Weak Selection and the Separation of Eco-evo Time Scales using Perturbation Analysis.


Journal

Bulletin of mathematical biology
ISSN: 1522-9602
Titre abrégé: Bull Math Biol
Pays: United States
ID NLM: 0401404

Informations de publication

Date de publication:
19 03 2022
Historique:
received: 14 09 2021
accepted: 22 02 2022
entrez: 19 3 2022
pubmed: 20 3 2022
medline: 6 4 2022
Statut: epublish

Résumé

We show that under the assumption of weak frequency-dependent selection a wide class of population dynamical models can be analysed using perturbation theory. The inner solution corresponds to the ecological dynamics, where to zeroth order, the genotype frequencies remain constant. The outer solution provides the evolutionary dynamics and corresponds, to zeroth order, to a generalisation of the replicator equation. We apply this method to a model of public goods dynamics and construct, using matched asymptotic expansions, a composite solution valid for all times. We also analyse a Lotka-Volterra model of predator competition and show that to zeroth order the fraction of wild-type predators follows a replicator equation with a constant selection coefficient given by the predator death rate. For both models, we investigate how the error between approximate solutions and the solution to the full model depend on the order of the approximation and show using numerical comparison, for [Formula: see text] and 2, that the error scales according to [Formula: see text], where [Formula: see text] is the strength of selection and k is the order of the approximation.

Identifiants

pubmed: 35305188
doi: 10.1007/s11538-022-01009-3
pii: 10.1007/s11538-022-01009-3
pmc: PMC8934331
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

52

Informations de copyright

© 2022. The Author(s).

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Auteurs

Philip Gerlee (P)

Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden. gerlee@chalmers.se.
Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden. gerlee@chalmers.se.

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Classifications MeSH