Hydroacoustic Estimation of Zooplankton Biomass at Two Shoal Complexes in the Apostle Islands Region of Lake Superior |
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| Affiliation: | 1. Office of Undergraduate Biology, 216 Stimson Hall, Cornell University, Ithaca, NY 14853, USA;2. Great Lakes Center, Buffalo State College, Buffalo, NY 14222,USA;3. The Research Foundation of The State University of New York, Buffalo State College, Office of Sponsored Programs, Buffalo, NY 14222, USA;4. Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY 11794-5245, USA;1. USEPA Great Lakes National Program Office, 77 W. Jackson Blvd., Chicago, IL 60604, USA;2. CSRA LLC and Department of Earth and Environmental Sciences, University of Illinois at Chicago, 845 W. Taylor St., Chicago, IL 60607, USA;3. CSRA LLC, 1359 W. Elmdale Ave., Suite 2, Chicago, IL 60660, USA;1. Biology Department, University of Minnesota Duluth, 1035 Kirby Drive, Duluth, MN 55812, USA;2. U.S. Geological Survey, Lake Superior Biological Station, 2800 Lake Shore Dr. East, Ashland, WI 54806, USA |
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| Abstract: | Hydroacoustics can be used to assess zooplankton populations, however, backscatter must be scaled to be biologically meaningful. In this study, we used a general model to correlate site-specific hydroacoustic backscatter with zooplankton dry weight biomass estimated from net tows. The relationship between zooplankton dry weight and backscatter was significant (p < 0.001) and explained 76% of the variability in the dry weight data. We applied this regression to hydroacoustic data collected monthly in 2003 and 2004 at two shoals in the Apostle Island Region of Lake Superior. After applying the regression model to convert hydroacoustic backscatter to zooplankton dry weight biomass, we used geostatistics to analyze the mean and variance, and ordinary kriging to create spatial zooplankton distribution maps. The mean zooplankton dry weight biomass estimates from plankton net tows and hydroacoustics were not significantly different (p = 0.19) but the hydroacoustic data had a significantly lower coefficient of variation (p < 0.001). The maps of zooplankton distribution illustrated spatial trends in zooplankton dry weight biomass that were not discernable from the overall means. |
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