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Estimating biotic integrity to capture existence value of freshwater ecosystems
The US Environmental Protection Agency (EPA) uses a water quality index (WQI) to estimate benefits of proposed Clean Water Act regulations. The WQI is relevant to human use value, such as recreation, but may not fully capture aspects of nonuse value, such as existence value. Here, we identify an ind...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10161049/ https://www.ncbi.nlm.nih.gov/pubmed/37094141 http://dx.doi.org/10.1073/pnas.2120259119 |
Sumario: | The US Environmental Protection Agency (EPA) uses a water quality index (WQI) to estimate benefits of proposed Clean Water Act regulations. The WQI is relevant to human use value, such as recreation, but may not fully capture aspects of nonuse value, such as existence value. Here, we identify an index of biological integrity to supplement the WQI in a forthcoming national stated preference survey that seeks to capture existence value of streams and lakes more accurately within the conterminous United States (CONUS). We used literature and focus group research to evaluate aquatic indices regularly reported by the EPA’s National Aquatic Resource Surveys. We chose an index that quantifies loss in biodiversity as the observed-to-expected (O/E) ratio of taxonomic composition because focus group participants easily understood its meaning and the environmental changes that would result in incremental improvements. However, available datasets of this index do not provide the spatial coverage to account for how conditions near survey respondents affect their willingness to pay for its improvement. Therefore, we modeled and interpolated the values of this index from sampled sites to 1.1 million stream segments and 297,071 lakes across the CONUS to provide the required coverage. The models explained 13 to 36% of the variation in O/E scores and demonstrate how modeling can provide data at the required density for benefits estimation. We close by discussing future work to improve performance of the models and to link biological condition with water quality and habitat models that will allow us to forecast changes resulting from regulatory options. |
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