Valuing the Ecosystem Services of Florida’s Forest Conservation Programs: The Economic Benefits of Protecting Water Quality

Melissa M. Kreye, Francisco J. Escobedo, Damian C. Adams, Taylor Stein, and Tatiana Borisova


Introduction

Forested ecosystems in Florida provide many kinds of ecosystem services, such as recreation, wildlife habitat, and carbon sequestration. One of the most beneficial services forests provide is the improvement of water quality through the reduction of pollutants, such as increased nutrients that result from various human activities. This paper will discuss the results of a study that examined the value of protecting water quality in Florida, and it will provide estimates of what Floridians may be willing to pay (WTP) for water quality protection programs that include forest conservation. Information about the value of using forest conservation to protect water quality in fresh water systems in Florida is limited, which makes it difficult to adequately account for the benefits associated with clean water when promoting the value of Florida's forests or when conducting economic analyses used in local and regional planning and policy formulation. One way to estimate the economic value of forest ecosystem services associated with clean water is to use an economic valuation method called "benefit transfer," or sometimes "meta-analysis." Benefit transfer uses an econometric model that takes economic dollar values from similar studies and applies those values to a specific or "new" site, adjusting for the characteristics of the new site. For an example of a benefit transfer see Figure 2.

Figure 1. Conceptual model of a meta-analysis model used to determine the statistical relationship among independent variables and the dependent variable (willingness-to-pay).
Figure 1.  Conceptual model of a meta-analysis model used to determine the statistical relationship among independent variables and the dependent variable (willingness-to-pay).

Figure 2. Conceptual model of how economic value estimates of program benefits can be transferred to a new site, or the policy site, using a meta-analysis of willingness-to-pay (WTP) valuation studies.
Figure 2.  Conceptual model of how economic value estimates of program benefits can be transferred to a new site, or the policy site, using a meta-analysis of willingness-to-pay (WTP) valuation studies.

This publication will present the results of a benefit transfer approach used to estimate the value of the water quality protection services provided by forests in Florida. Specifically it will introduce and discuss:

  1. How forest ecosystems reduce non-point source pollution in surface waters and how this ecosystem service benefits humans;

  2. How economic analyses can be used to assign a monetary value, or public willingness-to-pay, for this service;

  3. The results of a meta-analysis/benefit transfer approach to estimate the economic value of water quality protection and forest conservation programs in different regions of Florida; and, finally,

  4. A discussion about the drivers of WTP for different types of water protection programs, and a review of the implications and potential applications of this study.

Land-use decision makers such as county environmental department personnel, county commissioners, planners, and state and federal land and water quality managers can use this publication to educate policy makers and the general public about the value of ecosystem services provided by Florida's forests—specifically those ecosystem services related to water quality protection. This publication also will provide general estimates that can be used in planning/policy related economic analysis.

Protecting Water Quality with Forest Conservation

Non-point Source Water Pollution

Non-point source (NPS) nutrient pollution of surface waters is the introduction of excess nutrients into surface water bodies from land runoff and seepage. This type of pollution causes environmental problems such as algae blooms and depletion of oxygen and is a leading cause of water impairment in the United States and Florida (EPA 1996; Hauxwell et al., 2001). Forest ecosystems have key functions that affect water supply and quality, such as filtering, retention, and storage of water in streams, lakes, and aquifers. The filtering function, or retention of excess nutrients, is mainly performed by the vegetation cover and soil microbes (de Groot et al., 2002). These functions buffer aquatic ecosystems against NPS pollution and provide clean water, a service that greatly benefits humans. Urban and agricultural activities as well as forest management practices can result in NPS pollution associated with road-building, logging, and land-clearing activities. Such activities alter the structure and function of forest ecosystems and hence affect the provision of water quality protection services (Farber et al., 2002; MEA 2005). Human actions that change forest ecosystems often reduce the benefits those ecosystems otherwise would provide. Recreational experiences (fishing, swimming, and aesthetic values), pollution-mitigating services (waste decomposition and nutrient cycling), and supporting services (water purification) all may decrease (Dodds et al., 2008). The decision to conserve forestland is an important step toward reducing stress on aquatic ecosystems so that they continue to provide clean water services and maintain the benefits associated with good water quality (Wainger and Mazzotta 2011). To ensure that forests perform their role in maintaining water quality, policies often use various types of forest conservation programs and approaches.

