Spatiotemporal Hotspots of Juvenile Bigeye and Yellowfin Tuna Catches Under Drifting Fish‐Aggregating Devices in the Eastern Atlantic Ocean to Define Moratorium Strata
Bibliographic record
Abstract
ABSTRACT To reduce catches of juvenile bigeye and yellowfin tuna, while maintaining skipjack catches under drifting fish aggregating devices (dFAD), we analyzed spatiotemporal distributions of dFAD catches by European purse seiners in the Eastern Atlantic Ocean during 1996–2019. To detect hotspots of juvenile dFAD catches, we: identified periods of maximum abundance using a seasonal sub‐series diagram; normalized monthly FAD catches per unit effort; and used emerging hotspots analysis on spatiotemporal density. Two main spatiotemporal strata were identified in the Guinean Gulf, which could be used to establish moratoria on dFAD fishing. These spatiotemporal strata differed from the existing ICCAT moratorium, which spanned a larger part of the African coast. Our findings also indicated that time‐area closures of dFAD‐fishing lasting 3–4 months in smaller areas could be more effective than the current dFAD moratorium to reduce unwanted bycatch in the Eastern Atlantic region. The two metrics we developed for comparison provided clear and measurable evidence that demonstrated how strategic and data‐informed moratoriums can lead to substantial improvements in conservation.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".