Predation risk, stoichiometric plasticity and ecosystem elemental cycling
Bibliographic record
Abstract
It is widely held that herbivore growth and production is limited by dietary nitrogen (N) that in turn constrains ecosystem elemental cycling. Yet, emerging evidence suggests that this conception of limitation may be incomplete, because chronic predation risk heightens herbivore metabolic rate and shifts demand from N-rich proteins to soluble carbohydrate-carbon (C). Because soluble C can be limiting, predation risk may cause ecosystem elemental cycling rates and stoichiometric balance to depend on herbivore physiological plasticity. We report on a stoichiometrically explicit ecosystem model that investigates this problem. The model tracks N, and soluble and recalcitrant C through ecosystem compartments. We evaluate how soluble plant C influences C and N stocks and flows in the presence and absence of predation risk. Without risk, herbivores are limited by N and respire excess C so that plant-soluble C has small effects only on elemental stocks and flows. With predation risk, herbivores are limited by soluble C and release excess N, so plant-soluble C critically influences ecosystem elemental stocks flows. Our results emphasize that expressing ecosystem stoichiometric balance using customary C:N ratios that do not distinguish between soluble and recalcitrant C may not adequately describe limitations on elemental cycling.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".