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A bunch of tiny individuals—Individual-based modeling for microbes
Authors:Ferdi L Hellweger  Vanni Bucci
Institution:Civil and Environmental Engineering Department, 400 Snell Engineering Center, Northeastern University, Boston, MA 02115, USA
Abstract:The individual-based (aka agent-based) approach is now well established in ecological modeling. Traditionally, most applications have been to organisms at higher trophic levels, where the importance of population heterogeneity (intra-population variability), complete life cycles and behavior adapted to internal and external conditions has been recognized for some time. However, advances in molecular biology and biochemistry have brought about an increase in the application of individual-based modeling (IBM) to microbes as well. This literature review summarizes 46 IBM papers for bacteria in wastewater treatment plants, phytoplankton in ocean and inland waters, bacteria in biofilms, bacteria in food and other environs, and “digital organisms” and “domesticated computer viruses” in silico. The use of IBM in these applications was motivated by population heterogeneity (45%), emergence (24%), absence of a continuum (5%), and other unknown reasons (26%). In general, the challenges and concepts of IBM modeling for microbes and higher trophic levels are similar. However, there are differences in the microbe population dynamics and their environment that create somewhat different challenges, which have led to somewhat different modeling concepts. Several topics are discussed, including producing, maintaining and changing population heterogeneity (different life histories, internal variability, positive feedback, inter-generation memory), dealing with very large numbers of individuals (different up-scaling methods, including representative space vs. super-individual, number vs. biomass based, discrete vs. continuous kinetics, various agent accounting methods), handling space, simulating interactions with the extracellular environment (hybrid Eulerian–Lagrangian approach), modeling agent–agent interaction (self-shading, predation, shoving) and passive transport (random walk with spatially variable diffusivity, well-mixed reactors). Overall, the literature indicates that the application of IBM to microbes is developing into a mature field. However, several challenges remain, including simulating various types of agent–agent interactions (formation and function of colonies or filaments, sexual reproduction) and even smaller individuals (viruses, genes). Further increases in intracellular detail and complexity in microbe IBMs may be considered the combination of systems biology and systems ecology, or the new field of systems bioecology.
Keywords:Agent-based modeling  Individual-based modeling  Systems ecology  Intra-population variability  Population heterogeneity  Emergence  Continuum  Microorganisms  Microbes  Bacteria  Phytoplankton
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