sources: AHPA (2012) and Chamberlain and others (2013b).

Table 5.3—Volume by weight in pounds of dry wild American ginseng harvested by States

State 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total

Alabama 457 1,025 749 221 761 318 717 1,345 474 454 476 626 7,623

Arkansas 2,073 2,632 1,770 504 927 989 1,190 1,796 1,195 487 238 1407 15,208

Georgia 266 426 263 402 167 280 406 293 212 158 361 346 3,580

Kentucky 15,085 22,583 16,717 9,392 13,713 11,345 11,839 19,246 15,041 13,176 15,276 20,025 183,439

North 

Carolina 8,790 6,548 4,271 5,602 7,060 12,378 11,402 10,531 8,041 9,716 8,765 7,849 100,953

Tennessee 5,815 10,826 8,690 5,280 8,153 8,695 8,435 14,642 11,464 9,322 10,145 13,867 115,334

Virginia 3,801 4,675 3,435 1,571 2,878 3,050 2,918 4,081 3,610 3,856 4751 4370 42,996

 Total 36,287 48,715 35,895 22,973 33,659 37,055 36,908 51,934 40,037 37,169 40,012 48,490 469,133

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 71
Table 5.4—Volume by weight in pounds of dry 

saw palmetto berries 

Wild 

harvested

dried 

(pounds)

Conversion factors

Times 2 for 

underreportinga

Times 3.3 for 

fresh fruit 

(pounds)b

1997 1,253,280 2,506,560 8,271,648

1998 1,966,685 3,933,370 12,980,121

1999 1,082,594 2,165,188 7,145,120

2000 4,663,613 9,327,226 30,779,846

2001 2,206,157 4,412,314 14,560,636

2002 2,877,519 5,755,038 18,991,625

2003 3,397,465 6,794,930 22,423,269

2004 2,918,940 5,837,880 19,265,004

2005 5,786,806 11,573,612 38,192,920

2006 2,277,504 4,555,008 15,031,526

2007 4,199,685 8,399,370 27,717,921

2008 2,644,813 5,289,626 17,455,766

2009 1,581,106 3,162,212 10,435,300

2010 1,461,125 2,922,250 9,643,425

Total 38,317,292 76,634,584 252,894,127

Average 2,736,949 5,473,899 18,063,866

a Industry representative estimates that reported harvest 

volumes are one-half what is actually harvested. 

b A factor of 3.3 is the standard for converting from dried to 

fresh product.

Source: Dentali and Zimmermann (2012).

72 Chapter 5. Forest Ecosystem Services: Provisioning of Non-Timber Forest Products

Decorative forest products—Many forest plants and their parts 

are used in decorative arrangements, to complement and furnish 

the backdrop for flowers, and as the main component of fresh 

and dried ornaments. The end uses for forest-harvested floral 

decoratives include fresh/dried flowers, greenery, basket filler, 

wreaths, and roping. Galax (Galax urceolata) from western North 

Carolina is an iconic floral product from the hardwood forests. 

The city of Galax, Virginia, is named after the plant, reflecting its 

historical importance to the local economy. Spanish moss from 

southern forests also are in this market segment. Conifer boughs 

may be the most widely sold decorative forest product in the 

United States (Chamberlain 2000). The products in this category 

contribute significantly to regional economies. For example, 

in 1995, the United States exported more than $14 million in 

forest-harvested moss and lichens, most of which originated from 

Appalachia and the Pacific Northwest (Goldberg 1996).

Nursery and landscaping forest products—Live forest 

plants are collected for the nursery and landscaping industry. 

These may be marketed as bare root stock or balled live plants 

for direct planting. Common examples include rhododendron 

(Rhododendron spp.), azaleas (Azalea spp.), mountain laurel 

(Kalmia latifolia), and the endemic Fraser fir (Abies fraseri). 

The Christmas tree industry has realized tremendous growth 

over the last decades, due in part to the germplasm from Fraser 

fir, growing in a very limited distribution in western North 

Carolina and southern Virginia. Its value to these States could 

be significant. Pine straw, harvested throughout the South, is 

used extensively in landscaping. The National forests report 

the permitted harvests of plant materials used for nurseries and 

landscaping. In 2013, more than 43 percent of the total recorded 

harvest in all National forests came from North Carolina. 

Collection of forest understory wildflowers for horticultural sales 

is a cottage industry in the southern Appalachian region, and 

many wildflowers are readily available through internet sales 

and brick-and-mortar stores (Botanical Wonders Nursery 2015, 

Cullina 2000, Mainely Crafts 2015).

Fine art and craft forest products—Artisans using non-timber 

products to craft luxury items find the ingredients for their 

creations in forest plants. The use of NTFPs for fine arts and 

crafts is limited only by the artisans’ imagination. Wood collected 

from forests may be formed into carvings, turnings, walking 

sticks, utensils, and containers. Moss, lichens, and seeds may be 

formed into jewelry. Vines are crafted into wreaths, sculptures, 

and statues. Fine baskets are crafted from splints of wood or 

grass stems. The outlets for these fine arts are varied as well. 

For some artisans, the preferred venue is local and regional craft 

fairs. Others may market their products through specialty retail 

stores or internet based shops. NTFPs used for fine arts and 

crafts contribute to a multi-million dollar handicraft industry. 

Determining the proportional value of the provisioning ecosystem 

service to this industry is problematic because of the challenge 

of differentiating the value of the forest input from the value of 

human artistry.

Forest Type Classifications

Each forest type supplies distinct NTFPs. Appendix B of the 

Forest Inventory and Analysis (FIA) manual for southern forest 

inventories identifies nine forest types of the South, along 

with their associated species (USDA Forest Service 2010). 

These forest types and associated tree species are provided 

in appendix 5.2 of this chapter. The FIA manual provides 

information on the tree species found in each forest type, but 

information on the associated plants and fungi is lacking.

Forest Ownership Classifications

The ownership of southern forests reflects historical and 

contemporary trends in economic sectors, stakeholder 

preferences, and technological developments. While the 

ownership class (public, corporate, family) of forests may affect 

the quantity of NTFP harvest, harvesting opportunities do exist 

across these ownership classes (Alexander and others 2011, 

Butler 2008, Salwasser 2006). Attempts to value NTFPs must 

consider the resource base and the interactions and impacts 

of its changing ownership and management. As competition 

for land continues in the South, changing forest land uses and 

management practices could impact forest ecosystems in ways 
Table 5.5—Criteria and indicators for selection of NTFPs to 

estimate value

Criteria Indicator(s)

C1. Amount of harvest 

by volume

I.1 Permit volume reported by National Forests

I.2 Permit volume reported by State

I.3 Harvest volume reported by industry

I.4 Harvest volume reported by regulatory agencies

C2. Availability of data I.1 Harvest volume reported by regulatory agencies

I.2 Number of dealers

I.3 Permit volumes reported by National Forests

C3. Amount of potential 

product stock in State’s 

forests

I.1 Acres of potential habitat, as determined by forest 

type and other parameters

C.4. State’s relative 

standing as producer or 

potential producer

I.1 Acres of potential habitat compared to other States

I.2 Relative harvest volumes

C.5. Economic importance 

to specific communities

I.1 Expert social knowledge

C.6. Ecological 

vulnerability to overharvest

I.1 Expert ecological knowledge

I.2 State’s threatened and endangered listings

I.3 State’s natural heritage listings

I.4 Plant’s conservation status

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 73

that affect the availability and values of NTFPs. If products 

become more/less available on private lands, their value from 

public lands will decrease/increase, as well.

Criteria for Selecting NTFPs for Valuation

Deciding which NTFP or suite of NTFPs to value in each State is 

the first step in estimating the value of NTFPs in the U.S. South. 

Harvest activity, demand, and a State’s position as a producer of a 

particular NTFP will help determine whether to value a particular 

NTFP in that State. The perceived importance to a State’s cultural 

heritage, economy, and ecological diversity should also be 

criteria for targeting valuation efforts. The criteria and indicators 

presented in table 5.5 and discussed below provide guidance on 

deciding which product, or suite of products, to prioritize.

Criterion 1—Amount of harvest by volume. There is little 

incentive to devote limited resources for valuation of products 

that have insignificant demand. There needs to be an indication 

that large quantities, relative to the product’s abundance, are 

being harvested. One good source of the amount being harvested 

are the National Forest “cut-and-sold” reports (USDA Forest 

Service 2015a). For example, the National Forests of North 

Carolina reported that more than 10,000 pounds of forest herbs 

were harvested in 2014. In the same year, the National Forests in 

Florida reported 48,000 pounds of “foliage” as being harvested. 

These harvest quantities suggest that it would be worthwhile 

estimating the value of these products, starting with determining 

which species are categorized under these product codes. 

Other sources of data that might help estimate harvest volumes 

and identify priority NTFPs are export databases such as the 

Interactive Tariff and Trade DataWeb (U.S. International Trade 

Commission 2016).

Criterion 2—Availability of data. The basic data requirements 

to value a non-timber forest product are the harvested or standing 

stock volumes, measured in an appropriate unit (e.g., pounds), the 

prices paid to a clearly identified market player (e.g., harvester, 

primary buyer, secondary buyer), and the associated costs (labor, 

capital, transport, processing). Lack of volume, price, or costs 

data could thwart valuation efforts. However, just because data 

are not available does not mean that a particular NTFP should 

be disregarded. If there is evidence of large harvest volumes 

or values, lack of data may suggest that funding should be 

allocated to data collection. Potential data sources are listed in 

appendix 5.3. Further development of sources of data is necessary 

to value many NTFPs. Perhaps the most valuable type of data 

would be the amounts of per-acre payments to landowners for the 

rights to harvest a product, where relevant.

Criterion 3—Amount of potential product stock in State’s 

forests. The forest types, and the amount, found in a State 

are indicators of the resource base and should be a factor in 

selecting which NTFP to value. A State with large amounts of 

pine forests that could be the source of pine straw may want 

to direct resources to estimating the value of provisioning that 

product. Upland hardwood forests, mixed mesophytic forests, 

and Appalachian hardwood forest types (classified as oak/hickory 

group and maple/beech/birch group by FIA) have tremendous 
Table 5.6—Area of potential oak/hickory and maple/beech/birch habitat for ginseng by ownership 

group and State

Ownership

group

State

AL AR GA KY NC TN VA Total

National Forest 215,248 1,280,534 541,963 789,820 889,384 572,202 1,486,968 5,776,121

Other Federal 83,871 191,850 104,814 290,252 271,419 486,375 314,118 1,742,698

State and local 200,468 131,427 264,390 208,062 284,177 671,329 381,969 2,141,823

Private 6,604,943 6,281,779 5,543,069 9,300,586 5,926,558 8,659,048 7,886,110 50,202,092

 Total 7,104,530 7,885,590 6,454,236 10,588,720 7,371,538 10,388,954 10,069,165 59,862,734

74 Chapter 5. Forest Ecosystem Services: Provisioning of Non-Timber Forest Products

plant diversity that provision medicinal and edible plants. In 

States with large areas of forest types that produce American 

ginseng (as shown in table 5.6), valuation efforts should include 

that product. Information about the extent of different forest types 

in different States is readily available through FIA databases.

Criterion 4—State’s relative standing as producer or 

potential producer. An important criterion for selecting NTFPs 

to value is the market share that a State realizes from a particular 

product. A State that is the sole producer, or a major producer, 

should consider directing more resources to estimating the value 

or provisioning that product. For example, Florida is the sole, 

or major, producer of saw palmetto. North Carolina is the sole 

producer of galax leaves for the floral industry. Efforts by these 

States to value the respective products would contribute much to 

a comprehensive valuation of NTFPs in the South. Estimates of 

the marginal value of forest for production of NTFPs common 

in other States may be available in reports from those States, 

assuming that each State directs valuation efforts based on local 

harvest activities and the local resource base.

Criterion 5—Economic importance to specific communities.

The perceived importance of NTFPs to a State’s rural economy 

should be considered in selecting NTFPs to value. How 

important are these products to rural people of each State? For 

example, sweet grass baskets from South Carolina are important 

to the cultural and economic well-being of African-American 

communities, who can trace this activity to their ancestors. 

Valuing this product would be important to South Carolina. 

Communities in western North Carolina and eastern Tennessee 

depend on annual ramp festivals to generate revenues for fire 

departments and other civic groups. There are at least 10 ramp 

festivals in western North Carolina and eastern Tennessee, and 

people travel for many hours to attend them. Large volumes 

of ramps are harvested during the spring and sold through the 

festivals and through farmers’ markets, roadside stands, and 

restaurants. These edible forest products are critical to the rural 

economy of these States.

Criterion 6—Ecological vulnerability to over-harvest. Priority 

consideration may be given to forest species that are vulnerable 

or at risk of over-harvesting or some other stressor that can 

endanger the product. Common species that are widespread may 

be less of an immediate concern in valuation. For example, it 

may be more important to estimate the value of orchids rather 

than Joe-Pye weed (Eupatorium purpureum), both of which 

are used for their medicinal properties. Orchids are much less 

common than Joe-Pye weed, and the marginal value of forest for 

provisioning a relatively scarce product is likely to be higher. 

Species of ecological concern may be identified from State 

threatened or endangered lists.

