Economic

Research

Service

Economic

Research 

Report 

Number 183

February 2015

United States Department of Agriculture

Targeting Investments To Cost 

Effectively Restore and Protect 

Wetland Ecosystems: Some 

Economic Insights

LeRoy Hansen, Daniel Hellerstein, Marc Ribaudo, 

James Williamson, David Nulph, Charles Loesch, 

and William Crumpton
Economic Research Service 

www.ers.usda.gov

The U.S. Department of Agriculture (USDA) prohibits discrimination in all its programs and activities on 

the basis of race, color, national origin, age, disability, and, where applicable, sex, marital status, familial 

status, parental status, religion, sexual orientation, genetic information, political beliefs, reprisal, or because 

all or a part of an individual’s income is derived from any public assistance program. (Not all prohibited 

bases apply to all programs.) Persons with disabilities who require alternative means for communication of 

program information (Braille, large print, audiotape, etc.) should contact USDA’s TARGET Center at (202) 

720-2600 (voice and TDD). 

To file a complaint of discrimination write to USDA, Director, Office of Civil Rights, 1400 Independence 

Avenue, S.W., Washington, D.C. 20250-9410 or call (800) 795-3272 (voice) or (202) 720-6382 (TDD). USDA 

is an equal opportunity provider and employer.

United States Department of Agriculture

Access this report online:

www.ers.usda.gov/publications/err-economic-research-report/err183

Download the charts contained in this report:

• Go to the report’s index page www.ers.usda.gov/publications/

 err-economic-research-report/err183

• Click on the bulleted item “Download err183.zip”

• Open the chart you want, then save it to your computer

Recommended citation format for this publication:

Hansen, LeRoy, Daniel Hellerstein, Marc Ribaudo, James Williamson, David Nulph, 

Charles Loesch, and William Crumpton. Targeting Investments To Cost Effectively 

Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183, U.S. 

Department of Agriculture, Economic Research Service, February 2015.

Cover images: U.S. Fish and Wildlife Service, Charles Loesch (top and middle) and USDA/NRCS (bottom).

Use of commercial and trade names does not imply approval or constitute endorsement by USDA. 
United States Department of Agriculture

Economic 

Research 

Service

Economic

Research

Report

Number 183

February 2015

Abstract

USDA has spent more than $4.2 billion on wetland restoration and protection over the last 

two decades. One challenge in allocating these funds is the lack of information on variations in wetland benefits and costs across the Nation. This report discusses the biophysical 

impacts of new wetlands for eight benefit categories: duck hunting, carbon sequestration, 

flood protection, nitrogen removal, species protection, open space, sediment removal, and 

groundwater recharge, as well as the value of these impacts for some categories. In addition, it presents county-level estimates of the costs of restoring and preserving wetlands 

for some parts of the United States. Although the estimates range in precision and are 

not comprehensive, they call attention to some areas where the benefits of new wetlands 

are likely to exceed costs or perhaps may be insignificant. For example, the benefits of 

restoring and preserving wetlands near the Missouri River in central North and South 

Dakota are likely to exceed costs. Findings underscore the need for additional information 

that may increase the number, accuracy, and spatial resolution of wetland benefit estimates. 

Keywords: Wetland conservation, ecosystem benefits, environmental economics, 

environmental targeting, nonmarket benefits, values of wetland ecosystems

Acknowledgments

The authors thank the following people for their comments: Lori Lynch of USDA’s 

Economic Research Service (ERS); Janet Perry, Steve Parkin, and Noel Gollehon of 

USDA’s Natural Resources Conservation Service; Carl Pasurka of the U.S. Environmental 

Protection Agency; James Caudill, Drew Laughland, Ron Reynolds (retired), and Dan 

Hertel of the U.S. Fish and Wildlife Service; Jason McNees of the Nature Conservancy; 

LeRoy Hansen, Daniel Hellerstein, Marc Ribaudo, 

James Williamson, David Nulph, Charles Loesch, 

and William Crumpton

Targeting Investments To Cost 

Effectively Restore and Protect 

Wetland Ecosystems: Some 

Economic Insights
ii

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Michelle Perez of the World Resources Institute; Jeanne Christie of the Association of State Wetland 

Managers; and Zhiliang Zhu of the U.S. Geological Survey. Roger Claassen of ERS and Alex 

Barbarika and Richard Iovanna of USDA’s Farm Service Agency provided valuable peer reviews. 

Thanks also to John Weber and Cynthia A. Ray of ERS for editorial and design assistance. 

About the authors

LeRoy Hansen, Dan Hellerstein, Marc Ribaudo, and Jim Williamson are agricultural economists 

and David Nulph is a systems analyst with ERS. Charles Loesch is a wildlife biologist with the 

U.S. Fish and Wildlife Service. William Crumpton is an associate professor in the Department of 

Ecology, Evolution, and Organismal Biology at Iowa State University. 
iii

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Contents

Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

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

The Costs of Wetland Establishment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Drivers of wetland easement and restoration costs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Predicting the public cost of establishing new wetlands. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Selected Estimates of the Benefits of Wetland Conservation. . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Estimating the value of wetlands and their ecosystem services . . . . . . . . . . . . . . . . . . . . . . . . . 10

Duck hunting benefits: What the study found . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Species protection: What the study found. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Flood protection: What the study found . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Net greenhouse gas emissions: What the study found. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Groundwater recharge, sediment removal, and open space: What the study found. . . . . . . . . . . 26

Targeting Wetland Conservation Efforts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Duck hunting benefits and costs of prairie pothole wetlands. . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Nitrogen removal: The cost effectiveness of wetlands of the Upper Mississippi 

and Ohio River watersheds. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Survival of imperiled species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Carbon sequestration in the PPR and MAV. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Considering benefits together. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

The current distribution of restored and protected wetland acreage. . . . . . . . . . . . . . . . . . . . . . 33

Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Appendix 1—The Costs of Wetland Conservation Options. . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Results and model applications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Appendix 2—Conceptual Framework for Assessing Environmental Benefits. . . . . . . . . . . . . 51

Economic and biophysical frameworks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

Alternative approaches for benefits analyses. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

Appendix 3—Predicting New Wetlands Effects on Ducks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

Appendix 4—Calculating Wetlands’ Nitrogen Removal Potential. . . . . . . . . . . . . . . . . . . . . . . 56
United States Department of Agriculture

A report summary from the Economic Research Service

ERS is a primary source 

of economic research and 

analysis from the U.S. 

Department of Agriculture, 

providing timely information on economic and policy 

issues related to agriculture, 

food, the environment, and 

rural America. www.ers.usda.gov

Economic

Research

Service

Economic

Research 

Report 

Number 183

February 2015

United States Department of Agriculture

Targeting Investments To Cost 

Effectively Restore and Protect 

Wetland Ecosystems: Some 

Economic Insights

LeRoy Hansen, Daniel Hellerstein, Marc Ribaudo, 

James Williamson, David Nulph, Charles Loesch, 

and William Crumpton

February 2015

Find the full report 

at www.ers.usda.

gov/publications/erreconomic-researchreport/err183

LeRoy Hansen, Daniel Hellerstein, Marc Ribaudo, James Williamson, 

David Nulph, Charles Loesch, and William Crumpton

Targeting Investments To Cost Effectively 

Restore and Protect Wetland Ecosystems: 

Some Economic Insights

What Is the Issue?

Over the last several decades, concerns over the loss of wetland ecosystems have led to legislation 

restricting wetland conversion and promotion and funding of wetland restoration and conservation. Consequently, USDA has spent more than $4.2 billion on wetland restoration and protection 

during the period. The environmental benefits of wetland conservation—cleaner water, increases 

in wildlife populations, and carbon sequestration—depend on climate, human influences, and 

landscape characteristics. This study assesses how future wetland conservation funding might be 

targeted within States and regions and across the United States to maximize benefits relative to 

costs of restoring and preserving wetlands. Information on the sizes and spatial distributions of 

the benefits and costs of wetland protection can help public and private decisionmakers understand the economic implications of efforts to reduce wetland losses, improve existing wetlands, 

and restore prior-existing wetlands through regulation and economic incentives. 

What Did the Study Find?

A number of different types of wetland benefits were considered as part of this analysis. The 

ranges in wetland benefits and costs across the country demonstrate potential gains from 

targeting public and private wetland restoration efforts by location and by wetland characteristics. Some benefits can be estimated more precisely than others:

• The annual benefits to duck hunting from restoring wetlands in the Prairie Pothole Region 

(primarily, lands in the eastern Dakotas and western edges of Minnesota and Iowa) range 

from near $0 to $143 per wetland acre.

• The annualized value of a new wetland’s effect on atmospheric concentrations of greenhouse 

gases ranges from $0 to $129 per wetland acre in the areas studied. In other areas, wetlands 

can increase, decrease, or have no net effect on atmospheric levels of greenhouse gases.

• Wetlands on agricultural land are not likely to provide notable flood-protection benefits 

unless they are located in close proximity to urban areas.

• Wetlands in the Upper Mississippi and Ohio River watersheds can annually remove from 11 

to 1,800 pounds of nitrogen per wetland acre in waters leaving farm fields from watershed 

streams and rivers. 
• About 1,756 counties in the contiguous States have wetland-associated imperiled species, with some counties 

having as many as 23 imperiled species. About 1,355 counties have no wetland-associated imperiled species, 

but this does not suggest that the value of wetland-species protection benefits in these counties is low. The 

analysis found no information that illustrates how a new wetland might affect species’ survival probabilities. 

Additionally, it found no information on the public’s willingness to pay (or how it might prioritize support) 

for changes in imperiled species’ survival probabilities. 

• Many wetlands recharge groundwater supplies, but the majority do not. Some wetlands exist because they 

are fed by groundwater. Others exist because they have impermeable subsoil.

• Sediment removed by wetlands, while protecting other bodies of water, can reduce other wetland benefits as 

the sediment accumulates. 

• The benefits of wetlands as open-space protection in rural areas are likely to be very small. 

Based on contract data from USDA’s Wetlands Reserve Program, the costs of restoring and preserving a 

wetland range from $170 per acre in the western Dakotas, Montana, Arkansas, and Louisiana to $6,100 per acre 

in the major corn-producing areas and along the Northern Pacific Coast. These estimates reflect the change in 

the value of the land with and without a permanent wetland easement plus wetland restoration costs.

An analysis of the combined benefits and costs of new wetlands revealed the following:

• Restoring wetlands in the western Prairie Pothole Region is likely to generate duck-hunting benefit-cost 

ratios close to or greater than one; that is, restoration funds spent in this area would be a good investment. 

However, most of the people who would benefit from the added duck populations in the region are hunters 

who live elsewhere. 

• The value of new wetlands’ greenhouse gas impacts exceeds wetland costs in the western half of the Prairie 

Pothole Region and in most of the Mississippi Alluvial Valley (from southern Illinois, covering western 

portions of Tennessee and Mississippi and eastern portions of Missouri and Louisiana). 

• The amount of nitrogen that can be removed for each dollar spent on wetland restoration and protection in the 

Upper Mississippi and Ohio River watersheds ranges from 0.2 to 34.0 pounds. The costs of nitrogen removal 

through new wetlands range from $0.03 to over $5.00 per pound of reduced N loadings in nearby waterways. 

How Was the Study Conducted?

To quantify wetland ecosystem effects on amenities, and the value the public places on these amenities, ERS 

researchers reviewed and analyzed economic, ecological, and engineering literature and data. In some cases, 

researchers used existing data and models; new models were also developed. Benefits were estimated at the 

county and subcounty levels across limited portions of the Nation, depending on the spatial resolution (e.g., 

geographic reliability) of supporting data and economic and ecological models. 

Researchers used Wetlands Reserve Program contract data to empirically estimate wetland cost models for 

major wetland regions. These models were then used to generate county-level estimates of the costs of new 

wetlands. Where the estimates allowed, researchers generated county- and subcounty-level benefit-cost ratios 

by dividing the benefit estimates by the cost estimates. These ratios illustrate areas where wetland restoration 

funding might be allocated to best serve public interests. When it was not possible to estimate economic benefits, researchers generated ratios of the wetlands’ cost effectiveness—the quantity of services produced relative 

to costs. Lastly, where data were limited, representative measures were generated that illustrate the scope and 

the magnitude of possible benefits.

www.ers.usda.gov
1

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Targeting Investments To Cost 

Effectively Restore and Protect 

Wetland Ecosystems: Some 

Economic Insights

Introduction

Since European settlement, the 48 contiguous States are estimated to have lost about half of the 

estimated 220 million original wetland acres. Some areas lost greater shares than others—regions 

within Iowa, Illinois, and Indiana lost as much as 90 percent. Most losses stemmed from drainage 

for agriculture, as farmers found that the land provided returns that covered the cost of wetland 

conversion. In fact, prior to the 1970s, the Federal Government provided subsidies for some 

wetland conversion. 

In more recent years, the breadth of ecological services provided by wetlands, ranging from serving 

as critical habitat of many plant, fish, and wildlife species to carbon sequestration, has been widely 

recognized and appreciated. Nonetheless, economic incentives for private landowners to provide 

most wetland services are generally weak—the benefits provided by wetlands and their ecosystems 

often have a nonmarket “public goods” nature. Furthermore, the individuals that benefit may be far 

from the wetland, making the collection of monetary returns all the more difficult. 

Public goods are characterized as being nonrival in consumption (an additional individual can 

enjoy the good without affecting others) and by the difficulty of excluding nonpayers (Kaul et al., 

1999). For example, the view of a wetland from public land, such as a highway, is a pure public 

good. Similarly, wetlands can boost duck populations. But it is difficult to exclude those who are 

not willing to pay for the subsequent increase in hunting quality and views of migratory ducks. 

Generally speaking, even though some amenities provided by wetlands are not pure public goods, 

the public-good characteristics (as well as wetlands’ effects on other amenities) are likely to make 

market provision inefficient (Ribaudo et al., 2008). 

Since the 1970s, having recognized the public goods provided by wetlands, Federal, State, and local 

governments, as well as nongovernmental organizations (NGOs), have initiated efforts to reduce 

wetland losses, improve existing wetlands, and restore prior-existing wetlands through regulation 

and economic incentives. USDA’s most significant wetland restoration effort was the Wetlands 

Reserve Program (WRP), a voluntary program established by the Food, Agriculture, Conservation, 

and Trade Act of 1990 (the 1990 Farm Act).1

1The Agricultural Act of 2014 rolled functions of the Wetlands Reserve Program, Grassland Reserve Program (easement portion), and the Farm and Ranch Lands Protection Program into the Agricultural Conservation Easement Program 

(ACEP). All land enrolled in these earlier programs is now considered enrolled in ACEP. The three earlier programs 

received average annual funding of $686 million for 2008-13, but annual ACEP funding for 2014-18 is expected to average $375 million. 
2

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

The objective of the WRP was to protect, restore, and enhance wetland ecosystems to protect and 

improve:

• Habitat for migratory waterfowl and other wetland-associated wildlife, including imperiled 

species 

• Water quality and groundwater recharge

• Floodplains and water flows to reduce flooding

• Aesthetics and open space, and native flora and fauna 

• Education and scientific scholarship

By the end of 2012, approximately 2.6 million acres were enrolled in the WRP, of which 2.1 million 

acres are restored wetlands, about 0.14 million acres are prior-existing wetlands, and the remainder 

are surrounding uplands.2 The WRP’s financial commitments varied over time but averaged about 

$200 million per year from 2009 to 2012. 

The Conservation Reserve Program (CRP) is USDA’s other major wetland conservation effort, 

though wetland conservation is not the primary goal of the program. By the end of 2012, the CRP 

had 2.29 million wetland-related acres under contract, including 0.50 million acres of improved, 

prior existing wetlands; 0.54 million acres of newly restored wetlands; and 1.251 million upland 

acres (e.g., dry lands surrounding wetlands). In 2012, annual expenditures on CRP wetland-related 

contracts totaled about $175 million.3 Together, the WRP and CRP protect about 2.6 million 

restored and 6.4 million prior-existing wetland acres.4

Four features in the design of the WRP and CRP are noteworthy, particularly in regards to wetland 

conservation programs and NGO initiatives. First, for both the WRP and CRP, a participating landowner maintains ownership of the land, is allowed limited uses of the land, and can sell the land. 

However, the contractual agreement, and its associated constraints, stays with the land in the event 

of a transfer of ownership. 

Second, the lengths of the contracts vary by program. About 87 percent of the WRP contract acres 

are permanent easements, 6 percent are 30-year easements, and the remainder are 10-year agreements. In contrast, CRP wetland-related contracts range from 10 to 15 years (about 25 percent are 

for 10 years, 75 percent are for 14 or 15 years). The differences in contract lengths may affect the 

types of benefits generated. For example, some wetland ecosystems take years to recover. In such 

cases, the annual services of newly restored or improved wetlands might increase over time as they 

move toward their full potential.

2Total WRP acreage data are from www.nrcs.usda.gov/Internet/NRCS_RCA/reports/fb08_cp_wrp.html. The breakdown 

of Wetlands Reserve Program (WRP) contract acreages is based on ERS analysis of detailed data on WRP contracts supplied by USDA’s Natural Resources Conservation Service. The detailed contract data file has a little more than half of all 

WRP contracts. We have assumed that the distribution of contract types in it is representative of all WRP contracts. 

3Estimates are based on CRP data supplied by USDA’s Farm Service Agency and include only yearly rental payments 

(cost share expenses for installing land covers, and the cost of signup incentive payments, are not included).

