Energy transfer efficiency rather than productivity determines the strength of aquatic trophic cascades
Bibliographic record
Abstract
Trophic cascades are important determinants of food web dynamics and functioning, yet mechanisms accounting for variation in trophic cascade strength remain elusive. Here, we used food chain models and a mesocosm experiment (phytoplankton-zooplankton-shrimp) to disentangle the relative importance of two energetic processes driving trophic cascades: primary productivity and energy transfer efficiency. Food chain models predicted that the strength of trophic cascades was increased as the energy transfer efficiency between herbivore and predator (predator efficiency) increased, while its relationship with primary productivity was relatively weak. These model predictions were confirmed by a mesocosm experiment, which showed that the strength of trophic cascade increased with predator efficiency but remained unaffected by nutrient supply rate or primary productivity. Combined, our results indicate that the efficiency of energy transfer along the food chain, rather than the total amount of energy fixed by primary producers, determines the strength of trophic cascades. Our study provides an integrative perspective to reconcile energetic and population dynamics in food webs, which has implications for both ecological research and ecosystem management.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".