QUANTIFICATION OF NTFP PROVISIONING SERVICES

While the challenges of accurately valuing ecosystem services are 

numerous, the results depend heavily on quantifying the amounts 

of NTFPs harvested per acre of productive habitat. Quantification 

can take the form of an estimate of the total physical standing 

inventory, or “stock,” of each NTFP present; or the rate of 

harvest, or “flow,” from those areas. Most researchers prefer 

flow measures (Godoy and others 1993, Tewari 2000). The flow 

approach relies on measuring the amount of NTFPs harvested 

from a region (e.g., forest, watershed, State) often through 

reporting of volumes sold to market entities. This provides 

insight of the volumes of products that enter the market. To 

estimate values, data are needed on both annual harvest volumes 

and prices paid to a clearly defined market player (preferably the 

harvester). In this section, we discuss quantification of harvest 

volumes and the challenges of estimating the marginal quantity 

harvested per hectare, following the decision tree in figure 5.2.

There are a few sources (appendix 5.3) of data on the volumes 

of NTFP harvest in a State, and each has limitations. One major 

challenge with existing data sources is that none measure or 

report marginal per-acre NTFP flows. They report at the forest, 

county, State, or national level. Estimating even average peracre harvest volumes would require knowing how many acres of 

product are in the forest. This requires inventorying the respective 

NTFPs. We know of no inventories of standing stocks of NTFPs. 

Trees within the forest are regularly inventoried, and growth 

and yield models are developed for many tree species. Trees 

that provide NTFPs, such as tulip poplar (bark) and slippery elm 

(bark), can be assessed for their per-acre stock volumes, using 

FIA database. In general, this information does not exist for forest 

plants and fungi that are harvested as non-timber products. To 
Stratified sample 

landowners and/or 

harvesters to determine 

average per-acre value.

Does existing data source 

document quantity harvested

or consumed in geographic 

region of interest?

Is there a robust market of harvesters 

paying landowners per acre 

for access to harvest the NTFP?

Use FIA or other spatial data on forest types to 

determine acreage of habitat in geographic region 

of interest. Divide to find average flow per acre.

Use data on quantity 

harvested for geographic 

region of interest. 

Is the NTFP traded 

in a market? 

Are data on 

annual quantity traded

available? 

Would land 

owners/managers 

have knowledge or 

records of NTFP

harvest on their land? 

Stratified sample 

landowners to estimate 

quantity harvested, or 

use permit records to 

sample harvesters.

Sample general 

public to estimate 

quantity harvested.

Can cross-border 

trading be assumed 

negligible or near 

net zero?

Are harvesters 

and/or local dealers 

known?

Are they a small, 

relatively homogeneous 

group?

Snowball sample 

harvesters or dealers to 

estimate quantity 

harvested in geographic 

region of interest.

Survey or census 

harvesters or dealers to 

estimate quantity 

harvested in geographic

region of interest.

Stratified sample 

harvesters and/or dealers 

to estimate quantity 

harvested in geographic 

region of interest.

Yes

Yes

Yes

No

No

No

No

No

No

Yes

Yes

No Yes

No

Yes

Yes

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 75

Figure 5.2—Decision tree showing the quantification of NTFP provisioning services.
76 Chapter 5. Forest Ecosystem Services: Provisioning of Non-Timber Forest Products

obtain this information, forest agencies would need to develop 

methods and protocols to inventory these products. Efforts are 

underway to develop inventory protocols for some medicinal 

plants harvested for their roots (Chamberlain and others 2013a, 

Small and others 2011).

Given this lack of data, and the probable uneven distribution of 

individual NTFP populations and NTFP harvest within particular 

forest types, estimating the quantity of NTFP supplied by a 

“marginal” acre may not be possible at this time. An impact or 

land-use change on one “marginal” acre may not have any impact 

on NTFP flows at all, whereas a different acre might greatly 

impact flows. Thus, the best available estimate of the impact 

of a marginal change in acreage of forest of a given type on 

NTFP flows is the per-acre average flow for that forest type in a 

particular geographic region. However, it is important to keep in 

mind the fact that average and marginal are different measures 

and to identify conditions under which marginal values are likely 

to be substantially different than average ones. For example, 

there might be great geographic diversity where NTFPs are 

found and also where they are harvested. The areas that provide 

the highest net value of NTFP flows per acre may be those that 

are near access points (e.g., roads and trails), relatively closer 

to towns, and with productive sites, since costs would be lower. 

Also, the presence (or lack thereof) of sufficient substitute NTFP

harvest sites may decrease (or increase) the marginal value of 

a specific site.

Another issue of particular concern for an ecosystem service 

valuation is variation in harvest (flow) over time. As table 5.2 

demonstrates, aggregate NTFP harvests are quite variable. 

Variables explaining change in aggregate NTFP harvest levels 

over time have not been widely researched, but they likely 

include macroeconomic conditions, weather, and policy (Bailey 

199916). The challenge is that most ecosystem service studies 

estimate values only at a single point in time. That single point 

in time could be substantially higher or lower than the average, 

leading to erroneous estimates of the ecosystem service value. 

At its worst, the ecosystem service value might be based on a 

level of harvest that is unsustainable, and thus impossible over 

the long term. If conducting a single point in time estimate, the 

analyst should consult with individuals within the NTFP sector of 

interest to determine if the studied year is likely to be an over- or 

underestimate of the average, and if so, how to adjust it. If current 

harvest levels are unsustainable, they should be adjusted with a 

depletion premium (Godoy and others 1993) or by subtracting the 

amount of the overharvest. The overharvest adjustment would be 

equal to the difference between the annual amount harvested and 

the amount of new product that is generated every year.

16 Also see: Frey, G.E.; Chamberlain, J.L.; Prestemon, J.P. 2017. Supply, demand, 

and regulation of wild American ginseng. Unpublished manuscript. On file with: 

Gregory Frey, Research Forester, USDA Forest Service, Southern Research 

Station, P.O. Box 12254, 3041 E. Cornwallis Rd., Research Triangle Park, 

NC 27709-2254.

The main sources of harvest volumes are the National Forests 

and the U.S. Fish and Wildlife Service. “Cut-and-sold” reports 

are available from the National Forests since fiscal year 1977 and 

are based on harvest permits issued by National Forests (USDA 

Forest Service 2015a). Data on NTFP harvest in the “cut-andsold” reports for 13 National Forests in 12 Southern States (USFS 

Region 8) include Christmas trees, limbs and boughs, foliage, 

mosses, needles, cones (dry or green), transplants, roots, herbs, 

grass, vines, mushrooms, and other plants among non-convertible 

removals from National Forests for which a permit is required. 

Data from “cut-and-sold” reports reflect the permitted harvests 

amounts on National Forests only. Thus, they may not accurately 

represent the actual harvest amounts, and they may underestimate 

harvests for an entire State.

“Cut-and-sold” reports provide information on the volume and 

value of permitted harvests but not the number of permits. Also, 

the value of permitted harvests is based on the amount charged 

for the permit and does not reflect prices paid to harvesters for 

the product. With few exceptions, the “product” description and 

species codes do not provide enough information to identify 

specific species. American ginseng is the exception, though 

the use of the “species” code that identifies this NTFP is 

questionable. For example, the National Forests in Florida use 

the species code for ginseng in reporting “other plant” material 

harvested in 2014, even though the species is not found in the 

State. Other National Forests use the species code for ginseng in 

reporting permitted harvests of “transplants,” which is an unlikely 

use of the product. The National Forest System is aware of these 

challenges and is making efforts to improve the reporting system. 

However, even an improved system will provide data on harvests 

only from National Forests and no other public or private land 

ownership categories.

State forests may also be a potential source of information about 

NTFP harvests. Of the 13 Southern States, 7 (Alabama, Florida, 

Georgia, Kentucky, North Carolina, South Carolina, Tennessee) 

indicated that NTFP harvest on State forests is allowed, at least 

in some cases, while 5 (Arkansas, Louisiana, Mississippi, Texas, 

Virginia) indicated that no NTFP harvest is allowed on any 

State forest, and one State (Oklahoma) has no lands officially 

designated as State forests (Frey and Chamberlain 2016). 

State agency representatives indicated that NTFPs commonly 

harvested from State lands include pine straw, saw palmetto, 

pine cones, berries, medicinal plants, and transplants. In the 

States that allow harvest, activity is controlled by methods such 

as permits (both free and for a fee), leases, and other contracts 

(Frey and Chamberlain 2016). Unfortunately, in most cases the 

fees charged for harvest access are not set by the market, so most 

likely they bear little relation to marginal values. The quality and 

accessibility of harvest data from these State forests varies from 

State to State.
Table 5.7—Southern States certified to export American ginseng

State Ginseng program 

Alabama http://www.agi.alabama.gov/divisions/plant-health/

Arkansasa http://www.aad.arkansas.gov/ginseng-program 

Georgia http://www.georgiawildlife.com/GinsengProgram 

Kentucky http://www.kyagr.com/marketing/ginseng.html 

North Carolina http://www.ncagr.gov/plantindustry/plant/plantconserve/ginseng.htm 

Tennessee http://www.tennessee.gov/environment/article/na-ginseng-program 

Virginia http://www.vdacs.virginia.gov/plant-industry-services-ginseng.shtml

Note: this table provides links to State program Web sites showing the regulations enacted to manage 

the harvest of American ginseng [Date accessed: October 4, 2017].

a On last date of access, the URL listed for Arkansas did not contain information, but it is the official 

website for the Arkansas ginseng program.

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 77

Data are available for American ginseng in States that are 

certified, by the U.S. Fish and Wildlife Service, to export the 

roots. Ginseng buyers are required to register with the appropriate 

State agency, keep records of each transaction (volume and 

harvest location by county), and have ginseng roots inspected 

and certified by the State agency before the roots can leave the 

State. The records are sent to State agencies who report annually 

to the U.S. Fish and Wildlife Service. Web addresses are provided 

in table 5.7 for appropriate State agencies. Buyers of American 

ginseng regularly buy other medicinal forest products, but they 

are not required to report volumes of these other products.

Market Harvest Volumes

Many NTFPs are sold in markets and used, gifted, or bartered by 

harvesters (McLain and others 2008). When a particular NTFP is 

primarily harvested for sale, the analyst must decide if the market 

harvest volume in a State is a reasonable approximation of the 

total volume. Using only market harvest volumes may leave 

out some quantities that are never traded and used for personal 

use by the harvester, but for some products, this might be a 

negligible amount.

NTFP ecosystem values are produced at the location of harvest. 

If data on volumes traded are based on the location of sale rather 

than the location of harvest, the analyst must determine if crossborder (e.g., interstate) trading of NTFPs can be considered 

negligible or, alternatively, if the trade is roughly equivalent in 

both directions (net zero). If one of these two assumptions can be 

made reasonably, then data at location of sale are appropriate for 

estimating NTFPs harvested in the State. On the other hand, if 

trade goes mostly one direction (either mostly into or mostly out 

of a State), then a further survey will be needed to determine the 

location of harvest.

Using existing data sources—The Southern United States has a 

dynamic and significant commercial NTFP industry, with active 

and substantial trade within and across State borders. The States 

of the South are in many cases the global source of particular 

non-timber forest products. Yet complete data are not available 

to fully assess the values of these products. Data are primarily 

available for medicinal forest products, gathered regularly by 

the American Herbal Products Association (AHPA). The AHPA 

surveys its members every 2 years and publishes the findings. 

To illustrate the significance of the medicinal plant industry 

in the South, we provide examples based on these findings. In 

addition to ginseng (described below), the average annual harvest 

(2006- 2010) of another 21 medicinal forest products are tracked 

by the AHPA (Dentali and Zimmermann 2012). Quantities 

range from 43 dry pounds of Virginia snakeroot (Aristolochia 

serpentari) to 2.4 million pounds berries of saw palmetto 

(Serenoa repens). Over 14 years (1997-2010), more than 19,730 

dried tons of dried saw palmetto berries were harvested, primarily 

from the forests of Florida (table 5.4). Average annual harvest 

declined for about half of the products from the 5-year period 

2001-2005 to the period 2006-2010.

We provide two examples of the flow (harvest) approach to 

quantifying NTFPs. First, American ginseng is harvested 

from forests in seven Southern States, and harvests are well 

documented. In this example, we start by estimating the total 

volume of ginseng harvest in each State. Once total volume is 

estimated, we calculate average volume per acre based on the 

number of acres of habitat (table 5.6). The wide range across 

States illustrates the importance of examining market share of a 

product to determine the urgency of valuing any given NTFP in a 

particular State. The second example, saw palmetto, is harvested 

almost exclusively from forests in Florida. Reporting of harvest 

volumes of saw palmetto is voluntary and facilitated through a 

biennial (every 2 years) industry survey.

Example: American ginseng—Data on ginseng harvest is 

available from the U.S. Fish and Wildlife Service, and to a lesser 

extent the National Forest “cut-and-sold” reports. States first need 

to determine if this product is worth valuing. An examination 

of the States that are certified to export ginseng reveals seven 

Southern States (i.e., Alabama, Arkansas, Georgia, Kentucky, 

North Carolina, Tennessee, Virginia) that produce significant 
Ginseng Annual Harvest

Lbs/year

1–90

91–180

181–360

361–600

601–1,200

78 Chapter 5. Forest Ecosystem Services: Provisioning of Non-Timber Forest Products

quantities of American ginseng (table 5.2). From 2002 through 

2013, more than 469,000 pounds of American ginseng were 

harvested from the forests of these States (table 5.3). Of these 

Southern States, western North Carolina, eastern Tennessee, and 

eastern Kentucky accounted for approximately 85 percent of 

the southern harvest from 2002 through 2013 (fig. 5.3). Virginia 

accounted for about 9 percent of the South’s total, while Arkansas 

accounted for about 3 percent.

