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Application of Species Distribution Models (SDMs) and corridor mapping for conservation of an Endangered charismatic mammal: brown bear (Ursus arctos) in Iran
  • Farnoosh Kouchali,
  • Bagher Nezami,
  • Masoud Yousefi
Farnoosh Kouchali
Natural Environment and Biodiversity, Collage of Environment
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Bagher Nezami
Research Center for Environment and Sustainable Development

Corresponding Author:[email protected]

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Masoud Yousefi
Damghan University
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Abstract

The brown bear (Ursus arctos) is the largest terrestrial carnivore in Iran with a rapidly shrinking range. In this study, we assembled the most comprehensive and up-to-date distribution dataset of brown bears in Iran. We applied Species Distribution Models (SDMs)and corridor mapping to identify this charismatic mammal’s suitable habitats and its corridors across the Zagros and Alborz mountains to ensure this Endangered charismatic large carnivore in Iran. We also estimated protected areas coverage for the species’ suitable habitats. Our data confirmed the presence of the species in 22 of 31 provinces of the country. The total suitable area for the species is 347,728 km2. We showed that significant parts of the suitable areas, 77%, of the brown bear’s suitable habitats, are located outside of the protected areas network. Slope and vegetation were the most important variables shaping the species distribution, and dense forests in the absence of mountain areas are not suitable for the species. Alborz ecoregion in north Iran is the main central habitat for brown bears due to its continuity and integration. The data showed that 93.2% of the Alborz mountains in the north are composed of suitable habitats, however, only 6.4% of this area was legally protected. We encourage conservation and regular monitoring of the high-priority habitats and corridors identified in this study to ensure this Endangered and umbrella mammal species’ long-term survival in Iran.
02 Oct 2024Submitted to Ecology and Evolution
04 Nov 2024Submission Checks Completed
04 Nov 2024Assigned to Editor
25 Nov 2024Reviewer(s) Assigned