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Statistical Techniques for Determination and Prediction of Fundamental Fish Assemblages of the Mid-Atlantic Highlands
Michael Cyterski, Craig Barber, Rajbir Parmar, Brenda Rashleigh and Kurt Wolfe
U.S. Environmental Protection Agency (USEPA), ORD, Athens, Georgia
A statistical software tool, Stream Fish Community Predictor (SFCP), based on EMAP stream sampling in the mid-Atlantic Highlands, was developed to predict stream fish communities using stream and watershed characteristics. Step one in the tool development was a cluster analysis that characterized observed fish communities to form groups of streams with similar fish species. Twenty-three clusters, each defined by a fundamental fish assemblage, resulted. Step two was a discriminant analysis, which produced a system of equations to predict a stream's fundamental fish assemblage (its cluster) based on characteristics of that stream and its watershed (e.g., stream slope, percent forested area in the watershed, stream bank vegetation, latitude, longitude).
The discriminant equations, when tested using our sample data, correctly predicted a stream's fish assemblage with approximately 35% accuracy. If the user examined the three most probable assemblages for a stream, the accuracy rose to approximately 65% (i.e., 65% of the time one of those three choices was the correct assemblage). Randomly, given three choices, one would only have a 3 in 23 chance of picking the correct assemblage (13%).
The tool will be used to predict fish communities in streams for which basic watershed and stream characteristics are known. This software also allows users to investigate potential impacts of environmental restoration or degradation by altering stream and watershed characteristics, then examining changes in the predicted fish community.
This tool is currently available from the Canaan Valley Institute's website at http://www.canaanvi.org/
Keywords: cluster analysis, discriminant analysis, fish communities, Mid-Atlantic Highlands, watershed
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