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Record W4417527413 · doi:10.1186/s40462-025-00618-6

Unexpected migration patterns in a high-latitude breeding songbird: evidence from multi-sensor geolocators and isotopes

2025· article· en· W4417527413 on OpenAlexfundaboutno aff
Stephanie J. Szarmach, Johanna K Beam, M. N. Moore, Benjamin M. Van Doren, Alan Brelsford, David P. L. Toews

Bibliographic record

VenueMovement Ecology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersUniversity of California, RiversideWilson Ornithological SocietyAnimal Behavior SocietyPennsylvania State UniversityAmerican Ornithological SocietyAlberta Conservation Association
KeywordsGeolocationAnimal ecologyRange (aeronautics)Bird migrationPopulationLeverage (statistics)

Abstract

fetched live from OpenAlex

BACKGROUND: Migratory birds often exhibit within-species variation in migration routes and non-breeding areas, yet the mechanisms shaping these patterns remain poorly understood, particularly in high-latitude breeding populations. Several hypotheses have been proposed to explain why birds follow particular routes: optimal migration theory proposes that routes minimizing time or energy expenditure are favored, whereas the historical contingency hypothesis posits that routes are shaped by past range expansion, sometimes resulting in "suboptimal" migrations. We investigated whether distance minimization or historical contingency more strongly influenced migration routes in high-latitude breeding myrtle warblers (Setophaga coronata coronata), which indirect evidence previously suggested follow a shorter route to the Pacific Coast rather than the core Gulf Coast nonbreeding area. METHODS: We tracked the migrations of six Alaskan myrtle warblers using geolocators measuring both light and atmospheric pressure and inferred nonbreeding areas using hydrogen isotopes for a larger sample of birds breeding in Alaska, British Columbia, and Alberta (n = 167). Additionally, we compared migration tracks derived from light-level data exclusively with those that incorporated atmospheric pressure. RESULTS: Contrary to expectations, all geolocator-tracked birds and most with stable isotope data migrated to the southeastern United States, with just 5% of individuals possibly wintering on the Pacific Coast. Using pressure data allowed us to resolve migration routes and timing more precisely than traditional light-level methods, while also elucidating flight altitude and fine-scale elevational movements. CONCLUSIONS: We found that myrtle warblers breeding in northwestern North America migrate farther than previously thought, despite being generally regarded as a relatively short-distance migrant. Our findings contradict previous studies that suggested myrtle warblers breeding in Alaska and northern British Columbia typically follow a shorter migration route to the Pacific Coast. This seemingly suboptimal route-similar to routes followed by the few other songbirds tracked from the region-is consistent with the historical contingency hypothesis, which proposes that migration routes reflect past range expansions. We recommend that researchers conducting geolocation studies leverage tags with barometers, as the additional atmospheric pressure data greatly improved our ability to characterize migration at a fine scale over the full annual cycle.

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 score0.128
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)0.0020.000

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 head0.014
GPT teacher head0.249
Teacher spread0.235 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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