Emissions of nitrous oxide after application of dairy slurry on bare soil and perennial grass in a maritime climate
Bibliographic record
Abstract
Over half the slurry manure produced on dairy farms in the high-rainfall, coastal region of British Columbia (BC), Washington State and northern Oregon is applied from mid-February to early May. This study was conducted to compare the emissions of nitrous oxide (N2O) after manure application during this period on perennial forage grass or winter fallow land. The experimental site soil was moderately well- to well-drained medium-textured river deposit of the Monroe series. Treatments consisted of liquid dairy manure applied either at 270 (Early) or 450 (Late) Tsum (accumulation of average air temperatures above 0ºC from Jan. 01) on bare land or a perennial stand of tall fescue (Festuca arundinacea Schreb.) at a rate of 55.5 m3 ha-1 giving a total ammoniacal N (TAN) loading of 100 and 111 kg ha-1 in 2001 and 2002, respectively. An additional grass treatment consisted of split applications (Split) of manure at half the rate on each of the two application dates. Untreated (Control) bare and grass treatments were also included. Emissions were monitored for 105 d (28 Feb. to 12 Jun.) in 2001 and 121 d (26 Feb. to 26 Jun.) in 2002. Cumulative N2O emissions, during the measurement period (averaged over manure application times), from manured bare soil were 2.19 and 2.74 kg N ha-1 for 2001 and 2002, respectively and those from manured grass treatment were 0.21 and 0.58 kg N ha-1 for 2001 and 2002, respectively. Time of application altered seasonal emission pattern, but effect on total emission was inconsistent, probably due to conflicting effects of temperature and moisture. Significant differences in soil NO3-N levels between the grass and the bare soil treatments may explain the differences in N2O emission. Key words: Mineral N, herbage, water-filled pore space, winter fallow, Festuca arundinacea Schreb
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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".