Mechanistic understanding of human-wildlife conflict through a novel application of dynamic occupancy models.

摘要: Crop and livestock depredation by wildlife is a primary driver of human-wildlife conflict, problem that threatens the coexistence people globally. Understanding mechanisms underlie patterns holds key to mitigating conflicts across time space. However, most studies do not consider imperfect detection reporting conflicts, which may lead incorrect inference regarding its spatiotemporal drivers. We applied dynamic occupancy models elephant crop data from India between 2005 2011 estimate occurrence model underlying dynamics as function covariates while accounting for conflicts. The probability detecting was consistently <1.0 negatively influenced distance roads elevation gradient, averaging 0.08-0.56 periods (distinct agricultural seasons within each year). ranged 0.29 (SE 0.09) 0.96 0.04). sites raided elephants in period t would be + 1 varied with gradient different mean rainfall village density positively forests. Negative effects variation forests best explained 1. With our novel application models, we teased apart drivers factors influence how they are observed, thereby allowing more reliable on observed conflict patterns. found associated increased accessibility availability (e.g., patterns) were dynamics. Such an understanding essential rigorous prediction future critical requirement effective management context increasing interactions.