The stoichiometry of soil microbial biomass determines metabolic quotient of nitrogen mineralization
Bibliographic record
Abstract
Abstract Soil nitrogen (N) mineralization is crucial for the sustainability of available soil N and hence ecosystem productivity and functioning. Metabolic quotient of N mineralization ( Q min ), which is defined as net soil N mineralization per unit of soil microbial biomass N, reflects the efficiency of soil N mineralization. However, it is far from clear how soil Q min changes and what are the controlling factors at the global scale. We compiled 871 observations of soil Q min from 79 published articles across terrestrial ecosystems (croplands, forests, grasslands, and wetlands) to elucidate the global variation of soil Q min and its predictors. Soil Q min decreased from the equator to two poles, which was significant in the North Hemisphere. Soil Q min correlated negatively with soil pH, total soil N, the ratio of soil carbon (C) to N, and soil microbial biomass C, and positively with mean annual temperature and C:N ratio of soil microbial biomass at a global scale. Soil microbial biomass, climate, and soil physical and chemical properties in combination accounted for 41% of the total variations of global soil Q min . Among those predictors, C:N ratio of soil microbial biomass was the most important factor contributing to the variations of soil Q min (the standardized coefficient = 0.39) within or across ecosystem types. This study emphasizes the critical role of microbial stoichiometry in soil N cycling, and suggests the necessity of incorporating soil Q min into Earth system models to better predict N cycling under environmental change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".