Research Project Overview

Stochastic Synthesis: Simulating the Environmental Transformations of Natural Organic Matter
(Project Overview - slides)

Steve Cabaniss1, Jerry Leenheer2, Laura Leff3, Greg Madey4, Patricia Maurice4, Robert Wershaw2, Robert Wetzel5

University of New Mexico
(2) US Geological Survey (USGS), Denver
(3) Kent State University
(4) University of Notre Dame
(5) University of North Carolina - Chapel Hill

Natural organic matter (NOM) is a heterogeneous mixture of organic molecules found in terrestrial and aquatic environments - from forest soils and streams to coastal rivers and marshes to the open ocean.   NOM plays a vital role in ecological and biogeochemical processes, including chemical buffering, mineral dissolution/precipitation, photochemistry, and microbial nutrition.  The production of NOM from biological precursor compounds and its remineralization into CO2 are closely linked both to ecosystem function and to the global carbon cycle.  No current models of NOM production and evolution describe both the quantitative aspects of organic carbon transfer and the qualitative aspects of NOM structural and functional heterogeneity.  

This project consists of an interdisciplinary team of environmental (biology, chemistry, geology) and IT scientists that is developing a stochastic model for the time-dependent evolution of NOM in the environment. The scientific objectives are to produce both a new methodology and a specific program for predicting the properties of NOM over time as it evolves from precursor molecules to eventual mineralization.  The methodology being developed is a mechanistic, stochastic simulation of NOM transformations, including biological and non-biological reactions, as well as adsorption, aggregation and physical transport.  It employs recent advances in agent-based simulation, web-based deployment of scientific applications, a collaboratory for sharing simulations and data, and scalable web-based database management systems to improve the reliability of the stochastic simulations and to facilitate analysis of the resulting large datasets using datamining techniques.

The stochastic synthesis model of NOM evolution is being developed as a dialogue between coding and numerical testing on the one hand and environmental data-based testing on the other.  Initially, a simple model program was coded to simulate "steady state" transformations of NOM in a stable environment.  This program was made available to applications scientists in biology and geochemistry, who tested the behavior of the model for fidelity to laboratory data and field observation, and who directed the parameterization of the model and the inclusion or deletion of various molecular transformations (e.g., hydrolysis, photolysis, adsorption, microbial consumption, etc.).  The program is being modified as indicated by these tests, and additional code modules will be added to simulate NOM transport (in soil, ground or surface waters) and the response of the biological community.  We plan to make the Web-based simulation  available to external investigators.

This model has enormous potential benefits in a wide range of disciplines, since literally all aspects of biogeochemistry are related to NOM.  It will provide a testable mechanistic model of NOM development which can be applied to aquatic ecosystem studies, soil and crop science, environmental protection, remediation in the surface and sub-surface, and global climate change predictions.  Unlike current models, the project methodology explicitly treats NOM as a heterogeneous mixture, so that distributions of physical, chemical and biological properties can be predicted; this treatment will allow detailed, quantitative predictions of NOM structure and function and should provide considerable mechanistic insight.

The material presented at this web site is based in part upon work supported by the National Science Foundation, Information Technology Research/(ITR/AP-DEB), under Grant No. 0112820.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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