ArticleGenetics2018
Evolutionary Rescue over a Fitness Landscape.
Article in Genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed.
- "Excluded phenotypes" restrict genetic paths toward adaptation in declining populations.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Alternative Mutational Architectures Producing Identical M-Matrices can Lead to Different Patterns of Evolutionary Divergence.Genome biology and evolution · 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
- Lethal mutagenesis and the transient within-host dynamics of viral adaptation.Virus evolution · 2025Article
- Demographic feedbacks during evolutionary rescue can slow or speed adaptive evolution.Proceedings. Biological sciences · 2024Article
- Evolutionary rescue on genotypic fitness landscapes.Journal of the Royal Society, Interface · 2023Article
- Evolutionary Pathways and Trajectories in Antibiotic Resistance.Clinical microbiology reviews · 2021Article
- Drug-induced resistance evolution necessitates less aggressive treatment.PLoS computational biology · 2021Article
- Predicting population genetic change in an autocorrelated random environment: Insights from a large automated experiment.PLoS genetics · 2021Article
- A simple completion of Fisher's fundamental theorem of natural selection.Ecology and evolution · 2021Article
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- Environmental fluctuations can promote evolutionary rescue in high-extinction-risk scenarios.Proceedings. Biological sciences · 2020Article
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- Evolutionary tracking is determined by differential selection on demographic rates and density dependence.Ecology and evolution · 2020Article
- Genetic Paths to Evolutionary Rescue and the Distribution of Fitness Effects Along Them.Genetics · 2020Article
- Evolutionary Rescue of an EnvironmentalFrontiers in microbiology · 2020Article
- Environmental pleiotropy and demographic history direct adaptation under antibiotic selection.Heredity · 2018Article
- The probability of evolutionary rescue: towards a quantitative comparison between theory and evolution experiments.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2013Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Evolutionary rescue describes a situation where adaptive evolution prevents the extinction of a population facing a stressing environment. Models of evolutionary rescue could in principle be used to predict the level of stress beyond which extinction becomes likely for species of conservation concern, or, conversely, the treatment levels most likely to limit the emergence of resistant pests or pathogens. Stress levels are known to affect both the rate of population decline (demographic effect) and the speed of adaptation (evolutionary effect), but the latter aspect has received less attention. Here, we address this issue using Fisher's geometric model of adaptation. In this model, the fitness effects of mutations depend both on the genotype and the environment in which they arise. In particular, the model introduces a dependence between the level of stress, the proportion of rescue mutants, and their costs before the onset of stress. We obtain analytic results under a strong-selection-weak-mutation regime, which we compare to simulations. We show that the effect of the environment on evolutionary rescue can be summarized into a single composite parameter quantifying the effective stress level, which is amenable to empirical measurement. We describe a narrow characteristic stress window over which the rescue probability drops from very likely to very unlikely as the level of stress increases. This drop is sharper than in previous models, as a result of the decreasing proportion of stress-resistant mutations as stress increases. We discuss how to test these predictions with rescue experiments across gradients of stress.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.