Summary: | Dataset: McMurdo Sound acoustic backscatter krill and silverfish Acoustic echosounder data were collected as part of an ecosystem study in McMurdo Sound, which is located at the southern extent of the Ross Sea in the Southern Ocean. The major goal of this multi-disciplinary project was to assess the influence of top−down forcing (predation) on pelagic zooplankton and fish. Stations were located along the fast ice edge, and along three transects into the fast ice along the eastern side of McMurdo Sound (Ross Island), in the middle of the Sound, and on the western side of the Sound. Krill and fish were sampled between 17 November 2014 – 1 January 2015, both acoustically and visually beneath the fast ice using the tethered SCINI ROV, which was deployed and operated through a 25 cm diameter hole drilled through the sea ice. SCINI contained cameras and thrusters, and towed a sensor package consisting of a WET Labs fluorometer (ECO-AFL/FL) and a single-beam Biosonics 120 kHz DT-X echosounder. Visual targets were identified to the lowest taxon possible; these observations were used primarily to verify classification of acoustic signals. The echosounder operated at a nominal ping rate of 1 ping s-1; however, this rate was occasionally adjusted if false bottom signals were observed. The general profile of a dive included a surface transect of ~300 m horizontal distance, where the acoustic transducer faced downward, and also a dive to ~120 m if conditions allowed. Echogram data were saved to a depth of 500 m, and background noise was removed. Given the effective range of the transducer of approximately 100 m (resolving -80 dB targets), surveys characterized the upper 200 m of the water column.Raw acoustic data were analyzed using Echoview software (version 5.3). All acoustic aggregations greater than 4 pings in width were manually delineated, and acoustic energy of the aggregations was integrated into bins of six seconds wide by 1 m in depth. These aggregations were classified as potentially krill or silverfish, based ...
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