Wang Huiming, Huang Bin, Xu Lei, Chen Ting
Sino-Pakistan International Center on Traditional Chinese Medicine, School of Pharmaceutical Sciences, Hunan University of Medicine, Huaihua 418000, China.
The First School of Clinical Medicine, Yunnan University of Chinese Medicine, Kunming 650500, China.
Biology (Basel). 2025 Aug 1;14(8):972. doi: 10.3390/biology14080972.
W. T. Wang, commonly known as Yanhusuo, is an important and rare medicinal plant resource in China. Its habitat integrity is facing severe challenges due to climate change and human activities. Establishing an integrative quality zoning system for this species is of significant practical importance for resource conservation and adaptive management. This study integrates multiple data sources, including 121 valid distribution points, 37 environmental factors, future climate scenarios (SSP126 and SSP585 pathways for the 2050s and 2090s), and measured content of tetrahydropalmatine (THP) from 22 sampling sites. A predictive framework for habitat suitability and spatial distribution of effective components was constructed using a multi-model coupling approach (MaxEnt, ArcGIS spatial analysis, and co-kriging method). The results indicate that the MaxEnt model exhibits high prediction accuracy (AUC > 0.9), with the dominant environmental factors being the precipitation of the wettest quarter (404.8654.5 mm) and the annual average temperature (11.817.4 °C). Under current climatic conditions, areas of high suitability are concentrated in parts of Central and Eastern China, including the Sichuan Basin, the middle-lower Yangtze plains, and coastal areas of Shandong and Liaoning. In future climate scenarios, the center of suitable areas is predicted to shift northwestward. The content of THP is significantly correlated with the mean diurnal temperature range, temperature seasonality, and the mean temperature of the wettest quarter ( < 0.01). A comprehensive assessment identifies the Yangtze River Delta region, Central China, and parts of the Loess Plateau as the optimal integrative quality zones. This research provides a scientific basis and decision-making support for the sustainable utilization of and other rare medicinal plants in China.
延胡索，通常被称为元胡，是中国一种重要且稀有的药用植物资源。由于气候变化和人类活动，其栖息地完整性正面临严峻挑战。建立该物种的综合质量分区系统对于资源保护和适应性管理具有重要的现实意义。本研究整合了多个数据源，包括121个有效分布点、37个环境因子、未来气候情景（2050年代和2090年代的SSP126和SSP585路径）以及22个采样点的延胡索乙素（THP）实测含量。采用多模型耦合方法（MaxEnt、ArcGIS空间分析和协同克里金法）构建了栖息地适宜性和有效成分空间分布的预测框架。结果表明，MaxEnt模型具有较高的预测精度（AUC>0.9），主要环境因子为最湿润季度降水量（404.8654.5毫米）和年平均温度（11.817.4℃）。在当前气候条件下，高适生区集中在中国中部和东部部分地区，包括四川盆地、长江中下游平原以及山东和辽宁沿海地区。在未来气候情景下，适宜区域中心预计将向西北方向移动。THP含量与日平均温度范围、温度季节性以及最湿润季度平均温度显著相关（<0.01）。综合评估确定长江三角洲地区、中国中部和黄土高原部分地区为最佳综合质量区。本研究为中国延胡索及其他珍稀药用植物的可持续利用提供了科学依据和决策支持。
