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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 7, issue 4
Geosci. Model Dev., 7, 1519–1533, 2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 7, 1519–1533, 2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model experiment description paper 24 Jul 2014

Model experiment description paper | 24 Jul 2014

Comparing microbial and chemical kinetics for modelling soil organic carbon decomposition using the DecoChem v1.0 and DecoBio v1.0 models

G. Xenakis1,* and M. Williams1 G. Xenakis and M. Williams
  • 1School of GeoSciences, University of Edinburgh, Crew Building, The King's Buildings, West Mains Road, Edinburgh, Midlothian, EH9 3JN, UK
  • *now at: Forest Research, Northern Research Station, Roslin, Midlothian, EH25 9SY, UK

Abstract. Soil organic matter is a vast store of carbon, with a critical role in the global carbon cycle. Despite its importance, the dynamics of soil organic carbon decomposition, under the impact of climate change or changing litter inputs, are poorly understood. Current biogeochemical models usually lack microbial processes and thus miss an important feedback when considering the fate of carbon. Here we use a series of modelling experiments to evaluate two different model structures: one with a standard first-order kinetic representation of soil decomposition (DecoChem v1.0, hereafter chemical model) and one with control of soil decomposition through microbial activity (DecoBio v1.0, hereafter biological model). The biological model includes cycling of organic matter into and out of microbial biomass, and simulates the decay rate as a functional of microbial activity. We tested two hypotheses. First, we hypothesized different responses in the two models to increased litter inputs and glucose additions. In the microbial model we hypothesized that this perturbation would prime microbial activity and reduce soil carbon stocks; in the chemical model we expected this perturbation to increase C stocks. In the biological model, responses to changed litter quantity were more rapid, but with the residence time of soil C altering such that soil C stocks were buffered. However, in the biological model there was a strong response to increased glucose additions (i.e. changes in litter quality), with significant losses to soil C stocks over time, driven by priming. Secondly, we hypothesized that warming will stimulate decomposition in the chemical model and loss of C, but in the biological model soil C will be less sensitive to warming, due to complex microbial feedbacks. The numerical experiments supported this hypothesis, with the chemical model soil C residence times and steady-state C stocks adjusting strongly with temperature changes, extending over decades. On the other hand, the biological model showed a rapid response to temperature that subsided after a few years, with total soil C stocks largely unchanged. The microbial model shows qualitative agreement with experimental warming studies that found transient increases in soil respiration that decline within a few years. In conclusion, the biological model is largely buffered against bulk changes in litter inputs and climate, unlike the chemical model, while the biological model displays a strong priming response to additions of labile litter. Our results have therefore highlighted significantly different sensitivities between chemical and biological modelling approaches for soil decomposition.

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