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Record W2166211519 · doi:10.1029/2005gl024239

Multidecadal North Atlantic climate variability and its effect on North American salmon abundance

2005· article· en· W2166211519 on OpenAlexaboutno aff
Alan Condron, Robert M. DeConto, Raymond S. Bradley, Francis Juanes

Bibliographic record

VenueGeophysical Research Letters · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
Fundersnot available
KeywordsAtlantic multidecadal oscillationFishingAbundance (ecology)Climate changeEnvironmental scienceStock (firearms)OceanographyPacific decadal oscillationSea surface temperatureOverwinteringFish stockFisheryClimatologyGeographyEcologyBiologyGeology

Abstract

fetched live from OpenAlex

Climate variability is now known to play a key role in the abundance of marine fisheries, and must be accounted for to implement sustainable management strategies. We show that North American Atlantic salmon abundance has fluctuated in parallel with the Atlantic Multidecadal Oscillation (AMO); a basin‐wide, low frequency climate mode producing cold‐warm‐cold sea surface temperatures over the last century. During the AMO warm (cool) phase salmon abundance is lower (higher). Changes in sea surface temperature associated with the AMO are most pronounced in the winter season near the Grand Banks of Newfoundland, a known overwintering area for salmon and an important time for determining survival. A moratorium on salmon fishing was established in 1992, but has so far contributed few signs of improvement in stock size. This may be explained by a shift in the AMO to a positive phase, producing persistently warm temperatures in the marine environment. Our findings show that a continued warming near the Grand Banks of Newfoundland will have a detrimental impact on this already depleted stock despite the reduction in commercial fishing.

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 score0.061
Threshold uncertainty score0.122

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 communication0.0000.000
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 head0.021
GPT teacher head0.299
Teacher spread0.278 · 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

Citations41
Published2005
Admission routes1
Has abstractyes

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