Biology of extinction risk in marine fishes
Bibliographic record
Abstract
We review interactions between extrinsic threats to marine fishes and intrinsic aspects of their biology that determine how populations and species respond to those threats. Information is available on the status of less than 5% of the world's approximately 15500 marine fish species, most of which are of commercial importance. By 2001, based on data from 98 North Atlantic and northeast Pacific populations, marine fishes had declined by a median 65% in breeding biomass from known historic levels; 28 populations had declined by more than 80%. Most of these declines would be sufficient to warrant a status of threatened with extinction under international threat criteria. However, this interpretation is highly controversial, in part because of a perception that marine fishes have a suite of life history characteristics, including high fecundity and large geographical ranges, which might confer greater resilience than that shown by terrestrial vertebrates. We review 15 comparative analyses that have tested for these and other life history correlates of vulnerability in marine fishes. The empirical evidence suggests that large body size and late maturity are the best predictors of vulnerability to fishing, regardless of whether differences among taxa in fishing mortality are controlled; there is no evidence that high fecundity confers increased resilience. The evidence reviewed here is of direct relevance to the diverse criteria used at global and national levels by various bodies to assess threat status of fishes. Simple life history traits can be incorporated directly into quantitative assessment criteria, or used to modify the conclusions of quantitative assessments, or used as preliminary screening criteria for assessment of the approximately 95% of marine fish species whose status has yet to be evaluated either by conservationists or fisheries scientists.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".