A Global Red List for Hydrothermal Vent Molluscs
Bibliographic record
Abstract
With the accelerating development of direct and indirect anthropogenic threats, including climate change and pollution as well as extractive industries such as deep-sea mining, there is an urgent need for simple but effective solutions to identify conservation priorities for deep-sea species. The International Union for Conservation of Nature (IUCN) Red List of Threatened Species is an effective and well-recognized tool to promote the protection of species and presents an opportunity to communicate conservation threats to industry, policy makers, and the general public. Here, we present the Vent Red List for molluscs: a complete global assessment of the extinction risk of all described molluscs endemic to hydrothermal vents, a habitat under imminent threat from deep-sea mining. Of the 184 species assessed, 62% are listed as threatened: 39 are Critically Endangered, 32 are Endangered, and 43 are Vulnerable. In contrast, the 25 species that are fully protected from deep-sea mining by local conservation measures are assessed as Least Concern, and a further 45 species are listed as Near Threatened, where some subpopulations face mining threats while others lie within protected areas. We further examined the risk to faunas at specific vent sites and biogeographic regions using a relative threat index, which highlights the imperiled status of vent fields in the Indian Ocean while other vent sites within established marine protected areas have a high proportion of species assessed as Least Concern. The Vent Red List exemplifies how taxonomy-driven tools can be utilized to support deep-sea conservation and provides a precedent for the application of Red List assessment criteria to diverse taxa from deep-sea habitats.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".