Dynamics for a non-autonomous fall armyworm-maize interaction model with a saturation functional response

Area of Science:

• Mathematical modeling of ecological systems
• Agricultural entomology
• Pest management

Background:

• Maize is a globally significant crop, vulnerable to fall armyworm (Spodoptera frugiperda) infestations.
• Seasonal variations critically influence pest-host dynamics, impacting agricultural yields.
• Understanding these dynamics is crucial for effective pest control strategies.

Purpose of the Study:

• To develop and analyze a non-autonomous mathematical model for fall armyworm-maize interactions in a periodic environment.
• To investigate the impact of seasonal variations on pest population dynamics.
• To evaluate the efficacy of time-dependent control strategies for managing fall armyworm populations.

Main Methods:

• Development of a non-autonomous mathematical model incorporating a Holling type II functional response.
• Analysis of the basic model's dynamical behaviors: positive invariance, boundedness, permanence, global stability, and non-persistence.
• Incorporation of time-dependent controls representing traditional methods and chemical insecticides.

Main Results:

• Seasonal variations significantly influence the population dynamics of all fall armyworm life stages (egg, larvae, pupae, moth).
• Optimal control strategies effectively reduce fall armyworm population sizes across various scenarios.
• In specific scenarios, optimal control measures can lead to the complete elimination of fall armyworm populations.

Conclusions:

• The developed model provides a robust framework for understanding fall armyworm-maize interactions under seasonal influences.
• Optimal control strategies are essential for mitigating fall armyworm outbreaks and protecting maize production.
• The study highlights the potential for integrated pest management approaches combining different control methods.