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Eco‐evolutionary effects on population recovery following catastrophic disturbance

2011· article· en· W1678464877 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEvolutionary Applications · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsMcGill UniversityDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsBiologyDisturbance (geology)Evolutionary dynamicsPopulationNatural selectionMicroevolutionExperimental evolutionEcologyPersistence (discontinuity)Threatened speciesAdaptation (eye)TraitGenetic FitnessStatus quoEvolutionary biologyBiological evolutionDemographyGenetics

Abstract

fetched live from OpenAlex

Fine-scale genetic diversity and contemporary evolution can theoretically influence ecological dynamics in the wild. Such eco-evolutionary effects might be particularly relevant to the persistence of populations facing acute or chronic environmental change. However, experimental data on wild populations is currently lacking to support this notion. One way that ongoing evolution might influence the dynamics of threatened populations is through the role that selection plays in mediating the 'rescue effect', the ability of migrants to contribute to the recovery of populations facing local disturbance and decline. Here, we combine experiments with natural catastrophic events to show that ongoing evolution is a major determinant of migrant contributions to population recovery in Trinidadian guppies (Poecilia reticulata). These eco-evolutionary limits on migrant contributions appear to be mediated by the reinforcing effects of natural and sexual selection against migrants, despite the close geographic proximity of migrant sources. These findings show that ongoing adaptive evolution can be a double-edged sword for population persistence, maintaining local fitness at a cost to demographic risk. Our study further serves as a potent reminder that significant evolutionary and eco-evolutionary dynamics might be at play even where the phenotypic status quo is largely maintained generation to generation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.213
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it