Literature DB >> 27868195

Predicting patterns of long-term adaptation and extinction with population genetics.

J Bertram1, K Gomez2, J Masel1.   

Abstract

Population genetics struggles to model extinction; standard models track the relative rather than absolute fitness of genotypes, while the exceptions describe only the short-term transition from imminent doom to evolutionary rescue. But extinction can result from failure to adapt not only to catastrophes, but also to a backlog of environmental challenges. We model long-term adaptation to long series of small challenges, where fitter populations reach higher population sizes. The population's long-term fitness dynamic is well approximated by a simple stochastic Markov chain model. Long-term persistence occurs when the rate of adaptation exceeds the rate of environmental deterioration for some genotypes. Long-term persistence times are consistent with typical fossil species persistence times of several million years. Immediately preceding extinction, fitness declines rapidly, appearing as though a catastrophe disrupted a stably established population, even though gradual evolutionary processes are responsible. New populations go through an establishment phase where, despite being demographically viable, their extinction risk is elevated. Should the population survive long enough, extinction risk later becomes constant over time.
© 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Entities:  

Keywords:  Cost of selection; Red Queen; eco-evolutionary dynamics; genetic load; reverse-time Markov chain

Mesh:

Year:  2016        PMID: 27868195     DOI: 10.1111/evo.13116

Source DB:  PubMed          Journal:  Evolution        ISSN: 0014-3820            Impact factor:   3.694


  2 in total

1.  Mutation bias can shape adaptation in large asexual populations experiencing clonal interference.

Authors:  Kevin Gomez; Jason Bertram; Joanna Masel
Journal:  Proc Biol Sci       Date:  2020-10-21       Impact factor: 5.349

2.  Evolutionary Rescue Through Partly Heritable Phenotypic Variability.

Authors:  Oana Carja; Joshua B Plotkin
Journal:  Genetics       Date:  2019-01-29       Impact factor: 4.562

  2 in total

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