Projection of suitable region for Amblyomma maculatum distribution in China using the genetic algorithm for rule-set prediction model

doi:10.11853/j.issn.1003.8280.2022.02.018

Abstract

Abstract: Objective To project the suitable region in China for Amblyomma maculatum distribution and the grade of the region through analysis of climatic environmental factors and the distribution of A. maculatum, and to provide a scientific basis for the prevention and control of invasive species. Methods The collated distribution data, combined with environmental data provided by WorldClim, were collected to project the suitable region of A. maculatum using the ecological niche model based on the genetic algorithm for rule-set prediction(GARP). SPSS 25.0 software was used to perform the one-sided Chi-square test, plot the receiver operating characteristic curve, and calculate the area under the curve (AUC) to validate the model. Results A total of 11 environmental factors were included in the model through screening. The AUC of the model was 0.927, suggesting good predictive ability of the model. The potential suitable regions of A. maculatum in China were located in South China, East China, and Central China. The high, middle and low suitable habitats are distributed from southeast to northwest, and the farthest reaches Sichuan, Shaanxi, Shanxi and northern Hebei. Conclusion The GARP ecological niche model is more reliable in projecting the suitable region of A. maculatum. There are a lot of suitable regions in China, and the relevant departments should carry out targeted prevention.

Key words: Amblyomma maculatum, Genetic algorithm for rule-set prediction, Biological invasion, Geographic information system

摘要： 目的通过气候环境因素与斑体花蜱分布相关性的研究，预估斑体花蜱在中国适生区的有无及适生区的等级，为外来入侵生物的防控提供科学依据。方法收集整理斑体花蜱的分布数据，结合WorldClim提供的环境数据，使用规则集遗传算法（GARP）生态位模型，预估斑体花蜱的适生区，利用SPSS 25.0统计软件进行χ²单侧检验，构建受试者工作特征曲线（ROC）并计算曲线下面积（AUC）值验证模型。结果经过筛选最后纳入11个环境数据进入模型，模型的AUC值为0.927，模型的预测结果较好，斑体花蜱主要适生区在我国华南、华东和华中地区，高中低适生区沿东南向西北变化，最远可达四川、陕西、山西和河北北部等地区。结论 GARP模型预测斑体花蜱在我国适生区较为可靠，斑体花蜱在我国存在大量适生区，相关部门应进行针对性的预防。

关键词: 斑体花蜱, 规则集遗传算法模型, 生物入侵, 地理信息系统

CLC Number:

R384.4

MA De-long, LI Chao, ZHOU Ruo-bing, LI Wen-yu, LI Wen, GAO Yuan, WANG Jun, LIU Qi-yong, ZHANG Qin-feng. Projection of suitable region for Amblyomma maculatum distribution in China using the genetic algorithm for rule-set prediction model[J]. Chinese Journal of Vector Biology and Control, 2022, 33(2): 262-267.

马德龙, 李超, 周若冰, 李文玉, 李文, 高源, 王君, 刘起勇, 张钦凤. 基于规则集遗传算法模型的斑体花蜱在中国适生区预估[J]. 中国媒介生物学及控制杂志, 2022, 33(2): 262-267.

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