Improved Ability to Characterize Recruitment of Gray Snapper in Three Florida Estuaries along the Gulf of Mexico through Targeted Sampling of Polyhaline Seagrass Beds. Flaherty-Walia, K., E., Switzer, T., S., Winner, B., L., J. Tyler-Jedlund, A., & Keenan, S., F. Transactions of the American Fisheries Society, 144(5):911-926, Taylor and Francis Inc., 9, 2015.
Improved Ability to Characterize Recruitment of Gray Snapper in Three Florida Estuaries along the Gulf of Mexico through Targeted Sampling of Polyhaline Seagrass Beds [pdf]Paper  abstract   bibtex   
Abstract: Estuarine-dependent Gray Snapper Lutjanus griseus support extensive recreational fisheries in estuarine and coastal waters throughout the eastern Gulf of Mexico. Multiyear fisheries-independent monitoring data collected in three Florida estuaries can be used to estimate the strength of juvenile Gray Snapper recruitment, which has been critical to assessments of other fish populations. Earlier evaluation of these data indicated that Gray Snapper inhabit polyhaline seagrass beds, which are underrepresented in ongoing monitoring efforts. During this study, in addition to the routine monitoring of shorelines and channel habitats, sampling of shoal and deepwater polyhaline seagrass habitats was implemented using 183-m haul seines and 6.1-m otter trawls. The incorporation of polyhaline seagrass surveys from 2008 through 2011 allowed a more thorough sampling of the Gray Snapper population, resulting in improved catch rates, increased frequency of occurrence, and a substantial reduction of the coefficient of variation for CPUE in most years and estuarine systems. Habitat-based sampling of polyhaline seagrass habitats also provided additional data for annual abundance indices and therefore improved the ability to characterize the strength of recruitment for Gray Snapper over time. These results demonstrated that periodically reevaluating habitat-based stratification approaches to estimate fish abundance indices from long-term surveys can lead to more precise estimates and greater numbers of measured individuals, which are key components of successful monitoring programs. Received October 24, 2014; accepted May 14, 2015

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