Galapagos giant tortoise trafficking case demonstrates the utility and applications of long‐term comprehensive genetic monitoring
Bibliographic record
Abstract
Abstract Illegal Wildlife Trade (IWT) is a cause for global concern as pressure stemming from IWT threatens wild species and can even lead to extinction. Galapagos giant tortoises (Chelonoidis sp.) are a group of threatened species protected under CITES, which forbids their import–export for international trade; however, IWT of this group persists. In this study, we describe the use of two extensive genetic repositories of mitochondrial and nuclear microsatellite markers for Galapagos giant tortoises to identify an unsuspected source of trafficked juvenile tortoises. Our genetic analyses, together with morphological and captive‐born registry data, provide evidence that the smuggled juveniles were from two breeding centers dedicated toward conservation located on the Galapagos islands of San Cristobal and Isabela. This is the first documentation of smuggled tortoises being taken from breeding centers rather than the wild. The findings from our genetic analysis provided key evidence that enabled legal investigation. This case demonstrates the importance of the comprehensive genetic characterization of Galapagos giant tortoises and the suitability of standard genetic markers for identifying the species and islands of origin of trafficked animals. We also discuss the efficacy, adequacy, and reach of existing measures against IWT. Overall, this case illustrates an important application of long‐term and comprehensive genetic repositories of endangered species and the crucial role of collaborations among academic laboratories maintaining those repositories, local practitioners responsible for species protection, and the bodies that implement and enforce antitrafficking regulations.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".