Use of Population Viability Analysis to Evaluate CITES Trade‐Management Options for Threatened Marine Fishes
Bibliographic record
Abstract
Achieving multiple conservation objectives can be challenging, particularly under high uncertainty. Having agreed to limit seahorse (Hippocampus) exports to sustainable levels, signatories to the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) were offered the option of a single 10-cm minimum size limit (MSL) as an interim management measure for all Hippocampus species (> or =34). Although diverse stakeholders supported the recommended MSL, its biological and socioeconomic implications were not assessed quantitatively. We combined population viability analysis, model sensitivity analysis, and economic information to evaluate the trade-off between conservation threat to and long-term cumulative income from these exploited marine fishes of high conservation concern. We used the European long-snouted seahorse (Hippocampus guttulatus) as a representative species to compare the performance of MSLs set at alternative biological reference points. Our sensitivity analyses showed that in most of our scenarios, setting the MSL just above size at maturity (9.7 cm in H. guttulatus) would not prevent exploited populations from becoming listed as vulnerable. By contrast, the relative risk of decline and extinction were almost halved--at a cost of only a 5.6% reduction in long-term catches--by increasing the MSL to the size reached after at least one full reproductive season. On the basis of our analysis, a precautionary increase in the MSL could be compatible with sustaining fishers' livelihoods and international trade. Such management tactics that aid species conservation and have minimal effects on long term catch trends may help bolster the case for CITES trade management of other valuable marine fishes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".