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Record W3214416286 · doi:10.1002/fee.2431

The global rise of crustacean fisheries

2021· review· en· W3214416286 on OpenAlexaff
Robert Boenish, Jacob P. Kritzer, Kristin M. Kleisner, Robert S. Steneck, Karl Michael Werner, Wenbin Zhu, Frederick R. Schram, Douglas N. Rader, William W. L. Cheung, J. Ingles, Yongjun Tian, John Mimikakis

Bibliographic record

VenueFrontiers in Ecology and the Environment · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of British ColumbiaFisheries and Oceans Canada
FundersMaine Sea Grant, University of MaineHigh Meadows Foundation
KeywordsFishingFisheryFisheries managementCrustaceanEcosystemBusinessNatural resource economicsEcologyEconomicsBiology

Abstract

fetched live from OpenAlex

Globally, wild decapod crustacean fisheries are growing faster than fisheries of any other major group, yet little attention has been given to the benefits, costs, and risks of this shift. We examined more than 60 years of global fisheries landings data to evaluate the socioeconomic and ecological implications of the compositional change in global fisheries, and propose that direct and indirect anthropogenic alterations and enhancements to ecosystems continue to benefit crustaceans. Crustaceans are among the most valuable seafood, but provide low nutritional yields and drive 94% of the projected increase of global fishery carbon emissions, due to low capture efficiency. Unequivocally, the increasing global demand for luxury seafood comes with serious environmental costs, but also appears to offer lucrative fishing opportunities. The potential for more prosperous fisheries carries unevaluated risks, highlighting the need for a nuanced perspective on global fisheries trade‐offs. Addressing this unique suite of trade‐offs will require substantive changes in both science and management.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
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 head0.011
GPT teacher head0.243
Teacher spread0.233 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations102
Published2021
Admission routes1
Has abstractyes

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