Broadbill swordfish: status of established fisheries and lessons for developing fisheries
Bibliographic record
Abstract
Guidelines for the assessment and management of developing swordfish fisheries are derived through an examination of five swordfish fisheries. As they develop, swordfish fisheries may be inclined to local depletion around underwater features, such as seamounts and banks. Few nations have applied the precautionary approach in managing their developing swordfish fisheries. Without controls, swordfish fisheries expand geographically and fishing effort increases, often overshooting optimum levels. However, it is difficult to distinguish clear evidence of fishery collapse; modern longliners harvest widely distributed tuna and swordfish and they are able to relocate to distant areas or switch between target species in response to fluctuations in species abundance and price. Furthermore, the wide distribution of swordfish combined with year‐round spawning and high growth rates amongst juveniles probably contribute to the apparent resilience of swordfish stocks to intensive harvesting. Over half the world’s swordfish catch is taken as an incidental catch of longliners fishing for tuna. In several areas, such as the North Atlantic, catch quotas have sometimes caused tuna longline fishers to discard swordfish. Minimum size limits have also resulted in discarding of swordfish in tuna fisheries and in dedicated swordfish fisheries. In addition to weakening the effectiveness of those management measures, bycatch and discarding add to the complexities of managing swordfish fisheries and to uncertainties in assessing the stocks. Longliners that target swordfish often fish at high latitudes where interactions with marine wildlife, such as seabird, are generally more frequent than at low latitudes. Concern over incidental catches of marine wildlife and other species is becoming a driving force in the management of several swordfish fisheries. Fishery management organisations will need to implement management measures to protect non‐target species and gather reliable data and information on the situation by placing observers on boats fishing for swordfish.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".