Flux of CO2, CH4 and N2O from temperate woodland soil under elevated CO2
Notice bibliographique
Résumé
Atmospheric fluxes of greenhouse gases (GHG’s) in the form of CO2, CH4 and N2O from temperate forest soils are an important aspect of the net global warming potential and climate change mitigation function of forests. However, it remains unclear how the magnitude of these atmospheric fluxes of GHG’s will respond to rising atmospheric CO2 concentrations in mature temperate forests. An increase in carbon capture by temperate forests under elevated atmospheric CO2 concentration (eCO2) and its subsequent storage in biomass and soils can have direct impact on the activities of soil microbes. In addition to indirect effects through shifting soil moisture regimes, potentially altering GHG production and consumption processes and hence net emissions from temperate forests. The Birmingham Institute of Forest research established a Free Air Carbon Enrichment Facility (BIFoR-FACE) whereby a mature temperate forest in the UK is exposed to +150 ppm CO2 above the ambient (aCO2), mimicking future CO2 conditions. Understanding GHG exchange from soils under elevated atmospheric CO2 levels is critical for addressing this component of the systems response to eCO2. Fumigation started in 2017 and continues to date, where the ecological and biogeochemical responses of the forest is being studied. In this abstract, the focus is placed on quantifying ~5-years (2019 – 2024) of GHG flux response to eCO2 to elucidate shifts in fluxes as influenced by eCO2 and local microclimatic conditions.The flux of CO2 from the soil has been continuously measured within fumigated treatment (eCO2) and ambient control (aCO2) arrays since 2017 via LI-COR 8100A long-term measurement systems. With capabilities to additionally measure CH4 and N2O being added in 2020 through a coupled Picarro-G2508 analyser. Initial trends from 2017 - 2020 indicated that eCO2 arrays had a higher efflux of CO2 relative to paired aCO2 arrays by +20%. However, from 2020 – 2022 a significant decline of -46.6% in the efflux of CO2 was detected, in addition to a -76.6% reduction in N2O effluxes and a -44.3% decline in the CH4 uptake by the soil component. This period corresponds to a significant decline in soil moisture across the soil profile from the surface (0.05m) to a depth of 0.4m, equivalent to a -36% decline in volumetric water content under eCO2 relative to aCO2. Which when coupled with the prevalence of drought periods during the growing seasons of 2021 and 2022 suggest an enhanced drying of soil under eCO2, which is in turn exacerbated by drought events. During 2023 and the wettest July on record for the UK, the moisture deficit between eCO2 and aCO2 shrunk, reducing the variance in the efflux of CO2 to just ~4.5%. Therefore, it is possible that a functional change in the heterotrophic and autotrophic mediated flux dynamic could be occurring, driven by significant soil drying under eCO2, an affect which is exacerbated during drought events. Inter and intra-seasonal patterns of GHG fluxes will be examined in further detail, whilst also partitioning between autotrophic and heterotrophic contributions.
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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) | 0,002 | 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 ».