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Article Abstract

Climate change can significantly impact the ecological suitability and diversity of species. , a critically endangered species in China, requires a thorough understanding of its habitat distribution and the environmental factors that affect it in the context of climate change. The Maxent algorithm was used to examine the key factors influencing the distribution of in China, using data from 127 species occurrences and environmental variables from the Last Interglacial (LIG), Last Glacial Maximum (LGM), Mid-Holocene (MH), current, and future scenarios. The Maxent model was optimized utilizing the R package ENMeval, providing the most accurate predictions for suitable habitats across various scenarios. Results show that suitable regions for encompass approximately 15.02% (14.42 × 10 km) of China, predominantly on the Qinghai-Tibetan Plateau. The mean UV-B of the highest month (UVB3: 39.7%), elevation (elev: 28.7%), and the warmest season of precipitation (Bio18: 17.4%) are the major limiting factors for suitable habitat. The optimal species distribution ranges are identified as > 7500 J m day for UVB3, 2700-5600 m for elev, and 150-480 mm for Bio18. Predictions for the historical climate indicate the presence of refugia at the junction of Sichuan, Tibet, and Qinghai. The MH predictions show an increase in climatic suitability for compared to the LIG and LGM, with an expansion of suitable areas westward. Future climate change scenarios indicate that the potential suitable habitat for is expected to increase with increasing radiative forcing, with higher latitude regions becoming new marginally suitable habitats. However, predicted environmental changes in western Tibet may drive the loss of highly suitable habitats in the future. These findings enhance our understanding of how environmental factors impact the habitat suitability of and provide valuable insights for developing effective management and conservation strategies for this important species.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11532267PMC
http://dx.doi.org/10.1002/ece3.70503DOI Listing

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