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Record W1997032028 · doi:10.1007/s00300-011-1030-1

Age-dependent genetic structure of arctic foxes in Svalbard

2011· article· en· W1997032028 on OpenAlexafffund
Dorothée Ehrich, Lindsey Carmichael, Eva Fuglei

Bibliographic record

VenuePolar Biology · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaNorsk PolarinstituttNorges Forskningsråd
KeywordsBiologyBiological dispersalArcticGenetic structurePhilopatryEcologyArchipelagoRange (aeronautics)PopulationLitterZoologyGenetic variationDemographyGenetics

Abstract

fetched live from OpenAlex

Arctic foxes are highly mobile arctic predators with a very weak population genetic structure over large parts of their range. Less is, however, known about the more local genetic structure within regions. Here, we analyze genotypes at 12 microsatellite loci for 561 arctic foxes trapped in the high-arctic archipelago Svalbard and investigate the genetic structure in three different age classes. Significant linkage disequilibrium, deficit of heterozygotes, genetic differentiation, and a decrease in relatedness with distance among animals trapped in their first winter suggested that some litter mates remain in proximity of each other during the first winter. This pattern was stronger for females than for males, indicating male-biased juvenile dispersal, and weaker for older animals. There was no genetic differentiation among adult foxes harvested in different hunting areas. The foxes from the protected area around Hornsund were however more differentiated than expected based on geographic distance alone, suggesting a possible disrupting effect of harvest on the spatial genetic structure in the rest of Svalbard. Our results also indicated a possible kin structure among adult females, suggesting natal philopatry, but further investigations will be needed to reach firm conclusions concerning kin structure in arctic foxes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.552

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 head0.014
GPT teacher head0.235
Teacher spread0.220 · 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

Citations17
Published2011
Admission routes2
Has abstractyes

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