Abstract
SummaryCollisions of vehicles with wildlife kill and injure animals and are also a risk to vehicle occupants, but preventing these collisions is challenging. Surveys to identify problem areas are expensive and logistically difficult. Computer modeling has identified correlates of collisions, yet these can be difficult for managers to interpret in a way that will help them reduce collision risk. We introduce a novel method to predict collision risk by modeling hazard (presence and movement of vehicles) and exposure (animal presence) across geographic space. To estimate the hazard, we predict relative traffic volume and speed along road segments across southeastern Australia using regression models based on human demographic variables. We model exposure by predicting suitable habitat for our case study species (Eastern Grey Kangaroo Macropus giganteus) based on existing fauna survey records and geographic and climatic variables. Records of reported kangaroo–vehicle collisions are used to investigate how these factors collectively contribute to collision risk. The species occurrence (exposure) model generated plausible predictions across the study area, reducing the null deviance by 30.4%. The vehicle (hazard) models explained 54.7% variance in the traffic volume data and 58.7% in the traffic speed data. Using these as predictors of collision risk explained 23.7% of the deviance in incidence of collisions. Discrimination ability of the model was good when predicting to an independent dataset. The research demonstrates that collision risks can be modeled across geographic space with a conceptual analytical framework using existing sources of data, reducing the need for expensive or time‐consuming field data collection. The framework is novel because it disentangles natural and anthropogenic effects on the likelihood of wildlife–vehicle collisions by representing hazard and exposure with separate, tunable submodels.
Highlights
Roads have well-documented negative ecological impacts (Forman and Alexander 1998; Spellerberg 1998; van der Ree et al 2015), including effects on terrestrial fauna
Ecology and Evolution published by John Wiley & Sons Ltd
Risk of animal collisions can be expressed as a function of exposure and hazard: Ri 1⁄4 a Á Ei Á Hi where Ri is the risk, Ei is the exposure, Hi is the hazard, a is a constant of proportionality, and i represents a modeling unit
Summary
Roads have well-documented negative ecological impacts (Forman and Alexander 1998; Spellerberg 1998; van der Ree et al 2015), including effects on terrestrial fauna. Perhaps the most visible impact is direct mortality through wildlife–vehicle collisions (WVC) – billions of fauna are killed annually around the world (Seiler and Helldin 2006). Such an issue has prompted many road management authorities to routinely collect animal carcasses struck and killed by moving vehicles to reduce visual impacts for road travelers (Huijser et al 2007) and avoid secondary collisions with scavenging wildlife species. The frequency, magnitude, and distribution of WVC have been widely studied Many such studies relate rate of collisions to environmental conditions, anthropogenic variables, and animal biology, behavior, and characteristics.
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call