The importance of ginseng to a State can be further assessed by 

examining permitted harvests on National Forests. Only four 

National Forests reported the permitted harvest of American 

ginseng (table 5.8) and then only for 2009 through 2013. During 

this period, the total amount of American ginseng harvested from 

National Forests in the southern United States was approximately 

4,450 pounds. The National Forests of North Carolina generated 

more than 60 percent of this volume. The Cherokee National 

Forest generated 13 percent of the total volume of American 

ginseng from National Forests.

The next step in quantifying ginseng flow is to determine the 

volumes harvested in each State. These data are available through 

the U.S. Fish and Wildlife Service and can be complemented by 

National Forest data from the “cut-and-sold” reports. Table 5.3 

Figure 5.3—Concentration of American ginseng harvest for 2001-2007. Source: Chamberlain and others (2013).

summarizes volume of ginseng harvest by State and year 

(2002- 2013). State level data can be disaggregated to the county 

level, while national forest data are for the specific forest.

The challenge now is to determine the per-acre marginal flow 

of American ginseng. To approximate this with the average 

production per acre, we need to know how many acres of 

appropriate habitat are producing ginseng in each State. American 

ginseng prefers mixed mesophytic forests (e.g., north-facing cove 

forests) but may be found in similar forest types. FIA classifies 

this forest type as oak/hickory group and maple/beech/birch 

group. Trees found in these groups under which ginseng grows 

include yellow-poplar, northern red oak, black walnut, black 

cherry, ash, yellow birch, and red maple. However, because it has 

been harvested extensively, American ginseng may not appear in 

forests that should support the plant.

Using FIA databases, we can estimate the area of appropriate 

forest habitat in each State (table 5.6). To estimate the volume 

per acre, the best available approximation may be to assume 

that harvest occurs evenly over the entire area of potential 

habitat. This assumption will likely lead to an underestimate 

of the volume per marginal acre where ginseng is actually 

being harvested.
Table 5.8—Pounds of permitted wild-harvested ginseng from National 

Forests, 2009–2013

State National Forest

Pounds of permitted wild-harvesting ginseng

2009 2010 2011 2012 2013 Total

Georgia Chattahoochee/Oconee 38 70 29 50 123 310

Kentucky Daniel Boone 95 74 197 178 132 676

North Carolina Pisgah/Nantahala 637 417 458 626 728 2,866

Tennessee Cherokee 55 36 46 58 406 601

 Total 825 597 730 912 1,389 4,453

Source: National Forest cut-and-sold reports.

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 79

Example: saw palmetto—Saw palmetto is endemic to 

coastal plains from South Carolina to southeastern Louisiana, 

including the Florida panhandle. It is found in every county in 

Florida (Smithsonian Marine Station at Fort Pierce 2015) and 

is considered a keystone species (Carrington and others 2000). 

Figure 5.4 shows saw palmetto growing in east Texas and 

north into Arkansas (Seiler and others 2015). Saw palmetto is a 

characteristic understory shrub in pine flatwoods, prairies, scrub, 

and live oak-sea oats communities (Duever 2011, Smithsonian 

Marine Station at Fort Pierce 2015). It is an indicator of poorly 

drained soils in pine flatwoods (Tanner and others 1996). The 

major center of harvesting is southwest Florida (Collier County), 

although harvesting also occurs in central Florida (Polk and 

Indian River Counties) and in southeast Georgia (Carrington and 

others 2000).

Figure 5.4—Range of saw palmetto. Source: Seiler and others (2015).

The berries of saw palmetto are harvested for their medicinal 

properties. The American Herbal Products Association includes 

saw palmetto in its biennial survey of the herbal industry and is 

the primary source of data regarding harvest volumes. Table 5.4 

presents estimated quantity of harvest volumes (HVs) of saw 

palmetto for 1997 through 2010 as reported by Dentali and 

Zimmermann (2012). They argue that “under-reporting of saw 

palmetto berry harvests is a certainty” (Dentali and Zimmermann 

2012) and a “reasonable estimate” is that harvest data capture 

only half of total dry weight. Estimates of harvest volume data 

are transformed to account for under-reporting (table 5.4). As 

harvesters are paid for fresh fruit, estimates of dried weight are 

multiplied by 3.3 (a standard industry conversion rate) to reflect 

fresh fruit HVs.
80 Chapter 5. Forest Ecosystem Services: Provisioning of Non-Timber Forest Products

Determining per-acre marginal flow of saw palmetto depends 

on accurate estimates of acreage of the plant and yield per acre. 

Mitchell (2014) estimated the suitable habitat for saw palmetto 

in Florida at approximately 9,266,265 acres. We could use this 

estimate to calculate average harvest per acre if we assume 

that all available habitats are harvested. An inventory of actual 

harvest area is needed.

Estimating harvest volumes with no data sources—

Determining commercial HVs when there are no data available 

will require States to survey the industry. Surveying harvesters 

and primary buyers is probably the best way to get volume 

estimate at or near “farm gate.” Neither harvesters nor primary 

buyers are easy to identify as there are few if any directories 

of these market players. Unlike timber processors, there are no 

sampling frames available for non-timber product enterprises.

Significant thought and care should be put into determining the 

(human) population of interest and designing a sample frame 

and sampling technique based on the product(s) of interest. The 

sampling frame might then be stratified to account for variability 

in scale of operation, market participant type, sub-regions, and 

forest type. We present some guidance here on survey design 

and implementation, but an analyst considering a survey method 

should review the broader literature on surveys, including 

Dillman and others (2009).

Step 1: Identify sources of business information—Segmenting 

the NTFP industry by markets can help to focus development 

of sample frames. The segments discussed in “Quantification 

of NTFP Provisioning Services” provide a convenient and 

consistent framework. For medicinal forest products, the list of 

ginseng buyers provides a good starting place to craft a sample 

frame. Ongoing research with the USDA Forest Service and 

Virginia Tech substantiate that most ginseng buyers also buy 

other medicinal herbs. Dealers from around the State could 

be recruited to seek more information and could ask one or 

two simple questions to harvesters. Other sources of business 

information include trade associations (e.g., Christmas tree 

growers, florists and floral decorative, nurseries), U.S. Census 

Bureau (companies over a certain value are listed), State 

Chamber of Commerce, and the Internet. Also, some universities 

may have lists of businesses that have been included in 

previous studies.

Step 2: Determine what information is desired—Keep the 

requested information at a minimum and in an easy format to 

encourage maximum response rates. Surveys that are long and 

tedious typically do not get good response rates. Simple and 

straightforward surveys are much more productive.

Step 3: Create a sample frame—This can be a simple list of the 

market players (i.e., firms, enterprises, companies), with contact 

information, that you want to survey. This group of buyers can 

help identify harvesters who bring products from the forest to 

them. Once the sample frame is completed, maintaining it is 

less costly.

Step 4: Determine the level of sampling needed to achieve 

representation of the population—In some cases, where the 

human population of interest is limited, it may be possible to 

undertake a census of all market players. In other cases, sampling 

the population will be necessary. For example, in 2002 there were 

11 galax dealers in North Carolina and taking a census of these 

would be possible. Conversely, there are hundreds of ginseng 

primary buyers, and sampling the population may be more 

appropriate. Deciding on which approach to use will be easier 

once a sample frame has been created.

In some cases, the human population of interest is uncommon 

among the general population, and population members are 

unknown to the researchers. In these cases, one of a few methods 

for sampling rare populations may be used (see: Kalton and 

Anderson 1986, Wagner and Lee 2014). An example of these 

sampling methodologies includes “snowball sampling,” in 

which a few members of the population are identified by the 

researchers and asked to identify associates that are also within 

the population, a process which is continued until a relatively 

complete list of individuals is developed (Kalton and Anderson 

1986, Wagner and Lee 2014). As an example, ginseng buyers 

may know other dealers who trade in non-ginseng botanicals, 

forming the basis for a snowball sample of botanical dealers. An 

indication that the process has “snowballed” sufficiently to cover 

the population of interest is when the same people are identified 

over and over again.

Step 5: Contact and evaluate non-respondents—Once the 

survey is implemented and responses have been received, 

efforts should be made to get data from non-respondents. Nonrespondents could impact survey results if they represent a large 

portion of NTFP production. Examining this portion of the 

sample is critical to ensuring credible reporting. It allows the 

analyst to determine if the survey represents the population.

Example: pine straw—Pine straw markets operate at various 

levels of formality and scale. There may be a few large scale 

producers that collect needles from many properties in a year, 

as well as numerous smaller scale operations that collect pine 

straw on weekends or seasonally. Furthermore, there may be 

many private landowners who collect their own straw and sell to 

wholesalers or even retail the product directly. With pine straw, 

stratifying the sample of pine straw collectors into large scale, 

small scale, and landowners may make sense. Other stratification 

schemes may be more appropriate for another State. In the subset 

of large scale collectors, it likely makes sense to interview all the 

producers or as many as possible, since there are relatively few 

and each has a disproportionate impact on the market. Small scale 

producers and landowners might be identified by an expert panel 
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 81

Given the lack of publicly available data, if quantification of 

NTFP harvest for non-commercial purposes is desired, it is 

necessary to create and implement a survey. One approach would 

be to survey the general public in each State to determine how 

many people collect NTFPs, how much, and for what purpose 

it is used. For example, Maher and others (2013) used a survey 

of the general population in a region of Alaska to determine 

NTFP harvest quantities for 20 different NTFPs. Robbins and 

others (2008) undertook a phone-based random sample survey 

of residents of New England to examine personal use of NTFPs. 

An alternative approach would be to survey landowners, 

stratified by land ownership type and scale, forest type, and 

other characteristics.

If personal use, or “recreational” NTFP harvest is allowed via 

permits on public lands (National forest, State forest, etc.) in 

the State, it may be possible to access those permit records to 

contact harvesters. This approach was taken by Starbuck and 

others (2004) in Washington State. This would give a narrow 

sample and avoid the expense of surveying the general public, the 

majority of whom may collect no NTFPs at all.

VALUATION OF MARGINAL CHANGES IN 

NTFP PROVISIONING SERVICE

The value of anything is first identified as it fulfills the demands 

of humans. The majority of NTFPs fall within the three important 

categories of needs: physiological (food), safety (medicinal), and 

social (crafts, greenery, flowers) (Blatner and Alexander 1998, 

Greenfield and Davis 2003). When available, market prices are 

the most accurate measure of value at the margin—the value 

society places on one additional unit of a product or service. 

Unfortunately, NTFP markets may be informal with no data 

recorded, or NTFPs may not be traded at all. In this section, 

we discuss estimating the marginal value of products that are 

harvested for commercial and non-commercial uses.

Market Harvest Values

Assigning a price may be the most challenging part of valuation 

and it is best to use market price, if possible. It is usually 

necessary to have a basic understanding of the way the market 

for that product works, as the product changes hands from the 

harvester to the first point of sale, to various intermediaries and 

value-added processors, to the final consumer. To understand the 

intricacies of small, informal markets, studies frequently utilize 

interviews, written surveys, diaries, and face-to-face interactions 

with harvesters and other participants in NTFP activities (e.g., 

Alexander and others 2002b, Blatner and Alexander 1998, Carroll 

and others 2003, Davis and Persons 2014, Emery and others 

2003, Greene and others 2000, Greenfield and Davis 2003, Jones 

and others 2004, Schlosser and Blatner 1995, Wolfe and others 

2005). It is important to keep in mind that the results from these 

studies may be relevant only to the specific locations, products, 

and using snowball sampling. Subsets of the population may be 

further stratified by other characteristics and a sample of each 

subset surveyed.

Some subsets of market participants may be extremely difficult to 

identify; for instance, landowners who collect straw themselves 

and retail directly. That portion of the market that is informal is 

difficult to quantify and track. State analysts may have to rely 

on an expert estimate of the informal market size or undertake a 

few select interviews with sellers that can be identified. Another 

option is to acknowledge that this segment of the market is 

insignificant and missed in the analysis.

Non-Market Harvest Volumes

Non-commercial NTFP uses include subsistence, recreation, 

cultural and spiritual uses, and education. While these uses 

are the most difficult to identify, quantify, and value, they may 

provide significant economic value to a State. Unfortunately, 

we know of very few data collected on non-commercial NTFP 

harvesting, and what is collected does not ask about quantities 

harvested and is limited in its reach to a single land ownership 

class. While this information alone is insufficient to estimate 

the quantity of NTFPs harvested, it could form the basis for a 

secondary survey.

One database that includes information on NTFP harvest is 

the National Visitor Use Monitoring (NVUM) Program, which 

collects data on recreational visitors to National Forests (English

and others 2002). In summarizing the NVUM methodology, 

which is described in detail in English and others (2002), the 

USDA Forest Service (2013) states, “In essence, visitation is 

estimated through a combination of traffic counts and surveys 

of exiting visitors. Both are obtained from a random sample of 

locations and days distributed over an entire forest for a year.” 

