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Record W2032802709 · doi:10.1093/beheco/ari035

Reproductive consequences of natal dispersal in a highly philopatric seabird

2005· article· en· W2032802709 on OpenAlexafffund
Ulrich K. Steiner, Anthony J. Gaston

Bibliographic record

VenueBehavioral Ecology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsCarleton University
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsBiological dispersalBiologyPhilopatryReproductive successInbreedingInbreeding avoidanceEcologySeabirdPopulationZoologyMate choiceDemographyMating

Abstract

fetched live from OpenAlex

Natal and breeding dispersal have a major impact on gene flow and population structure. We examined the consequences of natal dispersal on the reproductive success (proportion of pairs rearing chicks) of colonial-breeding Thick-billed murres (Uria lomvia). Reproductive success increased with distance dispersed for the first and second breeding attempt. The increase in breeding success leveled off at natal dispersal distances above 7 m. Our results were consistent with the idea that the relationship between dispersal and reproductive success is caused by site availability and mate choice as birds willing to disperse farther had a greater choice of potential sites and mates. This hypothesis was supported by the fact that birds dispersing farther were more likely to pair with an experienced breeder, which increases the likelihood of breeding success for young breeders. Explanations for increasing breeding success with increased dispersal based on inbreeding effects were unlikely because most breeding failures were caused by egg loss rather than infertility or nestling death. However, we could not explain why >50% of birds return within 3 m of the natal site, despite having an up to 50% lower reproductive success than birds dispersing 7 m or more.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.997

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.020
GPT teacher head0.279
Teacher spread0.259 · 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.

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

Citations48
Published2005
Admission routes2
Has abstractyes

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