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林业科学 ›› 2019, Vol. 55 ›› Issue (2): 118-127.doi: 10.11707/j.1001-7488.20190212

• 论文与研究报告 • 上一篇    下一篇

基于新型最大熵模型预测刺槐叶瘿蚊(双翅目:瘿蚊科)在中国的适生区

赵佳强, 石娟   

  1. 北京林业大学 林木有害生物防治北京市重点实验室 北京 100083
  • 收稿日期:2018-07-11 修回日期:2018-11-01 出版日期:2019-02-25 发布日期:2019-03-20
  • 基金资助:
    国家重点研发计划(2016YFC1202102);林业公益性行业科研专项(201504304)。

Prediction of the Potential Geographical Distribution of Obolodiplosis robiniae (Diptera: Cecidomyiidae) in China Based on A Novel Maximum Entropy Model

Zhao Jiaqiang, Shi Juan   

  1. Beijing Key Laboratory for Forestry Pest Control Beijing Forestry University Beijing 100083
  • Received:2018-07-11 Revised:2018-11-01 Online:2019-02-25 Published:2019-03-20

摘要: [目的]基于对刺槐叶瘿蚊在全国的普查情况,利用最大熵模型MaxEnt软件的互补双对数输出方式对刺槐叶瘿蚊在中国当前和未来(2050年)的适生区进行预测,为林业和海关检疫部门对刺槐叶瘿蚊当前与未来的防控与检疫工作提供重要参考依据。[方法]使用MaxEnt、ArcGIS、R软件对刺槐叶瘿蚊危害点,气候图层,模型参数这3方面进行科学的优化选择,确保模型的科学性、有效性。当前气候适生区的预测使用WorldClim网站全球气候数据Version 1.4,未来数据则采用通用气候系统模型CCSM4下3种外排情景(RCP26、RCP45、RCP85)。[结果]最终确定52个危害点,7个主导气候图层,运用互补双对数输出方式对适生区进行预测。模拟结果的测试遗漏率与理论遗漏率基本吻合,ROC曲线即AUC值为0.919,标准差为0.023,表明所使用的数据无空间自相关,构建的模型达到"极好"的标准。通过刀切图分析,对刺槐叶瘿蚊分布影响最大的3个气候图层分别为Bio1(年平均气温)、Bio12(年降水量)、Bio5(最热月的最高温度)。对当前气候刺槐叶瘿蚊适生区进行划分,刺槐叶瘿蚊在中国的适生范围为22.08°-48.42°N,39.39°-135.06°E,达国土面积的31.90%。除西藏、青海、海南、台湾4省区外,其余省份均包含其适生区,其高度适生区以西南(四川、重庆)和华北(北京、天津、河北、山东、陕西)为主。对未来(2050年)适生区的预测,3种外排情景RCP26、RCP45、RCP85的总适生区均比当前气候的总适生范围大,以高度、中度适生区面积的增大为主,新疆和我国北部区域面积显著扩增。RCP85情景下的刺槐叶瘿蚊适生区面积最大,达国土面积的39.71%,比当前预测的多出75万km2。[结论]结合实际调查情况,新型MaxEnt模型预测结果可信度高,阐明影响刺槐叶瘿蚊分布的主导气候因子,预测出刺槐叶瘿蚊当前与未来的分布范围及适生程度情况,对刺槐叶瘿蚊的防控具有重要意义。

关键词: 刺槐叶瘿蚊, MaxEnt, 适生区, 互补双对数输出

Abstract: [Objective] Based on the national investigation of Obolodiplosis robiniae,the current and future (2050) sustainable habitats of O.robiniae in China were predicted by using the complementary log-log (Cloglog) of maximum entropy model.This study would provide an important reference for forestry and quarantine authorities to control and quarantine of O.robiniae at present and in the future.[Method] MaxEnt,ArcGIS,and R software were used to scientifically optimize the three aspects of the O.robiniae distribution points,bio-climatic variables and model parameter setting,to ensure the scientificity and validity of the model.The current bio-climatic variables for the suitable area were predicted by using WorldClim Website Global Weather Database Version 1.4,with5 min of spatial resolution.The future data were derived from three representative concentration pathways RCP26,RCP45 and RCP85 under CCSM4.[Result] A total of 52 distribution points and 7 bio-climatic variables were finally determined.The complementary log-log output format was used to predict the potential geographical distribution.The test omission rate of simulation results is basically consistent with the theoretical omission rate.The ROC (receiver operating characteristic curve),which has an AUC (area under the ROC curve) of 0.919 and a standard deviation of 0.023,indicating that the test and training data have no spatial autocorrelation and the constructed model meets the"excellent"standard.Through Jackknife test analysis,the three bio-climatic variables that have the greatest influence on O.robiniae distribution are Bio1(Annual mean temperature),Bio12(Annual precipitation) and Bio5(Max temperature of warmest month).For the current classification of the potential geographical distribution for O.robiniae,the suitable range is in the range of 22.08°-48.42°N,39.39°-135.06°E,accounting for 31.90% of the national area.With the exception of Tibet,Qinghai,Hainan,and Taiwan province,the other provinces have their own potential geographical distribution,and the highly potential geographical distribution regions are mainly in the southwest (Sichuan,Chongqing) and Northern China (Beijing,Tianjin,Hebei,Shandong,and Shaanxi).For the prediction of the future (2050),the total susceptibility zones of the three representative concentration pathways RCP26,RCP45,and RCP85 are larger than the total habitats in the current climate,especially for high and moderate suitable habitats.The areas in Xinjiang and northern China will expand significantly.The risk area under the RCP85 scenario is the largest,reaching to 39.71% of the national area,750 000 km2 more than the current prediction.[Conclusion] Combined with the actual investigation,the novel MaxEnt model has high reliability to clarify the dominant climatic factors affecting the distribution of O.robiniae,and predict the distribution and fitness of O.robiniae current and future (2050),which is of important value for the prevention and control of O.robiniae.

Key words: Obolodiplosis robiniae, MaxEnt, potential geographical distribution, complementary log-log output

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