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

Migration, movements, and survival in a partially migratory elk (Cervus canadensis) population

“…Mortalities from vehicle and train collisions (average annual mortality rate of 0.05) appeared to be much higher than what occurred during the 1982-1996 study (5% of all known elk mortalities; Gibson & Sheets, 1997). Upwards of two thirds of wildlife-vehicle collisions are likely unreported, often due to animals dying off the highway right of way (Lee et al, 2021)-neither of the two elk-vehicle collision mortalities on numbered highways were reported in provincial databases. Wildlife-train collisions within the study area are also likely underreported and may represent a significant source of elk mortality.…”

Identification of Emerging Roadkill Hotspots on Korean Expressways Using Space–Time Cubes

“…Recently, studies on the reliability and accuracy of roadkill data collected to implement appropriate roadkill mitigation measures are being conducted [ 33 , 34 , 35 ]. The potential biases of roadkill data could be due to (1) carcass removal, for example, by scavenging animals or people, (2) detectability, as small road-killed animals are less likely to be observed than are large animals and (3) injury; that is, animals are not immediately killed by the collision but are injured and die some distance, out of sight of the road [ 36 , 37 ]. This could lead to an underreporting of the actual number of deaths.…”

Collision Avoidance Path Planning for Vehicles Combining MPC and CACC Controllers

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