田间大豆蚜季节性种群动态的模型拟合

doi:10.1016/j.jia.2023.02.021

Journal of Integrative Agriculture ›› 2023, Vol. 22 ›› Issue (6): 1797-1808.DOI: 10.1016/j.jia.2023.02.021

田间大豆蚜季节性种群动态的模型拟合

收稿日期:2022-07-12 修回日期:2023-02-17 接受日期:2022-11-21 出版日期:2023-06-20 发布日期:2022-11-21

Model fitting of the seasonal population dynamics of the soybean aphid, Aphis glycines Matsumura, in the field

XU Lei¹, ZHAO Tong-hua¹, Xing Xing², XU Guo-qing^1#, XU Biao², ZHAO Ji-qiu¹

¹Institute of Plant Protection, Liaoning Academy of Agricultural Sciences, Shenyang 110161, P.R.China
²Agricultural Technology Extension Center of Xiuyan Manchu Autonomous County, Anshan 114300, P.R.China

Received:2022-07-12 Revised:2023-02-17 Accepted:2022-11-21 Online:2023-06-20 Published:2022-11-21
About author:XU Lei, E-mail: syxlei81@hotmail.com; #Correspondence XU Guo-qing, Tel: +86-24-31021234, Fax: +86-24-88419895, E-mail: ylzwch@hotmail.com
Supported by:
This study was supported by the Chinese National Special Fund for Agro-scientific Research in the Public Interest (201003025 and 201103022), the National Key Research and Development Program of China (2018YFD0201004) and the Discipline Construction Project of Liaoning Academy of Agricultural Sciences, China (2019DD082612).

摘要/Abstract

摘要：

大豆蚜虫是大豆生产中的最大威胁之一，其种群动态的趋势性及周期性分析对害虫综合治理（IPM）具有重要意义。本研究在对田间大豆蚜种群系统调查（2018–2020）的基础上，首次采用反Logistic模型，同时结合经典Logistic模型，描述了大豆蚜从田间定殖到绝迹的季节性种群消长规律。通过计算模型的拐点，划分了种群波动的递增和递减阶段，直观地呈现出不同年份大豆蚜虫种群的季节性变化趋势。此外，首次建立了田间大豆蚜量随时间以及相关环境因子变化的多元Logistic模型，可以根据气象数据预测对应时间下的瞬时蚜量。总体而言，本研究方法的成功运用可为实践中的大豆蚜虫IPM策略提供理论框架

Abstract:

The soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), is one of the greatest threats to soybean production, and both trend analysis and periodic analysis of its population dynamics are important for integrated pest management (IPM). Based on systematically investigating soybean aphid populations in the field from 2018 to 2020, this study adopted the inverse logistic model for the first time, and combined it with the classical logistic model to describe the changes in seasonal population abundance from colonization to extinction in the field. Then, the increasing and decreasing phases of the population fluctuation were divided by calculating the inflection points of the models, which exhibited distinct seasonal trends of the soybean aphid populations in each year. In addition, multifactor logistic models were then established for the first time, in which the abundance of soybean aphids in the field changed with time and relevant environmental conditions. This model enabled the prediction of instantaneous aphid abundance at a given time based on relevant meteorological data. Taken as a whole, the successful approaches implemented in this study could be used to build a theoretical framework for practical IPM strategies for controlling soybean aphids.

Key words: soybean aphid , population dynamics , logistic model , inverse logistic model , multifactor logistic model

XU Lei, ZHAO Tong-hua, XING Xing, XU Guo-qing, XU Biao, ZHAO Ji-qiu. 田间大豆蚜季节性种群动态的模型拟合[J]. Journal of Integrative Agriculture, 2023, 22(6): 1797-1808.

XU Lei, ZHAO Tong-hua, Xing Xing, XU Guo-qing, XU Biao, ZHAO Ji-qiu.

Model fitting of the seasonal population dynamics of the soybean aphid, Aphis glycines Matsumura, in the field [J]. Journal of Integrative Agriculture, 2023, 22(6): 1797-1808.

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田间大豆蚜季节性种群动态的模型拟合

Model fitting of the seasonal population dynamics of the soybean aphid, Aphis glycines Matsumura, in the field

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