MétaCan
Menu
Back to cohort

Variable rate precision application of feedlot cattle manure mitigates soil greenhouse gas emissions

2025· article· en· W4406737293 on OpenAlex
R.D. Hangs, J.J. Schoenau, J. Diane Knight, R. Farrell

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGeoderma · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Soil, Plant Science
Canadian institutionsUniversity of Saskatchewan
FundersUniversity of Saskatchewan
KeywordsFeedlotGreenhouse gasManureEnvironmental scienceAgronomyAnimal scienceBiologyEcology

Abstract

fetched live from OpenAlex

• Constant and variable manure rates impact GHG emissions within commercial silage barley fields. • Landscape position and its catchment area size impacted N 2 O, CH 4 , and CO 2 emissions. • Phosphorus-limited crop growth increased yield- and value-scaled N 2 O, CH 4 , and CO 2 emissions. • Solid cattle manure did not influence ecosystem respiration or the CO 2 -equivalent emissions. • Variable rate manure application reduced N 2 O emissions and increased CH 4 sink strength. Solid cattle manure amendments provide a low-cost alternative nutrient source to inorganic fertilizers, while providing a carbon input to the soil. The augmented soil organic carbon levels, however, may be largely offset by manure-related greenhouse gas (GHG) emissions. Soil nitrous oxide (N 2 O), methane (CH 4 ), and carbon dioxide (CO 2 ) emissions were measured at the landscape-scale in a Canadian prairie agricultural field supporting silage barley ( Hordeum vulgare L.) production. Manure was applied to meet barley P requirements, while total N rate was supplemented using anhydrous ammonia. A non-manured control (NMC) also was included, to calculate N 2 O emission factors. The NMC zone consisted of an annual application of anhydrous ammonia at 80 kg N ha −1 . In addition to solid cattle manure at a constant (CRM; 45 Mg ha −1 ) or variable (VRM; 0–72 Mg ha −1 ) rate, the manured treatment zones also received 80 kg N ha −1 of anhydrous ammonia. The VRM treatment included set-backs from the watershed basin centers in ephemeral wetlands that did not receive solid cattle manure. Gas samples were collected using chamber-based methodology, with chambers installed at 130 locations across six watershed basins (n = 2 per zone) during 2019–2021. Cumulative N 2 O emissions were 76 % (CRM) and 62 % (VRM) higher following manure addition. The normalized N 2 O emissions for CRM were 24 % greater than VRM and NMC, with CRM having 31 % larger manure-induced N 2 O emissions than VRM. Though all soils were net CH 4 sinks, manure application reduced CH 4 consumption by 33 % (CRM) and 25 % (VRM) compared with the NMC. Manure addition did not impact cumulative CO 2 emissions. Although VRM application mitigated manure-related GHG emissions, enhanced GHG intensity following manure addition highlights the importance of ensuring balanced soil fertility, to support optimal crop growth and maximize yield-scaled GHG performance metrics in manured landscapes.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.226

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.210
Teacher spread0.202 · 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