Spatial wildlife-vehicle collision models: a review of current work and its application to transportation mitigation projects.

In addition to posing a serious risk to motorist safety, vehicle collisions with wildlife are a significant threat for many species. Previous spatial modeling has concluded that wildlife-vehicle collisions (WVCs) exhibit clustering on roads, which is attributed to specific landscape and road-related factors. We reviewed twenty-four published manuscripts that used generalized linear models to statistically determine the influence that numerous explanatory predictors have on the location of WVCs.

A comparison of data sets varying in spatial accuracy used to predict the occurrence of wildlife-vehicle collisions.

Wildlife-vehicle collisions (WVCs) pose a significant safety and conservation concern in areas where high-traffic roads are situated adjacent to wildlife habitat. Improving transportation safety, accurately planning highway mitigation, and identifying key habitat linkage areas may all depend on the quality of WVC data collection. Two common approaches to describe the location of WVCs are spatially accurate data derived from global positioning systems (GPS) or vehicle odometer measurements and less accurate road-marker data derived from reference points (e.