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Record W2163664748 · doi:10.1093/beheco/arr158

Spatial variation in food availability predicts extrapair paternity in the arctic fox

2011· article· en· W2163664748 on OpenAlexaffabout
Cassandra Cameron, Dominique Berteaux, France Dufresne

Bibliographic record

VenueBehavioral Ecology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsCenter for Northern StudiesUniversité du Québec à RimouskiAboriginal Affairs Northern Dev Canada
Fundersnot available
KeywordsBiologyMating systemVulpesPopulationArctic foxEcologyArcticMatingLagopusIntraspecific competitionZoologyDemographyPredation

Abstract

fetched live from OpenAlex

Extrapair paternity (EPP) is described in many socially monogamous species, but within-population variability in its frequency is poorly documented. Availability and distribution of food may influence polyandrous behaviors, either directly by affecting the need for paternal care or indirectly via their effect on population density. We quantified the frequency of EPP in a population of arctic foxes (Vulpes lagopus), a predominantly socially monogamous species with high paternal investment. We then tested whether spatial (presence of a goose colony) and temporal (cycles of lemmings) variations in food availability were linked to variations in mating systems within the population. From 2003 to 2008, we studied the mating systems of arctic foxes on Bylot Island (Nunavut, Canada) by combining molecular analyses with behavioral observations during cub rearing. Although the dominant social mating system was monogamy, at least 31% of cubs with known social father were born from extrapair matings (in 10 of 38 litters sampled). Likelihood of EPP was associated with food availability. It was greatest (86%) at the center of the goose colony and decreased sharply with increasing distance from it. EPP can thus be frequent in the socially monogamous arctic fox, and intraspecific variability in extrapair matings is strongly correlated with food availability during cub rearing.

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 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 score0.123
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.045
GPT teacher head0.242
Teacher spread0.197 · 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

Citations44
Published2011
Admission routes2
Has abstractyes

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