Does pasture rejuvenation by sod-seeding with non-bloat legumes affect greenhouse gas emissions?
Notice bibliographique
Résumé
Pasture rejuvenation through sod-seeding (i.e., the use a zero-till drill to place the seed directly into the soil) with non-bloat legumes, such as cicer milkvetch (Astragalus Cicer L.) or sainfoin (Onobrychis vicifolia Scop.), has emerged as a favored strategy for ranchers in the western Canadian prairies due to it being both time- and cost-effective. Meanwhile, this management also makes alterations to soil carbon and nitrogen cycling as well as to the diet of cattle grazing the pastures. Yet, our understanding on how these changes influence the greenhouse gas (GHG) budgets of the pastures remains limited. The goal of this research was to assess the impact of rejuvenating pastures by sod-seeding cicer milkvetch or sainfoin into a depleted meadow bromegrass-alfalfa mixed pasture on GHG emissions and their contribution to the total GHG footprint of the pasture system. To achieve this goal, field studies were conducted in east-central Saskatchewan, Canada to: (1) evaluate and compare GHG emissions between the rejuvenated pastures and the depleted pasture, and (2) quantify GHG emissions from dung and urine patches deposited by cattle grazing these pastures. Finally, the legume option resulting in the lowest GHG footprint was identified by integrating the GHG data with enteric methane (CH4) production by the cattle. \nThe results indicate pasture rejuvenation through sod-seeding had only a minimal impact on soil-derived GHG emissions relative to the control (depleted) pasture, likely due to the limited soil disturbance associated with this method. At the paddock-scale, annual GHG emissions averaged 10.11 Mg CO2-C ha-1, 2.54 kg CH4-C ha-1 (uptake), and 0.18 kg N2O-N ha-1, with no significant differences among pasture types. However, changes in grazing diet resulting from the pasture rejuvenation were found to affect urine patch N2O emissions, with the highest cumulative N2O emissions associated with beef cattle grazing on the depleted pastures sod-seeded with cicer milkvetch. Surprisingly, this did not reflect differences in the available N content of the urines, suggesting a potential link to the presence of secondary metabolites such as hippuric acid. Notably, the dung and urine patches yielded distinctly different N2O emission factors, averaging 0.03% and 0.26%, respectively. Within the pastures, landscape position emerged as a dominant regulatory factor for CO2 and CH4 emissions—with the lower slope positions exhibiting the highest CO2 emissions and the lowest CH4 uptake, likely due to denser vegetative cover in these areas due to an accumulation of soil moisture. Such landscape-scale patterns remained unaffected by dung/urine deposition. Partial C footprints for the pastures (based on non-CO2 emissions from the soil, cattle excreta, and enteric CH4) were developed and it was determined that there were no significant differences between the rejuvenated and depleted pastures. Averaged across pastures, the C footprint was 970 kg CO2eq ha-1 yr-1, with enteric CH4 being the largest contributor to the footprint. Insights gained from this study will be valuable for ranchers and policymakers in developing sustainable pasture management strategies.
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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 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».