4At the end of fiscal year 2014, the CRP had 2 million wetland-related acres under contract (http://www.fsa.usda.gov/

Internet/FSA_File/summarysept2014.pdf). At the time of publication of this report, WRP contract data were not available beyond 2012. 
3

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Third, the program payment schedules vary by program. In the WRP, a landowner receives a onetime upfront payment from the Federal Government. In contrast, CRP contracts are agreements 

under which the landowner receives annual payments. This design feature engenders comparisons of 

benefits and costs provided by the two programs over time. The WRP is an investment that provides 

wetland benefits, in most cases indefinitely, whereas the annual CRP payments are more analogous to annual rental payments, and the stream of environmental benefits flowing from the retired 

land may decline after the contract expires. From 2009 to 2013, approximately 50 percent of the 

CRP acres in expiring contracts were re-enrolled.5 For the other 50 percent, historical use suggests 

that a portion of the land might return to agricultural production—these lands were typically in 

crop production in the 1980s and, while profitable then, recent increases in commodity prices 

have boosted returns. But under the following circumstances, landowners may choose not to drain 

wetlands: the land is more profitable if left as a wetland (i.e., it may be profitable to allow forested 

wetlands to mature); the landowner enjoys having a wetland; or the costs to covert the land are 

prohibitively high. And, if wetlands are left undrained, wetland ecosystems will continue to produce 

public benefits without public funding. 

Lastly, competitive enrollments can reduce program costs and increase benefits. Generally, lands 

that can provide wetland benefits are accepted in the CRP as long as they meet certain baseline 

requirements, such as having been used in crop or livestock production.6 Enrollment in the WRP is 

competitive. To participate, landowners submit offers to USDA’s Natural Resources Conservation 

Service (NRCS) State field offices. The State field offices assign scores to each offer based on 

ranking criteria. Most State offices develop their own ranking criteria, though some States have 

worked together. The ranking criteria award points to contract offers based on a range of expected 

environmental effects and, in some States, costs. Within each State, offers receiving the highest 

scores are generally accepted, given budget constraints and acreage enrollment targets. 

Federal, State, and local governments and NGOs that wish to develop and improve ranking criteria 

that represent public interests in wetlands’ environmental impacts face at least two major challenges. First, they must determine how a new wetland and its ecosystem might affect environmental 

amenities. Second, they must assign weights to the various wetland amenities that reflect the relative 

strengths of public preferences. Because the information needed to make these determinations is 

limited, ranking criteria are based on the judgments of program managers, individuals, community 

groups, NGOs, and commercial enterprises.

This study assesses how future wetland conservation funding might be targeted within States, 

regions, and across the United States to maximize benefits relative to costs. It uses data, model 

results, and findings from previous research to generate spatial estimates of the costs and benefits of 

new wetlands. That is, to the extent possible, the analysis taps biophysical and economic sciences to 

quantify wetlands’ and their ecosystems’ effects on amenities, the public’s preferences for amenities, and wetland costs. Findings offer geographically disaggregate illustrations of costs and some 

environmental benefits and impacts in some regions of the United States. Findings also illustrate the 

many areas where more information is needed.

5This result is based on an analysis of all CRP contracts. Current data limitations do not allow for an evaluation of 

expiring wetland-related CRP contracts.

6The general CRP uses a competitive auction mechanism to select acres. However, most CRP wetland contracts are 

enrolled via the continuous CRP, which accepts any offer that meets eligibility requirements. 
4

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

The Costs of Wetland Establishment

The primary data used in the cost analyses come from WRP contracts. The WRP file includes the 

amounts of the payments accepted by landowners for the easement and wetland restoration—the 

dependent variable in the cost functions. The WRP contract data are particularly appealing because 

the program, by congressional design, caps easement payments at the difference between the values of 

land before and after it is enrolled. When administered correctly, easement payments are not likely to 

overcompensate landowners and are a good measure of opportunity costs. WRP data do not include the 

cost of technical support provided by USDA. Thus, the cost estimates may understate the total cost of 

restoring and protecting a wetland. Any bias in the estimates, however, is expected to be relatively small. 

Clearly, larger wetland easements will require greater easement (incentive) payments and have 

greater restoration costs, all else being equal. But a number of other factors affect the size of the 

payments landowners are willing to accept and the wetland restoration costs. The WRP data provide 

other variables, including a county identifier, which enable one to link each observation to other 

county-level data.

Drivers of wetland easement and restoration costs

Restoring and preserving a wetland through a publicly funded voluntary program involves two 

types of costs: the net opportunity cost (current minus the alternative land use values) is the cost of 

the permanent wetland easement;7 and the cost of restoring wetland hydrology can include simple 

measures (blocking or slowing water movement) or significant construction (dredging wetland fill), 

as well as the establishment of appropriate flora and wildlife habitat in the wetland. 

Given the program’s features and based on a review of the literature, the biggest drivers of wetland 

easement costs are the following:

1. Current land value—Landowners will want to be compensated for what they give up, which 

will usually be less than the market value of their land, given that the remaining property rights 

have value. The current market value of farmland is at least as great as its agricultural value but 

can be higher when there is a potential for urban or other higher valued uses. 

2. The value of the land with an easement—The amount that a landowner gives up when selling 

the easement (e.g., the opportunity cost of the easement) also depends on the value of the land 

with the easement—the compensation payment a landowner demands will be inversely related 

to the value of the land with the easement. The market value of land with an easement will 

be at least equal to its remaining agricultural-use value (i.e., occasional grazing and haying) 

plus the value of the land for onsite recreation (i.e., bird watching and hunting), but it could 

be greater. It is expected that the remaining agricultural value will be correlated with the size 

of the easement and, possibly, its pre-wetland agricultural value. The onsite recreation value 

is expected to be directly affected by the number of people likely to use the wetland, which is 

likely to be closely related to the size of the surrounding population.8

7Past research on wetland benefits has failed to recognize the value of the land with wetlands. See, for example, Jenkins et al. (2010) and van Kooten et al. (2011).

8Studies provide strong evidence that, in the past, demand for lands with wetlands can sometimes drive the value of 

the lands above their agricultural and alternative-use values (Reynolds and Regalado, 2002: Earnhart, 2001; Pease et al., 

1997). 
5

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

3. The value of land near the wetland—Landowners who own other land near the wetland are 

likely to consider the effects of the wetland on the values of those lands—should the value 

of surrounding lands increase (decrease), the landowner is likely to accept a lower (higher) 

easement payment. Findings suggest that the value of land surrounding a wetland easement 

can increase when buyers are willing to pay a premium for land with a wetland view (Ma and 

Swinton, 2011; Mahan et al., 2000; Doss and Taff, 1996)—the greater the urban pressure, the 

greater the premium. Note that Reynolds and Regalado (2002) found that the type of wetland 

affects the premium. But findings also suggest that a restored wetland nearby can reduce the 

urban development value of land. In an analysis of the rapidly growing Raleigh-DurhamChapel Hill region of North Carolina, Kazak and BenDor (2013) found that a new wetland 

lowered the urban-development value of land within 0.5 miles of the wetland. While urban 

development pressure can have some effect, the direction of the effect, if any, is uncertain.

4. Nuisance cost—Nuisance cost is the increase in fuel, time, and fencing needed to maneuver 

equipment around and keep livestock out of new wetlands—or, alternatively, the opportunity 

cost of altering farm production or cattle grazing on the surrounding lands. The nuisance cost 

is borne by the landowner. Easement payments will need to offset nuisance costs to encourage 

landowner participation (Pattison et al., 2011). It is expected that larger contracts will impose 

greater nuisance costs, driving up the cost of an easement.

5. Good steward—A landowner wishing to be a “good steward” may accept a lower easement 

payment. While good stewardship can have an effect on the easement payment a landowner 

would find acceptable, this analysis does not include an explicit measure of such.

The primary drivers of (or factors affecting) wetland restoration costs are the following:

1. Size—Larger easements require more restoration resources.

2. Hydrology—The cost of restoring a wetland’s hydrology depends on the level of construction 

needed. For example, filling channels, eliminating tile drainage, and restoring flow impediments 

can be much less costly than excavating filled wetlands. The actions taken to restore wetlands’ 

hydrology would not be expected to differ substantially across wetlands of the same type.

3. Flora and fauna—The cost of restoring flora and fauna that support wetland ecosystems 

depends on the type of activities involved, such as planting seeds or planting live vegetation, transporting live fauna or allowing natural recovery, planting by machine or by hand, 

and preventing or controlling invasive species. For example, restoring grassed wetland may 

only require drill-seeding the land prior to restoring the hydrology, while restoring a forested 

wetland may require planting young plants by hand and, hence, may be very labor intensive. 

The actions taken to restore wetlands’ fauna would not be expected to differ substantially 

across wetlands of the same type. 

Based on these drivers, a database was developed to serve as the explanatory variables (including variable proxies) in a model of wetland costs. We first considered current farmland values. Because spatial 

data on farmland values nationwide are not available, we used county-level data on farmland rental 

rates—which are, effectively, an annualized measure of the agricultural value of land. We therefore 

generated a proxy variable for the agricultural value of land in an easement by multiplying the rental 

rate values by the number of acres in the easement. Note that, as discussed earlier, the agricultural 

value of land is expected to have positive effects on lands with and without wetland easements. 
6

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Another variable included in the database serves as an indicator of urban pressure. Urban pressure can drive up farmland values—the greater the potential for nonfarm development, the greater 

the land value. But urban pressure can also drive up the values of lands with easements and lands 

surrounding easements. Hence, the net effect of urban pressure is uncertain.

A third variable included is the size of the wetland. For a given type of wetland, the cost of restoring 

the wetlands’ hydrology and ecosystems and nuisance costs are expected to increase with the size of 

the wetland. The agricultural value of land with a wetland is also expected to increase with easement 

size, which may partially offset the other two effects. However, there may be economies of scale or 

fixed costs associated with restoration and the other factors so that costs may not be proportional to 

the size of the wetland. To account for nonlinear relationships, a higher order term of this variable 

was included in the regression models. 

To control for differences in restoration costs across wetland types, separate models were estimated 

for each of 10 major U.S. wetland regions, as defined by NRCS, where adequate data are available 

(fig. 1). By design, these regions reflect wetland similarities. It seems reasonable to assume that, 

within a wetland region, determinants of the cost of restoring a wetland—other than the size of the 

wetland—are likely to be similar. The demand for the view of a wetland will depend on the appearance of the wetland and the type of ecosystem it supports, which is expected to show little spatial 

Figure 1

Major wetland regions of the contiguous States 

USDA, Natural Resources Conservation Service.

Glaciated Interior Plains

Northwest

Prairie Pothole Region

Gulf-Atlantic Coastal Flats

Appalachian Highlands

Piedmont

High Plains

Mississippi Alluvial Valley

Central Valley

Gulf Atlantic Rolling Plains

Central Plains

Wetlands component

assessment regions

1

2

3

4

5

6

8

9

10

11

7
7

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

variation for a given type of wetland. Regional analysis helped control for several drivers of the cost 

of wetland easements. (For details on the model variables, see appendix 1.9)

Predicting the public cost of establishing new wetlands

Across the 10 models, most coefficients are statistically significant at the 99-percent level, and the 

estimated models explain 53 to 88 percent of the variation in wetland costs (as measured by each 

model’s adjusted R-square). The five best-fitting wetlands cost models capture more than 75 percent 

of the variation in total wetland cost, and the three weakest capture 53 to 60 percent. (For estimation 

results, see appendix 1.)

Using these results to generate county-level estimates of the total cost of a new wetland requires 

selecting appropriately representative sizes for each wetland region. For this analysis, we chose the 

median size of previously established WRP contracts (within a region), as this facilitates generating 

an estimate of median cost. Given the nonlinearity of the cost models, the average-sized contract 

will not generate an estimate of the average contract cost. We also used county-specific measures of 

agricultural land rental rates. Thus, the county estimates are driven by a regionally representative 

median contract size, the region-specific estimated coefficients, and county-specific agricultural land 

rental value.

To allow cross-region comparisons, we converted total wetland cost estimates to per-acre costs. The 

per-acre cost estimates range from $170 to $6,100, with some of the lowest costs in western North 

Dakota and eastern Montana and the highest in major corn-producing areas and western Washington 

and Oregon (fig. 2).10 Wetland costs are most variable spatially within the Prairie Pothole Region 

(where values increase from northwestern to southeastern extremes), Northwest (where values 

are high in much of the region), and Appalachian Plains (where values vary sharply throughout). 

Wetland costs could not be estimated for areas that lie outside the NRCS wetland regions examined 

in this analysis.

9We included a variable that was meant to account for the effects of urban proximity, found it to be statistically insignificant, and dropped it from the final model. Our belief is that urban proximity has offsetting effects. The potential for 

urban development can boost farmland prices above their agricultural values (which will tend to increase the cost of an 

easement). Conversely, urban proximity can increase the values of land and surrounding wetlands because of greater 

demand for wetland amenities (see appendix 1).

10Lawley and Towe (2014) recently examined the cost of easements on existing wetlands that cap land uses at the 

current levels in the Prairie Pothole Region (PPR) of Canada. They found that easement payments averaged $86 per acre 

(U.S. $). Two primary factors suggest that, although low, the Lawley and Towe (2014) estimate is consistent with the ERS 

estimate in this study. First, the easements in this analysis are placed on land that had been drained and is being cropped, 

while Lawley and Towe (2014) evaluated easements on existing wetlands (e.g., land in a lower valued use). Second, the 

estimated pattern of easement costs (they drop as one moves northwesterly) in this study suggests that easement costs 

would be lower in Canada (in an area that is north and west of the U.S. PPR). 
8

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Figure 2

County-level estimates of the cost of restoring and preserving a new wetland 

White denotes areas where cost estimates were not calculated. The major boundary lands on the map define the 

wetland regions shown in figure 1.

Source: USDA, Economic Research Service using data from Wetlands Reserve Program contract files.

Dollars per acre

171 - 1,050

1,051 - 1,600

1,601 - 2,300

2,301 - 3,300

3,301 - 6,116
9

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Selected Estimates of the Benefits of Wetland 

Conservation

Wetlands have been credited with increasing and enhancing water quality, protecting fish and 

wildlife populations, providing flood protection, sequestering carbon, and providing open space 

and aesthetic beauty.11 This section briefly describes the biophysical and economic models used 

to estimate wetland services, amenities, and the value of amenities.12 We then present a summary 

of findings on the values of a suite of eight types of wetland benefits within a number of wetland 

regions. The estimates of wetland benefits are reported in annual values. To provide a more intuitive 

comparison of costs and benefits, we convert wetland costs to annualized values using a 4-percent 

discount rate.13

The eight wetland benefits examined include the following:

• Duck hunting

• Nitrogen removal

• Species protection

• Flood protection 

• Greenhouse gas reductions

• Groundwater recharge

• Sediment removal

• Open space

The choice of these eight benefits is driven by the availability of data, the ability to develop biophysical and economic models, and findings of past research that have some level of spatial resolution. 

This group reflects some of the often-stated benefits of wetlands. Wetland benefits not addressed 

here include impacts on other wildlife, increased biodiversity, reduced phosphorous and pesticide 

loadings, and improved recreational and commercial fisheries. We were unable to generate most of 

the benefits across all regions. The results presented here do not reveal the optimal allocation of U.S. 

wetland restoration funds because the number of benefits estimated is limited and confined to only 

parts of the United States. Even so, the estimates (1) provide a perspective on the size and spatial 

variation in some benefits in some areas; (2) can aid judgments on how to weave reported and unreported economic and biophysical information together to support information-based decisions on 

targeting wetland conservation funding; and (3) illustrate the need for additional data and analyses 

to further support information-based decisionmaking. 

11For example, see the U.S. Environmental Protection Agency’s discussion on wetland impacts at: http://water.epa.gov/

type/wetlands/outreach/upload/EconomicBenefits.pdf

12Not all wetland “benefits” are positive—some people may look at wetlands as a source of mosquitos and displeasing 

odor.

13We apply a 4-percent market rate of discount in this analysis, the longrun return on AAA bonds (U.S. Federal Reserve, 2012), because interest rates observed on AAA bonds are reflective of the time preference for money, void of any 

risk premium. 
10

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Estimating the value of wetlands and their ecosystem services 

To estimate the value of a new wetland’s benefits, one must apply economic and biophysical 

sciences. Biophysical sciences enable one to quantify the services that a new wetland and its ecosystems are likely to produce. The same sciences can link changes in services to changes in environmental amenities—that is, the things people care about. Economic analyses can enable one to 

estimate the public’s willingness to pay for changes in amenities.14

Each of these economic and biophysical tasks is critical; the strength of a wetland benefit estimate 

is only as strong as its weakest link. As one’s understanding of each link improves, so, too, will the 

analyses of wetlands’ spatial benefits.15 Furthermore, a better understanding of these links will help 

one better understand the tradeoffs embedded in wetland ranking criteria. 

Table 1 lists some of the services wetlands and their ecosystems produce, the amenities that services 

produce, and the ways in which the public values amenities. Appendix 2 provides details on the 

biophysical and economic framework critical in evaluating the benefits of a new wetland. 

This framework for estimating the value of benefits requires several kinds of information (both data 

and models). The specific units that define a wetland service and the amenities provided by each 

service are “grey” in that the way in which they are specified by an analyst will depend on the available data, models, and other information. What is important is the conceptual framework that the 

functions illustrate. When this information is not fully available, a number of shortcuts can be taken, 

including reduced-form models, proxy variables, and meta analysis. But, as discussed in appendix 

2, several features leave meta analyses unsuited to generate spatially disaggregated estimates of 

benefits. 

Duck hunting benefits: What the study found 

Wetlands directly affect duck populations. Between 55 and 80 percent of all North American ducks 

nest in the Prairie Pothole Region (PPR) (see fig. 1). Ducks of the PPR region migrate using all of 

the continent’s major flyways, including the coastal flyways. Increases in duck populations generate 

a variety of amenities that people throughout the country enjoy:

• Improved hunting quality

• Better bird watching throughout the year

• An increase in the size and number of fall migrating flocks 

This study focuses on wetlands’ impacts on hunting quality and people’s willingness to pay for the 

changes. 

14Valuing changes in amenities is complicated by the nonmarket nature of these goods. Instead of market prices, valuation models are used to calculate a marginal price. (See box “Analytical Methods for Valuing Environmental Amenities” 

for a short list and brief description of methods used to value environmental amenities.)

