A Rosenzweig-MacArthur pest-plant model for information-driven farmer control of coffee berry borer

We develop a behavioural pest-plant model to investigate how farmers’ information-driven decisions affect the control of coffee berry borer (CBB) infestations, a major cause of yield losses in coffee production worldwide. Starting from a Rosenzweig-MacArthur predator-prey framework in which coffee berry biomass and the CBB population play the role of prey and predator, we introduce an information-dependent killing rate that represents voluntary pest-control actions triggered by perceived infestation. The qualitative analysis shows that co-existence equilibria arise only when the pest reproduction number Rpest exceeds one; notably, Rpest is independent of the information-related parameters. Consequently, information-driven actions alone cannot reduce Rpest below one and thus cannot eradicate the infestation. We then use numerical simulations to assess the impact of information coverage and reactivity on coffee berry biomass and pest abundance, showing that information-induced farmers’ actions may dampen and, for sufficiently strong responses, suppress the sustained oscillations exhibited by the baseline Rosenzweig-MacArthur model.