A spatial approach to statistical habitat suitability modeling: The Mt. Graham red squirrel case study.

Abstract

Multivariate statistical techniques were applied to the development of habitat suitability models for the Mt. Graham red squirrel, an endangered species. A digital map data base and a geographic information system (GIS) were used to support the analysis and provide input for two logistic multiple regression models. Squirrel presence/absence is the dichotomous dependent variable whose probability the models pretend to predict. Independent variables are a set of environmental factors in the first model, and locational variables in the second case, where a logistic trend surface was developed. Bayesian statistics were then used to integrate the models into a combined model. Potential habitat losses resulting from the development of an astronomical observatory were assessed using the environmental model and are found to represent about 3% of currently available habitat.