Forest Conservation Programs

The objective of many forest conservation programs is to use management practices that preserve or conserve ecosystem structure and function in forest lands, in mixed land-use areas, and especially in riparian areas. These programs are often implemented using strategies such as land acquisition and conservation easements (Demers and Carter 2011), as well as landowner incentives or assistance programs (Blaine and Smith 2006). Some examples of forest conservation programs include the Florida Forever Program, a lands acquisition program that protects Florida's surface and groundwater quality (www.dep.state.fl.us/lands/fl_forever.htm), and the Florida Forest Stewardship Program, an education program that assists non-industrial private landowners in managing their lands for long-term environmental, economic, and social benefits (www.sfrc.ufl.edu/Extension/florida_forestry_information; Ricci et al., 2010).

Valuing Ecosystem Services Provided by Forests

Valuing the Environment

The public's WTP for programs that improve the environment is often measured using a specific survey method known as contingent valuation (CV). This survey method asks respondents how much they would pay for a water quality protection program with specific characteristics providing for certain benefits such as fishing, swimming, and aesthetic values (Mitchell and Carson 1989; Just et al., 2004). Determining the public's WTP for forest conservation programs gives each program a "value," so the public or policy makers can better weigh the advantages and disadvantages of various types of forest conservation programs and the likelihood that they will assist with the achievement of nutrient pollution reduction objectives (Farber et al., 2002; Condon 2004; Lee et al., 2007). Contingent valuation can also help formulate cost-effective conservation and land-use policies that will help develop conservation programs that provide the greatest possible ecosystem services given fixed budgets.

Previous Studies That Value Water Quality Protection Programs

When reviewing which water quality economic valuation studies were relevant for this analysis we found that few focused exclusively on WTP for protecting relatively unpolluted aquatic systems. Moreover, most studies vaguely described the proposed water protection programs as "environmental programs," leaving us with little understanding about other important program characteristics, such as how the program would be implemented (Greenley et al., 1981; Aiken 1985; Whitehead 1990; Sanders et al., 1990; Holmes et al., 2004; and Petrolia 2011). Only a few studies specify the use of land conservation tools such as land acquisition and conservation easements to produce specific water quality benefits (Condon 2004; Cho et al., 2005; Blaine and Smith 2006). It is therefore important to compare WTP for programs that use specified tools like land acquisition and easements with WTP for programs that do not list tools or use relatively vague descriptors like "environmental programs." A respondent's WTP might be influenced by the amount of information provided on the survey.

Data Collection, Analysis, and Benefit Transfer

We compiled the economic valuation data using a comprehensive literature review of 17 studies that examined WTP for the maintenance or protection of benefits associated with unpolluted aquatic resources; this provided us with 43 WTP observations (Table 1). The literature review included refereed and professional publications, technical reports, and other "grey" literature. All studies in the comprehensive review met the following criteria: 1) valued in-stream fresh water resources were considered to be relatively unpolluted; and 2) contingent valuation methods were used to estimate WTP.

Next, we used a meta-analysis model to determine the statistical relationship among WTP and other study characteristics, such as survey method (e.g., survey type, year of survey, number of people that responded to the survey), socioeconomics (e.g., annual household income), and site attributes (e.g., geographic region, type of water body, geographic scale, type of program implementation strategy). A conceptual model of a meta-analysis can be found in Figure 1. A full description of variable characteristics used in this analysis can be found in Table 2, and the results of the meta-analysis can be found in Table 3.

