Abstract:
In landscapes around the world, humans and wildlife are mutually adapting to each other, creating dynamic feedbacks that, if overlooked, limit the effectiveness of conservation policies. Mechanistic social-ecological systems (SES) modeling has a high potential to overcome this limitation. To illustrate the utility of mechanistic SES modeling to wildlife conservation, I present findings from two interrelated agent-based models of human-wildlife interactions. The first model investigates the effects of human disturbance (prey depletion, road infrastructure) on the globally endangered tiger (Panthera tigris) in an isolated protected area in Nepal. The second model investigates human-wildlife conflict, such as crop raiding and livestock depredation, along a simulated interface of wild and agricultural lands. Unanticipated model outcomes provide crucial insights on ways to improve conservation strategies in shared landscapes. By simulating both ecological processes and human decision making, multi-model approaches foster transferability of gained insights to other contexts and case studies that prevail in the Anthropocene.