Asymmetric responses of terrestrial C:N:P stoichiometry to precipitation change
Bibliographic record
Abstract
Abstract Aim The aim was to test whether the responses of C:N:P stoichiometry in plant–soil–microorganism systems to precipitation changes support the prediction of the double asymmetry model, which predicts ecological processes (i.e. aboveground productivity, soil microbial community, and soil respiration) are more sensitive to increased precipitation (R+) than decreased precipitation (R−) under normal precipitation changes, whereas more sensitive to R− than R+ under extreme precipitation changes. Location Global. Time period 1999–2020. Major taxa studied Plants, soils, and soil microorganisms. Methods We performed a global meta‐analysis of 848 observations (587 R− and 261 R+ manipulations) from 160 studies, which tested the effects of precipitation changes on C:N:P across plants, soils, and soil microorganisms. The data encompassed broad variations in ecosystems, climate, precipitation intensity, and experimental duration. Results We revealed that the C:N and C:P ratios of different ecosystem compartments were more sensitive to moderate R+ rather than moderate R−, whereas they exhibited a higher response to extreme R− rather than extreme R+, which supported the prediction of the double asymmetry model. Moreover, such responses were more pronounced under higher precipitation intensities and longer experimental duration. The effects of precipitation changes on the C:N:P stoichiometry of plants, soils, and soil microorganisms were consistent across ecosystem types (i.e. forests and grasslands) and associated background climates (i.e. mean annual temperature and precipitation). Main conclusions Our findings provide the first evidence of the asymmetric responses of C:N:P stoichiometry in above‐ and belowground systems to precipitation change. These results extend the double asymmetric model and improve our understanding of C and N cycling, as well as facilitate the prediction of ecosystem responses to precipitation changes.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 | 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".