MaxEnt-based evaluation of climate change effects on the habitat suitability of in China.

This study aimed to assess the impact of climate change on the potential distribution of the endangered medicinal plant in China. We sought to identify key bioclimatic variables influencing its distribution, predict current and future suitable habitats, and evaluate shifts in these habitats under different climate scenarios. We constructed a dataset comprising 405 distribution records of and 9 major environmental factors. The MaxEnt model, integrated with GIS software, was employed to predict the potential distribution under current (1970-2000) and future periods (2050s, 2070s, and 2090s). Model optimization was conducted using the ENMeval package to adjust regularization multiplier and feature combination parameters, ensuring enhanced predictive accuracy. The optimized MaxEnt model demonstrated high predictive precision with an AUC value of 0.917. The minimum temperature of the coldest month, mean diurnal range, and annual precipitation were identified as the key environmental variables influencing distribution, with contribution rates of 72.7%, 11.6%, and 4.2%, respectively. The suitable habitat was predicted to expand by 2050s under the SSP1-2.6 scenario but showed a reduction in highly suitable areas under more severe scenarios like SSP5-8.5. Centroid shift analyses indicated a northwestward migration of suitable habitats. These results from this study suggest that climate change poses significant risks to the distribution of , with potential shifts in both the extent and quality of suitable habitats. Our findings highlight the importance of considering climate change projections in conservation planning and underscore the need for adaptive strategies to ensure the sustainability of this medicinally valuable species. The study provides a scientific basis for the conservation and sustainable use of in the context of climate change.