ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2013
The probability of evolutionary rescue: towards a quantitative comparison between theory and evolution experiments.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
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Who cites it
59 citing papers in PubMed.
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- "Excluded phenotypes" restrict genetic paths toward adaptation in declining populations.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Effectiveness of CRISPR-Cas in sensitizing bacterial populations with plasmid-encoded antimicrobial resistance.Genetics · 2025Article
- Founders predict trait evolution and population performance after evolutionary rescue in the red flour beetle.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
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- The speed of vaccination rollout and the risk of pathogen adaptation.Journal of the Royal Society, Interface · 2025Article
- Evolutionary rescue of bacterial populations by heterozygosity on multicopy plasmids.Journal of mathematical biology · 2025Article
- Impacts of limits to adaptation on population and community persistence in a changing environment.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Review
- The many dimensions of combination therapy: How to combine antibiotics to limit resistance evolution.Evolutionary applications · 2024Article
- Temperature dependence of the mutation rate towards antibiotic resistance.JAC-antimicrobial resistance · 2024Article
- Evolutionary rescue in resistance to pesticides.Proceedings. Biological sciences · 2024Article
- Building pyramids against the evolutionary emergence of pathogens.Proceedings. Biological sciences · 2024Article
- Demographic feedbacks during evolutionary rescue can slow or speed adaptive evolution.Proceedings. Biological sciences · 2024Article
- Quantifying stochastic establishment of mutants in microbial adaptation.Microbiology (Reading, England) · 2023Review
- Evolutionary rescue in a fluctuating environment: periodic versus quasi-periodic environmental changes.Proceedings. Biological sciences · 2023Article
- On the capacity for rapid adaptation and plastic responses to herbivory and intraspecific competition in insular populations ofEvolutionary applications · 2022Article
- How will mosquitoes adapt to climate warming?eLife · 2021Article
- Article
- Stochastic bacterial population dynamics restrict the establishment of antibiotic resistance from single cells.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
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5 authors.
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Abstract
Evolutionary rescue occurs when a population genetically adapts to a new stressful environment that would otherwise cause its extinction. Forecasting the probability of persistence under stress, including emergence of drug resistance as a special case of interest, requires experimentally validated quantitative predictions. Here, we propose general analytical predictions, based on diffusion approximations, for the probability of evolutionary rescue. We assume a narrow genetic basis for adaptation to stress, as is often the case for drug resistance. First, we extend the rescue model of Orr & Unckless (Am. Nat. 2008 172, 160-169) to a broader demographic and genetic context, allowing the model to apply to empirical systems with variation among mutation effects on demography, overlapping generations and bottlenecks, all common features of microbial populations. Second, we confront our predictions of rescue probability with two datasets from experiments with Saccharomyces cerevisiae (yeast) and Pseudomonas fluorescens (bacterium). The tests show the qualitative agreement between the model and observed patterns, and illustrate how biologically relevant quantities, such as the per capita rate of rescue, can be estimated from fits of empirical data. Finally, we use the results of the model to suggest further, more quantitative, tests of evolutionary rescue theory.
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