PRED = k x Q 35 [log(L 1 + k 2 (Q3 5 /Q3 6 )] [exp k 3 T] (8) 



where T is temperature, L\ is related to minimal feeding rate for small organisms, 

 (Q35/Q35) is average size of predator, and k's are empirical coefficients. Similar 

 expressions are used for predation by juveniles but different prey items are 

 involved. Thus, both juvenile and adult feeding contribute to biomass (Q35), 

 allowing for ontogenic changes in diets (e.g., Carr and Adams 1973). 



Prey availability is defined as the product of prey biomas (Qfc), a poly- 

 nominal function of average prey size, f(Q b /Q n ), and a prey refuge function 

 created by SAV, 



PREY = k 4 Q b [f(Q b /Q n )] [L 2 + exp(-k 5 (Q p -L 3 ) ) ] (9) 



where L 2 is the maximum refuge offered, L3 is the lower threshold of plant bio- 

 mass (Qp) for incipient refuge effect, and where the availability function can- 

 not exceed unity. The polynominal function of average prey size exhibits a 

 broad central region (20-180% of mean prey size) with reduced availability when 

 prey become very small or very large. Other details of model formulation are 

 described in Kemp et al., (1981). 



The general behavior of this model is indicated in the calibration simulation 

 presented in figure 6. Simulated time-course of benthic infaunal biomass follows 

 field observations reasonably close, both in magnitude and timing, although the 

 model shows a slower winter-spring growth in the community than the data would 

 indicate. At this preliminary stage of model development, we can only say that 

 model output is in the right order-of-magnitude , and that certain temporal trends 

 such as abundance of Resident and juvenile Schooling Fish are reasonably consis- 

 tent with data. Seasonal patterns of biomass are generally skewed too far into 

 the autumn, probably due to problems in the emigration subroutines. Ultimately, 

 it is hoped that this model will help us to understand the way in which compet- 

 itive shifts among the autotrophic groups influence the relative balance in 

 fish abundance among the 3 groups (fig. 5) which are well down the trophic 

 chain from those primary producers. Model simulations can be used to distin- 

 guish the relative importance of habitat (e.g., predatory refuge) versus primary 

 food production in leading to these effects, while such a distinction could 

 not easily be made through field experimentation. 



RESOURCE MANAGEMENT MODELING 



Management Modeling Framework 



Parallel to the detailed ecosystem modeling, we developed a system of 

 resource management models for focusing on the multiple interactions of human 

 activities with resource ecosystems. In general this modeling effort was de- 

 signed to assist in utilizing scientific knowledge towards balanced and productive 

 management of Chesapeake Bay resources. In contrast to the detailed ecosystem 

 models, this research was intended to assess both the relative importance of 

 factors contributing to the decline in SAV abundance, and the consequences of 

 this decline (in terms of such factors as fish production). The modeling 



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