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生态学杂志 ›› 2022, Vol. 41 ›› Issue (10): 2008-2016.doi: 10.13292/j.1000-4890.202209.014

• 研究报告 • 上一篇    下一篇

气候变化背景下茶小绿叶蝉在中国的潜在适生区预测

姜明鑫1,2,3,钟文玉1,2,3,胡海琴1,2,3,郑志强1,2,3,陈燕婷4,尤民生2,5,陈李林2,3,5*


  

  1. （1福建农林大学安溪茶学院， 福建安溪 362406； 2闽台作物有害生物生态防控国家重点实验室， 福建农林大学植物保护学院， 福州 350002； 3中国白茶研究院， 福建福鼎 355200； 4福建省农业科学院植物保护研究所， 福州 350013； 5海峡两岸特色作物安全生产省部共建协同创新中心， 福建农林大学植物保护学院， 福州 350002）

  • 出版日期:2022-10-10 发布日期:2022-10-13

Prediction of potential suitable regions of tea green leafhopper in China in the context of climate change.

JIANG Ming-xin1,2,3, ZHONG Wen-yu1,2,3, HU Hai-qin1,2,3, ZHENG Zhi-qiang1,2,3, CHEN Yan-ting4, YOU Min-sheng2,5, CHEN Li-lin2,3,5*#br#

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  1. (1Anxi Tea College, Fujian Agriculture and Forestry University, Anxi 362406, Fujian, China; 2State Key Laboratory of Ecological Pest Control in Fujian and Taiwan Crops, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, China; 3Institute of China White Tea, Fuding 355200, Fujian, China; 4Institute of Plant Protection, Fujian Academy of Agricultural Sciences, Fuzhou 350013, China; 5The Collaborative Innovation Center for the Safe Production of Featured Crops Established by Provinces and Ministries Across the Taiwan Straits, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, China).

  • Online:2022-10-10 Published:2022-10-13

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摘要： 基于茶小绿叶蝉当前在中国的308个分布点和7个环境变量，利用MaxEnt模型预测当前及未来（2050年、2070年）2种气候情景（SSP2_45、SSP5_85）下茶小绿叶蝉在中国的潜在适生区分布范围及适生程度。结果表明：AUC值为0.904，模型预测准确，结果可靠；利用刀切法得到影响茶小绿叶蝉潜在分布的主要环境变量为最冷月份最低温（bio6）、昼夜温差月均值（bio2）、最干月份降水量（bio14）、最湿季降水量（bio16）；当前茶小绿叶蝉高适生区主要集中在浙江、福建、江西、湖南、贵州、重庆和海南等地。未来气候情景下，茶小绿叶蝉潜在适生区面积呈扩大趋势，适生区范围向北迁移；2070年SSP5_85气候情景下适生区面积最大，相比当前适生区增加了21.1%；茶小绿叶蝉广泛分布于中国大部分地区，应加强茶小绿叶蝉的预测预报，及时采取防控措施，为茶叶安全优质生产保驾护航。


关键词: 小绿叶蝉, 气候变化, MaxEnt模型, 适生性分析

Abstract: Based on the current 308 sites of tea green leafhopper (Empoasca onukii Matsuda) recorded in China and 7 environmental variables, a maximum entropy model (MaxEnt) was used to predict the current and future (2050 and 2070) potential distributions and its suitable degree under two climate scenarios (SSP2_45 and SSP5_85). The area under curve (AUC) value was 0.904, indicating that the accuracy of the model was good and the outcomes were reliable. The main environmental variables estimated by the Jackknife method were the lowest temperature in the coldest month (bio6), the mean monthly temperature difference between day and night (bio2), the precipitation in the driest month (bio14), and the precipitation in the wettest season (bio16). Currently, the highly suitable regions of tea green leafhopper were mainly concentrated in Zhejiang, Fujian, Jiangxi, Hunan, Guizhou, Chongqing, and Hainan. Under future climate scenarios, the potentially suitable regions would be expanding and move northward. The suitable region is the largest under the SSP5_85 climate scenario in 2070, with a 21.1% increase compared to the current suitable area. Given the wide distribution of tea green leafhopper in most regions of China, accurate predictions of its distribution are vital, and timely control measures should be taken to protect the high-quality production of tea.


Key words: tea green leafhopper, climate change, MaxEnt model, habitat suitability analysis.

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