Identifying barriers and pinch-points of large mammal corridors in Iran

Ehsan Rahimi () and Pinliang Dong ()
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Ehsan Rahimi: Shahid Beheshti University
Pinliang Dong: University of North Texas

Journal of Environmental Studies and Sciences, 2023, vol. 13, issue 2, No 5, 285-297

Abstract: Abstract Human modifications of the landscapes have led to species with wide home ranges being trapped within protected areas, disrupting their relationship with species in other protected areas. In this regard, identifying potential corridors that species use to migrate and access other resources can help preserve the species’ survival. Iran, with 246 protected areas, is home to a variety of vertebrates, including large mammals. This study aims to identify the least-cost corridors between core habitat areas of two large mammals of brown bear (Ursus arctos) and Persian leopard (Panthera pardus saxicolor) in Iran, as well as the barriers along these corridors. We also identify areas known as pinch-points or bottlenecks to determine mammalian conservation priorities. For this purpose, after creating a resistance map using species distribution models (SDMs), the Linkage Mapper toolkit was used to model the landscape connectivity. For brown bears, our results showed that the average length of the least-cost corridors in 84 core habitat areas was 74 km. Brown bears have to cross 179 barriers on average to migrate to another region, mostly due to linear infrastructure such as roads. For the Persian leopard, we identified 5 core areas with an average corridor length of 397 km and 36 barriers between them. This study suggests that in addition to determining the least-cost corridors between core habitats, it is necessary to identify the barriers and pinch-points along these corridors. The results of this study offer new insights for protected area managers to better manage these areas.

Keywords: Large mammals; Landscape connectivity; Pinch-points; Barrier analysis; Least-cost modeling; Species distribution models (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s13412-023-00823-y

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