Threat and decline in fishes: an indicator of marine biodiversity
Bibliographic record
Abstract
Recent policy commitments aim to reduce biodiversity loss and integrate environmental concerns into fisheries management. However, there are few operational indicators for reporting biodiversity trends and judging progress in relation to management objectives. Here we develop a threat indicator based on the population status of a suite of 23 North Sea fishes from 1982 to 2001 estimated using World Conservation Union (IUCN) Red List decline criteria. The composite indicator was calculated from the weighted average of the threat scores of individual species in each year and varies from 0 to 3, where a score of 3 is equivalent to each species qualifying as "critically endangered". The proportion of threatened fishes, their degree of threat, and the composite indicator value increased steadily over time. The composite indicator value has been >1 since the late 1990s, equivalent to all species meeting the "vulnerable" criterion. A suitable reference trajectory, consistent with the World Summit on Sustainable Development commitment to "achieve by 2010 a significant reduction of the current rate of biodiversity loss" would be a significant reduction in the rate of increase in this indicator before 2010, a limit reference point could be 1 (all species vulnerable) and a target reference point could be 0 (no threatened species).
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".