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Record W3108868719 · doi:10.1111/jav.02629

The costs of using night roosts for migrating whimbrels

2020· article· en· W3108868719 on OpenAlexaff
Bryan D. Watts, Fletcher M. Smith, Chance Hines, Laura Duval, Diana J. Hamilton, Tim Keyes, Julie Paquet, Lisa Pirie‐Dominix, Jennie Rausch, Barry R. Truitt, Brad Winn, Paul Woodard

Bibliographic record

VenueJournal of Avian Biology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsEnvironment and Climate Change CanadaMount Allison University
Fundersnot available
KeywordsForagingEnergy expenditureMarshPredationHabitatEcologyEnergeticsGeographyPhysical geographyEnvironmental scienceBiologyWetland

Abstract

fetched live from OpenAlex

Migrant shorebirds operate within a series of landscapes and must adjust their daily activities to achieve seasonal time and energy objectives. Night roosts are essential landscape elements that provide safety from predators for many shorebird species. What costs migrants incur to use night roosts and how these costs vary across staging sites are poorly understood. We tracked 42 adult whimbrels Numenius phaeopus with satellite transmitters and used night locations to delineate 39 night roosts during spring and fall migration. We used daytime locations to measure round‐trip commuting distances between night roosts and foraging areas and estimated daily commuting costs including distance, time and metabolic energy expenditure. We identified night roosts on offshore islands (n = 20) and onshore locations including along habitat edges (n = 13) and on topographic highs within extensive marshes (n = 6). Mean daily commuting costs varied between roosts. Whimbrels took 3.9–52.1 min (median = 15.2) to fly 3.1–42.2 km (median = 12.3) which costs 6.1–82.4 kj (median = 22.3) in lean mass energy expenditure and 8.1–109.2 kj (median = 31.5) in leaving mass energy. Birds using offshore roosts had twice the commuting distance and associated costs compared to those using onshore roosts. The contribution of commuting costs to the premigratory energy budget ranged from 1.5 to 18.8% with costs for nearly 30% of roosts exceeding 10%. Commuting costs to and from night roosts appear to be biologically relevant within some staging sites and should be considered among other constraints faced by migrants during stopover periods when food or time is limiting.

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 score0.084
Threshold uncertainty score0.166

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)0.0000.000

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 head0.030
GPT teacher head0.284
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 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

Citations12
Published2020
Admission routes1
Has abstractyes

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