Identifying human-caused mortality hotspots to inform human-wildlife conflict mitigation

Abstract

Humans are responsible for over a quarter of all wildlife mortality events across the globe. The pressure this puts on wildlife populations contributes to the decline of many at-risk species. To minimize human-caused mortality and reverse population declines in species across the world, we first need to know where these events are happening or likely to occur since managers and public agencies often have limited resources to devote to a problem. As such, our objective was to develop a modeling approach to delineate human-caused wildlife mortality hotspots in regions with limited data. We used internet search engines and national media to collect data on brown bear ( Ursus arctos ) mortality events in Iran from 2004 to 2019. We then developed a spatially-explicit Maximum Entropy (MaxEnt) model using anthropogenic and environmental variables to predict the probability of human-caused brown bear mortality. We were able to delineate 7000 km 2 as human-caused mortality hotspots, along with the geographical locations of those hotspots. This provides information that can help identify where critical conflict mitigation efforts need to be implemented to reduce the potential for human-caused wildlife mortality. However, more targeted studies such as surveys of local people will be needed inside hotspots identified with this methodology to assess the attitudes of humans toward different wildlife species, informing the specific mitigation actions that will need to be made. Finally, we suggest that media data can be used to identify these hotspots in regions where systematic data is lacking.