Finally, we conducted a benefit transfer by adjusting the meta-analysis model based on the characteristics of a new site often referred to as a "policy site" (Boyle et al., 2010). Figure 2 shows a conceptual model of how a meta-analysis can be used to conduct a benefit transfer to the policy site. In our case, the policy sites were four regions in Florida (see Table 4 for a list of Florida counties in each region). The characteristics we adjusted for include average annual household income for each region of Florida, region (southeastern USA), resource (all water bodies), scale (drainage basin), and program (land acquisition/conservation easement program and non-specific environmental program).

Economic Value of Water Quality-Related Forest Conservation Programs

Results of the Meta-Analysis Model

The meta-analysis model found all of the study variables to be significant predictors of WTP, which indicates that this model may be useful in describing public preferences for water protection programs.

Overall, respondents were willing to pay:

  • Increasingly more over the last 35 years to protect water quality, even after accounting for an increase in annual household income.

  • Slightly less to protect water quality in the southeastern United States compared to other regions in the country.

  • Slightly more to protect lakes, wetlands, or all water resources in the study area, compared to just rivers and streams.

  • More for programs that protect water resources within their own drainage basin or watershed.

Less for programs that propose the use of land acquisition or conservation easements compared to programs that do not state how the program would be implemented.

Results of the Benefit Transfer

For programs that used land acquisition or conservation easements to protect all surface water resources within a drainage basin, we estimated that annual household WTP would range from $3.32 in the panhandle to $4.79 in central Florida (Table 5). Total annual WTP would be around $1,714,000 in the Florida Panhandle, $4,162,000 in north Florida, $7,280,000 in central Florida and $3,933,155 in south Florida for a statewide total combined annual value of almost $17 million. Households' annual WTP for non-specific programs or programs that do not use acquisition or easement approaches to protect all water resources was estimated to range from $64.81 per individual household in the Panhandle to $94.01 per individual household in central Florida. Total annual WTP was around $33,418,000 in the Florida Panhandle, $81,565,000 in north Florida, $142,803,000 in central Florida and $77,100,000 in south Florida for a total combined annual value of almost $335 million for the entire state of Florida (Table 5).

Conclusions and Implications

Our economic analysis showed that WTP has increased over the last 35 years, suggesting that the public is willing to pay more every year to protect relatively unpolluted water resources. This result is not unexpected because urban pressures from population growth in Florida and other regions in the United States increase the need for reliably unpolluted water for human populations even as they leave water supplies increasingly vulnerable to harm. The results of this study indicate that policy makers should consider the importance and benefits that are likely provided by existing programs such as Florida Forever and the Florida Forest Stewardship; programs that conserve forests and protect Florida's unpolluted water resources. Related studies describe similar forest conservation programs have resulted in a significant reduction in water pollution (Frank et al., 2012). The results of the meta-analysis highlight some key biophysical (region, resource) and socioeconomic (income) factors that likely influence WTP and may be helpful when formulating policies or developing water-quality-related forest conservation program characteristics. The benefit transfer of total WTP highlights the substantial economic value individuals may place on forest conservation and water quality protection.

Of interest, the analysis also found that WTP was lower for programs that use land acquisition or conservation easements compared to programs that do not state how they will be implemented. Results suggest that public support and WTP for forest conservation programs are likely not independent of program design, which has implications for WTP estimation and reliance on existing studies to inform policy decisions. Additional research is needed to determine whether this sensitivity in WTP is due to information availability (e.g., in the absence of program details, respondents make assumptions about the program), measurement error (e.g., important attributes are omitted from the study), attitudes and beliefs about how forests should be used and who should manage them (e.g., a belief that certain policy strategies represent an inappropriate use of public authority), or other important factors.

Overall, the results of these study can be used to gain a better understanding of the economic benefits of forest-provided ecosystem services, like the protection and maintenance of water quality, and they may be used to conduct a cost/benefit analysis and/or to estimate the total amount of potential funds that could be made available to support a water quality protection program through taxes or fees. The information presented in this publication can also be used to help decision makers understand the priorities of individuals regarding forest conservation and water resource protection strategies.

Literature Cited

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Tables

Table 1. 

Characteristics of valuation studies estimating Willingness to Pay (WTP) for the maintenance or protection of benefits associated with well conserved aquatic resources.

