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Record W2105225121 · doi:10.1642/auk-13-071.1

Comparative population structure of cavity-nesting sea ducks

2014· article· en· W2105225121 on OpenAlexafffund
John M. Pearce, John M. Eadie, Jean‐Pierre L. Savard, Thomas Kjær Christensen, James B. Berdeen, Eric J. Taylor, Sean Boyd, Árni Einarsson, Sandra L. Talbot

Bibliographic record

VenueThe Auk · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsEnvironment and Climate Change Canada
FundersU.S. Geological SurveyNational Wildlife Research CenterU.S. Fish and Wildlife ServiceSimon Fraser University
KeywordsBiological dispersalPopulationWaterfowlEcologyGeographyBiologyGene flowNest (protein structural motif)Genetic diversityHabitatDemography

Abstract

fetched live from OpenAlex

A growing collection of mtDNA genetic information from waterfowl species across North America suggests that larger-bodied cavity-nesting species exhibit greater levels of population differentiation than smaller-bodied congeners. Although little is known about nest-cavity availability for these species, one hypothesis to explain differences in population structure is reduced dispersal tendency of larger-bodied cavity-nesting species due to limited abundance of large cavities. To investigate this hypothesis, we examined population structure of three cavity-nesting waterfowl species distributed across much of North America: Barrow's Goldeneye (Bucephala islandica), Common Goldeneye (B. clangula), and Bufflehead (B. albeola). We compared patterns of population structure using both variation in mtDNA control-region sequences and band-recovery data for the same species and geographic regions. Results were highly congruent between data types, showing structured population patterns for Barrow's and Common Goldeneye but not for Bufflehead. Consistent with our prediction, the smallest cavity-nesting species, the Bufflehead, exhibited the lowest level of population differentiation due to increased dispersal and gene flow. Results provide evidence for discrete Old and New World populations of Common Goldeneye and for differentiation of regional groups of both goldeneye species in Alaska, the Pacific Northwest, and the eastern coast of North America. Results presented here will aid management objectives that require an understanding of population delineation and migratory connectivity between breeding and wintering areas. Comparative studies such as this one highlight factors that may drive patterns of genetic diversity and population trends.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.729

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)0.0010.000

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 head0.016
GPT teacher head0.261
Teacher spread0.244 · 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

Citations12
Published2014
Admission routes2
Has abstractyes

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