Fuente:
Sustainability - Revista científica (MDPI)
Sustainability, Vol. 18, Pages 1976: Maxent Modeling of Habitat Suitability for Alpine Musk Deer (Moschus chrysogaster) and Blue Sheep (Pseudois nayaur) in the Typical Canyons of the Sanjiangyuan Region
Sustainability doi: 10.3390/su18041976
Authors:
Le Niu
Ping Li
Zhenzhen Hao
Junyong Ma
Habitat degradation and fragmentation driven by climate change and human activities are major threats to wildlife, particularly in the ecologically sensitive Sanjiangyuan region on the Qinghai–Tibet Plateau. Alpine musk deer (Moschus chrysogaster) and blue sheep (Pseudois nayaur), two key ungulate species, face severe habitat challenges due to these environmental pressures. Understanding their habitat requirements and distribution patterns is critical for developing effective conservation strategies. This study applied the Maximum Entropy (MaxEnt) model to predict the habitat suitability of alpine musk deer and blue sheep in the characteristic canyons of the Sanjiangyuan region. Data from 55 infrared camera traps and 26 environmental variables, including climate, topography, land use, and human disturbance, were analyzed. The results indicated that annual mean temperature, altitude, temperature annual range, and distance to water were the most influential factors for both species. The suitable habitats for alpine musk deer and blue sheep were limited, covering only 9.61% and 10.84% of the study area, respectively. These areas were primarily distributed along the main stream of the Yellow River and its primary tributary canyons. The limited availability of high-quality habitats underscores the vulnerability of these species to ongoing habitat degradation and fragmentation. To effectively protect ungulate populations, we suggest continuously monitoring the trends of critical habitats, strengthening the protection of existing habitats, and improving the current conservation systems. The findings provide critical insights for conservation planning and management in the Sanjiangyuan region.
