Grey seal predation mortality on three depleted stocks in the West of Scotland: What are the implications for stock assessments?
Bibliographic record
Abstract
The decrease in groundfish stocks in the North Atlantic since the mid-1900s coupled with increases in grey seal (Halichoerus grypus) populations is responsible for an enduring controversy between fishers and conservationists regarding the role seals have played in stock declines. We used a Bayesian state-space model to investigate stock trends in the presence of grey seals and associated maximum sustainable yield (MSY) reference points in the West of Scotland. This study provides new estimates of seal predation mortality on haddock (Melanogrammus aeglefinus) and whiting (Merlangius merlangus) and updates the estimates for cod (Gadus morhua), which together form the traditional main components of the mixed demersal fishery in this area. Grey seal predation mortality is greatest on cod, resulting in estimates of total natural mortality higher than those used in the current ICES assessments. Seal predation mortality is low for haddock and whiting. Considering seal predation in stock assessments changes the scale of biomass and fishing mortality estimates for the three stocks. The estimates of F0.1 and FMSY are sensitive to seal predation for cod and whiting but not for haddock. In all cases, MSY decreases with increased seal predation.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".