Predictive Framework Based on GBIF and WorldClim Data for Identifying Drought- and Cold-Tolerant <i>Magnolia</i> Species in China
Minxin Gou | Jie Xu | Haoxiang Zhu | Qianwen Liao | Haiyang Wang | Xinyao Zhou | Qiongshuang Guo
This study developed a preliminary screening framework for identifying candidate <i>Magnolia</i> 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 <i>Magnolia</i> 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.
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