Distribution spatiale des communautés de vers de terre et leur effet sur les gaz à effet de serre en champs agricoles et en bandes riveraine forestières
Notice bibliographique
Résumé
This thesis reports the findings from a research project that aimed to determine the effect of earthworms on greenhouse gas (GHG) emissions in forested riparian buffer strips (FRBS). This project had two research questions. Firstly, we wanted to determine how earthworms are distributed in agricultural ecosystems and whether they had a preference for FRBS over adjacent agricultural fields. Secondly, we wanted to determine the effect of earthworms on the emission of the three most prominent GHG (CO2, N2O and CH4) and how the effect of earthworms is affected by soil characteristics, namely, soil origin and soil texture. We expected earthworms to have a preference for FRBS and for them to have a positive effect on GHG emissions. \n \nFor the first research question, we conducted a field survey on agricultural fields with adjacent FRBS in Southern Quebec and Ontario as well as in the Czech Republic. At each site, we quantified earthworm numbers from each functional group (anecic, endogeic and epigeic) and characterized the site by noting the percentage coverage of the different types of vegetation and analysing soil’s physicochemical properties. We found that for Eastern Canada, earthworm numbers, organic matter and soil moisture were all higher in FRBS than in adjacent agricultural fields. However, in Czech Republic, earthworm numbers were higher in agricultural fields than FRBS and there was no significant difference in moisture between agricultural fields and FRBS. This indicated that moisture is an important variable in predicting the distribution of earthworms. Furthermore, we found that earthworm numbers are positively associated with organic matter, pH, clay content and the percent coverage of deciduous trees and negatively associated with sand content and the percent coverage of coniferous trees. Following these results, the next step was to determine what effect earthworms have on GHG emissions. \n \nIn order to determine the effect of earthworms on GHG emissions we conducted controlled microcosm experiments. These experiments were conducted using a replicated factorial design comprising of 3 soil origins (deciduous FRBS, coniferous FRBS, agricultural field) x 2 soil textures (field conditions, high clay) x 3 earthworm life habits (anecic, endogeic, no earthworm). Soils originating from FRBS emitted more CO2 than soils from agricultural fields with soils from deciduous stands having higher emissions than soils from coniferous stands. Soils with a higher clay content emitted less CO2 than soils with a lower clay content. Soils with earthworms emitted more CO2 than soils without earthworms, however, this effect diminished with time and was no longer significant after ten weeks. Additionally, soils with earthworms emitted more N2O than soils without earthworms. For CH4, the transformation rates were higher for soils from FRBS than soils from agricultural fields under both anaerobic and aerobic conditions. \n \nWith earthworms having an overall positive effect on GHG emissions, FRBS should be designed such that they prevent the establishment of earthworms. Therefore, coniferous trees would be preferable over deciduous trees. Firstly, earthworm numbers were shown to be negatively associated with coniferous tree coverage, and, in the event that earthworms do become established, GHG emissions were shown to be lower from coniferous soils than deciduous stands.
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Comment cette classification a été obtenuedéplier
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 | 0,001 |
| Communication savante | 0,000 | 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) | 0,000 | 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 ».