Quantifying evolutionary rescue probabilities upon standing genetic variation and <i>de novo</i> mutations

This study quantifies the probabilities of evolutionary rescue (ER) in populations facing abrupt environmental changes. We consider a population of asexual haploid individuals that evolves without recombination. The research integrates standing genetic variation and de novo mutations within a framework beyond traditional single-locus models. Utilizing Fisher's geometric model and a combination of analytical derivations and stochastic simulations, the study examines how the likelihood of ER is influenced by factors such as the number of traits, the magnitude of environmental change, and the interplay between preexisting genetic variation and newly arising mutations. The results provide insights into the governing factors of ER, including the roles of mutation effect size and probability.

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Publication Details

Journal
Physical review. E
Published
2025-06-24
DOI
https://doi.org/10.1103/f5c1-rpc4
Primary Topic
Evolution and Genetic Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Quantifying evolutionary rescue probabilities upon standing genetic variation and de novo mutations

Paulo R. A. Campos
Physical review. E
Evolution and Genetic Dynamics
article

Quantifying evolutionary rescue probabilities upon standing genetic variation and de novo mutations

Paulo R. A. Campos
article en

Abstract

This study quantifies the probabilities of evolutionary rescue (ER) in populations facing abrupt environmental changes. We consider a population of asexual haploid individuals that evolves without recombination. The research integrates standing genetic variation and de novo mutations within a framework beyond traditional single-locus models. Utilizing Fisher's geometric model and a combination of analytical derivations and stochastic simulations, the study examines how the likelihood of ER is influenced by factors such as the number of traits, the magnitude of environmental change, and the interplay between preexisting genetic variation and newly arising mutations. The results provide insights into the governing factors of ER, including the roles of mutation effect size and probability.

Physical review. EVol. 112(1)
Universidade Federal de Pernambuco (BR)
Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco
Openalex Percentile: Top 83%
Evolution and Genetic Dynamics
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