Synergism between research and simulation models of estuarine microbial food webs |
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Authors: | Robert R Christian Richard L Wetzel |
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Institution: | (1) Biology Department, East Carolina University, 27858 Greenville, North Carolina, USA;(2) Virginia Institute of Marine Sciences, College of William and Mary, 23064 Gloucester Point, Virginia, USA |
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Abstract: | Construction of mathematical simulation models helps to organize current information and extend inferences from available
data. During the past two decades, microbial ecology has undergone rapid developments in both quantity and quality of available
data. In particular, considerable advances have been made in our knowledge of microbial food web dynamics in the Duplin River
watershed at Sapelo Island, Georgia. Here we provide examples of how modeling and microbial ecology have interfaced. In the
early 1970s, construction of a 14-compartment model of carbon flow through a salt marsh ecosystem aided in directing method
development and field experiments on the sediment microbial community. In turn, the results of field experiments corroborated
the model's postulated controls on the community. Also, during the past 12 years we have developed a series of simulation
models reflecting the growing information on the aquatic microbial food web. Early models provided evidence for the microbial
loop but illustrated the paucity of knowledge concerning controls for bacterial growth on detritus. Results from newer methods
in microbial ecology and studies from the Duplin River have allowed us to construct a model which provides realistic simulations
but is also highly sensitive to certain parameter value changes (e.g., in organic matter availability and grazing by protozoans).
Thus improvements in model structure and corroboration of the models with extant data have been closely tied to methodological
and conceptual advances in microbial ecology. The relationship is viewed as synergistic, as needs for model parameter values
and equation forms have directed further development of methods, experimentation, and field observations. |
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