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Record W4376279132 · doi:10.1093/ornithology/ukad024

Pacific Barrow’s Goldeneye refine migratory phenology in response to overwintering temperatures and annual snowmelt

2023· article· en· W4376279132 on OpenAlexafffund
J. G. Kemp, W. Sean Boyd, Tesia M. Forstner, Daniel Esler, Timothy D. Bowman, David C. Douglas, Danica Hogan, Malcolm McAdie, J. E. Thompson, Megan Willie, David J. Green

Bibliographic record

VenueThe Auk · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsEnvironment and Climate Change CanadaAlberta Environment and Protected AreasSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Geological SurveyEnvironment and Climate Change CanadaAlaska Department of Fish and GameAlberta Conservation AssociationU.S. Fish and Wildlife ServiceDucks Unlimited Canada
KeywordsOverwinteringPhenologyAnnual cycleSnowmeltBird migrationLatitudeGeographyEcologyPhenotypic plasticityBiology

Abstract

fetched live from OpenAlex

Abstract Timing of seasonal bird migrations is broadly determined by internal biological clocks, which are synchronized by photoperiod, but individuals often refine their migratory timing decisions in response to external factors. Using 11 years of satellite telemetry data, we show that Pacific Barrow’s Goldeneye (Bucephala islandica) at higher latitudes initiated spring and molt migrations later and fall migration earlier than individuals at lower latitudes. We further show that individuals refined migratory timing in response to interannual variation in environmental conditions. Individual Barrow’s Goldeneye initiated spring migration earlier in years with warmer springs at their overwintering locations and concluded spring migration earlier in years with earlier annual snowmelt on their breeding grounds. Because individuals respond to conditions both where they initiate and where they conclude spring migration, our results suggest that Barrow’s Goldeneye update their migratory decisions en route. For all 3 migrations in their annual cycle, birds delayed initiating migration if they had been captured and tagged prior to that migration. Birds that initiated migration late for their latitude were less likely to include a stopover and completed that migration faster, partially compensating for delayed departures. Our results are consistent with the hypothesis that Barrow’s Goldeneye uses a combination of endogenous cues and environmental cues in migratory decision making. Sensitivity to environmental cues suggests that Barrow’s Goldeneye may have behavioral plasticity that is adaptive when faced with 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score1.000

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)0.0010.001

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 head0.009
GPT teacher head0.241
Teacher spread0.232 · 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.

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

Citations6
Published2023
Admission routes2
Has abstractyes

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