inputs to the others. This procedure is necessarily iterative, where the 

 modeler serves as an interfacing mechanism. While it can be tedious, this 

 approach has the flexibility to allow the modeler's intuition to function freely. 

 Theoretically, if each subsystem model is well-calibrated, the interconnections 

 among them would match. 



Subsystems were defined so as to maximize internal interactions and 

 minimize connections with external variables (Simon 1973). The resulting Sub- 

 systems are (fig. 2): (1) the Autotrophs which compete for light and nutrients, 



(2) the Epibiota which inhabit leaf surfaces of the dominant autotroph (SAV), 



(3) the Water, with its suspended and dissolved substances, (4) the Benthos and 

 the sediments supporting them, (5) the Large Mobile Invertebrates, and (6) the 

 Nekton which feed on production from other subsystems. The sum of the state 

 variables contained in all 6 subsystem models is 45; however, 8 of these occur 

 in more than one subsystem. This redundancy of variables means that the state 

 spaces overlap, and it further insures consistency in the overall behavior of 

 the SAV ecosystem model and its subsystem simulations. It is apparent in figure 

 2 that the number of common variables (in shaded boxes) decrease away from the 

 Autotrophs, suggesting a reduction in the number of direct interactions among 

 variables at higher trophic levels. 



These models were designed to represent a unit area of water and sediment 

 in an SAV ecosystem with spatial averaging implied. Both carbon (C) and 

 nitrogen (N) are modeled in this scheme, where N is conserved within the model 

 during all transactions while C is transformed (with CO2 making the difference) 

 as needed according to prescribed C:N ratios for all biological state variables. 

 Flows of both C (and associated free energy) and N are crucial to the behavior 

 of this ecosystem. However, to include both with completely conserved materials 

 would require nearly twice the number of variables. Other chemical factors such 

 as oxygen and phosphorus are assumed to be nonlimiting to the ecosystem's 

 behavior, and those are thus omitted. Several previous modeling studies have 

 explicitly considered both C and N (e.g., Walsh 1975 a,b, Kremer and Nixon 1977, 

 Hopkinson and Day 1977, Najarian and Taft 1981). However, most ecosystem models 

 have been confined to tracing the flows of either carbon (energy) or nutrients 

 but not both (Najarian and Harleman 1977, Wetzel and Wiegert 1983). 



The mathematical structure of this model uses nonlinear, first-order 

 differential equations simulated by finite difference techniques. There is one 

 equation for each state variable, and each term in an equation represents an 

 interaction between variables. In the following two sections of this paper, 

 we report some salient aspects of two of these subsystem models, the Autotrophs 

 and the Nekton. These subsystems are at opposite ends of the ecological trophic 

 chain, one (Autotrophs) being more externally regulated (by Sunlight, nutrient 

 inputs, etc.), while nekton dynamics result more directly from production at 

 lower trophic levels. 



The Autotroph Subsystem Mode l 



A major objective in developing the Autotroph subsystem model was to 

 examine the consequence of changing patterns of turbidity, nutrients and grazing 

 on the competitive balance among the primary producers in an SAV community. 

 This model is depicted in figure 3, where phytoplankton, epiflora, SAV and 

 benthic micro-algae all compete for limited availabilities of light and 

 nutrients. Competition for light is direct via shading, while competition 



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