An overview of marine ornamental fish breeding as a potential support to the aquarium trade and to the conservation of natural fish populations
Bibliographic record
Abstract
The aquarium fi sh trade moves more than two billion live fi sh worldwide per year. For fresh water organisms, more than 90 % of them are captive bred, but over 90 % of commercial marine organisms are wild-caught. Wild-caught organisms come mainly from coral reefs and adjacent areas. Destructive collection techniques, such as cyanide, quinaldine, even dynamite or explosives, are commonly used. These techniques not only affect the target fi sh but causes terrible damages to the ecosystems and the reef habitat itself, as well as coral and crustacean bleaching. This damage has not been assessed globally, but locally, where populations have been overharvested; it has created environmental imbalances due to the selective fi sheries focused on a few species, sexes or ages with high market value. A number of measures can be taken in order to reduce the environmental damage. The most important depend largely on the efforts by local governments, community groups, environ-mental organisations and the private sector. The fi nal objective of these measures is to place the ornamental trade on a sustainable basis. Moreover, new research into aquaculture technology on target species with the aim of diminishing the fi shing pressure on wild stocks as well as increasing the effectiveness of aquaculture facili-ties must be carried out. This is especially important in rural populations dependent on the aquarium trade. The present article presents an overview of the ornamental fi sh trade regarding the most important species involved and their situation and the harvesting effects on the ecosystem. In addition it discusses updated information on breeding protocols for some high-value marine fi sh species.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".