MétaCan
Menu
Back to cohort
Record W3203279401 · doi:10.3354/meps13905

Seasonal variations in migration strategy of a longdistance Arctic-breeding seabird

2021· article· en· W3203279401 on OpenAlexafffundabout
Yannick Seyer, Gilles Gauthier, Joël Bêty, JF Therrien, Nicolas Lecomte

Bibliographic record

VenueMarine Ecology Progress Series · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversité de MonctonUniversité du Québec à RimouskiUniversité LavalCenter for Northern Studies
FundersArcticNetNatural Resources CanadaGovernment of NunavutGarfield Weston FoundationUniversité de MonctonPolar Knowledge Canada
KeywordsSeabirdForagingPhenologyArcticEcologyFledgeBird migrationGeographyFisheryBreedAnnual cycleBiological dispersalBiologyPredationPopulation

Abstract

fetched live from OpenAlex

Long-distance migratory seabirds need to adjust their migration strategy according to internal (breeding, molting) and external factors (seasonality, resource availability). Time-minimizing strategies are common during spring migration to arrive at the optimal time to breed. We studied the annual movements and migration strategy of the long-tailed jaeger Stercorarius longicaudus , a small arctic-nesting seabird. First, we documented year-round movements (routes, wintering sites) of male and female jaegers breeding in the Canadian Arctic. We then compared their migration strategies between seasons (phenology, stopover use, travel distance, speed) to determine whether they adopt a time-minimizing strategy in spring. Over 6 yr, we collected 43 tracks from geolocators deployed on Bylot and Igloolik Islands. Jaegers departed the breeding site over a 5 wk period and traveled on average 32375 km (round trip) before returning to breed, one of the longest documented migrations on Earth. Birds used a major stopover area east of the Grand Banks of Newfoundland in spring and fall, and wintered in high marine productivity areas of the South Atlantic. Unexpectedly, the spring migration was 40% longer and 32% slower than in fall, and birds increased their time spent on water (foraging and/or resting) by 61%. A time-minimizing strategy in fall may help to reach the wintering site rapidly and start molting early. In spring, a fly-and-forage strategy seems to be adopted to increase foraging effort, probably for the accumulation of body reserves before breeding and in anticipation of unfavorable conditions that may prevail at arrival on their arctic breeding site.

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 score0.025
Threshold uncertainty score0.997

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)0.0040.000

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 head0.011
GPT teacher head0.241
Teacher spread0.230 · 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

Citations21
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueMarine Ecology Progress SeriesSame topicAvian ecology and behaviorFrench-language works237,207