Response of Anglers to Less-Restrictive Harvest Controls in a Recreational Atlantic Salmon Fishery
Bibliographic record
Abstract
Abstract In any fishery, it is important to know whether management decisions have an impact on catch and effort. This study demonstrates that bag limits can be an effective management tool for reducing effort when dealing with a retention-oriented angling population. Since 1997, four different management regimes (MRs) have been applied to a recreational Atlantic Salmon Salmo salar fishery on Harry's River in Newfoundland, Canada. The four MRs include catch and release only (MR1); catch and release at the start of the season, with allowed retention after an in-season review of stock status (MR2); retention angling for the whole season, with a fixed bag limit of two salmon (MR3); and retention angling for the whole season, with an increase in bag limit from two to four salmon after an in-season review (MR4). A time series MA(1) model (moving average of order 1) was used to study the effect of MR on effort, with salmon abundance (measured as adult returns to the river) included as a confounding variable. Significantly less effort was reported by anglers fishing Harry's River under an MR1 fishery compared with any other management scenario. However, MR1 produced the greatest average CPUE, suggesting that a catch-and-release fishery attracted a more skilled or differently motivated angler. Catch and effort were linearly correlated, with an expected increase in total catch of 0.6 Atlantic Salmon for every extra day of effort. The greatest difference in effort occurred between MR1 and MR3, suggesting that a compromise between catch and release only and a bag limit of four salmon would likely satisfy challenge-seeking as well as harvest-oriented anglers.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".