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林业科学 ›› 2019, Vol. 55 ›› Issue (6): 86-95.doi: 10.11707/j.1001-7488.20190611

• 论文与研究报告 • 上一篇    下一篇

外来入侵新害虫刺槐突瓣细蛾在中国的适生区预测

樊婷婷1, 高尚坤1,2, 孟凡玲3, 尹红增3, 李超4, 王庆华4, 周成刚1,2   

  1. 1. 山东农业大学植物保护学院 泰安 271018;
    2. 山东省林业有害生物防控工程技术研究中心 泰安 271018;
    3. 泰安市园林管理局 泰安 271021;
    4. 泰安市徂徕山林场 泰安 271000
  • 收稿日期:2017-10-23 修回日期:2018-01-26 出版日期:2019-06-25 发布日期:2019-07-11

Prediction of Suitable Distribution Regions of a New Invasive Pest: Chrysaster ostensackenella (Lepidoptera: Gracillariidae) in China

Fan Tingting1, Gao Shangkun1,2, Meng Fanling3, Yin Hongzeng3, Li Chao4, Wang Qinghua4, Zhou Chenggang1,2   

  1. 1. College of Plant Protection, Shandong Agricultural University Tai'an 271018;
    2. Engineering Research Center of Forest Pest Management of Shandong Province Tai'an 271018;
    3. Tai'an Landscape Administration Bureau Tai'an 271021;
    4. Mount Culai Forest Farm of Tai'an Tai'an 271000
  • Received:2017-10-23 Revised:2018-01-26 Online:2019-06-25 Published:2019-07-11

摘要: [目的]刺槐突瓣细蛾是2008年在山东省烟台市新发现的重要外来入侵害虫,严重为害我国重要外来树种——刺槐。通过预测其适生区,为高效率地做好检疫、监管和及时防治工作提供依据。[方法]收集刺槐突瓣细蛾在全国的11个分布点数据,并利用ArcGIS10.0从WorldClim下载1970-2000年的19个环境变量中筛选出相关系数<|0.9|的9个变量,并将其转化为MaxEnt需要的ASCⅡ格式数据。设置模型为双对数(cloglog)输出格式,输出文件类型ASCⅡ和线性(linear)特征。为了提高预测效果的精确性和缩小不确定的水平,在模型中设置10倍交叉验证并重复运行10次,获得平均结果。采用刀切法分析各个环境变量在模型中对潜在地理分布的贡献率,将最优模拟结果在ArcGIS10.0软件中转化并分类,即模型模拟得出的刺槐突瓣细蛾在中国的适宜指数分为4类,即非适生区、低度适生区、中度适生区、高度适生区,最后得到刺槐突瓣细蛾的不同程度适生区分布图。利用2050年和2070年的RCP 8.5气候数据进行投射预测物种的未来分布。用ROC曲线下面积AUC和真实技巧统计法TSS的大小评价MaxEnt生态模型的精确度。[结果]在当前气候条件下,刺槐突瓣细蛾中高度适生区主要集中在山东及其周边省份(辽宁、北京、天津、河北、山西、河南、安徽、江苏),以及四川和云南局部地区;在未来气候条件下,至2050年,刺槐突瓣细蛾在RCP8.5气候条件下的中高度适生区范围比当前的呈整体扩大且向西南部蔓延,至2070年,在相同气候情景下该虫的适生区范围亦呈整体明显扩大且适生区北界向东北移动。而其与2050年的预测结果相比较,高度适生区小幅度减少。刀切法检测表明:年均降水量、最湿季度降水量、最冷月最低温对刺槐突瓣细蛾的分布影响较大,其中年均降水量适宜值为382.08~1 135.81 mm,最适值为753.85 mm;最湿季度降水量适宜值为241.61~693.86 mm,最适值为464.55 mm;最冷月最低温适宜值为-16.96~6.36℃,最适值为-5.5℃;AUC和TSS值分别为0.957±0.052和0.8±3.05,表明模型预测准确性极好。[结论]通过预测结果可知,刺槐突瓣细蛾对刺槐构成了重大的威胁,建议相关造林绿化和植物检疫部门高度重视。

关键词: 入侵害虫, 刺槐突瓣细蛾, MaxEnt, AUC, TSS, 适生区

Abstract: [Objective] Chrysaster ostensackenella ((Lepidoptera:Gracillariidae) is an important alien invasive pest newly discovered in Yantai, Shandong Province in 2008 and severely damages Robinia pseudoacacia, an important economic greening plant in China. Prediction of the suitable areas can provide a basis for promoting the efficiency of quarantine, supervision and control of the pest.[Method] In this study, data of 11 distribution locations of C. ostensackenella in China were collected, and nine environment variables with correlation coefficients <|0.9|were screened from 19 environment variables downloaded from WordClim between 1970 and 2000 by ArcGIS 10.0. Then the data were converted into the ASCⅡ format data required for MaxEnt, and the model was set to cloglog output format, outputting file type was ASCⅡ and linear features. To improve the accuracy of the predictive effects and reduce the level of uncertainty, a 10-times cross-validation was set up in the model and repeated 10 runs to get the average values. The contribution rate of each environment variable to the potential geographic distribution in this model was analyzed by Jackknife method, and the optimal simulation results were transformed and classified in ArcGIS10.0, that is, the habitat suitability indexes of C. ostensackenella in China were divided into four categories:non-suitable areas, low suitable areas, middle suitable areas, high suitable areas. Finally, the distribution map of different extent suitable habitats of the insect was obtained. The future distribution areas of C. ostensackenella were predicted using RCP 8.5 climate data of 2050 and 2070. The model precisions of MaxEnt were evaluated by areas under the ROC curve and True skill statistics.[Result] Under current climatic conditions, the high and middle suitable areas of C. ostensackenella were mainly concentrated in Shandong and its neighboring provinces (Liaoning, Beijing, Tianjin, Hebei, Shanxi, Henan, Anhui, Jiangsu), as well as in parts of Sichuan and Yunnan; Under the future climate conditions, by 2050, the middle and high suitable regions of C. ostensackenella under RCP 8.5 climatic conditions would be larger than those in present and spread to the southwest. By 2070, the suitable regions also would enlarge obviously and move to the northeast. Compared with the predicted results in 2050, the high suitable area decreased slightly. The Jackknife test indicated that annual precipitation, precipitation of wettest quarter, min-temperature of coldest month had a great contribution to the distribution of C. ostensackenella. The range of the optimum annual average precipitation is 382.08-1 135.81 mm, with the optimum of 753.85. The optimum wet season precipitation is 241.61-693.86 mm, with the optimum of 464.55 mm, and the optimum minimum temperature in the coldest month is -16.96-6.36℃ with the optimum of -5.5℃. The AUC and TSS values are 0.957±0.052 and 0.8±3.05, respectively, which indicates that the prediction accuracy of the model is excellent.[Conclusion] According to the results of this study, it is known that the pest is a major threat to black locust, R. pseudoacacia in China, and a high attention should be paid by the relevant afforestation and plant quarantine departments.

Key words: invasive pest, Chrysaster ostensackenella, MaxEnt, AUC, TSS, suitable distribution regions prediction

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