Technical ArticleIndividual-Based Modeling of Carbon and Nitrogen Dynamics in Soils: Parameterization and Sensitivity Analysis of Abiotic ComponentsGras, Anna1; Ginovart, Marta2; Portell, Xavier1; Baveye, Philippe C.3Author Information 1Department of Agri-Food Engineering and Biotechnology, Universitat Politècnica de Catalunya, Campus Baix Llobregat, Esteve Terrades 8, 08860 Castelldefels, Barcelona, Spain. Dr. Anna Gras is corresponding author. E-mail: [email protected] 2Department of Applied Mathematics III, Universitat Politècnica de Catalunya, Campus Baix Llobregat, Castelldefels, Barcelona, Spain. 3SIMBIOS Centre, Abertay University, Dundee, United Kingdom. Received February 10, 2010. Accepted for publication June 17, 2010. Soil Science: August 2010 - Volume 175 - Issue 8 - p 363-374 doi: 10.1097/SS.0b013e3181eda507 Buy SDC Metrics Abstract The need to predict with reasonable accuracy the fate of soil C and N compounds in soils in response to climate change is stimulating interest in a new generation of microscale models of soil ecosystem processes. Essential to the development of such models is the ability to describe the growth and metabolism of small numbers of individual microorganisms. In this context, the key objective of the research described in this article was to further develop an individual-based soil organic matter (SOM) model, INDISIM-SOM, first proposed a few years ago, and to assess its performance with a broader data set than previously considered. The INDISIM-SOM models the dynamics and evolution of C and N associated with organic matter in soils. The model involves a number of state variables and parameters related to SOM and microbial activity, including growth and decay of microbial biomass, temporal evolution of mineralized intermediate C and N, mineral N in ammonium and nitrate, carbon dioxide, and O2. Simulation results demonstrate good fit of the model to experimental data from laboratory incubation experiments performed on three different types of Mediterranean soils. A second objective was to determine the sensitivity of the model toward its various parameters. Sensitivity was small for several of the parameters, suggesting possible simplifications of the model for specific uses, but was significant particularly for the parameter associated with the fraction of the soil C present in the biomass. These results suggest that research should be focused on improving the measurement of this latter parameter. © 2010 Lippincott Williams & Wilkins, Inc.