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Tuesday, May 19, 2009 - 11:15 AM
174
Using mean and quantile regression with broken-stick models to develop stressor – response relationships to assess the potential causes of biological impairment in streams
Michael B. Griffith1, Joel W. Chirhart2, Scott L. Niemela2, and Robert E. Murzyn3. (1) National Center for Environmental Assessment, U.S. Environmental Protection Agency, Office of Research and Development, 26 W. Martin Luther King Drive, Cincinnati, OH 45140, (2) Biological Monitoring Program, Minnesota Pollution Control Agency, 520 Lafayette Road, St. Paul, MN 55155, (3) Environmental Data Management, Minnesota Pollution Control Agency, 520 Lafayette Road, St. Paul, MN 55155
USEPA’s CADDIS approach uses many types of evidence; one type discussed here compares stressors and responses at a site to stressor–response relationships developed from other sites. We developed models for % sand & fines and biotic metrics using Minnesota monitoring data and broken-stick models in mean and quantile (i.e., 90th percentile) regressions with prediction limits. Broken-stick models estimated where the slope changed. If the slope change was not significant, a linear model was tacit. Then, we used the models to assess 12 impaired sites not included in model development. For metrics exhibiting various models along the 90th percentile (e.g., % abundance, intolerant invertebrates; % abundance, clingers), sediment fines were a likely cause at two sites, because the metric was within the quantile prediction limits and % sand & fines was greater than any threshold. At nine sites, the metric was less than the quantile lower prediction limit; other stressors were also likely causes. At one site, where benthic insectivore richness exhibited a threshold, sediment fines were discounted as a likely cause, because % sand & fines were less than the threshold. Thus, we illustrate that field data and a clear inferential process can help identify causes of biotic impairments.
Web Page: causal asssessment, biological impairment, quantile regression