Legume green manure as partial fallow replacement in semiarid Saskatchewan: Effect on carbon fluxes
Bibliographic record
Abstract
Increasing atmospheric CO2 concentrations, largely due to burning of fossil fuels, may accentuate the risk of global warming. Scientists are optimistic that with appropriate management soils can function as sinks for C and contribute to CO2 abatement strategies. The objective of this study was to determine if soil C can be increased using an annual legume green manure (GM) as partial fallow replacement in a fallow-wheat (Triticum aestivum L.)-wheat (F-W-W) rotation in the Brown soil zone of Saskatchewan. In 1995 and 1996 we measured soil C fluxes in all phases of F-W-W and GM-W-W rotations, which were two of the treatments in an experiment initiated in 1987 on a medium-textured Orthic Brown Chernozem. The GM, Indianhead black lentil (Lens culinaris Medikus) was estimated to add 1800 and 1400 kg C ha−1 in 1995 and 1996, respectively. Annual inputs of C in residues of the wheat crops were two to three times those of GM. Comparison of CO2 emissions from GM with those from the fallow phase of the F-W-W system suggested that GM largely decomposed in the interval between incorporation (mid-July) and freeze-up in fall. Fluxes of CO2 from the wheat phases of GM-W-W closely matched those from the corresponding phases of F-W-W, confirming that there was little carryover of undecomposed GM to the following growing season. Our results suggest that, in a 3-yr rotation, partial fallow replacement with legume GM may have only a minor impact on C sequestration because the increase in C inputs is relatively small (~ 25% in this study) and GM decomposes rapidly in the soil due to its narrow C:N ratio (12–13). Green manuring may, however, play a more significant role in enhancing soil C levels in a F-W system, where relatively large increases in C inputs could be achieved using currently-available legume species. Key words: Carbon sequestration, carbon dioxide emissions, crop residue decomposition, wheat, summerfallow, lentil
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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".