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Fishery Bulletin 92(2), 1994 



However, in this and other simulations, 

 the population density is consistently higher 

 after six years with the lower, more re- 

 stricted food supply associated with the 

 missing spring bloom (e.g. Fig. 7 vs. 9; Table 

 4). The effect occurs regardless of the size- 

 class distribution of mortality or the mortal- 

 ity rate. The initial surmise that more food 

 should result in higher densities is not con- 

 firmed. Reproductive effort is higher at the 

 higher food supply only in the first year (Fig. 

 7 vs. 9) and declines more rapidly thereaf- 

 ter as population density declines. Initially 

 this would appear to be counterintuitive; 

 more food should result in higher population 

 densities and greater reproductive effort. 

 However, increased food in the spring in- 

 creases growth rate so that more oysters 

 grow more rapidly into size classes suffering 

 mortality. As a result, the number of adults 

 and population reproductive potential de- 

 clines. This results in a lower population den- 

 sity. The model simulations indicate that oys- 

 ter population abundance is the result of a 

 complicated interplay between the timing of 

 food supply, reproductive effort, and mortality. 



Lowered recruitment success 



30 36 42 

 Julian Month 



10000 



8000 



B 



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I 4000H 



!■ 



2000  



„U_ — I 



12 3 4 5 6 

 Julian Year 



2345678910 

 Size Class 



An additional source of mortality for oyster 

 populations is through decreased survivor- 

 ship of the planktonic larvae (Table 5, Fig. 

 10). Lower larval survivorship results in decreased 

 recruitment success and lower population densities, 

 as expected. However, loss of the spring bloom en- 

 hances oyster population density as before (Table 5). 

 Nevertheless, a reduction in recruitment success, 

 when combined with mortality on the post-settle- 

 ment population, results in populations that are less 

 resistant to population crashes. For example, a ten- 

 fold reduction in recruitment success in a popula- 

 tion exposed to a 75% mortality rate in size classes 

 3 and larger produces the effect observed for a mor- 

 tality rate of 99.9% with an order of magnitude 

 higher recruitment success. 



One additional important concept arises from this 

 series of simulations. Simulations that included high 

 recruitment success and various mortality rates pro- 

 duced final size-frequency distributions similar to 

 those shown in Fig. 10, E and F. Few individuals are 

 found in size classes 5 and larger. The legal size for 

 the oyster fishery is typically size classes 6 and 

 larger. No fishery could exist under these conditions. 

 High population density produces stunted individu- 

 als. A reduction in recruitment success over a range 



Figure 7 



Simulated time development and population distribution of a 

 Galveston Bay Crassostrea virginica population exposed to a 

 continuous mortality rate of 99.9% restricted to size classes 3 

 and larger. (A) Monthly-averaged values of the number of in- 

 dividuals, the number of adults (j=4, 10), and the monthly re- 

 productive effort in kcal for the 6-year simulation. (B) The 

 yearly reproductive effort (number of kcal spawned). (C) The 

 final size class distribution in the population at day 2,160. 

 Further information in Figure 3 and Table 2, case 9. 



of mortality rates (Fig. 10, A-D) gives size-frequency 

 distributions shifted towards the larger size classes. 

 In fact, more market-sized animals exist in these 

 populations than in the ones shown in Figure 10, E 

 and F. Shifting mortality to lower size classes results 

 in even more market-size individuals (Fig. 10, 

 G-H). A successful fishery requires some degree of 

 mortality, including juvenile mortality. 



Effect of seasonal mortality 



The commercial oyster fishery is typically confined 

 to a winter season. In some cases, a restricted sum- 

 mer season is also allowed. Agents of natural mor- 

 tality, like Perkinsus marinus and Thais haema- 

 stoma, typically extract a greater toll during the 

 summer. The effect of mortality restricted to the 

 summer and to the winter is illustrated in Figures 

 11 and 12, respectively, and in Table 6. For this se- 

 ries of simulations, we define winter as the months 

 of October through March and summer as the 

 months of April through September. Thus each 

 simulated oyster population has the same number 



