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Record W4283075343 · doi:10.1139/cjfas-2021-0312

Nonstationary patterns in demographic traits covary with Chinook salmon marine distributions

2022· article· en· W4283075343 on OpenAlexaffvenue
Cameron Freshwater, Charles K. Parken, Strahan Tucker, Antonio Velez‐Espino, Jackie King

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsOncorhynchusChinook windJuvenileBiologyFisheryPopulationProductivityEcologyDemographyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The abundance of many Chinook salmon ( Oncorhynchus tshawytscha) stocks has declined despite reductions in harvest. We used state-space models parameterized with data from 57 Chinook salmon indicator stocks, ranging from coastal Oregon to southeast Alaska, to quantify long-term (since 1972 release year) changes in juvenile marine survival rate and mean age-at-maturity, as well as identify stock groupings with coherent dynamics. We found that juvenile marine distribution—rather than freshwater life history, run timing, or adult marine distribution—was the best predictor of trends in both survival and age. Only subyearling stocks that enter the Strait of Georgia showed evidence of transitioning to a low juvenile survival period, other groupings exhibited low and stable or cyclical patterns in survival. Conversely, declines in mean age-at-maturity were widespread and do not appear to have stabilized, suggesting that future declines in Chinook salmon population productivity may be influenced by earlier maturation or increased adult mortality, rather than further reductions in juvenile marine survival.

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)0.003
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 score0.982
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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 head0.008
GPT teacher head0.186
Teacher spread0.177 · 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 routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicFish Ecology and Management Studies→French-language works237,207→