Tillage Effects on Carbon Fluxes in Continuous Wheat and Fallow–Wheat Rotations
Bibliographic record
Abstract
The traditional cropping system in semiarid regions of the Canadian prairies involves frequent summer fallowing with several tillage operations to control weeds during the fallow period. Recently, there has been a trend toward reduced tillage and more intensive cropping, but the impact of this shift in management on sequestration of atmospheric CO 2 remains uncertain. In 1995 and 1996, we measured fluxes of CO 2 in a tillage experiment that had been initiated in 1982 on a silt loam (Typic Haploboroll) in southwestern Saskatchewan. The experiment comprised two spring wheat ( Triticum aestivum L.) rotations (continuous wheat [Cont. W] and fallow–wheat [F–W]), each with conventional tillage (CT) and no‐till (NT) treatments. In Cont. W, CO 2 fluxes tended to be lower under NT than under CT (mean annual flux was ≈20 to 25% less for NT than CT). In F–W, tillage effects on mean annual CO 2 flux were significant ( P < 0.05) in the wheat phase only (NT ≈ 10% less than CT). Tillage had negligible effect on C inputs in crop residues. Lower CO 2 fluxes under NT than under CT were attributed to slower decomposition of crop residues placed on the surface of NT soil than when they were incorporated. With good growing conditions (and thus large inputs of residues) between 1989 and 1996, there was an accumulation of partially decomposed residues on the surface of NT soil. Carbon in surface residues represented about one‐half of the C gained by NT soil. In Cont. W, surface residue C (in 1996) amounted to 3.6 t ha −1 under NT vs 1.4 t ha −1 under CT. Residue C amounts were smaller in the F–W system: 1.7 t ha −1 (NT) and 0.7 t ha −1 (CT). Based on our results, producers on medium‐textured soils in the semiarid Canadian prairies who switch from the traditional wheat production system (conventionally tilled fallow–wheat) to continuous no‐till cropping could, potentially, sequester 5 to 6 t C ha −1 in soil organic matter and surface residues in 13 to 14 yr.
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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 | 0.001 |
| 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".