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    杨柳, 刘君昂, 周国英, 何苑皞, 段翔, 周洁尘. 气候变化下中国油茶毒蛾潜在分布区模拟预测研究[J]. 北京林业大学学报. DOI: 10.12171/j.1000-1522.20230034
    引用本文: 杨柳, 刘君昂, 周国英, 何苑皞, 段翔, 周洁尘. 气候变化下中国油茶毒蛾潜在分布区模拟预测研究[J]. 北京林业大学学报. DOI: 10.12171/j.1000-1522.20230034
    Yang Liu, Liu Junang, Zhou Guoying, He Yuanhao, Duan Xiang, Zhou Jiechen. Simulation and prediction of potential distribution area of Euproctis pseudoconspersa under climate change scenarios in China[J]. Journal of Beijing Forestry University. DOI: 10.12171/j.1000-1522.20230034
    Citation: Yang Liu, Liu Junang, Zhou Guoying, He Yuanhao, Duan Xiang, Zhou Jiechen. Simulation and prediction of potential distribution area of Euproctis pseudoconspersa under climate change scenarios in China[J]. Journal of Beijing Forestry University. DOI: 10.12171/j.1000-1522.20230034

    气候变化下中国油茶毒蛾潜在分布区模拟预测研究

    Simulation and prediction of potential distribution area of Euproctis pseudoconspersa under climate change scenarios in China

    • 摘要:
        目的  油茶是国家重点发展的木本油料作物,具有较高的经济价值和生态价值。油茶毒蛾是油茶的主要病虫害之一,严重制约了油茶的产量和质量。本研究针对油茶毒蛾的潜在分布开展模拟预测,以期为油茶毒蛾的预警和具体防控行动提供科学依据。
        方法  基于油茶毒蛾在中国的有效地理分布数据和生物气候数据,利用MaxEnt生态位模型和ArcGIS软件,模拟预测油茶毒蛾在当前气候条件的潜在分布,以及SSP1-2.6、SSP2-4.5和SSP5-8.5 3种气候情景下2050年和2070年油茶毒蛾在中国潜在适生区分布范围,并分析了制约其适生区分布的主导环境因子。
        结果  (1)影响油茶毒蛾适生区分布的主导环境因子为最干月降水量、年降水量、最冷月最低温度和温度日较差月均值。当最干月降水量28 ~ 148 mm、年降水量1 290 ~ 2 080 mm、最冷月最低温度1.0 ~ 10.1 ℃、温度日较差月均值7.2 ~ 8.5 ℃时最适宜油茶毒蛾的生存。(2)当前气候条件下,油茶毒蛾总适生区面积占我国国土面积的20.0%,主要分布在我国南方的长江中下游地区和华南地区,高度适生区面积为64.2 × 104 km2,中度适生区面积为61.8 × 104 km2,低度适生区面积为66.0 × 104 km2。(3)在未来两个时期和三种气候情景下,油茶毒蛾适生区面积出现不同程度的扩大,新增适生区面积在9.4 × 104 ~ 33.1 × 104 km2之间,地理分布中心迁移距离在24.4 ~ 125.1 km之间。气候变暖越明显,油茶毒蛾的潜在分布区面积增加越多,地理分布中心点的迁移距离越远。
        结论  油茶毒蛾在中国的适生区范围较广,几乎囊括了中国南部所有的省份。在未来气候情景下,油茶毒蛾的适生区将向北、向西等高纬度的内陆地区扩张。为此,建议相关部门应提前制定预案和政策,加强对油茶毒蛾的观测和防控,减少其对油茶产业造成的损失。

       

      Abstract:
        Objective  Camellia oleifera is a woody oleiferous plant with high economic and ecological value. Euproctis pseudoconspersa is one of the main pests of C. oleifera, which seriously restricts the yield and quality of C. oleifera. In order to provide scientific basis for early warning and specific prevention and control of the E. pseudoconspersa, the potential distribution of E. pseudoconspersa was simulated and predicted in this study.
        Method  Based on the distribution data and biological climate data of E. pseudoconspersa in China, MaxEnt model and ArcGIS software were used to predict the suitable areas for E. pseudoconspersa in China under the current climate, and the distribution range and potential suitable areas of E. pseudoconspersa in China in the 2050 and 2070 under SSP1-2.6, SSP2-4.5 and SSP5-8.5 climate change scenarios, and then the dominant environmental variables affecting the distribution of its potential suitable areas were analyzed.
        Result  (1) The dominant environmental variables affecting the distribution of the suitable habitat of E. pseudoconspersa were the precipitation of driest month, the annual precipitation, the min temperature of coldest month, the mean diurnal range (mean of monthly (max temp - min temp)) The optimum conditions were 28-148 mm the precipitation of driest month, 1 290−2 080 mm the annual precipitation, 1.0−10.1 ℃ the min temperature of coldest month and 7.2−8.5 ℃ the mean diurnal range (mean of monthly (max temp - min temp)). (2) Under the current climate conditions, the total suitable area of E. pseudoconspersa accounts for 20.0% of China’s land area, mainly distributed in the middle and lower reaches of the Yangtze River and South China, with a high suitable area of 642 000 km2, a medium suitable area of 618 000 km2, and a low suitable area of 660 000 km2. (3) In the next two periods and three climate scenarios, the suitable area of Camellia oleifera moth will be enlarged to different degrees, with the newly increased area of 94 000-331 000 km2 and the migration distance of the geographical distribution center between 24.4-125.1 km. The more obvious the climate warming is, the more the potential distribution area increases, and the farther the geographical distribution center moves.
        Conclusion  E. pseudoconspersa has a wide range of habitats in China, including almost all the provinces in southern China. In the future climate change scenario, the suitable habitat of E. pseudoconspersa will expand northward, westward and other high latitude inland areas. Therefore, it is suggested that relevant departments should make plans and policies in advance to strengthen the observation and control of E. pseudoconspersa, so as to reduce its losses to camellia oleifera industry.

       

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