Carbon Dioxide and Nitrous Oxide Emissions following Fall and Spring Applications of Pig Slurry to an Agricultural Soil
Bibliographic record
Abstract
In Québec, most pig slurry is applied to agricultural soils in the spring and fall. A study was initiated to compare the impact of the contrasting spring and fall weather conditions on CO 2 and N 2 O emissions, and on the transformation of pig slurry C and N in a loamy soil cropped to maize ( Zea mays L.). Treatments were approximately 200 kg total N ha −1 either as a spring (SPRING) or fall (FALL) application of pig slurry, and 150 kg N ha −1 as NH 4 NO 3 (control). Fluxes of CO 2 and N 2 O, and soil O 2 , CO 2 , N 2 O, NH 4 + , NO 3 − , extractable C and microbial biomass C (MBC) contents were measured 50 times over a 1‐yr period. Fluxes of N 2 O were generally low during the experiment but were greatly increased in recently manured soils when soil O 2 concentration fell below 0.20 mol mol −1 Soil was warm and well‐aerated following spring slurry application. Under these conditions, slurry NH 4 –N was rapidly nitrified and high N 2 O emissions attributed to denitrification occurred when soil was rewetted by abundant rainfall. For the fall applied slurry, wet and cool conditions limited net nitrification and resulted in little accumulation of NO 3 –N, thus limiting potential for subsequent denitrification and N 2 O emissions. Cumulated N 2 O emissions during the experiment represented 1.74, 2.73, and 1.14% of added N in the FALL, SPRING, and NH 4 NO 3 plots, respectively. Fluxes of CO 2 and cumulated CO 2 –C losses were also greater for SPRING than for FALL application. Our results clearly show that the impacts of the timing of animal manure application on N 2 O emissions cannot be generalized, but will vary between years in response to interactions between crop, climatic, and soil factors.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".