The economic value of stream restoration

Abstract

[1] The economic value of restoring Deckers Creek in Monongalia and Preston counties of West Virginia was determined from mail, Internet, and personal contact surveys. Multiattribute, choice experiments were conducted and nested logit models were estimated to derive the economic values of full restoration for three attributes of this creek: aquatic life, swimming, and scenic quality. Their relative economic values were that aquatic life > scenic quality % swimming. These economic values imply that respondents had the highest value for aquatic life when fully restoring Deckers Creek to a sustainable fishery rather than a ''put and take'' fishery that cannot sustain fish populations. The welfare improvement estimates for full restoration of all three attributes ranged between $12 and $16 per month per household. Potential stream users (anglers) had the largest welfare gain from restoration, while nonangler respondents had the lowest. When these estimates were aggregated up to the entire watershed population, the benefit from restoration of Deckers Creek was estimated to be about $1.9 million annually. This benefit does not account for any economic values from partial stream restoration. On the basis of log likelihood tests of the nested logit models, two subsamples of the survey population (the general population and stream users) were found to be from the same population. Thus restoration choices by stream users may be representative of the watershed population, although the sample size of stream users was small in this research.

The Value of Forest Conservation for Water Quality Protection

“…Further research is warranted on the influence of program design attributes such as incentives, education programs, and assistance on WTP to protect water quality, and how the WTP for these programs compares to WTP for acquisition and easement strategies, as well as non-specified programs. Unfortunately, there are relatively few valuation studies that focus on the role of forest conservation to reduce pollution [36,39,41] compared to those that focus on WTP to improve water quality in polluted aquatic systems [13,[29][30][31][32][33]. We also see a need for identifying how information about the proposed program type may lead to WTP estimates that are more representative of actual WTP, and whether providing this information can reduce unexplained variation in econometric models of WTP.…”

“…Despite this, there are relatively few studies that adequately describe the forest conservation-water quality link in a valuation context. In the body of valuation literature addressing water quality issues, many studies focus on WTP to improve water quality in already polluted aquatic systems, for example [13,[29][30][31][32][33][34]. Such studies would be appropriate for assessing afforestation efforts (i.e., WTP to improve water quality through increased forest cover), but they are not compatible for assessing conservation efforts (e.g., WTP to prevent reductions in forest cover).…”

Measuring the Economic Impact of Water Quality Initiatives: A Case Study of the Fund for Lake Michigan

“…Additional studies used include Bolitzer and Netusil (2000) and Doss and Taff (1996) which contain helpful insight on property values. Brander, Florax and Vermaat (2006), Collins, Rosenberger and Fletcher (2005), Hanley and Alvarez-Farizo (2003) and Loomis, Kent, Strange, Fausch and Covich (2000) all examine the value of restoration ranging from streams to wetlands. Murray, Sohngen and Pendleton (2001) studies visitor spending based on water quality at the Great Lakes.…”

A framework for predicting impacts on ecosystem services from (sub)organismal responses to chemicals

“…The full list of beneficiaries for these environments also includes municipal drinking water plant operators, wastewater-treatment plant operators, residential property owners, water subsisters, food subsisters, experiencers and viewers, boaters, and "people who care" (existence and option values). References for uses of metrics: [85][86][87][88][89][90][91][92][93].…”