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Title: Responses of two nonlinear microbial models to warming and increased carbon input

Abstract

A number of nonlinear microbial models of soil carbon decomposition have been developed. Some of them have been applied globally but have yet to be shown to realistically represent soil carbon dynamics in the field. A thorough analysis of their key differences is needed to inform future model developments. In this paper, we compare two nonlinear microbial models of soil carbon decomposition: one based on reverse Michaelis–Menten kinetics (model A) and the other on regular Michaelis–Menten kinetics (model B). Using analytic approximations and numerical solutions, we find that the oscillatory responses of carbon pools to a small perturbation in their initial pool sizes dampen faster in model A than in model B. Soil warming always decreases carbon storage in model A, but in model B it predominantly decreases carbon storage in cool regions and increases carbon storage in warm regions. For both models, the CO 2 efflux from soil carbon decomposition reaches a maximum value some time after increased carbon input (as in priming experiments). This maximum CO 2 efflux (F max) decreases with an increase in soil temperature in both models. However, the sensitivity of F max to the increased amount of carbon input increases with soil temperature inmore » model A but decreases monotonically with an increase in soil temperature in model B. These differences in the responses to soil warming and carbon input between the two nonlinear models can be used to discern which model is more realistic when compared to results from field or laboratory experiments. Lastly, these insights will contribute to an improved understanding of the significance of soil microbial processes in soil carbon responses to future climate change.« less

Authors:
 [1];  [2];  [3];  [4];  [5]; ORCiD logo [6];  [7];  [8]; ORCiD logo [9];  [10];  [11];  [11]
  1. CSIRO Ocean and Atmosphere (Australia)
  2. Univ. of Tennessee, Knoxville, TN (United States). Department of Ecology and Evolutionary Biology
  3. Univ. of Texas, Arlington, TX (United States). Department of Mathematics
  4. Austin Peay State University, Clarksville, TN (United States). Department of Mathematics and Statistics
  5. Univ. of California, Davis, CA (United States). Department of Environmental Science and Policy
  6. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computational Earth Sciences Group
  7. Imperial College, London (United Kingdom). Department of Mathematics
  8. Microsoft Research, Cambridge (United Kingdom). Computational Science Laboratory
  9. Univ. of Oklahoma, Norman, OK (United States). Department of Microbiology and Plant Biology; Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  10. Univ. of Oklahoma, Norman, OK (United States). Department of Mathematics
  11. Univ. of Oklahoma, Norman, OK (United States). Department of Microbiology and Plant Biology
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1327618
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Biogeosciences (Online)
Additional Journal Information:
Journal Name: Biogeosciences (Online); Journal Volume: 13; Journal Issue: 4; Journal ID: ISSN 1726-4189
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 58 GEOSCIENCES

Citation Formats

Wang, Y. P., Jiang, J., Chen-Charpentier, Benito, Agusto, Fola B., Hastings, Alan, Hoffman, Forrest M., Rasmussen, Martin, Smith, Matthew J., Todd-Brown, Katherine E., Wang, Y., Xu, X., and Luo, Y. Q. Responses of two nonlinear microbial models to warming and increased carbon input. United States: N. p., 2016. Web. doi:10.5194/bg-13-887-2016.
Wang, Y. P., Jiang, J., Chen-Charpentier, Benito, Agusto, Fola B., Hastings, Alan, Hoffman, Forrest M., Rasmussen, Martin, Smith, Matthew J., Todd-Brown, Katherine E., Wang, Y., Xu, X., & Luo, Y. Q. Responses of two nonlinear microbial models to warming and increased carbon input. United States. doi:10.5194/bg-13-887-2016.
Wang, Y. P., Jiang, J., Chen-Charpentier, Benito, Agusto, Fola B., Hastings, Alan, Hoffman, Forrest M., Rasmussen, Martin, Smith, Matthew J., Todd-Brown, Katherine E., Wang, Y., Xu, X., and Luo, Y. Q. Thu . "Responses of two nonlinear microbial models to warming and increased carbon input". United States. doi:10.5194/bg-13-887-2016. https://www.osti.gov/servlets/purl/1327618.
@article{osti_1327618,
title = {Responses of two nonlinear microbial models to warming and increased carbon input},
author = {Wang, Y. P. and Jiang, J. and Chen-Charpentier, Benito and Agusto, Fola B. and Hastings, Alan and Hoffman, Forrest M. and Rasmussen, Martin and Smith, Matthew J. and Todd-Brown, Katherine E. and Wang, Y. and Xu, X. and Luo, Y. Q.},
abstractNote = {A number of nonlinear microbial models of soil carbon decomposition have been developed. Some of them have been applied globally but have yet to be shown to realistically represent soil carbon dynamics in the field. A thorough analysis of their key differences is needed to inform future model developments. In this paper, we compare two nonlinear microbial models of soil carbon decomposition: one based on reverse Michaelis–Menten kinetics (model A) and the other on regular Michaelis–Menten kinetics (model B). Using analytic approximations and numerical solutions, we find that the oscillatory responses of carbon pools to a small perturbation in their initial pool sizes dampen faster in model A than in model B. Soil warming always decreases carbon storage in model A, but in model B it predominantly decreases carbon storage in cool regions and increases carbon storage in warm regions. For both models, the CO2 efflux from soil carbon decomposition reaches a maximum value some time after increased carbon input (as in priming experiments). This maximum CO2 efflux (Fmax) decreases with an increase in soil temperature in both models. However, the sensitivity of Fmax to the increased amount of carbon input increases with soil temperature in model A but decreases monotonically with an increase in soil temperature in model B. These differences in the responses to soil warming and carbon input between the two nonlinear models can be used to discern which model is more realistic when compared to results from field or laboratory experiments. Lastly, these insights will contribute to an improved understanding of the significance of soil microbial processes in soil carbon responses to future climate change.},
doi = {10.5194/bg-13-887-2016},
journal = {Biogeosciences (Online)},
number = 4,
volume = 13,
place = {United States},
year = {2016},
month = {2}
}

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    Works referencing / citing this record:

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