Hydrology, carbon dynamics and hydrochemical properties of ponds in an extensive low gradient High Arctic wetland, Polar Bear Pass, Bathurst Island, Nunavut, Canada
Notice bibliographique
Résumé
Ponds form the dominant feature of Polar Bear Pass (PBP), one of the largest wetlands in the Canadian High Arctic, and in order to understand the ramifications of climatic changes on PBP we must first understand the ponds' responses to seasonal changes in climatic, physical, chemical, and carbon components. Fieldwork (2007-2010) at PBP aimed (i) to determine water budgets of ponds with various hydrologic settings, (ii) to identify the processes controlling the changes in pond carbon and geochemistry on seasonal and inter-annual bases with a special focus on the snowmelt period, and (iii) to establish the baseline hydrochemistry and hydrology of ponds within the PBP wetland complex. Pond systems at PBP have two hydrologic settings: (i) ones which are hydrologically connected to additional sources of water from their catchments beyond seasonal inputs of snowmelt and rainfall, or (ii) ponds which fail to form a link or only have a limited connection with their surrounding catchments. Intensive seasonal monitoring of water and carbon mass balance showed that elevated loads of dissolved organic carbon (DOC) in ponds were mostly of terrestrial origin and occurred in ponds receiving meltwater from snowbeds and/or discharge from hillslope creeks. The seasonal strength in the connectivity of a pond to its catchment from snowmelt to the postsnowmelt period was critical in controlling DOC loads and concentrations. This study provided the first estimates of DOC yields at Polar Bear Pass, and reported elevated DOC loadings from wet meadow catchments into ponds. This highlights their importance as a source of carbon to pond ecosystems during snowmelt and heavy rainfall events. The water chemistry and environmental data showed that waters at PBP were dominated by calcium and bicarbonate ions that fell on a common dilution line, however, they had distinct proportional major ionic variability due to the location, lithology, and level of water-bedrock interaction, and these dynamics were controlled by differences in climatic conditions and hydrologic connectivity. Results relating to pond-landscape linkages and their role in solute transport to ponds showed (i) elevated surface and subsurface water contribution to ponds in hydrologically connected catchments. The primary mechanism for solute and carbon transport was overland flow during snowmelt and surface/subsurface inflow during the post-snowmelt season. There was (ii) a potential for higher solute inflow during seasons with frequent or large precipitation events. Lastly, (iii) isolated ponds were subject to evapo-concentration resulting in solute enrichment in pond waters during warm, dry periods. An analysis of carbon dioxide (C02) concentrations in surface waters during snowmelt was conducted to provide the first estimates of this greenhouse gas in ponds at PBP and to further support the interpretation of hydro logic and carbon dynamics in ponds during the snowmelt and early post-snowmelt season. Surface waters at PBP were strong sources of C02 to the atmosphere, with C02 emissions dramatically increasing at the beginning of snowmelt and then declining during peak snowmelt. The required inputs of carbon to support the estimated C02 emissions could be explained by surface or subsurface inflows of dissolved organic carbon and dissolved inorganic carbon, and possibly from mineralization of terrestrial organic carbon in the water column and sediments of ponds. The findings of this study will aid in the future management of the PBP wetland, and may be applied to other arctic ponds situated in High Arctic wetland environments or in any area in the circumpolar Arctic that has similar geomorphologic features and climatic setting.
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) | 0,000 | 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 | 0,002 |
| 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 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 ».