Code and Data for Reduced net methane emissions due to microbial methane oxidation in a warmer Arctic [version 1.0]

This publication contains code and data of a biogeochemistry model, XPTEM-XHAM, that includes microbial dynamics of high-affinity methanotrophs (HAM) and methanogens with permafrost carbon dynamics. You will find 4 zipped files when downloading the bundle. One file (Code_XPTEM-XHAM.zip) contains C++...

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Main Authors: Bo Elberling, David Medvigy, Edward J. Dlugokencky, Gustaf Hugelius, Licheng Liu, Lisa R. Welp-Smith, Lori Bruhwiler, Ludovica D'Imperio, Maggie C.Y. Lau, Qianlai Zhuang, Tullis C. Onstott, Youmi Oh
Format: Dataset
Language:unknown
Published: 2020
Subjects:
Online Access:https://doi.org/10.4231/Q3R8-SZ17
id ftpurdueunivpurr:https://doi.org/10.4231/Q3R8-SZ17
record_format openpolar
spelling ftpurdueunivpurr:https://doi.org/10.4231/Q3R8-SZ17 2023-11-12T04:11:50+01:00 Code and Data for Reduced net methane emissions due to microbial methane oxidation in a warmer Arctic [version 1.0] Bo Elberling David Medvigy Edward J. Dlugokencky Gustaf Hugelius Licheng Liu Lisa R. Welp-Smith Lori Bruhwiler Ludovica D'Imperio Maggie C.Y. Lau Qianlai Zhuang Tullis C. Onstott Youmi Oh 2020-02-04T08:30:09Z https://doi.org/10.4231/Q3R8-SZ17 unknown Hannah, M. (2021). QAnon and the information dark age. First Monday, 26(2). https://doi.org/10.5210/fm.v26i2.10868 Hannah, M. N. (2021). A Conspiracy of Data: QAnon, Social Media, and Information Visualization. Social Media + Society, 7(3). https://doi.org/10.1177/20563051211036064 https://doi.org/10.4231/Q3R8-SZ17 Arctic Region Biogeochemistry EAPS Earth and Atmospheric Sciences Methane Dynamics Model (MDM) Methane Emission Microbial-Based Model soil publications:dataset 2020 ftpurdueunivpurr https://doi.org/10.4231/Q3R8-SZ1710.5210/fm.v26i2.1086810.1177/20563051211036064 2023-10-30T09:32:16Z This publication contains code and data of a biogeochemistry model, XPTEM-XHAM, that includes microbial dynamics of high-affinity methanotrophs (HAM) and methanogens with permafrost carbon dynamics. You will find 4 zipped files when downloading the bundle. One file (Code_XPTEM-XHAM.zip) contains C++ codes, compiler, and guidelines for the XPTEM-XHAM model. Other three files (Data_XPTEM_XHAM_2000_2016.zip, Data_XPTEM_XHAM_2017_2100_default. zip, and Data_XPTEM_XHAM_2017_2100_w_Physiology. zip) contain raw and processed model results for contemporary period (2000-2016) and future projections (2017-2100), and Matlab files to plot the processed data in Matlab. Methane emissions from organic-rich soils in the Arctic have been extensively studied due to their potential to increase the atmospheric methane burden as permafrost thaws. However, this methane source might have been overestimated without considering high affinity methanotrophs (HAM, methane oxidizing bacteria) recently identified in Arctic mineral soils. Here, we find that HAM dynamics double the upland methane sink (~5.5 TgCH4yr-1) north of 50°N in simulations from 2000-2016 by integrating the dynamics of HAM and methanogens into a biogeochemistry model that includes permafrost SOC dynamics. The increase is equivalent to at least half of the difference in net methane emissions estimated between process-based models and observation-based inversions, and the revised estimates better match site-level and regional observations. The new model projects doubled wetland methane emissions between 2017-2100 due to more accessible permafrost carbon. However, most of the increase in wetland emissions is offset by a concordant increase in the upland sink, leading to only an 18% increase in net methane emission (from 29 to 35 TgCH4yr-1). The projected net methane emissions may decrease further due to different physiological responses between HAM and methanogens in response to increasing temperature. Dataset Arctic permafrost Purdue University Research Repository Arctic
institution Open Polar
collection Purdue University Research Repository
op_collection_id ftpurdueunivpurr
language unknown
topic Arctic Region
Biogeochemistry
EAPS
Earth and Atmospheric Sciences
Methane Dynamics Model (MDM)
Methane Emission
Microbial-Based Model
soil
spellingShingle Arctic Region
Biogeochemistry
EAPS
Earth and Atmospheric Sciences
