Temporal pattern of moose-vehicle collisions

[Display omitted] •We used GPS-telemetry, road traffic and weather to explain moose-vehicle collisions.•The 303 collisions we analysed took place mainly after sunset and in autumn.•Variation in moose activity over time best predicted temporal pattern in collisions.•Moose presence near roads, traffic, precipitation and fog were also important.•Identifying temporal collision pattern can help in reducing the collision risk. Wildlife-vehicle collisions have become an increasing problem in recent decades as they seriously affect both animals and road users, leading to fatalities, substantial economic losses, and high biodiversity costs. We used GPS tracking of 37 moose, traffic volume, weather conditions, and information on moose-vehicle collisions (MVCs) reported on the Internet to explain the temporal patterns of MVCs in Poland from 2003 to 2019. MVCs peaked in early autumn (September-October). In all seasons, the greatest MVC risk occurred during the few hours after dusk, while in early autumn, MVC risk was also elevated during the hours preceding dawn. Moose activity was the strongest positive predictor of MVCs, but moose presence near roads, traffic volume, fogginess, and lack of precipitation were also positively correlated with MVC risk. We conclude that introducing seasonally adjusted measures (e.g. speed limitations, temporary warning signs) could substantially reduce the number of MVCs.