Developing a correction factor to apply to animal–vehicle collision data for improved road mitigation measures

Abstract Context Road mitigation to reduce animal–vehicle collisions (AVCs) is usually based on analysis of road survey animal carcass data. This used identify sections with high AVC clusters. Large mammals that are struck and die away from a not recorded nor considered in these analyses, reducing our understanding the number AVCs cost–benefit measures. Aims Our aim was develop method calculate correction factor for large mammal data reported through survey. will improve magnitude cost AVCs. Method Citizen scientists carcasses walking surveys along transects parallel highway observations using smartphone application at three sites over 5-year period. These were compared traditional Key result We found many involved are, therefore, surveys. A 2.8 region can be applied account injury bias error Conclusions For mammals, underestimates. To information about where little known, we recommend conducting similar research conventionally collected Implications Identifying by transportation agencies tends focus above-threshold numbers analyses deem necessary. improves estimate accuracy, improving identification appropriate mitigation, and, ultimately, benefitting people wildlife risks