基于优化MaxEnt模型预测玫瑰蜗牛（Euglandina rosea）在中国的潜在分布区

doi:10.11853/j.issn.1003.8280.2023.02.002

中国媒介生物学及控制杂志 ›› 2023, Vol. 34 ›› Issue (2): 137-144.DOI: 10.11853/j.issn.1003.8280.2023.02.002

• 重要外来入侵媒介和病原生物 • 上一篇下一篇

基于优化MaxEnt模型预测玫瑰蜗牛（Euglandina rosea）在中国的潜在分布区

殷颖璇, 徐安远, 潘筱雯, 何晴, 吴银娟, 李学荣

中山大学中山医学院寄生虫学教研室, 中山大学教育部热带病防治研究重点实验室, 广东省媒介生物防控工程技术研究中心, 国家原子能机构核技术(昆虫不育)研发中心, 广东广州 510080

收稿日期:2023-01-31 出版日期:2023-04-20 发布日期:2023-04-26
通讯作者: 李学荣,E-mail：xuerong2@mail.sysu.edu.cn;吴银娟,E-mail：wuyinjuan@mail.sysu.edu.cn
作者简介:殷颖璇,女,在读硕士,主要从事病媒生物研究工作,E-mail：yinyx23@mail2.sysu.edu.cn;徐安远,女,在读硕士,主要从事病原生物感染与免疫研究工作,E-mail：xuany3@mail2.sysu.edu.cn
基金资助:
国家重点研发计划（2020YFC1200100）；广东省自然科学基金（2022A1515012560，2023A1515010955）；广州市科技项目（202201011723）

Predicting the potential distribution of Euglandina rosea in China using an optimized MaxEnt model

YIN Ying-xuan, XU An-yuan, PAN Xiao-wen, HE Qing, WU Yin-juan, LI Xue-rong

Department of Parasitology, Zhongshan School of Medicine, Sun Yat-sen University, Key Laboratory for Tropical Diseases Control, Ministry of Education, Sun Yat-sen University, Provincial Engineering Technology Research Center for Biological Vector Control, CAEA Center of Excellence on Nuclear Technology Applications for Insect Control, Guangzhou, Guangdong 510080, China

Received:2023-01-31 Online:2023-04-20 Published:2023-04-26
Supported by:
National Key R&D Program of China (No. 2020YFC1200100);Natural Science Foundation of Guangdong Province of China (No. 2022A1515012560, 2023A1515010955);Science and Technology Program of Guangzhou (No. 202201011723)

摘要/Abstract

摘要： 目的通过优化后的最大熵模型（MaxEnt）预测在当前和未来气候条件下玫瑰蜗牛在我国的潜在分布，为我国防控玫瑰蜗牛的生物入侵提供理论依据。方法收集玫瑰蜗牛的全球分布数据，使用ENMtool进行筛选；用maxent 3.4.1软件和GraphPad Prism 8根据环境变量贡献率、刀切法以及变量相关性分析对环境变量进行筛选；在R 4.0.4软件中运行“kuenm”程序包计算调整模型参数，包括正则化乘数和特征组合；利用优化MaxEnt模型预测当前和未来不同气候情景条件下玫瑰蜗牛在中国的潜在分布范围；使用ArcGIS 10.7软件进行结果处理及可视化。结果共筛选出780个玫瑰蜗牛分布点，4个环境变量构建MaxEnt模型，模型的曲线下面积（AUC）值为0.963。对玫瑰蜗牛分布影响最大的环境因子为最干季降水量和2月最高温。MaxEnt模型预测当前玫瑰蜗牛潜在适生区分布在我国东南地区，集中于福建和广东省以及广西壮族自治区中部。未来将逐步向北扩大至湖南省、江西省、安徽省中部、湖北省东部以及浙江省的部分地区。结论玫瑰蜗牛在我国存在潜在适生区，随着全球变暖，其潜在适生区将逐步扩大，东南部较低纬度适生区则略有收缩，使得玫瑰蜗牛潜在适生区的整体重心向北移动。

关键词: 玫瑰蜗牛, 最大熵模型, 生物入侵, 气候变化, 适生区

Abstract: Objective To predict the potential distribution of Euglandina rosea in China under current and future climatic conditions via an optimized maximum entropy (MaxEnt) model, and to provide a theoretical basis for the prevention and control of invasion of E. rosea in China. Methods The global occurrence records of E. rosea were collected and screened using ENMtool. Maxent 3.4.1 and GraphPad Prism 8 were used to screen environmental variables according to the contribution rate of environmental variables, the jackknife method, and the correlation analysis of variables. The "kuenm" package was run in R 4.0.4 software to calculate and adjust the model parameters by means of regularization multipliers and feature combinations. The optimized MaxEnt model was used to predict the potential distribution of E. rosea in China under current and future climate scenarios. ArcGIS 10.7 was used to process the results and map the images. Results A total of 780 E. rosea occurrence records were identified, and four environmental variables were used to construct the MaxEnt model. The area under the curve (AUC) of the model was 0.963. The most influential environmental factors on the distribution of E. rosea were precipitation of the driest quarter and the highest temperature in February. The MaxEnt model predicted that the current potential areas of E. rosea were distributed in the southeast of China, concentrated in Fujian province, Guangdong province, and central Guangxi Zhuang Autonomous Region. It would gradually expand northward to Hunan province, Jiangxi province, central Anhui province, eastern Hubei province, and some areas of Zhejiang province in the future. Conclusions E. rosea has potential distribution in China. With global warming, its potential habitat areas will gradually expand, while at lower latitudes in the southeast they will slightly shrink. As a result, the overall center of potential areas shifts northward.

Key words: Euglandina rosea, MaxEnt, Biological invasion, Climate change, Suitable habitat

中图分类号:

S40
R183

殷颖璇, 徐安远, 潘筱雯, 何晴, 吴银娟, 李学荣. 基于优化MaxEnt模型预测玫瑰蜗牛（Euglandina rosea）在中国的潜在分布区[J]. 中国媒介生物学及控制杂志, 2023, 34(2): 137-144.

YIN Ying-xuan, XU An-yuan, PAN Xiao-wen, HE Qing, WU Yin-juan, LI Xue-rong. Predicting the potential distribution of Euglandina rosea in China using an optimized MaxEnt model[J]. Chinese Journal of Vector Biology and Control, 2023, 34(2): 137-144.

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基于优化MaxEnt模型预测玫瑰蜗牛（Euglandina rosea）在中国的潜在分布区

Predicting the potential distribution of Euglandina rosea in China using an optimized MaxEnt model

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