Letter: Trophic interactions regulate peatland carbon cycling
Bibliographic record
Abstract
Abstract Peatlands are the most efficient natural ecosystems for long‐term storage of atmospheric carbon. Our understanding of peatland carbon cycling is based entirely on bottom‐up controls regulated by low nutrient availability. Recent studies have shown that top‐down controls through predator‐prey dynamics can influence ecosystem function, yet this has not been evaluated in peatlands to date. Here, we used a combination of nutrient enrichment and trophic‐level manipulation to test the hypothesis that interactions between nutrient availability (bottom‐up) and predation (top‐down) influence peatland carbon fluxes. Elevated nutrients stimulated bacterial biomass and organic matter decomposition. In the absence of top‐down regulation, carbon dioxide (CO 2 ) respiration driven by greater decomposition was offset by elevated algal productivity. Herbivores accelerated CO 2 emissions by removing algal biomass, while predators indirectly reduced CO 2 emissions by muting herbivory in a trophic cascade. This study demonstrates that trophic interactions can mitigate CO 2 emissions associated with elevated nutrient levels in northern peatlands.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.012 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.009 |
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".