A GIS-based analysis of wildlife vehicle collisions in the Chignecto Isthmus

Abstract

This study analyzed the geospatial clustering of wildlife-vehicle collisions (WVCs) on major roadways in the Chignecto Isthmus, with a focus on identifying important parameters influencing collision hotspots. The Chignecto Isthmus represents a major corridor for the movement of animals and people alike, with a well-documented pattern of wildlife-vehicle collisions, but many unanswered collisions about specific factors during WVCs remain. Ripley’s K analysis was used to determine the scale at which collision clusters occur. This analysis found a scale of 14km across five mobility-based functional groups, these were defined as Birds, Amphibians and Reptiles, Carnivores, Ungulates, and Small-Medium Vertebrates (SMV). The road parameters defined using GIS analysis included traffic volume and driver visibility, while land classification contained Agriculture, Forest, Urban, and Wetland/Water categories. There was insufficient data to test Amphibians and Reptiles, and Carnivores but generalized linear mixed modelling revealed that Ungulates were significantly predicted by topographic driver visibility, SMV by traffic volume and forest land classification, and birds by all land classification types except Water/Wetland. This paper has implications for the protection of the animal movement passages and habitat in the Chignecto Isthmus though increased species-specific management styles and future research may be required in this region. It is suggested that road ecology predictive models continue to use animal, road, and roadside parameters to help prioritize areas in need of collision mitigation.