Cattle Methane Emission and Pasture Carbon Dioxide Balance of a Grazed Grassland
Bibliographic record
Abstract
Grasslands constitute a major land use globally and are a potential sink of atmospheric carbon dioxide (CO). They are also an important habitat for wildlife and a source of feed that supports ruminant livestock production. However, the presence of ruminants grazing these grasslands is also a source of methane (CH) that contributes to buildup of greenhouse gases in the atmosphere. Our study measured enteric CH from 40 confined heifers in 1-ha paddocks using a dispersion model and CO exchange from an adjacent grassland site using a micrometeorological technique. The study was conducted at a mixed prairie grassland located in southern Alberta, Canada. The mean (standard error) CH emission was 189 (± 6) g animal d over four campaigns (over a 3-yr period). The daily averaged CO exchange from the grassland peaked at +2.2 g m h (sink) in early July and declined to negative values (source) in mid-August. Annually, the grazed grassland was either a net sink for carbon (C) at +40 kg C ha or a small source at -7 kg C ha depending on a cattle stocking density of 0.1 or 0.2 animals ha, respectively. However, in basing the exchange on CO equivalence (CO), both stocking densities resulted in the grazed grassland being a source of greenhouse gas of -9 or -338 kg CO ha y. This study illustrates the need to consider the cattle CH emissions and the stocking density when evaluating the environmental sustainability of grazed grasslands.
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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) | 0.001 | 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".