Biogeochemical and Ecological Responses to Warming Climate in High Arctic Polar Deserts
Notice bibliographique
Résumé
High Arctic polar deserts cover 26% of the Arctic and are predicted to transform dramatically with rapidly rising temperatures. Previous studies found that polar deserts store larger amounts of soil organic carbon (SOC) in the permafrost than previously expected and can emit greenhouse gases (GHGs) at rate comparable to mesic Arctic ecosystems. However, the mechanism of the GHG production is not clear, which contributes to a great source of uncertainty regarding ecological feedbacks to the warming climate. Extreme climate conditions thaw the uppermost part of the permafrost, and the accumulated soil nutrients are ejected into the overlying soil layers where the subsurface nutrient patches (diapirs) form to increase carbon and nitrogen (N) contents by 7% and 20%, respectively. Previous mechanical models suggest that the ejection is facilitated by the increase in soil viscosity in the overlying soil layer. We previously found that diapirs developed about 30% of sorted circles in our study site and that the dominant vascular plant (Salix arctica) increased root biomass and nitrogen uptake from diapirs. To understand a GHG-feedback to the warming climate, we collected 40 soil samples with diapirs and 40 without diapirs during July and August 2013 to investigate gross N transformation rates and GHG emissions associated with diapirs in laboratory. Our study site encompasses two Canadian High Arctic polar deserts and is located near Alexandra Fjord (78°51′N, 75°54′W), Ellesmere Island, Nunavut, Canada. To deal with small amounts of nitrous oxide (N2O) emissions near or below the detection limit, we employed the hurdle models including (1) a Bernoulli component that models whether the data cross the detection limit based on covariates and (2) generalized linear model component that models the data above the detection limit. Our results showed that diapirs decreased gross N mineralization up to 48% and slowed carbon dioxide and methane emissions. Consistently, we found that diapirs contained more recalcitrant SOC using attenuated total reflectance Fourier transformed mid-infrared (ATR-FTIR) spectroscopy. ATR-FTIR also showed higher amounts of polysaccharides known to raise soil viscosity. The hurdle model approach showed that diapirs increased the estimated N2O emissions by up to 49% under wet conditions and suggested that the increase links to the increase in the probability of N2O emissions. On the other hand, under dry conditions, the hurdle models suggested that the increase in the estimated N2O emissions from diapirs links to the increase in the magnitude of the N2O emissions. The higher abundance of polysaccharides and recalcitrant SOC may indicate that biological factors are involved in forming diapirs and that diapirs supply vascular plants with nutrients as a result of a mutualistic relationship. Our study showed that diapirs altered GHG emissions and suggest that future research should include plant-microbe relationship in diapirs and other factors such as occlusion in soil aggregates for a more robust evaluation of diaper-GHG production. Furthermore, we suggest that the hurdle model may be a useful tool for evaluating N2O emissions that are locally small but could be critical in total in the Arctic.
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 | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 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) | 0,000 | 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 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 ».