Modeling vehicle collision risk for the jungle cat in the Hyrcanian forests of Iran: A guide for vehicle collision prevention

Abstract

Wildlife-vehicle collisions are an important wildlife conservation challenge, especially for carnivores. In Iran, such vehicle collisions pose a major threat to carnivores. The jungle cat ( Felis chaus ) is a small carnivore species facing multiple threats, including habitat destruction, land use changes, and particularly vehicle collisions. We collected data on jungle cat vehicle collisions in the Hyrcanian forests of northern Iran to model the jungle cat vehicle collision risk and identified high vehicle collision risk areas within the 1 km and 5 km buffers. To check validity of Maxent results, we additionally carried out a binomial Generalized Linear Model (GLM). Results showed that western Golestan province, eastern Mazandaran province, and central Gilan province as the highest vehicle collision risk for the jungle cat in the Hyrcanian forests. According to the Maxent model, human footprint and slope and based on the GLM model, NDVI and human footprint were the most important predictor of jungle cat vehicle collision risk in the Hyrcanian forests. We recommend to implement roadside vegetation management and wildlife crossings in the high collision-risk areas in the Hyrcanian forests to mitigate road mortality and support conservation planning for jungle cats in Iran.