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Record W4311320296 · doi:10.1002/ece3.9581

Carry‐over effects of weather and decision‐making on nest success of a migratory shorebird

2022· article· en· W4311320296 on OpenAlexafffundabout
Sarah J. Clements, Jason P. Loghry, Bart M. Ballard, Mitch D. Weegman

Bibliographic record

VenueEcology and Evolution · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of Saskatchewan
FundersNational Science Foundation of Sri LankaEnvironment and Climate Change CanadaTexas A and M University-KingsvilleWaterbird SocietyRobert J. Kleberg, Jr. and Helen C. Kleberg FoundationAnimal Behavior SocietyWebster Groves Nature Study SocietyUniversity of MissouriNational Science Foundation
KeywordsNest (protein structural motif)GeographyEcologyZoologyBiology

Abstract

fetched live from OpenAlex

Abstract Weather conditions experienced by birds can influence their migration decision‐making and strategy both within and across seasons. Additionally, decision‐making during migration may influence subsequent fitness (reproductive success and/or survival). Examining the effects of fine‐scale weather variables on individuals throughout the year could help identify stages of the annual cycle when species may be most affected by weather. In this study, we captured 24 black‐bellied plovers (gray plovers; Pluvialis squatarola ) on nonbreeding areas along the western Gulf of Mexico coast and tracked their locations once every 2 h through their breeding season in the Alaskan and Canadian Arctic. We quantified migration strategies and weather conditions experienced by each individual throughout the nonbreeding, northward migration, and breeding seasons. We used a Bayesian hierarchical model which connected regressions linking weather with migration metrics, and migration metrics and breeding season weather with reproductive success. We found strong negative relationships between two migration metrics (migration duration and number of stopovers) and reproductive success, but no substantial relationships between breeding season weather variables and reproductive success. We found negative relationships between nonbreeding season temperature, migration temperature, and migration NDVI and both migration duration and number of stopovers, in addition to positive relationships between the number of stopovers and storms during migration, migration duration, and nonbreeding season precipitation. These results suggest that reproductive success is influenced by weather throughout the annual cycle and migration strategy is a key mechanism through which these effects operate. Our findings suggest that environmental factors throughout the year influence shorebird fitness, and, because black‐bellied plovers are often associated with mixed‐species flocks, many species likely experience similar constraints.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.004
GPT teacher head0.222
Teacher spread0.219 · 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 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

Citations13
Published2022
Admission routes3
Has abstractyes

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