Abstract

Objective: The study aims at comprehending and mitigating human-animal conflict in the Nilgiris district of Tamil Nadu, where crop damage occurs near forest edges by wildlife such as elephants, wild boars, sloth bears, Indian porcupines, bonnet macaques, and gaurs. Using an agent-based modeling approach, it assesses the potential effect of different mitigation strategies on the pattern of conflict and the amount of crops lost. Materials: The description of the research refers to the use of a spatially explicit agent-based analytic platform developed with NetLogo for the simulation of a 100 km² agro-forest landscape. The system has 500 farmer agents, interacting with multiple wildlife species whose behaviour is modelled on real-life data. The data sources include land use maps from the Forest Survey of India, reports of conflicts from the Tamil Nadu Forest Department, and maps of wildlife corridors. Three scenarios were tested with the simulation: baseline (no management intervention), deterrents (fences, watchtowers), and crop switching (low-risk crops). Result: Simulation results showed 420 crop-raiding events per season in the baseline scenario, reduced to 220 with deterrents, and further to 150 with crop switching. Crop loss occurred in 18% without mitigation, 10% with deterrents, and 6% with crop switching. Crop attractiveness played an important role; bananas and maize had more raids, while tea and lemongrass were less affected. Conflict hotspots were mostly near wildlife corridors, and smaller farms close to forests suffered the most. Sensitivity analysis confirmed that wildlife density, deterrent effectiveness, and crop type strongly influenced outcomes. Conclusion: Interaction with human-wildlife conflict can be treated with agent-based modelling. Within the strategies tested, crop switching helped best to reduce conflicts and crop losses. The study shows that mitigation methods should be tailored to each location and based on behaviour, supporting both conservation and farming.