Study

Observation per study.1

Program process

Water body type2

Scale

Valuation methodology

State

Adjusted individual annual WTP values (for a water protection program; in 2010 dollars)

Aiken (1985)

4

Not specified

River and lakes

Statewide

CV-iterative bidding and open ended

Colorado

13.43–31.02

Blaine and Smith (2006)

2

Easement

River/

stream

Region in state

Other

Ohio

7.59–13.18

Blaine et al., (2003)

1

Easement

All water resources

Region in state

CV-Dichotomous choice

Ohio

11.06

Blaine and Lichtkoppler (2004)

1

Easement

Wetland

Region in state

Dichotomous choice

Ohio

17.53

Cho et al., (2005)

2

Easement

All water resources

Region in state

CV-Dichotomous choice

Oregon

4.95–9.85

Condon (1996)

2

Acquisition and Easement

All water resources

Region in state

Attribute based choice experiment

North Carolina

17.07–20.37

Cooksey and Howard (1995)

1

Easement

All water resources

Region in state

Other

New Hampshire

18.60

Giraud et al., (2001)

3

Not specified

River/

stream

Region in state

CV-Dichotomous choice

Colorado

237.77–269.73

Greenly et al., (1981)

5

Not specified

River/

stream

Region in state

CV-Dichotomous choice

Colorado

8.38–59.34

Hanemann et al., (1991)

2

Not specified

Wetland/

estuary

Region in state

CV-Dichotomous choice

California

82.32–139.32

Holmes et al., (2004)

3

Not specified

River/

stream

Specific site

CV-Dichotomous choice

North Carolina

12.74–25.12

Mannesto and Loomis. (1991)

2

Not specified

Wetland/

estuary

Specific site

CV-Payment card

California

29.43–54.24

Petrolia et al., (2011)

2

Not specified

Wetland/

estuary

Region in state

CV-Dichotomous choice

Louisiana

221.11–266.48

Sanders et al., (1990)

4

Not specified

River/

stream

Region in state

CV-open ended

Colorado

14.15–32.08

Shrestha and Alavalapati (2004)

2

Land owner incentives

Lake

Specific site

Other

Florida

14.84–34.92

Sutherland and Walsh (1985)

4

Not specified

River/

stream

Region in state

CV-open ended

Montana

6.05–21.64

Whitehead (1990)

2

Not specified

Wetland/

estuary

Specific site

Other

Kentucky

4.05–8.78

1 Multiple WTP estimates from a single study were available due to in-study variation in such factors as elicitation methods and statistical analysis.

2 Water body type can include: river/stream, lakes, wetlands/estuaries or all water resources combined.

3 All values were adjusted for inflation to the 2010 US dollar value according to the Consumer Price Index.

Table 2. 

Description of meta-analysis variables

Variable Category

Level

Description

Mean (SE)

Willingness to pay (dependent)

Ln_WTP

Natural log of willingness-to-pay to maintain or protect water resources, in 2010 US Dollars

3.01 (0.710)

Survey method

CV_ALL

1 if reference WTP was estimated using a survey instrument, including payment card, dichotomous choice, iterative bidding and attribute based choice experiment; 0 otherwise.

0.772 (0.116)

Survey method

CV_OE

1 if WTP was estimated using an open ended survey instrument; 0 otherwise.

0.166 (0.241)

Year

YR_INDX

Index of year the study was conducted (1970 baseline).

24.67 (6.080)

Weighting

RR_COFF

Weighting variable, calculated as response rate divided by sample size.

0.186 (0.174)

Median household income

INCOME

Median household income of respondents as reported by the original study or calculated from US Census data (2010 dollars).

50,605 (5,074)

Region

SOUTH

1 if the study was conducted in the southern region of the US (Tennessee, North Carolina, South Carolina, Georgia, Alabama, Mississippi, Louisiana, and Florida); 0 otherwise.

0.333 (0.304)

Resource

RIVER

1 if protected resource is a river; 0 otherwise.

