DEMENT
Steven D. Allison, University of California Irvine
Department of Ecology and Evolutionary Biology
Department of Earth System Science
Website
Description
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