These surveys ask whether part of the trip involved gathering 

of NTFPs, or “special forest products,” and whether this was 

the primary reason for the visit (Bowker and others 2009, 

USDA Forest Service 2013). It does not specify which NTFP 

was harvested.

Another source of NTFP harvest information is the National 

Woodland Owners’ Survey (NWOS), which collects data on the 

attitudes, perceptions, and management of family forests in the 

United States (Butler and others 2005, USDA Forest Service 

2015b). The most recent iterations of NWOS include questions 

about whether NTFPs have been collected on these forests during 

the time they have been owned by the current landowners. It asks 

about market segment (edible, medicinal, etc.) and if the product 

was for sale or personal use. However, it does not ask about 

the quantity of product collected, so it would be impossible to 

use these data alone to estimate quantity of NTFP harvested on 

private lands.
82 Chapter 5. Forest Ecosystem Services: Provisioning of Non-Timber Forest Products

and time period, such that decisionmakers are cautioned not to 

apply valuations from one study to other areas or use them to 

aggregate values to a larger scale.

Prices (and harvest quantities) can vary greatly over time (Blatner 

and Alexander 1998, Schlosser and Blatner 1995) due to factors 

such as weather patterns, land use policies, supplies of competing 

food sources, and overall economic conditions in the region, 

creating uncertainty in what price to use. With an understanding 

of the market, sometimes one can track reasons for price and 

quantity variations. For example, in the Pacific Northwest, early 

and heavy snow decreases supply and increases price in floral 

greens. If prices are available there are a number of issues that 

need to be addressed. Prices will vary depending on a number of 

factors such as season, harvest volume, product quality, distance 

to processor or consumer, and locality. Many NTFPs are sold in 

small quantities, so it is hard to quantify and collect data across 

perhaps thousands of individual sellers. Therefore, prices for the 

same product in the same region can vary dramatically based on 

market conditions.

When possible, the ecosystem service value should use the price 

at the first point of sale after harvest; however, without a basic 

understanding of the market, this first point may not be clear. 

Many NTFP harvesters who sell their products have a point of 

sale near the forest and in the local area (Godoy and Lubowski 

1992, Gram 2001). That first point of sale for the harvester is 

the primary buyer who may consolidate transactions and sell to 

secondary buyers, or may be a retailer (from a small roadside 

stand to a local brick-and-mortar store).

NTFPs such as ginseng and other medicinals, and florals for 

landscaping and nurseries, are part of formal markets, with 

dealers and distributors that move the products, with or without 

further value-added processing, along the supply chain. Gatherers 

of pine straw, bark, and other landscaping and nursery materials 

also work in formal markets. Local and regional landscaping and 

gardening nurseries and depots drive demand for much of the 

floral and greenery NTFPs. In addition to local and community 

gardening retail shops and self-employed landscaping businesses, 

harvesters sell generally to small dealers who, in turn, may 

transport wholesale quantities to regional businesses. Harvesters 

of these NTFPs likely realize a larger share of the overall value 

of the delivered product given that much of the intrinsic values of 

these products are reflected in the near natural state and form of 

the raw material itself.

The characteristics and behavior of market agents reflect the 

degree of structure in the market for the particular category 

of NTFP and the spatial scale of the market. In more formal 

markets, established agencies or organizations may track prices 

of particular NTFPs. A few data sources for NTFP prices are 

reported in appendix 5.2. For example, medicinal and herbal 

NTFPs such as black cohosh, bethroot, goldenseal, and bloodroot 

are tracked by the American Herbal Products Association (AHPA 

2007, Dentali and Zimmermann 2012). Past literature may also 

be useful; however, reported prices may not be up-to-date, or may 

not reflect local conditions.

If price data are not available, or are not adequate, from an 

existing data source, prices can be obtained through direct 

surveys of harvesters or buyers. Obtaining price data from 

harvesters or buyers could be costly in time and money across 

a broad swath of producers. Producers may be sensitive 

about revealing actual price information for competition and 

confidentiality reasons. Depending on the type of NTFP, 

having local dealers as a focal point to collect data may work 

to address the decentralized nature of the business. The section 

on “Estimating Harvest Volumes with No Data Sources” 

discusses some approaches for determining basic sampling and 

stratification approaches in the context of NTFPs. The same 

basic decisions apply here, as outlined in the decision tree in 

figure 5.5. These include snowball sampling; stratified sampling 

of harvesters, dealers, and/or landowners; or a survey or census 

of harvesters or dealers without stratification.

Example: American ginseng—In the American ginseng 

market, harvesters sell roots to primary buyers who sort, 

grade, consolidate, and market larger volumes to national and 

international buyers. Davis and Persons (2014) reported historical 

price ranges for American ginseng for 31 years (1982-2012). 

During the years 2000 through 2007, primary buyers paid, on 

average, wild-harvesters $430 for a pound of dried American 

ginseng root (Chamberlain and others 2013b). Table 5.9 

summarizes prices paid to harvesters for a pound of dried 

ginseng. There are other sources, including the State agencies 

with responsibilities for administering the ginseng program. 

These may provide only historical prices; current prices are best 

obtained directly by surveying dealers.

Example: saw palmetto—Estimating the value of saw palmetto 

requires having estimates of prices paid to harvesters. Carrington 

and others (2000) reported prices paid to “freelance” harvesters of 

$0.10-$0.11 (1997-98) per pound of fresh fruit. Mitchell (2014) 

recorded prices paid to harvesters ranging from $0.10 to $1.00, 

and notes that a price of $0.50 per pound is average. Landowners, 

who hired crews to harvest, received $0.20-$0.21 per pound and 

paid harvesters about $0.07 per pound of fresh fruit (Carrington 

and others 2000). To get up-to-date prices, State analysts need to 

visit saw palmetto buying stations during the harvest seasons and 

ask harvesters what they are being paid. Several visits are needed 

throughout the season to record variations.

Carrington and others (2000) also reported one value of particular 

note: the price per acre received by landowners from contractors 

who harvest the saw palmetto. In industries structured this way 

(pine straw may be another example where this type of per-acre 

contracting occurs), this per-acre value in a competitive market 
Use past studies 

and interviews to better 

understand the market

structure.

Is NTFP value based on 

recreation, spiritual or 

cultural uses, or similar 

non-market value?

Is the NTFP traded in a market?

Is the market 

formal or informal?

Are prices published or

price data otherwise 

available for the relevant

point in time?

Are harvesters and/or 

local dealers known?

Use price at closest 

point to harvest.

Survey or census 

harvesters or dealers 

Are harvesters/dealers 

a small, relatively 

homogeneous group?

Are harvesters/dealers 

a small, relatively 

homogeneous group?

Snowball sample 

harvesters or dealers to 

estimate average price at 

closest point to harvest.

Snowball sample 

harvesters or dealers to 

estimate average price at 

closest point to harvest.

Is NTFP harvest in the 

geographic region of 

interest limited to 

well-defined sites?

Utilize travel cost method. 

Sample harvesters to 

determine aggregate 

willingness to pay based 

on distance from sites.

Survey harvesters to 

find willingness to pay 

to access NTFPs using 

stated preference 

methods.

Are harvesters known?

Stratified sample 

harvesters and/or 

dealers to estimate 

average price at closest 

point to harvest.

Yes

Formal Informal

Yes

No

No

No No

No

No Yes

No Yes

Yes

Yes

Yes Yes

No

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 83

Figure 5.5—Decision tree for valuation of marginal changes in NTFP provisioning service.
Table 5.9—Wild American ginseng high and low yearly prices paid to harvesters 

Price 

range 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

$/dry pound

Low 250 300 250 250 300 400 250 350 350 320 400 800

High 500 400 500 550 600 1,150 1,000 600 1,100 750 1,250 850

Source: Davis and Persons (2014).

84 Chapter 5. Forest Ecosystem Services: Provisioning of Non-Timber Forest Products

is essentially the ecosystem value as we have defined it, and 

may even obviate the need for collecting information on harvest 

quantity (see section on Conceptual Model). However, such 

per-acre contracting is not typical among NTFPs. Landowners 

who contracted for the harvesting of saw palmetto received about 

$15.42-$31.25/acre at 151-303 pounds per acre.

Non-Market Harvest Values

When traditional markets do not exist, valuing the provisioning 

services of non-commercial NTFPs poses difficulties. Nonmarket valuation techniques, as described in chapter 2, can be 

applied to NTFP harvesting opportunities. In many cases, NTFP 

harvest may be considered recreational in nature, and recreation 

valuation techniques can be applied (chapter 2). Even if the 

NTFP harvest is not considered “recreational” to the harvester 

(e.g., for subsistence, cultural, spiritual, educational, or other 

purpose), from a methodological standpoint, similar valuation 

techniques can be used. Contingent valuation and contingent 

behavior methods are the most popular examples of stated 

preference methods. Revealed preference methods for nonmarket valuation are based on actual behavior rather than stated 

intentions. Hedonic pricing uses data on real attributes to estimate 

how those attributes affect market prices. The travel cost method 

is the most commonly used revealed preference technique when 

valuing access to public lands for recreation activities.

Imputed values method—When the NTFP of interest has no 

market value, an alternative approach would be to use imputed 

values based on the market value of a good that is commonly 

bartered for the NTFP, or the market value of a close substitute 

for the NTFP (Godoy and others 1993). These would be good 

approaches if the analyst was confident that the estimated 

imputed or substitute prices were consistent enough across a 

broad human population that they could be relied upon. However, 

in most parts of the United States, bartering for lack of a market 

is not widespread enough to be consistently applied. Likewise, 

finding a true market substitute for a non-market product is 

unlikely. For example, one might propose that the value of storebought (field cultivated) berries could be used as a substitute for 

non-commercial wild-harvested berries. However, if one were to 

ask the consumer, he or she likely places high value either on the 

harvesting itself (for cultural or recreational reasons) or on the 

fact that the berries are natural.

Hedonic pricing method—Similarly, hedonic pricing may have 

applicability for NTFP valuation in some rare cases, but the 

method does not seem promising. We are unaware of any studies 

that have used hedonic pricing for NTFP valuation. We do not 

want to dismiss the concept entirely, however. Hedonic pricing 

with NTFPs would rely on estimating the difference that people 

are willing to pay to access or purchase land that has NTFPs, 

compared to similar land that has equivalent characteristics but 

no NTFPs. Unfortunately, data on real estate sales do not include 

availability of NTFPs on the property, and the use of any proxy 

(e.g., forest type) for NTFP availability is just as likely to also be 

a proxy for many other characteristics other than NTFPs, all of 

which might impact price just as much or more than presence of 

NTFPs. One might consider a “market” for campsites or some 

similar access points, which have NTFPs or not, but it is hard 

to see how this could form the basis for a study or how the data 

could even be collected. Most campgrounds charge a flat rate 

regardless of the site; if sites with NTFPs are filled before other 

sites, this might be an indicator of some value, but trying to 

estimate that value in dollar terms is challenging in the least.

Stated preference methods—Stated preference methods could 

be used to value non-market NTFPs, although we are not aware 

of any studies in the United States that have done so. The analyst 

would use one of various approaches, described in more detail 

in chapter 2, to elicit people’s willingness to pay for a particular 

product, through a survey. In this case, a best metric would be 

to elicit a willingness to pay to access the product, assuming 

that the survey respondent would hypothetically have to harvest 

and process the product themselves. In this way, the respondent 

implicitly factors out harvest costs. Stated preference methods 

may be the most applicable for NTFPs when the population of 

harvesters can be identified. This would serve as the population 

for the survey.

Travel cost method (TCM)—If the harvest or collection of 

NTFPs is not traded commercially, and is mostly valued for 

recreational, spiritual, or cultural purposes, then the total quantity 

of product harvested may be less important to value than access 

to the resource. TCM can be used to estimate a value per trip or 

per visitor-day. Because the TCM is used to derive a demand 

curve for recreation, and if quantity of NTFP was calculated on a 

per trip basis, a dollar value per unit of NTFP or per acre can be 

calculated (Starbuck and others 2006).
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 85

To estimate demand for NTFP harvesting on southern forests 

using the TCM, a crucial assumption is made that the cost of 

travel to the site (including associated fees) is a proxy, or shadow 

price, for the harvesting activity. In the United States, TCM has 

been rarely used to value NTFP provisioning services, with two 

examples being Markstrom and Donnelly (1988) and Starbuck

and others (2004). However, the methodology is not substantially 

different from how TCM would be used to value any recreational 

resource, and more guidance can be found in chapter 2. A 

comprehensive review of the development of recreation demand 

models and TCM can be found in Phaneuf and Smith (2005).

TCM involves surveying or observing recreational participants 

at one or more sites, with the goal of determining the cost 

of traveling to the site and the time spent at the site for each 

participant. These data are used to generate a demand curve, 

usually expressed in terms of numbers of visits at various levels 

of cost. For TCM to be effective, the analyst must be able to 

determine a distance from origin to destination to calculate travel 

costs. One approach to valuing NTFPs would be to use the ZIP 

code of origin to the forest centroid as the distance calculation 

upon which the travel cost is based. This allows TCM to be 

used to define a value per unit of harvest for a regional area 

(such as a forest area with a high density of NTFP harvesting). 

