Document Type : Research Paper
Authors
1 Department of Soil science, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran
2 Department of Reclamation of Arid and Mountainous Region, Faculty of Natural Resources, University of Tehran, Karaj, Iran
Abstract
Wild sheep (Ovis orientalis) represent a critical component of wildlife biodiversity in Iran, categorized as Vulnerable (VU) on the IUCN Red List. This species plays a crucial role in the integrity of rangeland ecosystems and contributes to the maintenance of ecological balance within their habitats. Variations in land characteristics including climate, topography, soil, vegetation, hydrological factors and land use, result in the delineation of distinct land suitability classifications for this species. The present study was undertaken through a longitudinal observation of wild sheep behavior over a decade, with the objective of identifying the paramount factors impacting habitat suitability for wild sheep and generating a habitat suitability map employing machine learning algorithms alongside the Analytical Hierarchy Process (AHP) within Khabr National Park. The findings indicated that the region possesses relatively high suitability for this species; Elevation, slope, vegetation cover, and proximity to water resources were as the most important factors affecting the land suitability for wild sheep. The validation of the results through the kappa coefficient and the overall accuracy index demonstrates a high level of precision in the findings, thereby emphasizing the significance of employing machine learning models integrated AHP in land suitability evaluation studies and aiding management in understanding the species’ ecological requirements while also identifying areas of conservation priority
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