A numerical approach to determine mutant invasion fitness and evolutionary singular strategies - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Theoretical Population Biology Année : 2017

A numerical approach to determine mutant invasion fitness and evolutionary singular strategies

Résumé

We propose a numerical approach to study the invasion fitness of a mutant and to determine evolutionary singular strategies in evolutionary structured models in which the competitive exclusion principle holds. Our approach is based on a dual representation, which consists of the modelling of the small size mutant population by a stochastic model and the computation of its corresponding deterministic model. The use of the deterministic model greatly facilitates the numerical determination of the feasibility of invasion as well as the convergence-stability of the evolutionary singular strategy. Our approach combines standard adaptive dynamics with the link between the mutant survival criterion in the stochastic model and the sign of the eigenvalue in the corresponding deterministic model. We present our method in the context of a mass-structured individual-based chemostat model. We exploit a previously derived mathematical relationship between stochastic and deterministic representations of the mutant population in the chemostat model to derive a general numerical method for analyzing the invasion fitness in the stochastic models. Our method can be applied to the broad class of evolutionary models for which a link between the stochastic and deterministic invasion fitnesses can be established.
Fichier principal
Vignette du fichier
manuscript.pdf (950.11 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-01413638 , version 1 (12-12-2016)
hal-01413638 , version 2 (23-05-2017)

Identifiants

Citer

Coralie Fritsch, Fabien Campillo, Otso Ovaskainen. A numerical approach to determine mutant invasion fitness and evolutionary singular strategies. Theoretical Population Biology, 2017, 115, pp.89-99. ⟨10.1016/j.tpb.2017.05.001⟩. ⟨hal-01413638v2⟩
544 Consultations
348 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More