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Record W2131641433 · doi:10.1098/rspb.2009.1960

Kin selection in Columbian ground squirrels ( <i>Urocitellus columbianus</i> ): littermate kin provide individual fitness benefits

2009· article· en· W2131641433 on OpenAlexaff
Vincent A. Viblanc, Coline M. Arnaud, F. Stephen Dobson, Jan O. Murie

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsKin selectionKin recognitionInclusive fitnessSocialityPhilopatryBurrowBiologyEcologyReproductive successDemographyBiological dispersalSociologyPopulation

Abstract

fetched live from OpenAlex

Since W. D. Hamilton's seminal work on the evolution of sociality, a large body of research has accumulated on how kin selection might explain the evolution of cooperation in many group-living species. Our study examined the evolutionary basis of philopatry and cooperation; specifically, whether individuals benefit from the presence of close kin. We applied an individual fitness approach to a 16-year study of Columbian ground squirrels (Urocitellus columbianus) to investigate potential causal paths by which the presence of kin might act on individual fitness. Our results indicate that individual fitness benefits resulted from associations of philopatric female kin, and support the hypothesis that increased tolerance of proximity of kin is a proximate mechanism for these benefits. The major life-history influence of kin on individual fitness was through improved reproductive success, and this benefit may have been owing to philopatric settlement of kin that were recognized through familiarization in the natal burrow. Thus, we demonstrated an evolutionary basis necessary for ongoing kin-selected cooperation in Columbian ground squirrels, though the mechanism of familiarity may determine which kin individuals benefit from cooperative behaviours.

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 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)0.001
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 score0.006
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.027
GPT teacher head0.241
Teacher spread0.215 · 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 teacher head, 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

Citations50
Published2009
Admission routes1
Has abstractyes

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