Assessment of Atlantic mackerel in 2022
Bibliographic record
Abstract
Based on preliminary data, mackerel landings in Canadian waters totalled 4,505 t in 2021 (TAC = 4,000 t) and 74 t were landed in 2022 (TAC = 0 t). Mackerel landings in U.S. waters totalled 8,053 t in 2021 and 3,302 t in 2022, of which 20–80% is assumed to be from the northern contingent. The Spawning Stock Biomass (SSB) of the northern contingent of mackerel estimated with the revised assessment model was at its lowest values in 2021 and 2022 (40% and 42% of the Limit Reference Point; LRP), relative to 79% and 56% of the LRP in 2019 and 2020, respectively. Recent average recruitment (2012–2022) is at 27% of previous levels (1969–2011). There have been no signs of a substantial recruitment event since 2015. The probability of the SSB exiting the Critical Zone by 2025 ranges from 37.5% under a TAC of 0 t to 17.5% under a TAC of 8,000 t. The probability that the SSB in 2025 will be greater than in 2023 ranges from 78.5% (75–82%) under a TAC of 0 t to 32.5% (29–36%) under a TAC of 8,000 t. The probability of the SSB exiting the Critical Zone by 2025 under a baseline scenario assuming no Canadian fisheries removals is 38.5% (38–39%). The probability that the SSB in 2025 will be greater than in 2023 in the same scenario is 81% (78–84%). An investigation of predation pressure on mackerel by various predators in Canadian and U.S. waters suggests an overall increase in predation-induced mackerel mortality over time, with high interannual variability. The stock’s decline into the Critical Zone (2005–2011) was associated with high total landings and estimated fishing mortality above the reference level, with no further reduction in stock productivity and no known evidence of habitat degradation or loss. The northern contingent of mackerel has been in or near the Critical Zone since 2011. The available evidence indicates the stock rebuilding potential is currently limited by a truncated age structure, low recruitment, and high predation pressure.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".