<i>Probarbus jullieni</i> and <i>Probarbus labeamajor</i>: the management and conservation of two of the largest fish species in the Mekong River in southern Laos
Bibliographic record
Abstract
Abstract Probarbus jullieni and Probarbus labeamajor are two of the largest carps in the Mekong River Basin, each reaching a maximum weight of about 70 kg. P. jullieni is listed in Appendix 1 of the Convention on the International Trade in Endangered Species, and both are listed on the IUCN Red List of Threatened Species, the first as ‘endangered’ and the second as ‘data deficient’. Six years of quantitative monitoring of a large‐meshed gill net fishery for Probarbus just below the Khone Falls in Khong district, Champasak province, in southern Laos shows that 78% of the overall catch is comprised of Probarbus, with P. jullieni making up 65% of landings. Over the 6‐year period catches of Probarbus declined significantly. However, catch‐per‐unit effort statistics do not indicate that the fishery is in decline, although fishers are convinced that real stock reductions are a large part of the reason for catch declines and decreases in fishing effort. A number of ecological and social factors are affecting the number and quality of gill nets in use, the length of fishing seasons, and gill net efficiency, making it difficult to compare catch‐per‐unit effort between years. There has been a shift from using large‐meshed gill nets for catching Probarbus to targeting smaller species using gill nets with smaller mesh‐sizes. This is an example of the ‘fishing down’ of a Mekong fish community, in which large long‐lived species are the first to be affected by heavy fishing pressure. Copyright © 2006 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".