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Record W4401373671 · doi:10.1111/nrm.12406

A regional analysis of climate change effects on global snow crab fishery

2024· article· en· W4401373671 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNatural Resource Modeling · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsFisheryClimate changeSnowGlobal warmingEnvironmental scienceGeographyEcologyBiologyMeteorology

Abstract

fetched live from OpenAlex

Abstract The snow crab fishery faces increasing vulnerability to environmental factors, yet the literature on the relationship between climate change and snow crab harvest remains limited. This study estimates snow crab harvest functions using climate change indicators with unbalanced panel data of snow crab production from the eastern Bering Sea (Alaska), the southern Gulf of St. Lawrence (Canada), the Sea of Japan, and the Barents Sea (Norway‐Russia). The relationship between snow crab biomass, stock, and catch is analyzed and the endogeneity of stock in the harvest function is also addressed using climate change indicators as instrumental variables (IVs). The results show that the extent of Arctic sea ice is effective in addressing the endogeneity, and the random effects IV model with error components two stage least squares estimator performs the best to control heterogeneity. A 1% increase in snow crab fishing effort is associated with a 0.42% increase in snow crab harvest, and a 1% increase in snow crab stock causes a 0.98% increase in snow crab harvest. The reported estimates indicate a large stock‐harvest elasticity and provide supporting evidence to prioritize stock enhancement in snow crab fishery policy designs to maintain stocks at sustainable levels and minimize government expenditures on subsidies. Recommendations This study explores how snow crab harvests are influenced by snow crab populations and fishing efforts in the context of global warming across various global regions, including the Bering Sea, the Gulf of St. Lawrence, the Sea of Japan, and the Barents Sea. A 1% increase in fishing effort is associated with a 0.42% increase in harvest, while a 1% increase in snow crab population leads to a 0.98% increase in harvest, showing a high dependency on snow crab biomass. Arctic sea ice extent is identified as a crucial climate factor affecting snow crab biomass and harvests, making it a valuable variable for understanding and managing snow crab populations. The study supports the prioritization of stock enhancement policies by fishery agencies and suggests standardizing how fishing effort is measured across different regions to improve snow crab fishery management and future research.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.946
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.028
GPT teacher head0.287
Teacher spread0.259 · 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