A Better Understanding of CO₂ Fluxes within Canadian Boreal Forests through Satellite Based XCO₂ Data
Notice bibliographique
Résumé
This research seeks a better understanding of carbon fluxes in the Canadian boreal forest in recent years due to the profound impacts of climate change and recent increases in wildfire occurrences. These forests play a significant role in the global carbon cycle, acting as major carbon sinks by absorbing carbon dioxide from the atmosphere However, the balance between carbon absorption and release is delicate and can be easily disrupted by climate change, leading to increased temperatures, changes in precipitation patterns, and more frequent and severe wildfires. These environmental changes have direct consequences on the carbon balance of the boreal forests. Wildfires, not only release large amounts of stored carbon back into the atmosphere but also alter the forest landscape, affecting its future ability to store carbon. Canadian boreal forests are significant carbon reservoirs, with approximately 28 pg of carbon across biomass, dead organic matter, and soil. This includes both aboveground biomass and belowground components like roots and soil organic matter. The dynamics of these pools are subject to growth rates, mortality, and disturbances such as fires and insect infestations. This research focuses on quantifying the levels and fluxes of carbon dioxide within Canada's boreal forests. With integrating top down satellite observations with bottom up field measurements, the research seeks to provide a comprehensive quantification and modeling of CO₂ fluxes, enhancing our understanding of carbon sequestration mechanisms. Key objectives include identifying the primary drivers of CO₂ exchange variability, assessing the impact of wildfires on forest carbon balances, and assess post fire forest recovery and its implications for carbon sequestration. Methodologically, the research leverages an array of satellite data, including bias corrected XCO₂ values from OCO-2/3 Lite File, Solar Induced Fluorescence data, and vegetation indices such as NDVI from MODIS and Landsat satellites. These space based observations will be coupled with in situ measurements from networks like FluxNet for validation. An inverse modeling approach using the Global Earth system Monitoring model (GEOS Chem) will assist in interpreting the data to identify the CO₂ fluxes and their association with vegetation dynamics and climate conditions. Furthermore, the study will utilize satellite imagery to analyze land cover changes, fire disturbances, and post fire regeneration. The research aims to combine top down satellite observations with bottom up ground measurements to address the frequency, extent, and intensity of wildfires and their subsequent effect on the forest carbon balance. Furthermore, the study will utilize satellite imagery to analyze land cover changes, fire disturbances, and post fire regeneration. The research aims to combine top down satellite observations with bottom up ground measurements to address the frequency, extent, and intensity of wildfires and their subsequent effect on the forest carbon balance. This is the WDCAG Conference 2024 Award Winner for Best PhD Poster.
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 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) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».