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林业科学 ›› 2024, Vol. 60 ›› Issue (11): 139-148.doi: 10.11707/j.1001-7488.LYKX20230073

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基于优化的MaxEnt模型预测气候变化下松褐天牛在我国的潜在适生区

刘磊1,2,赵立娟1,2,刘佳奇1,2,张辉盛1,2,张志伟1,2,黄瑞芬3,高瑞贺1,2,*   

  1. 1. 山西农业大学林学院 晋中 030800
    2. 山西省林业危险性有害生物检验鉴定中心 晋中 030800
    3. 国家林业和草原局生物灾害防控中心 沈阳 110034
  • 收稿日期:2023-02-25 出版日期:2024-11-25 发布日期:2024-11-30
  • 通讯作者: 高瑞贺
  • 基金资助:
    国家自然科学基金项目(32401594);山西省应用基础研究计划(自由探索类)青年科技研究基金项目(20210302124062);山西省回国留学人员科研资助项目(2023-087);2024年中央财政林业科技推广示范项目“松材线虫病媒介昆虫监测与综合防控技术示范”。

Potentially Suitable Distribution Areas of Monochamus alternatus in China under Current and Future Climatic Scenarios Based on Optimized MaxEnt Model

Lei Liu1,2,Lijuan Zhao1,2,Jiaqi Liu1,2,Huisheng Zhang1,2,Zhiwei Zhang1,2,Ruifen Huang3,Ruihe Gao1,2,*   

  1. 1. College of Forestry, Shanxi Agricultural University Jinzhong 030800
    2. Shanxi Dangerous Forest Pest Inspection and Identification Center Jinzhong 030800
    3. Biological Disaster Prevention and Control Center of National Forestry and Grassland Administration  Shenyang 110034
  • Received:2023-02-25 Online:2024-11-25 Published:2024-11-30
  • Contact: Ruihe Gao

摘要:

目的: 预测松褐天牛在我国最新的潜在适生区及其对气候变化的响应,为松褐天牛的传播风险分析及其精准防控提供理论依据。方法: 利用松褐天牛650个分布点数据和20个环境变量,基于优化的MaxEnt模型和ArcGIS 10.7软件,预测当前和未来气候情景下松褐天牛在我国的潜在适生区分布及其空间格局变化。结果: 模型优化结果显示,当特征组合选取线型、二次型、铰链型、乘积型,调控倍频设置为1.5时,模型为最优模型,准确度最高;Jackknife检验表明,温差月均值、年降水量、最干月降水量、最暖季度降水量和海拔是影响松褐天牛分布的主导环境变量;在当前气候情景下,松褐天牛在我国的适生区主要分布于黄河以南地区;在未来气候情景下,松褐天牛的适生区面积呈显著增加趋势,新增适生区主要集中于陕西省、河南省、甘肃省、山东省和辽宁省。结论: 优化后的MaxEnt模型能够准确预测松褐天牛在我国的潜在适生区分布;温度和降水是影响松褐天牛分布的主导环境变量;气候变化会引起松褐天牛适生区迁移。

关键词: 松褐天牛, 优化的MaxEnt模型, 适生区, 气候变化

Abstract:

Objective: To predict the latest potential suitable areas of Monochamus alternatus in China and its responses to climate change, so as to a theoretical basis for the risk analysis and the precise prevention and control of M. alternatus in China. Method: Based on the latest 650 occurrence data of M. alternatus and 20 environmental factors, the optimized MaxEnt model and ArcGIS 10.7 software were used to predict the current and future potentially suitable areas of M. alternatus in China under different climatic conditions. Result: The results of model optimization show that when the feature combination of LQHP (linear, quadratic, hinge, product) is selected and the regularization multiplication is set to 1.5, the model is the optimal one with the highest accuracy. The Jackknife shows that the monthly mean temperature difference, annual precipitation, precipitation of driest month, precipitation of warmest quarter and elevation were the dominant bioclimatic variables affecting the distribution of M. alternatus. Under the current climate scenario, the suitable areas of M. alternatus in China are mainly distributed in the areas south of the Yellow River. Under the future climate scenarios, there is a significant increase trend for the potentially suitable areas of M. alternatus, and the newly added areas are mainly concentrated in Shaanxi, Henan, Gansu, Shandong and Liaoning Province. Conclusion: The optimized MaxEnt model can accurately predict the distribution of M. alternatus in our country. Temperature and precipitation are the main environmental factors affecting the distribution of M. alternatus. Climate change will cause the migration of suitable areas of M. alternatus.

Key words: Monochamus alternatus, the optimized MaxEnt model, suitable area, climate change

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