Zhang Fen-Guo, Liang Furong, Wu Kefan, Xie Liyuan, Zhao Guanghua, Wang Yongji
College of Life Science, Shanxi Engineering Research Center of Microbial Application Technologies, Shanxi Normal University, Taiyuan, Shanxi, China.
Front Plant Sci. 2024 Jul 29;15:1388099. doi: 10.3389/fpls.2024.1388099. eCollection 2024.
Since the 20th century, global climate has been recognized as the most important environmental factor affecting the distribution of plants. () has been in great demand as a medicinal herb and flavoring, but the lack of seed sources has hindered its development. In this study, we utilized the Maxent model combined with Geographic Information System (GIS) to predict the potential habitat of in China based on its geographical distribution and 22 environmental factors. This prediction will serve as a valuable reference for the utilization and conservation of resources.The results indicated that: (1) the Maxent model exhibited high accuracy in predicting the potential habitat area of , with a mean value of the area under the ROC curve (AUC) at 0.879 and a TSS value above 0.6; (2) The five environmental variables with significant effects were bio6 (Min temperature of the coldest month), bio12 (Annual Precipitation), bio17 (Precipitation of Driest Quarter), elevation, and slope, contributing to a cumulative total of 89.6%. Suitable habitats for were identified in provinces such as Yunnan, Guizhou, Guangxi, Sichuan, Hunan, and others. The total area of suitable habitat was projected to increase, with expansion primarily in middle and high latitudes, while areas of decrease were concentrated in lower latitudes. Under future climate change scenarios, the centers of mass of suitable areas for were predicted to shift towards higher latitudes in the 2050s and 2090s, particularly towards the North China Plain and Northeast Plain. Overall, it holds great significance to utilize the Maxent model to predict the development and utilization of germplasm resources in the context of climate change.
自20世纪以来，全球气候被公认为影响植物分布的最重要环境因素。（）作为一种草药和调味品需求量很大，但种子来源的缺乏阻碍了其发展。在本研究中，我们利用最大熵模型（Maxent）结合地理信息系统（GIS），根据其地理分布和22个环境因素预测了（）在中国的潜在栖息地。这一预测将为（）资源的利用和保护提供有价值的参考。结果表明：（1）Maxent模型在预测（）潜在栖息地面积方面表现出较高的准确性，ROC曲线下面积（AUC）的平均值为0.879，TSS值高于0.6；（2）影响显著的五个环境变量分别是生物6（最冷月最低温度）、生物12（年降水量）、生物17（最干燥季度降水量）、海拔和坡度，累计贡献率为89.6%。在云南、贵州、广西、四川、湖南等省份发现了适合（）生长的栖息地。预计适宜栖息地总面积将增加，主要在中高纬度地区扩张，而减少的区域集中在低纬度地区。在未来气候变化情景下，预计（）适宜区域的质心将在2050年代和2090年代向高纬度地区移动，特别是向华北平原和东北平原移动。总体而言，利用Maxent模型预测气候变化背景下（）种质资源的开发利用具有重要意义。