The inaccuracy introduced by using a forest centroid instead 

of a specific coordinate is well within the error of the estimate 

(Bowker and others 2009, English and others 2002).

While imperfect, TCM can yield important economic and 

demographic information about NTFP harvesting and provide a 

proxy for the value of the NTFPs associated with recreation. If a 

State has a number of forests that provide the NTFP in question, 

the analyst would want to survey visitors about which forest they 

visited and then aggregate across all the forests of similar type 

to estimate a total State value. For any non-market valuation, 

one must survey visitors and obtain information on behavior to 

estimate demand and hence monetary value. TCM can be applied 

to any spatial scale so long as the origin-destination information 

is obtained and there is sufficient information to calculate a cost 

per trip or per day value.

The sampling frame and visitor characteristics need to 

be carefully considered. When a survey is designed, map 

information that shows trail and parking access points must be 

used to identify where to “trap” the most representative sample. 

Questions regarding demographics and activities can then 

be compared to other sampling or population information to 

generate an estimate of the sample characteristics relative to the 

population. Numerous estimation methods exist to account for 

endogenous stratification and other sampling issues known to be 

exist in recreation data. With a well-designed sampling frame and 

survey protocol issues related to the reliability of the estimate 

resulting from sampling issues can be minimized and does not 

significantly increase the cost of generating a non-market value 

for an NTFP. For TCM to be effective the survey must ask 

information about the purpose of the trip and what portion of trip 

time and expenditures are related to each listed activity. This is 

easily done by a well-designed survey instrument and does not 

pose a significant issue in the application of TCM.

The analyst must consider the number and distribution of harvest 

sites of the particular NTFP throughout the State, and whether 

only one site or multiple sites are of interest. In general, singlesite analysis would be relevant for a narrow policy question 

involving only that site (for example, a change in a National 

Forest management plan) or in the rare case where only one 

harvest site exists. Multiple-site analysis would be appropriate 

for a statewide valuation if the NTFP is restricted to a relatively 

few, relatively well-known sites, such as National or State forests. 

Bowker and others (2009) constructed a multiple-site TCM 

using NVUM data from 120 National Forests, which included 

NTFP gathering, although it did not estimate a value for NTFPs 

independently. The complexity of harvesting location and site 

definition for a multi-site TCM are not insurmountable, and 

again relate to the development of the sampling frame and survey 

implementation. Bowker and others (2009) developed a rigorous 

sampling framing and survey method, and the NVUM results 

could have easily been extended to NTFP if a question on NTFP 

harvesting had appeared as a list of recreational activities.

In summary, for TCM to be effective, one must collect origindestination information and demographic information. In a 

well-executed TCM, it is important to ask about the primary 

purpose of the trips and the types of activities and/or percentage 

of trip for each purpose in order to handle issues of substitution 

that can affect valuation (Freeman 2003, p. 424-425). These 

considerations provide initial insight and guidance about using 

the travel cost method to value NTFP provisioning. While it is 

has been infrequently used for NTFPs, the TCM may offer a way 

to value NTFPs that are harvested recreationally.

ESTIMATION OF PRODUCTION COSTS

Provisioning ecosystem service can be interpreted to mean the 

portion of value of a product that is generated by the ecosystem. 

In this case, the portion of value that is generated by humans, that 

is the human-incurred production costs, should be factored out 

(equation 1), leaving a “residual value” that can be attributed to 

ecosystem function. Human-incurred production costs include 

costs of establishment, management, and harvest. In the case 

of wild-harvested NTFPs, there are no costs of establishing or 

managing these populations. Ginseng harvesters are supposed 

to plant seeds that are found on plants that they harvest. In this 

case, the “establishment cost” would be the time it takes for the 

harvester to plant seed, which likely would be negligible in this 

case, and could be simply considered part of the harvest cost. 

Harvesters of other products have fewer restrictions. This section 

focuses on measuring costs incurred in production of NTFPs.
86 Chapter 5. Forest Ecosystem Services: Provisioning of Non-Timber Forest Products

To estimate the cost of harvesting an NTFP, an analyst would 

need to interview or survey the harvesters. The costs of 

harvesting include fuel, any equipment needed to harvest, any 

food or lodging required (most harvesters in Southern United 

States probably do not overnight anywhere during harvest trips), 

and the harvesters’ labor.

In many cases, labor is the principal cost of NTFP production 

and is not paid in terms of a wage. The value of this labor can 

be estimated as the “opportunity cost” of some alternative 

economic activity. In general, if the harvest activity is relatively 

low-skill, the average hourly wage for low-skill labor may be an 

appropriate value to put on this opportunity cost. This is usually 

somewhat higher than minimum wage (but could be lower than 

minimum wage if there is a larger informal labor market in the 

area). Certain specific types of NTFP harvest activities might 

correspond more closely with higher-skilled employment. The 

U.S. Bureau of Labor Statistics provides data on average wages 

by occupation and area, which can be used to find an appropriate 

opportunity cost of time for the typical NTFP harvesters in your 

area (U.S. Bureau of Labor Statistics 2016).

For certain products, there might be numerous harvest methods 

with varying levels of mechanization. For example, pine straw 

can be harvested with a rake and a wooden manual baler, or with 

a tractor and mechanical baler. For the former, equipment costs 

are minimal and labor might be the most important input, so 

using an appropriate opportunity cost of time is important. For 

the latter, harvest would also include such expenses as equipment 

depreciation, fuel, etc.

Determining production costs of NTFPs harvested from 

“managed” populations of NTFPs will require “utilization” 

studies, similar to what the USDA Forest Service FIA program 

does for timber. In these types of studies, the analysts actually 

spend time monitoring all aspects of establishment and 

management of the product. Care must be taken not to double 

count costs when estimating production costs for NTFPs that 

might be produced with other products (e.g., pine straw with 

timber and cattle). Also, the amount of labor required should be 

recorded and stratified by different tasks (e.g., site preparation, 

maintenance, harvesting, transport) along with equipment and 

materials costs. To make these studies relevant, they need to be 

replicated over time and locations so that generalizations can 

be made.

Some NTFPs are being grown in a “forest farming” system that 

have associated establishment and management costs. These 

costs include labor to undertake site preparation, planting, and 

maintenance. The costs of seed, equipment, pesticides, and other 

inputs can be estimated directly by monitoring forest farming 

activities. A few studies have created “forest farming budgets” 

for selected NTFPs (e.g., Burkhart and Jacobson 2009, Davis and 

Persons 2014); however, unlike typical crop budgets published 

by State Cooperative Extension services, these sources are not 

updated periodically or replicated in different geographic areas.

Initially, efforts to estimate the value of natural forest ecosystems 

to provide NTFPs can disregard production costs. There is little 

evidence that most NTFP harvesting from natural populations is 

being managed, nor are there associated establishment costs. As 

forest management agencies begin to actually manage for these 

products, then associated costs will occur and can be estimated.

SCALING UP/AGGREGATING

The guidance here has been written with a State-level valuation 

in mind. We assume that the desire is in valuing NTFPs across 

the entire State by forest type and landowners. Many of the 

recommendations may be valuable for other spatial scales. To 

be sure, local (e.g., National Forest or district) level valuations 

provide valuable information for managers of those areas, but 

they often cannot be scaled up because of differences within 

the population of harvesters. For example, if a small number of 

individuals have an extra-large impact on the market, a simple 

random sample at low sampling intensity may not capture the 

value accurately. A small number of large harvesters can skew 

results of a valuation exercise. It is, therefore, critical that surveys 

of harvesters get a representative sample of all harvesters.

A State-level valuation should strive to account for variations 

in harvester populations by appropriately sampling from 

different operational scales, forest types, ownership classes, 

and/or management/regulation regimes. This is called stratified 

sampling, which strives to sample across the variety of players. 

After an initial survey of the populations, efforts should be made 

to make sure that each strata is represented. Also, efforts should 

be made to get responses from “non-respondents.”

Results of small studies can be “scaled up” or aggregated to 

represent State-level spatial dynamics with effort, thought, and 

consideration. Small scale “pilot” studies allow the researcher 

or analyst to better understand factors that may inform larger 

studies of challenges that need to be addressed. Undertaking 

small studies across landscapes can provide valuable information 

on per-acre production, growth, and yields and operational costs. 

To scale these to State-level analyses requires that they capture 

variations across forest types and landowner classification. To 

aggregate small studies to the State level, they must represent all 

spatial and temporal variations.
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 87

CONCLUSIONS

Non-timber forest products contribute to the economies of every 

State in the South. They are important provisioning services 

of all forest ecosystems of the region. Yet, they have not been 

included in efforts to value forests. People collect these products 

for personal consumption and to generate income to support 

families. Different approaches are used to estimate market and 

non-market values of these products. Estimating market values is 

simply the product of quantity harvested (or standing stock) and 

market price (farm gate) as a proportion of habitat. Non-market 

estimation is more complicated and requires interviewing and 

surveying harvesters and translating results into comparable units 

of measure.

The major challenge with estimating the provision service of 

ecosystems for NTFPs is the lack of data. In general, there are 

insufficient data to estimate the provisioning of NTFPs from 

forest ecosystems. There are volume data for a few NTFPs, 

such as American ginseng, although this is the only NTFP 

for which county-level data is available. Price data exists for 

ginseng as well, but not for most other products. Determining 

standing stock of NTFPs will require inventorying plants within 

the forests, similar to what is done with trees. Determining the 

flow, or annual harvest rate, will require utilization surveys of 

market players.

Designing and implementing surveys requires thought and 

consideration for the designed end-use. The first task will be to 

develop a sample frame that represents various market segments 

(for market valued NTFPs) and personal use harvesters. These 

will take significant time and resources, but once these are 

completed, maintaining them is less costly. There are standard 

and well-accepted methods for designing and undertaking 

surveys (Dillman and others 2009). 

The initial investment to estimate the provisioning of NTFPs 

by forest ecosystems may be significant for any one State. By 

collaborating on valuing specific priority (high valued) products, 

States can reduce their investment requirements. Further, after 

the initial investment has been made, replicating and refining 

the estimating efforts will be significantly reduced. All evidence 

indicates that NTFPs are economically and ecologically 

significant and worthy of valuing. The total ecosystem 

provisioning value of forests will remain elusive until NTFPs 

are included.

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Paoli, G.D.; Peart, D.R.; Leighton, M.; Samsoedin, I. 2001. An ecological and 

economic assessment of the nontimber forest product gaharu wood in Gunung 

Palung National Park, West Kalimantan, Indonesia. Conservation Biology. 

15(6): 1721-1732.

Peters, C.M.; Gentry, A.H.; Mendelsohn, R.O. 1989. Valuation of an Amazonian 

rainforest. Nature. 339: 655-656.

Phaneuf, D.J.; Smith, V.K. 2005. Recreation demand models. Handbook of 

environmental economics. 2: 671-761.
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Robbins, P.; Emery, M.R.; Rice, J.L. 2008. Gathering in Thoreau’s backyard: 

nontimber forest product harvesting as practice. Area. 40(2): 265-277.

Robles-Diaz-de-Leon, L.; Kangas, P. 1998. Evaluation of potential gross income 

from non-timber products in a model riparian forest for the Chesapeake Bay 

watershed. Agroforestry Systems. 44(2-3): 215-225.

Salwasser, H. 2006. Meeting the challenges of sustainability. Corvallis, OR: 

Oregon State University.

Schlosser, W.E.; Blatner, K.A. 1995. The wild edible mushroom industry 

of Washington, Oregon and Idaho: a 1992 survey. Journal of Forestry. 

93(3): 31- 36.

Seiler, J.; Jensen, E.; Niemiera, A.; Peterson, J. 2015. Saw palmetto. Blacksburg, 

VA: Department of Forest Resources and Environmental Conservation, College 

of Natural Resources and Environment, Virginia Tech. http://dendro.cnre.

vt.edu/dendrology/syllabus/factsheet.cfm?ID=355. [Date accessed unknown].

Small, C.J.; Chamberlain, J.L.; Mathews, D.S. 2011. Recovery of black cohosh 

(Actaea racemosa L.) following experimental harvests. The American Midland 

Naturalist. 166(2): 339-348.

Smith, J.; Crone, L.K.; Alexander, S.J. 2010. A U.S. Forest Service special forest 

products appraisal system: background, methods, and assessment. Gen. Tech. 

Rep. PNW-GTR-822. Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station. 22 p.

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smsi.si.edu/irLspec/Sereno_repens.htm. [Date accessed: February 26, 2015].

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special forest products harvesting: a two-step travel cost recreation demand 

analysis. Journal of Forest Economics. 10(1): 37-53.

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forest products. In: Pearce, D., ed. Valuation methodologies. Cheltenham, 

United Kingdom: Edward Elgar. 27 p.

Tanner, G.W.; Mullahey, J.J.; Maehr, D. 1996. Saw-palmetto: an ecologically 

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accessed: unknown].

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February 4, 2016].

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Inventory and Analysis.

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Wolfe, K.L.; Best, M.J.; Price, T. 2005. Pine straw market analysis for southwest 

Georgia. Market Analysis 05-01. Athens, GA: The University of Georgia. 10 p.
Appendix 5.1

Summary of select valuation studies of NTFPs in the U.S. South and around the world, cont.

