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

Abstract

The ratio of the number of observed taxa to that expected to occur in the absence of human-caused stress (OIE) is an intuitive and ecologically meaningful measure of biological integrity. We examined how OIE 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 mod- els 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 0 and E based on all taxa with probabilities of capture (Pj) > 0; the other calculated 0 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 OIE values differed among unimpaired reference sites and potentially impaired test sites, and (3) the degree to which test site OIE values were correlated with independent measures of watershed alteration. Predictions of species models were more accurate than those of family models, and pre- dictions of the PC ? 0.5 species model were more robust than predictions of the PC > 0 model. OIE 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.