Organic Carbon Transformation and Mercury Methylation in Tundra Soils from Barrow Alaska

This dataset includes information on soil labile organic carbon transformation and mercury methylation for tundra soils from Barrow, Alaska. The soil cores were collected from high-centered polygon (trough) at BEO and were incubated under anaerobic laboratory conditions at both freezing and warming...

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Bibliographic Details
Main Authors: Yang, Ziming, Gu, Baohua
Language:unknown
Published: 2023
Subjects:
Online Access:http://www.osti.gov/servlets/purl/1235032
https://www.osti.gov/biblio/1235032
https://doi.org/10.5440/1235032
Description
Summary:This dataset includes information on soil labile organic carbon transformation and mercury methylation for tundra soils from Barrow, Alaska. The soil cores were collected from high-centered polygon (trough) at BEO and were incubated under anaerobic laboratory conditions at both freezing and warming temperatures for up to 8 months. Soil organic carbon including reducing sugars, alcohols, and organic acids were analyzed, and CH4 and CO2 emissions were quantified. Net production of methylmercury and Fe(II)/Fe(total) ratio were also measured and provided in this dataset. This dataset includes two files, one csv and one pdf. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) 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).