未来气候变化对孑遗植物鹅掌楸地理分布的影响

为了解未来气候波动对鹅掌楸(Liriodendron chinense)潜在适生区的影响,利用最大熵模型(Maxent)和地理信息系统(ArcGIS)软件,结合物种地理分布点信息,对鹅掌楸当前适生区分布进行了模拟和划分,同时预测了2061-2080年间气候变化条件下鹅掌楸的潜在适生分布区变化,进而分析影响鹅掌楸地理分布的主要气候因子。结果表明,Maxent模型预测的准确性较高,受试者工作特征曲线(ROC)的曲线下面积(AUC)均大于0.9。在未来4种不同的气候变化场景下(RCP 2.6、RCP4.5、RCP 6.0和RCP 8.5)鹅掌楸的地理分布发生变化,在RCP 4.5情景下,鹅掌楸适生面积明显增加;RCP 8.5情景下适生面积明显减少,尤其在贵州地区以及贵州、重庆与湖南的交界处。因此,鹅掌楸适生区分布的几何中心不变,而适生面积随着温室气体浓度的增加呈现先增加后减少的趋势。昼夜温差月均值、最湿季降雨和最干季降雨是影响鹅掌楸地理分布的主要气候因子,其累计贡献率达77.1%。

Potential Impacts of Climate Change in Future on the Geographical Distributions of Relic Liriodendron chinense

It is of great significance to quantify the impacts of future climate fluctuation on the potential suitable area of Liriodendron chinense and to analyze the climatic factors affecting its distributions, so that to better protect its genetic resources. The Maxent model and ArcGIS software, combined with geographic distribution data, are used to predict the distribution of current and future (2061-2080) potential suitable areas of L. chinense, the distribution of potential suitable areas of L. chinense under future climate fluctuations, and the main climatic factors affecting the geographical distribution of L. chinense were also discussed. The results showed that Maxent model was a good choice when applying to predict the suitable distribution areas of L. chinense due to its high accuracy, and the area under the curve (AUC) of the working characteristic curve (ROC) of subjects is greater than 0.9. The geographic distribution of L. chinense would change with four potential scenarios of carbon emission (RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5) in future. The suitable area of L. chinense increase significantly under the condition of RCP4.5, which was significantly reduced under the condition of RCP 8.5, especially in Guizhou and the border of Chongqing, Guizhou and Hunan. Therefore, with the increase of greenhouse gas concentration, the suitable distribution area of L. chinense will increase at first and then decrease, while the distribution geographic center will keep unchanged. The three variables of monthly mean diurnal range, precipitation of wettest and driest quarters are the main factors affecting the geographic distribution of L. chinense with the total contribution rate of 77.1%.