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Record W4294550708 · doi:10.1139/cjz-2022-0028

Drivers of winter population cycles in the Varied Thrush (<i>Ixoreus naevius</i>)

2022· article· en· W4294550708 on OpenAlexvenueno aff
Walter D. Koenig, Johannes M. H. Knops

Bibliographic record

VenueCanadian Journal of Zoology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
FundersNational Park ServiceU.S. Forest ServiceNature ConservancyCalifornia Department of Parks and RecreationU.S. Department of Agriculture
KeywordsAcornAbundance (ecology)BiologySeasonal breederRange (aeronautics)ThrushEcologyPopulationBorealDemography

Abstract

fetched live from OpenAlex

The drivers of year-to-year difference in winter abundance patterns, particularly dramatic in the “eruptions” of many boreal seed-eating birds, are poorly understood. Varied Thrush ( Ixoreus naevius (Gmelin, 1789)), endemic to the Pacific Northwest of North America, is a boreal species that exhibits pronounced, often biennially cyclic, changes in winter abundance within most of its normal wintering range. Although the drivers of this variability have not previously been explored, it has been suggested that differences in acorn abundance, a key winter food resource, might be important. Here, we examine three hypotheses for the drivers of this pattern: the acorn crop within the bird's normal winter range, weather within the bird's winter range, and weather during the previous breeding season within the bird's breeding range. Analyses supported the importance of breeding season conditions, particularly breeding season rainfall, with more birds wintering following wetter years. No support was found for the hypotheses that winter conditions, neither the acorn crop nor winter weather, correlate with winter abundance patterns. For this forest species, year-to-year differences in winter abundance patterns are apparently not driven by the “pull” of winter food supply or winter conditions, but by environmental factors during the prior breeding season that presumably affect reproductive success and subsequent population size.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.012
GPT teacher head0.222
Teacher spread0.209 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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