Policies, law enforcement and sustainable use of nautilus shells in Indonesia and the effect of the 2017 CITES Appendix II listing on their trade
Bibliographic record
Abstract
The trade in wildlife and development often clashes with biodiversity conservation and the sustainable use of natural resources; three of the Sustainable Development Goals specifically recognise the need to focus on assessing the sustainability of fisheries and wildlife trade and reducing its illegal or illicit aspects. We here focus on the chambered nautilus ( Nautilus pompilus ) in Indonesia as a model to explore interactions among society, development, trade regulations, and implications for sustainable development. Despite the species having been protected in Indonesia since 1987, the country was one of the largest suppliers of nautilus shells internationally with 10,000s shells being exported. Domestic trade likewise was not permitted but nautilus shells were commonly and openly offered for sale especially in tourism hotspots. In 2017 all international trade in the species became regulated through the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). We conducted surveys of shops selling whole nautilus shells before (2013–2014) and after (2018–2024) the CITES listing to quantify any changes; we quantified international trade and report on successful prosecutions of nautilus traders. We establish that the island of Bali is the centre for Indonesia’s nautilus shell trade, including its export. Indonesia did not report the export of any nautilus shells post-CITES, reports of substantial imports of nautilus shells into the USA over this period, all from exporters based in Bali, is evidence of ongoing international trade. We recorded 1055 chambered nautilus shells openly offered for sale in Bali, i.e., 363 before and 692 after the CITES listing. The mean number of shells recorded per survey did not change (before 36.4 ± 14.0 shells/survey, after 27.3 ± 13.5 shells/survey), nor did the number of shops offering shells (3.9 ± 0.7 vs 3.4 ± 0.8 shops/survey). Asking prices (US$32 ± 4) increased somewhat following the CITES listing and more shells were on offer with increasing foreign tourist numbers. The number of successful prosecutions for people trading did not change following the 2017 CITES listing; the mean sentence was 6.6 ± 1.7 months imprisonment and a US$149 ± 52 fine (or an additional 2.0 ± 0.3 months imprisonment). We conclude that the 2017 CITES Appendix II listing of chambered nautilus has had no noticeable effect on their domestic trade. We further surmise that Indonesia is not meeting parts of its Sustainable Development Goals in terms of curbing illegal wildlife trade and stopping the illicit flow of money, and by not doing so, hampers biodiversity conservation and sustainable development.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".