Hydroacoustic Survey Data from Lower Cook Inlet, Alaska

FIELD: Hydroacoustic data were obtained from a hull-mounted SIMRAD ER60 split beam dual frequency echosounder operating at 120 and 38 kHz. Tranducers were calibrated at the start of each survey following Foote et al. (1987). Raw data were collected to a maximum depth of 500 m at 0.512 ms transmitted pulse length. Latitude and longitude point locations were recorded continuously during transects using SIMRAD ER60 ver.2.4.3. Acoustic backscatter in the water column were classified for depths between 4 m below the surface to 1 m above the bottom using frequency response methods for inshore waters (De Robertis and Ormseth 2018). The difference in mean volume backscattering strength (Sv, dB re 1 m-1, hereafter dB) between 120 and 38 kHz data (ΔSv120kHz – 38 kHz) in each 5 ping by 5 m acoustic sample was computed in the log domain using a minimum threshold of -67 dB to exclude jellyfish (Parker-Stetter et al. 2016). For 120 kHz data, samples with ΔSv120kHz – 38 kHz values between -16 to 8 dB were classified as fish based on known acoustic scattering characteristics (De Robertis, McKelvey, and Ressler 2010). Echointegration was conducted with Echoview (ver. 11, Echoview Software Ltd., Hobart, Tasmania, Australia). Area backscattering coefficient (ABC, sa, m2m-2) data were aggregated by 500 m transect segments and summed across two depth strata: shallow (4 – 20 m), and deep (21 m – 1 m above bottom).

LAB: Sounder-detected bottom line were edited by visually inspecting the 38 kHz echogram. Passive noise was removed from both transducers using a data generator for each frequency following Parker-Stetter et al. 2009, and background noise was removed from the 120 kHz transducer following De Robertis and Higginbottom (2007). Any data below the bottom line and above 4 m from the surface were excluded from the integration export.

LITERATURE CITED: De Robertis, A., Higginbottom, I., 2007. A post-processing technique to estimate the signal-to-noise ratio and remove echosounder background noise. ICES Journal of Marine Science 64(6):1282-1291. doi:10.1093/icesjms/fsm112 De Robertis A., McKelvey D.R., Ressler P.H., 2010. Development and application of an empirical multifrequency method for backscatter classification. Canadian Journal of Fisheries and Aquatic Sciences 67(9):1459-1474. doi:10.1139/F10-075 De Robertis, A., Ormseth, O., 2018. Inshore Acoustic Surveys in the Eastern and Central Gulf of Alaska. Deep Sea Research Part II: Topical Studies in Oceanography 165:255-267. doi:10.1016/j.dsr2.2018.05.001 Foote, K.G., Knudsen, H.P., Vestnes, G., MacLennan, D.N., Simmonds, E.J., 1987. Calibration of acoustic instruments for fish density estimation: A practical guide. ICES Cooperative Research Report no.144 63pp. Parker-Stetter, S.L., Rudstam, L.G., Sullivan, P.J., Warner, D.M., 2009. Standard operating procedures for fisheries hydroacoustic surveys in the Great Lakes. Great Lakes Fishery Commission Special Publication 09-01 165pp. Parker-Stetter, S.L., Urmy, S., Horne, J.K., Eisner, L., Farley, E., 2016. Factors affecting summer distributions of Bering Sea forage fish species: Assessing competing hypotheses. Deep Sea Research Part II: Topical Studies in Oceanography 134:255-269. doi:10.1016/j.dsr2.2016.06.013