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Enregistrement W6908420970 · doi:10.26092/elib/2686

Mobilization of terrestrial organic matter from thawing Arctic permafrost regions: Insights from lignin-derived phenols and their compound-specific radiocarbon ages

2023· article· en· W6908420970 sur OpenAlexaboutno aff

Notice bibliographique

RevueMedia (https://www.suub.uni-bremen.de/) · 2023
Typearticle
Langueen
DomaineEarth and Planetary Sciences
ThématiqueClimate change and permafrost
Établissements canadiensnon disponible
Organismes subventionnairesChina Scholarship Council
Mots-clésPermafrostOrganic matterArcticVegetation (pathology)Total organic carbonThermokarstSedimentTerrestrial plantTerrestrial ecosystem

Résumé

récupéré en direct d'OpenAlex

Global climate change is expected to have a huge impact on Arctic warming, leading to an increased remobilization of permafrost organic carbon. More than twice as much carbon as in the atmosphere is contained in permafrost soils, and may upon destabilization expose large amounts of organic matter to microbial degradation and release climate-forcing greenhouse gases. As an important link in the land-ocean continuum, rivers are important pathways for permafrost OC remobilization. Arctic ocean sediments are thus receptors of terrestrial OC remobilization for a large part of the circum-Arctic drainage basin and offer an archive to study past terrestrial OC remobilization as during the last deglaciation. This thesis studies terrestrial OC in sub-Arctic ocean sediments to study OC remobilization from permafrost regions across temporal and spatial scales. A detailed study of two sediment cores from the Bering Sea and Okhotsk Sea, allowed the reconstruction of vegetation development, permafrost OC mobilization, and transport pathways of permafrost OC remobilization during the last deglaciation. Vegetation development and permafrost OC remobilization have been investigated by analyses of the mass accumulation rate of terrestrial biomarkers (lignin phenols and lipids). To study the influence of climatic conditions on the stability of inland permafrost soils, the sea surface temperature of the Bering Sea was investigated (TEXL86). For the study of terrestrial OC remobilization from different carbon pools, compound-specific radiocarbon analysis (CSRA) was applied to terrestrial compounds (lignin-derived phenols). A modified method for the purification of lignin-derived phenols was used for CSRA. Downcore records of lignin flux from the Yukon and Amur basins covering the early deglaciation to the Holocene are discussed in the first study. It was found that vegetation change and permafrost remobilization occurred earlier in the Yukon than in the Amur basin. The retreat of sea ice coupled with increased sea surface temperatures in the Bering Sea and adjacent ocean areas during the early deglaciation (19.0-14.6 kyr) might have promoted early permafrost mobilization. The results reveal that lipids and lignin might have been delivered to the ocean by identical processes, i.e., runoff and erosion, which is not consistent with previous studies of modern Arctic river systems. A simplified procedure for the purification of lignin phenols based on the published method by Feng et al., (2013b) and an evaluation of the fraction of modern carbon (F14C) and the mass of the associated procedural blank is described in the second study. Lignin phenols were purified only by one HLB SPE cartridge (Waters Oasis, 200 mg, 6 mL). Samples were eluted from the HLB cartridge with 60 mL ethyl acetate to achieve a clean-up of lignin-derived phenols. Single compound separation and collection was achieved by HPLC on a Phenomenex Synergi Polar-RP column at 40 °C. The blank carbon contribution of the entire method, as determined with reference compounds, was found to be 4.17 ± 0.35 mgC with an F14C of 0.55 ± 0.04. In the third study, the revised method of lignin purification was applied to obtain first downcore CSRA records of lignin-derived phenols from sediment cores retrieved off the Yukon and Amur Basins. The radiocarbon ages of phenols from sediments of the Bering and Okhotsk Seas are expected to reflect inputs from at least two different terrigenous sources that are characterized by different ages and degradation degrees during the last deglaciation. The age offsets between lignin phenols and fatty acids were controlled by surface discharge in the Yukon and Amur Basins. Deep OC enriched in long-chain lipids can be mobilized both through coastal erosion and thawing of inland thermokarst which can be transported to marine sediments by surface runoff in the last deglaciation. The radiocarbon ages of lignin phenols and long-chain fatty acids are controlled by processes that are affected by climate change, and the 14C age offset between lipids and lignin phenols can be used as palaeo-proxy for these changing processes. The fourth study investigates lignin phenols flux and radiocarbon ages in short cores off the Lena River, covering the last century. The vegetation in the Lena Basin is a mixture of woody gymnosperm and non-woody angiosperm sources and has not changed significantly in the past century. Young and old terrigenous carbon pools both affect the D14C values of phenols in the two sediment cores. The D14C values of lignin phenols in shallow Laptev Sea sediments may be treated as an indicator of runoff. This thesis highlights the vulnerability of permafrost OC to Arctic warming over time and space, thus contributing to a better understanding of climate-carbon couplings in the Earth system.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,012
Score d'incertitude au seuil0,024

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,042
Tête enseignante GPT0,225
Écart entre enseignants0,182 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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