Climate change mitigation through irrigation strategies during rice growing season is off-set in fallow season
Notice bibliographique
Résumé
Non-continuous flooding irrigation practices, such as alternate wetting and drying (AWD) and mid-season drainage (MSD), have been implemented in rice agroecosystems to reduce water use and mitigate climate change. Draining fields reduces methane (CH 4 ) emissions, as soil aeration decreases the abundance and activity of soil methanogens. Mitigation effects during the growing season have been widely studied. However, there is a knowledge gap regarding potential effects these growing season practices might have on subsequent fallow season emissions. This is relevant when assessing overall annual CH 4 emissions, particularly in systems in which fallow seasons account for a significant part of these. A field experiment was implemented in the Ebro Delta region (Catalonia, Spain) with the objective of identifying potential effects of growing season AWD and MSD on CH 4 emitted during the following flooded fallow season, in comparison to continuously flooded fields. Both emissions and the structure of soil microbial communities were analyzed for rice field plots under the assessed irrigation strategies during the growing season and later for a continuously flooded mesocosm across the fallow season. Both practices achieved an average 86% decrease in CH 4 fluxes when compared to continuous flooding during the growing season. AWD resulted in the highest fallow season emissions, leading to increases in overall annual cumulative CH 4 emissions ( + 8%), global warming potential ( + 30%) and yield-scaled global warming potential ( + 70%) compared to continuous flooding. Growing season AWD decreased the relative abundance of both methanogens and methanotrophs in the fallow season. Reduced methanotroph communities might lead to lower CH 4 consumption, resulting in higher fallow season emissions and offsetting the mitigation effect achieved during the growing season. Under the studied conditions, MSD represented a more effective mitigation strategy. These results highlight the importance of considering both rice growing and fallow season when assessing climate change mitigation strategies. • AWD climate change mitigation effect is off-set in flooded fallow seasons. • MSD can be a more effective mitigation strategy, depending on system conditions. • AWD can decrease yields, increasing its annual yield scaled global warming potential. • Irrigation strategies result in legacy effect on soil microbial communities. • Assessments of rice management must consider both growing and fallow seasons.
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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 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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 | 0,000 |
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 ».