ArticleJournal of mathematical biology2018
Frequency-dependent growth in class-structured populations: continuous dynamics in the limit of weak selection.
Article in Journal of mathematical biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 13 citations in OpenAlex.
- Towards a replicator dynamics model of age structured populations.Journal of mathematical biology · 2021Article
- Diffusion approximation for an age-class-structured population under viability and fertility selection with application to fixation probability of an advantageous mutant.Journal of mathematical biology · 2019Article
- A mathematical formalism for natural selection with arbitrary spatial and genetic structure.Journal of mathematical biology · 2019Article
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2 authors at 1 institution in 1 country.
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Abstract
In this paper we consider class-structured populations in discrete time in the limit of weak selection and with the inverse of the intensity of selection as unit of time. The aim is to establish a continuous model that approximates the discrete model. More precisely, we study frequency-dependent growth in an infinite haploid population structured into a finite number of classes such that individuals in each class contribute to a given subset of classes from one time step to the next. These contributions take the form of generalized fecundity parameters with perturbations of order 1 / N that depends on the class frequencies of each type and the type frequencies. Moreover, they satisfy some mild conditions that ensure mixing in the long run. The dynamics in the limit as [Formula: see text] with N time steps as unit of time is considered first in the case of a single type, and second in the case of multiple types. The main result is that the type frequencies as [Formula: see text] obey the replicator equation with instantaneous growth rates for the different types that depend only on instantaneous equilibrium class frequencies and reproductive values. An application to evolutionary game theory complemented by simulation results is presented.
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