The role of catch shares in Pacific halibut bycatch reduction in the U.S. West Coast bottom trawl fishery
Bibliographic record
Abstract
Pacific halibut (Hippoglossus stenolepis) are a valuable target species in the U.S. and Canada, but are also caught as bycatch in other groundfish fisheries. In 2011, a catch shares (CS) management program was implemented in the U.S. west coast limited entry (LE) bottom trawl fishery, shifting responsibility for catch limits, including P. halibut bycatch, from the fleet to individual vessels. After CS implementation, P. halibut bycatch decreased significantly from an annual mean of 312.5 metric tons (mt) (2007-2010) to 65.6 mt (2011-2014). I hypothesized that this reduction in P. halibut bycatch resulted from changes in fishing behavior initiated by the shift to CS. I evaluated changes in variables associated with P. halibut bycatch, including fishing latitude, depth, duration, and catch of correlated species, before and after CS implementation. Comparisons of associated variables under LE versus CS management showed that significant changes to all variables occurred after CS implementation. To predict and compare relative P. halibut bycatch among LE versus CS hauls, I modeled how associated variables predicted P. halibut encounters, bycatch weight, and mortality for LE data, and re-ran these models for CS data. My results indicate that the relationship between predictor variables and P. halibut bycatch changed under CS from what was observed in the LE fleet. These changed relationships suggest that fishers altered their behavior following the management shift, likely contributing to the reduction in P. halibut bycatch under CS management. This work will help the Pacific Fishery Management Council and International Pacific Halibut Commission understand how CS has changed fishing behavior and P. halibut bycatch in bottom trawl fisheries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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 teacher head, 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".