Status and challenges for sustainable billfish fisheries in the Western Indian Ocean
Bibliographic record
Abstract
Billfish species (families Istiophoridae and Xiphiidae) are caught in artisanal, recreational, and commercial fisheries throughout the Western Indian Ocean region. However, data and information on the interactions among these fisheries and the ecology of billfish in the WIO are not well understood. Using an in-depth analysis of peer-reviewed articles, grey literature, observation studies, and authors' insider knowledge, we summarize the current state of knowledge on billfish fisheries in 10 countries. To describe historical and current trends, we examined fisheries statistics from governmental and non-governmental agencies, sportfishing clubs' reports, diaries of sportfishing captains, and the catch and effort databases of the Indian Ocean Tuna Commission. We highlight two key points. First, billfish fisheries in the Western Indian Ocean are highly diverse, comprising two distinct segments-coastal and oceanic. However, data are poor for most countries with significant gaps in information especially for sport and artisanal fisheries. Second, the evidence assembled showed that billfish species have immense social, cultural, and economic value. Swordfish are targeted by both large-scale and semi-industrial fisheries, while other billfish species, particularly marlin, are highly sought after by sport fisheries in most countries. Our paper provides a comprehensive review of billfish fisheries and available information in the context of the WIO underscoring the need to strengthen data collection and reporting, citizen science, and collaborative sustainable development and management of billfish. Supplementary Information: The online version contains supplementary material available at 10.1007/s11160-022-09725-8.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".