Volume 52
Regression Analysis of the Relationships Among Life Stage Abundances of Brown Shrimp, Penaeus aztecus, and Environmental Variables in Southern Louisiana, USA
Authors
Haas, H.L.; Shaw, R.F.; Rose, K.A.; Benfield, M.C.; Keithly Jr., W.R. Download PDF Open PDF in BrowserOther Information
Date: November, 1999
Pages: 231-241
Event: Proceedings of the Fifty Second Annual Gulf and Caribbean Fisheries Institute
City: Key West, Florida
Country: USA
Abstract
Brown shrimp (Penaeus aztecus Ives) landings in the Gulf of Mexico display substantial interannual variability. We used regression techniques to anaIyze relationships among Z7 years of postlarval, juvenile, and adult abundance estimates and a suite of environmental variables. Environmental variables included water temperature, salinity, turbidity, river flow rateo acres of suitable habitat, and precipitation. We used a combination of manual and stepwise model building procedures to develop annual models with offshore catch, late-juvenile, early-juvenile, and postlarval abundances as dependent variables. Environmental variables and preceding life history stages were exploratory variables. Commercial catch was described by late-juvenile abundance, water temperature, previous commercial catch, and river flow, The biological variables in the model explained 55% of the variability in offshore catch, whereas the environmental variables explained 24% of the variability. EnvilOnmental variables explained variation between each life history stage and were the only significant predictors of postlarval and juvenile abundance. The lack of biological links among early life history stages may result from envilOnmentally-driven, density-independent relationships or biologically-driven. nonlinear relationships. We are designing an individual-based simulation model of shrimp to further explore the relationships among their early life history stages. Both the regression and simulation models are ongoing efforts. We hope the combination of statistical and individual-based simulation modeling will provide further insight into the factors that affeet variability in brown shrimp recruitment.