Accounting for geographic variation in species-habitat associations during habitat suitability modeling

Range-wide species conservation efforts are facilitated by spatially explicit estimates of habitat suitability. However, species-environment relationships often vary geographically and models assuming geographically constant relationships may result in misleading inferences. We present the first range-wide habitat suitability model (HSM) for the federally threatened eastern indigo snake (Drymarchon couperi) as a case study illustrating an approach to account for known latitudinal variation in habitat associations. Specifically, we modeled habitat suitability using interactive relationships between minimum winter temperature and several a priori environmental covariates and compared our results to those from models assuming geographically constant relationships. We found that multi-scale models including interactive effects with winter temperature outperformed single-scale models and models not including interactive effects with winter temperature. Our top-ranked model had suitable range-wide predictive performance and identified numerous large (i.e., ≥1000 ha) potential habitat patches throughout the indigo snake range. Predictive performance was greatest in southern Georgia and northern Florida likely reflecting more restrictive indigo snake habitat associations in these regions. This study illustrates how modeling interactive effects between temperature and environmental covariates can improve the performance of HSMs across geographically varying environmental gradients.