Crop residue incorporation alters soil nitrous oxide emissions during freeze–thaw cycles
Bibliographic record
Abstract
Pelster, D. E., Chantigny, M. H., Rochette, P., Angers, D. A., Laganière, J., Zebarth, B. and Goyer, C. 2013. Crop residue incorporation alters soil nitrous oxide emissions during freeze–thaw cycles. Can. J. Soil Sci. 93: 415–425. Freeze–thaw (FT) cycles stimulate soil nitrogen (N) and carbon (C) mineralization, which may induce nitrous oxide (N2O) emissions. We examined how soybean (Glycine max L.) and corn (Zea mays L.) residue incorporation affect N2O emissions from high C content (35 g kg−1) silty clay and low C content (19 g kg−1) sandy loam soils over eight 10-d FT cycles, as a function of three temperature treatments [constant at +1°C (unfrozen control), +1 to −3°C (moderate FT), or +1 to −7°C (extreme FT)]. In unamended soils, N2O emissions were stimulated by FT, and were the highest with extreme FT. This was attributed to the increased NO3 availability measured under FT. Application of mature crop residues (C:N ratios of 75 for soybean and 130 for corn) caused rapid N immobilization, attenuating FT-induced N2O emissions in the silty clay. In the sandy loam, residue addition also induced immobilization of soil mineral N. However, N2O emissions under moderate FT were higher with than without crop residues, likely because N2O production in this low-C sandy loam was stimulated by C addition in the early phase of incubation. We conclude that FT-induced N2O emissions could be reduced through incorporation of mature crop residues and the subsequent immobilization of mineral N, especially in C-rich soils.
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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".