15Knowledge of these links is also necessary when evaluating benefits of on-field conservation incentives. Additionally, 

analysts face the challenge of quantifying indirect effects of the incentive payments, where indirect effects are defined as 

the changes in farming practices made elsewhere in response to the conservation incentive (Smith and Weinberg, 2004). 

For example, incentives that discourage some farmers from sequential years of corn production can increase the price of 

corn and increase corn production (and subsequent environmental impacts) elsewhere. 
11

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Table 1

Functional relationships between new wetlands’ direct effect on the environment and the 

value the public places on the subsequent impacts on amenities

Biophysical and environmental processes Economic valuations

Resource

The services 

produced by 

wetland x

Amenities that stem 

from services 

The public’s demands or willingness 

to pay for amenities

f

i

(x)→ gj(fi(x))→ Dk(gj

(fi(x)))

E

C

O

S

Y

S

T

E

M

S

E

R

V

I

C

E

S

Habitat for 

terrestrial and 

aquatic species 

Improved species’ 

survival rates

What are people willing to pay to better protect 

species?

Improved duck hunting 

quality 

What are people willing to pay for better 

hunting?

Increased health of 

game fish species

What are people willing to pay for better 

recreational fishing?

Increased health of 

commercial fish species

What is the change in the commercial fishing 

industry’s profits?

Nutrient removal Less algae in 

freshwaters

What are people willing to pay to have cleaner 

water?

Commercial fish populations less affected by 

hypoxic zones

What is the change in the commercial fishing 

industry’s profits? 

Lower nitrogen level in 

waters used by 

municipalities 

What are the municipal water-treatment costs 

savings associated with reduced nitrogen in 

intake waters?

Reductions in 

greenhouse gas

Economic, ecological, 

and health impacts of 

climatic change

What are people willing to pay for a reduction in 

the economic, ecological, and health impacts of 

climatic change?

S

E

R

V

I

C

E

S

Groundwater 

recharge

Drinking water supply What is a municipality willing to pay for an increase in water supply?

Groundwater use in 

agriculture

How much will increases in groundwater affect 

agricultural profits?

Groundwater’s effect on 

stream amenities 

What are people willing to pay to see an 

increase in the amenities? 

Floodwater 

retention

Reduced flood heights 

(wetland bounce) and 

water speeds

What is the expected value of the reduced 

expected property damages? 

What are people willing to pay to reduce risks to 

health and safety?

Open space Improved views What are people willing to pay to view a wetland, 

given its location?

Source: USDA, Economic Research Service.
12

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Analytical Methods for Valuing Environmental Amenities

The following descriptions are meant to strengthen our illustration of the analytic framework supporting the 

valuation of wetland benefits. For more details on these and additional approaches and their application to wetland benefit analyses, see Brander et al. (2006).

Contingent Valuation relies on surveys of a sample of the relevant population. Individuals are asked about their 

willingness to pay for (or accept) a change in an environmental amenity. There are many variations of this approach, 

but they involve surveys on preferences. The collected data are then used to estimate the public’s demand (or willingness to pay) for the amenity (Loomis and Walsh, 1997). 

Travel Cost Method uses survey data that included details on the quality of the amenity each survey respondent 

sees, personal information, travel time and costs, and recreation activities associated with the amenity. Changes in 

consumer surplus associated with a change in the amenity are derived from the estimated demand function.

Hedonic Analyses derive social values of environmental amenities by estimating demands for market goods as 

a function of (among other things) the quantity and quality of the amenities. This approach is suitable when the 

existence of an amenity directly affects the price individuals are willing to pay for a market good. For example, 

one can value an improvement in a lake’s water quality by estimating consequential changes in the market prices 

of properties around the lake. 

Damage Function Approach is based on the assumption that the value of a change in an amenity (such as the 

economic impact of a flood) is approximately equal to the cost of repair damages, loss in profits, and decrease in 

standards of living associated with the change in the amenity. The approach is thought to provide imprecise benefit 

estimates because it implicitly assumes that no remedial actions are taken and there is no accounting for market 

effects. For example, a reservoir can reduce flood damages. The value of the reservoir’s flood protection benefit, 

based on the damage function approach, is the reduction in expenditures made to repair flood damages. But, with 

reduced risks of flooding, individuals will reduce expenditures on flood-damage prevention. This cost savings is 

also a flood protection benefit.

Replacement Cost Method assumes that the welfare effect of a loss in an amenity is approximately equal to any 

increase in expenditures that would subsequently restore the amenity. For example, the loss of safe drinking water 

from one’s well is approximately equal to one’s subsequent purchases of bottled water. This approach is made difficult because changes in expenditures may not be observed, and remedial action may not be taken.

Averting (Defensive) Expenditure Method assumes that the welfare effect of public actions taken to reduce 

or prevent impacts to an amenity (e.g., reduce downstream flood damages) is approximately equal to the dollar 

amount individuals pay to reduce or avoid the impacts (such as their cost of sandbagging floodwaters). Some 

studies argue that this approach overstates benefits (Freeman, 1993; Ribaudo, 1989). Although, in practice, it can 

be difficult to isolate the portion of expenditures that are attributable to averting damages, the approach continues 

to be used (Whitehead, 2005). 

Benefits Transfer is a valuation approach used to generate benefit estimates based on the results of past research. 

There are (roughly) three types of benefit transfer approaches. The value transfer approach reviews the economic 

literature for per-unit values (or average values) that are then used as a measure of value. The second approach 

uses past benefit functions and their results to generate more generalized benefit or willingness-to-pay functions. 

And meta-analyses estimate benefit functions using findings of past research as independent variables. While this 

approach is convenient, it has imposed substantial errors (Brander et al., 2006).
13

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

For this analysis, we developed a biophysical model and applied findings of earlier research to 

generate spatial estimates of the effects of new wetlands on duck populations (an ecosystem service). 

Then, using findings of past research and reasonable assumptions, we linked changes in duck 

populations to changes in hunting quality (an amenity). Finally, we used benefits transfer to tie an 

economic value to changes in hunting quality. In the PPR, annual per-acre values of the effects of 

new wetlands on hunting quality ranged from near $0 to $143 per acre, with the highest values in the 

PPR’s western fringe (fig. 3).

The biophysical models: Duck populations

Duck population growth is constrained by the availability of breeding habitat and factors affecting 

nest success (Hoekman et al., 2002). In other words, an increase in wetlands that support duck 

reproduction will increase duck populations (a wetland service). We developed models that generate 

spatial estimates of expected increases in numbers of hatchlings (of the five dominant duck species) 

produced by new wetlands in the PPR. The models were constructed using a combination of earlier 

models, findings of past research, and available data. The models simultaneously predict the number 

of duck nesting pairs that are likely to take residence in a new wetland and the probability that a nest 

is successful (that is, the eggs hatch), given its location and the surrounding vegetative cover (for 

details, see appendix 3). To determine the subsequent change in duck populations, we applied findings of Krapu et al. (2000) and Nichols and Hines (1983), which suggest that about 50 percent of all 

duck hatchlings reach adulthood.

Dollars per acre

per year

0 - 11

12 - 21

22 - 30

31 - 39

40 - 50

51 - 63

64 - 82

83 - 143

Figure 3

Value of new wetlands' effects on duck-hunting quality in the Prairie Pothole Region

Source: USDA, Economic Research Service analysis of wetlands’ effects on hunting quality (appendix 3) and a 

“per-duck” consumer surplus estimate of $106.
14

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

The effects of new wetlands on hatchling populations were found to vary substantially across the 

PPR, with the greatest impacts in the Dakotas along the Missouri River. We found that the effect of 

a new wetland can range from 0 to over 55 hatchlings (27.5 adult ducks) per wetland acre.

Valuation of amenities: Duck hunting benefits 

Multiple studies evaluated the economic value associated with duck hunting. But, only three generated estimates of consumer surplus that result from an improvement in the quality of duck hunting 

on a scale suitable to analyses of national or regional conservation policies and programs (table 2).16

Each of these studies defines hunting quality (the amenity) as the number of ducks bagged. Across 

these studies, willingness-to-pay estimates for a marginal improvement in hunting quality range 

from $15 to $140 per duck (in 2011 dollars). These studies have limitations (see box “Estimating 

the Value of One More Duck”). Based on our assessment of this literature, we use a value toward 

the upper end of this range ($106) and discuss how estimates and their implications are affected by 

lower duck-value estimates. 

Linking services to amenities: Hunting quality 

With ducks bagged as a proxy measure of hunting quality, we used prior research and reasonable 

assumptions to link changes in duck populations to changes in ducks bagged. Based on mallard 

harvest rates of approximately 10-12 percent and a blue-wing teal harvest rate of approximately 

2.5 percent (U.S. Fish and Wildlife Service, 2012), we applied what we believe to be a conservative harvest rate of 5 percent. In other words, each additional duck has a 1-in-20 chance of being 

bagged. Using an amenity value of $106 per bagged duck, the expected value of an additional duck 

is approximately $5.00, or $2.50 for each additional hatchling. Multiplying the hatchling value by a 

wetland’s effect on hatchlings, we find that, within the PPR, the annual per-acre values of wetlands 

duck-hunting benefits range from near $0 to $143, with the highest values in the western fringe of 

the PPR. Both the value of bagging a duck and the harvest rate directly affect the per-acre value of 

a wetland. For example, if one were to apply a $26 per-duck value (which is about 25 percent of the 

value we applied), per-acre values would fall by 75 percent—from near $0 to $46 per acre. If one 

were to apply a 10-percent harvest rate, per-acre benefits would double. Applying other per-duck 

values and harvest rates is equally straightforward. In all cases, the pattern of relative values shown 

in figure 3 remains unchanged. 

16Suitable data for analyses of hunter demands require population surveys with questions that relate to hunting opportunities and details on activities (see box “Estimating the Value of One More Duck”). 

Table 2

Studies that estimate the change in consumer surplus associated with bagging an 

additional duck

Study Valuation method and type of data Consumer surplus per duck bagged

Hammack and Brown (1974) Time series data on hunting activities $15 to $34 with a mean value 

of $24.50

Charbonneau and Hay (1978) Survey of hunting activities of hunters 

in the Mississippi River flyway 

$106

Mackenzie (1993) Survey of Delaware hunters on 

hypothetical hunting options

$132 to $140

Note: All values are reported in 2011 inflation-adjusted dollars.

Source: USDA, Economic Research Service. 
15

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Estimating the Value of One More Duck 

Our review of the literature revealed five core studies with objectives that include estimating hunters’ demand for 

duck hunting.1 Three studies specified demand as a function of (among other things) hunting quality (see table 2). 

These studies derive hunters’ willingness to pay for a marginal change in duck hunting quality by differentiating the 

demand function with respect to hunting quality—bagging one more duck. The first (Hammack and Brown, 1974) 

used time-series data on hunting behavior in the Pacific Northwest. It estimated the gain in consumer surplus of 

bagging an additional duck to be between $15.38 and $33.62 (in 2011 inflation-adjusted dollars). 

The second (Charbonneau and Hay, 1978) used cross-sectional data from the 1975 National Survey of Hunting, 

Fishing, and Wildlife Associated Recreation (NSHFWAR) to estimate demand as a function of hunting quality, 

experience, costs (travel expenses and the opportunity cost of travel time), and income. Based on their estimated 

demand function, the authors found that hunters are willing to pay, on average, $106 to bag an additional duck on 

a single day (see table 2). 

The third study (Mackenzie, 1993) used data from a survey of Delaware duck hunters where hunters were asked 

to choose from alternative hypothetical sites to estimate hunters’ demand for duck and goose hunting. Similar to 

the approach of Charbonneau and Hay (1978), demand was estimated as a function of travel cost, travel time, the 

site characteristics, hunting partners, and site congestion. Mackenzie found that, on average, hunters’ willingness 

to pay for an additional duck bagged ranged from $132 to $140 (see table 2).

Two other studies have directly estimated demands for duck hunting; neither estimated WTP for improved 

hunting quality. Each generated per-day consumer surplus estimates, as did Charbonneau and Hay (1978). We 

therefore compare the day-value estimates to gain some insight into the consistencies of the estimated demand 

functions. Charbonneau and Hay (1978) estimated per-day consumer surplus to be $121. Brown and Hay 

(1987)—employing the 1980 NSHFWAR data—estimated per-day consumer surplus to range from $64 to $82, 

which is about 65 to 80 percent of the Charbonneau and Hay (1978) estimate. However, Brown et al. (1978)—

using the same data as Charbonneau and Hay—estimated average per-day consumer surplus to be $122, which 

supports the findings of Charbonneau and Hay (1978).

We chose not to use Hammack and Brown (1974) because, unlike subsequent research, they failed to account 

for the opportunity cost of time—the opportunity cost continues to be recognized as a critical part of travel 

cost (Larson and Lew, 2014; Menon et al., 2014). Additionally, Gascoigne et al. (2011) rejected the Hammack 

and Brown (1974) model because, upon the use of more recent values of the independent variables, they felt the 

model generated values that were unacceptably low (less than $4 per duck).2

We applied the Charbonneau and Hay estimate of $106. The more recent Mackenzie (1993) results suggest this 

value might be low. Conversely, our day-value comparison with the Brown and Hay (1987) estimates suggests the 

Charbonneau and Hay (1978) estimate might be high. 

The age of these studies raises questions: Has the public’s willingness to pay changed over time? Has the 

increase in the U.S. population increased the number of duck hunters and the number of people benefiting from 

improved hunting quality? Have behavioral models or empirical methods improved in such a way that duck 

hunting demand might be better estimated? These same questions arise in most meta analyses. As with authors 

of previous studies, we assume that, after adjusting for price-level changes, the reported values are reasonable. 

But given our uncertainty of this estimate, we also use other duck values to illustrate the sensitivity of our results. 

1These five studies estimate hunters’ demand for hunting across wide regions—they estimate the aggregate demand within their study 

area. Many other studies estimate hunters’ demand at a single site or across substitute sites, such as game refuges in California. Demand 

at each site depends on the size and interest of the surrounding population, travel costs, the quality of hunting at surrounding sites, and 

other location-specific factors. If the results of a substantial number of site-demand studies scattered throughout the relevant region were 

available, it may be possible to estimate an aggregate demand based on the results of the site-level studies. However, instead of the studies being scattered throughout, the majority of the studies focus on sites on public lands in areas where hunting is popular. 

2Gascoigne et al. (2011) subsequently moved from a marginal benefit analysis to an aggregate day-value approach. 
16

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Nitrogen removal: What the study found

Wetlands can improve water quality by removing chemicals before they reach streams, rivers, and 

other waterways. Of particular interest is the ability of wetlands to filter out reactive nitrogen (N).17

Reducing nitrogen loadings in water provides various amenities:

• Improvements in the quality of municipal intake waters

• Cleaner water for swimming, boating, and recreational fishing

• Increased profitability of commercial fisheries

Confined by the limitations of data and models, we evaluated N removal by new wetlands in the 

Upper Mississippi and Ohio River watersheds—this area is the primary source of N affecting the 

hypoxic zone of the Gulf of Mexico, where excess nutrients have depleted oxygen needed to support 

marine life. Additionally, this region has opportunities for wetland restoration because 80 to 90 

percent of prior-existing wetlands were drained. But we could not link the change in nitrogen loadings to an impact on an environmental amenity, nor could we find or estimate a monetary value for 

impacts on amenities. We therefore focused on N removal and found that rates varied substantially, 

ranging from 11 pounds to nearly 1 ton per wetland acre per year (see fig. 4). 

The biophysical model: Nitrogen removal

Building on available models and data, we generated estimates of the expected quantity of N 

removed by a restored 10-acre wetland. These models work with hydrology, inflow water quality, 

and weather and climatic conditions at grid points throughout much of the Upper Mississippi and 

Ohio River watersheds.18 To capture the effects of daily and annual variations in precipitation levels 

and intensity on nitrogen movement and wetland effectiveness, we ran 20-year simulations (see 

appendix 4). 

Economic models of amenities affected by nitrogen inflows

We found two large-scale economic analyses of the benefits of reducing N loadings; both relied on 

reduced-form models. First, in an attempt to value changes in Gulf of Mexico hypoxia, Diaz and 

Solow (1999) used 30-year time-series and geographical data to estimate economic impacts on 

commercial fisheries and recreational fishing activities as a function of the size of the hypoxic zone 

and other factors and found no statistically significant results. 

Second, in an analysis of municipal water treatment costs, Ribaudo et al. (2011) found that nitrogen 

has a statistically significant impact on costs. They reported municipalities’ longrun nitrogen 

removal costs ranging from $20 to $36 per million gallons of treated water in those areas where 

treatment plants are necessary. Note that this cost estimate is a function of the volume of water and 

17Reactive nitrogen is a general term used to represent the set of nitrogen compounds that support plant growth. Other 

chemicals include phosphorous, herbicides, and insecticides. Due to a paucity of data on the prevalence and impacts of 

these chemicals, these issues are left for future research.

18Other wetlands are known to remove nitrogen from surface waters, but the complexities of very similar wetlands’ hydrology make it difficult to predict effects of similar wetlands. For example, in an analysis of depressional wetlands near 

the Chesapeake Bay, Denver et al. (2014) found that the depth of the aquifer below the wetland is the largest determinant 

of nitrogen removal. Information on aquifer depth is not readily available, making it difficult to predict the nitrogen 

removal rate of a restored wetland in some areas.
17

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

not the quantity of nitrogen. Even so, the study’s findings suggest that a change in nitrogen inflow to 

streams affects water treatment costs.

At the national level, the U.S. Environmental Protection Agency Science Advisory Board (2007) 

examined both the benefits and co-benefits of nitrogen conservation practices, including those 

at wetlands. The Board found evidence of economic benefits of N reductions but concluded that 

co-benefits (such as the values of consequential decreases in soil erosion) may exceed the nitrogen 

reduction benefits.

