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Record W2116093469 · doi:10.1139/f10-081

Trends in the abundance of marine fishes

2010· article· en· W2116093469 on OpenAlexaffvenue
Jeffrey A. Hutchings, Cóilín Minto, D. Ricard, Julia K. Baum, Olaf P. Jensen

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMaximum sustainable yieldPopulationDemersal fishBiodiversityAbundance (ecology)FisheryMarine protected areaEcologyBiomass (ecology)BiologyGeographyFishingFisheries managementDemography

Abstract

fetched live from OpenAlex

The Convention on Biological Diversity (CBD) established a target in 2002 to reduce the rate of biodiversity loss by 2010. Using a newly constructed global database for 207 populations (108 species), we examine whether the 2010 target has been met for marine fishes, while accounting for population biomass relative to maximum sustainable yield, BMSY. Although rate of decline has eased for 59% of populations declining before 1992 (a pattern consistent with a literal interpretation of the target), the percentage of populations below BMSY has remained unchanged and the rate of decline has increased among several top predators, many of which are below 0.5BMSY. Combining population trends, a global multispecies index indicates that marine fishes declined 38% between 1970 and 2007. The index has been below BMSY since the mid-1980s and stable since the early 1990s. With the exception of High Seas pelagic fishes and demersal species in the Northeast Pacific and Australia – New Zealand, the multispecies indices are currently below BMSY in many regions. We conclude that the 2010 CBD target represents a weak standard for recovering marine fish biodiversity and that meaningful progress will require population-specific recovery targets and associated time lines for achieving those targets.

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 score0.903
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.240
Teacher spread0.220 · 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

Citations109
Published2010
Admission routes2
Has abstractyes

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