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Record W7133277689

Green Sea Urchin stock status update and harvest options

2025· other· en· W7133277689 on OpenAlexfundaboutno aff
Fisheries and Oceans Canada, Pêches et Océans Canada

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersFisheries and Oceans Canada
KeywordsStock assessmentStock (firearms)Fish stockSea urchinPopulationFisheries managementSustainable management
DOInot available

Abstract

fetched live from OpenAlex

British Columbia’s Green Sea Urchin (Strongylocentrotus droebachiensis) stock is assessed every three years using the assessment model developed by Perry et al. (2003). The last assessment was conducted in 2021 (DFO 2021a) and was used to inform the Pacific Region’s Green Sea Urchin 2021-2024 Integrated Fishery Management Plan (IFMP) (DFO 2021b, 2022, 2023). The present assessment provides updated advice, based on the inclusion of new data, for the development of the next IFMP in 2024 and subsequent IFMPs until spring 2027. Fisheries and Oceans Canada (DFO) Fisheries Management has requested advice for the Green Sea Urchin fishery in British Columbia (BC), by spring 2024, on the following: 1. Evaluate stock status of Green Sea Urchins in Northeast (Pacific Fisheries Management Areas - PFMAs: 11, 12, and 13) and Southeast Vancouver Island (PFMAs 14, 18, 19, and 20) using provisional reference points and density estimates derived from biological surveys within each management region. 2. Provide the ranges of sustainable harvest options for the commercial harvest regions (PFMAs 11, 12, 13, 14, 18, 19, and 20). 3. Analyze index site survey data (PFMAs 12 and 19) and present the recent trends in the local populations and population structure for Green Sea Urchins. 4. Examine and identify uncertainties in the data and methods. 5. Provide recommendations for additional research or stock assessment programs. This assessment updates previously published time series data and provides new harvest options for the 2024-2025 to 2026-2027 Green Sea Urchin fishery. Methods remain largely unchanged since 2003 and a Bayesian biomass dynamic model continues to be used in the assessment of BC’s Green Sea Urchin stock (Perry et al. 2003, 2006; Zhang and Perry 2005; Waddell et al. 2010; DFO 2015, 2016, 2018a, 2021a). This assessment updates the model results with the most recently available commercial catch (fishery-dependent) and biological dive survey (fishery-independent) information. Provisional reference points compliant with the DFO’s Fishery Decision-Making Framework Incorporating the Precautionary Approach (DFO Precautionary Approach; DFO 2009) were established (DFO 2018a) and subsequently implemented in the fishery (DFO 2018b). Using these reference points, Green Sea Urchin stock status can be estimated in the regions of Northeast Vancouver Island (PFMAs 11, 12, and 13) and Southeast Vancouver Island (14, 18, 19, and 20); the two regions where the long-term index sites are located (PFMAs 12 and 19). This Science Response Report results from the May 23, 2024 regional peer review on Stock Status Update and Harvest Options for the Green Sea Urchin (Strongylocentrotus droebachiensis) Fishery in British Columbia, 2024-2027.

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)0.002
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.987

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.003

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 head0.008
GPT teacher head0.240
Teacher spread0.231 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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Same venueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du CanadaFrench-language works237,207