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Record W7133275380

Application of management procedure framework for inside quillback rockfish

2023· other· en· W7133275380 on OpenAlexfundno 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 · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersFisheries and Oceans Canada
KeywordsGroundfishStock (firearms)RockfishStock assessmentOperating modelFisheries management
DOInot available

Abstract

fetched live from OpenAlex

The inside stock of Quillback Rockfish (Sebastes maliger, Inside Quillback Rockfish) occurs in Groundfish Management Area 4B (Queen Charlotte Strait, Strait of Georgia, and Strait of Juan de Fuca) in British Columbia (BC). This analysis provides scientific advice for the sustainable management of Inside Quillback Rockfish consistent with the Precautionary Approach (PA) Policy through application of the Management Procedure (MP) Framework developed for BC groundfishes (Anderson et al. 2021). The MP Framework evaluates the performance of MPs across alternative plausible states of nature explored in different operating models (OMs). Current stock status partly determines management actions related to policy requirements. The stock status was evaluated with regard to a Limit Reference Point (LRP) and Upper Stock Reference (USR) of 0.4 BMSY and 0.8 BMSY, respectively. The 2021 spawning biomass was estimated to be 88% of BMSY (with an interquartile range of 46-147% credible interval (CI)), above the LRP with a 79% probability, and above the USR with a 52% probability, averaged across three OMs. Since the current stock biomass is estimated to be above the LRP, the conservation objective is to maintain the stock above the LRP after one generation (24 years) with a minimum probability of 75%. Other objectives include maintaining the stock above the USR, and maintaining fishery access and catch. These objectives follow strategic objectives identified in workshops held in 2021 (see Haggarty et al. 2022). The generation time was estimated to be 24 years, based on the natural mortality value of 0.067 and 50% maturity at 8.7 years. Natural mortality is based on the maximum observed age of 80 years. Since the previous assessment, the relationship between natural mortality and maximum observed age has been updated based on meta-analyses in the scientific literature. Five total OMs were explored. Three reference OMs differ in values of mean natural mortality (M = 0.067, 0.055, 0.088). Two robustness OMs include an OM that excludes Area 12 jig survey data, and an OM that assumes low future recruitment. Environmental conditions affecting stock dynamics were considered with the alternative values of natural mortality and low recruitment OMs. Our understanding of the environment and stock productivity, however, is not sufficient to model these relationships mechanistically. The Management Procedures (MPs) evaluated included two constant catch MPs, eight MPs based on an index of survey abundance, and a “no fishing” and “fishing at FMSY” reference MP. All MPs met the conservation objective of being above the LRP after one generation with 75% probability under the OM reference set scenarios. A trade-off between maintaining the stock above the LRP after one generation, and maximizing catch over one generation was identified across the candidate MPs. Minimal trade-off between catch after one generation and catch after three generations was observed. MPs that advise high catches after one generation continue to do so after three generations. Since index-based management procedures were implemented biennially in the projections, we recommend updating the catch advice from the selected MP (if index-based) every two years. Exceptional circumstances that would trigger a re-evaluation of the OMs should be reviewed on a regular basis.

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)0.011
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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 designSimulation or modeling
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
Published2023
Admission routes1
Has abstractyes

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