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Title: Compiled Multi-Lab Geochemistry Synoptic Survey (LANL, ORNL, LBNL), Barrow, Alaska, 2012

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. DOI 10.5440/1164833; https://doi.org/10.5440/1164833

Authors:
;
Publication Date:
Other Number(s):
NGA011
DOE Contract Number:  
DE-AC05-00OR22725
Product Type:
Dataset
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)
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
OSTI Identifier:
1164833
DOI:
https://doi.org/10.5440/1164833

Citation Formats

Throckmorton, Heather, and Newman, Brent. Compiled Multi-Lab Geochemistry Synoptic Survey (LANL, ORNL, LBNL), Barrow, Alaska, 2012. United States: N. p., 2015. Web. doi:10.5440/1164833.
Throckmorton, Heather, & Newman, Brent. Compiled Multi-Lab Geochemistry Synoptic Survey (LANL, ORNL, LBNL), Barrow, Alaska, 2012. United States. doi:https://doi.org/10.5440/1164833
Throckmorton, Heather, and Newman, Brent. 2015. "Compiled Multi-Lab Geochemistry Synoptic Survey (LANL, ORNL, LBNL), Barrow, Alaska, 2012". United States. doi:https://doi.org/10.5440/1164833. https://www.osti.gov/servlets/purl/1164833. Pub date:Mon Jan 12 00:00:00 EST 2015
@article{osti_1164833,
title = {Compiled Multi-Lab Geochemistry Synoptic Survey (LANL, ORNL, LBNL), Barrow, Alaska, 2012},
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. DOI 10.5440/1164833; https://doi.org/10.5440/1164833},
doi = {10.5440/1164833},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2015},
month = {1}
}