Spatiotemporal Distribution of Black Bear–Human Conflicts in Colorado, USA

Management and conservation of large carnivores increasingly includes conflicts with humans. Consequently, a greater understanding of spatiotemporal trends of conflicts is needed to efficiently allocate resources and apply targeted management. Therefore, we examined spatial and temporal distribution of American black bear (Ursus americanus; hereafter, bear)–human conflicts in Colorado, USA, related to 3 conflict types (agriculture operations, human development, and road kills). We used the Getis–Ord spatial clustering statistic to describe location and assess magnitude of bear–human conflicts in Colorado during 1986–2003 and investigated temporal trends of bear–human conflicts by type. Bear–human conflicts showed distinct spatial clustering by type, and areas of high clustering overlapped conflict types. Clustering for agriculture operations conflicts had the largest overall value and overlapped counties with high sheep production. Both human development and road-kill conflict clusters were high in areas of high-quality oak (Quercus spp.)–shrub habitat in the central and southern portions of Colorado's Front Range region and near the city of Durango in southwestern Colorado. Bear–human conflicts varied by year and type but overall increased during the 18 years. Summed across years, most conflicts were related to agriculture (32%), followed by road kills (27%) and human development (24%). The greatest proportion of agriculture operations–related conflicts (76%), human development–related conflicts (36%), and road kills (47%) occurred in 1988, 1999, and 2003, respectively. Considering that bear–human conflicts in Colorado increased over time and will likely continue to increase, we suggest wildlife managers improve data collection by obtaining detailed location data, categorizing conflict types uniformly, and applying conflict regulations consistently to strengthen inference of similar analyses. We also suggest that managers target efforts to mitigate damage by focusing on areas with high clustering of conflicts.