Luo Liangliang, Wang Qian, Li Xiaolan, Xu Delin, Hu Huan
Microbial Resources and Drug Development Key Laboratory of Guizhou Provincial Department of Education, School of Stomatology Zunyi Medical University Zunyi China.
School of Preclinical Medicine Zunyi Medical University Zunyi China.
Ecol Evol. 2025 Aug 19;15(8):e72043. doi: 10.1002/ece3.72043. eCollection 2025 Aug.
We assessed the genetic diversity and population structure of the protected orchid across 18 wild populations in southwestern China. Eight pairs of simple sequence repeat (SSR) molecular markers were employed for its genetic diversity and population structure analyses, while the optimized Maxent model was utilized to predict changes in the habitat distribution under historical conditions and three future climate scenarios (SSP126, SSP245, and SSP585) with 141 natural distribution data and 19 climatic factors. The results revealed an average number of alleles () of 3.549 and an effective number of alleles () of 2.636, with a mean polymorphic information content () of 0.748 across the populations. Moderate genetic diversity was observed (observed heterozygosity, = 0.402; expected heterozygosity, = 0.509), with 73% of the total variation found within populations, while the 02 population in Zhijin Guizhou exhibited relatively high genetic differentiation ( = 0.675, = 0.658). UPGMA clustering, population structure analyses, and principal component analysis identified two primary subgroups within . Among the 19 climate variables analyzed, four temperature-related factors and two precipitation-related factors were identified as key drivers influencing the geographical distribution of . Future projections for the 2050s and 2070s under varying climate scenarios indicate a northward expansion of suitable habitats for . The proportion of suitable habitat area is expected to increase from 288.3450 × 10 km under historical conditions (1970-2000) to 351.9792-405.6077 × 10 km (2050s-2070s). The wild populations in southwestern China and adjacent regions represent valuable germplasm resources with high genetic diversity, offering significant potential for artificial cultivation initiatives. Moreover, predictions of future distribution dynamics provide critical insights to guide the conservation, development, and sustainable utilization of .
我们评估了中国西南地区18个野生种群中受保护兰花的遗传多样性和种群结构。使用了八对简单序列重复（SSR）分子标记进行其遗传多样性和种群结构分析，同时利用优化的Maxent模型，结合141个自然分布数据和19个气候因子，预测历史条件下以及三种未来气候情景（SSP126、SSP245和SSP585）下栖息地分布的变化。结果显示，在这些种群中，平均等位基因数（）为3.549，有效等位基因数（）为2.636，平均多态信息含量（）为0.748。观察到中等程度的遗传多样性（观察杂合度， = 0.402；期望杂合度， = 0.509），73%的总变异存在于种群内，而贵州织金的02种群表现出相对较高的遗传分化（ = 0.675， = 0.658）。UPGMA聚类、种群结构分析和主成分分析确定了该兰花内的两个主要亚组。在分析的19个气候变量中，四个与温度相关的因子和两个与降水相关的因子被确定为影响该兰花地理分布的关键驱动因素。在不同气候情景下对2050年代和2070年代的未来预测表明，该兰花适宜栖息地将向北扩展。适宜栖息地面积比例预计将从历史条件下（1970 - 2000年）的288.3450×10平方公里增加到2050年代至2070年代的351.9792 - 405.6077×10平方公里。中国西南地区及邻近地区的野生兰花种群代表了具有高遗传多样性的宝贵种质资源，为人工栽培计划提供了巨大潜力。此外，未来分布动态的预测为指导该兰花的保护、开发和可持续利用提供了关键见解。
