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Record W4287958842 · doi:10.3389/fmars.2022.938033

Age-Related Interactions with Wind During Migration Support the Hypothesis of Developmental Learning in a Migrating Long-Lived Seabird

2022· article· en· W4287958842 on OpenAlexafffund
Kevin D. Powers, Isabeau Pratte, Robert A. Ronconi, Sarah N. P. Wong, Peter G. Ryan, Linda Welch, Tammy L. Silva, Kent A. Hatch, Andrew J. Westgate, David N. Wiley

Bibliographic record

VenueFrontiers in Marine Science · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsEnvironment and Climate Change Canada
FundersNational Oceanic and Atmospheric AdministrationDalhousie UniversityMassachusetts MassWildlife Division of Fisheries and WildlifeUniversity of North Carolina WilmingtonU.S. Department of the Interior
KeywordsSeabirdBird migrationShearwaterForagingWind speedGlobal wind patternsGeographyPrevailing windsBiologyEcologyWind directionEnvironmental sciencePhysical geographyMeteorologyPredation

Abstract

fetched live from OpenAlex

Wind patterns shape migratory pathways and detours of many procellariiform bird species that seasonally migrate between hemispheres. These seabirds are long-lived, and the period of immaturity is presumed to be a time of development and learning the environment, specifically how to use wind to their advantage. We assess how wind encountered by individual Great Shearwaters ( Ardenna gravis ) varies along the migration journey and compare responses between presumed mature and immature birds (early and late, respectively) in southbound migration and mature birds in northbound migration. We analyze modeled Argos locations from 71 individual tracks of migratory Great Shearwaters with concurrent U (East/West) and V (North/South) wind components. Migration in seabirds is well studied, but there is limited quantitative work measuring individual birds directly interacting with wind and their associated changes in flight behavior during migration. We show that Great Shearwaters made optimal use of winds, and that different age groups made decisions that exposed them to different wind constraints. Overall, Great Shearwaters derived positive responses from wind under most conditions and did not rely on a drifting strategy, which would be suggested if wind effect (difference between ground and airspeed) was predominantly positive during migrations. Instead, they appeared to use a compensating strategy to achieve an acceptable course and speed. The difference we observed in migration phenologies suggests that by migrating later, immature birds might travel the path of least resistance and experience flight conditions that are less risky furthering their ability to withstand a variety of wind conditions encountered later in life as done by adults, which migrate earlier and are subject to more variable flight conditions. We conclude that like other procellariiforms, a longer period of sexual maturity is required to enhance flight performance and mediate energy expenditure through experiential learning and increased fitness.

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)0.001
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 score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.008
GPT teacher head0.208
Teacher spread0.199 · 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

Citations7
Published2022
Admission routes2
Has abstractyes

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