Evidence map›Paper›PMID 31002665›Full record

ArticlePLoS computational biology2019

Fluctuating environments select for short-term phenotypic variation leading to long-term exploration.

Rosangela Canino-Koning, Michael J Wiser, Charles Ofria

Abstract read
In one paragraph

Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. The variability of evolvability: Properties of dynamic fitness landscapes determine how phenotypic variability evolves.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  2. Evolution takes multiple paths to evolvability when facing environmental change.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Evolution in alternating environments with tunable interlandscape correlations.Evolution; international journal of organic evolution · 2021
    Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Rosangela Canino-KoningDepartment of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA.ORCID 0000-0002-7536-7750
Michael J WiserBEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI, USA.ORCID 0000-0003-1686-9272
Charles OfriaDepartment of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic spaces are often described in terms of fitness landscapes or genotype-to-phenotype maps, where each genetic sequence is associated with phenotypic properties and linked to other genotypes that are a single mutational step away. The positions close to a genotype make up its "mutational landscape" and, in aggregate, determine the short-term evolutionary potential of a population. Populations with wider ranges of phenotypes in their mutational neighborhood are known to be more evolvable. Likewise, those with fewer phenotypic changes available in their local neighborhoods are more mutationally robust. Here, we examine whether forces that change the distribution of phenotypes available by mutation profoundly alter subsequent evolutionary dynamics. We compare evolved populations of digital organisms that were subject to either static or cyclically-changing environments. For each of these, we examine diversity of the phenotypes that are produced through mutations in order to characterize the local genotype-phenotype map. We demonstrate that environmental change can push populations toward more evolvable mutational landscapes where many alternate phenotypes are available, though purely deleterious mutations remain suppressed. Further, we show that populations in environments with harsh changes switch phenotypes more readily than those in environments with more benign changes. We trace this effect to repeated population bottlenecks in the harsh environments, which result in shorter coalescence times and keep populations in regions of the mutational landscape where the phenotypic shifts in question are more likely to occur. Typically, static environments select solely for immediate optimization, at the expensive of long-term evolvability. In contrast, we show that with changing environments, short-term pressures to deal with immediate challenges can align with long-term pressures to explore a more productive portion of the mutational landscape.

Indexed as

Biological Variation, PopulationGene-Environment InteractionModels, GeneticComputational BiologyComputer SimulationEnvironmentEvolution, MolecularGenetic FitnessGenetics, PopulationMutationPhylogenySoftware

Identifiers

PMID31002665
PMCPMC6474582

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.