Xiang Yangzhou, Li Yuan, Liu Ying, Yuan Yingying, Li Suhang, Yang Qiong, Zhang Jinxin
School of Geography and Resources Guizhou Education University Guiyang China.
Grasslands and Sustainable Farming, Production Systems Unit Natural Resources Institute Finland Kuopio Finland.
Ecol Evol. 2025 Jun 24;15(6):e71664. doi: 10.1002/ece3.71664. eCollection 2025 Jun.
a regionally endemic medicinal plant in China, is crucial for ecosystems and traditional medicine. This study evaluates climate change impacts on the geographic spread of by employing an optimized MaxEnt model based on 625 valid occurrence points and various climatic variables. The model was refined with ENMeval in R, selecting optimal feature combinations (FC) and regularization multipliers (RM). The model's predictive performance was evaluated via the AUC metric, and the distribution changes were analyzed across three Shared Socioeconomic Pathways (SSPs) spanning the 2050s, 2070s, and 2090s. The findings indicated that the refined MaxEnt model exhibited strong predictive performance, achieving an AUC of 0.904. The min temperature of coldest month (Bio6) and the standard deviation of temperature seasonality (Bio4) were identified as the principal climatic variables affecting the geographic range of , contributing 68.7% and 20.2%, respectively, under current climatic conditions. Within the SSP1-2.6 pathway, the viable habitat zone remained relatively stable, with retention rates of 86.78%, 86.13%, and 82.03% during the decades of the 2050s, 2070s, as well as 2090s. However, in the context of the SSP5-8.5 pathway, the retention rate significantly decreased to 64.77% by the 2090s, indicating greater habitat instability and expansion needs. The research highlights the critical role of thermal variables in shaping 's distribution and emphasizes the need for adaptive conservation strategies targeting stable or expanding habitats to ensure its long-term survival amid climate change.
一种在中国局部地区特有的药用植物，对生态系统和传统医学至关重要。本研究通过基于625个有效分布点和各种气候变量的优化最大熵模型，评估气候变化对该植物地理分布范围的影响。该模型在R语言中使用ENMeval进行优化，选择最佳特征组合（FC）和正则化乘数（RM）。通过AUC指标评估模型的预测性能，并分析了2050年代、2070年代和2090年代三个共享社会经济路径（SSP）下的分布变化。研究结果表明，优化后的最大熵模型表现出很强的预测性能，AUC值达到0.904。最冷月份的最低温度（Bio6）和温度季节性标准差（Bio4）被确定为影响该植物地理分布范围的主要气候变量，在当前气候条件下分别贡献了68.7%和20.2%。在SSP1-2.6路径下，适宜栖息地范围相对稳定，在2050年代、2070年代和2090年代的保留率分别为86.78%、86.13%和82.03%。然而，在SSP5-8.5路径下，到2090年代保留率显著下降至64.77%，表明栖息地稳定性更低且需要扩张。该研究突出了热变量在塑造该植物分布中的关键作用，并强调需要针对稳定或扩张栖息地制定适应性保护策略，以确保其在气候变化中得以长期生存。
