A system dynamics model for predicting African armyworm occurrence and population dynamics

This study develops a comprehensive system dynamics model to predict and manage African armyworm (Spodoptera exempta) outbreaks, a major threat to cereal crops across Africa. We applied system dynamics approache with its archetypes (causal loop diagram (CLD), reinforcing (R) and balancing (B)) to analyse the population dynamics of the pest. The VENSIM modelling platform (Ventana Systems Inc., DSS 8.2) was used to implement the models and carry out the simulations. The research integrates extensive data from 1980 to 2023, encompassing the African armyworm's life cycle stages, climatic variables, and intervention strategies, to simulate potential outbreak scenarios and evaluate the impacts of various control measures. The model demonstrates the ability to accurately capture the solitary and gregarious phases of the armyworm, showing how different climatic conditions influence these phases and affect the outbreak patterns across various African regions. The findings reveal that precipitation and humidity are critical factors affecting African armyworm outbreaks, with variations in these elements significantly influencing the pest population dynamics. Scenario analysis within the model indicates that integrated pest management (IPM) strategies, which combine biological control, cultural practices, and chemical methods, can effectively reduce armyworm populations, and mitigate crop damage. This approach not only helps manage current infestations but also contributes to sustainable agricultural practices by reducing reliance on chemical pesticides. The simulations of the model provide insights into the timing and intensity of armyworm outbreaks and illustrate how different interventions can alter these dynamics. For instance, the study highlights the effectiveness of early intervention and the potential consequences of delayed action, underscoring the importance of timely and informed decision-making in pest management. This research advances the understanding of African armyworm ecology and management by providing an approach that can predict outbreaks and evaluate the effectiveness of various control strategies under different climatic conditions. By incorporating real-world data and simulating realistic scenarios, the model offers a valuable resource for researchers, policymakers, and farmers in developing targeted, effective, and sustainable pest management strategies. This study stands out for its unique integration of biological, ecological, and IPM strategies, providing a holistic approach to addressing the challenges posed by S. exempta outbreaks in Africa. The implications of this work are significant, offering potential to enhance food security and economic stability in regions affected by the African armyworm, thereby supporting broader efforts to manage agricultural pests in a changing global climate.