Influence of fertilizer nitrogen source and management practice on N<sub>2</sub>O emissions from two Black Chernozemic soils
Bibliographic record
Abstract
Fertilizer nitrogen use is estimated to be a significant source of nitrous oxide (N2O) emissions in western Canada. These estimates are based primarily on modeled data, as there are relatively few studies that provide direct measures of the magnitude of N2O emissions and the influence of N source on N2O emissions. This study examined the influence of nitrogen source (urea, coated urea, urea with urease inhibitor, and anhydrous ammonia), time of application (spring, fall) and method of application (broadcast, banded) on nitrous oxide emissions on two Black Chernozemic soils located near Winnipeg and Brandon Manitoba. The results of this 3-yr study demonstrated consistently that the rate of fertilizer-induced N2O emissions under Manitoba conditions was lower than the emissions estimated using Intergovernmental Panel on Climate Change (IPCC) coefficients. The Winnipeg site tended to have higher overall N2O emissions (1.7 kg N ha-1) and fertilizer-induced emissions (~0.8% of applied N) than did the Brandon site (0.5 kg N ha-1), representing ~0.2% of applied N. N2O emissions in the first year of the study were much higher than in subsequent years. Both the site and year effects likely reflected differences in annual precipitation. The N2O emissions associated with the use of anhydrous ammonia as a fertilizer source were no greater than emissions with urea. Fall application of nitrogen fertilizer tended to result in marginally greater N2O emissions than did spring application, but these differences were neither large nor consistent. Key words: Nitrogen fertilizer, nitrous oxide emissions, nitrate intensity, anhydrous ammonia, urea
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".