Predicting locations of moose-vehicle collisions in Sweden.
Animal-vehicle collisions are a serious problem for road planners and biologists concerned with traffic safety, species conservation and animal welfare. In Sweden, vehicle collisions with moose (MVC) are an important safety issue. Police records average approximately 4500 incidents year-1, including 10-15 human fatalities. New mitigation policies require improved knowledge of the factors influencing the spatial distribution of MVC. Three logistic regression models were developed to predict MVC risks on public roads for use in strategic and project-related impact assessment. The models were based on remotely sensed landscape data, road and traffic statistics and estimations of moose density, quantified at 2000 accident and 2000 non-accident control sites in south-central Sweden. Model predictions were validated on 2600 1- km road sections in the county of Örebro, which were classified as either accident or non-accident roads. Model performances were compared using Akaike's information criterion. Traffic volume, vehicle speed and the occurrence of fences were dominant factors determining MVC risks, identifying 72.7% of all accident sites. Within a given road category, however, the amount of and distance to forest cover, density of intersections between forest edges, private roads and the main accident road, and moose abundance indexed by harvest statistics, significantly distinguished between accident and control sites. In combination, road-traffic and landscape parameters produced an overall concordance in 83.6% of the predicted sites and identified 76.1% of all test road sections correctly. Synthesis and applications. The risk of moose-vehicle collisions in Sweden can be predicted from remotely sensed landscape data in combination with road traffic data. Prediction models suggest that reduced vehicle speed in combination with road fencing and increased roadside clearance may provide effective tools for road planners in counteracting MVC. However, effective mitigation will depend on integrated management of the surrounding landscape and moose population, as well as increased responsibility of individual drivers. Remedying animal-vehicle collisions must involve road authorities as much as landowners and the public.