Effect of wildfire burn severity on dissolved organic carbon concentration and dissolved organic matter composition export from Boreal Shield peatlands 3- to 5-years post-wildfire
Notice bibliographique
Résumé
Northern peatlands function as important global carbon sinks. However, due to climate change, there are concerns about whether these peatlands will maintain this net carbon sink function. Climate change is already increasing boreal biome drying, area-burned, wildfire intensity, and burn severity as observed in the unprecedented 2023 wildfire season in Canada (>15 Mha burned). Of particular concern in boreal wildfires are deep burning smouldering peat fires that can switch peatlands to net emitters of atmospheric carbon. However, less studied are the effects of peat fires on water-borne carbon and the potentially deleterious impacts it has on downstream water quality as the burned area recovers 3- to 5-years post-fire. To better understand the impacts of wildfires on northern peatlands, we investigated the effects of varying peat burn severities on the dissolved organic carbon (DOC) concentration and the composition of dissolved organic matter (DOM) exported in the fall from peatlands located in Ontario's Boreal Shield ecozone. A paired peatlands approach was used with seven burned peatlands and six unburned peatlands. Each burned and unburned group contained three peatlands of similar size, average peat depth, and catchment size. The burned peatlands were located within the Parry Sound #33 wildfire footprint roughly 65 km north of the unburned peatlands that are located near Dinner Lake. Vegetation recovery was measured at the burned sites while runoff, water quality, water table depth, and precipitation were measured at both unburned and burned sites. Over a three-year period (2021-2023), exported DOC concentrations decreased significantly with increasing burn severity, but the composition of DOM varied across burn severities. Both the unburned and burned sites experienced fall flushing events in both 2022 and 2023 with the burned sites experiencing an additional flushing event mid-summer in 2023. The burned peatland with the highest percent burn experienced a delayed flushing event late fall due to the lack of discharge earlier in the season. Moss recovery was found to have the largest impact on DOM composition with increased Sphagnum moss regrowth associated with significant increases in DOM molecular size, weight, aromaticity, and degree of humification. The degree of moss recovery varied across high burn severity peatlands indicating a delay in recovery compared to low burn severity peatlands. Considering that climate change is increasing burn severity, future research should investigate the impact burn severity has on DOC concentration immediately following wildfire in landscapes dominated by fill and spill hydrological processes. Additionally, examining the impact of burn severity and average peat depth on vegetation recovery and exported DOM composition could lead to a better understanding of exported DOM composition following future wildfires on peatlands in this landscape.
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 | 0,000 | 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 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| 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 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 ».