Natural enemies deployment in patchy environments for augmentative biological control - Université Pierre et Marie Curie Accéder directement au contenu
Article Dans Une Revue Applied Mathematics and Computation Année : 2015

Natural enemies deployment in patchy environments for augmentative biological control

Résumé

Biological control is an important tool for ecologically friendly crop protection against pests, that consists in using a biological organism (predator, parasitoid, pathogen) to reduce the population density of the targeted pest. We examine the effectiveness of periodic impulsive releases of biocontrol agents (beneficial species) into a two-patch environment through mathematical modeling. In this paper, we consider a spatio-temporal Lotka–Volterra pest–predator system defined over two patches. We show that the threshold predator release rate guaranteeing the stability of the pest-free solution is actually independent of the release period when predators in both patches follow balanced dynamics or pests do not disperse. Otherwise, the stability threshold becomes period-dependent and more specifically it is an increasing function of the release period. This implies that the deployment of biological control agents at a given release rate can possibly succeed if releases are frequent and small and fail otherwise. In the various cases we also show what the optimal strategy is that minimizes the total release rate or how to spread a given release rate between the two patches.
Fichier principal
Vignette du fichier
AMC-R1.pdf (427.49 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-01171118 , version 1 (29-03-2022)

Identifiants

Citer

Bapan Ghosh, Frédéric Grognard, Ludovic Mailleret. Natural enemies deployment in patchy environments for augmentative biological control. Applied Mathematics and Computation, 2015, 266 (1), pp.982-999. ⟨10.1016/j.amc.2015.06.021⟩. ⟨hal-01171118⟩
186 Consultations
45 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More