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Specialization to cold‐water upwellings may facilitate gene flow in seabirds: new evidence from the Peruvian pelican <i>Pelecanus thagus</i> (Pelecaniformes: Pelecanidae)

2013· article· en· W2011003422 on OpenAlexafffund
Will S. Jeyasingham, Scott A. Taylor, Carlos B. Zavalaga, Alejandro Simeone, Vicki L. Friesen

Bibliographic record

VenueJournal of Avian Biology · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyPelicanGene flowBiological dispersalPanmixiaEcologyUpwellingPopulationRange (aeronautics)ZoologyGenetic variationGeneGenetics

Abstract

fetched live from OpenAlex

Recent research has shown that tropical seabirds specialized to feed on cold water upwellings exhibit low population genetic differentiation and high gene flow across large geographic distances. This pattern is opposite to the general pattern of differentiation reported for tropical seabirds, and led us to hypothesize that specialization to cold‐water upwellings facilitates gene flow between colonies. As a test of this hypothesis we characterized population differentiation and gene flow across the range of the Peruvian pelican Pelecanus thagus , an upwelling specialist endemic to the Humboldt Current, using an 838 base pair segment of the mitochondrial control region and seven microsatellite loci. In support of our hypothesis we report genetic panmixia across the geographic range of this species and inferred high gene flow between colonies. The high dispersal propensity of upwelling specialist seabirds (adults and/or juveniles) may reduce loss of genetic diversity during population declines, and increase the ability of these species to colonize new islands.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
Threshold uncertainty score0.542

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 science0.0010.000
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 head0.023
GPT teacher head0.239
Teacher spread0.216 · 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 designBench or experimental
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

Citations10
Published2013
Admission routes2
Has abstractyes

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