Deconvolving Climatic and Non-Climatic Controls on Holocene Glacier and Ecological Change on Baffin Island, Arctic Canada
Notice bibliographique
Résumé
The Arctic is warming at double the rate of the rest of the planet. Pronounced warming is causing dramatic changes in glacier extent and tundra ecosystems, which in turn contribute to positive feedbacks that further amplify climate change. In this dissertation, I look to the geologic record to critically assess how climate variability, as well as non-climatic factors, drove changes in the cryosphere and biosphere on Baffin Island, Arctic Canada, over the last ~10,000 years. Baffin Island is an ideal setting to investigate high-amplitude Arctic paleoenvironmental changes because 1) it is the locus of inception and final demise for the climatically-important Laurentide Ice Sheet; 2) it hosts a multitude of extant (and paleo-) glaciers and ice caps that respond sensitively to climate change; and 3) pristine lakes across the island contain continuous, datable sedimentary records of paleoclimate and paleoenvironmental change. The paleo perspective generated by this research provides important constraints on the rates and mechanisms of expected future environmental change across Arctic landscapes.\nIn order to investigate past glacier activity, I use cosmogenic 10Be to date moraines that were deposited on Baffin Island during the Holocene. In Chapter 2, 10Be ages on Neoglacial moraine complexes indicate that late Holocene cooling likely initiated glacier expansion before 5 ka. However, a spread in exposure ages suggests that post-depositional moraine degradation limits the precision of exposure dating in such settings. Numerical modeling offers additional insights into the glacial and geomorphic processes involved in the formation and evolution of ice-cored moraines. In chapter 3, I examine the glacial response to abrupt cooling during the otherwise warm early Holocene. Four moraines on eastern Baffin Island were deposited around the time of known cooling events centered on 9.3 and 8.2 ka, which were likely driven by disruptions to the Atlantic Ocean overturning circulation. I further examine the role of Baffin Bay sea surface conditions and the potential for a mechanical adjustment of tributary glacier profiles during regional deglaciation to contribute to short-lived early Holocene glacier advances.\nTo further our understanding of the links between climate and ecosystems, I then investigate tundra vegetation changes through the Holocene using ancient DNA extracted from lake sediment cores (sedaDNA). In Chapter 4, I assess the performance of this emerging technique in two Baffin Island lake sediment records that span the last ~7 ka and 12 ka, respectively. Metabarcoding using two genetic markers for plants reveals dynamic tundra communities at both sites. These results confirm that sedaDNA is sourced locally and is more reliable than traditional pollen-based approaches for determining the presence/absence of certain woody shrubs at high latitudes. In chapter 5, I combine a sedaDNA record from southern Baffin Island with a biomarker-based paleotemperature reconstruction to investigate postglacial landscape development. This combination of molecular proxies provides tight constraints on the colonization timing of dwarf birch and highlights a previously unrecognized migration lag relative to local deglaciation and warmest temperatures of the Holocene.\nTaken together, this research offers numerous valuable insights into how key features of the Arctic system, including mountain glaciers and tundra ecosystems, respond nonlinearly to climate variability on a variety of timescales, with clear implications for a changing Arctic today.
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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 | 0,000 |
| 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) | 0,003 | 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 ».