Earth and Atmospheric Sciences, Department of



Leilani Arthurs

Date of this Version

Spring 2006


Published in Natural Resource Modeling 19:1 (Spring 2006), pp. 67–90. Copyright © 2006 Rocky Mountain Mathematics Consortium; published by Wiley-Blackwell. Used by permission.


Natural organic matter (NOM) is ubiquitous in terrestrial and aquatic ecosystems, and it plays a crucial role in the evolution of soils, the transport of pollutants, and the global carbon cycle. NOM is a complex mixture of molecules and is thus heterogeneous in structure and composition. As NOM passes through an ecosystem, it is acted upon by a variety of processes, such as microbial degradation, adsorption to mineral surfaces, and photochemical reactions that can change its properties and reactivity. The evolution of NOM in space and time thus is an important research area in biology, geochemistry, ecology, soil science, and water resources. Due to its complex structural and chemical heterogeneity, new simulation approaches are needed to help better understand the evolution of NOM properties and reactivity as it passes through an ecosystem. We present a new stochastic model, which explicitly treats NOM as a large number of discrete heterogeneous molecules (“agents”) with different probabilities of transformations or reactions. The NOM, the microorganisms, and their environment are taken together as a complex system, with the NOM interactions within this system simulated using an agent-based stochastic modeling approach. The initial users of the NOM simulations include a geographically separated group of NSF-sponsored scientists and engineers from different research disciplines, including both academics and U.S. government scientists. A Web-based interface serves as a prototype NOM “collaboratory” designed to promote collaboration among the various researchers and to allow them to share their data, model results, and suggested approaches or improvements across distributed sites. This Web-based interface has been designed to allow researchers to access the simulation model remotely from a standard Web browser. The Web-based interface thus allows researchers at distant locations to provide parameters for their simulations, to start and stop simulations, and to plot and view results, all remotely.