Conflicts and collisions with an endangered carnivore: Landscape drivers and spatial risk pattern

Human–wildlife conflicts and anthropogenic mortality are expected to increase with the continuous encroachment on natural habitats within and around protected areas, yet the processes governing these risks remain poorly understood. We investigated the spatiotemporal dynamics and drivers of two distinct processes involving the endangered Florida panther (Puma concolor coryi; hereafter, panther): (1) direct human–panther interactions and livestock depredation (hereafter, conflicts), and (2) vehicle collisions (hereafter, collisions). Using long-term data collected between 2006 and 2022 within the panther's breeding range in Southwest Florida, USA, we applied dynamic occupancy models to estimate probabilities of occurrence, colonization, and extinction of conflicts and collisions while accounting for imperfect detection. A total of 277 conflicts and 239 collisions were recorded during the study period. Occurrence probabilities for both conflicts and collisions increased during the early years of the study and subsequently stabilized. Landscape configuration consistently showed strong associations with both processes. Conflicts were more likely in areas with fragmented but closely spaced habitat patches, whereas collisions were more likely along road segments characterized by connected landscapes with low resistance to panther movement. In contrast, areas that showed greater distances between habitat patches and increased proportions of protected area were associated with lower probabilities of conflict or collision persistence over time. A predictive map was created to highlight areas with high probability of conflict and road segments with high probability of collision in Southwest Florida, USA. Identifying areas with elevated risk can inform targeted mitigation strategies, including habitat management, wildlife crossings, and outreach efforts, and further support long-term coexistence between humans and large carnivore populations.