南京林业大学学报(自然科学版) ›› 2019, Vol. 43 ›› Issue (6): 121-128.doi: 10.3969/j.issn.1000-2006.201808046

• 研究论文 • 上一篇    下一篇

基于随机森林模型的美国白蛾在中国的潜在生境预测

纪烨琳1(), 苏喜友1,*(), 于治军2   

  1. 1.北京林业大学信息学院,北京 100083
    2.国家林业和草原局森林病虫害防治总站,辽宁 沈阳 110034
  • 收稿日期:2018-08-27 修回日期:2019-03-18 出版日期:2019-11-30 发布日期:2019-11-30
  • 通讯作者: 苏喜友
  • 基金资助:
    北京农业信息技术研究中心开放课题(KF2018W004)

Potential habitat prediction of Hyphantria cunea based on a random forest model in China

JI Yelin1(), SU Xiyou1,*(), YU Zhijun2   

  1. 1. School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China
    2. General Station of Forest Pest Management, State Forestry and Grassland Administration, Shenyang 110034, China
  • Received:2018-08-27 Revised:2019-03-18 Online:2019-11-30 Published:2019-11-30
  • Contact: SU Xiyou

摘要:

【目的】基于随机森林模型原理,对当前气候环境以及21世纪50年代的美国白蛾在中国的空间分布、环境因子重要性、发生面积及迁移情况进行预测和分析,为美国白蛾有效防控提供理论参考。【方法】获取2011—2017年美国白蛾发生的县市级数据, 利用地理信息系统ArcGIS中随机点生成工具生成未发生点数据。采用随机森林模型原理,选择19个气候因子以及海拔、坡度、坡向、植被覆盖率、有效光合辐射等5个环境因子,通过ArcGIS中的提取值工具提取发生点和未发生点的24个环境变量的值,将海拔、坡度、坡向进行离散化。使用R语言模拟2011—2030年美国白蛾的潜在生境分布模型,以ROC曲线验证模型的精度;利用构建好的模型分析环境因子重要性并排序,预测在2050s(2041—2060年)时期两种气候情景(RCP2.6、RCP4.5)下全中国范围内美国白蛾的潜在生境分布。【结果】ROC曲线分析表明,随机森林模型预测美国白蛾潜生境分布的训练数据和测试数据的AUC值分别为0.997和0.963,模型精度较高;当前时期下美国白蛾潜在生境(适生区)占中国国土面积的8.74%,其中低适生区、中适生区、高适生区和极高适生区面积分别占适生区总面积的41.47%、20.85%、18.90%和18.78%,适生区主要集中在华北地区东南部、中南地区北部、华东地区北部和东北地区南部。对美国白蛾潜在生境分布影响较大的环境因子依次是:海拔、植被覆盖率、最湿季平均气温、最暖季平均气温。在2050 s时期RCP2.6气候情景下,美国白蛾适生区总面积占中国国土面积的14.38%,其中低适生区、中适生区、高适生区和极高适生区面积分别占适生区总面积的51.87%、20.37%、16.49%和12.27%;在RCP4.5气候情景下,美国白蛾适生区总面积占中国国土面积的19.06%,其中低适生区、中适生区、高适生区和极高适生区面积分别占适生区总面积的51.14%、15.11%、20.36%和13.39%;2050s时期美国白蛾潜在生境质心平均向北迁移93.65 km,新增适生区有黑龙江省、吉林省、四川省、湖北省、山西省、河南省、内蒙古东部、台湾岛等地区。【结论】美国白蛾适宜生活在海拔较低、夏季高温多雨、拥有较为丰富的森林资源的地区。随着气候变化,美国白蛾潜在生境整体向中国北部和内陆湿度较高地区偏移,发生面积逐渐扩大,发生程度逐渐加重。

关键词: 美国白蛾, 随机森林模型, 潜在生境, 气候情景, 空间分布

Abstract:

【Objective】 Hyphantria cunea is extremely harmful to plant that are highly susceptible to outbreaks of infection. Predicting the potential habitat of H. cunea is essential for its prevention and control, and this prediction is based on a random forest model, which predicts and analyzes spatial distribution, the importance of environmental factors, occurrence area and migration situation of H. cunea under the current climate and based on the data from the 1950s; overall, these data can provide a theoretical basis for effective prevention and control for this pest. 【Method】 County and municipal data on the occurrence of H. cunea from 2011 to 2017 were obtained, and non-occurrence points were made with the create random points tool of ArcGIS. By adopting the principle of the random forest model, 19 climate and 5 environmental factors (altitude, slope, aspect, vegetation coverage and effective photosynthetic radiation) were selected, and the environmental variables of occurrence and non-occurrence points were extracted by extracting values using the points tool of ArcGIS. Then, the altitude, slope and aspect were discretized. This study used R to simulate a potential habitat distribution model forH. cunea from 2011 to 2030, and the ROC curve was used to check the accuracy of the model. The order of importance of environmental factors was determined using this model. The future habitat distribution of H. cunea in China was also predicted under two climate scenarios (RCP2.6 and RCP4.5) for 2041-2060 (2050s). 【Result】 ROC curve analysis indicated that the use of the random forest model to predict the potential habitat distribution ofH. cunea achieves high precision; the AUC of training and testing data was 0.997 and 0.963, respectively. In the current period, the potential distribution (suitable areas) of H. cunea accounted for 8.74% of the total study area; the areas of low, medium, high and extremely high suitable accounted for 41.47%, 20.85%, 18.90% and 18.78%, respectively. The suitable areas were mainly concentrated in the southeast of northern China, north of central and southern China, north of eastern China, and south of northeastern China. In order of importance, the environmental factors that influence the potential habitat distribution of H. cunea are as follows: altitude, vegetation coverage, average temperature in the wettest season, and maximum temperature in the warmest month. Under RCP2.6 for the 2050s, the potential distribution of H. cunea will account for 14.38% of the total study area, whereas the low, medium, high and extremely high suitable areas will account for 50.87%, 20.37%, 16.49% and 12.27%, respectively; under RCP4.5, the potential distribution of H. cunea will account for 19.06% of the total study area, and the low, medium, high and extremely high suitable areas will account for 51.14%, 15.11%, 20.36% and 13.39%, respectively. In the 2050s, the centroids of the potential habitats ofH. cunea will migrate 93.65 km toward the north on an average. New suitable areas will include Heilongjiang, Jilin, Sichuan, Hubei, Shanxi, Henan, eastern Inner Mongolia and Taiwan. 【Conclusion】H. cunea is adapted to live at low altitudes, in areas with high temperatures, in rainy summers, and in areas with rich forest resources. With climate change, the potential habitat of this pest will spread toward the north of China and inland areas with a high humidity. The area and degree of its occurrence will gradually increase.

Key words: Hyphantria cunea, random forest model, potential habitat, climate scenarios, spatial distribution

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