Spatially Explicit Models of Striped Bass Growth Potential in Chesapeake Bay

Abstract

Fish growth rate potential is defined as the expected growth rate of a predator if placed in a particular volume of water having known physical and biological characteristics. We used the concept of fish growth rate potential to evaluate the seasonal and spatial growth patterns of striped bass Morone saxatilis across a midsection of the Chesapeake Bay. The growth rate potential of a 4-year-old (1.9-kg) striped bass was assessed by integrating spatially explicit field data on prey sizes, prey densities, and water temperature with a foraging model and a species-specific bioenergetics model offish growth rate, Prey sizes and densities were measured bimonthly at a high spatial resolution along a west–east transect of the bay with a 120-kHz dual-beam acoustic system. Along the transect, the water column was divided by columns and rows into a grid of cells 30 m long and 0.5 m deep. Growth and foraging models were implemented in each cell to calculate expected striped bass growth rate, Two-dimensional (horizontal, vertical) spatial maps of striped bass growth potential showed strong seasonal differences, even though overall prey biomass was similar from month to month, Striped bass growth rates were highest during October and nil during August. Mean growth rate potentials across the bay derived from the spatially explicit model were lower in all months than estimates generated with cross-bay, spatial averages of prey density. We argue that such spatially explicit modeling is necessary for directly linking biological function to physical and biological structure and for predicting how spatial patterning and absolute scaling of the habitat affect fish growth rates and production.