Assessing East African trade in seahorse species as a basis for conservation under international controls
Bibliographic record
Abstract
Abstract Seahorses (Hippocampus spp.), many of which are listed as Vulnerable or Endangered on the IUCN Red List, are traded worldwide as souvenirs, aquarium fish and, primarily, for use in traditional medicines. Given concern over the sustainability of this trade, the genus was added to Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) in May 2004. This paper reports findings of the first ever survey of seahorse trade in Africa, conducted in Kenya and Tanzania in May and June 2000. Seahorse trade in Kenya was found to be negligible, with approximately 10 live seahorses exported as aquarium fish annually. Until 1998, however, Kenya may have imported somewhere from 1 to 2.3 t of dried seahorses annually from Tanzania for re‐export to Asian medicine markets. Seahorse trade in Tanzania remained substantial, with at least 630–930 kg of dried seahorse exported directly to Asia each year. Accounts of declines in seahorse availability and seahorse size, although few in number, could be early warning signs that wild populations are suffering, at least locally. Close monitoring of future developments in the trade will be essential to allow for timely conservation action as and when necessary, and would contribute to our understanding of the ecological and economical implications of small‐scale, non‐food fisheries. Copyright © 2004 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".