Soil p<scp>H</scp>‐dependent nitrogen stimulation of plant biomass: magnesium and calcium as key constraints
Bibliographic record
Abstract
Anthropogenic nitrogen (N) deposition can alleviate N limitation and stimulate plant growth in many terrestrial ecosystems. While theoretical models often emphasize phosphorus limitations as a constraint on this positive N effect, the impact of N-induced magnesium (Mg) and calcium (Ca) deficits due to soil acidification has been largely overlooked. Here, we synthesized data from 243 experiments across diverse terrestrial ecosystems to investigate the role of Mg and Ca in plant biomass responses to N addition. We found that the effect of N addition on aboveground biomass (AGB) shifted from neutral in low pH (≤ 4.5) to positive in medium (4.5-7.5) and high pH (> 7.5) soils. By contrast, belowground biomass (BGB) responses to N addition were independent of soil pH, leading to asymmetric increases in AGB and BGB. These variations in biomass accumulation across pH levels were primarily explained by changes in foliar Mg and Ca concentrations, which were negatively affected by N addition in low-pH soils but remained stable in medium and high-pH soils. Our findings underscore the critical role of Mg and Ca in modulating plant responses to N fertilization, providing new insights for improving Earth system models and better predicting climate-biosphere feedback.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".