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Biogeosciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/bg-2018-10
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-2018-10
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 23 Jan 2018

Submitted as: research article | 23 Jan 2018

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This preprint has been withdrawn by the authors.

Modeling transient soil moisture limitations on microbial carbon respiration

Yuchen Liu1, Matthew J. Winnick2, Hsiao-Tieh Hsu2,3, Corey R. Lawrence4, Kate Maher2,5, and Jennifer L. Druhan1 Yuchen Liu et al.
  • 1Department of Geology, University of Illinois Urbana Champaign, Champaign IL 61820-6371, USA
  • 2Department of Geological Sciences, Stanford University, Stanford CA 94305-2115, USA
  • 3Department of Chemistry, Stanford University, Stanford, CA
  • 4United States Geological Survey, Denver
  • 5Rocky Mountain Biological Laboratory, PO Box 519, Crested Butte, CO 81224

Abstract. Observations show that soil microorganisms can survive periods of aridity and recover rapidly after wetting events. This behavior can be explained by a moisture-dependent adaptation (i.e. the ability to transition between a dormant state in dry conditions and an active state in wet conditions). Though this dynamic behavior has been previously incorporated into modeling frameworks, a direct comparison between a model application of this active-dormant transition mechanism and a more simplified first-order model has yet to be made. Here, we developed two models, one using simplified first-order kinetics and the other featuring a process-based rate expression incorporating the transition between active and dormant biomass. The two approaches are contrasted through a benchmarking exercise using a set of time series soil incubation datasets. We evaluated the two models using an Akaike Information Criterion (AIC). Combining the AIC evaluation and model-data comparison, we conclude that the dormancy-incorporated model performs better for shallow soils (above 108 cm), despite the added parameters required. In addition, this model is uniquely capable of reproducing transient CO2 flux rates associated with dynamic microbial response to changing soil moisture. In contrast, the first-order model achieves better AIC scores when simulating the incubation data obtained from our deepest soils (112–165 cm). However, deep soils constitute a minor contribution to the overall CO2 flux of an intact soil column. Thus, the dormancy-incorporated model may better simulate respiration of the whole soil.

This preprint has been withdrawn.
Yuchen Liu et al.
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Yuchen Liu et al.
Yuchen Liu et al.
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Short summary
Microbes naturally occur in soils and respire CO2, thus constituting a significant source of atmospheric greenhouse gases. We seek to improve predictions for the amount of CO2 emitted from soil by contrasting two models compared against lab measured respiration rates using natural soil samples at a range of soil moistures. Results show that a simplified model is more suitable for interpreting soil respiration rates below 100 cm, while a more complex approach is necessary for shallower depths.
Microbes naturally occur in soils and respire CO2, thus constituting a significant source of...
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