Tracking the rising extinction risk of sharks and rays in the Northeast Atlantic Ocean and Mediterranean Sea
Bibliographic record
Abstract
The loss of biodiversity is increasingly well understood on land, but trajectories of extinction risk remain largely unknown in the ocean. We present regional Red List Indices (RLIs) to track the extinction risk of 119 Northeast Atlantic and 72 Mediterranean shark and ray species primarily threatened by overfishing. We combine two IUCN workshop assessments from 2003/2005 and 2015 with a retrospective backcast assessment for 1980. We incorporate predicted categorisations for Data Deficient species from our previously published research. The percentage of threatened species rose from 1980 to 2015 from 29 to 41% (Northeast Atlantic) and 47 to 65% (Mediterranean Sea). There are as many threatened sharks and rays in Europe as there are threatened birds, but the threat level is nearly six times greater by percentage (41%, n = 56 of 136 vs. 7%, n = 56 of 792). The Northeast Atlantic RLI declined by 8% from 1980 to 2015, while the higher-risk Mediterranean RLI declined by 13%. Larger-bodied, shallow-distributed, slow-growing species and those with range boundaries within the region are more likely to have worsening status in the Northeast Atlantic. Conversely, long-established, severe threat levels obscure any potential relationships between species' traits and the likelihood of worsening IUCN status in the Mediterranean Sea. These regional RLIs provide the first widespread evidence for increasing trends in regional shark and ray extinction risk and underscore that effective fisheries management is necessary to recover the ecosystem function of these predators.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".