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Record W4386524171 · doi:10.5751/jfo-00341-940314

Shifts in breeding distribution, migration timing, and migration routes of two North American swift species

2023· article· en· W4386524171 on OpenAlexafffund
Erik Prytula, Matthew W. Reudink, Steffi LaZerte, Jared Sonnleitner, Ann E. McKellar

Bibliographic record

VenueJournal of Field Ornithology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of New BrunswickBrandon UniversityThompson Rivers University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSwiftGeographyDistribution (mathematics)BiologyEcology

Abstract

fetched live from OpenAlex

Climate change has resulted in changes to ecosystems and weather because of earlier onset of spring weather, later onset of fall weather, and more extreme weather patterns. Migratory birds may experience challenges adjusting to these new conditions. We utilized community science data from eBird that spanned 2009–2018 to test for changes in distribution and migration of two North American swift species. We asked if Vaux’s Swifts (<em>Chaetura vauxi</em>) and Chimney Swifts (<em>Chaetura pelagica</em>) changed their breeding distribution, migration routes, timing of migration, or speed of spring and fall migration over time. Our results show that Vaux’s Swifts shifted their breeding centroid south-east and Chimney Swifts shifted their breeding centroid west. There was also a shift in Vaux’s Swifts migration route to the east, almost proportionate in magnitude to its eastern shift in breeding range. Vaux’s Swifts displayed an advance in their start of spring migration, and Chimney Swifts exhibited a delay in their start of fall migration. These responses may be due to earlier onset of spring and a possible delay of colder temperatures associated with the onset of fall conditions. Our results indicated that both species are breeding further away from the coastline and more toward central North America, and suggest that swifts may display some phenotypic plasticity in response to changing environmental conditions. What remains unclear is if this phenotypic plasticity will be enough to prevent further population loss in the two species of swift, in the face of ongoing climate change.

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 score0.012
Threshold uncertainty score0.701

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 head0.019
GPT teacher head0.269
Teacher spread0.250 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

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