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气候变化情境下吴茱萸的潜在适生区分布预测
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Abstract:
吴茱萸是中国传统的中药材，野生资源较少，主要来源于种植，预测吴茱萸的潜在适生区对吴茱萸的栽培和植物的保护具有指导意义。利用吴茱萸在中国的318个地理分布记录，结合14个有效环境因子，应用最大熵模型(MaxEnt)研究影响吴茱萸适宜性分布的生态因子，结合ArcGIS软件预测未来(2041~2060年、2080~2100年)吴茱萸在中国的潜在适生区分布。研究结果表明：(1) MaxEnt模型的ROC曲线的平均训练集的AUC值为0.945 (>0.9)，说明该模型构建准确可靠。(2) 影响吴茱萸适宜性生长的主要环境因子为最冷季度的平均温度(Bio11)、最暖季度的降水量(Bio18)、温度季节性变化(Bio4)和坡向(Aspect)，其中最冷季度的平均温度(Bio11)起到至关重要的作用。(3) 当前吴茱萸在中国分布较广，高适生区在江西、广西、贵州、湖南等省份，总适生区面积为131.69 × 104 km2，占我国陆地表面积的13.72%。(4) 未来气候变化有利于吴茱萸在我国的分布，其高适生区和总适生区在不同气候情境下均有明显的扩张。以上预测为吴茱萸潜在适生区分布提供了参考，为吴茱萸的物种资源保护和开发利用提供了视野。
Euodia rutaecarpa is a traditional medicinal herb in China. The wild resources of E. rutaecarpa are scrace, and they are primarily sourced from cultivation. Predicting the potential suitable areas of E. rutaecarpa holds guiding significance for its cultivation and plant conservation. Using the MaxEnt (Maximum Entropy) and ArcGIS software, we predicted potential suitable habitat of E. rutaecarpa in China in the future (2041~2060, 2080~2100) through 318 occurrence records along with 14 environmental factors. The results indicated the following: (1) The model exhibited outstanding accuracy with AUC = 0.945 (>0.9), indicating that the model is constructed accurately and reliably. (2) The primary environmental factors influencing the distribution of E. rutaecarpa were average temperature of coldestquarter (Bio11), precipitation in the warmest quarter (Bio18), seasonal variation of temperature (Bio4), and aspect. Among these, average temperature of coldestquarter (Bio11) was the most influential environmental factor on E. rutaecarpa distribution. (3) Currently, E. rutaecarpa is widely distributed in China, with suitability areas located in provinces such as Jiangxi, Guangxi, Guizhou, and Hunan, covering 131.69 × 104 km2 (13.72% of China’s total land area). (4) Future climate change is projected to favor the distribution of E. rutaecarpa in China, with notable expansion in its potential total suitable areas and high suitability areas under different climate scenarios. These accurate predictions serve as a scientific references for the identification of suitable areas of E. rutaecarpa, and provide insights into both the conservation and sustainable utilization of its germplasm resources.
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