Peters and Chigbu: Abundance of juvenile Centropristis striata in Maryland coastal bays 
513 
-1.0 -0.5 0.0 0.5 
log(Predicted values) 
Figure 8 
Diagnostic plot for the generalized linear model with the lowest Akaike 
information criterion (residuals versus log-transformed predicted val¬ 
ues). This model was chosen as the best indicator for predicting re¬ 
cruitment of black sea bass (Centropristis striata) in the Maryland 
coastal bays. 
Year 
Figure 9 
Observed and predicted values of catch of black sea bass (Centropristis 
striata ) recorded during Maryland Department of Natural Resources 
surveys from the generalized linear model with a Poisson distribution 
and the lowest Akaike information criterion (age-0 catch ~ salinity + 
annual North Atlantic Oscillation index). A chi-square goodness of fit 
test (P=0.166) revealed no significant difference between the observed 
and predicted values. 
why the highest abundance of black sea bass occurred 
in the southernmost site in May in this study. 
Catch per unit of effort of black sea bass corre¬ 
lated with water depth, but not with temperature or 
dissolved oxygen. In the MCBs, there were not much 
within-season spatial differences in temperature and 
dissolved oxygen, which perhaps explains why the 
spatial distribution of juvenile black sea bass was not 
correlated with the environmental factors. In New Jer¬ 
sey estuaries, black sea bass were found 
in the deeper area of estuaries (>2 m), 
not the shallower parts (<1 m) (Able and 
Hales, 1997). The depth at each site in 
the MCBs ranged from 0.90 to 2.88 m. 
Low CPUE occurred at depths of 0.50- 
1.00 m and high CPUE at sites with 
depths greater than 2 m. Results from 
this study and past studies suggest ju¬ 
venile black sea bass prefer deeper areas 
of estuaries. 
Black sea bass were more abundant in 
Assawoman, Isle of Wight, and Sinepuxent 
Bays than in Newport Bay and the central 
part of Chincoteague Bay. Because abiotic 
factors measured did not show much cor¬ 
relation with the abundance of black sea 
bass, other factors, such as proximity to 
the inlets through which the black sea 
bass enter and leave the bays and avail¬ 
ability of physical structure in the bays, 
are likely the reasons for differences in 
abundance between sites sampled in the 
survey. Able et al. (1995) found that black 
sea bass were more abundant in habitats 
with sand and shell bottoms, and in areas 
where amphipod tubes were abundant. A 
study that examined the effects of oys¬ 
ter shell planting on fish abundance in 
the Chincoteague Bay found that catch 
rates of black sea bass increased when 
shells were added (Arve, 1960). Because 
black sea bass are a structure-oriented 
species, their distribution may be affected 
by the presence and amount of available 
structured habitat; however, there is cur¬ 
rently little information on the distribu¬ 
tion of structured benthic habitats in the 
MCBs. The only known information on 
benthic cover is that seagrasses are more 
abundant on the eastern than the west¬ 
ern half of the bays, macroalgae are more 
abundant in the northern than southern 
bays (Morales-Nunez and Chigbu, 2016), 
and oyster shells and beds are scarce. In 
other estuaries, juvenile black sea bass 
are rarely seen over nonvegetated sandy 
areas (Allen et al., 1978), but are com¬ 
monly seen in areas of high shell density 
and structured habitats, such as wharves, 
oyster reefs, and rock reefs (Drohan et 
al., 2007). 
The growth rate of black sea bass from May un¬ 
til September was determined to be 0.58 mm TL/day. 
There was no significant correlation between growth 
rate each year and the average temperature and abun¬ 
dance of black sea bass for those years; however, the 
numbers of fish caught in the trawls were low and this 
might have been responsible for the lack of significant 
correlations. Previous studies using a mark-recapture 
