Prediction of krill swarm characteristics off East Antarctica

• Other Authors: AADC (owner), AADC, DATA OFFICER (distributor), AADC, DATA OFFICER (custodian), AU/AADC > Australian Antarctic Data Centre, Australia (hasAssociationWith), Australian Antarctic Data Centre (publisher), Australian Antarctic Division (sponsor), Bestley, S., Raymond, B. and Cox, M. (originator), COX, MARTIN (collaborator), COX, MARTIN (hasPrincipalInvestigator), RAYMOND, BEN (collaborator), RAYMOND, BEN (hasPrincipalInvestigator), RAYMOND, BEN (author)
• Format: Dataset
• Language: unknown
• Published: Australian Ocean Data Network
• Subjects: biota; oceans; EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > ANIMALS/INVERTEBRATES > ARTHROPODS > CRUSTACEANS > EUPHAUSIIDS (KRILL); OCEANS > OCEAN ACOUSTICS; CLIMATE INDICATORS > BIOSPHERIC INDICATORS > SPECIES MIGRATION; BIOSPHERE > ECOSYSTEMS > MARINE ECOSYSTEMS; KRILL; ACOUSTIC SOUNDERS; R/V AA > R/V Aurora Australis; AMD/AU; ACE/CRC; AMD; CEOS; GEOGRAPHIC REGION > POLAR; Antarc*; Antarctica; aurora australis; East Antarctica
• Online Access: https://researchdata.edu.au/prediction-krill-swarm-east-antarctica/2819079

Progress Code: completed Purpose The acoustic data were collected during the multi-disciplinary Baseline Research on Oceanography, Krill and the Environment (BROKE)-West survey off East Antarctica in the austral summer of 2006 (Nicol et al. 2010). We used the easternmost half of the BROKE-West survey transects (T7-11) covering 60-80 degrees E. Individual krill swarms were isolated by applying the schools detection algorithm of (Barange 1994), implemented in Echoview. After (Tarling et al. 2009) school detection was carried out on a 7x7 identity matrix convolution of the 120 kHz pre-processed data using the detection parameters of (Tarling et al. 2009) and a mean volume backscattering strength Sv threshold of -70 dB re 1 m -1. These aggregations were classified as krill or not by applying the validated 'dB-difference' technique (Watkins and Brierley 2002) to the 7x7 convolution of 120-38 kHz pre-processed data falling within the detected aggregation boundaries. As implemented here, the dB-difference technique is a binary classification, and aggregations falling within a dB difference range were deemed to be krill. Outside of the dB difference range an aggregation was classified as coming from other species and excluded from further analysis. The dB-difference ranges were calculated using the krill acoustic target strength model (Calise and Skaret 2011) and based on length frequency distribution clusters (Kawaguchi et al. 2010). Once identified, volume integrations were carried out on 120 kHz falling within krill swarms at a -80 dB threshold and swarm internal density rho was calculated using rho = 10^(Sv-TS_kg)/10, where TS_kg is the target strength of 1 kg of krill. Statistical models were developed to predict two specific characteristics of individual krill swarms (1) internal swarm density (g m-3), and (2) mean vertical depth (m) of the swarm in the water column. A mixed-effects modelling approach was adopted to account for the inherent structure in the krill survey observations. We used Generalised Additive ...