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Record W2214323018 · doi:10.1139/cjfas-2015-0344

Disentangling individual- and population-scale processes within a latitudinal size gradient in sockeye salmon

2015· article· en· W2214323018 on OpenAlexafffundvenue
Cameron Freshwater, Marc Trudel, Terry D. Beacham, Lyse Godbout, Chrys-Ellen Neville, Strahan Tucker, Francis Juanes

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans CanadaUniversity of Victoria
FundersBritish Columbia Knowledge Development FundFisheries and Oceans CanadaBonneville Power AdministrationNatural Sciences and Engineering Research Council of CanadaLiber Ero Foundation
KeywordsOncorhynchusOtolithJuvenileBiologyEcologyPopulation sizePopulationFisheryDemography

Abstract

fetched live from OpenAlex

We examined how individual processes contribute to a latitudinal gradient in body size within populations of migrating juvenile sockeye salmon (Oncorhynchus nerka) while simultaneously testing for size-selective mortality, a potentially confounding population scale process. Using otolith microstructure techniques and structural equation modeling, we determined that ocean entry size and phenology had strong, direct effects on size at capture. Population identity and freshwater age also had strong indirect effects, moderated by size at entry. Conversely, marine growth rates immediately after entry or before capture were relatively weak predictors of size during migration. We next tested for shifts in size distribution indicative of selective mortality, but detected no evidence of smaller individuals experiencing lower survival during early marine migrations. These results indicate that the migratory distributions of juvenile sockeye salmon are influenced by body size and that this variation is predominantly driven by traits present prior to freshwater outmigration, rather than marine growth or differential survival. We suggest integrating individual variation in migratory characteristics with the effects of environmental conditions experienced en route to provide an improved understanding of migratory species.

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 score0.964
Threshold uncertainty score0.073

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 studies0.0000.001
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 head0.024
GPT teacher head0.224
Teacher spread0.200 · 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

Citations19
Published2015
Admission routes3
Has abstractyes

Explore more

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