Methane Dynamics Model (MDM)
Methane Emission
Microbial-Based Model
soil
Bo Elberling
David Medvigy
Edward J. Dlugokencky
Gustaf Hugelius
Licheng Liu
Lisa R. Welp-Smith
Lori Bruhwiler
Ludovica D'Imperio
Maggie C.Y. Lau
Qianlai Zhuang
Tullis C. Onstott
Youmi Oh
Code and Data for Reduced net methane emissions due to microbial methane oxidation in a warmer Arctic [version 1.0]
topic_facet Arctic Region
Biogeochemistry
EAPS
Earth and Atmospheric Sciences
Methane Dynamics Model (MDM)
Methane Emission
Microbial-Based Model
soil
description This publication contains code and data of a biogeochemistry model, XPTEM-XHAM, that includes microbial dynamics of high-affinity methanotrophs (HAM) and methanogens with permafrost carbon dynamics. You will find 4 zipped files when downloading the bundle. One file (Code_XPTEM-XHAM.zip) contains C++ codes, compiler, and guidelines for the XPTEM-XHAM model. Other three files (Data_XPTEM_XHAM_2000_2016.zip, Data_XPTEM_XHAM_2017_2100_default. zip, and Data_XPTEM_XHAM_2017_2100_w_Physiology. zip) contain raw and processed model results for contemporary period (2000-2016) and future projections (2017-2100), and Matlab files to plot the processed data in Matlab. Methane emissions from organic-rich soils in the Arctic have been extensively studied due to their potential to increase the atmospheric methane burden as permafrost thaws. However, this methane source might have been overestimated without considering high affinity methanotrophs (HAM, methane oxidizing bacteria) recently identified in Arctic mineral soils. Here, we find that HAM dynamics double the upland methane sink (~5.5 TgCH4yr-1) north of 50°N in simulations from 2000-2016 by integrating the dynamics of HAM and methanogens into a biogeochemistry model that includes permafrost SOC dynamics. The increase is equivalent to at least half of the difference in net methane emissions estimated between process-based models and observation-based inversions, and the revised estimates better match site-level and regional observations. The new model projects doubled wetland methane emissions between 2017-2100 due to more accessible permafrost carbon. However, most of the increase in wetland emissions is offset by a concordant increase in the upland sink, leading to only an 18% increase in net methane emission (from 29 to 35 TgCH4yr-1). The projected net methane emissions may decrease further due to different physiological responses between HAM and methanogens in response to increasing temperature.
format Dataset
author Bo Elberling
David Medvigy
Edward J. Dlugokencky
Gustaf Hugelius
Licheng Liu
Lisa R. Welp-Smith
Lori Bruhwiler
Ludovica D'Imperio
Maggie C.Y. Lau
Qianlai Zhuang
Tullis C. Onstott
Youmi Oh
author_facet Bo Elberling
David Medvigy
Edward J. Dlugokencky
Gustaf Hugelius
Licheng Liu
Lisa R. Welp-Smith
Lori Bruhwiler
Ludovica D'Imperio
Maggie C.Y. Lau
Qianlai Zhuang
Tullis C. Onstott
Youmi Oh
author_sort Bo Elberling
title Code and Data for Reduced net methane emissions due to microbial methane oxidation in a warmer Arctic [version 1.0]
title_short Code and Data for Reduced net methane emissions due to microbial methane oxidation in a warmer Arctic [version 1.0]
title_full Code and Data for Reduced net methane emissions due to microbial methane oxidation in a warmer Arctic [version 1.0]
title_fullStr Code and Data for Reduced net methane emissions due to microbial methane oxidation in a warmer Arctic [version 1.0]
title_full_unstemmed Code and Data for Reduced net methane emissions due to microbial methane oxidation in a warmer Arctic [version 1.0]
title_sort code and data for reduced net methane emissions due to microbial methane oxidation in a warmer arctic [version 1.0]
publishDate 2020
url https://doi.org/10.4231/Q3R8-SZ17
geographic Arctic
geographic_facet Arctic
genre Arctic
permafrost
genre_facet Arctic
permafrost
op_relation Hannah, M. (2021). QAnon and the information dark age. First Monday, 26(2). https://doi.org/10.5210/fm.v26i2.10868
Hannah, M. N. (2021). A Conspiracy of Data: QAnon, Social Media, and Information Visualization. Social Media + Society, 7(3). https://doi.org/10.1177/20563051211036064
https://doi.org/10.4231/Q3R8-SZ17
op_doi https://doi.org/10.4231/Q3R8-SZ1710.5210/fm.v26i2.1086810.1177/20563051211036064
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