Effects of converting cropland to grassland on greenhouse gas emissions from peat and organic-rich soils in temperate and boreal climates: a systematic review
Notice bibliographique
Résumé
Abstract Background To align with climate goals, greenhouse gas (GHG) emissions from agriculture must be reduced significantly. Cultivated peatlands are an important source of such emissions. One proposed measure is to convert arable fields on peatlands to grassland, as the Intergovernmental Panel on Climate Change (IPCC) default emission factors (EF) for organic soils are lower from grasslands. Yet, these EFs are based on limited data with high variability and comparisons are difficult due to differences in climate, soil properties, and crop management. This systematic review synthesizes available evidence on the effects of converting cropland to grassland on GHG emissions from peat and organic-rich soils in temperate and boreal climates using data from comparable fields. Methods Literature was searched using five bibliographic databases, four archives or search engines for grey literature, and Google Scholar. Eligibility screening was performed in two steps on (1) title/abstract, with consistency among reviewers assessed by double-screening 896 articles, and (2) full text screened by two reviewers. Eligible articles were critically appraised independently by at least two reviewers. Disagreements were reconciled through discussions. Data and key metadata are presented in narrative synthesis tables, including risk of bias assessments. Meta-analyses comparing grasslands with croplands were performed using raw mean difference as the effect size. Review findings A total of 10,352 unique articles were retrieved through the literature searches, and 18 articles including 29 studies were considered relevant to answer the review question. After critical appraisal, it was concluded that two articles reported the same data, so a total of 28 studies, comprising 34 comparisons were included in the systematic review. Most of the included studies were conducted in the Nordic countries and Germany, one in Belarus and one in Canada. A meta-analysis was conducted on 24 studies pairing cropland and grassland sites. No significant differences in carbon dioxide (CO2) or methane (CH4) emissions were found. Emissions of nitrous oxide (N2O) from grasslands were found to be 7.55 kg ha−1 y−1 lower than from cropland, however the sensitivity analysis showed that the difference was not robust, making it uncertain whether conversion from cropland to grassland has a significant effect on N2O emissions from organic soils. The difference was also smaller when root crops were excluded from the comparator group. Further, net ecosystem exchange (NEE) of CO2 and net ecosystem carbon balance (NECB) were higher in grasslands compared to croplands in cases where the grasslands were fertilized. Conclusions This systematic review underlines the ambiguity of GHG emissions from peatlands and their relationship to land use. Our understanding of the factors influencing emissions from these soils remains incomplete, and the specific impact of land use on emissions is still unclear. CO2 emissions represent a major part of the climate impact of cultivated peat soils, so the data analyzed allow to draw the conclusion that a conversion from arable to grassland would not lead to large benefits in terms of GHG emissions, especially if root crops are not part of the arable crop rotation, or the grassland is fertilized. Graphical abstract
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 | 0,008 | 0,036 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,008 | 0,009 |
| Bibliométrie | 0,008 | 0,009 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».