Status-quo management of marine recreational fisheries undermines angler welfare
Bibliographic record
Abstract
Recreational fisheries can have a significant impact on fish populations and can suffer from the same symptoms of open access as commercial fisheries. However, recreational fisheries receive little attention compared with their commercial counterparts. Regulations designed to allocate scarce fish, such as seasonal closures and bag limits, can result in significant losses of value to anglers. We provide an estimate of these foregone benefits by estimating the potential gains to implementing management reforms of the headboat portion of the recreational red snapper fishery in the US Gulf of Mexico. This fishery has suffered from a regulatory spiral of shortened seasons and lowered bag limits in spite of rebuilding stocks. We gather primary survey data of headboat anglers that elicit trip behavior and their planned number and seasonal distribution of trips under status-quo and alternative management approaches. We use these data to estimate a model of anglers' seasonal trip demand as a function of the ability to retain red snapper, bag limits, and fees. We find that a hypothetical rights-based policy, whereby vessels with secure rights to a portion of annual catch could offer their customers year-round fishing in exchange for lower per-angler retention and increased fees, could raise the average angler's welfare by $139/y. When placed in the global context of recreational fishing, these estimates suggest that status-quo management may deprive anglers of billions of dollars of lost economic value per year.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".