Incorporating conservation limit variability and stock risk assessment in precautionary salmon catch advice at the river scale
Bibliographic record
Abstract
Abstract International wild Atlantic salmon management priorities have moved from exploitation to conservation since the 1990s, recognizing the need to protect diversity and abundance at individual river levels amid widespread declines. Here we review international salmon-stock assessments and describe a simple, transferable catch-advice framework, established for management of fisheries that conforms to international obligations. The risk assessment approach, applied at the river scale, jointly incorporates uncertainty in estimated and forecasted returning salmon numbers with the level of uncertainty around spawning requirements (Conservation Limits). Outputs include quantification of risk of stocks not attaining conservation limits (CL) and surpluses above CL on stocks able to support sustainable exploitation via total allowable catches (TAC), with monitoring by rod catch or fish counter. Since management implementation and cessation of at-sea mixed-stock fisheries, there has been a deterioration in the performance of many individual stocks, without any sustained increase in fisheries open to harvest. Given declines in mid-latitude Atlantic salmon populations over 30 years, the novel framework presented provides an approach to protect stocks failing to meet spawning thresholds while supporting sustainable exploitation of those achieving them. On-going management policy of adopting scientific advice and allowing exploitation only on stocks exceeding CLs is central to the objective of protecting salmon stocks.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".