PS 50-98 - Genetic stock structure of spotted seatrout, Cynoscion nebulosus, populations in the western Gulf of Mexico

Wednesday, August 5, 2009
Exhibit Hall NE & SE, Albuquerque Convention Center
Courtney T. Lee, Texas A&M-Galveston, Galveston, TX, Cynthia Morales, Life Sciences, Texas A&M-Corpus Christi, Corpus Christi, TX, Gregory W. Stunz, Harte Research Institute for Gulf of Mexico Studies, Texas A&M University-Corpus Christi, Corpus Christi, TX, Robert Vega, GCCA/CPL Marine Development Center, Texas Parks and Wildlife Department, Corpus Christi, TX and R. Deborah Overath, Texas A&M University - Corpus Christi, Corpus Christi, TX
Background/Question/Methods

Sustainability of fisheries, especially recreationally and economically important fishes, has been the main focus of fisheries management along the Gulf of Mexico. The estuarine-dependent spotted seatrout, Cynoscion nebulosus, is a popular recreational fish and a bioindicator for estuaries. In Texas the Texas Parks and Wildlife Department manages this fishery and stocks juvenile fishes in Texas bays. Knowing the stock structure of these populations is important for appropriately managing these populations. The purpose of this study is to describe the stock structure of spotted seatrout among Texas bays using genetic analysis. We hypothesize that since spotted seatrout are estuarine-dependent and appear to remain in or near their natal bays, genetic differences among populations should be significant. We extracted from approximately 24 pectoral fins from each of eight populations. We genotyped each individual using microsatellite primers developed conjunction with the Texas Parks and Wildlife Department.

Results/Conclusions

We used ARLEQUIN 3.1 to analyze genetic variation and its distribution across populations to uncover stock structure. Observed heterozygosity is high (Ho = 0.819) across all loci and all populations. FST, which is a measure of the amount of variation among populations versus within populations, was 0.126 (P = 0.004) indicating significant stock structure. However, an analysis of molecular variation (AMOVA) indicated that most of the variation in our samples (>70%) occurred within individuals within bays. These data indicate that managers should take into account possible differences among bays when setting policies for this fishery.

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