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

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.

Keywords

• soybean aphid
• population dynamics
• logistic model
• inverse logistic model
• multifactor logistic model