MOFLUX Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: Modeling Archive.

Liang, J.; Wang, G.; Singh, S.; Jagadamma, S.; Gu, L.; Schadt, C.; Wood, J.D.; Hanson, P.J.; Mayes, M.A.

doi:10.25581/ornlsfa.023/1804106

Title: MOFLUX Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: Modeling Archive.

Abstract

This Modeling Archive is in support of a TES-SFA publication “Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: A Mechanistic Modeling Analysis” (Liang et al., 2021). Here we provide model code, inputs, outputs and evaluation datasets for the Microbial ENzyme Decomposition (MEND) model for the Missouri Ozarks AmeriFlux eddy covariance measurement site (MOFLUX) near Ashland, Missouri USA. The MEND model was developed with explicit representation of microbial and enzyme pools to mechanistically simulate the role of microbial organisms and extracellular enzymes in soil organic carbon (SOC) decomposition. Long-term SOC dynamics under intensified moisture extremes are studied using the MEND model that is parameterized with 11 years of measurements from the MOFLUX forest. The model explicitly represents microbial dormancy and resuscitation, different types of SOC-degrading enzymes, and how they vary with changes in soil moisture (Wang et al. 2015, 2019). A combination of two levels of frequency and severity of soil moisture, as well as a control with normal interannual variability, are used to simulate a range of moisture scenarios over 100 years. The code of Microbial-ENzyme Decomposition (MEND) as well as the input and output data are included in the archive. A user’s manual (MEND_Readme.pdf) is included with instructionsmore »« less

Authors:

Liang, J.; Wang, G.; Singh, S.; Jagadamma, S.;

; Schadt, C.; Wood, J.D.; Hanson, P.J.; Mayes, M.A.

Publication Date:: 2021-01-01

DOE Contract Number:: AC05-00OR22725

Research Org.:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: USDOE Office of Artificial Intelligence and Technology (AITO); USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division

Subject:: 54 ENVIRONMENTAL SCIENCES

Keywords:: MEND model, soil organic carbon (SOC) decomposition, MOFLUX, model code, inputs, outputs, evaluation datasets, Microbial ENzyme Decomposition model

Geolocation:: 38.7441, -92.2

OSTI Identifier:: 1804106

DOI:: https://doi.org/10.25581/ornlsfa.023/1804106

Project Location:: Missouri Ozark AmeriFlux (MOFLUX) Site

Citation Formats


                    Liang, J., Wang, G., Singh, S., Jagadamma, S., Gu, L., Schadt, C., Wood, J.D., Hanson, P.J., and Mayes, M.A. MOFLUX Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: Modeling Archive..  United States: N. p., 2021. 
        Web.  doi:10.25581/ornlsfa.023/1804106.

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                    Liang, J., Wang, G., Singh, S., Jagadamma, S., Gu, L., Schadt, C., Wood, J.D., Hanson, P.J., & Mayes, M.A. MOFLUX Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: Modeling Archive..  United States.  doi:https://doi.org/10.25581/ornlsfa.023/1804106

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                    Liang, J., Wang, G., Singh, S., Jagadamma, S., Gu, L., Schadt, C., Wood, J.D., Hanson, P.J., and Mayes, M.A. 2021.  
"MOFLUX Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: Modeling Archive.".  United States.  doi:https://doi.org/10.25581/ornlsfa.023/1804106.  https://www.osti.gov/servlets/purl/1804106. Pub date:Fri Jan 01 00:00:00 EST 2021

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@article{osti_1804106,

  title        = {MOFLUX Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: Modeling Archive.},

  author       = {Liang, J. and Wang, G. and Singh, S. and Jagadamma, S. and Gu, L. and Schadt, C. and Wood, J.D. and Hanson, P.J. and Mayes, M.A.},

  abstractNote = {This Modeling Archive is in support of a TES-SFA publication “Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: A Mechanistic Modeling Analysis” (Liang et al., 2021). Here we provide model code, inputs, outputs and evaluation datasets for the Microbial ENzyme Decomposition (MEND) model for the Missouri Ozarks AmeriFlux eddy covariance measurement site (MOFLUX) near Ashland, Missouri USA. The MEND model was developed with explicit representation of microbial and enzyme pools to mechanistically simulate the role of microbial organisms and extracellular enzymes in soil organic carbon (SOC) decomposition. Long-term SOC dynamics under intensified moisture extremes are studied using the MEND model that is parameterized with 11 years of measurements from the MOFLUX forest. The model explicitly represents microbial dormancy and resuscitation, different types of SOC-degrading enzymes, and how they vary with changes in soil moisture (Wang et al. 2015, 2019). A combination of two levels of frequency and severity of soil moisture, as well as a control with normal interannual variability, are used to simulate a range of moisture scenarios over 100 years. The code of Microbial-ENzyme Decomposition (MEND) as well as the input and output data are included in the archive. A user’s manual (MEND_Readme.pdf) is included with instructions for compiling and running the model to simulate soil organic carbon decomposition under various moisture scenarios.},

  doi          = {10.25581/ornlsfa.023/1804106},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {2021},

  month        = {1}

}

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DOI: https://doi.org/10.25581/ornlsfa.023/1804106

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Works referenced in this record:

Organic-matter decomposition along a temperature gradient in a forested headwater stream
journal, June 2016

Griffiths, Natalie A.; Tiegs, Scott D.
Freshwater Science, Vol. 35, Issue 2
https://doi.org/10.1086/685657

Global, Regional, and National Fossil-Fuel CO2 Emissions (1751 - 2014) (V. 2017)
dataset, January 2017

Boden, T.; Marland, G.; Andres, R. J.
ESS-DIVE: Deep Insight for Earth Science Data, 9 KB
https://doi.org/10.3334/CDIAC/00001_V2017

Influence of dual nitrogen and phosphorus additions on nutrient uptake and saturation kinetics in a forested headwater stream
journal, December 2018

Griffiths, Natalie A.; Johnson, Laura T.
Freshwater Science, Vol. 37, Issue 4
https://doi.org/10.1086/700700

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Similar Records

Title: MOFLUX Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: Modeling Archive.

Abstract

Citation Formats

Organic-matter decomposition along a temperature gradient in a forested headwater stream journal, June 2016

Global, Regional, and National Fossil-Fuel CO2 Emissions (1751 - 2014) (V. 2017) dataset, January 2017

Influence of dual nitrogen and phosphorus additions on nutrient uptake and saturation kinetics in a forested headwater stream journal, December 2018

Organic-matter decomposition along a temperature gradient in a forested headwater stream
journal, June 2016

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dataset, January 2017

Influence of dual nitrogen and phosphorus additions on nutrient uptake and saturation kinetics in a forested headwater stream
journal, December 2018