Citation

Geographic 

location

Stock 

or flow 

quantification

Market 

or nonmarket 

valuation

Marginal value 

estimates Other methodological notes

Adger and 

others (1995)

Mexico Multiple NTFPs

$330 per hectare per year

Coffee and other NTFPs

$1,540 per hectare per year

Alcorn (1989) Mexico

Alexander and 

others (2002a)

Pacific 

Northwest

flow market Matsutake, chanterelle, 

and morel mushrooms

$0.4-99 per hectare 

per year

Describes soil expectation 

value approach similar to that 

in section 1.2 here. Describes 

assumption and methodological 

choices. Variation in values due 

to differences in species, location, 

and methodological assumptions.

Chamberlain, 

Prisley, and 

others (2013)

U.S. South flow market Not applicable Calculates average annual harvest 

and revenue (2000-2007) for 

ginseng in the United States. 

De Groot, 

Wilson, and 

Boumans (2002)

Worldwide flow market 

and nonmarket

Not applicable Synthesis of meta-analysis which 

summarizes the relationships 

between ecosystem functions and 

monetary valuation techniques

Godoy and 

Feaw (1989)

Indonesia Rattan

$495 per hectare per year

Gram (2001) Peru flow market 

and nonmarket

Fishing, hunting, gathering

$9 - $17 per hectare 

per year

Analysis of strengths and 

weaknesses of valuation methods 

for economic importance of local 

extraction activities 

Grimes and 

others (1994)

Ecuador flow market Fruit, medicinal and 

handicrafts

NPV $1,257 - $2,939 per 

hectare per year

Estimates sustainable harvest 

levels and net present value of 

fruit, medicinal and handicraft 

products on three plots

Greenfield and 

Davis (2003)

North 

Carolina

flow market Not applicable Looks at 46 forest botanical 

products (medicinal, edible plants, 

floral plants, ornamentals) in 

25 western counties, using an 

exploratory, inductive approach 

estimate volumes, sales, 

economic and socio-economic 

information and prices of NTFPs.

(continued to next page)

90 Chapter 5. Forest Ecosystem Services: Provisioning of Non-Timber Forest Products
Summary of select valuation studies of NTFPs in the U.S. South and around the world, cont.

Citation

Geographic 

location

Stock 

or flow 

quantification

Market 

or nonmarket 

valuation

Marginal value 

estimates Other methodological notes

Godoy and 

Lubowski (1992)

Sri Lanka

Brazil

Peru

flow market 

and nonmarket

Florals 

$50-$420 per hectare 

per year

Babassu palm products

$59 per hectare per year

Wild camu

$167 per hectare per year

Summarizes net economic 

valuation studies in multiple 

countries

Paoli and others 

(2001)

Indonesia stock 

and flow

market Gaharu wood

$3.80 - $18.56 per hectare

Average of $10.83 

per hectare

Estimates net present value per 

hectare for five major forest types

Peters, Gentry, 

and Mendelsohn 

(1989)

Ecuador Fruit and latex

$6,820 per hectare 

per year

Robles-Diazde-Leon and 

Kangas (1998)

Chesapeake 

Bay 

Watershed, 

Maryland

stock 

and flow

nonmarketOrnamentals, edible fruits, 

edible nuts

$60,694 per hectare 

per year

Calculates total gross income 

obtained from a riparian 

forest buffer

Starbuck and 

others (2004)

Gifford 

Pinchot 

National 

Forest,

Washington

flow nonmarketNot applicable Estimates recreation demand 

(consumer surplus) for 

NTFP gathering

Tewari (2000) stock 

and flow

market 

and nonmarket

Explains the variation dynamic 

and static, income and wealth 

valuation models of NTFPs

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 91

Appendix 5.1 continued
Forest Type Group/Species

White / red / jack pine group

Jack pine

Red pine

Eastern white pine

Eastern white pine / eastern hemlock

Eastern hemlock

Spruce / fir group

Balsam fir

White spruce

Red spruce

Red spruce / balsam fir

Black spruce

Tamarack

Northern white-cedar

Fraser fir

Red spruce / fraser fir

Longleaf / slash pine group

Longleaf pine

Slash pine

Tropical softwoods group

Tropical pines

Loblolly / shortleaf pine group

Loblolly pine

Shortleaf pine

Virginia pine

Sand pine

Table Mountain pine

Pond pine

Pitch pine

Spruce pine

Other eastern softwoods group

Eastern redcedar

Florida softwoods

Exotic softwoods group

Scotch pine

Other exotic softwoods

Norway spruce

Introduced larch

Forest Type Group/Species

Oak / pine group

Eastern white pine / northern red oak / 

 white ash

Eastern redcedar / hardwood

Longleaf pine / oak

Shortleaf pine / oak

Virginia pine / southern red oak

Loblolly pine / hardwood

Slash pine / hardwood

Other pine / hardwood

Oak / hickory group

Post oak / blackjack oak

Chestnut oak

White oak / red oak / hickory

White oak

Northern red oak

Yellow-poplar / white oak / northern red

 oak

Sassafras / persimmon

Sweetgum / yellow-poplar

Bur oak

Scarlet oak

Yellow-poplar

Black walnut

Black locust

Southern scrub oak

Chestnut oak / black oak / scarlet oak

Cherry / white ash / yellow-poplar

Elm / ash / black locust

Red maple / oak

Mixed upland hardwoods

Oak / gum / cypress group

Swamp chestnut oak / cherrybark oak

Sweetgum / Nuttall oak / willow oak

Overcup oak / water hickory

Atlantic white-cedar

Baldcypress / water tupelo

Sweetbay / swamp tupelo / red maple

Baldcypress / pondcypress

Forest Type Group/Species

Elm / ash / cottonwood group

Black ash / American elm / red maple

River birch / sycamore

Cottonwood

Willow

Sycamore / pecan / American elm

Sugarberry / hackberry / elm / green ash

Silver maple / American elm

Red maple / lowland

Cottonwood / willow

Oregon ash

Maple / beech / birch group

Sugar maple / beech / yellow birch

Black cherry

Hard maple / basswood

Red maple / upland

Aspen / birch group

Aspen

Paper birch

Gray birch

Balsam poplar

Pin cherry

Tropical hardwoods group

Sable palm

Mangrove

Other tropical

Exotic hardwoods group

Paulownia

Melaleuca

Eucalyptus

Other exotic

92 Chapter 5. Forest Ecosystem Services: Provisioning of Non-Timber Forest Products

Appendix 5.2

FIA Forest Groups and Associated Tree Species
Appendix 5.3

SUMMARY OF DATA SOURCES

Data sources for non-timber forest products in the U.S. South are varied and disparate

Source Data type Notes

Interviews/surveys of harvesters and dealers price, volume, acreage

USDA Forest Service cut and sold reports volume includes value of permit fees 

USDI Geological Survey models acreage, geographic 

distribution

species habitat

Interactive Tariff and Trade DataWeb 

(U.S. International Trade Commission 2016)

volume export data

Greenfield and Davis (2003) price North Carolina ginseng, 

goldenseal, galax, ramps

Davis and Persons (2014) price historic ginseng prices

U.S. Fish and Wildlife Service volume, geographic 

distribution

ginseng, county and State

American Herbal Products Association volume 17 Appalachian medicinal 

products

National Woodland Owners survey acreage By number of owners, type 

of sale, type of product

USDA Forest Inventory and Analysis acreage, geographic 

distribution

forest type, bark

State Natural Heritage databases geographic distribution —

Wholesalers price, volume various NTFPs

Ginseng dealers price, volume by State

National Christmas Tree Association price, volume, acreage by total U.S., State

State agriculture departments price, volume pine straw

Farmers markets price, volume edibles

USFS and State forestry agencies volume also permit fees

Maple Syrup Association price, volume, acreage and other saps

National Agriculture Statistics Service price, volume maple syrup, blueberries

Green nursery/landscaping industries/

associations

price, volume forest florals, cones

Georgia Farm Gate Value Reports price, volume includes pine straw

Mitchell (2014) price, volume, acreage saw palmetto

Chamberlain and others (2013a) price, acreage black cohosh

Chamberlain and others (2013b) price, volume ginseng

For the purposes of this report, and for future analysis by State foresters, the above list provides a starting point of 

some specific research studies and general resources with regular collection and compilation of data on NTFPs.

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 93

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 95

the wealthier the affected population. Thus, in addition to 

quantifying the flows of ecosystem services in particular 

times and places, the analyst must consider the size of the 

population that benefits from those services. The relevant 

“public” can range from immediate downstream water users 

to the global population affected by climate change. State 

assessments should identify both the relevant “public” who 

reside in the State, and the total “public” of all people who 

benefit from ecosystem services generated by forests in the 

State no matter where they reside.

5. Diminishing returns are critical and inescapable. The 

other side of the valuation coin concerns the abundance of 

supply. Economic value is determined on the margin: the 

economic value afforded by an acre of forest is determined 

not by the services the forest as a whole provides, but rather, 

by what additional services that acre provides over and 

above those that would have been available in its absence 

(i.e., the forest’s marginal product). With rare exceptions 

(e.g., where additional acres provide habitat contiguity), the 

value of the ecosystem services provided by each additional 

unit of forest diminishes as the total area of forest increases, 

and vice-versa: i.e., an additional unit of forest is more 

valuable where there is less total forest area. Analysts should 

only use valuation methods that acknowledge diminishing 

returns, and they should caution against inappropriate use of 

their estimated marginal values. For example, they should 

discourage multiplying the total acres of forest in a State by 

the marginal value of ecosystem services from one additional 

acre of forest.

6. Only final services should be included to avoid doublecounting. It is inappropriate to sum the value of an 

ecosystem service that contributes to some final outcome and 

the value of that outcome itself. For example, we do not need 

to estimate the value of the soil structure created by forests if 

we have an estimate of the value of the resulting stabilization 

of water flows, because the value of the soil structure as an 

input into the hydrological system is already reflected in the 

value of that watershed service. Likewise, accounts should 

not include both the value of a forest in filtering water so that 

expensive purification is not required and the cost savings 

from not having to purify water that has been cleansed by a 

forest. A corollary is that in order to fully account for forest 

values, we need estimates of the values of all final ecosystem 

services now and into the future.

T

his concluding chapter recommends a standardized approach 

to accounting for forest ecosystem services in the Southern 

States. First, we synthesize 10 principles from the preceding 

chapters. Next, we present a template for State forest ecosystem 

service assessments, recommending a staged approach with 

five outputs.

PRINCIPLES OF ECONOMIC ACCOUNTING 

FOR ECOSYSTEM SERVICES

1. Accounting involves multiplying total quantities by 

marginal values. Accounting requires understanding 

total annual flows of ecosystem services from forests; for 

example, the total volume of water that flows through a 

forest ecosystem, the sediment load in water exiting those 

ecosystems, or the net amount of carbon sequestered or 

released. Other examples include the total number of 

recreation user days or total volume of medicinal plants 

harvested. Weighting each of these physical flows by its 

marginal value provides an economically meaningful 

measure of the value of forest ecosystem services.

2. Not all units of an ecosystem service have the same 

marginal value. Just like a market price, the marginal value 

of an ecosystem service reflects its supply and demand in a 

particular time and place. Thus, the most useful measures 

of the value of ecosystem services are based on spatially 

disaggregated estimates of changes in the annual flows of 

those services multiplied by marginal values that reflect the 

level of supply (e.g., extent of forest ecosystem) and demand 

(e.g., number of people who can “consume” the ecosystem 

service) in different locations.

3. Marginal values depend crucially on context. Economic 

value reflects scarcity. When the supply of a good or service 

is limited, it is economically valuable. Goods and services 

with abundant supply are less valuable. Scarcity is relative, 

as it is determined by the relationship between the supply 

and the demand for a good or service at a particular time 

and place. Thus, values calculated for one time and place 

may be very different for another. A spatial catalog of values 

can serve for both tracking changes over time and for costbenefit analysis of alternative policies.

4. When ecosystem services are public goods, their 

value depends on the size of the “public.” Demand–or 

willingness to pay–is, in general, greater the larger and 

Chapter 6

Conclusion

Erin O. Sills, R. David Simpson, D. Evan Mercer
96 Chapter 6. Conclusion

7. Some–but not all–final ecosystem services are reflected in 

traditional economic accounts. The value of the inputs used 

to produce marketed goods and services is reflected in the 

value of those goods and services as recorded in GDP (Gross 

Domestic Product). Because inputs include forest ecosystem 

services, we can say that some part of GDP is attributable to 

those services. For example, the total value of agricultural 

production reflects the values of hydrological and pollination 

services provided by forests to the agricultural sector. In 

this case, accounting for forest ecosystem services means 

giving them credit for their contribution to GDP. Other 

ecosystem services affect well-being directly in ways that 

are not counted in GDP, e.g., by providing a more pleasant 

environment and creating a sense of place. Just as the value 

of home-cooked meals (and therefore the contribution of 

home cooks to our well-being) is excluded from GDP, so 

are the psychological benefits of the forest landscape (and 

therefore the contribution of that cultural ecosystem service 

from forests).

