| Grizzly bear (Ursus arctos) deaths in the US tend to be concentrated on the periphery of core habitats. These deaths were often preceded by conflicts with humans. Management removals of “nuisance” and or habituated grizzly bears are a leading cause of death in many populations. This exploratory study focuses on the conditions that lead to human-grizzly bear conflicts on private lands near core habitat. I examined spatial associations among reported human-grizzly bear conflicts during 1986–2001, landscape features, and agricultural-attractants in north-central Montana. I surveyed 61 of a possible 64 active livestock related land users and I used geographic information system (GIS) techniques to collect information on cattle and sheep pasture locations, seasons of use, and bone yard (carcass dumps) and beehive locations. I used GIS spatial analyses, univariate tests, and logistic regression models to explore the associations among conflicts, landscape features, and attractants.; A majority (75%) of conflicts were found in distinct seasonal conflict hotspots. Conflict hotspots with spatial overlap were associated with riparian vegetation, bone yards, and beehives in close proximity to one another and accounted for 62% of all conflicts. Consistently available seasonal attractants in overlapping hotspots such as calving areas, sheep lambing areas and spring, summer, and fall sheep and cattle pastures appear to perpetuate the occurrence of conflicts. I found that lambing areas and spring and summer sheep pastures were strongly associated with conflict locations as were cattle calving areas, spring cow/calf pastures, fall pastures, and bone yards. Logistic regression modeling revealed that the presence of riparian vegetation within a 1.6 km search radius strongly influenced the likelihood of conflict. After controlling for riparian vegetation, I found that unmanaged bone yards, unfenced and fenced beehives, all increased the odds of conflict. For every 1 km moved away from spring, summer, and fall sheep and cattle pastures, the odds of conflict decreased. The model confirmed the existence of conflict hotspots and illustrated that a collection of attractants beyond the effects of riparian vegetation were associated with conflicts. Contour probability plots of logistic regression models showed good predictive capacity. We discuss these findings and offer management recommendations. |
