Sustainability of fisheries has been the main focus of fisheries managers. The estuarine-dependent spotted seatrout, Cynoscion nebulosus, is a popular recreational fish under state management. Texas Parks and Wildlife Department uses bag limits and stock enhancement to manage this fishery. Knowing the stock structure of these populations is critical to appropriate management. The purpose of this study was to use genetic techniques and otolith chemistry to describe any existing stock structure in spotted seatrout among Texas bays. Spotted seatrout are estuarine-dependent and appear to remain in or near their natal bays. Therefore, genetics and otolith chemistry should vary significantly among bays. DNA was extracted from pectoral fin clips of approximately 24 fish from each of nine bays. We genotyped each individual using 10 sets of microsatellite primers. We then estimated levels of genetic variation and its distribution among bays to determine stock structure. We also extracted sagittal otoliths and measured stable isotopic concentrations of δ13C and δ18O from five regions along the southern Texas coast. We then analyzed these data using discriminant function analysis to determine if bays have unique chemical signatures and to examine connectivity among these regions.
Results/Conclusions
Observed heterozygosity was high across all loci and all populations (Ho = 0.774, s. d. = 0.045). FST, which is a measure of the amount of variation among populations versus within populations, was 0.0868 (P = 0.000), indicating significant stock structure. However, an analysis of molecular variation (AMOVA) revealed that most of the variation in our samples (>75%) occurred within individuals. Discriminant function analysis of the stable isotope (δ13C and δ18O) concentrations in otoliths revealed that on average 64% of samples were assigned to the correct region. These classification patterns indicated that mixing most likely occurs between adjacent regions, which is consistent with the genetic analyses. Consequently, our two techniques suggest that fish from different bays represent different stocks with some connectivity between adjacent bays. These results indicate that managers should consider possible differences among bays with some connectivity between adjacent bays when setting regulatory policies for this fishery.
