DEVELOPMENT AND EVALUATION OF PREDICTIVE MODELS FOR MEASURING THE BIOLOGICAL INTEGRITY OF STREAMS

Authors

  • Charles P. Hawkins,

    1. Department of Fisheries and Wildlife, Watershed Science Unit, and Ecology Center, Utah State University, Logan, Utah 84322-5210 USA
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  • Richard H. Norris,

    1. Cooperative Research Centre for Freshwater Ecology, University of Canberra, ACT, 2616 Australia
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  • James N. Hogue,

    1. Department of Fisheries and Wildlife, Watershed Science Unit, and Ecology Center, Utah State University, Logan, Utah 84322-5210 USA
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    • Present address: Department of Biology, California State University, Northridge, California 91330-8303 USA.

  • Jack W. Feminella

    1. Department of Fisheries and Wildlife, Watershed Science Unit, and Ecology Center, Utah State University, Logan, Utah 84322-5210 USA
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    • Present address: Department of Zoology and Wildlife Science, Auburn University, Auburn, Alabama 36849-5414 USA.


Abstract

The ratio of the number of observed taxa to that expected to occur in the absence of human-caused stress (O/E) is an intuitive and ecologically meaningful measure of biological integrity. We examined how O/E ratios derived from stream invertebrate data varied among 234 unimpaired reference sites and 254 test sites potentially impaired by past logging. Data were collected from streams in three montane ecoregions in California. Two sets of River Invertebrate Prediction and Classification System (RIVPACS) predictive models were built: one set of models was based on near-species taxonomic resolution; the other was based on family identifications. Two models were built for each level of taxonomic resolution: one calculated O and E based on all taxa with probabilities of capture (Pc) > 0; the other calculated O and E based on only those taxa with Pc ≥ 0.5. Evaluations of the performance of each model were based on three criteria: (1) how well models predicted the taxa found at unimpaired sites, (2) the degree to which O/E values differed among unimpaired reference sites and potentially impaired test sites, and (3) the degree to which test site O/E values were correlated with independent measures of watershed alteration. Predictions of species models were more accurate than those of family models, and predictions of the Pc ≥ 0.5 species model were more robust than predictions of the Pc ≥ 0 model. O/E values derived from both species models were related to land use variables, but only assessments based on the Pc ≥ 0.5 model were insensitive to naturally occurring differences among streams, ecoregions, and years.

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