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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-133
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-133
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: development and technical paper 02 Jul 2019

Submitted as: development and technical paper | 02 Jul 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

Dynamic upscaling of decomposition kinetics for carbon cycling models

Arjun Chakrawal1,2, Anke M. Herrmann3, Johannes Koestel3, Jerker Jarsjö1,2, Naoise Nunan4, Thomas Kätterer5, and Stefano Manzoni1,2 Arjun Chakrawal et al.
  • 1Department of Physical Geography, Stockholm University, Svante Arrhenius väg 8C, Frescati, SE-106 91 Stockholm, Sweden
  • 2Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
  • 3Department of Soil & Environment, Swedish University of Agricultural Sciences, P.O. Box 7014, 75007 Uppsala, Sweden
  • 4Institute of Ecology and Environmental Sciences - Paris, Sorbonne Universités, CNRS-IRD-INRA-P7-UPEC, 4 placeJussieu, 75005 Paris, France
  • 5Department of Ecology, Swedish University of Agricultural Sciences, P.O. Box 7014, 75007 Uppsala, Sweden

Abstract. The distribution of organic substrates and microorganism in soils is spatially heterogeneous at the micro-scale. Most soil carbon cycling models do not account for this micro-scale heterogeneity, which may affect predictions of carbon (C) fluxes and stocks. In this study, we hypothesize that the mean respiration rate R at the soil-core scale (i) is affected by the micro-scale spatial heterogeneity of substrate and microbes and (ii) depends upon the degree of this heterogeneity. To assess theoretically the effect of spatial heterogeneities on R, we contrast highly heterogeneous conditions with isolated patches of substrate and microbes versus spatially homogeneous conditions equivalent to those assumed in most soil C models. Moreover, we distinguish between biophysical heterogeneity, defined as the non-uniform spatial distribution of substrate and microbes, and full heterogeneity, defined as the non-uniform spatial distribution of substrate quality (or accessibility) in addition to biophysical heterogeneity.

Three commonly used formulations for decomposition kinetics (linear, multiplicative and Michaelis-Menten) are considered in a coupled substrate-microbial biomass model valid at the micro-scale. We start with a 2D domain characterized by a heterogeneous substrate distribution and numerically simulate organic matter dynamics at each cell in the domain. To interpret the mean behavior of this spatially-explicit system, we propose an analytical scale transition approach in which micro-scale heterogeneities affect R through the second order spatial moments (spatial variances and covariances).

It was not possible to capture the mean behavior of the heterogeneous system when the model assumed spatial homogeneity, because the second order moments cause the heterogeneous system to deviate from the behavior attained under homogeneous conditions. Consequently, R in the heterogeneous system can be higher or lower than the respiration of the homogeneous system, depending on the sign of the second order spatial moments. This effect of the spatial heterogeneities appears in the upscaled nonlinear decomposition formulations, whereas the upscaled linear decomposition model deviates from homogeneous conditions only when substrate quality is heterogeneous. Thus, this study highlights the inadequacy of applying at the macro-scale the same decomposition formulations valid at the micro-scale, and proposes a scale transition approach as a way forward to capture micro-scale dynamics in core-scale models.

Arjun Chakrawal et al.
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Arjun Chakrawal et al.
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Dynamic upscaling of decomposition kinetics for carbon cycling models: Heterogeneous_SOMDynamics A. Chakrawal https://doi.org/10.5281/zenodo.3253880

Arjun Chakrawal et al.
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Short summary
Soils are heterogeneous which results in a non-uniform spatial distribution of substrates as well as the microorganisms feeding on them. Our results show variability in the location of substrates and microorganisms at the pore scale is important because it affects how fast substrates are used by microorganisms and thus the decomposition rate observed at the larger scale. In conclusion, this work provides a methodology to explicitly include micro-scale heterogeneity in soil carbon cycling models.
Soils are heterogeneous which results in a non-uniform spatial distribution of substrates as...
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