Influence of seasonal climate and water table management on corn yield and nitrous oxide emissions
Bibliographic record
Abstract
Compared to regular tile drainage (FD), controlled drainage systems with sub-irrigation (CDS) can increase crop yield but could potentially heighten the production and subsequent emission of nitrous oxide (N2O). Accounting for growing season rainfall categorized under wet, dry and normal, the long-term effects of CDS on crop yield and nitrous oxide (N2O) emissions were investigated at a commercial corn farm in southwestern Quebec. Based on yield data collected over 12 years at the study site, CDS improved grain yield compared to regular tile drainage (FD), depending on the quantity and temporal distribution of rainfall during the growing season. On average, CDS positively affected grain yield by 17.7% and 3.4% in dry and normal years, but reduced yield by 25% in a wet year. The lower yield under CDS was particularly observed when excessive monthly rainfall (230 mm) occurred during the crop’s vegetative period. In three of six years, N2O fluxes under CDS treatments were greater by 49% than those under FD but 45% lower in the remaining years, implying that – notwithstanding the quantity of growing season rainfall – CDS does not necessarily always produce greater fluxes than FD. N2O fluxes coincided more with fertilizer application, particularly when associated with a rainfall event. Given that CDS tends to increase crop yield and does not heighten N2O emissions, it remains a beneficial management practice to be adopted in subsurface drained croplands, where appropriate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".