Th-BA-22
Spatial and Temporal Patterns Of The U.S. East Coast Nearshore Fish Assemblage From Florida To New York

Thursday, September 12, 2013: 3:40 PM
Marriott Ballroom A (The Marriott Little Rock)
Mark Stratton , Department of Fisheries Science, Virginia Institute of Marine Science, Gloucester Point, VA
Christopher F. Bonzek , Dept. of Fisheries Science, Virginia Institute of Marine Science, Gloucester Point, VA
Jeanne Boylan , Marine Resources Research Institute, South Carolina Department of Natural Resources, Charleston, SC
James Gartland , Dept. of Fisheries Science, Virginia Institute of Marine Science, Gloucester Point, VA
Marcel Reichert , South Carolina Department of Natural Resources, Charleston, SC
Pearse Webster , Marine Resources Research Institute, South Carolina Department of Natural Resources, Charleston, SC
Robert J. Latour , Dept. of Fisheries Science, Virginia Institute of Marine Science, Gloucester Point, VA
Understanding fish stock and community patterns across broad ecological gradients and between management zones requires a comparative approach integrating data from multiple sources. This study utilizes data from two fishery-independent bottom trawl surveys, the Northeast Area Monitoring and Assessment Program (NEAMAP) and the Southeast Area Monitoring and Assessment Program – U.S. South Atlantic (SEAMAP–SA), to characterize spatial and temporal patterns of the nearshore U.S. East Coast fish assemblage from Montauk, NY to Cape Canaveral, FL. For this analysis, NEAMAP and SEAMAP catch data were limited to spring and fall, from 2008‒2012, and 4‒13 m water depth. Hierarchical agglomerative clustering of tow level finfish biomass densities indicates seasonally-dependent connectivity between management regions (Mid-Atlantic and South Atlantic) and Large Marine Ecosystems (Northeast U.S. and Southeast U.S.). Relative contributions of individual species to cluster separations will be presented. Results highlight the dynamic nature of spatial and temporal patterns in nearshore fish community composition and will guide future species- and community-level modeling efforts. Species-specific differences in gear selectivity between surveys are not currently available and thus were not directly accounted for here. Quantifying selectivity differences will be paramount to generation of comparable indices of abundance for future use in stock assessments.