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Record W2024730688 · doi:10.1098/rspb.2002.2224

Genetic and plastic responses of a northern mammal to climate change

2003· article· en· W2024730688 on OpenAlexaffabout
Denis Réale, Andrew G. McAdam, Stan Boutin, Dominique Berteaux

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsUniversité du Québec à RimouskiUniversity of AlbertaMcGill University
Fundersnot available
KeywordsBiologyTraitPopulationPhenotypic plasticitySelection (genetic algorithm)Climate changeEcologyHeritabilityZoologyEvolutionary biologyDemography

Abstract

fetched live from OpenAlex

Climate change is predicted to be most severe in northern regions and there has been much interest in to what extent organisms can cope with these changes through phenotypic plasticity or microevolutionary processes. A red squirrel population in the southwest Yukon, Canada, faced with increasing spring temperatures and food supply has advanced the timing of breeding by 18 days over the last 10 years (6 days per generation). Longitudinal analysis of females breeding in multiple years suggests that much of this change in parturition date can be explained by a plastic response to increased food abundance (3.7 days per generation). Significant changes in breeding values (0.8 days per generation), were in concordance with predictions from the breeder's equation (0.6 days per generation), and indicated that an evolutionary response to strong selection favouring earlier breeders also contributed to the observed advancement of this heritable trait. The timing of breeding in this population of squirrels, therefore, has advanced as a result of both phenotypic changes within generations, and genetic changes among generations in response to a rapidly changing environment.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.038
GPT teacher head0.255
Teacher spread0.217 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations511
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Royal Society B Biological SciencesSame topicAnimal Ecology and Behavior StudiesFrench-language works237,207