Relative importance between nitrification and denitrification to N<sub>2</sub>O from a global perspective
Bibliographic record
Abstract
Abstract Nitrous oxide (N 2 O) is a potent greenhouse gas, and its mitigation is a pressing task in the coming decade. However, it remains unclear which specific process between concurrent nitrification and denitrification dominates worldwide N 2 O emission. We snagged an opportunity to ascertain whence the N 2 O came and which were the controlling factors on the basis of 1315 soil N 2 O observations from 74 peer‐reviewed articles. The average N 2 O emission derived from nitrification (N 2 O n ) was higher than that from denitrification (N 2 O d ) worldwide. The ratios of nitrification‐derived N 2 O to denitrification‐derived N 2 O, hereof N 2 O n :N 2 O d , exhibited large variations across terrestrial ecosystems. Although soil carbon and nitrogen content, pH, moisture, and clay content accounted for a part of the geographical variations in the N 2 O n :N 2 O d ratio, ammonia‐oxidizing microorganisms (AOM):denitrifier ratio was the pivotal driver for the N 2 O n :N 2 O d ratios, since the AOM:denitrfier ratio accounted for 53.7% of geographical variations in N 2 O n :N 2 O d ratios. Compared with natural ecosystems, soil pH exerted a more remarkable role to dictate the N 2 O n :N 2 O d ratio in croplands. This study emphasizes the vital role of functional soil microorganisms in geographical variations of N 2 O n :N 2 O d ratio and lays the foundation for the incorporation of soil AOM:denitrfier ratio into models to better predict N 2 O n :N 2 O d ratio. Identifying soil N 2 O derivation will provide a global potential benchmark for N 2 O mitigation by manipulating the nitrification or denitrification.
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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 | 0.001 |
| 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".