Spatially explicit capture–recapture analysis of bobcat (Lynx rufus) density: implications for mesocarnivore monitoring

Abstract

Context Accurate density estimation is crucial for conservation and management of elusive species. Camera-trapping may provide an efficient method for density estimation, particularly when analysed with recently developed spatially explicit capture–recapture (SECR) models. Although camera-traps are employed extensively to estimate large carnivore density, their use for smaller carnivores has been limited. Moreover, while camera-trapping studies are typically conducted at local scales, the utility of analysing larger-scale patterns by combining multiple camera studies remains poorly known. Aims The goal of the present study was to develop a better understanding of the utility of SECR models and camera-trapping for the estimation of density of small carnivores at local and regional scales. Methods Based on data collected from camera-traps, we used SECR to examine density of bobcats (Lynx rufus) at four study sites in north-central Texas. We then combined our density estimates with previous estimates (from multiple methodologies) across the bobcat’s geographic range, and used linear regression to examine drivers of range-wide density patterns. Key results Bobcat densities averaged 13.2 per 100 km2 across all four study sites, and were lowest at the site in the most heavily modified landscape. Bobcat capture probability was positively related to forest cover around camera-trap sites. At the range-wide scale, 53% of the variation in density was explained by just two factors: temperature and longitude. Conclusions Our results demonstrate the utility of camera-traps, combined with SECR, to generate precise density estimates for mesocarnivores, and reveal the negative effects of landscape disturbance on bobcat populations. The associations revealed in our range-wide analysis, despite variability in techniques used to estimate density, demonstrate how a combination of multiple density estimates for a species can be used for large-scale inference. However, improvement in our understanding of biogeographic density patterns for mesocarnivores could be obtained from a greater number of camera-based density estimates across the range of a species, combined with meta-analytic techniques. Implications Camera-trapping and SECR should be more widely applied to generate local density estimates for many small and medium-sized carnivores, where at least a portion of the individuals are identifiable. If such estimates are more widely obtained, meta-analytic techniques could be used to test biogeographic predictions or for large-scale monitoring efforts.