Estimating observed-to-expected taxonomic richness in streams and lakes to support existence valuation of biological health

The U.S. EPA is striving to quantify the existence value of biological health in the Nation’s streams and lakes through stated preference (SP) surveys. Through focus groups, we concluded that the public understood observed-to-expected taxonomic richness (O/E) better than other candidate indicators of biological health. To quantify how value varies with proximity to resource, we need spatial interpolations of O/E for all perennial streams and lakes within the conterminous US. To make these interpolations, we used random forest to model O/E with data from the National Aquatic Resource Surveys and StreamCat/LakeCat datasets for the Eastern, Plains, and Western ecoregions. Benthic macroinvertebrates (BMI) and plankton were used for streams and lakes, respectively. The models explained 25-30% of the variation in BMI O/E scores (RMSE: 0.25-0.27) and 13-36% in plankton O/E scores (RMSE: 0.22-0.25). Maps of model residuals showed no visual spatial biases, however, there were noticeable differences in predicted values at ecoregion boundaries. To improve model performances, we are exploring modeling O and E separately, using different modeling algorithms, and including new landscape variables. We will also discuss challenges and solutions for combining model interpolations from streams and lakes.

Impact/Purpose

EPA’s National Center for Environmental Economics (NCEE), within the Office of the Administrator, is developing an economic willingness-to-pay study to estimate the value of incremental improvements in biological condition. To extract these values, the NCEE needs estimates of observed-to-expected (O/E) macroinvertebrate and plankton richness in US streams and lakes, respectively. Currently, these O/E estimates only exist for specific US streams and lakes where National Aquatic Resource Surveys (NARS) were sampled by the EPA’s Office of Water and their partners. To assist the NCEE, we performed spatial interpolations to unsampled streams and lakes which resulted in models that explained 13-30% of the variation in NARS O/E values. Achieving models with acceptable accuracies are needed to improve the way we value resources in economic analyses. This presentation will describe the approach and progress we have made to date towards this objective to an audience of aquatic scientists. Additionally, we will describe our next steps to improve the performances of these models and the challenges we expect to encounter. We hope to further the discussion on how these products may be improved upon and discuss challenges with a broad community of aquatic ecologists. This study supports the development of spatial interpolations of aquatic condition to improve economic research being conducted by the NCEE. This work presents progress on an FY21 deliverable under SSWR 1.2.2 (“Empirical models to interpolate benthic macroinvertebrate observed/expected ratios, or other biological indicator(s) of aquatic ecosystem health, from NARS stream and lake condition to HUC12 or HUC8 units over the conterminous US (CONUS) FY21”).

Citation

Doyle, J., Ryan A Hill, S. Leibowitz, P. Ringold, Chris Moore, AND B. Rashleigh. Estimating observed-to-expected taxonomic richness in streams and lakes to support existence valuation of biological health. Annual Meeting of the Society for Freshwater Science, Corvallis, OR, May 23 - 27, 2021.