Landscape-level models of potential habitat for Sonoran pronghorn

A population of endangered Sonoran pronghorn (Antilocapra americana sonoriensis) exists in the United States, and 2 populations exist in Mexico. Because of the vulnerability of small, remnant populations of this subspecies to stochastic events, an important aspect of recovery planning is identifying suitable areas for establishment of new populations. To support translocation efforts, we developed landscape-level Classification and Regression Tree (CART) and logistic regression models of potential Sonoran pronghorn habitat in southwestern Arizona through a 2-part modeling process. First, we used approximately half of Sonoran pronghorn locations (total n=3,219, collected from 1994 to 2002 from radiocollared animals in the United States) and unused points (total n=3,142, randomly generated in areas within the range of Sonoran pronghorn below 21% slope, but > 1.6 km from pronghorn locations) to create habitat models from 5 explanatory variables (i.e., slope, aspect, biome, distance to wash, and soil category). We validated models with the second half of pronghorn and unused points. Both models determined whether areas would or would not be used by Sonoran pronghorn based upon values of explanatory variables at Sonoran pronghorn locations and unused points. The CART model correctly identified 63% of pronghorn locations and 65% of unused points. The logistic regression model correctly identified 57% of pronghorn locations and 62% of unused points. Second, we created a predictive Geographic Information System (GIS) map of Sonoran pronghorn habitat and applied it to the evaluation area. Both models identified > 12,000 km(2) of potential habitat for Sonoran pronghorn on the evaluation area. Our models are a first step toward identifying potential translocation sites for Sonoran pronghorn. Potential translocation sites should be further evaluated with respect to habitat factors not included in our models, including barriers to pronghorn movements, water supplies, and forage resources.