Differences in field‐scale N<sub>2</sub>O flux linked to crop residue removal under two tillage systems in cold climates
Bibliographic record
Abstract
Abstract Residue removal for biofuel production may have unintended consequences for N2O emissions from soils, and it is not clear how N2O emissions are influenced by crop residue removal from different tillage systems. Thus, we measured field‐scale N2O flux over 5 years (2005–2007, 2010–2011) from an annual crop rotation to evaluate how N2O emissions are influenced by no‐till (NT) compared to conventional tillage (CV), and how crop residue removal (R−) rather than crop residue return to soil (R+) affects emissions from these two tillage systems. Data from all 5 years indicated no differences in N2O flux between tillage practices at the onset of the growing season, but CT had 1.4–6.3 times higher N2O flux than NT overwinter. Nitrous oxide emissions were higher due to R− compared to R+, but the effect was more marked under CT than NT and overwinter than during spring. Our results thus challenge the assumption based on IPCC methodology that crop residue removal will result in reduced N2O emissions. The potential for higher N2O emission with residue removal implies that the benefit of utilizing biomass as biofuels to mitigate greenhouse gas emission may be overestimated. Interestingly, prior to an overwinter thaw event, dissolved organic C (DOC) was negatively correlated to peak N2O flux (r = −0.93). This suggests that lower N2O emissions with R+ vs. R− may reflect more complete stepwise denitrification to N2 during winter and possibly relate to the heterotrophic microbial capacity for processing crop residue into more soluble C compounds and a shift in the preferential C source utilized by the microbial community overwinter.
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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) | 0.000 | 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) | 0.001 | 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".