Gou Minxin, Xu Jie, Zhu Haoxiang, Liao Qianwen, Wang Haiyang, Zhou Xinyao, Guo Qiongshuang
School of Horticulture and Landscape Architecture, Southwest University, Chongqing 400715, China.
School of Resources and Environment, Southwest University, Chongqing 400715, China.
Plants (Basel). 2025 Jun 27;14(13):1966. doi: 10.3390/plants14131966.
This study developed a preliminary screening framework for identifying candidate species potentially resistant to drought and cold conditions, using open access plant specimens and climate data. Based on 969 specimens, a distribution database was constructed to map 35 species in China. Nonparametric variance analysis revealed significant interspecific differences in precipitation of the driest quarter (PDQ) and minimum temperature of the coldest month (MTCM). Using the updated climatic thresholds, nine candidate species each were identified as having drought resistance (PDQ < 60.5 mm) and cold tolerance (MTCM < 0.925 °C). In conclusion, the proposed method integrates geocoded specimen information with climate data, providing preliminary candidate species for future physiological validation, conservation planning, and further botanical research. However, the primary focus on climate data and lack of consideration of non-climatic factors warrant cautious interpretation of the results and comprehensive investigations for validation of the present study results.
本研究利用开放获取的植物标本和气候数据，开发了一个初步筛选框架，用于识别可能对干旱和寒冷条件具有抗性的候选物种。基于969个标本，构建了一个分布数据库，以绘制中国35种物种的分布图。非参数方差分析显示，最干旱季度降水量（PDQ）和最冷月最低温度（MTCM）存在显著的种间差异。利用更新后的气候阈值，分别确定了9种具有抗旱性（PDQ < 60.5毫米）和耐寒性（MTCM < 0.925°C）的候选物种。总之，所提出的方法将地理编码的标本信息与气候数据相结合，为未来的生理验证、保护规划和进一步的植物学研究提供了初步的候选物种。然而，主要关注气候数据且未考虑非气候因素，因此对结果的解释需谨慎，并需进行全面调查以验证本研究结果。
