Diverse rotations impact microbial processes, seasonality and overall nitrous oxide emissions from soils
Bibliographic record
Abstract
Abstract Many studies haveexamined soil‐borne nitrous oxide (N 2 O) emissions from crops, but little effort has gone into determining the N 2 O emissions from each phase of a crop rotation. A 4‐yr study on a long‐term field experiment compared growing season N 2 O emissions from continuous corn (CC; Zea mays L.) and a 4‐yr crop rotation involving corn (RC), oat (Avena Sativa L .) underseeded to alfalfa ( Medicago sativa L.) (RO), and 2 yr of alfalfa (RA1, RA2). Molecular microbial biomass (DNA yield), as well as N‐cycling functioning genes (mineralization, nitrification, and denitrification), were also evaluated. Although 4‐yr cumulative N 2 O emissions from RC (9.25 kg N ha –1 ) were significantly greater than from CC (7.94 kg N ha –1 ), cumulative emissions from the entire rotation were 54% lower (3.69 kg N ha –1 ) than CC because of low emissions from RO (3.1 kg N ha –1 ), RA1, and RA2 (1.11–1.27 kg N ha –1 ). Years that had substantial early‐season precipitation combined with high soil inorganic N from alfalfa plow‐down contributed to elevated N 2 O emissions from RC. Improved soil conditions and fertility under rotation increased RC grain yields by 35% (9.45 Mg ha –1 ) compared with CC (7.01 Mg ha –1 ). Microbial biomass was 73% greater in RC compared with CC. Nitrogen mineralization genes were 19% greater in RC but they were not correlated to N 2 O emissions, whereas bacterial nitrifiers were positively correlated. Denitrification was likely responsible for N 2 O emissions under CC, while nitrifier‐denitrification appeared to be the primary pathway under RC. The N 2 O emissions and microbial processes from all phases of a rotation should be considered for environmental modeling and policy decisions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".