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Record W3210076619 · doi:10.3389/fevo.2021.710007

Timing of Breeding Site Availability Across the North-American Arctic Partly Determines Spring Migration Schedule in a Long-Distance Neotropical Migrant

2021· article· en· W3210076619 on OpenAlexafffund
Jean‐François Lamarre, Gilles Gauthier, Richard B. Lanctot, Sarah T. Saalfeld, Oliver P. Love, Eric T. Reed, Oscar W. Johnson, Joe Liebezeit, Rebecca L. McGuire, Mike Russell, Erica Nol, Laura Koloski, Felicia J. Sanders, Laura McKinnon, Paul A. Smith, Scott A. Flemming, Nicolas Lecomte, Marie‐Andrée Giroux, Silke Bauer, Tamara Emmenegger, Joël Bêty

Bibliographic record

VenueFrontiers in Ecology and Evolution · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsYork UniversityUniversité de MonctonTrent UniversityUniversité LavalAlberta Environment and Protected AreasUniversity of WindsorEnvironment and Climate Change CanadaUniversité du Québec à Rimouski
FundersFonds de recherche du Québec – Nature et technologiesCanadian Nuclear Safety CommissionNunavut Wildlife Management BoardU.S. Fish and Wildlife ServiceEnvironment and Climate Change CanadaGovernment of AlbertaNew Brunswick Innovation FoundationParks CanadaNatural Resources CanadaIndigenous and Northern Affairs CanadaUniversité de MonctonArctic Landscape Conservation CooperativeNatural Sciences and Engineering Research Council of CanadaW. Garfield Weston FoundationNational Fish and Wildlife FoundationUniversité du Québec à RimouskiChurchill Northern Studies Centre
KeywordsEcologyArcticWaterfowlRange (aeronautics)GeographySnowSnowmeltFlywayBiological dispersalPluvialisBiologyHabitatPopulationDemography

Abstract

fetched live from OpenAlex

Long-distance migrants are under strong selection to arrive on their breeding grounds at a time that maximizes fitness. Many arctic birds start nesting shortly after snow recedes from their breeding sites and timing of snowmelt can vary substantially over the breeding range of widespread species. We tested the hypothesis that migration schedules of individuals co-occurring at the same non-breeding areas are adapted to average local environmental conditions encountered at their specific and distant Arctic breeding locations. We predicted that timing of breeding site availability (measured here as the average snow-free date) should explain individual variation in departure time from shared non-breeding areas. We tested our prediction by tracking American Golden-Plovers ( Pluvialis dominica ) nesting across the North-American Arctic. These plovers use a non-breeding (wintering) area in South America and share a spring stopover area in the nearctic temperate grasslands, located >1,800 km away from their nesting locations. As plovers co-occur at the same non-breeding areas but use breeding sites segregated by latitude and longitude, we could disentangle the potential confounding effects of migration distance and timing of breeding site availability on individual migration schedule. As predicted, departure date of individuals stopping-over in sympatry was positively related to the average snow-free date at their respective breeding location, which was also related to individual onset of incubation. Departure date from the shared stopover area was not explained by the distance between the stopover and the breeding location, nor by the stopover duration of individuals. This strongly suggests that plover migration schedule is adapted to and driven by the timing of breeding site availability per se . The proximate mechanism underlying the variable migration schedule of individuals is unknown and may result from genetic differences or individual learning. Temperatures are currently changing at different speeds across the Arctic and this likely generates substantial heterogeneity in the strength of selection pressure on migratory schedule of arctic birds migrating sympatrically.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score0.708

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.229
Teacher spread0.221 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations14
Published2021
Admission routes2
Has abstractyes

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