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Title: Modeling Transient Soil Moisture Limitations on Microbial Carbon Respiration

Abstract

Soil microorganisms are known to survive periods of aridity and to recover rapidly after wetting events, with the ability to transition between a dormant state in dry conditions and an active state in wet conditions. While this dynamic behavior has been previously incorporated into soil carbon respiration modeling frameworks, a direct comparison between this active-dormant transition mechanism and a more simplified first-order model has yet to be made. Here, we demonstrate the necessary extent of model complexity needed to reproduce transient carbon respiration rates obtained from a set of soil incubation experiments implemented over a range of soil depths and time intervals. Two approaches are tested, one uses simplified first-order kinetics, whereas the other employs a transition between active and dormant biomass. The performance of each model is evaluated using an Akaike Information Criterion (AIC) based on the accuracy with which they reproduce an experimental dataset consisting of two sets of time series soil incubations collected across a range of time and depth resolutions. Based on the AIC evaluation and model-data comparison, we conclude that a dormancy-enabled model featuring two distinct microbial strategists performs best for the majority of the soil profile (above 108 cm) for both high and lowmore » depth resolution and sampling frequency, despite the added parameters required. In contrast, the first-order model achieves better AIC scores when simulating our deepest soils (112–165 cm), where moisture fluctuations are expected to be less prevalent. These findings guide how and where we choose to apply more cost intensive models.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [4]; ORCiD logo [5]; ORCiD logo [1]
  1. Univ. of Illinois at Urbana-Champaign, IL (United States)
  2. U.S. Geological Survey, Denver, CO (United States)
  3. Stanford Univ., CA (United States); Univ. of Massachusetts, Amherst, MA (United States)
  4. Stanford Univ., CA (United States)
  5. Stanford Univ., CA (United States); Rocky Mountain Biological Lab., Crested Butte, CO (United States)
Publication Date:
Research Org.:
Stanford Univ., CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
OSTI Identifier:
1594055
Alternate Identifier(s):
OSTI ID: 1543371
Grant/Contract Number:  
SC0018155; SC0014556; DE‐SC0014556; DE‐SC0018155
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Geophysical Research. Biogeosciences
Additional Journal Information:
Journal Volume: 124; Journal Issue: 7; Related Information: jgrg21444-sup-0002-2018JG004628-SI.docxWord 2007 document , 158.8 KB Supporting Information S1jgrg21444-sup-0001-2018JG004628-fs01.docxWord 2007 document , 62.7 KB Figure S1; Journal ID: ISSN 2169-8953
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; soil moisture; reactive transport; soil carbon; microbial respiration

Citation Formats

Liu, Yuchen, Lawrence, Corey R., Winnick, Matthew J., Hsu, Hsiao‐Tieh, Maher, Katharine, and Druhan, Jennifer L. Modeling Transient Soil Moisture Limitations on Microbial Carbon Respiration. United States: N. p., 2019. Web. doi:10.1029/2018JG004628.
Liu, Yuchen, Lawrence, Corey R., Winnick, Matthew J., Hsu, Hsiao‐Tieh, Maher, Katharine, & Druhan, Jennifer L. Modeling Transient Soil Moisture Limitations on Microbial Carbon Respiration. United States. doi:10.1029/2018JG004628.
Liu, Yuchen, Lawrence, Corey R., Winnick, Matthew J., Hsu, Hsiao‐Tieh, Maher, Katharine, and Druhan, Jennifer L. Tue . "Modeling Transient Soil Moisture Limitations on Microbial Carbon Respiration". United States. doi:10.1029/2018JG004628.
@article{osti_1594055,
title = {Modeling Transient Soil Moisture Limitations on Microbial Carbon Respiration},
author = {Liu, Yuchen and Lawrence, Corey R. and Winnick, Matthew J. and Hsu, Hsiao‐Tieh and Maher, Katharine and Druhan, Jennifer L.},
abstractNote = {Soil microorganisms are known to survive periods of aridity and to recover rapidly after wetting events, with the ability to transition between a dormant state in dry conditions and an active state in wet conditions. While this dynamic behavior has been previously incorporated into soil carbon respiration modeling frameworks, a direct comparison between this active-dormant transition mechanism and a more simplified first-order model has yet to be made. Here, we demonstrate the necessary extent of model complexity needed to reproduce transient carbon respiration rates obtained from a set of soil incubation experiments implemented over a range of soil depths and time intervals. Two approaches are tested, one uses simplified first-order kinetics, whereas the other employs a transition between active and dormant biomass. The performance of each model is evaluated using an Akaike Information Criterion (AIC) based on the accuracy with which they reproduce an experimental dataset consisting of two sets of time series soil incubations collected across a range of time and depth resolutions. Based on the AIC evaluation and model-data comparison, we conclude that a dormancy-enabled model featuring two distinct microbial strategists performs best for the majority of the soil profile (above 108 cm) for both high and low depth resolution and sampling frequency, despite the added parameters required. In contrast, the first-order model achieves better AIC scores when simulating our deepest soils (112–165 cm), where moisture fluctuations are expected to be less prevalent. These findings guide how and where we choose to apply more cost intensive models.},
doi = {10.1029/2018JG004628},
journal = {Journal of Geophysical Research. Biogeosciences},
number = 7,
volume = 124,
place = {United States},
year = {2019},
month = {7}
}

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