Could recent overfishing of New England groundfish have been prevented? A retrospective evaluation of alternative management strategies
Bibliographic record
Abstract
We conducted a retrospective evaluation of alternative management strategies for stocks in the New England groundfish complex that have had recent history of target catches being set above the level that defines overfishing. In many cases the original target catches were unsustainable and would have resulted in stock collapses if the target catch had been removed. We evaluated (i) alternative harvest control rules, (ii) whether or not to do projections, (iii) whether the inputs to the projections (starting abundance and future recruitments) should be modified, and (iv) whether the target catches should be smoothed to prevent large changes from year to year. The greatest reductions in target catches resulted when no projections were done and the target catch was fixed over the period between assessments. Large reductions in target catches also occurred when a downward adjustment was made to the starting abundance in the projections based on the retrospective pattern. Neither approach alone was sufficient to prevent overfishing for most stocks, but when used in conjunction with one another or with an alternative control rule that reduced the target harvest rate as biomass fell below the target, the magnitude and frequency of overfishing was greatly reduced for most stocks. Attempts to adjust recruitment based on perceived changes over time were also effective for a few stocks, while attempts to smooth the target catches over often resulted in increases in the target catches.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".