8. Economic accounts sum up changes experienced by 

everyone in the accounting framework, e.g., everyone 

in the State. A positive sum indicates the possibility that 

everyone could gain. For example, an increase in the total 

value of forest ecosystem services in a State means that there 

is a positive gain in value that could be distributed among 

everyone in the State. However, gains (and losses) are almost 

never distributed evenly, and concentrated gains or losses are 

often the most visible and most discussed. Both accounting 

totals and the distribution of gains and losses are relevant to 

forest policy decisions.

9. Accounting for ecosystem services necessitates thinking 

broadly ... Ecosystems give rise to economic values that 

span a broad spectrum. At one end are those that accrue 

largely to private individuals in consequence of private 

choices, such as recreational use of forests or collection 

of non-timber forest products. At the other end are values 

that may benefit people around the world, such as carbon 

sequestration. Some global values, for example the value of 

preserving endangered species, may not be associated with 

any market transactions. In between are services provided to 

local communities, such as flood protection and groundwater 

re-charge. Information from multiple sources is required 

to estimate quantities and values for the various types of 

services. Even in State studies focusing on values that 

accrue to State residents, values to populations outside the 

State should be noted, as they are likely to be relevant to the 

design of ecosystem service markets and national policies 

that affect the State.

10. ... but also prioritizing. The ultimate goal of ecosystem 

accounting exercises is to express all ecosystem service 

values in dollar terms. This is a long-term aspiration that 

is not fully achievable in the near future. Meanwhile, State 

assessments can:

a) identify all relevant forest ecosystem services 

(and disservices),

b) note those likely to be most affected by changes in 

forest area,

c) compile estimates of the marginal value of those services 

from comparable prior studies, and

d) call for additional research on services that lack marginal 

values but that are likely to be both valuable and 

vulnerable to changes in forest ecosystems.

In this way, State assessments can focus future valuation 

efforts on ecosystem services with values that are likely to be 

substantial but that have not been estimated using theoretically 

and methodologically sound approaches. They should steer 

researchers away from “deriving more precise estimates of 

zero,” i.e., employing the best methods and data to estimate 

values that are too small to affect decisions about forests. While 

this future research is pending, State assessments should focus 

on quantifying annual flows of these ecosystem services in 

physical terms, rather than heroically extrapolating values from 

other studies in ways that ultimately cannot be defended. An 

adage worth remembering here is that “absence of evidence is 

not evidence of absence.” The forest ecosystem services that 

have been valued in monetary terms are just a subset of all 

ecosystem services relevant to decisions about forest policy 

and management.

RECOMMENDED STRUCTURE FOR ASSESSMENT 

OF FOREST ECOSYSTEM SERVICES

These 10 principles imply that economic accounting of ecosystem 

services is not a single well-defined task, but rather requires 

tapping numerous data sources, making numerous judgment 

calls, and tailoring the approach to numerous different ecosystem 

services. As a result, we recommend that States undertake 

ecosystem services assessments in stages (fig. 6.1), allowing for 

adaptive management of the process and generating several kinds 

of outputs.

State assessments of forest ecosystem services should, at a 

minimum, generate the following five outputs:

1. A statement listing the ecosystem services generated by 

forests in the State,

a) highlighting priorities for future valuation studies 

(ecosystem services that are expected to be important but 

that have not been valued),

b) identifying services that can be included in accounts by 

transferring values from prior literature, and

c) acknowledging other forest ecosystem services with 

currently unknown values.
1a 1b

3a 3b

Stage 1

Stage 2

Stage 3

Stage 4

Assess trends in 

forest ecosystems as 

relevant to FES

Availability of credible and relevant 

estimates of marginal values of FES 

Accounting for ** (and * as budget and time allow)

Map previous FES 

valuation efforts

Quantify annual 

flows of FES

Systematic review 

of marginal values 

of FES 

Importance of changes in annual flows of FES

High Low

X

Drop

**

High Low

1. Statement 

of priority list

3. Spatial 

catalog of 

marginal 

values

2. Report on 

annual flows 

Calculate value of changes in FES 

resulting from annual gains and losses 

of forest ecosystems in the State

Check against Red Flags text box

Consultation with 

experts

*

4. Side-account 

of global 

values

5. Account 

of value 

gained or 

lost by the 

State

A

B

C

D

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 97

Figure 6.1—Template for Forest Ecosystem Service Assessment.
98 Chapter 6. Conclusion

2. A report on the annual flows of tangible forest ecosystem 

services per acre and in total from each forest type in each 

spatial zone in the State.

3. A spatial catalog of the marginal values of forest ecosystem 

services, per unit of final ecosystem service or per unit of 

forest, for each forest type in each spatial zone.

4. A side account of national and global values (to people 

residing outside the State) for ecosystem services gained or 

lost due to changes in forest ecosystems in the State from 

year to year.

5. An account of the value to State residents of ecosystem 

services gained or lost due to changes in forest ecosystems in 

the State from year to year.

The first output, produced from scoping studies and consultations 

in the early stages of the assessment, should provide a complete 

list of ecosystem services generated by forests in the State 

classified on 1) the likely importance of changes in the service 

due to loss or gain of forest ecosystems and 2) the availability 

of credible and relevant estimates of the marginal value of 

the service.

Services of high importance but lacking prior estimates should 

be included in a priority list for future research to inform 

State funding decisions and encourage other funders and 

researchers to focus valuation efforts on priority forest ecosystem 

services. Ecosystem services that have high importance and 

high availability of prior estimates should be evaluated in the 

remaining stages of the assessment, using benefit transfer to 

develop accounts and analyze policy alternatives. Depending 

on budget, time, and State priorities, ecosystem services with 

relatively low importance but high availability of prior estimates 

could also be included in the remaining stages of the assessment.

The second and third outputs should be developed in tandem, 

using consistent definitions and measurements of final ecosystem 

services to quantify their marginal production by forests and their 

marginal value to State residents. For ecosystem services that 

are not tangible and not associated with any observable behavior 

(such as many cultural services), the most appropriate measure 

may be area of the forest ecosystem. However, in most cases, 

the area of forest ecosystem should be considered as an input to 

production of a final ecosystem service.

Specifically, the second output should quantify annual flows of 

final forest ecosystem services in physical units appropriate to 

each service, generating both spatially differentiated estimates 

of the marginal product of forests, and “headline” numbers such 

as the proportion of a State’s drinking water that flows through 

forest ecosystems. The third output compiles estimates of the 

marginal value of those same final forest ecosystem services 

from previous studies. The resulting spatial catalog of marginal 

values is the key tool for developing accounts of the economic 

gains and losses due to changes in forest area over time and 

due to policy alternatives.

Finally, the fourth and fifth outputs are the typical outputs 

of green accounting exercises, depending on the accounting 

framework adopted. These accounts serve the purpose of 

monitoring, managing, and reporting the change in value of 

ecosystem services due to annual gains or losses in forest 

ecosystems in the State. The focus of State assessments is 

typically on the value of forest ecosystems to residents of the 

State. However, some ecosystem services from State forests 

also benefit people outside the State, at scales ranging from 

the population residing in watersheds fed by a State’s forest to 

the global population that benefits from mitigation of climate 

change through carbon sequestration in the State’s forests. We 

recommend tracking these values in a side account, recognizing 

that they can be only partially captured by State residents through 

ecosystem service markets or national policy.

To generate these outputs, assessments should proceed through 

the four stages illustrated in figure 6.1: 1) scoping studies, 

2) consultation to set parameters, 3) in-depth studies, and finally 

4) economic accounting of the value associated with changes in 

forest ecosystems in the State.

Stage 1

The first stage comprises two scoping studies to inform decisions 

about which ecosystem services to consider in the five outputs. 

Based on meetings with stakeholders from the Southern States, 

we recommend that at minimum, all assessments should include 

the following three categories of services:

a) watershed services (regulation of flow and maintenance 

of quality),

b) recreation (including tourism and hunting), and

c) supply of forest products with the greatest market values.

Because the market value of timber is already well understood 

and incorporated into policy decisions in the Southern States, the 

added value of an ecosystem service assessment is to account 

for non-timber values generated by forests, including non-timber 

products and services. The three categories listed above have 

been identified as the most important regulating, cultural, and 

provisioning services of southern forests and should be included 

in any assessment.

Of course, these are just a subset of all forest ecosystem services, 

and the scoping studies are intended to identify other services 

that should be included in particular State assessments, such as 

other cultural services and regulation of air quality and climate. 

Specifically, scoping study (1a) identifies important changes in 

forest ecosystem services by quantifying changes in the area 
Previous cover 

non-forest Planted pine Pine-oak

Non-forest Stable acres Loss of planted pine Loss of pine-oak

Planted pine Gain of planted pine Stable acres Pine-oak to planted pine

Pine-oak Gain of pine-oak Planted pine to pine-oak Stable acres

Current cover

State

Forested Area

High value 

forests for 

watersheds

High value 

forests for 

recreation

Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 99

of forest ecosystems over the past decade (or other recent time 

period), and scoping study (1b) surveys the literature on the 

economic value of ecosystem services, generating a “systematic 

map” of forest ecosystem service valuation.

For scoping study (1a), we recommend first identifying forest 

zones that 1) have the biggest effect on watershed functioning 

(see Chapter 3) and 2) are likely to support the most recreation, 

including hunting (see Chapter 2). Second, we recommend 

quantifying change in forest area over the past decade in the 

State as a whole and in those high value zones (for water and 

for recreation). Note that these zones are likely to overlap (see 

fig. 6.2). Change in forest area could be quantified as conversion 

into or out of FIA forest types (planted pine, natural pine, oakpine, upland hardwood, lowland hardwood). Based on these 

changes in forest area in the State as a whole and in the high 

value zones, the analyst can identify forest ecosystem services 

likely to have undergone important change.

For scoping study (1b), we recommend a “systematic mapping” 

approach (Atmadja and Sills 2015, Haddaway and others 

2016, James and others 2016, McKinnon and others 2015), 

supplemented by careful review of on-line catalogs, databases, 

and models designed to support benefits transfer (ESVD 2017, 

EVRI 2017, InVEST 2017, Loomis and others 2008, RUVD 

2017, USGS 2017). The objective is to assess the availability of 

credible and relevant estimates of the marginal value of forest 

ecosystem services. Credibility should be assessed based on the 

criteria described in the relevant chapters of this guide, as well as 

the general principles above and red flags (text box, next page) 

(e.g., the estimates should reflect benefits rather than costs, and 

the estimation methods should account for diminishing returns). 

Relevance should be based on the qualitative similarity of the 

study site to the State in terms of the type of forest, the relative 

scarcity or abundance of forest, and the size and income level 

of the population that benefits from the ecosystem service. The 

analyst can then determine whether there is relatively high or 

relatively low availability of credible and relevant estimates of 

the marginal value of each forest ecosystem service. This scoping 

study should also take note of the definition and measurement 

of the final ecosystem services that are valued, as an input to 

stage 3.

Stage 2

Both the managing agency and the research team should be 

involved in this stage, drawing on the results of the scoping 

studies and consulting with experts, in order to define the 

parameters for the rest of the assessment. In particular, the 

managing agency and other State forest experts should help 

verify and supplement the list of forest ecosystem services 

undergoing important changes in value. Specifically, they can 

offer insights about how future trends may diverge from past 

trends in forest ecosystems (e.g., due to socio-demographic and 

economic factors, policies and programs, or natural disasters and 

climate change) and other factors that shape the importance of 

ecosystem services (such as the cultural traditions and economic 

activities in the State).

Figure 6.2—Scoping for important changes in forest ecosystem services: forest transitions in priority areas.
100 Chapter 6. Conclusion

Combining estimates of values to different 

populations.

State accounts should include values to State 

residents, with values to other people reported 

separately. For example, the social cost of carbon 

is an estimate of the global cost of climate 

change due to carbon emissions, and therefore 

should not be reported in the same account as 

air quality benefits to State residents. In this case, 

the market value of carbon offsets may be a 

better estimate of the value to State residents. 

Estimating ecosystem service values larger 

than relevant total values. 

For example, the value of avoided damage to a 

sector should not be larger than the total value 

added of that sector, and willingness to pay 

should be bounded by income.

Combining measures of economic impacts 

or multiplier effects from regional economic 

analysis with estimates of economic values. 

These are based on fundamentally different 

assumptions and should not be added 

together, although they may provide useful 

complementary perspectives.

Employing estimates of cost instead of 

estimates of value. 

In general, replacement or restoration costs 

are not valid estimates of value. Likewise, 

expenditures on recreation—including travel 

costs—measure costs, rather than value. 

Reporting single values with no indication 

of uncertainty. 

Accounts should not rely solely on point 

estimates, but rather should draw on confidence 

intervals where available and conduct bounding 

exercises (using minimum and maximum 

possible values) when confidence intervals are 

not available. Likewise, analysts should assess 

sensitivity to key assumptions, such as the size of 

the beneficiary population and the discount rate 

for calculating present value.

RED FLAGS

Assuming forest is managed to optimize each 

ecosystem service. 

To estimate the annual flows of all ecosystem 

services that can be produced simultaneously 

by an acre of forest, it is important to make 

consistent assumptions about how that forest is 

managed. Management to optimize production 

of one ecosystem service will not necessarily 

optimize production of other services. 

Assuming a single fixed value for the marginal 

product or for the marginal value of an 

ecosystem service across all forest types and 

all locations. 

