7-6 Using a combination genetic markers and otolith chemistry to examine connectivity issues and management implications for spotted seatrout

Monday, September 13, 2010: 3:20 PM
403 (Convention Center)
R. Deborah Overath, PhD , Life Sciences, Texas A&M University -- Corpus Christi, Corpus Christi, TX
John T. Froeschke , Life Sciences/Harte Research Institute for Gulf of Mexico Studies, Texas A&M University -- Corpus Christi, Corpus Christi, TX
Cynthia Morales , Life Sciences, Texas A&M University -- Corpus Christi, Corpus Christi, TX
Kenneth C. Rainer , Life Sciences, Texas A&M University -- Corpus Christi, Corpus Christi, TX
Gregory W. Stunz, PhD , Life Sciences/Harte Research Institute for Gulf of Mexico Studies, Texas A&M University -- Corpus Christi, Corpus Christi, TX
Ivonne Blandon , GCCA/CPL Marine Development Center, Texas Parks and Wildlife Department, Corpus Christi, TX
Robert R. Vega, PhD , GCCA/CPL Marine Development Center, Texas Parks and Wildlife Department, Corpus Christi, TX
Regional declines of spotted seatrout stocks along the south Texas coast have prompted concerns about population connectivity among management regions.  Understanding connectivity will improve effectiveness of a recently implemented regional management strategy.  We investigated connectivity in five areas in south Texas by examining genetic variation in two genetic markers (10 microsatellite loci and ND4 sequence) and concentrations of two stable isotopes (δ13C and δ18O) in otoliths.  We collected adults from multiple locations within each region.  Analysis of molecular variance was used to assess genetic differentiation among regions as one measure of population connectivity.  We also quantified otolith d13C and d18O values to determine if region specific tags could be indentified and to assess the degree of mixing among regions.  Analysis of microsatellite data revealed significant population structure (FST = 0.04, P = 0.02); however, ND4 did not differentiate these five regions (FST = 0, P = 0.467).  Discriminant function analysis of stable isotope concentrations revealed that on average 64% of samples were assigned to the correct region.  Our results suggest that mixing is most likely between adjacent regions; however, long-distance migrations may occur; therefore, demographic connectivity, including mixing rates among regions, should be considered as part of management decisions.