Science Inventory

Estimating biotic integrity to capture existence value of freshwater ecosystems


Hill, Ryan A, Chris Moore, J. Doyle, S. Leibowitz, P. Ringold, AND B. Rashleigh. Estimating biotic integrity to capture existence value of freshwater ecosystems. PNAS (PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES). National Academy of Sciences, WASHINGTON, DC, 120(8):e2120259119, (2023).


The US Environmental Protection Agency (EPA) conducts economic analyses as one means to evaluate proposed regulations under the Clean Water Act. Current practice uses a Water Quality Index (WQI) to compare management scenarios to determine potential benefits and costs to society. However, a limitation of the existing WQI is that it focuses solely on human use values and fails to capture benefits that come from nonuse values. A range of research has shown that non-use values can be quite large, so quantifying them can be of critical importance to EPA decision making. In this paper, we describe research to identify an index of biological health (i.e., condition) to act as a companion to the WQI that can help the EPA estimate benefits associated with nonuse values. Using focus groups, we compared two indicators of biological condition that are commonly used by the EPA and states to assess the condition of streams and lakes. The selected indicator was found to be far more interpretable by focus group participants, which is critical to unbiased estimates of benefits. Previous work has shown that the willingness of the public to pay for (or accept) water quality regulations depends on current water quality near them. Interpolated values can help us refine our estimation of nonuse value by accounting for how biological condition varies regionally across the US. Therefore, we report on the development and application of preliminary models to interpolate values of this selected indicator to streams and lakes across the conterminous US. This work makes several contributions towards improving the accuracy and completeness of benefits estimation. First, to our knowledge, this is the first time that indicators of biological condition have been compared in a focus group setting. Our results provide insight into what makes an indicator of biological condition interpretable by the public and will improve forthcoming surveys of the public designed to measure their willingness to pay for improvements in water quality. The identification of an appropriate companion metric to the WQI is also a critical step to improving the completeness of benefits estimation since previous approaches did not account for nonuse values. Finally, this study will improve the way we value nonuse benefits by providing interpolated estimates of current biological condition near survey respondents. This research supports work being conducted in collaboration with economist in the EPA’s National Center for Environmental Economics. It also supports a deliverable under SSWR 1.2.2 - Interpolation and stressor-response analyses that extend the use of NARS data to support regulatory program needs.


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.

Record Details:

Product Published Date:04/24/2023
Record Last Revised:06/05/2023
OMB Category:Other
Record ID: 357992