Modeling and forecasting the climate-driven dynamics of Spodoptera frugiperda in maize: a mathematical and numerical study

Abstract

The fall armyworm Spodoptera frugiperda, hereafter referred to as FAW, is one of the most destructive invasive pests affecting maize production in sub-Saharan Africa. Understanding how climatic variability influences its population dynamics is essential for improving pest monitoring and management strategies. In this study, we develop and analyze a stage-structured mathematical model describing the population dynamics of the pest across its four developmental stages (eggs, larvae, pupae, and adults). We first investigate a baseline model with constant parameters, which allows a complete mathematical analysis of the system. A threshold quantity governing pest extinction or persistence is derived, and sensitivity analysis identifies the biological parameters that most strongly influence population growth. These results provide theoretical insights into which life stages represent the most effective targets for control strategies. We then extend the framework to incorporate climate-driven dynamics through temperature- and rainfall-dependent parameters. Using climatic observations from Pretoria (South Africa), we examine how seasonal environmental variability affects pest persistence. The analysis leads to the identification of two climate-dependent thresholds, R₀^min and R₀^max, which determine whether the pest population disappears or persists through periodic seasonal oscillations. Numerical simulations illustrate how climatic forcing can generate contrasting invasion scenarios and reproduce realistic seasonal patterns of pest abundance. Overall, the proposed framework highlights the central role of climatic variability in shaping FAW population dynamics and demonstrates how climate-informed mathematical models can serve as predictive tools for agricultural pest monitoring and integrated pest management.