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Record W6929658214 · doi:10.5061/dryad.v6wwpzgz5

Variation and correlation in the timing of breeding of North Atlantic seabirds across multiple scales

2022· dataset· en· W6929658214 on OpenAlexaff

Bibliographic record

VenueEdinburgh Research Explorer (University of Edinburgh) · 2022
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer and biochemical research
Canadian institutionsEnvironment and Climate Change CanadaAcadia UniversityMcGill UniversityUniversity of New Brunswick
Fundersnot available
KeywordsSeabirdPhenologyRange (aeronautics)Context (archaeology)PopulationHabitatVariation (astronomy)Spatial ecology

Abstract

fetched live from OpenAlex

Timing of breeding, an important driver of fitness in many populations, is widely studied in the context of global change, yet despite considerable efforts to identify environmental drivers of seabird nesting phenology, for most populations we lack evidence of strong drivers. Here we adopt an alternative approach, examining the degree to which different populations positively covary in their annual phenology to infer whether phenological responses to environmental drivers are likely to be (i) shared across species at a range of spatial scales, (ii) shared across populations of a species, or (iii) idiosyncratic to populations. We combined 51 long-term datasets on breeding phenology spanning 50 years from nine seabird species across 29 North Atlantic sites and examined the extent to which different populations share early versus late breeding seasons depending on a hierarchy of spatial scales comprising breeding site, small-scale region, large-scale region and the whole North Atlantic. In about a third of cases we found laying dates of populations of different species sharing the same breeding site or small-scale breeding region were positively correlated, which is consistent with the hypothesis that they share phenological responses to the same environmental conditions. In comparison we found no evidence for positive phenological covariation among populations across species aggregated at larger spatial scales. In general we found little evidence for positive phenological covariation between populations of a single species, and in many instances the inter-year variation specific to a population was substantial, consistent with each population responding idiosyncratically to local environmental conditions. Black-legged kittiwake (Rissa tridactyla) was the exception, with populations exhibiting positive covariation in laying dates that decayed with the distance between breeding sites, suggesting that populations may be responding to a similar driver. Our approach sheds light on the potential factors that may drive phenology in our study species, thus furthering our understanding of the scales at which different seabirds interact with interannual variation in their environment. We also identify additional systems and phenological questions to which our inferential approach could be applied.

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: Dataset · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.065
GPT teacher head0.330
Teacher spread0.265 · 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
GenreDataset

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

Citations2
Published2022
Admission routes1
Has abstractyes

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