The Use of Geographic Information Systems to Model Habitat for Puma concolor cougar in the Northern Blue Ridge of Virginia

Abstract

Geographic Information Systems (GIS) was used to predict suitable habitat for the eastern cougar (Puma concolor cougar) in the Northern Blue Ridge of Virginia. Two areas were studied, a primary area nested inside a secondary area. Objectives were accomplished by relating eastern cougar sighting locations, the dependent variable, to environmental variables considered important to habitat. These variables were elevation, geology, human density, land cover, landform, prey density, roads, and streams/rivers. Logistic regression identified elevation, geology, landform, and distance to the nearest road as significant predictor variables for the primary area, and no variables for the secondary area. The significant variables were fit to the regression equation, resulting in a sighting probability coverage, from which suitable habitat areas were derived and suitability was tested with additional sighting data. The regression equation generated by primary area data was applied to the secondary area and two habitat models were built, one with and one without the roads variable. Chi-square results indicated that three of the five habitat models tested were significantly better than random. The efficacy of predicting habitat suitability based on eastern cougar sighting data was dependent on the scale and quality of these data.