This is unlikely to be valid, because the 

relationship between the area of a forest 

ecosystem and the flow of forest ecosystem 

services is often non-linear, and marginal values 

are typically higher where ecosystem services 

are scarcer and where more people benefit. The 

principle of diminishing returns (i.e., diminishing 

marginal productivity and diminishing marginal 

utility) suggests that marginal values should 

generally be less than average values. 

Transferring marginal values from study sites 

with different forest types, different levels of 

abundance or scarcity of forest, and/or different 

income levels of the affected population. 

The study and target site should be similar 

for unit value transfers and should have an 

overlapping range of characteristics for predicting 

values based on benefit functions. 

Summing the values of intermediate and 

final services. 

This would almost certainly mean that some 

values have been double-counted because the 

value of final services includes the value of inputs 

(e.g., the values of regulating and provisioning), 

while cultural services include the value of 

supporting services (e.g., biodiversity and nutrient 

cycling).

Summing the values of overlapping sets of 

services estimated by different methods.

This results in double-counting services that 

appear in more than one set. In particular, stated 

preference surveys often encompass several 

services, some of which have also been the 

subjects of revealed preference studies. 
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 101

The next step is to plot the ecosystem services based on 1) their 

expected importance and 2) the availability of credible and 

reliable estimates of marginal value. They can then be sorted into 

the four categories shown in figure 6.1:

A. Ecosystem services that are undergoing significant changes 

(e.g., due to changes in forest ecosystems) and that have 

credible and relevant estimates of marginal value: these 

should be the primary focus of accounting efforts, since they 

are both important and possible to value.

B. Ecosystem services with fairly stable flows and with credible 

and relevant estimates of marginal value: these ecosystem 

services should be included in accounting efforts only 

if there is sufficient time and budget allocated to those 

efforts, because they are lower priority than the services in 

category A.

C. Ecosystem services that have been significantly affected by 

changes in forest ecosystems but with no credible/relevant 

estimates of marginal value: these ecosystem services should 

be excluded from accounting exercises–thus avoiding the 

temptation to guestimate or extrapolate to obtain marginal 

values. Instead, they should be added to a priority list of 

ecosystem services for future valuation studies. Depending 

on the budget, these studies may be part of the ecosystem 

service assessment. However, even if sufficient funding 

is not available, a formal list of State priorities, supported 

by a clear statement of the policy needs and information 

gaps (output 1), could influence and help researchers obtain 

funding for future research on these priority services.

D. Ecosystem services with fairly stable flows and no credible 

and relevant estimates of marginal value: given likely low 

importance and lack of information, these ecosystem services 

should be acknowledged but not quantified in ecosystem 

service assessments.

To ensure that accounts provide a conservative or lower-bound 

estimate of the total value of forests, any significant disservices 

of forests such as water use by fast growing plantations, wildlife 

damage/hazards, or production of volatile organic compounds 

(VOCs) should also be acknowledged (cf., Escobedo and others 

2011). If values of the (dis)services have been quantified in prior 

studies, they should be included in the accounts. Otherwise, they 

are candidates for the priority list for future valuation studies 

(category C).

In addition to defining which ecosystem services to include, this 

stage should also define how to disaggregate the State into spatial 

units for purposes of calculating changes in the annual flows of 

ecosystem services and their marginal values. At one extreme, 

each acre of forest might offer different marginal products 

and values of ecosystem services. At the other extreme, some 

previous State assessments have used a single average value 

for all forests in their State. We recommend an intermediate 

solution, using FIA forest types (planted pine, natural pine, oakpine, upland hardwood, lowland hardwood) as the highest level 

of disaggregation. Forest types should then be disaggregated 

as appropriate for each ecosystem service. These may overlap, 

as shown in figure 6.2 for watershed and recreation services. 

However, as long as they all nest in FIA forest types, they can be 

summed and aggregated.

Stage 3

This stage includes two studies that build on the scoping studies 

in stage 1 but focus on the smaller set of ecosystem services 

defined in stage 2.

Study (3a) quantifies total annual flows of ecosystem services 

from forests in each spatial unit defined in stage 2. Study (3b) 

generates a database of marginal values (and functions to 

compute marginal values) of each ecosystem service in each 

spatial unit defined in stage 2. These studies must be coordinated, 

so that the definitions and units of the final ecosystem service 

outputs quantified in study (3a) are the same as the final 

ecosystem services that are valued as inputs to production and 

well-being in study (3b). For some ecosystem services, marginal 

values may be reported for the service generated by an acre of 

forest, without specifying the quantity of service generated by 

that acre. This is particularly likely for non-tangible ecosystem 

services, such as a sense of place and natural heritage.

For most ecosystem services, study (3a) should quantify:

a) the marginal product of an additional acre of forest (i.e., 

how many more units of each final ecosystem service are 

generated by an additional acre of forest),

b) the extent of the market or the population that benefits from 

each service, and

c) the total annual flow of each ecosystem service, in each of the 

spatial units defined in stage 2.

The marginal products and population of beneficiaries are used 

for accounting in stage 4. The total annual flows form the basis 

for a report on the magnitude of forest ecosystem services (output 

2), including “headline numbers” such as the percent of drinking 

water that flows through forests, total air pollutants removed by 

forests, and number of recreational use-days in the State’s forests.

Study (3b) is a systematic review of marginal values of final 

forest ecosystem services reported in the scientific literature. 

Systematic reviews follow replicable procedures for searching 

the scientific literature and extracting consistent information from 

each study (Atmadja and Sills 2015, Moher and others 2009). 

In this case, the search protocol should screen for studies that 
102 Chapter 6. Conclusion

estimated marginal values of ecosystem services in similar forest 

biomes and socio-economic settings (i.e., temperate forest in 

developed countries). The information extracted should include:

a) the marginal value or the function that describes that value, 

specifying the units and year in which estimated,

b) which ecosystem services are included in the value,

c) whether the estimated value is for an annual flow of services 

or the capitalized value of all future services that a forest 

will provide,

d) the size of the population that benefits from services that are 

public goods,

e) characteristics of the beneficiary population in the study site 

(spatial extent, education, income level), and

f) characteristics of the forest in the study site, including forest 

type, extent, and how managed.

In addition, the reviewer should assess the credibility of the 

estimated values. This includes verifying that the study in 

fact estimated benefits (willingness to pay, change in welfare 

or utility) rather than expenditures or economic multipliers, 

and that it used a generally accepted method of valuation (as 

described in the previous chapters). It is also worth noting 

whether the estimated values have been assessed for plausibility 

(e.g., by comparing estimated total benefits with total income or 

total output).

Stage 4

The outputs of stage 3 can be used in a variety of ways to 

help monitor and manage change in forest ecosystems. This 

includes cost-benefit analysis of forest policy alternatives, 

selecting critical forest zones to target policy interventions, and 

identifying the best response to externally set standards (e.g., 

Federal standards for water quality). The first step is to quantify 

the extent of forest gain or loss in each spatial unit under each 

alternative considered (including the status quo). Both the type 

of forest and its management should be specified. Second, 

use the estimated marginal product of each final ecosystem 

service generated by a particular forest type under a particular 

management regime to quantify the changes in ecosystem 

services. Finally, apply the marginal values appropriate to each 

final ecosystem service in each spatial zone to generate the 

economic value.

The primary objective of this accounting is to quantify the value 

to State residents of changes in the State’s forest ecosystems. 

However, the literature also contains estimates of the marginal 

value of forests to the national or global population; for example, 

the social cost of carbon is an estimate of the total global cost of 

additional climate change due to one additional tonne of carbon 

dioxide emitted. These global values may be relevant to State 

residents if they are altruistic and care about the benefits that their 

State forests provide to the world, or if they expect to benefit 

from sales of those services in ecosystem service market. Thus, 

we recommend recording these national or global values in a side 

account (output 4), keeping them separate from the main account 

but ensuring that they are available for future negotiations.

There are many potential pitfalls when combining data and 

parameters from different sources in order to estimate values (see 

text box, p. 100). First, the marginal product and the marginal 

value must refer to the same final ecosystem service, defined in 

the same way, using consistent units. Second, some marginal 

values will have been estimated for bundles of ecosystem 

services, and in other cases for individual services. To obtain 

a defensible, lower-bound estimate, it is critical to avoid any 

double-counting. Last, we emphasize that the marginal values 

extracted from the literature are appropriate for valuing changes 

(not totals) in similar forest types and similar socio-economic 

settings as the study site.

As long as these red flags are heeded and pitfalls avoided, the 

report on changes in quantities of forest ecosystem services and 

the spatial catalog of marginal values of those services can be 

used to create an ecosystem services account that reports the 

value lost or gained by State citizens due to annual losses or gains 

of different forest types in different spatial zones (output 5). This 

account should be constructed from estimates of change in each 

spatial zone. We do not recommend reporting a “total value” of 

ecosystem services by summing the products of total forest area, 

marginal product, marginal values for each zone and for each 

service, because that would surely underestimate the total value 

of all forests, given the principle of diminishing returns.
Trees At Work: Economic Accounting for Forest Ecosystem Services in the U.S. South 103

Finally, we note that both outputs 4 and 5 report ecosystem 

service values both that contribute to GDP as conventionally 

measured (e.g., increased productivity of fisheries) and that 

represent additions to GDP (e.g., contribution of trout fishing 

to quality of life). These are worth distinguishing to facilitate 

interpretation and use of the accounts to understand the 

contribution of forests to the economy and to well-being.

LITERATURE CITED

Atmadja, S.; Sills, E. 2015. Identifying the causes of tropical deforestation: 

meta-analysis to test and develop economic theory. In: Köhl and Pancel. eds. 

Tropical forestry handbook. New York: Springer: 1-27.

Escobedo, F.J.; Kroeger, T.; Wagner, J.E. 2011. Urban forests and pollution 

mitigation: analyzing ecosystem services and disservices. Environmental 

Pollution. 159(8): 2078-2087.

ESVD. 2017. The TEEB valuation database–a searchable database of 1,310 

estimates of monetary values of ecosystem services. http://doc.teebweb.org/

wp-content/uploads/2017/03/teeb_database_teebweb.xlsx. [Date accessed: 

March 6, 2017].

EVRI. 2017. The environmental valuation reference inventory. https://www.evri.

ca/. [Date accessed: March 6, 2017].

Haddaway, N.R.; Bernes, C.; Jonsson, B.G.; Hedlund, K. 2016. The 

benefits of systematic mapping to evidence-based environmental 

management. Ambio. 45(5): 613-620.

InVEST. 2017. Natural capital project. http://www.naturalcapitalproject.org/

invest/. [Date accessed: March 6, 2017].

Loomis, J.; Kroeger, T.; Richardson, L.; Casey, F. 2008. The benefit transfer 

and use estimating model toolkit. http://dare.agsci.colostate.edu/outreach/

tools/#BTT. [Date accessed: March 6, 2017].

McKinnon, M.C. 2015. Map the evidence. Nature. 528(7581): 185.

Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G. 2009. Preferred reporting 

items for systematic reviews and meta-analyses: the PRISMA statement. PLoS 

Medicine. 6(7): e1000097. doi: 10.1371/journal.pmed.1000097.

RUVD. 2017. Recreation use values database. http://recvaluation.forestry.

oregonstate.edu/. [Date accessed: March 6, 2017].

USGS. 2017. Benefit transfer toolkit. https://my.usgs.gov/benefit-transfer/. [Date 

accessed: March 6, 2017].

A copy of this report is available for download at 

www.srs.fs.usda.gov/pubs/.

A limited number of hard copies are available; please direct 

requests for a hard copy to pubrequest@fs.fed.us.

Sills, Erin O.; Moore, Susan E.; Cubbage, Frederick W.; McCarter, 

Kelley D.; Holmes, Thomas P.; Mercer, D. Evan, editors. 2017.

Trees at work: economic accounting for forest ecosystem services 

in the U.S. South. Gen. Tech. Rep. SRS-226. Asheville, NC: U.S. 

Department of Agriculture Forest Service, Southern Research Station. 

103 p.

Southern forests provide a variety of critical ecosystem services, from 

purification of water and air to recreational opportunities for millions 

of people. Because many of these services are public goods with no 

observable market value, they are not fully accounted for in land use 

and policy decisions. There have been several efforts to remedy this by 

estimating the total value of forests in different States, with each effort 

including different bundles of ecosystem services and using different 

valuation methodologies. In this guide, we propose a more consistent and 

theoretically sound approach to 1) quantifying annual flows of ecosystem 

services, 2) developing a spatial catalog of the marginal values of changes 

in those flows, and 3) accounting for the total value of ecosystem services 

lost or gained as a result of changes in forest ecosystems. Four chapters—

on cultural services, watershed services, air quality and carbon, and 

provisioning of non-timber forest products—provide guidance on best 

practices for quantifying and estimating the values of these services as 

provided by forests. Expert panels were convened to write each chapter. 

The guide as a whole was developed with input from the Southern Group 

of State Foresters and stakeholder meetings held in 2014 and 2015.

Keywords: ecosystem services, non-market valuation, green accounting, 

southern forests, non-timber forest products, watershed services, air 

quality, cultural services.

Scan this code to submit your feedback, or go to 

www.srs.fs.usda.gov/pubeval
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