Spatiotemporal Distribution Shifts of Zelkova schneideriana Under Climate Change: A Biomod2-Driven Modeling Framework

气候变化下榉树时空分布的变化:基于Biomod2模型的建模框架

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Abstract

Zelkova schneideriana (Ulmaceae), an endemic relict species of the Tertiary in China, has experienced a sharp decline in population due to habitat fragmentation, poor natural regeneration, and anthropogenic disturbances. It is currently listed as a category II national key protected wild plant and categorized as Vulnerable by the International Union for Conservation of Nature (IUCN). To explore its response mechanisms to climate change, this study integrates 11 species distribution models (SDMs) to comprehensively predict its suitable habitat distribution patterns. Key environmental variables were identified as Bio06 (minimum temperature of the coldest month, 21.57%), Bio02 (mean diurnal range, 19.81%), Bio17 (precipitation of the driest quarter, 13.52%), Bio15 (precipitation seasonality, 8.32%), Bio07 (temperature annual range, 8.15%), Bio12 (annual precipitation, 6.58%), and elevation (6.57%), collectively contributing approximately 85%. Spatiotemporal analysis revealed that during historical glacial periods, suitable habitats were significantly restricted, and highly suitable zones were absent under extreme climatic conditions, suggesting the presence of potential glacial refugia. Under current climatic conditions, highly suitable habitats have expanded notably. However, under the high-emission scenario (SSP585) in the future, the suitable range is projected to shrink considerably, with a drastic reduction in highly suitable areas. Moreover, the suitability centroid is expected to shift markedly toward higher elevations in the northeast, indicating a potential adaptation strategy of Z. schneideriana toward mountainous regions in Hunan, Hubei, and Chongqing. These findings provide quantitative guidance for the formulation of targeted conservation strategies for Z. schneideriana and offer methodological insights for predicting suitable habitats and managing related relict plant species under the threat of climate change.

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