Literature DB >> 29330057

Fixation and absorption in a fluctuating environment.

Matan Danino1, Nadav M Shnerb2.   

Abstract

A fundamental problem in the fields of population genetics, evolution, and community ecology, is the fate of a single mutant, or invader, introduced in a finite population of wild types. For a fixed-size community of N individuals, with Markovian, zero-sum dynamics driven by stochastic birth-death events, the mutant population eventually reaches either fixation or extinction. The classical analysis, provided by Kimura and his coworkers, is focused on the neutral case, [where the dynamics is only due to demographic stochasticity (drift)], and on time-independent selective forces (deleterious/beneficial mutation). However, both theoretical arguments and empirical analyses suggest that in many cases the selective forces fluctuate in time (temporal environmental stochasticity). Here we consider a generic model for a system with demographic noise and fluctuating selection. Our system is characterized by the time-averaged (log)-fitness s0 and zero-mean fitness fluctuations. These fluctuations, in turn, are parameterized by their amplitude γ and their correlation time δ. We provide asymptotic (large N) formulas for the chance of fixation, the mean time to fixation and the mean time to absorption. Our expressions interpolate correctly between the constant selection limit γ → 0 and the time-averaged neutral case s0=0.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Keywords:  Absorption; Demographic stochasticity; Drift; Environmental stochasticity; Evolution; Fixation; Selection

Mesh:

Year:  2018        PMID: 29330057     DOI: 10.1016/j.jtbi.2018.01.004

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  4 in total

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3.  Noise-induced stabilization and fixation in fluctuating environment.

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Journal:  Sci Rep       Date:  2018-06-27       Impact factor: 4.379

4.  How the storage effect and the number of temporal niches affect biodiversity in stochastic and seasonal environments.

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  4 in total

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