Carbon Credit Systems in Agriculture: A Review of Literature
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Notice bibliographique
Résumé
Carbon-credit systems allow agricultural producers to earn an extra revenue through selling their surplus of carbon credits to producers who emit higher amounts of greenhouse gases (GHGs). However, agricultural carbon-credit systems are still at early stage; hence, these benefits cannot be guaranteed due to their uncertain nature and the paucity of scientific evidence about agricultural carbon credits. The objective of this study is to provide a comprehensive literature review to highlight the gaps in existing knowledge related to agricultural carbon credits/offsets. Our particular interest is on Alberta because the province indicates the highest agricultural GHG emissions from 1990 to 2019 and, therefore, developing strategies to reduce the sector’s carbon intensity without compromising its economic contribution to the provincial economy poses a challenge. Literature is evident for promising GHG-mitigation strategies such as adoption of 4R practices (the right source at the right rate, right time and right place) as a package and improved efficiency in cattle farm management. Reduced tillage has been found to be less efficient. Researchers favour the concept of regenerative agriculture, which is more likely to return better outcomes compared to tillage practices. Moreover, ranchers are willing to upgrade their farms with efficient cattle breeds to take advantage of decreased feed costs. Conversely, farmers are reluctant to participate in the Alberta Emission Offset System unless rewarded with incentives. However, carbon-credit markets are still growing; consequently, farmers may have more opportunities in the future. If the Alberta credit price continues to grow with no expected increase in transaction costs, agricultural producers would be more attracted to participate in the Alberta Emission Offset System. Moreover, endorsing farmers for carbon-crediting mechanisms by emphasizing the co-benefits and associated economic incentives is recommended, instead of prioritizing its potential financial gains. Nevertheless, due to the scarcity of published studies, it is too early to project the economic and climate-mitigative potential of carbon-offset–credit markets for Canadian farmers. Literature suggests farmers wait until the carbon market becomes more stable before making a decision. Future research and scientific evidence will be crucial to filling these gaps and to guaranteeing future protocols.
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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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,001 | 0,006 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 découle