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    黄梦伊, 赵佳强, 石娟. 基于MaxEnt对桉树枝瘿姬小蜂在中国发生趋势的预测[J]. 北京林业大学学报, 2020, 42(11): 64-71. DOI: 10.12171/j.1000-1522.20190053
    引用本文: 黄梦伊, 赵佳强, 石娟. 基于MaxEnt对桉树枝瘿姬小蜂在中国发生趋势的预测[J]. 北京林业大学学报, 2020, 42(11): 64-71. DOI: 10.12171/j.1000-1522.20190053
    Huang Mengyi, Zhao Jiaqiang, Shi Juan. Predicting occurrence tendency of Leptocybe invasa in China based on MaxEnt[J]. Journal of Beijing Forestry University, 2020, 42(11): 64-71. DOI: 10.12171/j.1000-1522.20190053
    Citation: Huang Mengyi, Zhao Jiaqiang, Shi Juan. Predicting occurrence tendency of Leptocybe invasa in China based on MaxEnt[J]. Journal of Beijing Forestry University, 2020, 42(11): 64-71. DOI: 10.12171/j.1000-1522.20190053

    基于MaxEnt对桉树枝瘿姬小蜂在中国发生趋势的预测

    Predicting occurrence tendency of Leptocybe invasa in China based on MaxEnt

    • 摘要:
        目的  桉树枝瘿姬小蜂是我国一种入侵性小蜂,自2007年传入我国广西省,在短短几年时间内危害了我国南部的桉树种植地,造成严重经济损失。本研究利用MaxEnt模型对桉树枝瘿姬小蜂在中国现在和未来的适生区进行预测,以了解桉树枝瘿姬小蜂在温度变化的影响下其适生地范围的变化。
        方法  采用MaxEnt预测模型—最大熵模型,通过收集桉树枝瘿姬小蜂在中国报道的分布地数据、调查最新发生地危害轻重程度对该蜂在中国的适生区现在以及未来RCP8.5气候情景下的适生区进行模拟并检测模拟结果的精准度。
        结果  模型模拟结果的测试遗漏率与理论遗漏率基本吻合。AUC 值为0.898,标准差为0.022,表明所使用的数据无空间自相关,模型筛选的参数结果可靠且准确度高。MaxEnt模型预测得到桉树枝瘿姬小蜂在中国的最佳适生区主要分布在长江以南的福建、广东、广西、海南等地,在RCP8.5气候情景下其未来中度适生区面积有小范围的下降,但整体适生区范围显著增加。
        结论  通过适生地范围预测结果的分析,本研究对桉树枝瘿姬小蜂的监测以及潜在危险入侵地区制定有效的防治手段具有重要的理论指导意义。

       

      Abstract:
        Objective  Leptocybe invasa is an invasive wasp common to China, which was first introduced into the Guangxi Province of southern China in 2007. It had endangered the eucalyptus plantations in southern China within just a few years, causing serious economic and ecological losses. This study employed the MaxEnt latest prediction model, a novel maximum entropy model to firstly analyze this invasive wasp distribution in China under current and future climate conditions. The results will be helpful to understand the range dynamic change of L. invasa under the influence of temperature change.
        Method  Data were collected on the current locations of this wasp, along with the damage incurred to eucalyptus. These data were used to create a forecast model for the present and future trends of the favorable habitat under the RCP 8.5 climate scenario. And model will test the accuracy of simulation results.
        Result  The test omission rate of simulation results was basically consistent with that of theory. The value of AUC was 0.898 while a standard deviation of 0.022. The verification results showed that the test and training data were not independent and the constructed model was highly reliable and accurate. MaxEnt model predicted that the potential distribution for L. invasa was mainly concentrated at the south of the Yangtze River in the provinces of Fujian, Guangdong, Guangxi and Hainan. The RCP 8.5 scenario predicted a small-scale potential reduction of moderately favorable habitat, but the whole favorable habitat increased.
        Conclusion  Based on the analysis of the predicted scope of this invasive wasp distribution, this study has established the grounds for the effective formulation of preventive and control measures for the monitoring of L. invasa and the prediction of its possible colonies, which is a significant theoretical reference on its own.

       

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