Can Cooperative Management of Tuna Fisheries in the Western Pacific Solve the Growth Overfishing Problem?
Bibliographic record
Abstract
Tuna fisheries in the western and central Pacific Ocean are important globally for both food and economic security. Yellowfin and bigeye tuna stocks in this region are declining, in part due to the juvenile bycatch of these species by the purse seine fishery using floating objects and fish aggregating devices (FADs). This leads to a conflict between the longline and handline fisheries, which target adult fish, and the purse seine fishery, whose bycatch is leading to growth overfishing. This paper develops a bioeconomic game-theoretic equilibrium model to determine if, at equilibrium, the elimination of juvenile fishing could bring economic benefits to the region. Specifically, we examine non-cooperative and cooperative outcomes for a threeplayer game: purse seine, longline and handline, incorporating skipjack, yellowfin and bigeye as target species. Our results suggest that the reduction or elimination of fishing on floating objects could result in increased net benefits to the region from US $100 million to US $350 million per year; however, this gain is not shared equitably among the three fisheries. Notably, purse seine fisheries stand to lose economically through this type of management decision. The realization of potential economic gains for this region will require the formation of a cooperative sharing system.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".