Habitat selection in a recovering bobcat (Lynx rufus) population

Abstract

Understanding habitat selection of top predators is critical to predict their impacts on ecological communities and interactions with humans, particularly in recovering populations. We analyzed habitat selection in a recovering population of bobcats (Lynx rufus) in south-central Indiana using a Random Forest model. We predicted that bobcats would select forest habitat and forest edges but avoid agriculture to maximize encounters with prey species. We also predicted that bobcats would avoid developed areas and roads to minimize potential antagonistic interactions with humans. Results partially supported our predictions and were consistent with bobcats in the early stages of population expansion. Bobcats exhibited elevated use near forest edges, thresholds of avoidance near agriculture, and thresholds of selection for low and intermediate habitat heterogeneity. Bobcats exhibited peak probability of use 1–3 km from major roads, >800 m from minor roads, and <1km from developed areas, suggesting tradeoffs in reward for high-quality hunting areas and mortality risk. Our Random Forest model highlighted complex non-linear patterns and revealed that most shifts in habitat use occurred within 1 km of the edge of each habitat type. These results largely supported previous studies in the Midwest and across North America but also produced refinements of bobcat habitat use in our system, particularly at habitat boundaries. Refined models of habitat selection by carnivores enable improved prediction of the most suitable habitat for recovering populations and provides useful information for conservation.