Using animal–vehicle collision data for wildlife population monitoring

Globally, collisions with vehicles result in millions of animal deaths every year, representing a major issue for wildlife conservation and management. Consequently, and importantly, much research has focused on understanding patterns of animal–vehicle collisions with the aim to reduce roadkill of wildlife. However, existing data on animal–vehicle collisions might also represent a novel opportunity to monitor wildlife populations. For this purpose, we compared data of >1.2 million hunter-shot deer and >40,000 deer–vehicle collisions collected over 11 years in Denmark. We show that deer–vehicle collision data can be useful for population monitoring of roe deer (Capreolus capreolus), fallow deer (Dama dama), and red deer (Cervus elaphus). Roe deer was the most numerous species, representing 90% of observations based both on deer–vehicle collisions and on hunting bag statistics. After accounting for factors related to road infrastructure (road length and density, traffic volume), local (municipality) deer–vehicle collisions were highly correlated with hunting bag data for roe and red deer (Pearson's r > 0.7) but not fallow deer, likely due to biases in hunting bags. Moreover, we used deer–vehicle collision data to map spatiotemporal changes in the distribution of fallow and red deer, and demographic changes in all species. Combined, our results suggest that animal–vehicle collision data can be a useful tool to supplement existing methods for monitoring wildlife populations, which will be relevant for the management of these populations. We point to important shortcomings in both animal–vehicle collision and hunting bag data and provide recommendations on how to improve their accuracy in the future, to be applicable for a broader range of species.