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Year of publication:
Decomposition Model of Enzymatic Traits (DEMENT)

Steven D. Allison, University of California Irvine

Department of Ecology and Evolutionary Biology

Department of Earth System Science





DEMENT uses microbial trait values and correlations to predict rates of organic matter decomposition. The most recent model version represents traits related to enzyme kinetics, enzyme production, growth efficiency, stoichiometry, and responses to moisture availability. During a model run, a large number (>100) of bacterial and fungal taxa are allowed to compete on a spatial grid representing the surface of decomposing organic material. Each taxon possesses a suite of physiological traits that are assigned based on trait correlations. Enzymes produced by the microbial taxa interact locally with substrates to generate monomers that are available for uptake. The model predicts microbial community composition by simulating the abundances of the initial taxa at a daily time step. Enzymatic degradation is a Michaelis-Menten process with Arrhenius temperature sensitivity functions built into Vmax and Km kinetic parameters.


Screen shots


Scientific articles

Allison, S. D. 2012. A trait-based approach for modelling microbial litter decomposition. Ecology Letters 15:1058–1070.

Allison, S. D. 2014. Modeling adaptation of carbon use efficiency in microbial communities. Frontiers in Microbiology 5:571.


Technical information

Operating system(s): All (coded in R)

Licence: Open source

Output(s): R workspace and png image files of microbial pools, substrate pools, enzyme pools, and respiration

Export format(s): R workspace, png

Other information: Contact Steven Allison for code

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