There is an underlying assumption in much of ecology, and perhaps science in general, that one learns about nature by isolating successively smaller parts for detailed measurement and study. This reductionism is implicit in a vast and growing literature devoted to the description of rates and responses of a variety of organisms under controlled laboratory conditions. While some of this work is done for the purpose of studying physiological processes per se, a great deal of it is undertaken in the hope that the results will reveal something about the role of the organism or species in nature. However, it is extremely difficult to perceive intuitively the consequences of any set of values in a complex, dynamic ecosystem with subtle feedback controls. One approach to this problem has led to the development of numerical simulation models, which can serve as powerful synthetic tools with which to assess quantitatively the consequences and consistency of complex sets of hypotheses. Such models may differ widely with respect to the processes and environments they are designed to represent, but in general all follow a similar developmental process and are all based on the same historical conception.
KeywordsStanding Crop Ecosystem Model Phytoplankton Population Spatial Element Atlantic Menhaden
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