Structure and stability in exploited marine fish communities: quantifying critical transitions
Bibliographic record
Abstract
Abstract Correlations between time series of the abundance of predator and prey fish species in heavily exploited western North Atlantic marine fisheries vary temporally but are generally positive in southern, warmer waters and negative in northern, colder ones. The correlations provide an index of trophic structure and dynamics. We construct a framework to quantify critical thresholds between states in which the predator–prey correlations are positive or negative. We do so by developing a quantitative model of the distribution of the correlations between predator (15 species) and prey (8 species) functional groups based on the annual predator depletion rates and bottom temperatures (or alternatively species richness). The model accounts for 58% of the variance of the correlations with a root mean square error of 0.3. This index of trophic structure indicates that warmer, species‐rich, southern fish populations resist transformation from positive to negative predator–prey correlations at exploitation rates that can be double those in the colder, relatively species‐poor, northern areas. The model can be used to set limits for exploitation rates that preserve the functional relationships between predator–prey groups in emerging fisheries, and to assess the potential for and measures required to achieve recovery of degraded fish communities.
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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 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".