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Record W1980370500 · doi:10.2134/jeq2013.09.0371

Cattle Methane Emission and Pasture Carbon Dioxide Balance of a Grazed Grassland

2014· article· en· W1980370500 on OpenAlexafffundabout
S. M. McGinn, K. A. Beauchemin, Trevor Coates, E. J. McGeough

Bibliographic record

VenueJournal of Environmental Quality · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsGrasslandEnvironmental scienceGreenhouse gasGrazingPastureSink (geography)StockingRangelandCarbon dioxideAgronomyLivestockMethaneAnimal scienceEcologyAgroforestryGeographyBiology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.767
Threshold uncertainty score0.110

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.242
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2014
Admission routes3
Has abstractyes

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