356 



Fishery Bulletin 92(2). 1994 



.o 



E 



z 



100000 



10000 



1000 



100 



10 



50000 



40000 



" 30000 



S 20000 



10000 



2A), one winter is colder and one summer 

 warmer than the other. As a result, the 

 first year in each pair is characterized by 

 lower reproductive effort as decreased 

 temperatures reduce filtration and inges- 

 tion rate and switch net production to- 

 wards somatic growth. Warmer tempera- 

 tures the second year result in a larger 

 reproductive effort. 



Within these simulated oyster popula- 

 tions, a complex interaction exists be- 

 tween population density, size frequency, 

 and mortality rate. Increasing mortality 

 removes individuals, thereby increasing 

 the available food supply for the remain- 

 ing individuals. Increased food supply 

 results in increased spawning effort, 

 which then increases population density. 

 This in turn then gives reduced spawning 

 effort. This feedback results in potential 

 population equilibria of different densities 

 and size frequencies for each level of mor- 

 tality (Table 3). Even at 99.9% yearly 

 mortality, however, the population sus- 

 tains itself at a fairly dense level. Of more 

 significance, each population approaches 

 an equilibrium or nearly so, such that 

 recruitment balances mortality over this 

 range of mortality rates. Year-to-year 

 shifts in population size over the 6-year 

 simulation show neither continually 

 strong declines nor increases in popula- 

 tion density for any of the mortality rates. 



In Figures 6—8, we compare the time-development 

 of oyster populations exposed to similar overall 

 mortality levels, but in which mortality extends into 

 lower size classes than in Figures 4 and 5. In these 

 simulations, mortality was imposed either on all 

 adult sizes and the larger juveniles (Figs. 6 and 7) 

 or on all size classes (Fig. 8). Figures 7 and 5 differ 

 only in the size classes exposed to mortality (5 and 

 larger vs. 3 and larger) as do Figures 6 and 8 (3 and 

 larger vs. 1 and larger). As high (90-99.9%) yearly 

 mortality rates are imposed on smaller oyster size 

 classes (Figs. 6-8), the population becomes more 

 susceptible to significant population declines. For 

 example, a 99.9% yearly mortality rate had little 

 effect when mortality was restricted to size classes 

 5 and larger (Fig. 5), but results in a population 

 crash if size classes 3 and larger are similarly ex- 

 posed (Fig. 7). Many more individuals die before 

 reproducing in the latter case than in the former. A 

 mortality rate of 99.9% is required for a population 

 crash at size classes 3 and larger (Fig. 7), but only 

 99' ! at size class 1 and larger (Fig. 8). As mortality 



Number of Individual* 

 Mortality (no/month) 



40000 



30000 



20000 3 



10000 



12 18 24 



30 36 42 

 Julian Month 



48 54 60 66 72 



2 3 4 5 

 Julian Year 



23456789 10 

 Size Class 



Figure 4 



Simulated time development and population distribution of a 

 Galveston Bay Crassostrea virginica population exposed to a con- 

 tinuous mortality rate of 50% per year on size classes 5 and larger. 

 (A) Monthly averaged values of the number of individuals, the 

 number of adults (j=4, 10), and the monthly reproductive effort 

 in kcal for the 6-year simulation. (B) The yearly reproductive ef- 

 fort (number of kcal spawned). (C) The final size class distribu- 

 tion in the population at day 2,160. Further explanation in Fig- 

 ure 3 and Table 2, case 2. 



extends into the smaller size classes, the mortality 

 rate that the population can sustain decreases. We 

 note that, although these mortality rates seem high, 

 they are well within the typical range for juvenile 

 survivorship in bivalve communities (e.g. Powell et 

 al., 1984; Cummins et al., 1986). 



