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

Ashoori, A.; Kafash, A.; Rabiei, K.; Hosseini, M.; Abdi, S.; Yousefi, M.

2024-12-03 ecology
10.1101/2024.11.27.625583 bioRxiv
Show abstract

Wildlife-vehicle collisions are an important wildlife conservation challenge, especially for carnivores. As in other countries, vehicle collisions pose a major threat to carnivores in Iran. 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 collisions to model jungle cat-vehicle collision risk in the Hyrcanian forests of northern Iran. We also modeled the jungle cat vehicle collision risk in the study area but by creating 1 km and 5 km buffers around the roads and identified high vehicle collision risk areas within the 1 km and 5 km butters. We used the Maxent model to identify most important predictors of collision risk. Our models showed that areas in west of Golestan province, east of Mazandaran province, and in central parts of Gilan province faced highest vehicle collision risk for the jungle cat in the Hyrcanian forests. Human footprint and slope were the most important predictors of the jungle cat vehicle collision, with 48.3% and 17.2% contribution and with positive and negative correlation respectively. Results of variable importance were similar when modeling area was limited to a 5 km buffer zone around the roads. But when modeling area was limited to a 1 km buffer zone around the roads, slope became insignificant. Collisions more likely occur where vegetation grows immediately adjacent to roads, so clearing a roadside strip would reduce potential collisions. We recommend that high collision-risk areas we identified for jungle cat in the Hyrcanian forests be a focus for future monitoring and conservation planning.

Published in PLOS ONE (predicted rank #2) · training set

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