In comparison to ecology on a macroscopic level, microbial ecology is a relatively underdeveloped field. In particular, there have been few attempts to model microbial communities and their dynamic behavior in response to changes in meteorological, physical, and chemical conditions (ecosystem state variables). Predictions from simulations could help shape effective environmental policies and management decisions related to ecosystem functions controlled by microbial processes. For this study, previously collected data from a humic lake (bog) in northern Wisconsin over the summer of 2003 were used to develop STELLA models that relate microbial community characteristics to environmental conditions. The data set includes abundance and composition of bacterial, phytoplankton, and zooplankton communities, as well as chemical, physical, and meteorological data for each site. Three model examples were developed using different network structures and dynamics. Constants for the first two were solved for, and the third is in progress. The success of these models is discussed here. We plan to validate the model from its simulation of community composition over subsequent years, and we anticipate that it will be able to predict the microbial community dynamics for a lake over a summer period, given initial composition, chemical and physical data of the lake and meteorological data of the region.

Original languageEnglish (US)
StatePublished - 2007
Event2007 ASABE Annual International Meeting, Technical Papers - Minneapolis, MN, United States
Duration: Jun 17 2007Jun 20 2007


Conference2007 ASABE Annual International Meeting, Technical Papers
Country/TerritoryUnited States
CityMinneapolis, MN


  • Humic lake
  • Microbial ecology
  • Modeling

ASJC Scopus subject areas

  • General Agricultural and Biological Sciences
  • General Engineering


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