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Record W3008441502 · doi:10.1093/condor/duz067

Barn Swallow (Hirundo rustica) fledglings use crop habitat more frequently in relation to its availability than pasture and other habitat types

2019· article· en· W3008441502 on OpenAlexafffundabout
Chloe K. Boynton, Nancy A. Mahony, Tony D. Williams

Bibliographic record

VenueOrnithological Applications · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsSimon Fraser UniversityEnvironment and Climate Change Canada
FundersEnvironment and Climate Change CanadaSimon Fraser University
KeywordsHirundoFledgeHabitatPastureEcologyBarnPopulationBiologyGeographyPredationDemography

Abstract

fetched live from OpenAlex

Abstract Populations of birds that forage on aerial insects have been declining across North America for several decades, but the main causes of and reasons for geographical variation in these declines remains unclear. We examined the habitat use and survival of post-fledging Barn Swallows (Hirundo rustica) near Vancouver, British Columbia, Canada, using VHF radio telemetry. We predicted that fledgling Barn Swallows hatched in higher-quality natal habitat (pasture) would fledge at higher quality, stay closest to the nest, disproportionately use higher-quality habitat during the post-fledge stage, and have higher survival rates in the region. Contrary to our predictions, we found that natal habitat (crop, pasture, or non-agriculture) had no effect on fledgling quality or movement distance. Barn Swallow fledglings used crop habitat more frequently in relation to its availability than other habitat types, including pasture. Barn Swallows had low post-fledging survival rates (0.44; 95% CI: 0.35–0.57), which could negatively influence the population trend of the species in this region. While natal habitat had only minor effects, crop habitat appears to be important for fledgling Barn Swallows and, therefore, a decline in this habitat type could have further negative implications for an already declining species.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.999

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)0.0020.005

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 head0.020
GPT teacher head0.260
Teacher spread0.240 · 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; both teacher heads agree on what is shown here.

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

Citations15
Published2019
Admission routes3
Has abstractyes

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