A GIS-Based Expert Systems Predictive Habitat Model for Threatened and Endangered Species: Case Study Using Kentucky Arrow Darter

Abstract

This study presents a Geographic Information Systems (GIS)-based predictive habitat suitability model for the Kentucky arrow darter (Etheostoma spilotum), a fish species of the upper Kentucky River basin that is a candidate for federal listing by the U.S. Fish and Wildlife Service. The model is based on previous work: the development of a similar predictive model for identifying the habitat of the blackside dace, a threatened minnow species of the upper Cumberland River basin in Southeastern Kentucky. The research describes a weighted, rules-based system which incorporates expert knowledge about habitat preferences for the arrow darter. For this model, five habitat factors were identified by experts as essential to modeling the habitat: stream gradient, canopy coverage, land cover, riparian zone width, and stream order. Using a GIS, the five habitat factors were parameterized and combined across the entire Kentucky River basin stream network. Experts evaluated combinations of habitat factors to determine habitat suitability. Using locational modeling statistics, the resulting model was tested against known Kentucky arrow darter occurrences. The analysis demonstrated successful identification of streams where the arrow darter was likely — and unlikely — to exist. Model results could be useful to transportation planners, particularly when determining sensitive landscape that could be impacted by transportation planning processes. This model may help planners save money on habitat mitigation when transportation initiatives take place in known unsuitable arrow darter habitats. A GIS model similar to the one developed in this study may be applicable to other endangered species.