PS 23-60 - Using participatory modeling and fuzzy logic cognitive mapping to understand the human – tiger conflict

Abstract: Human-wildlife conflict (HWC) has been increasing globally, posing a threat to food security, conservation, and sustainable development. Moving forward from conflicts to coexistence require understanding the drivers of HWC from the stakeholders involved, including their traditional ecological knowledge. Ecological factors driving HWC has been widely accepted, but multiple other drivers may exist and important to understand for effective management. To address this research gap, our goal is to evaluate human-tiger conflicts (HTCs) in and around Pilibhit Tiger Reserve, India. HTCs in India are an ideal case study for understanding multiple drivers of HWC. Increasing tiger population due to successful conservation and increasing human population create conditions for conflict due to sharing of limited space and resources. We hypothesize that villages around Tiger Reserve understand the complexity of HTC and should be relatively homogenous in their understanding of HTC. To test our hypothesis, we focused on the Pilibhit Tiger Reserve, created in 2014, in Uttar Pradesh which is the most populous state of India. With 70 recorded human deaths, Pilibhit Tiger Reserve is an ideal place to study HTCs. We conducted participatory modeling exercises in 14 villages located around the reserve during summer of 2022 in which villagers collectively described factors related to tiger conflicts and their interrelationships. We constructed and analyzed fuzzy cognitive maps using Mental Modeler software to understand the drivers and the interrelationship between drivers of HTC. The results show that HTC are driven not only by ecological drivers but social, economic, psychological, and ecological factors, and their interrelationships exhibiting complexity in mental models. However, contrary to our hypothesis, there is heterogeneity in these mental models across villages. This is interesting as these villages are in similar geographical surroundings experiencing similar HTC. This heterogeneity can be explained in terms of demographics but also traditional knowledge of the local communities which has not been captured in research so far. Overall, our results demonstrate that managing HWC is not only about addressing the ecological drivers but mitigation strategies that need to target these varied drivers and their interchanges. Incorporating the local stakeholders’ opinions and knowledge in policy making can create strategies that are more effective compared to current strategies, at mitigating HWC and promoting coexistence.