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Record W3099096540 · doi:10.1093/icesjms/fsaa164

Size-at-maturity shift in a male-only fishery: factors affecting molt-type outcomes in Newfoundland and Labrador snow crab (<i>Chionoecetes opilio</i>)

2020· article· en· W3099096540 on OpenAlexaffabout
Darrell Mullowney, Krista D. Baker

Bibliographic record

VenueICES Journal of Marine Science · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsIntraspecific competitionFisheryBiologySnowPopulationCrustaceanStock assessmentEcologyFishingGeographyDemography

Abstract

fetched live from OpenAlex

Abstract A sex-asymmetric downward shift in size-at-terminal-molt has recently occurred in males in some portions of the Newfoundland and Labrador (NL) snow crab stock range, a first known occurrence for such processes in snow crab (Chionoecetes opilio) stocks. This study examines plausible factors promoting the shift in size-at-terminal-molt [synonymous with size-at-maturity (SaM)] including individual size, temperature, population density, and sex ratio. Analyses highlight expanse of cold water and large male density as being significant predictors of molt-type outcomes. A confluence of cold conditions and low density of large males promoted the SaM shift. In turn, the low male density was associated with recently elevated fishery exploitation rates under quota-controlled management. It remains unknown the extent to which the reduction in terminal size reflects a phenotypic vs. genotypic process. Factors affecting skip-molting in male snow crab are investigated, and we find that skip-molting occurs most frequently under extreme cold and high population density conditions. Potential complications arising from altered growth dynamics are discussed. Overall, the results advance knowledge on intraspecific competition processes within snow crab populations and inform fisheries management systems that male-only harvest strategies do not provide full protection from biological harm to aquatic resources through 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 score0.831
Threshold uncertainty score0.335

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 head0.012
GPT teacher head0.242
Teacher spread0.230 · 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

Citations13
Published2020
Admission routes2
Has abstractyes

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Same venueICES Journal of Marine ScienceSame topicCrustacean biology and ecologyFrench-language works237,207