Management and conservation of aquatic systems require the ability to assess biological conditions and identify changes in biodiversity. Predictive models for fish assemblages were constructed to assess biological condition and changes in biodiversity for streams sampled in the eastern United States as part of the U.S. Geological Survey's National Water Quality Assessment Program. Separate predictive models were developed for northern and southern regions. Reference sites were designated using land cover and local professional judgment. Taxonomic completeness was quantified based on the ratio of the number of observed native fish species expected to occur to the number of expected native fish species. Models for both regions accurately predicted fish species composition at reference sites with relatively high precision and low bias. In general, species that occurred less frequently than expected (decreasers) tended to prefer riffle areas and larger substrates, such as gravel and cobble, whereas increaser species (occurring more frequently than expected) tended to prefer pools, backwater areas, and vegetated and sand substrates. In the north, the percentage of species identified as increasers and the percentage identified as decreasers were equal, whereas in the south nearly two-thirds of the species examined were identified as decreasers. Predictive models of fish species can provide a standardized indicator for consistent assessments of biological condition at varying spatial scales and critical information for an improved understanding of fish species that are potentially at risk of loss with changing water quality conditions.
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Predictive models for fish assemblages in eastern USA streams: implications for assessing biodiversity