Xiang Yangzhou, Yang Qiong, Li Suhang, Liu Ying, Li Yuan, Ren Jun, Yao Jiaxin, Luo Xuqiang, Luo Yang, Yao Bin
School of Geography and Resources, Guizhou Education University, Guiyang 550018, China.
School of Biological Sciences, Guizhou Education University, Guiyang 550018, China.
Plants (Basel). 2025 Aug 15;14(16):2539. doi: 10.3390/plants14162539.
Climate change poses unprecedented challenges to forest ecosystems. , a tree species with significant ecological and economic value in southern China, has been the subject of studies on its distribution pattern and response to climate change. However, research on the distribution pattern of and its response to climate change remains relatively limited. In this study, we developed a MaxEnt model incorporating multiple environmental variables, including climate, topography, soil, vegetation, and human activities, to evaluate model performance, identify key factors influencing the distribution of , and project its potential distribution under various future climate scenarios. Species occurrence data and environmental layers were compiled for China, and model parameters were optimized using the ENMeval package. The results showed that the optimized model achieved an AUC value of 0.956, indicating extremely high predictive accuracy. The four key factors affecting the distribution of were standard deviation of temperature seasonality (Bio4), normalized difference vegetation index (NDVI), mean temperature of driest quarter (Bio9), and annual precipitation (Bio12). Among them, the cumulative contribution rate of climatic factors reached 68.9%, but the influence of NDVI was significantly higher than that of precipitation factors. The current suitable habitat of is mainly concentrated in the southwestern region, covering an area of 179.32 × 10 km, which accounts for 18.68% of China's land area. Under the SSP126 scenario, the suitable habitat area first decreases and then increases in the future, while under the SSP370 and SSP585 scenarios, the suitable habitat area continues to shrink, with significant losses in high-suitability areas. In addition, the centroid of the suitable habitat of shows an overall trend of shifting northwestward. This indicates that is highly sensitive to climate change and its distribution pattern will undergo significant changes in the future. In conclusion, the distribution pattern of shows a significant response to climate change, with particularly prominent losses in high-suitability areas in the future. Therefore, it is recommended to strengthen the protection of high-suitability areas in the southwestern region and consider as an alternative tree species for regions facing warming and drying trends to enhance its climate adaptability.
气候变化给森林生态系统带来了前所未有的挑战。[具体树种名称]是中国南方具有重要生态和经济价值的树种,一直是其分布格局及对气候变化响应研究的对象。然而,关于[具体树种名称]分布格局及其对气候变化响应的研究仍然相对有限。在本研究中,我们开发了一个纳入多个环境变量(包括气候、地形、土壤、植被和人类活动)的MaxEnt模型,以评估模型性能,确定影响[具体树种名称]分布的关键因素,并预测其在各种未来气候情景下的潜在分布。收集了中国的物种出现数据和环境图层,并使用ENMeval软件包对模型参数进行了优化。结果表明,优化后的模型AUC值为0.956,表明预测精度极高。影响[具体树种名称]分布的四个关键因素是温度季节性标准差(Bio4)、归一化植被指数(NDVI)、最干季度平均温度(Bio9)和年降水量(Bio12)。其中,气候因素的累积贡献率达到68.9%,但NDVI的影响明显高于降水因素。[具体树种名称]目前的适宜栖息地主要集中在西南地区,面积为179.32×10平方千米,占中国陆地面积的18.68%。在SSP126情景下,未来适宜栖息地面积先减少后增加,而在SSP370和SSP585情景下,适宜栖息地面积持续缩小,高适宜性区域损失显著。此外,[具体树种名称]适宜栖息地的重心总体呈向西北方向移动的趋势。这表明[具体树种名称]对气候变化高度敏感,其分布格局未来将发生显著变化。总之,[具体树种名称]的分布格局对气候变化有显著响应,未来高适宜性区域损失尤为突出。因此,建议加强对西南地区高适宜性区域的保护,并将[具体树种名称]作为面临变暖和干燥趋势地区的替代树种,以增强其气候适应性。