Abstract--A density prediction model for juvenile brown shrimp (Farfantepenaeus aztecus) was developed by using three bottom types, five salinity zones, and four seasons to quantify patterns of habitat use in Galveston Bay, Texas. Sixteen years of quantitative density data were used. Bottom types were vegetated marsh edge, submerged aquatic vegetation, and shallow non-vegetated bottom. Multiple regression was used to develop density estimates, and the resultant formula was then ...
<100 mm) in shallow water habitats within the bay of approximately 1.3 billion. Furthermore, the geographic range of the model was assessed by plotting observed (actual) versus expected (model) brown shrimp densities in three other Texas bays. Similar habitat-use patterns were observed in all three bays--each having a coefficient of determination>
<50 mm TL) are likely to inhabit deeper bay waters; density estimates of small nekton, including shrimp, decline rapidly with depth (Mock, 1966; Baltz et al., 1993; Rozas, 1993; Rozas and Zimmerman, 2000). In addition, these CPUE values are likely underestimates of brown shrimp density; catch efficiency for shrimp in trawls can be roughly estimated at 20% (Zimmerman et al., 1984; Rozas and Minello, 1997). Despite these problems, shrimp abundance estimates in water>
<0.05.
Mean
[r. Observations square
Model fit sup.2] Mean (n) error
0.73 0.47 47 0.20
ANOVA
Sum of
Source df squares Mean square F ratio Prob><0.0001 *
Effects
Sum of
Source df squares F ratio Prob><0.0001 *
Bottom type x
Salinity zone 8 0.86 2.69 0.0242 *
Table 2
Variable coefficients (log +1) derived from brown shrimp
multivariate regression model. ME = marsh edge; SAV =
submerged aquatic vegetation; SNB = shallow nonvegetated bottom.
y-intercept Bottom type Season Salinity zone
0.335 0.113 (ME) 0.239 (spring) -0.525 (0-0.5)
0.043 (SAV) 0.165 (summer) -0.147 (0.5-5)
-0.156 (SNB) -0.045 (fall) 0.079 (5-15)
-0.359 (winter) 0.286 (15-25)
0.307 (>