Diet and landscape controls on greenhouse gas emissions from cattle excreta in a semi-arid environment
Notice bibliographique
Résumé
Sod-seeding low productivity, or depleted, pastures with legumes, and non-bloat legumes in particular, is considered a viable method of restoring productivity to the pasture. However, the impact of the change in plant composition of the pastures on GHG emissions from the urine and dung deposited by cattle grazing the pastures is as yet unknown. Excreta were collected from beef cattle grazing a low productivity, depleted meadow bromegrass-alfalfa mixed pasture (D-MA) and D-MA pastures rejuvenated by sod-seeding with a non-bloat legume, cicer milkvetch (R-CM) or sainfoin (R-SF). The excreta were subsequently applied back to the respective pastures at locations in upper and lower slope positions. In general, plant composition of the pastures had a small but significant impact on the C and N content of the cattle excreta; however, this yielded no significant differences among treatments in either cumulative CO 2 emissions or cumulative CH 4 uptake for either the urine or dung. Yet, whereas CH 4 uptake was unaffected by the application of either urine or dung, urine applications yielded CO 2 emissions that were greater than those from the control or dung-amended treatments. Nitrous oxide emissions were significantly impacted by the chemical composition of the urine, and here we report distinct N 2 O emission factors for urine and dung—with an average EF N2O of 0.034 ± 0.024 % for dung and 0.12 ± 0.10 % for the urine from cattle that grazed the depleted and rejuvenated pastures. Our data also suggest that, for urine at least, diet can significantly impact the EF N2O , with urine from cattle grazing the R-CM pasture yielding an EF N2O of 0.24 ± 0.10 % and urine from confined beef cattle fed a high crude protein, total mixed ration (TMR) diet yielding an EF N2O of 0.39 ± 0.13 %. These findings suggest that a disaggregation of emission factors based on excreta type and animal diet, while also considering temporal (seasonal) and spatial (landscape-scale) variability, can lead to improved accuracy of GHG emissions inventories. • Landscape position is an important regulator of excreta patch GHG emissions. • The composition of urine and dung deposited by beef cattle is related to the grazing diet. • Urine patch N 2 O emissions are diet-related and depend on more than just N concentration of the urine. • Nitrous oxide emission factors (EF N2O ) for beef cattle urine and dung were 0.19 % and 0.034 %, respectively. • The EF N2O for beef cattle urine and dung should be disaggregated for pastures in the semi-arid Canadian Prairies.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».