The first IUCN Red List of cold-water corals highlights global declines
Bibliographic record
Abstract
Abstract The most well-known species-based conservation tool is the International Union for the Conservation of Nature (IUCN) Red List of Threatened Species. The current coverage of species in the Red List is known to under-represent benthic marine species. Cold-water corals (CWCs) are increasingly recognised as key to deep-water biodiversity and integral to protected vulnerable marine ecosystems (VMEs), but no deep-sea coral species were previously included in the Red List. We selected 22 cold-water coral species in the Northeast Atlantic, including 4 reef-forming stony corals and 18 octocorals including sea pens and gorgonians, and completed the first IUCN Red List global assessments for corals inhabiting the deep sea. Most of the species assessed herein are habitat-forming, including those that form coral reefs and marine animal forests such as coral gardens or sea pen fields. We assessed eight species as near threatened, and one species as globally vulnerable: Desmophyllum pertusum. Some of these species are distributed across an entire ocean basin, but the cumulative damage from human impacts have reduced populations by upwards of 30% from recent baselines. In addition, three species are listed as data deficient, and the remaining 10 species are assessed as least concern. All assessments in threatened categories were made using Red List criterion A, based on evidence of past population declines, and the main threats in most cases are related to bottom-contact fishing. We also present five case studies that illustrate the application of the Red List criteria to cold-water corals. Despite technological limitations to establishing baseline populations, documented large-scale declines of widespread species clearly demonstrate the magnitude of threats to deep-sea ecosystems and the need for large-scale conservation measures.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".