Global climate change exerts profound impacts on biodiversity and species distributions, potentially leading to habitat contraction and species extinction. As an endemic near‐threatened species designated under China's National Class II Protected Wildlife, the tufted deer ( Elaphodus cephalophus ) lacks comprehensive predictions regarding its future distribution under climate change. This study employs an optimized MaxEnt model integrated with 19 climatic variables and environmental factors (topography, vegetation, and anthropogenic disturbances) to systematically predict the species' potential habitat distribution across China. Through parameter screening of 248 combinations using the Kuenm package, the optimal model configuration achieved exceptional predictive accuracy (AUC = 0.977 ± 0.002). Key findings include: (1) Current suitable habitats span 145.98 × 10 ⁴ km ² , predominantly clustered in the Sichuan‐Guizhou‐Yunnan mountainous regions and the Qinling‐Daba‐Wuling ranges; (2) Annual precipitation, elevation, slope, temperature annual range, NDVI, and temperature seasonality emerged as the variables that performed best in predicting habitat suitability for tufted deer; (3) Projected habitat areas under future climate scenarios will contract by 21.8%–28.4%, with shrinkage concentrated in eastern low‐elevation zones and expansion toward the eastern Qinghai‐Tibet Plateau; (4) Habitat centroids exhibit significant westward shifts, reaching 141.8 km under SSP585 (2090s). This study provided theoretical foundations for conserving E. cephalophus genetic resources and climate‐adaptive management, emphasizing the urgency to prioritize ecological corridor construction in western Sichuan‐southeastern Tibet.

The forest musk deer (Moschus berezovskii) is a national Class I protected wild animal in China, and the IUCN Red list classifies it as globally endangered. It has significant value in traditional Chinese medicine and spices. However, wild M. berezovskii has faced a severe population decline due to human hunting, habitat loss, and fragmentation. Thus, studying its population size and distribution pattern is of great importance to develop effective conservation measures. Here, we determined the optimal MaxEnt model and used stratified sampling and the fecal pile counting method to predict the population size and potential habitat distribution of wild M. berezovskii in Chongqing using 133 species distribution points and 28 environmental variables. The results were as follows: (1) When the optimal model parameters were RM = 3.5 and FC = LQHPT, it had high model prediction accuracy (AUC = 0.909 ± 0.010, TSS = 0.663). (2) Under various climatic, topographic, vegetation, and anthropogenic disturbance scenarios, M. berezovskii was primarily distributed in northern, eastern, southwestern regions of Chongqing, covering an area of approximately 5562.80 km². (3) The key environmental factors affecting the potential habitat distribution of M. berezovskii were elevation (36.5%), normalized difference vegetation index (NDVI, 16.6%), slope (11.8%), and land-use type (7.6%), whereas climate and anthropogenic disturbance factors had relatively little influence. (4) A population estimation for M. berezovskii identified approximately 928 ± 109 individuals in Chongqing. We recommend prioritizing the preservation of high-altitude habitats and native vegetation to mitigate human interference and minimize road damage. In summary, our results can enhance the understanding of M. berezovskii distribution and provide a basis for effective conservation and management initiatives.