Net CO2 and N2O exchange during perennial forage establishment in an annual crop rotation in the Red River Valley, Manitoba
Bibliographic record
Abstract
Maas, S. E., Glenn, A. J., Tenuta, M. and Amiro, B. D. 2013. Net CO2and N2O exchange during perennial forage establishment in an annual crop rotation in the Red River Valley, Manitoba. Can. J. Soil Sci. 93: 639-652. The long-term use of perennial forages in crop rotations can increase soil carbon (C) and lower nitrous oxide (N2O) emissions compared with continuous annual cropping. However, less is known of the short-term (within 2 yr) benefit of inclusion of perennial forages in an annual crop rotation on net carbon dioxide (CO2) and N2O fluxes. Perennial forage, primarily composed of alfalfa (Medicago sativa L.) and a minor component of timothy grass (Phleum pretense L.) was sown in 2008 on two 4-ha plots previously in annual cropping in the Red River Valley, Manitoba. Spring wheat (Triticum aestivum L.) and industrial rapeseed (Brassica napus L.) were grown on two adjacent plots in 2008 and 2009, respectively. Carbon dioxide and N2O fluxes were measured continuously using the flux-gradient micrometeorological method from 2008 May 01 to 2010 Apr. 30. During the 2-yr study, the newly established perennial forage was nearly twice the sink for atmospheric CO2 (mean and standard deviation of 4480±1840 kg C ha-1) as the annual crops (2470±700 kg C ha-1). The annual crop emitted more than four times the N2O (7.8±0.7 kg N ha-1) as the perennial forage stand (1.8±0.7 kg N ha-1). When accounting for harvest C removals (grain, straw, hay) and considering the greenhouse gas (GHG) emissions in CO2-equivalents (eq.), the newly established perennial forage was a net sink of 8470±5640 kg CO2-eq. ha-1 and the annual crop was a source of 3760±2450 kg CO2-eq. ha-1 during the study. The results indicate an immediate reduction in soil GHG emissions with the inclusion of perennial forage in the rotation, primarily from reduced N2O emissions, the lack of crop removal in the forage establishment year and the longer growing season period of net CO2 uptake of the perennial crop.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".