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Record W3157801376 · doi:10.1111/jav.02695

Do phylogeny and habitat influence admixture among four North American chickadee (family: Paridae) species?

2021· article· en· W3157801376 on OpenAlexaff
Brendan A. Graham, Ian Gazeley, Ken A. Otter, Theresa M. Burg

Bibliographic record

VenueJournal of Avian Biology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsUniversity of Northern British ColumbiaUniversity of Lethbridge
Fundersnot available
KeywordsBiologyHabitatEcologyTaxonDeciduousGenetic admixtureTaigaZoologyPopulationDemography

Abstract

fetched live from OpenAlex

Hybridization is an important aspect of speciation, yet questions remain about the ecological and environmental factors that influence hybridization among wild populations. We used microsatellite genotyping data and collected land cover and environmental data for four North American chickadee species: black‐capped Poecile atricapillus , mountain P. gambeli , chestnut‐backed P. rufescens and boreal P. hudsonicus chickadees. Combining these datasets, we sought to examine whether there is evidence of admixture between four widely distributed North American chickadee species; whether admixture takes place more often between more closely related species pairs or between species pairs with more similar ecological preferences; and whether certain habitat types have higher rates of admixture than others. We detected admixture for five of the six species pairs analyzed (chestnut‐backed–mountain chickadee pair showed no evidence of admixture), and found rates of admixture varied geographically, and within taxa pairs. Admixture was higher among less closely related species than more closely related species, although habitat similarity was not a significant predictor. Finally, rates of admixture were higher in urban parkland habitats than deciduous, mixed or coniferous forest habitats. Our work indicates admixture occurs frequently among North American parids, and habitat and environmental variation may play an important role in the frequency and geographic distribution of hybridization.

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 score0.143
Threshold uncertainty score0.495

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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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