Linking services to amenities: The value of reduced N inflows 

Overall, we were unable to link spatial changes in N flows into streams to the subsequent outflows 

to the Gulf of Mexico. But Rabotyagov et al. (2014) found a statistically significant link between N 

inflow to the Gulf of Mexico and the size of the hypoxic zone, using a simple statistical model and 

time-series data. 

Overall, evidence of the effects of the Gulf of Mexico’s hypoxic zone on ecosystems is mixed. 

Bianchi et al. (2010) found no evidence that discharge from the Mississippi River adversely impacted 

Gulf of Mexico fisheries. Consistent with the findings of Diaz and Solow (1999), other studies found 

no clear link between hypoxia and changes in fishery landings in the Gulf (Rabalais and Turner, 

2001). In fact, Bianchi et al. (2010) note that there appears to be some effect on the distributions of 

N removed (lbs/acre)

11 - 125

126 - 250

251 - 400

401 - 560

561 - 730

731 - 900

901 - 1,075

1,076 - 1,250

1,251 - 1,430

1,431 - 1,817

Figure 4

Amount of nitrogen removed annually by a new wetland in the Upper Mississippi and 

Ohio River watersheds 

Source: USDA, Economic Research Service. 
18

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

mobile fish species and phyto- and zooplankton that prosper in the nutrient-rich waters that add to, 

what appears to be, an additional food web. 

Still, there are grounds for concern about hypoxia in the Gulf of Mexico. For example, the FederalState Mississippi River Gulf of Mexico Watershed Nutrient Task Force (2013) noted that “low 

dissolved oxygen in the Gulf is a serious environmental concern that can impact valuable fisheries 

and disrupt sensitive ecosystems.” 

The findings of analyses of waters in the Gulf of Mexico must not be viewed as representative of 

other hypoxic zones. The hypoxic zone of the Gulf of Mexico lies within a great expanse of deep 

waters while, in most other cases, hypoxic zones are in shallow waters in bays and along shorelines 

where ecosystems are easily impaired and damaged (Bianchi et al., 2010).

Species protection: What the study found

The public’s willingness to pay to protect species reflects the following:

• A desire for opportunities to view the species 

• The ethics of protecting resources for future generations

• Uncertainty that there may be subsequent domino effects on other species if one or more species 

or their habitats are lost

This analysis considers only wetland-associated species identified by NatureServe as imperiled in 

2014.19 In 2014, approximately 597 wetland-associated species were listed as imperiled (217 are 

listed as critically imperiled) across the entire range for each in the United States.20 The number of 

wetland-associated imperiled species within a county ranges from 0 to 23 (fig. 5a).

The need for a biophysical model: Species protection

An appropriate biophysical model would quantitatively link the addition of a wetland to the affected 

species. We obtained data from NatureServe (2014) that lists each wetland-associated imperiled 

species and the counties where each exists. The data are insightful but do not indicate whether 

a species’ survival is affected by an additional wetland—other habitat conditions, such as water 

quality, predation, and migratory habitat, may have an effect. Even in counties with no wetlandassociated imperiled species, it is possible that an additional wetland could have a positive impact on 

imperiled species—that is, expanding wetland habitat could help imperiled species in neighboring or 

downstream counties.

Valuation of amenities: Species protection

Some view species protection as a moral or ethical issue and object to placing a value on protecting 

a species. However, Shogren et al. (1998) point out that, while most Americans believe in fully 

19The NatureServe data used in our analysis include all species that have a NatureServe Global Conservation Status 

Rank of G1or G2. A rank of G1 indicates that a species is critically imperiled across its entire range. A rank of G2 indicates the species is imperiled over its range. Rankings are based on various biological and external factors that may affect 

the long-term viability of a species (Regan et al., 2004). For details on species classifications, see appendix A, page 46 in 

www.natureserve.org/sites/default/files/publications/files/natureserveconservationstatusfactors_apr12_1.pdf

20ERS analysis of NatureServe 2014 data (NatureServe, 2014).
19

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

protecting endangered species, they are unwilling to bear the cost of increasing the strength of the 

1973 Endangered Species Act. Because public funding for species protection is limited, decisionmakers who prioritize wetland conservation efforts consider tradeoffs in species’ protection so that, 

implicitly or explicitly, species are being valued (Roughgarden, 1995). 

Past research suggests that the public tends to have a higher willingness to pay to protect so-called 

“charismatic” species, including many large birds and mammals, than to protect others (Loomis 

and White, 1996; Brander et al., 2006; Richardson and Loomis, 2009; and Woodward and Wui, 

2001). In developing data for their meta analysis, Richardson and Loomis (2009) collected 

published species valuation studies. Most of the studies they found used contingent valuation, 

where respondents are asked a series of questions that are designed to reveal their willingness to 

pay to protect one or more species. However, the reported values are often based on a generalized 

concept of protection that cannot be directly used to calculate values of marginal improvements in 

species’ survival. 

Amenities provided: Wetland effects on imperiled species

An increase in a species’ survival probability is a quantitative measure of an increase in an environmental amenity (see 5-8 in U.S. Environmental Protection Agency (2014)). Research has yet to 

develop biophysical models that quantify new wetlands’ effects on species survival probabilities 

(e.g., the amenities). Without a measure of new wetlands effects, estimates of the values of changes 

Number of species

0

1 - 2

3 - 5

6 - 9

10 - 15

16 - 23

Figure 5a

Wetland-associated imperiled species, by county 

Source: USDA, Economic Research Service using data from NatureServe, 2014.
20

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

in species’ survival probabilities offer little insight into the relative importance of different wetlands’ 

effect on imperiled species. 

In the absence of biophysical models, we have generated proxies to provide insight into the effects 

of wetland restoration on imperiled species. The proxy is the number of wetland-associated imperiled species in a county. This approach has been used in past studies—counties with high imperiled 

or endangered species counts are considered “hot spots” (Dobson et al., 1997; Ando et al., 1998). 

Szentandrasi et al. (1995) used this approach to assess how one might target CRP enrollments. 

An analysis of NatureServe data shows that imperiled species were located in 1,745 counties (about 

57 percent of all contiguous U.S. counties) in 2014, and that 1,366 counties have no wetland-associated imperiled species. Concentrations of imperiled species are greatest in the Southwest (as many 

as 23 per county) and are spread throughout much of the Southeast (fig. 5a). 

Restricting the analysis to vertebrate species (such as birds, amphibians, and mammals), which tend 

to receive the most public attention, we found a total of 76 imperiled wetland-associated species (28 

of which are critically imperiled) and numbers per county ranging from 0 (in 2,010 counties) to 8. 

Southern California and neighboring lands and Appalachia are the hot spots (fig. 5b).21

These findings must be cautiously interpreted because there are no measures of the effects of a new 

wetland or the values of effects on different species. Findings do, however, provide some perspective 

on where new wetlands might benefit a greater number of imperiled species.

Flood protection: What the study found 

Society is willing to pay to reduce flooding because of private and public benefits including 

damages:

• To reduce personal risks of damage to property and health and a disruption of daily lives

• To reduce public expenditures on disaster relief

• To avoid damage to public infrastructure

• To maintain healthy communities

• To adhere to ethics of protecting the health and property of others

Wetlands provide protection by storing water, slowing its movement, and reducing storm surges 

associated with heavy precipitation and rapid snow melts. Losses caused by floods include both 

human life and property. Floods damage private structures and public infrastructures, destroy crops, 

and wash away farmland. According to the U.S. Department of Commerce, National Oceanic and 

Atmospheric Administration (NOAA), annual property damages attributed to flooding usually lie 

between $1 billion and $10 billion, but a spike of $50 billion occurred in 2005 due to a large number 

of storms and the especially severe damage wrought by Hurricane Katrina.

21Counties where imperiled wetland-associated species are prevalent may not be important to agricultural policy if 

there are few opportunities to restore wetlands on agricultural land.
21

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

The biophysical model: Floodwater storage

In a comprehensive analysis, Bullock and Acreman (2003) reviewed 169 studies of wetlands’ hydrologic performances, including their effects on flooding. Findings of these studies varied widely—in 

some cases, wetlands increased flooding. They conclude that, while wetlands play a role in flood 

protection, comparisons of wetlands’ effectiveness must be given careful consideration. 

A wetland’s “bounce”—its ability to store additional water as rivers reach peak flows—can help 

determine whether the wetland can control flooding. A wetland’s bounce is usually small (Bullock 

and Acreman, 2003). However, bounce can be increased if water level can be controlled. For 

example, in a site-level analysis, Bengtson and Padmanabhan (1999) used a hydrologic model to estimate the relationship between reduced peak flow and storage bounce in the Red River Watershed of 

North Dakota. They found that, unless modified, wetlands in the watershed did little to reduce peak 

flows because, as river levels rose, wetlands filled. But, if wetlands were allowed to drain until rivers 

began to peak, a 1-foot impediment placed on all wetlands (creating a 1-foot storage bounce across 

the wetland acres) could reduce damages from high-frequency flood levels by 3.8 percent; a 2-foot 

impediment could reduce damages by over 5 percent.22

22Wetlands can reduce flood levels from short, heavy downpours when wetland water levels are relatively low, and they 

can capture a portion of the surge in water flows. 

Number of species

0

1

2

3 - 4

5 - 6

7 - 8

Figure 5b

Wetland-associated imperiled vertebrae species,* by county

*Includes birds, mammals, amphibians, and reptiles.

Source: USDA, Economic Research Service using data from NatureServe, 2014.
22

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Valuation of amenities: Expected reductions in flood damages

Five studies in the literature estimated the economic value of wetland flood protection benefits. The 

studies do not offer values directly transferable to wetlands restored on agricultural lands for one or 

more of the following reasons: they focus on wetlands in close urban proximity with limited agricultural lands; they focus on coastal areas where agricultural acreage is limited; they evaluate wetlands 

with flow impediments; and they aggregate wetlands with other land uses. However, the studies are 

likely to illustrate upper-bound ranges of flood protection values. 

Gupta and Foster (1975) estimated the flood control benefits of wetlands in the Charles River Basin 

of metropolitan Boston—a major urban area. Using Army Corps of Engineers data, they found 

expected avoided damages to be $56 to $440 per wetland acre (inflation adjusted to 2011 dollars) per 

year. Values such as these may be applicable to wetlands on agricultural lands but in limited areas 

with considerable housing or urban development. 

NOAA provides statistics on some U.S. coastal wetlands’ services, including estimates of coastal 

wetlands’ flood protection benefits that were originally generated by Costanza et al. (2008) (see 

http://stateofthecoast.noaa.gov/wetlands/welcome.html). Costanza et al. reported benefits of near 

$0 to $29,600 per acre per year, with some of the highest benefits in Louisiana. Conversely, Farber 

(1987) estimated benefits of flood protection by coastal wetlands in Louisiana to be substantially less 

(i.e., less than $50 per acre). Again, values such as these may be applicable to wetlands on agricultural lands in coastal areas.

Shultz and Leitch (2003) estimated the flood protection benefits of restoring 2,700 acres of 

wetlands—with flow impediments—in the Maple and Red River Watersheds of North Dakota. They 

found that when wetland outlets were controlled (e.g., water was captured only when flows were 

peaking, consistent with Bengtson and Padmanabhan (1999)), expected annual benefits ranged from 

$12 to $25 per acre. 

The U.S. Army Corps of Engineers (2013) estimated flood damage reduction benefits to downstream 

urban areas due to the CRP’s wetlands and riparian buffers. This pilot study focused on a small 

Iowa watershed (Indian Creek). It used several hydrologic models, simulated weather events, and 

a variety of CRP coverage scenarios (where each scenario differed in the quantity of CRP acreage 

and the distributions between wetlands and riparian buffers). The study found that, when rainfall 

events were short but very heavy, acres under CRP wetland practices can reduce property damage 

by 11 percent (although acres in riparian buffers are more cost effective). When the methods of this 

study were applied to a larger Iowa watershed (Cedar River), there was no measureable relationship 

between the CRP’s wetland and riparian buffer acreages and the change in flood stage.

Amenities provided: Reduced flooding due to wetlands

The dollar-per-acre flood protection benefits reported in Shultz and Leitch (2003) and other studies 

embody the link between the effects of wetlands on flooding and flood damages—they are reducedform analyses in which the benefit estimates are dependent on physical and economic parameters. We 

found too few studies in the literature that generated spatial estimates of wetlands’ flood protection 

benefits within any region to enable us to develop benefit models through benefits-transfer analyses.
23

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Net greenhouse gas emissions: What the study found

Many countries are seeking to reduce the growth in atmospheric concentration of greenhouse gases 

(GHG), primarily by reducing emissions. Some countries are also engaged in efforts to remove 

GHGs from the atmosphere, commonly through carbon sequestration. 

Wetlands are known to reduce atmospheric concentrations of carbon dioxide through carbon sequestration. But wetlands are also known to emit GHGs, primarily methane (CH4) and nitrous oxide 

(N2O). Both of these are considered “hot” and can more than offset the effect of CO2 removal.

Past research that has reviewed and evaluated findings of studies worldwide (Kayranli et al., 2010), 

within North America (Bridgham et al., 2006), and within the tropics and subtropics (Mitsch et al., 

2012) concluded that the effects of wetlands on GHG emissions are questionable, as carbon sequestration may be more than offset by methane and nitrous oxide emissions. These studies illustrate the 

importance of accounting for net GHG effects, but they do not provide measures of the GHG effects 

of different types and ages of wetlands. Similarly, many studies have estimated carbon sequestration 

and carbon storage by different types of wetlands (for an overview, see Bernal and Mitsch, 2012), 

but most do not measure net GHG impacts. 

Euliss et al. (2006) and U.S. Fish and Wildlife Service (2005) evaluated the net GHG effects of 

wetlands in the PPR and Mississippi Alluvial Valley (MAV) (see fig. 1), and findings from these 

studies are used in this analysis along with estimates of the marginal social cost of carbon developed 

by a Presidential Commission (U.S. Government, 2010). Based on these data, the annualized carbon 

sequestration benefit of a new, permanently restored wetland is $55 per acre in the PPR and $129 for 

an MAV wetland (table 3).

Net greenhouse gas emissions: The biophysical models—GHG impacts

Past research provides estimates of the net GHG impacts of wetlands in two regions: the PPR and 

MAV. Euliss et al. (2006) estimated that, 5 years after a wetland in the PPR is restored, 7.8 metric 

tons per acre of carbon is held in the living biota above and below ground—an average sequestration 

rate of 1.56 metric tons per acre per year. In subsequent years, carbon sequestration was estimated to 

average 0.34 metric tons per acre per year. Additionally, while wetlands of the PPR were estimated 

Table 3

Annual average per-acre carbon sequestration benefits of Prairie Pothole Region and 

Mississippi Alluvial Valley wetlands

Wetland regions*

SRD=3

r=4

SRD=5

r=4

SRD=2.5

r=4

SRD=3

r=5

SRD=3

r=3

$/acre*

PPR 1,378 371 2,160 1,251 1,536

MAV 3,222 930 4,955 2,776 3,667

Annualized values --------------------------4%-------------------------- 5% 3%

PPR 55 15 86 62 46

MAV 129 37 198 139 110

PPR=prairie pothole region; MAV=Mississippi Alluvial Valley: SRD=social rate of discount (%); r=market discount rate (%).

*2011 dollars.

Source: USDA, Economic Research Service.
24

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

to release methane and nitrous oxide, the release rates were estimated to equal the releases on the 

lands’ prior wetland restoration, meaning that the restored wetlands led to no change in the releases 

of these gases (Gleason et al., 2009; Gleason et al., 2005; Eagle et al., 2012).

In a second study in the PPR, Gleason et al. (2008) estimated carbon in above- and below-ground 

vegetation after 10 years to be about 11.13 metric tons per acre, which is about 1.6 metric tons per 

acre greater than the amount estimated by Euliss et al. (2006). We applied the Euliss et al. estimates 

because they are more conservative and they account for the effect of time on sequestration rates. 

Within the MAV, carbon accumulates primarily in the vegetative biomass (Faulkner et al., 2008). 

In 2005, the U.S. Fish and Wildlife Service (FWS) reported that vegetation on newly restored 

MAV wetlands held 99 metric tons per acre of carbon after 70 years for an average annual rate of 

1.41 metric tons per acre per year (USFWS, 2005). A second FWS analysis, also released in 2005, 

reports a 70-year average carbon sequestration rate of 1.77 metric tons per acre per year. We applied 

the more conservative 1.41 metric tons per acre per year. Research on N2O emissions by restored 

forested wetlands found no difference from the level released on agricultural cropland (in the first 

70 years), while net effects on CH4 releases are unknown but are not expected to have a large effect 

(Faulkner et al., 2008). 

The GHG impacts reported here are only relevant in cases where cropland is converted to wetlands. 

As with all evaluations of the GHG impacts of conservation practices, the prior use of the land and 

its effect on carbon loadings and releases of GHGs must be considered as it defines baseline conditions (see box “The Value of GHG Impacts Depends on GHG Emissions Over Time”). For example, 

pasture and hay land usually hold a greater stock of carbon in above- and below-ground vegetation 

than cropland. Therefore, the GHG impacts of wetlands restored on pasture or hay land will likely 

be lower than those of wetlands restored on cropland. 

Valuation of amenities: Net greenhouse gas emissions

To meet Executive Order 12866, an interagency research team was assembled to generate estimates 

of the social cost of carbon (SCC).23 These estimates are measures of the marginal cost imposed 

by a 1-ton change in atmospheric carbon dioxide in an observation year. Because the marginal 

economic effects increase as GHGs accumulate, the SCC increases over time (see table A1 in 

U.S. Government, 2010).24 The Executive Order requires agencies to use the estimates in costbenefit analyses of policies and actions that have marginal impacts on GHGs (for details, see U.S. 

Government, 2010). 

