Revised sablefish operating model
Bibliographic record
Abstract
Management of Sablefish (Anoplopoma fimbria) in British Columbia (BC) is guided by a Management Strategy Evaluation (MSE) process that has been jointly developed by Fisheries and Oceans Canada (DFO) and the BC Sablefish fishing industry. The MSE process is aligned with the requirements of the Fish Stocks provisions and domestic harvest policy (DFO 2009). Annual total allowable catches (TACs) for BC Sablefish have been set in a transparent and sustainable manner using simulation-tested management procedures (MPs) since 2011. The Sablefish operating model (OM) is used to provide an updated assessment of stock status and to simulation-test MPs under alternative scenarios representing stock and fishery dynamics. A revised version of the OM has been developed for 2022 that incorporates updated data as well as new hypotheses about stock and fishery dynamics. The revised OM was transitioned to a new software platform that is better supported in the fisheries science community and has better estimation performance than the original platform. Transition analyses showed that both implementations produced similar results, while the new platform offered better model diagnostics and computational performance. Stock status in 2022 was assessed via a weighted-average of the five OM scenarios representing uncertainty about productivity and recent female spawning stock biomass (where, female spawning stock biomass is hereafter denoted as B). OM scenario weights were based on plausibility values assigned by analysts. BC Sablefish female spawning stock biomass for 2022 (B2022) was estimated to be well above the level of female spawning stock biomass associated with maximum sustainable yield (BMSY). The weighted average estimate of B2022 is above BMSY with 92% probability (median value of 1.32 times BMSY). The estimated harvest rate (U) of legal-sized Sablefish in 2021 is below the harvest rate at MSY (UMSY) with 94% probability (median value of 0.72 times UMSY). When viewed individually, each of the five OM scenarios indicated a 100% probability of B2022 being above the limit reference point (LRP) of 0.4BMSY, and four of the five OMs estimated a 100% probability of B2022 being above the upper stock reference (USR) of 0.8BMSY. The OM scenario representing the lowest recent female spawning stock biomass indicated a 92% probability of B2022 being above the USR. Closed-loop simulations were used to test whether the current MP, with a maximum target legal harvest rate of 5.5%, was able to meet operational fishery objectives under the revised OM scenarios. Alternative versions of the current MP with a range of target harvest rates were also tested. Simulation performance showed that an increase in the current maximum target legal harvest rate up to 7.5% could be considered while still meeting conservation objectives aimed at remaining above the LRP (objective 1) and achieving the target reference point (TRP; objective 3). Environmental variables (EVs) potentially affecting BC Sablefish population dynamics were examined via pairwise correlations between eight EVs, annual recruitment, and a body condition index. None of the EVs were strongly correlated to recruitment. While the impact of climate change on BC Sablefish is unknown, recent research indicates that increasing temperature may increase habitat suitability for Sablefish. The potential risk of not including EVs into the BC Sablefish operating model seems low at this time. Future operating models should further explore alternative approaches to modelling at-sea releases to better account for release mortality in operating model simulations
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".