0.388 (0.315)

Scale

ST_WD

1 if reference WTP for resource protection is statewide; 0 otherwise.

0.052 (0.007)

Scale

DR_BSN

1 if resource protection is within a drainage basin; 0 otherwise.

0.722 (0.289)

Scale

SGL_SITE

1 if resource protection at a single site; 0 otherwise.

0.221 (0.268)

Program

PRG_AE

1 if the proposed water quality protection program uses acquisition or easement type strategies implemented by a government agency; 0 otherwise.

0.389 (0.315)

Table 3. 

Estimated multiple regression model of water protection valuation function (dependent variable is natural log of annual value per individual).

Variable category

Level 1

Coefficient (SE)

Intercept

Intercept

-0.883 (0.886)

Survey Method

CV_OE

-0.591** (0.220)

Year

YR_INDX

0.091*** (0.012)

Weighting

RR_COFF

0.897** (0.388)

Median household income

INCOME

0.058*** (0.000)

Region

SOUTH

-0.414 (0.259)

Resource

RIVER

-1.072*** (0.209)

Scale

DR_BSN

0.821** (0.340)

Scale

SGL_SITE

-1.294*** (0.415)

Program

PRG_AE

-2.990*** (0.209)

Sample size

 

43

R2 adjusted

0.8847

Standard error

 

0.246

F-statistic (degrees of freedom)

 

28.136* (9)

1Levels within each variable category were systematically compared against a corresponding reference variable to calculate a regression coefficient.

*** Significant at p < 0.01

** Significant at p < 0.05

* Significant at p < 0.10

Table 4. 

List of regions in Florida and counties included in each region.

Region in Florida

Florida Panhandle

North Florida

Central Florida

South Florida

Counties in Each Region

Bay

Calhoun

Escambia

Franklin

Gadsden

Gulf

Hamilton

Holmes

Jackson

Jefferson

Lafayette

Leon

Liberty

Madison

Okaloosa

Santa Rosa

Suwannee

Taylor

Wakulla

Walton

Washington

Alachua

Baker

Bradford

Clay

Columbia

Dixie

Duval

Flagler

Gilchrist

Levy

Marion

Nassau

Putnam

Saint Johns

Union

Volusia

Brevard

Citrus

Hardee

Hernando

Highlands

Hillsborough

Indian River

Lake

Manatee

Okeechobee

Orange

Osceola

Pasco

Pinellas

Polk

Seminole

Sumter

Broward

Charlotte

Collier

DeSoto

Glades

Hendry

Lee

Martin

Miami-Dade

Monroe

Palm Beach

Saint Lucie

Sarasota

Table 5. 

Annual household Willingness to Pay (WTP) values (2010 USD) for two water quality maintenance-protection programs that protect all water resources in the Florida Panhandle, north Florida, central Florida, and south Florida.

 

Program that uses acquisition or easment-type strategies

Nonspecific Program

Region

Households

Annual WTP

Total WTP

Annual WTP

Total WTP

Florida Panhandle

515,617

$3.32

$1,714,034

$64.81

$33,417,694

North Florida

927,333

$4.49

$4,162,010

$87.96

$81,564,757

Central Florida

1,519,000

$4.79

$7,279,996

$94.01

$142,802,599

South Florida

860,905

$4.57

$3,933,155

$89.56

$77,099,751

Footnotes

1. This document is FOR309, one of a series of the School of Forest Resources and Conservation Department, UF/IFAS Extension. Original publication date February 2013. Revised July 2020. Visit the EDIS website at https://edis.ifas.ufl.edu for the currently supported version of this publication. This document was funded in part by Conserved Forest Ecosystems: Outreach and Research, the Florida Forest Service, and the United States Forest Service.
2. Melissa M. Kreye, post-doctoral research associate; Francisco J. Escobedo, former associate professor; Damian C. Adams, assistant professor; Taylor Stein, professor, School of Forest Resources and Conservation; and Tatiana Borisova, assistant professor, Department of Food and Resource Economics; UF/IFAS Extension, Gainesville, FL 32611.