Using a systems approach to examine net greenhouse gas emissions from beef production in western Canada
Notice bibliographique
Résumé
A model, based on Intergovernmental Panel on Climate Change (IPCC) equations, was used to estimate annual net farm greenhouse gas (GHG) emissions from various management strategies.The model included methane (CHÐ emissions from livestock and manure, direct and indirect nitrous oxide (NzO) emissions from soil and manure, carbon dioxide (COz) emissions from energy use and soil carbon change.The model was used to examine the effects of 11 management practices (one baseline management scenario and ten variations of that baseline) on net whole-farm emissions from a beef production system, as estimated for hypothetical farms at four disparate locations in western Canada.Treatments from a systems-based research trial were also modeled, and treatment rankings obtained were examined along with those acquired from modeled predictions.The measured emissions were acquired from a field study which examined the mitigation potential of three fertility treatments applied to grazed forage.The treatments were no liquid hog manure (control); 242kg total N/ha in a spring application of liquid hog manure (fult); l2l kg total N/ha in each of a spring and fall application of liquid hog manure (split).Greenhouse gas emissions for a hypothetical treatment, where synthetic fertilizer was applied at242 kg total N/ha in the spring, were estimated using the model and examined along with the other fertility treatments to determine mitigation potential.The discrepancies observed between the predicted estimates and measured values were used to identify those facets of whole-farm emissions most in need of further study and those components with the largest effect on net emissions.Emissions were reported as net farm emissions (Mg CO2equivalents (CO2e)), net farm emissions per hectare (Mg CO2elha) and as net emissions per unit of protein exported off-farm (Mg lll CO2elNIg protein).The latter strategy was utilized to ensure that farm productivity was accounted for.Of the ten management practices that were compared to the baseline management scenario, pasturing cattle on alfalfa-grass showed the largest decrease (0.39 to 0.70 Mg CO2elMg protein) in emissions for all locations, while feeding lower quality forage over winter showed the greatest increase in emissions per unit protein on the southern Alberla (S.AB) (1.la Mg CO2elMgprotein) and northem Alberta C{.AB) (1.09 Mg CO2elMg protein) farms.Eliminating the fertlhzation of forages resulted in the largest increase (2.36}l4'g COze/Mg protein) in emissions per unit protein on the Saskatchewan (SK) farm, while reducing the fertilizer rate by half for all crops showed the largest increase (2.26};4,gCO2elMgprotein) on the Manitoba (MB) farm.The predictions and measured values for the fertility treatments showed the following ranking among treatments in net emissions per ha (Mg CO2e/ha): full > split > synthetic fertllizer > control (measured emissions did not include the synthetic fertilizer treatment).The predicted estimates and measured values showed the following rankings when expressed per unit protein: split > full > synthetic fertilizer > control (measured emissions did not show as much difference between split and full).The analyses indicate that a systems- based approach must be used to quantify net farm GHG emissions, and expressing emissions on the basis of CO2eper unit of protein exported off-farm provides a more accurate assessment of the impact of management changes.General recommendations on 'best' management practices cannot be made, as factors influencing GHG emissions differ with location.Uncertainty exists in both predicted and measured estimates of GHG emissions, and future research work should use both models and measurements to focus on the system components with the largest uncertainty and highest relative importance.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 source (Gemma direct ou Codex distillé), 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 ».