Decline in top predator body size and changing climate alter trophic structure in an oceanic ecosystem
Bibliographic record
Abstract
Globally, overfishing large-bodied groundfish populations has resulted in substantial increases in their prey populations. Where it has been examined, the effects of overfishing have cascaded down the food chain. In an intensively fished area on the western Scotian Shelf, Northwest Atlantic, the biomass of prey species increased exponentially (doubling time of 11 years) even though the aggregate biomass of their predators remained stable over 38 years. Concomitant reductions in herbivorous zooplankton and increases in phytoplankton were also evident. This anomalous trophic pattern led us to examine how declines in predator body size (approx. 60% in body mass since the early 1970s) and climatic regime influenced lower trophic levels. The increase in prey biomass was associated primarily with declines in predator body size and secondarily to an increase in stratification. Sea surface temperature and predator biomass had no influence. A regression model explained 65 per cent of prey biomass variability. Trait-mediated effects, namely a reduction in predator size, resulted in a weakening of top predation pressure. Increased stratification may have enhanced growing conditions for prey fish. Size-selective harvesting under changing climatic conditions initiated a trophic restructuring of the food chain, the effects of which may have influenced three trophic levels.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".