Strengthening protection of endemic wildlife threatened by the international pet trade: The case of the Australian shingleback lizard
Bibliographic record
Abstract
Abstract Unsustainable wildlife trade threatens an increasing number of species globally. Australia has a particularly rich and endemic herpetofauna, which is coveted on the international pet market. While Australia implements domestic protection of most of its native species, there is little to no regulation of international trade once live animals have been smuggled out of the country. This is a threat for a variety of rare, unique and/or range‐restricted species, subspecies and locality morphs. One of these species is the shingleback lizard ( Tiliqua rugosa ). We compiled Australian seizure data and international online trade data pertaining to shinglebacks. We found all four subspecies in trade across Asia, Europe and North America. Here we provide evidence that all four shingleback subspecies are illegally extracted from the wild in Australia and smuggled to international destinations, where they are sold and distributed globally. While shinglebacks are a protected species in Australia and can only be exported legally under a federal permit, their import into, and trade between, other countries is often not illegal, even in the absence of such a permit. These contradictory legal frameworks apply to the majority of nationally protected native fauna and must be addressed by each importing country on an individual basis; that is, by changing their legislation to cover and protect species that are nationally protected in their native range. Meanwhile, however, we argue that listing T . rugosa in Appendix III of the Convention on International Trade in Endangered Species of Wild Fauna and Flora is a meaningful way to provide other countries with the legal means to confiscate illegally exported shinglebacks from Australia. Our findings and recommendations are directly relevant for potential future Appendix III consideration of other nationally protected species that are found in international trade.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".