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Title: Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0)

Abstract

Explicit consideration of microbial physiology in soil biogeochemical models that represent coupled carbon–nitrogen dynamics presents opportunities to deepen understanding of ecosystem responses to environmental change. The MIcrobial-MIneral Carbon Stabilization (MIMICS) model explicitly represents microbial physiology and physicochemical stabilization of soil carbon (C) on regional and global scales. Here we present a new version of MIMICS with coupled C and nitrogen (N) cycling through litter, microbial, and soil organic matter (SOM) pools. The model was parameterized and validated against C and N data from the Long-Term Inter-site Decomposition Experiment Team (LIDET; six litter types, 10 years of observations, and 13 sites across North America). The model simulates C and N losses from litterbags in the LIDET study with reasonable accuracy (C: R2=0.63; N: R2=0.29), which is comparable with simulations from the DAYCENT model that implicitly represents microbial activity (C: R2=0.67; N: R2=0.30). Subsequently, we evaluated equilibrium values of stocks (total soil C and N, microbial biomass C and N, inorganic N) and microbial process rates (soil heterotrophic respiration, N mineralization) simulated by MIMICS-CN across the 13 simulated LIDET sites against published observations from other continent-wide datasets. We found that MIMICS-CN produces equilibrium values in line with measured values, showing that themore » model generates plausible estimates of ecosystem soil biogeochemical dynamics across continental-scale gradients. MIMICS-CN provides a platform for coupling C and N projections in a microbially explicit model, but experiments still need to identify the physiological and stoichiometric characteristics of soil microbes, especially under environmental change scenarios.« less

Authors:
 [1]; ORCiD logo [2];  [1];  [1]
  1. Univ. of New Hampshire, Durham, NH (United States)
  2. National Center for Atmospheric Research, Boulder, CO (United States); Univ. of Colorado, Boulder, CO (United States)
Publication Date:
Research Org.:
Univ. of Massachusetts, Amherst, MA (United States); Univ. of Colorado, Boulder, CO (United States); Cornell Univ., Ithaca, NY (United States)
Sponsoring Org.:
USDA; National Science Foundation (NSF); USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division
OSTI Identifier:
1711420
Alternate Identifier(s):
OSTI ID: 1863819
Grant/Contract Number:  
SC0016590; SC0014374; SC0016364; 2015-35615-22747; 2015-67003-23485; DGE-1450271
Resource Type:
Accepted Manuscript
Journal Name:
Geoscientific Model Development (Online)
Additional Journal Information:
Journal Name: Geoscientific Model Development (Online); Journal Volume: 13; Journal Issue: 9; Journal ID: ISSN 1991-9603
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES

Citation Formats

Kyker-Snowman, Emily, Wieder, William R., Frey, Serita D., and Grandy, A. Stuart. Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0). United States: N. p., 2020. Web. doi:10.5194/gmd-13-4413-2020.
Kyker-Snowman, Emily, Wieder, William R., Frey, Serita D., & Grandy, A. Stuart. Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0). United States. https://doi.org/10.5194/gmd-13-4413-2020
Kyker-Snowman, Emily, Wieder, William R., Frey, Serita D., and Grandy, A. Stuart. Tue . "Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0)". United States. https://doi.org/10.5194/gmd-13-4413-2020. https://www.osti.gov/servlets/purl/1711420.
@article{osti_1711420,
title = {Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0)},
author = {Kyker-Snowman, Emily and Wieder, William R. and Frey, Serita D. and Grandy, A. Stuart},
abstractNote = {Explicit consideration of microbial physiology in soil biogeochemical models that represent coupled carbon–nitrogen dynamics presents opportunities to deepen understanding of ecosystem responses to environmental change. The MIcrobial-MIneral Carbon Stabilization (MIMICS) model explicitly represents microbial physiology and physicochemical stabilization of soil carbon (C) on regional and global scales. Here we present a new version of MIMICS with coupled C and nitrogen (N) cycling through litter, microbial, and soil organic matter (SOM) pools. The model was parameterized and validated against C and N data from the Long-Term Inter-site Decomposition Experiment Team (LIDET; six litter types, 10 years of observations, and 13 sites across North America). The model simulates C and N losses from litterbags in the LIDET study with reasonable accuracy (C: R2=0.63; N: R2=0.29), which is comparable with simulations from the DAYCENT model that implicitly represents microbial activity (C: R2=0.67; N: R2=0.30). Subsequently, we evaluated equilibrium values of stocks (total soil C and N, microbial biomass C and N, inorganic N) and microbial process rates (soil heterotrophic respiration, N mineralization) simulated by MIMICS-CN across the 13 simulated LIDET sites against published observations from other continent-wide datasets. We found that MIMICS-CN produces equilibrium values in line with measured values, showing that the model generates plausible estimates of ecosystem soil biogeochemical dynamics across continental-scale gradients. MIMICS-CN provides a platform for coupling C and N projections in a microbially explicit model, but experiments still need to identify the physiological and stoichiometric characteristics of soil microbes, especially under environmental change scenarios.},
doi = {10.5194/gmd-13-4413-2020},
journal = {Geoscientific Model Development (Online)},
number = 9,
volume = 13,
place = {United States},
year = {Tue Sep 22 00:00:00 EDT 2020},
month = {Tue Sep 22 00:00:00 EDT 2020}
}

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