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Record W2164095952 · doi:10.1139/f09-143

Pelagic fish outburst or suprabenthic habitat occupation: legacy of the Atlantic cod (Gadus morhua) collapse in eastern Canada

2009· article· en· W2164095952 on OpenAlexaffvenueabout
Ian H. McQuinn

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsPelagic zoneGroundfishClupeaGadusFisheryOverexploitationPopulationHerringHaddockGeographyBiologyOceanographyFisheries managementFishingFish <Actinopterygii>Geology

Abstract

fetched live from OpenAlex

The use of bottom-trawl research survey data to estimate population trends for small pelagic fishes, despite the extremely low selectivity of this gear for these species, has created the impression of a pelagic fish outburst along eastern Canada in the 1990s as a top-down response resulting from the demise of the Atlantic cod ( Gadus morhua ) and other groundfish. Using Atlantic herring ( Clupea harengus ) population assessments, fisheries statistics, and an acoustic database, as well as grey seal (Halichoerus grypus) diet studies, I demonstrate that contrary to a pelagic outburst, pelagic catches in research bottom trawls increased in several eastern Canadian ecosystems as these species increasingly occupied the suprabenthic habitat vacated by their diminishing groundfish predators. Although several herring populations were actually decreasing in abundance, bottom-trawl indices (BTIs) were dramatically increasing as their availability to research bottom-trawl surveys increased. Studies using BTIs have systematically underestimated pelagic fish abundances before the cod decline and therefore have dramatically overestimated their importance since, seriously biasing our view of the past and present state of many Canadian east coast ecosystems.

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 score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.022
GPT teacher head0.235
Teacher spread0.214 · 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

Citations26
Published2009
Admission routes3
Has abstractyes

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