Atmosphere composition and N<sub>2</sub>O emissions in soils of contrasting textures fertilized with anhydrous ammonia
Bibliographic record
Abstract
Nitrous oxide production and emission in agricultural soils are often influenced by soil physical properties and mineral N content. An experiment was initiated on a commercial farm located in the St. Lawrence Lowlands to measure the effects of recommended (150 kg N ha-1) and excessive (250 kg N ha-1) rates of anhydrous ammonia on atmospheric composition (O2, CO2, CH4 and N2O) and N2O emissions in soils of contrasting textures (sandy loam, clay loam and clay) cropped to corn. N2O emissions and soil temperature, water content and atmospheric composition were measured from post-harvest tillage to the first snowfall during the first year (2000), and from spring thaw to mid-July during the following 2 yr. Episodes of high N2O concentrations and surface emissions coincided with periods of high soil water content shortly following rainfall events when soil O2 concentrations were lowest. The convergence of indicators of restricted soil aeration at the time of highest N2O production suggested that denitrification was a major contributor to N2O emissions even in soils receiving an NH4-based fertilizer. Soil texture had a significant influence on soil N2O concentration and emission rates on several sampling dates. However, the effect was relatively small and it was not consistent, likely because of complex interactions between soil physical properties and N2O production, consumption and diffusion processes. Nitrous oxide emissions during the study were not limited by soil N availability as indicated by similar fluxes at recommended and excessive rates of anhydrous ammonia. Finally, greater N2O emissions in 2001 than in 2002 stress the importance of multiyear studies to evaluate the effect of annual weather conditions on soil N2O dynamics. Key words: Greenhouse gasses, denitrification
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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) | 0.000 | 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".