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Record W4411193129 · doi:10.1002/ecy.70131

Bird migration on the edge: Experimental manipulation of corticosterone advances departure dates

2025· article· en· W4411193129 on OpenAlexafffund
Maëliss Hoarau, Frédéric Dulude‐de Broin, Frédéric LeTourneux, Frédéric Angelier, Maude Gauthier‐Bouchard, Marie‐Claude Martin, Akiko Kato, Josée Lefebvre, Philippe J. Thomas, Christopher K. Williams, Joël Bêty, Pierre Legagneux

Bibliographic record

VenueEcology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversité du Québec à RimouskiEnvironment and Climate Change CanadaUniversité LavalCenter for Northern Studies
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence FundEnvironment and Climate Change CanadaArcticNet
KeywordsEcologyGeographyEnhanced Data Rates for GSM EvolutionBiologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Endogenous reserves accumulated during migration stopovers help most migratory birds cope with environmental uncertainties and fuel energy demands associated with migration and/or reproduction. Migratory decisions, such as departure time, should thus be finely tuned to energy intake rate at stopover sites. However, the physiological drivers of these decisions remain poorly understood. Glucocorticoids such as corticosterone (CORT) are known to mediate the stress response in birds but also play a key role in the regulation of energy intake and behavior, particularly during demanding life-history stages. We investigated how baseline CORT influences bird energy acquisition and migratory decisions by manipulating the physiology of wild snow geese (Anser caerulescens atlanticus) through subcutaneous implantation of corticosterone pellets during spring stopover. Birds of similar body condition were paired, implanted with CORT or placebo pellets, and tracked with GPS-GSM collars and accelerometers to monitor foraging efforts, habitat use, and migration departure date. We measured foraging rates from accelerometer data and classified using an unsupervised algorithm calibrated with field video recordings. CORT-treated birds foraged 20% more on average than placebo individuals over 10 days, primarily by increasing foraging efforts rather than altering habitat use. Most of the difference occurred in the first days post-implantation (Foraging rates on Day 2, CORT: 0.4 [95% CI: 0.34, 0.47]; placebo: 0.3 [0.2, 0.36]) and gradually faded to zero afterward (Foraging rates on Day 10, CORT: 0.26 [0.21, 0.32]; placebo: 0.26 [0.21, 0.31]). These higher foraging rates advanced the median departure date of CORT-treated individuals by 2 days compared to placebo (median departure: CORT, May 17 [15, 17]; placebo, May 19 [17, 20]). Our experimental manipulation is one of the first to induce a positive shift in migration phenology and confirms the role of CORT baseline levels in modulating energy acquisition and migratory decisions in a wild bird 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.267
Teacher spread0.254 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations4
Published2025
Admission routes2
Has abstractyes

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