The SCC estimates—calculated using the damage function approach—are based on agreed-upon 

values related to many controversial issues, including the value of a human life, the expected rate of 

GHG accumulation, technological advances that offset impacts, and—perhaps the most economically controversial—the rate at which future damages (or adverse impacts to individuals’ life and 

23Executive Order 12866 required agencies “to assess both the costs and the benefits of the intended regulation and, 

recognizing that some costs and benefits are difficult to quantify, propose or adopt a regulation only upon a reasoned 

determination that the benefits of the intended regulation justify its costs” (U.S. Government, 2010).

24These social cost of carbon (SCC) estimates are somewhat higher but not out of line with those reported elsewhere. 

For example, Nordhaus (2014) estimated the SCC to be $18.60 per ton in 2015 while the International Panel on Climate 

Change (IPCC) reported an SCC of $23.80. But Nordhaus (2014) found the SCC increase to be faster (3 percent annually), reaching $52.30 in 2050, compared with the IPCC estimate of $44.90.
25

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

standard of living) are discounted, or social rate of discount (SRD) (U.S. Government, 2010). Some 

observers believe that the SRD should be 0 so that, for example, the value of a lost life in the future 

is the same as a lost life today; others believe a market discount rate is appropriate. This study 

applied SCC estimates that were derived from the agreed-upon SRD of 3 percent. For more on the 

conceptual differences between market and social discount rates and the sensitivity of the SCC estimates to the SRD, see U.S. Government (2010).

Amenities provided: Wetland impacts on GHG

Each year, the values of a new wetland’s GHG-reduction benefits differ due to variations in GHG 

impacts and the SCC. Instead of listing annual values, this study capitalized them using a 4-percent 

market rate of discount.25 We found that the present value of the GHG impacts of a restored wetland 

in the PPR is $1,378 per acre and $3,222 for an MAV wetland (assuming the wetland was restored in 

2013). Our estimates assume there will be no changes in wetlands’ GHG benefits after 2050 because 

there are no SCC estimates beyond this date. Had there been estimates for more years, our estimates of 

the GHG benefit of the restored and then undisturbed wetlands of the PPR and MAV would probably 

have been greater. To compare GHG benefits with our estimates of annual benefits and costs, we annu25The market discount rate is appropriate because we are evaluating investments in wetland resources, not the social 

welfare effects of losses in lives and human welfare. We apply a 4-percent market rate of discount in this analysis, the 

longrun return on AAA bonds (U.S. Federal Reserve, 2012). 

The Value of GHG Impacts Depends on GHG Emissions Over Time 

The carbon cycle associated with an agricultural practice is the annual change in atmospheric 

greenhouse gases (GHGs) over time, given what they would have been. This means that one must 

consider lands’ GHGs effects with and without the practice, even after the practice is terminated. 

Each social cost of carbon (SCC) estimate applied here is defined as the present-value sum of 

future damages of the climate change impact due to a marginal change in atmospheric GHG 

concentrations (see U.S. Government, 2010). The SCC estimates increase over time because, as 

GHG concentrations increase, marginal damages increase. 

Because the SCC rises over time (though the present value of future SCC estimates fall), it is critical to account for changes in GHG loadings on a year-by-year basis. This means one must account 

for effects after a conservation project’s life. By doing so, one finds that permanent conservation 

practices can generate far more benefits. For example, if a wetland restored (or tillage practice 

begun) at the beginning of 2013 sequesters 1 ton of carbon per year, its GHG benefits (assuming 

no impacts on other GHGs) would be $24.71 in 2013, $25.28 in 2014, etc.1 If the wetland is 

returned to agricultural production in 2015 and releases 1 ton of carbon each year, the damage due 

to the ton released in 2015 would be $25.82 and $26.00 for the ton released in 2016. The net GHG 

benefit of the wetland would be $2.09, when discounted to 2013 ($2.09=24.74 +25.28*(1.04)-1 – 

25.82*(1.04)-2 – 26.37*(1.04)-3). Should the same conditions hold and the wetland have a 10-year 

life, the net present value of the GHG impacts would be $34.00. Finally, if the wetland was left 

undisturbed, the net present value of the GHG impact would be $623—nearly 20 times the value 

of the 10-year life and 300 times the value of the 2-year wetland. 

1Values are from U.S. Government (2010) in 2011 dollars.
26

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

alized total benefits across the wetlands’ permanent lives using a 4-percent discount rate (as used in 

our cost analysis) and found regional values of $55 and $129 per acre, respectively (see table 3).

These benefit estimates are based on permanent restoration. If a wetland is moved back into agricultural production, carbon is released and GHG impacts become negative. For example, the present 

value of the carbon sequestration benefits of a permanently restored PPR wetland can be 20 times 

the value of a wetland that is converted to agriculture after 10 years (see box “The Value of GHG 

Impacts Depends on GHG Emissions Over Time”). All economic analyses of GHG benefits of 

conservation practices need to account for longevity. Conversely, losses of wetlands eliminate the 

flow of annual benefits provided, such as improved water quality and better hunting quality, but 

there are no subsequent damages (e.g., no negative costs imposed). 

Groundwater recharge, sediment removal, and open space: 

What the study found

No regional studies or data measure or value the effects of wetland restoration on groundwater 

recharge, sediment removal, or open space. Based on a number of small-scale studies, we concluded 

that (1) wetlands will sometimes provide positive recharge, sediment removal, and open-space benefits, but the sediment-trapping and open-space benefits can be negative; and (2) the benefits for each 

must be considered on a case-by-case basis.

Groundwater recharge: The analyses

The available literature indicates that, in some locations, wetlands may increase amenities through 

groundwater recharge (that is, the flow of water to groundwater supplies). But currently, little information is available on the effect of wetlands on groundwater. 

In most cases, wetlands do not recharge groundwater supplies. Some wetlands are wet because they 

are fed by groundwater, and some have a mutual exchange of water such that wetlands hold water 

when water tables are high and release water as the water table drops. In other cases, the soils under 

the wetlands are impermeable (Smith et al., 2011) (for more details on wetland types, see www.

water.ncsu.edu/watershedss/info/wetlands/function.html). However, wetlands in floodplains are 

often permeable and provide recharge that can help maintain flows in dry conditions (Bullock and 

Acreman, 2003). 

The value of water added to groundwater supplies depends on how the water might serve the public. 

Should the groundwater be a source of drinking or irrigation water, the affected individuals will 

value reduced pumping costs and any lessening of water-supply constraints. People will, indirectly, 

value groundwater that feeds lakes and streams if it subsequently increases amenities, such as fishing 

quality, species protection, and scenic beauty. 

Sediment removal: The analyses 

Based on the available literature, we were unable to conclude whether sediment trapping by any type 

of wetland will have net positive benefits. By trapping sediment, wetlands can improve water quality, 

but the sediment can damage the wetland ecosystems and, over time, fill some types of wetlands and 

eliminate subsequent wetland benefits (Gleason and Euliss, 1998). Other types of wetlands, such as 
27

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

riparian wetlands, may periodically receive high water flows that flush sediment into deeper waters 

and waterways; the flushed sediment can have adverse environmental impacts.

Open space: The analyses

We were unable to find studies that report the value of open space in rural settings. This is not 

unexpected because in rural areas, the public benefits of an additional acre of generic “open space” 

are likely to be small.26 However, wetlands—as natural open spaces—may have open space values 

greater than lands without wetlands. But a few factors may reduce the size of, or offset, this extra 

value. First, since these wetlands are on private land, they may not be accessible (or visible) to 

the public, which may reduce or eliminate open-space values. Second, “slippage” may occur. 

Specifically, a new wetland easement will preserve the open space of land in the easement, but it will 

not prevent the loss of open space anywhere else. The value of the open space that is preserved by 

the easement can be offset when land is subsequently developed elsewhere (Lichtenberg, 2011; Irwin 

and Bockstael, 2004). 

26Given that rural areas, almost by definition, have low population densities, open space is abundant. 
28

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Targeting Wetland Conservation Efforts

In this section, we overlay the spatial estimates of annual wetland benefits and costs and highlight 

implications for targeting wetland conservation funding to maximize these benefits relative to 

costs.27

Duck hunting benefits and costs of prairie pothole wetlands

Duck-hunting benefit-cost ratios are greater than one in about one-third of the PPR and are 

greatest in Montana and parts of western North Dakota, driven by both lower land costs and higher 

ecosystem productivity (fig. 6). This finding suggests that, in general, wetland restoration funds 

spent in the western PPR are likely to be a good investment in that they are likely to provide a positive social rate of return. Note that we have not conducted a site-by-site analysis, so some specific 

sites might have benefit-cost ratios that may or may not exceed our area estimate. 

27We were unable to include all costs, or all benefits, in our analysis so the estimated benefit-cost ratios may be too 

high or too low. However, for those benefits that were estimated, we expect that the spatial variations in benefit-cost ratios 

are realistic and informative for allocation decisions. 

Benefit/cost ratio

0 - 0.36

0.37 - 0.82

0.83 - 1.3

1.4 - 1.8

1.9 - 2.3

2.4 - 3

3.1 - 4

4.1 - 5.3

5.4 - 9.1

Figure 6

Duck-hunting benefits relative to wetland cost in the Prairie Pothole Region

Note: Based on a benefit estimate of $106 per duck.

Source: USDA, Economic Research Service analysis of the value of wetlands’ duck hunting benefits in figure 3 and 

wetland costs in figure 1. 
29

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Factors to consider when applying the duck-hunting benefit-cost estimates:

• If the value of new hatchlings differs across flyways, our benefit estimates may be missing some 

variation in wetland values.

• Other values of changes in duck populations, such as the value to birdwatchers, were not included 

because we found no measures.

• Wetlands of the PPR provide important duck nesting habitat (50 to 80 percent of all North 

American ducks nest in the PPR (Batt et al., 1989)). Wetlands in other parts of the country, suitable to nesting, will also increase duck populations and improve hunting quality. 

• Because duck populations are constrained by wetlands that can support nesting populations 

(Reynolds et al., 2007), improving or expanding wetlands in areas where ducks do not nest is not 

expected to increase duck populations. 

• We use a value of $106 per duck. Changing this value (for example, assuming the marginal value 

of a duck is $26) will cut benefits by 75 percent and reduce the size but not the spatial pattern 

of the distribution of the benefit-cost ratios. Conversely, if bag rates are greater than 4 percent (a 

value we feel is conservative), per-acre benefits would be greater. For example, increasing the bag 

rates to 10 percent would double the benefits amount. 

Nitrogen removal: The cost effectiveness of wetlands of the 

Upper Mississippi and Ohio River watersheds

The amount of nitrogen removed per dollar spent to restore and preserve a new wetland ranges from 

0.15 to 34 pounds (fig. 7). These estimates indicate that nitrogen removal costs, via new wetlands, 

range from $0.03 to $7.00 per pound. Within the area of study (the Upper Mississippi/Ohio River 

watershed), wetland restoration in east-central Illinois and southwestern Ohio tends to be most cost 

effective. If nitrogen reduction was the only environmental goal, these areas would be a good place 

to target wetland restoration funding.

Variations in costs and nitrogen removal rates both are strong drivers of cost-effectiveness. 

For example, east-central Illinois, southwestern Ohio, and north-central Iowa have some of the 

highest wetland nitrogen removal rates in the region (see fig. 4). However, high wetland costs in 

north-central Iowa make wetland restoration in this area less cost effective than in the other areas 

mentioned (see fig. 7).

Although nitrogen removal is not the only way that wetlands improve water quality, factors to 

consider when applying the nitrogen removal cost-effectiveness estimates include the following:

• The social values of reduced nitrogen loadings are unknown. But it appears that the presence of 

the hypoxic zone, and the evidence that schools of fish avoid it, increases the costs of harvesting 

fish due to an increase in travel cost. Also, public funding aimed at reducing nitrogen inflows to 

the Gulf of Mexico suggests that wetland impacts on nitrogen are likely to be of policy interest.

• There is little similarity between hypoxia’s effect on the ecosystems of the open and deep waters 

of the Gulf of Mexico and the effect on the much shallower waters of bays and along shorelines.
30

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

• The cost-effectiveness estimates reflect reduction in nitrogen entering a stream, lake, or river. 

The estimates do not necessarily reflect the cost effectiveness of reducing downstream impacts 

because they do not account for in-stream nitrification. 

• The costs and the effectiveness of wetlands vary by wetland size. Because of limits to modeling 

capabilities, this analysis considers only 10-acre wetlands. 

Survival of imperiled species 

Research results do not reveal how a change in wetland acreage will affect species’ survival probabilities. Also, with only a few estimates of people’s willingness to pay for a marginal increase in 

survival probabilities, we cannot value wetlands’ species protection benefits.

We did examine “hot spots”—areas with large numbers of wetland-associated imperiled species. 

Dividing by cost, we found species-per-dollar estimates to be greatest in much of California, in 

southern Oregon, along the Missouri River in the PPR, and in Appalachia (figs. 8a and 8b). 

Factors to consider when applying the cost-effectiveness estimates:

• We identify counties with some of the highest numbers of wetland-associated imperiled species and 

report ratios of the numbers of species relative to wetland costs. These numbers provide a perspective but in no way indicate economic advantages of restoring one wetland relative to another.

Pounds per dollar

0 - 2

3 - 4

5 - 6

7 - 8

9 - 11

12 - 13

14 - 16

17 - 34

Figure 7

Quantity of nitrogen removed relative to wetland cost in the Upper Mississippi and 

Ohio River watersheds

Source: USDA, Economic Research Service analysis of the estimated quantity of nitrogen that a new wetland can 

remove (figure 4) and the cost of new wetlands (figure 1).
31

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

• The available data identify counties where no or very few wetland-associated imperiled species 

currently exist, which suggests, but does not indicate, that species-protection benefits might be 

relatively low. 

Carbon sequestration in the PPR and MAV

The value of the GHG impacts of wetlands throughout the MAV and much of the central and 

western PPR, the two areas where wetlands’ GHG impacts have been estimated, exceeds our estimate of the cost of restoring and protecting wetlands (fig. 9). If a 5-percent SRD was applied, 

wetlands’ carbon sequestration benefit-cost ratios would fall by 70 percent. Even under this conservative scenario, benefit-cost ratios are greater than one in the northwestern part of the PPR and 

throughout much of the MAV. 

Factors to consider when applying the carbon sequestration benefit-cost estimates:

• Benefit estimates assume that the wetlands are restored on agricultural land. 

• Benefit estimates assume that the wetlands are permanent. Converting these wetlands back to 

agricultural use would result in the release of CO2 and possibly a very substantial fall in benefits.

Species per dollar

0.005 - 0.03

0.04 - 0.07

0.08 - 0.1

0.2

0.3 - 0.5

Figure 8a

Number of wetland-associated imperiled* species relative to the cost of new wetlands, 

by county 

*A classification of “imperiled” is based on various biological and external factors that may affect the long-term viability

 of a species (Regan et al., 2004).

Note: White indicates that there are either no imperiled species or no cost estimates. 

Source: USDA, Economic Research Service using data from NatureServe (2014) and the cost of new wetlands in 

figure 1.
32

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

• The economic benefits of marginal changes in GHGs are those prescribed by Executive Order 

12866 (U.S. Government, 2010). Agencies are required to use these values to assess the cost and 

benefits of GHG policy and program options.

Considering benefits together

Two of our benefit estimates overlap in the PPR: duck hunting and carbon sequestration. Summing 

the two PPR benefit-cost ratios, we find that wetlands in the western areas of the PPR have the highest 

ratios (fig. 10). This is expected given the symmetry in the hunting and GHG cost-benefit ratios. 

We estimated nitrogen-removal cost effectiveness in parts of the PPR. In these areas, 2 to 8 pounds 

of nitrogen are removed per dollar—$0.12 to $0.50 per pound—which is in the lower end of the 

$0.03 to $7.00 range estimated for wetlands across the Upper Mississippi and Ohio River Valleys. 

But, being different units of measure (e.g., pounds of nitrogen versus dollar benefits), the values are 

not additive. 

We found no biophysical or economic data or models that would enable us to estimate wetlands’ 

species-protection benefits. Spatial data indicate that the 57 percent of counties in the contiguous 

48 States have at least one wetland-associated imperiled species. But restoring a wetland in any 

county, even in one that currently has no wetland-associated imperiled species, may affect species’ 

Species per dollar

0.004 - 0.015

0.016 - 0.024

0.025 - 0.034

0.035 - 0.053

0.054 - 0.121

Figure 8b

Number of wetland-associated imperiled* vertebrae species** relative to the cost of 

a new wetland, by county 

*Includes birds, mammals, amphibians, fish, and reptiles. **A classification of “imperiled” is based on various biological 

and external factors that may affect the long-term viability of a species (Regan et al., 2004).

Note: White indicates that there are either no imperiled vertebrae species or no cost estimates.

Source: USDA, Economic Research Service using data from NatureServe (2014) and the cost of new wetlands in figure 1. 
33

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

survival probabilities.28 Conversely, it is also possible that restoring a wetland in counties with many 

imperiled species may provide no support. Biophysical models that can predict wetlands’ impacts on 

species’ survival probabilities would be very insightful. Additionally, studies that estimate the relative strengths of the public’s preferences (or their WTP) to protect different species are limited. As a 

result, it is difficult, at best, to evaluate the tradeoffs of restoring alternative wetlands. 

The current distribution of restored and protected wetland acreage

Although we did not estimate many wetland benefits, a comparison of benefits with the spatial 

distribution of wetland conservation acreages illustrates how the targeting of wetland conservation 

efforts might be improved. WRP contract acreage tends to be more concentrated in the MAV, the 

eastern portion of the PPR, and parts of California and Oregon (fig. 11). We find CRP wetlandrelated contract acreage spread across much of rural America, but with considerable concentration in 

the PPR (fig. 12). In a comparison with benefits, the most compelling findings include the following:

28Some of these counties may have no wetlands. Some of these counties may have few, if any, wetlands affected by 

agriculture. There is also the possibility that a wetland can have an indirect effect on a species that is not readily apparent. For example, a wetland’s effect on nitrogen loadings could affect the survival rate of a species that is not wetlandassociated. 

