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Title: Microtopographic and Depth Controls on Active Layer Chemistry in Arctic Polygonal Ground: Supporting Data

Abstract

Polygonal ground is a signature characteristic of the Arctic, and permafrost thaw can potentially generate substantial feedbacks to Arctic ecosystems and climate. This study describes the first comprehensive spatial examination of active layer biogeochemistry that extends across high- and low-centered polygons and their features, including depth. Water chemistry measurements were made on active layer water samples collected near Barrow, Alaska during summer, 2012. Several significant differences in chemistry were observed between high- and low-centered polygons suggesting polygon types may be useful for landscape-scale geochemical classification. However, differences were found for polygon features (centers and troughs) for analytes that were not significant for type, suggesting that finer scale features control biogeochemistry in a different way than polygon type. Depth variations were also significant, demonstrating important multi-dimensional aspects of polygonal ground biogeochemistry. These results have major implications for understanding how polygonal ground ecosystems function, and how they may respond to future change. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had twomore » field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).« less

Authors:
; ORCiD logo
Publication Date:
Other Number(s):
NGA011
DOE Contract Number:  
DE-AC05-00OR22725
Research Org.:
Next Generation Ecosystems Experiment - Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US); NGEE Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Collaborations:
PNL, BNL,ANL,ORNL
Subject:
54 Environmental Sciences
Keywords:
TOC; total organic carbon; Cations; Anions; nitrate; dissolved oxygen; DOC; dissolved organic carbon; Aqueous geochemistry; Soil pore water geochemistry; Barrow, Alaska; Utqiagvik, Alaska
OSTI Identifier:
1164833
DOI:
https://doi.org/10.5440/1164833

Citation Formats

Throckmorton, Heather, and Newman, Brent. Microtopographic and Depth Controls on Active Layer Chemistry in Arctic Polygonal Ground: Supporting Data. United States: N. p., 2021. Web. doi:10.5440/1164833.
Throckmorton, Heather, & Newman, Brent. Microtopographic and Depth Controls on Active Layer Chemistry in Arctic Polygonal Ground: Supporting Data. United States. doi:https://doi.org/10.5440/1164833
Throckmorton, Heather, and Newman, Brent. 2021. "Microtopographic and Depth Controls on Active Layer Chemistry in Arctic Polygonal Ground: Supporting Data". United States. doi:https://doi.org/10.5440/1164833. https://www.osti.gov/servlets/purl/1164833. Pub date:Wed Dec 08 00:00:00 EST 2021
@article{osti_1164833,
title = {Microtopographic and Depth Controls on Active Layer Chemistry in Arctic Polygonal Ground: Supporting Data},
author = {Throckmorton, Heather and Newman, Brent},
abstractNote = {Polygonal ground is a signature characteristic of the Arctic, and permafrost thaw can potentially generate substantial feedbacks to Arctic ecosystems and climate. This study describes the first comprehensive spatial examination of active layer biogeochemistry that extends across high- and low-centered polygons and their features, including depth. Water chemistry measurements were made on active layer water samples collected near Barrow, Alaska during summer, 2012. Several significant differences in chemistry were observed between high- and low-centered polygons suggesting polygon types may be useful for landscape-scale geochemical classification. However, differences were found for polygon features (centers and troughs) for analytes that were not significant for type, suggesting that finer scale features control biogeochemistry in a different way than polygon type. Depth variations were also significant, demonstrating important multi-dimensional aspects of polygonal ground biogeochemistry. These results have major implications for understanding how polygonal ground ecosystems function, and how they may respond to future change. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).},
doi = {10.5440/1164833},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Dec 08 00:00:00 EST 2021},
month = {Wed Dec 08 00:00:00 EST 2021}
}