Benefit/cost ratio

0.5 - 1.0

1.1 - 2.5

2.6 - 3.7

3.8 - 7.7

7.8 - 18.8

Figure 9

Wetlands’ carbon sequestration benefits relative to wetland cost in the Prairie Pothole 

Region and the Mississippi Alluvial Valley, by county

Source: USDA, Economic Research Service analysis of wetlands’ impacts on greenhouse gases, (reported by Euliss 

et al. (2006) and the USFWS (2005)), estimated values of marginal changes in greenhouse gasses (reported by 

U.S. Government (2010)) and the wetland cost estimates in figure 1.
34

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

• Figure 11 indicates that, in the PPR, WRP acreage is denser in the eastern portion, where costs 

tend to be higher (see fig. 2) and duck hunting benefits lower (see fig. 3). Additionally, the total 

(hunting plus carbon sequestration) benefit-cost ratio estimates are higher where WRP contract 

density is lower (see fig. 10). This suggests that, within the PPR, targeting wetland restoration and 

protection funding toward the western areas is likely to provide the greatest net social benefit—

note that not all benefits have been estimated. Furthermore, while the imperiled species perdollar estimates are high in the western portion of the PPR (see fig. 8a), the value of wetlands’ 

species protection is not necessarily higher. 

• Figure 12 indicates that in the PPR, the CRP wetland-related contract acreage is denser in 

the eastern portion, where (as pointed out above) costs tend to be higher (see fig. 2) and the 

duck hunting benefits lower (see fig. 3). Because the CRP contracts are only 10 to 15 years, 

carbon sequestration benefits will be substantially less than the values reported here (unless the 

CRP-funded wetlands remain in place long after contracts expire) (see box “The Value of GHG 

Impacts Depends on GHG Emissions Over Time” on page 25).

• The MAV has some of the highest density of WRP acreage (see fig. 11). The carbon sequestration 

benefits of the WRP acreage in most of this area tend to exceed costs—and these wetlands provide 

other benefits, including biodiversity and water quality. This result provides some justification for 

the greater density of the WRP acreage. 

Total benefit-cost ratio

0.01 - 1

1.1 - 2.2

2.3 - 3.1

3.2 - 4

4.1 - 5

5.1 - 6.4

6.5 - 8

8.1 - 9.8

9.9 - 15

Figure 10

Sum of duck-hunting and carbon-sequestration benefit-cost ratios of new wetlands in 

the Prairie Pothole Region

Source: USDA, Economic Research Service analysis of the benefits of duck hunting in figure 3, wetlands’ impacts on 

greenhouse gasses, (reported by Euliss et al. (2006) and the USFWS (2005)), estimated values of marginal changes in 

greenhouse gasses (reported by U.S. Government (2010)), and the cost of new wetlands in figure 1.
35

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

WRP acres 

Figure 11

Number of acres enrolled in the Wetlands Reserve Program, by county

Source: USDA, Economic Research Service analysis of USDA, Natural Resources Conservation Service confidential data 

on Wetlands Reserve Program contracts.

3 - 1,250

1,251 - 3,750

3,751 - 7,500

7,501 - 15,900

15,901 - 34,584

CEAP Wetland Regions
36

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Figure 12

Distribution of Conservation Reserve Program wetland-related contract acreage 

(both wetland and upland), by county

Source: USDA, Economic Research Service using confidential program data from USDA, Farm Service Agency, 

Conservation Reserve Program.

Acres

0 - 1,950

1,951 - 6,300

6,301 - 13,300

13,301 - 26,150

26,151 - 60,450 Total acres = 25.6 million
37

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Conclusions 

This study generates spatial estimates of the cost of restoring and preserving wetlands and the social 

values of some of the benefits they and their ecosystems produce. The results illustrate large spatial 

variations in wetland costs and benefits and economic advantages to targeting wetland conservation 

efforts. This information is designed to aid public policymakers, program operators, nongovernmental organizations, and the general public in efforts to employ evidence-based decisionmaking in 

wetland conservation. While limited by information constraints, this study begins to answer questions such as the following: Where are restored wetlands likely to be most cost effective at removing 

nitrogen? How much would duck hunters be willing to pay for additional wetlands across the PPR? 

How valuable are wetlands’ greenhouse impacts? What is the likely cost of establishing a new 

wetland? Answers to these and similar questions are fundamental in constructing and improving 

conservation contract ranking criteria, such as environmental benefit indexes. 

The findings and modeling framework discussed here provide guidance in setting future research 

priorities in two ways. First, and most apparent, the findings indicate where information is missing 

and draws attention to where further biophysical and economic research might be most useful. For 

example, we found that wetlands of the Upper Mississippi and Ohio River watersheds can be, but are 

not always, very effective at removing nitrogen, but we did not estimate the effectiveness of wetlands 

elsewhere. This result suggests that analyses of the nitrogen removal rates of wetlands in areas where 

nitrogen loadings impose social costs could prove to be useful. 

Second, the study’s analytic framework can help lay out relevant questions. First, is the value of the 

wetland benefit, D(g(f(x))), likely to be large relative to other benefits? Second, how weak is the 

weakest link or what link(s) is(are) missing: The data on wetland characteristics: x? The models of 

wetland service: f(x)? The models of amenities produced: g(f(x)))? Or the demand or willingness to 

pay function: D(g(f(x)))? And third, how can the derivation of one model help narrow the focus of 

research on the other models? For example, before allocating research funding to estimate wetland 

effects on groundwater recharge, consider the economic importance of groundwater: Do many people 

in the area consume groundwater either directly or through irrigation applications? Will additional 

groundwater reduce the potential for seasonal shortages of stream flows? Also, consider other critical 

biophysical links: Are the affected aquifers the same as those that feed consumers and streams? If the 

answers to these questions are “no,” then research efforts might be better channeled elsewhere.

After considering the contribution that economics can make and identifying some key information 

gaps, we offer suggestions for future research. This list is not comprehensive; rather, it is meant to 

illustrate areas where additional estimates will be useful. 

• Duck hunting benefits were found to be high but the estimates drew on willingness-to-pay analyses that are dated. Because of the economic significance of duck hunting benefits, accuracy is 

important. An update of individuals’ willingness to pay for improved hunting quality can help 

solidify results but will require data collection and analysis.

• Wetlands’ duck hunting benefits were found to be high and variable, but the spatial extent of the 

biophysical models are limited. This suggests that research that expands the spatial extent of 

biophysical models might be useful.
38

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

• Dollar-per-ton estimates are available for some soil conservation benefits (Hansen and Ribaudo, 

2008), and these estimates can be used to value wetlands’ soil conservation benefits. 29 But, 

to do so, estimates of wetlands’ effects on erosion are needed. One can expect erosion rates on 

converted wetland acreage to be less than county average rates because wetlands are commonly 

restored on flat lands. Land-use data, such as the National Resources Inventory, might be used to 

estimate erosion rates.

• The results of this study suggest that, in some areas, wetlands can be cost effective at removing 

nitrogen from nearby waterways. Thus, additional analyses of nitrogen removal by other sizes 

and types of wetlands across different-sized watersheds within and outside of the study area 

may be useful. 

• We did not review literature on public consumption of groundwater—we did not have estimates 

of wetlands’ effects on groundwater. Economic research that provides spatial estimates of the 

public’s willingness to pay for increased groundwater will indicate to hydrologists where they 

might focus analyses of wetlands’ effects on groundwater. Similarly, if research by hydrologists identifies areas where wetlands do affect groundwater, economists will see where to focus 

research on the valuation of groundwater. 

• Similarly, economic research that generates spatial estimates of the social cost of algae blooms 

in freshwaters (due to phosphorus loadings) can suggest to biophysical scientists areas of the 

country where they might focus research on phosphorus removal by wetlands. 

• The public’s willingness to pay to protect species appears to be high but not infinite, as indicated 

by historical expenditures (Shogren et al., 1998). A further review of the economics literature 

along with a survey of peoples’ preferences across species and levels of protection (e.g., changes 

in survival probabilities) can provide biologists with insights on those species that are of greatest 

public interest, hence, areas where they might prioritize research. The same information can 

also give those engaged in conservation efforts a better idea of how to prioritize funding for 

species protection. There are data that might enable analysts to examine the biophysical effects 

of wetlands on imperiled species. For example, information on the effects of habitat on species 

population may be contained within various descriptive text fields in NatureServe’s central database (www.fort.usgs.gov/Products/ProdSpecies_Index.asp) and on the U.S. Geological Survey 

Web site (www.fort.usgs.gov/Products/ProdSpecies_Index.asp).

29The soil-productivity benefit estimates reported in Hansen and Ribaudo (2008) should not be applied when land is 

not to be moved back into agricultural production. In cases where the land is idled temporarily, as with the CRP, one 

must account for the delay in the yield gains resulting from the increase in productivity.
39

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

References

Ando, A., J. Camm, S. Polasky, and A. Solow. 1998. “Species Distributions, Land Values, and 

Efficient Conservation,” Science 279(5359):2126-2128.

Arnold, J., and N. Fohrer. 2005. “SWAT 2000: Current Capabilities and Research Opportunities in 

Applied Watershed Modeling,” Hydrological Processes 19(3):563-72.

Batt, B., M. Anderson, M. Anderson, and F. Caswell. 1989. “The Use of Prairie Potholes by North 

American Ducks,” pp. 204-27, in A.G. van der Valk (ed.), Northern Prairie Wetlands, Ames, IA: 

Iowa State University Press. 

Bengtson, M., and G. Padmanabhan. 1999. A Review of Models for Investigating the Influence of 

Wetlands on Flooding, North Dakota Water Resources Research Institute, North Dakota State 

University. 

Bernal, B., and W. Mitsch. 2012. “Comparing Carbon Sequestration in Temperate Freshwater 

Wetland Communities,” Global Change Biology 18(5):1636-47.

Bianchi, T., S. DiMarco, J. Cowan Jr., R. Hetland, P. Chapman, J. Day, and M. Allison. 2010. 

“The Science of Hypoxia in the Northern Gulf of Mexico: A Review,” Science of the Total 

Environment 408(7):1471-84.www.sciencedirect.com/science/article/pii/S0048969709011620

(September, 2014). 

Borisova-Kidder, A. 2006. “Meta-Analytical Estimates of Values of Environmental Services 

Enhanced by Government Agricultural Conservation Programs,” Ph.D. Dissertation, Ohio State 

University.

Brander, L.M., R. Florax, and J. Vermaat. 2006. “The Empirics of Wetland Valuation: A 

Comprehensive Summary and a Met-Analysis of the Literature,” Environmental and Resource 

Economics 33:223-50.

Bridgham, S., J. Megonigal, J. Keller, N. Bliss, and C. Trettin. 2006. “The Carbon Cycle of North 

American Wetlands,” Wetlands 26 (4):889-916. 

Brown, G. Jr., J. Charbonneau, and M. Hay. 1978. “Estimating Values of Wildlife: An Analysis of the 

1975 Hunting and Fishing Survey,” Working Paper No. 7, U.S. Department of the Interior, Fish 

and Wildlife Service, Division of Program Plans.

Brown, G. Jr., and M. Hay. 1987. “Net Economic Recreation Values for Deer and Waterfowl 

Hunting and Trout Fishing, 1980,” Working Paper No. 23. U.S. Department of the Interior, U.S. 

Fish and Wildlife Service, Division of Policy and Directives Management. 

Bullock, A., and M. Acreman. 2003. “The Role of Wetlands in the Hydrological Cycle,” Hydrology 

and Earth System Science 7:358-89.

Charbonneau, J., and M. Hay. 1978. “Determinants and Economic Values of Hunting and Fishing,” 

Transactions of the 43rd North American Wildlife and Natural Resources Conference, 391-403 

Wildlife Management Institute, Washington, DC.
40

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Costanza, R., O. Perez-Maqueo, M. Luisa Marinez, P. Sutton, S.J. Anderson, and K. Mulder. 2008. 

“The Value of Coastal Wetlands for Hurricane Protection,” AMBIO: A Journal of the Human 

Environment 37(4):241-8. 

Cooper, J., and J. Loomis. 1993. “Testing Whether Waterfowl Hunting Benefits Increase With 

Greater Water Deliveries to Wetlands,” Environmental and Resource Economics 3:545-61. 

Cowardin, L. M., T. L. Shaffer, and P. M. Arnold. 1995. Evaluations of Duck Habitat and Estimation 

of Duck Population Sizes With a Remote-Sensing-Based System, Biological Science Report 2, 

National Biological Service, Northern Prairie Wildlife Research Center, Jamestown, ND. 

Crumpton, W., D. Green, A. Loan-Wilsey, R. McNeely, K. Kane, D. Otis, T. Cooper, and R. Johnson. 

2010. Assessment of Environmental Services of CREP Wetlands in Iowa and the Midwestern Corn 

Belt, Progress Report IV, Prepared for U.S. Department of Agriculture, Farm Service Agency.

Crumpton, W., G. Stenback, B. Miller, and M. Helmers. 2006. Potential Benefits of Wetland Filters 

for Tile Drainage Systems: Impact on Nitrate Loads to Mississippi River Subbasins, CSREES 

Project Completion Report, U.S. Department of Agriculture, Cooperative State Research, 

Education, and Extension Service. 

Denver J., S. Ator, M. Lang, T. Fisher, A. Gustafson, R. Fox, J. Clune, and G. McCarty. 2014. 

“Nitrate Fate and Transport Through Current and Former Depressional Wetlands in an 

Agricultural Landscape, Choptank Watershed, Maryland, United States,” Journal of Soil and 

Water Conservation 69(1):1-16.

Diaz, R., and A. Solow. 1999. Ecological and Economic Consequences of Hypoxia: Topic 2 

Report for the Integrated Assessment on Hypoxia in the Gulf of Mexico, NOAA Coastal Ocean 

Program Decision Analysis Series No. 16, U.S. Department of Commerce, National Oceanic and 

Atmospheric Administration, Coastal Ocean Program.

Dobson, A.P., J.P. Rodriguez, W.M. Roberts, and D.S. Wilcove. 1997. “Geographic Distribution of 

Endangered Species in the United States,” Science 257:550-3.

Doss, C., and S. Taff. 1996. “The Influence of Wetland Type and Wetland Proximity on Residential 

Property Values,” Journal of Agricultural and Resource Economics 21(1):120-9.

Eagle, A., L. Olander, L.R. Henry, K. Haugen-Kozyra, N. Millar, and G.P. Robertson. 2012. 

Greenhouse Gas Mitigation Potential of Agricultural Land Management in the United 

States: A Synthesis of the Literature, Report NIR 10-04, Third Edition, Nicholas Institute for 

Environmental Policy Solutions, Duke University, Durham, NC.

Earnhart, D. 2001. “Combining Revealed and Stated Preference Methods to Value Environmental 

Amenities at Residential Locations,” Land Economics 77(1):12-29.

Euliss, N. Jr., R. Gleason, A. Olness, R. McDougal, H. Murkin, R. Robarts, R. Bourbonniere, and 

B. Warner. 2006. “North American Prairie Wetlands Are Important Non-Forested Land-Based 

Carbon Storage Sites,” Science of the Total Environment 361:179-88. 

Farber, Stephen. 1987. “The Value of Coastal Wetlands for Protection of Property Against Hurricane 

Wind Damage,” Journal of Environmental Economics and Management 14(2): 143-151.
41

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Faulkner, S., W. Barrow, B. Keeland, S. Walls, T. Moorman, D. Twedt, and W. Uihlein, III. 2008. 

Assessment of Ecological Services Derived from U.S. Department of Agriculture Conservation 

Programs in the Mississippi Alluvial Valley: Regional Estimates and Functional Condition 

Indicator Models, Interim Report, U.S. Geological Survey, National Wetlands Research Center. 

Feather, P., D. Hellerstein, and L. Hansen. 1999. Economic Valuation of Environmental Benefits and 

the Targeting of Conservation Programs: The Case of the CRP, Agriculture Economic Report 

No. 778, U.S. Department of Agriculture, Economic Research Service, www.ers.usda.gov/publications/aer-agricultural-economic-report/aer778.aspx#.U_4gqWM_xQI 

Freeman, A., III. 1993. The Measurement of Environmental and Resource Values: Theory and 

Methods, Washington, DC: Resources for the Future.

Gascoigne, W., D. Hoag, L. Koontz, B. Tangen, T. Shaffer, R. Gleason. 2011. “Valuing Ecosystem 

and Economic Services Across Land-Use Scenarios in the Prairie Pothole Region of the Dakotas, 

USA,” Ecological Economics 70(10):1715-25.

Gleason, R., and N. Euliss Jr. 1998. “Sedimentation of Prairie Wetlands,” Great Plains Research

8(1), Northern Prairie Wildlife Research Center Online, www.npwrc.usgs.gov/resource/wetlands/

sediment/index.htm 

Gleason, R., N. Euliss, Jr., R. Mcdougal, K. Kermes, E. Steadman, and J. Harju. 2005. Potential of 

Restored Prairie Wetlands in the Glaciated North American Prairie to Sequester Atmospheric 

Carbon, Plains CO2 Reduction Partnership, University of North Dakota.

Gleason, R, M. Laubhan, and N. Euliss Jr. (eds). 2008. Ecosystem Services Derived from Wetland 

Conservation Practices in the United States Prairie Pothole Region with an Emphasis on 

the U.S. Department of Agriculture Conservation Reserve and Wetland Reserve Programs, 

Professional Paper 1745, U.S. Department of the Interior, U.S. Geological Survey.

Gleason, R., B. Tangen, B. Browneb, and N. Euliss, Jr. 2009. “Greenhouse Gas Flux From Cropland 

and Restored Wetlands in the Prairie Pothole Region,” Soil Biology & Biochemistry 41:2501-7.

Gupta, T., and J. Foster. 1975. “Economic Criteria for Freshwater Wetland Policy in Massachusetts,”

American Journal of Agricultural Economics 57: 40-45.

Hammack, J., and G.M. Brown, Jr. 1974. Waterfowl and Wetlands: Toward Bioeconomic Analysis, 

Washington, DC. Resource for the Future, Inc.

Hansen, L., and M. Ribaudo. 2008. Soil Conservation Benefit Variables: Regional Values for 

Policy Assessment, Technical Bulletin No. 1922, U.S. Department of Agriculture, Economic 

Research Service, September, www.ers.usda.gov/publications/tb-technical-bulletin/tb1922.

aspx#.U_4gAGM_xQI 

Hansen, L., J. Delgado, M. Ribaudo, and W. Crumpton. 2012. “Minimizing Costs of Reducing 

Agricultural Nitrogen Loadings: Choosing Between On- and Off-field Conservation Practices,”

Environmental Economics 3(4): 97-112.

Hansen, L., P. Feather, and D. Shank. 1999. “Valuation of Agriculture’s Multisite Environmental 

Impacts,” Agricultural and Resource Economics Review, 28(2): 199-207. 
42

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Hansen, L., V. Breneman, C. Davison, and C. Dickens. 2002. “The Cost of Soil Erosion to 

Downstream Navigation,” Journal of Soil and Water Conservation 57(4): 205-212. 

Hoekman S., L. Mills, D. Howerter, J. Devries, and I. Ball. 2002. “Sensitivity Analyses of the Life 

Cycle of Midcontinent Mallards,” Journal of Wildlife Management 66:883-900. 

Irwin, E., and N. Bockstael. 2004. “Land Use Externalities, Open Space Preservation, and Urban 

Sprawl,” Regional Science and Urban Economics 34:705-725.

Jenkins, W. Aaron, Brian C. Murray, Randall A. Kramer, E Stephen P. Faulkner. 2010. “Valuing 

Ecosystem Services From Wetlands Restoration in the Mississippi Alluvial Valley,” Ecological 

Economics, 69(5): 1051-1061. 

Kaul, I., I. Grunberg, and M. Stern. 1999. “Introduction,” in Global Public Goods: International 

Cooperation in the 21st Century, Inge Kaul, Isabellle Grunberg, and Marc A. Stern (eds)., New 

York: Oxford University Press. 

Kayranli, B., M. Scholz, A. Mustafa, and Å. Hedmark. 2010. “Carbon Storage and Fluxes Within 

Freshwater Wetlands: A Critical Review,” Wetlands 30:111-124.

Kazak, N., and T. BenDor. 2013. “The Land Value Impacts Wetland Restoration,” Journal of 

Environmental Management, Vol. 127: 289-299, September. 

Krapu, G., P. Pietz, D. Brandt, and R. Cox, Jr. 2000. “Mallard Brood Survival in Prairie Pothole 

Landscapes,” Waterfowl 13:18. 

Langpapa, C., and J. Kerkvliet. 2012. “Endangered Species Conservation on Private Land: Assessing 

the Effectiveness of Habitat Conservation Plan,” Journal of Environmental Economics and 

Management 64(1): 1-15. 

Larson, D., and D. Lew. 2014. “The Opportunity Cost of Travel Time as a Noisy Wage Fraction,” 

American Journal of Agricultural Economics 96(2): 420-437.

Lawley, C., and C. Towe. 2014. “Capitalized Costs of Habitat Conservation Easements,” American 

Journal of Agricultural Economics 96(3): 657-672.

Lichtenberg, E. 2011. “Open Space and Urban Sprawl: The Effects of Zoning and Forest 

Conservation Regulations in Maryland,” Agricultural and Resource Economics Review 40(3): 

393-404, December.

Loomis, J., and R. Walsh. 1997. Recreation Economic Decisions, Comparing Benefits and Costs, 

State College, PA: Venture Publishing, Inc., 436 p.

Loomis, J., and D. White. 1996. “The Economics Benefits of Rare and Endangered Species: 

Summary and Meta-Analysis,” Ecological Economics 18:197-206.

Ma, S., and S. Swinton. 2011. “Valuation of Ecosystem Services from Rural Landscapes Using 

Agricultural Land Prices,” Ecological Economics 70:1649-1659.

MacKenzie, J. 1993. “A Comparison of Contingent Preference Models,” American Journal of 

Agricultural Economics 75: 593-603, August.
43

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Mahan B., S. Polasky, and R. Adams. 2000. “Valuing Urban Wetlands: A Property Price Approach,” 

Land Economics, 76(1): 100-113.

Mayfield, H. 1975. “Suggestions for Calculating Nest Success” Wilson Bulletin 87: 456-466.

Menon, M., F. Perali, and M. Veronesi. 2014. “Recovering Individual Preferences for Non-Market 

Goods: A Collective Travel-Cost Model,” American Journal of Agricultural Economics 96(2): 

438-457.

Mississippi River Gulf of Mexico Watershed Nutrient Task Force. 2013. Reassessment 2013: 

Assessing Progress Made Since 2008, U.S. Environmental Protection Agency, Office of 

Wetlands, Oceans, and Watersheds.

Mitsch, W., B. Bernal, A. Nahlik, U. Mander, L. Zhang, C. Anderson, S. Jørgensen, H. Brix. 2012. 

“Wetlands, Carbon, and Climate Change,” Landscape Ecology, Published online: DOI 10.1007/

s10980-012-9758-8 

NatureServe. 2014. “NatureServe’s Central Databases,” Arlington, VA. 

Nichols, J., and J. Hines. 1983. “The Relationship Between Harvest and Survival Rates of Mallards: 

A Straightforward Approach With Partitioned Data Sets,” Journal of Wildlife Management 47: 

334-348.

Nordhaus, W. 2014. “Estimates of the Social Cost of Carbon: Concepts and Results From the DICE2013R Model and Alternative Approaches,” Journal of the Association of Environmental and 

Resource Economists 1(1/2).

Pattison, J., P. Boxall, and W. Adamowicz. 2011. “The Economic Benefits of Wetland Retention and 

Restoration in Manitoba,” Canadian Journal of Agricultural Economics/Revue Canadienne 

d’agroeconomie 59: 223-244. 

Pease, J., M.L. Rankin, J. Verdon, and R. Reisz. 1997. “Why Landowners Restore Wetlands: A 

National Survey,” Iowa State University Extension, Department of Animal Ecology. 

Rabalais, N., and R. Turner (eds). 2001. “Coastal Hypoxia: Consequences for Living Resources and 

Ecosystems,” American Geophysical Union, Washington, DC.

Rabotyagov, S., T. Campbell, M., Philip W. Gassman, J. Arnold, L. Kurkalova, S. Secchi, H.li 

Feng, and C. Kling. 2010. “Least-Cost Control of Agricultural Nutrient Contributions to 

the Gulf of Mexico Hypoxic Zone, Ecological Application, 20(6):1542-1555, http://dx.doi.

org/10.1890/08-0680.1

Rabotyagov, S., C. Kling, P. Gassman, N. Rabalais, and R. Turner. 2014. “The Economics of Dead 

Zones: Causes, Impacts, Policy Challenges, and a Model of the Gulf of Mexico Hypoxic Zone,” 

Review of Environmental Economic Policy 8(1), pp. 58-79, doi: 10.1093/reep/ret024 

Regan, T., L. Master, and G. Hammerson. 2004. “Capturing Expert Knowledge for Threatened 

Species Assessments: A Case Study Using NatureServe Conservation Status Ranks,” Acta 

Oecologica 26:95-107.
44

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Reynolds, R., and A. Regalado. 2002. “The Effects of Wetlands and Other Factors on Rural Land 

Values,” Appraisal Journal, 72:182-190, April.

Reynolds, R., C. Loesch, B. Wangler, T. Shaffer. 2007. “Waterfowl Response to the Conservation 

Reserve Program and Swampbuster Provision in the Prairie Pothole Region, 1992-2004,” U.S. 

Department of the Interior, Bismarck, ND. 

Reynolds R., T. Shaffer, C. Loesch, and R. Cox Jr. 2006. “The Farm Bill and Duck Production in the 

PPR: Increasing the Benefits,” Wildlife Society Bulletin, 34(4), pp. 963-974, November.

Reynolds R., T. Shaffer, R. Renner, W. Newton, and B. Batt. 2001. “Impact of the Conservation 

Reserve Program on Duck Recruitment in the U.S. Prairie Pothole Region,” Journal of Wildlife 

Management 65: 765 780. 

Richardson, L., and J. Loomis. 2009. “The Total Economic Value of Threatened, Endangered and 

Rare Species: An Updated Meta-Analysis,” Ecological Economics 68:1535-1548.

Ribaudo, M. 1989. Water Quality Benefits from the Conservation Reserve Program, U.S. 

Department of Agriculture, Economic Research Service, Agricultural Economic Report No. 

606, February, www.ers.usda.gov/publications/aer-agricultural-economic-report/aer606.

aspx#.U_4k7mM_xQI 

Ribaudo, M., J. Delgado, L. Hansen, M. Livingston, R. Mosheim, J. Williamson. 2011. Nitrogen in 

Agricultural Systems: Implications for Conservation Policy, Economic Research Report No. 127, 

U.S. Department of Agriculture, Economic Research Service, www.ers.usda.gov/publications/erreconomic-research-report/err127.aspx 

Ribaudo, M., L. Hansen, D. Hellerstein, and C. Greene, 2008, The Use of Markets To Increase 

Private Investment in Environmental Stewardship, Economic Research Report No. 64, U.S. 

Department of Agriculture, Economic Research Service, September, www.ers.usda.gov/publications/err-economic-research-report/err64.aspx#.U_4lmGM_xQI

Rosen, S. 1974. “Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition,” 

Journal of Political Economy 82(1), 34-55. 

Roughgarden, J. 1995. The Economics and Ecology of Biodiversity Decline, Cambridge, UK: 

Cambridge University Press.

Shogren, J.F., J. Tschirhart, T. Anderson, A. Whritenour, A. Ando, S.R. Beissinger, D. Brookshire, 

G.M. Brown, Jr., D. Coursey, R. Innes, S.M. Meyer, and S. Polasky. 1998. “Why Economics 

Matters for Endangered Species Protection and the ESA,” Conservation Biology 3(6):1257-61.

Shultz, S., and J. Leitch. 2003. “The Feasibility of Restoring Previously Drained Wetlands to Reduce 

Flood Damage,” Journal of Soil and Water Conservation 58(1):21-29. 

Smith, L., M. Haukos, S. McMurry, T. LaGrange, and D. Willis. 2011. “Ecosystem Services 

Provided by Playas in the High Plains: Potential Influences of USDA Conservation Programs,” 

Ecological Applications 21:S82-S92. 
45

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Smith K., and M. Weinberg. 2004. “Measuring the Success of Conservation Programs,” Amber 

Waves, USDA, Economic Research Service, September, http://webarchives.cdlib.org/sw1vh5dg3r/

http:/ers.usda.gov/amberwaves/september04/features/measuringsuccess.htm

Stephens, S., J. Walker, D. Blunck, A. Jayaraman, D. Nalugle, J. Ringeiman, J. Ringelman, and 

A. Smith. 2008. “Predicting Risk of Habitat Conversion in Native Temperate Grasslands,” 

Conservation Biology 22: 1320-1330, doi: 10.1111/j.1523-1739.2008.01022.x 

Stewart, R.E., and H.A. Kantrud. 1971. Classification of Natural Ponds and Lakes in the Glaciated 

Prairie Region, Resource Publication 92, U.S. Fish and Wildlife Service, www.npwrc.usgs.gov/

resource/wetlands/pondlake/index.htm

Sullivan, P., D. Hellerstein, L. Hansen, R. Johansson, S. Koenig, R. Lubowski, W. McBride, D. 

McGranahan, M. Roberts, S. Vogel, S. Bucholtz. 2004. The Conservation Reserve Program: 

Economic Implications for Rural America, Agricultural Economic Report No. 834, U.S. 

Department of Agriculture, Economic Research Service, October, www.ers.usda.gov/publications/aer-agricultural-economic-report/aer834.aspx#.U_4oJ2M_xQI

Szentandrasi, S., S. Polasky, R. Berrens, and J. Leonard. 1995. “Conserving Biological Diversity and 

the Conservation Reserve Program,” Growth & Change 26(3):383-404.

U.S. Army Corps of Engineers. 2013. “Conservation Reserve Program Flood Damage Reduction 

Benefits to Downstream Urban Areas,” Rock Island District Pilot Project Report, Mississippi 

Valley Division Initiative, www.fsa.usda.gov/Internet/FSA_File/fsa_pilot_report_final.pdf

U.S. Department of Agriculture, National Agricultural Statistics Service (USDA, NASS). 2009. 

“Land Values and Cash Rents: 2009 Summary,” August, http://usda.mannlib.cornell.edu/usda/

nass/AgriLandVa//2000s/2009/AgriLandVa-08-04-2009.pdf.

U.S. Department of Commerce, National Oceanic and Atmospheric Administration. 2008. “Billion 

Dollar U.S. Weather Disasters 1980-2008,” National Climatic Data Center, www.ncdc.noaa.gov/

oa/reports/billionz.html

U.S. Environmental Protection Agency. 2014. “Benefits Analysis for the Final Section 316(b) 

Existing Facilities Rule,” EPA-821-R-14-005, May, http://water.epa.gov/lawsregs/lawsguidance/

cwa/316b/upload/Cooling-Water_Phase-4_Benefits_2014.pdf 

U.S. Environmental Protection Agency, Science Advisory Board (SAB). 2007. “Hypoxia in 

the Northern Gulf of Mexico: An Update,” EPA-SAB-08-003, http://yosemite.epa.gov/sab/

sabproduct.nsf/C3D2F27094E03F90852573B800601D93/$File/EPA-SAB-08-003complete.

unsigned.pdf 

U.S. Federal Reserve. 2012. “Moody’s Seasoned AAA Corporate Bond Yield,” Board of Governors 

of the Federal Reserve System, www.forecasts.org/index.htm.

U.S. Fish and Wildlife Service. 2012. “Adaptive Harvest Management: 2012 Hunting Season,” 

U.S. Department of Interior, Washington, DC, www.fws.gov/migratorybirds/mgmt/AHM/

AHM-intro.htm
46

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

U.S. Fish and Wildlife Service. Habitat and Population Evaluation Team, USFWS Region 6, 

Bismarck, ND, unpublished data.

U.S. Fish and Wildlife Service. 2005. “Entergy, Louisiana Partners Celebrate 2,900-Acre Addition 

to Tensas River Refuge Using Innovative Conservation Tool,” Press release May 23, www.fws.

gov/southeast/news/2005/r05-041.html 

U.S. Government. 2010. “Interagency Working Group on Social Cost of Carbon,” Technical Support 

Document: Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866, 

www.epa.gov/otaq/climate/regulations/scc-tsd.pdf 

Van Kooten, G. Cornelis, P. Withey, and L. Wong. 2011. “Bioeconomic Modeling of Wetlands 

and Waterfowl in Western Canada: Accounting for Amenity Values,” Canadian Journal of 

Agricultural Economics, January. 

Whitehead, J. 2005. “Environmental Risk and Averting Behavior: Predictive Validity of Jointly 

Estimated Revealed and Stated Behavior Data,” Environmental and Resource Economics 

32:301-316.

Woodward, R., and Y. Wui. 2001. “The Economic Value of Wetland Services: A Meta Analysis,”

Ecological Economics 37:257-270. 

Zinn J., and C. Copeland. 2007. Wetlands: An Overview of Issues, Congressional Research Report, 

Congressional Research Service, Washington, DC.
47

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Appendix 1—The Costs of Wetland Conservation Options

Our primary data are from a Wetlands Reserve Program (WRP) contract file. These data provide 

our associated variable: the total cost of a wetland (TWC). TWC is the sum of the restoration and 

easement costs of each contract. WRP contract data are agreed-upon contract payments and acreages 

and estimates of the wetland restoration costs—actual costs may differ. Overall, we expect these 

data to be representative of WRP costs. As long as the contract data are not systematically biased, 

they should be suitable for estimating wetland cost models. The data include a variable that identifies 

the county where the contract is located. We use this variable to link the WRP data to other data. 

We specified our cost model as:

TWC = f(Acres, AcresSq, AgrValue, AgrValueSq, Rural) 

Information on the size of each contract (Acres) is included in the WRP contract file. As discussed 

earlier, we expect the cost of restoring wetlands to increase with the size of the wetland, all else 

being equal. And we expect this relationship to be nonlinear; hence, we have included the seconddegree term acres squared (AcresSq). We also expect the nuisance costs of wetlands to be dependent 

on the size of the wetland and that the effect is nonlinear, all else being equal. We estimate each cost 

model using observations from the same wetland region to minimize variations in other determinants of restoration costs.

We have no county-level data on farmland values. But per-acre farmland rental rate data are 

available and can serve as a suitable proxy for variation in the value of the land’s agricultural 

productivity. We generated indicators of the agricultural value of land in contracts (AgrValue), by 

multiplying the contract acreage (Acres) by the county-average dry land rental rates reported by 

USDA’s National Agricultural Statistics Service (NASS). NASS generates rental values from various 

sources, including the recently initiated county-level cash rents survey (USDA, NASS, 2009). 

Because we expect a nonlinear relationship, we include the square of AgrValue (AgrValueSq).

We use the Population-Interaction Zones for Agriculture (PIZA) data to determine locations that 

may have urban pressure (Rural). The PIZA scores are designed to measure unban influence. The 

PIZA data classify counties as rural or as one of three levels of urban. (Documentation and PIZA 

data are available at: www.ers.usda.gov/data-products/population-interaction-zones-for-agriculture-

(piza).aspx). We use the PIZA scores to generate a zero-one dummy variable, Rural, that equals one 

when urban influence is likely to be minimal. 

Data that quantify actions taken to restore wetland hydrology and ecosystems and eliminate or 

control invasive species are not available. To overcome or minimize the effect of this shortcoming, 

we estimated separate cost functions for each of the USDA, Natural Resources Conservation 

Service’s Conservation Effects Assessment Project (CEAP) wetland regions (see fig. 1). By design, 

CEAP regions are defined by wetland similarities. It seems reasonable to assume that, within 

a wetland region, determinants of the cost of restoring a wetland—other than the size of the 

wetland—are less likely to vary than are determinants across wetlands regions. 

We acknowledge that AgrValue and Acres are correlated, as the size of a contract is one of the 

drivers of the cost of land and the cost of restoring and improving a wetland. This correlation can 

weaken conclusions one can draw about the signs, sizes, and statistical significance (due to inflated 

standard errors) of the estimated coefficients. However, correlation between independent variables is 
48

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

a model structural issue: it affects one’s ability to assess causality. It does not introduce systematic 

bias and therefore may not weaken the model’s prediction capabilities, which is our motivation for 

estimating the cost functions. 

Results and Model Applications

The adjusted R-squares of the estimated models top out at 0.88. Half capture more than 75 percent of 

the variation in the dependent variable; the three weakest capture 53 to 60 percent (table A1). Given 

the complications resulting from variable correlations, one cannot make any conclusions about the 

economic implications of the estimated coefficients. 

Before generating estimates of expected TWC for a new wetland, we need to identify appropriately representative contract sizes (Acres) for each wetland region. A comparison of the means and 

median indicates that the distribution of contract sizes is skewed toward the larger sizes (table A1). 

We chose to set Acres equal to the median-sized contract (for the region) as a useful representative 

measure since half of the contracts will be greater in size and half will be smaller. Because the cost 

functions are nonlinear, one does not know how cost estimates based on mean values compare with 

the potential range of estimated costs. For example, using the average wetland size is not likely to 

generate an estimate of average cost. One advantage of using median values is that the models will 

generate median cost estimates when based on median wetland sizes.

We generated estimates of total and average wetland costs for each county. Estimates show that there is 

less variability in projected costs in much of the Southeast than elsewhere; hence, benefit-cost ratios are 

less likely to be driven by variation in costs in the Southeast (see fig. 2). The Appalachian Highlands—

with a cost model that captures 88 percent of the variation in the dependent variable—has the widest 

range in predicted wetland costs, with values in a scattered distribution across the area. Predicted costs 

also vary widely across the Prairie Pothole Region, but the values show a consistent pattern of increase 

as one goes from the region’s northwest counties to the southeastern counties.
49

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Table A1

Estimated coefficients of the wetland cost models of the 10 wetland regions—continued

Wetland region Adjusted 

R-square Variable* Coefficient Standard error**

Number of 

observations

Glaciated Interior Plains 0.81

Intercept -1247.23 3162.32167

3,656

AgrValue 13.323 0.58039

AgrValueSq -2.98E-07 9.85E-07

Acres 434.2865 38.52275

AcresSq -0.02602 0.00738

Pacific Mountain 0.53

Intercept -31659 27684

265

AgrValue 46.83228 4.69902

AgrValueSq 0.000506 -0.00004666

Acres -419.998 175.86181

AcresSq 0.37051 0.0653

Prairie Pothole Region 0.79

Intercept -3870.37 2615.75999

2,468

AgrValue 29.22938 0.57392

AgrValueSq -0.00016 0.00000509

Acres -421.041 26.21381

AcresSq 0.19056 0.00684

Gulf Atlantic Coastal Flats 0.58

Intercept 207399 71840

283

AgrValue -3.57109 1.7062

AgrValueSq 5.86E-06 9.89E-07

Acres 790.5241 102.37909

AcresSq -0.02619 0.00321

Appalachian Highlands 0.88

Intercept 6509.232 1167.2668

1,537

AgrValue 40.12727 1.6565

AgrValueSq -0.00016 0.00003148

Acres -422.888 60.72724

AcresSq 0.23552 0.07277

High Plains 0.71

Intercept 14978 8847.30368

240

AgrValue 12.08406 3.76541

AgrValueSq 0.000264 0.00009641

Acres 473.1165 97.13946

AcresSq -0.31101 0.05205

Mississippi Alluvial Valley 0.60

Intercept 4339.446 9551.82475

1,417

AgrValue 23.84496 2.49292

AgrValueSq -5.7E-05 0.00001686

Acres -417.548 108.46545

AcresSq 0.14741 0.02848

Central Valley 0.76

Intercept -69276 44584

199

AgrValue 15.05214 9.40191

AgrValueSq 9.53E-05 0.00012050 

Acres 1597.231 214.96889

AcresSq -0.26999 0.07019

Continued—
50

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Table A1

Estimated coefficients of the wetland cost models of the 10 wetland regions—continued

Wetland region Adjusted 

R-square Variable* Coefficient Standard error**

Number of 

observations

Gulf Atlantic Coastal Plains 0.70

Intercept 11896 11909

963

AgrValue 8.59126 1.62986

AgrValueSq 2.86E-05 0.00000621

Acres 429.924 47.14001

AcresSq -0.03638 0.00344

Central Plains 0.84

Intercept 10650 4277.74641

706

AgrValue -3.57894 1.2879

AgrValueSq 0.000118 0.00000549

Acres 712.5908 43.61911

AcresSq -0.11722 0.0055

*In the first regression runs, we found that, in most cases, the coefficient on Rural was insignificant. Hence we dropped the variable. 

The R-square fell by less than two points. 

**Despite the fact that our variables are likely to be correlated and, consequently, the standard errors of the coefficients inflated, 

nearly all variable coefficients are statistically significant at the 99-percent level. 

Source: USDA, Economic Research Service. 
51

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Appendix 2—Conceptual Framework for Assessing 

Environmental Benefits

Economic and biophysical frameworks

The productivity of wetlands varies similar to the productivity of agricultural lands. There are 

different types of wetlands and different types of agricultural lands. Their outputs are affected by a 

variety of environmental factors. On the agricultural side, markets bring society’s preferences and 

production resources into alignment: producers choose what, how, and how much to produce based 

on prices and factor productivity. The prices consumers accept reveal society’s preferences.30

On the wetland side, there are few markets that can provide measures of the values of wetland 

services. Instead, efforts to cost effectively restore and protect wetlands must rely on estimates of 

wetland productivity and the public’s demands. 

This appendix provides a structural framework suitable to evaluating and comparing wetland 

conservation benefits. Consider the following simple algebraic formulation using x, f(x), g(f(x)), and 

D(g(f(x))).

• x: measures of eco-environmental characteristics, such as the size and type of wetland, daily 

temperature and precipitation, climatic conditions, surrounding land uses, quantity and quality of 

inflow waters, and the existence of invasive species.

• f

i

(x): the quantity of service i that a wetland produces. This will be a function of eco-environmental characteristics. For example, changes in coastal wetland conditions affect offshore fishery 

populations. 

o gj(fi(x)): the quantity of amenity j that is provided by a wetland. That is, a single service, 

f

i

(x), can produce a variety of amenities. For example, a new wetland can yield an increase 

in fish populations, fFISH(x), and the increase in fish populations can improve the catch of 

commercial fishing operations (gHARVEST(f

FISH(x))) and the quality of recreational fishing 

(gFISHINGQUALITY(fFISH(x))).31

• Dk(gj(f

i(x))): an amenity can be of value to people and commercial operations. When amenities 

directly affect commercial markets, the measurement of value is straightforward—the value of a 

change in the amenity is equal to the resulting change in profits, DPROFITS(gHARVEST(fFISH(x))). 

For example, extending the fish example, one could estimate the economic impact on commercial 

fishing by multiplying the dockside price of fish by the gain in harvest. When amenities affect 

nonmarket goods, estimating willingness to pay is more complicated. Again, extending the fish 

example, demand for improved fishing quality can be measured through a population survey 

where individuals are asked what they would be willing to pay for improved fishing quality. 

Or, in situations where participants are choosing from multiple sites with differences in fishing 

30When market failures exist (such as when farmers do not pay for damages or are not compensated for benefits their 

practices generate), market equilibrium is not likely to be socially optimal.

31Because the quality of recreational fishing is likely to depend on both catch rates and the size of fish caught, developing a measure of such an amenity, gFISHINGQUALITY(fFISH(x)), is challenging.
52

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

quality, willingness to pay can be derived from data on travel costs, fishing quality, and other 

environmental and population characteristics. 

The boundaries between x, f(x), g(f(x)), and D(g(f(x))) are “grey.” For example, one could define a 

wetland’s effect on duckling or adult populations as a service. We specify the link between a wetland 

and its amenities in a two-step process, g(f(x)) to emphasize that there can be a chain of relationships involved—that is, a new wetland removes nitrogen, which reduces nitrogen in river systems, 

which reduces nitrogen entering estuaries, which reduces hypoxia, which affects a bay’s ecosystem, 

which affects marine fisheries. 

The specifications of x, f(x), g(f(x)), and D(g(f(x))) are subject to the data and models that are 

available. Also, past environmental benefit analyses have applied shortcuts to measuring these 

relationships.

Alternative approaches for benefits analyses

Reduced form models

Reduced form models commonly shortcut the need to estimate the effect of an environmental 

service on an amenity by modeling demand as a function of the service D((f(x)). A variety of studies 

estimated regional and national water quality benefits of soil conservation practices by, first, using 

the Revised Universal Soil Loss Equation to estimate erosion, f(x), and, second, estimating willingness to pay for changes in water quality as a function of soil erosion (Sullivan et al., 2004; Hansen et 

al., 2002; Feather et al., 1999). In a regional analysis of the Conservation Reserve Program’s hunting 

benefits, Hansen et al. (1999) estimated a reduced-form spatial model where five of the independent 

variables (the surrounding mix of agricultural land uses) served as a proxy for the environmental 

amenity (hunting quality).

Proxy variables 

Proxy or indicator variables can sometimes be substituted for variables or data that are not available. 

For example, one could use the observed percent change in fish catch rates in the fisheries industry 

as a proxy for the percent change in the quality of recreational fishing. The strength of a proxy variable hinges on the correlation between the proxy variable and the true variable’s value. 

Meta-analysis

Meta-analyses use findings and models reported in previous research as data. Meta-analyses have 

been used to directly value wetlands, sidestepping the need to estimate the many biophysical relationships and economic values of the amenities. A major shortcoming of meta analyses related to 

wetlands is that, in most cases, they provide a single national or a limited number of regional values, 

and, hence, capture virtually no spatially resolution to variations in wetland benefits. Another shortcoming of meta analyses is that the studies used have not evaluated wetlands that are representative 

of the kinds of wetlands that are restored on agricultural land. For example, Brander et al. (2006) 

used the results of a study by Cooper and Loomis (1993) in a meta analysis of wetland values. But 

Cooper and Loomis used a travel cost analysis to determine hunters’ willingness to pay to hunt 

sites on public lands. Additionally, willingness to pay is determined by the sizes and proximities of 

surrounding populations, water levels in the wetlands, and other factors—these factors and features 

of public wetlands are not likely to be representative of wetlands restored on agricultural lands. 
53

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Borisova-Kidder (2006) attempted to estimate a wetland-benefits model suitable for U.S. agriculture 

policy and program analyses but was unable to control for differences in wetland benefits across 

wetland types. For example, there was only one appropriate study that evaluated a wetland in the 

Prairie Pothole Region of the Upper Midwest.
54

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Appendix 3—Predicting New Wetlands Effects on Ducks

We developed models that predict the number of hatchlings a new wetland is likely to produce 

for the five dominant duck species of the Prairie Pothole Region (PPRP (blue-winged teal (Anas 

discors), gadwall (A. strepera), mallard (A. platyrhynchos), northern pintail (A. acuta), and northern 

shoveler (A. clypeata)). Put simply, we model hatchlings (H) produced by a specific species at a 

wetland as a function of the nesting pairs (NP) the wetland attracts, nest success (NS), re-nesting 

propensity (NI), and clutch size (CS): 

H = NP * NS * NI * CS.

We built this relationship from data on duck species, findings of prior research, and two types of 

models—a nesting pair model and a nest success model—that were developed for the PPR of North 

and South Dakota and northeastern Montana. We extended this model and drew on other resources 

to generate estimates of wetland effects on hatchlings in the PPR of Iowa and Minnesota. 

We generated estimates of NP (nesting pairs) from a set of “pair-wetland relationship models,” one 

for each species and wetland class (i.e., temporary, seasonal, semi-permanent, lake, river (Steward 

and Kantrud, 1971, 1972; Cowardin et al., 1995) that were developed for field-level evaluations of 

the expected effects of a new wetland. Pair models were developed from breeding pair and wetland 

condition data collected during the U.S. Fish and Wildlife Service Annual Breeding Waterfowl 

Survey from 1987-2008 (Cowardin et al., 1995, Reynolds et al., 2006). We applied these pair models 

across 1 mile x 1 mile fishnet cells. This enabled us to generate a GIS surface of the number of 

breeding pairs added with a new wetland.

Nest success (NS) is the probability an egg survives all exposure days (Mayfield, 1975) and is a 

primary driver of duck population maintenance (Hoekman et al., 2002). Nest success is positively 

related to the share of surrounding grassland cover (Reynolds et al., 2001; Stephens et al., 2008). 

To estimate NS, we began with available daily nest survival rate (DNS) models (Mayfield, 1975) 

and developed spatially explicit models from Reynolds et al. (2001). The DNS model for a species i

is expressed as DNSi = ai + (b1 * percent grass) + (b2 * easting) + (b3 * northing) + (b4 * easting 

* northing), where ai is the intercept, percent grass is the share of grass cover within a 1-mile 

radius of the centroid point of each pixel, and easting and northing are longitudinal and latitudinal 

measures of the centroid point (Reynolds et al., 2001).

32

We used spatially specific measures of percent grass from landcover data from Thematic Mapper 

satellite imagery (93.5 ft. x 93.5 ft. pixel) for the years 2001-03 (Habitat and Population Evaluation 

Team, USFWS Region 6, Bismarck, ND, unpublished data). With these data and employing a 

moving window analysis, we calculated percent grass (which includes CRP) within the surrounding 

3.14-mile2 area (1 mile radius) of each pixel.

Finally, to generate spatial estimates of NS (the probability that a nest survives all days from when 

the first egg is laid to the day when the eggs hatch) for each species, we raised the DNS estimate of 

each species to the power of the number of nest-exposure days. 

32Values of easting and northing are expressed in meters and are based on the Universal Transverse Mercator, NAD 

83, zone 14. In our analysis, easting and northing were both divided by 100,000. 
55

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Nesting propensity (NI) accounts for cases where a nesting pair re-nests after losing its nest. By 

re-nesting, the nesting pair can still add to the hatchling population so it must be accounted for. 

Nesting propensity of a given species was treated as a constant and was taken for Bellrose (1980).

Average clutch size (CS) varies by species: mallard=8.4, gadwall=9.9, teal=10.2, pintail=9.9, and 

shoveler=7.1.

We generated estimates of the effect of new wetlands across the PPR and found that productivity 

ranges from near 0 to 57 hatchlings per acre. The distribution of the productivity of wetlands is 

skewed toward the lower end, with the bottom 10 percent of the wetlands likely to produce 3 hatchlings per acre or less. The productivity of the top 10 percent is 18 hatchlings per acre or more. The 

median level of productivity is 5.5 hatchlings per acre.
56

Targeting Investments To Cost Effectively Restore and Protect Wetland Ecosystems: Some Economic Insights, ERR-183

Economic Research Service/USDA

Appendix 4—Calculating Wetlands’ Nitrogen Removal 

Potential

We estimated the potential nitrate mass removal by wetlands as the product of nitrate mass load 

intercepted and the nitrate removal rate for locations across the Upper Mississippi and Ohio River 

Basins. Detailed descriptions on the estimation and application of the models that generated the 

mass loads and nitrate removal rates and supporting data sources are available in Crumpton et al. 

(2006) and Crumpton et al. (2010). In summary, Crumpton et al. (2006) generated spatial estimates 

of nitrate mass load based on the average water flow that would be intercepted by a wetland and 

the average nitrate concentration in that flow. Percent nitrate removal was calculated as a function 

of average hydraulic loading rate expected for wetlands at each location. Crumpton et al. (2010) 

extended the Crumpton et al. (2006) estimates to include the effect of tile drainage on nitrate 

concentration. Essentially, they estimated field nitrogen mass loss within a wetland watershed as 

a function of land uses (fraction of area in corn and soybean cultivation), tile drainage (fraction of 

crop land with tile drainage), and hydraulic loading rate and found all variables to be statistically 

significant (Crumpton et al., 2010). 

Our nitrogen-removal estimates were generated using the above models, Landsat land cover data 

from Landsat Thematic Mapper imagery, NRCS Soil Survey Geographical (SSURGO) data, 1980-

2005 U.S. Geological Survey stream gauge data, and 20-year simulations to capture expected variations in precipitation and rainfall intensity and their subsequent impact on nitrogen movement and 

wetland effectiveness. We assumed that wetlands are strategically placed at the bottoms of 1,000-

acre wetland watersheds.33 Our review of the literature and the analyses supporting the models 

we have applied indicate that a 1,000-acre wetland watershed is likely to be large enough to supply 

enough water to maintain a healthy wetland ecosystem and not atypical within our study areas. 

Furthermore, a recent study found that, in northwestern Ohio, a wetland of roughly 10 acres is most 

cost effective at nitrogen removal (Hansen et al., 2012). While other sized wetlands and wetland 

watersheds might have been considered, for the sake of brevity, we have not done so here. Our 

results indicate that, depending on where it is located, a new 10-acre wetland may remove 11 pounds 

to nearly 1 ton of nitrogen per wetland acre (see fig. 4).

33Strategic locations are locations where wetlands will capture surface and subsurface water flows from fields, as opposed to placing wetlands indiscriminately. When it comes to wetland location, the N removal estimates reported here 

should be viewed as upper-bound estimates.