Methodology:

Raw (calibrated as per Demer et al., 2015) Simrad EK60 echosounder data (18, 38 and 120 kHz; Kongsberg Maritime, Norway) collected annually in August and September between 2011 and 2016 as part of the Barents Sea Ecosystem Survey (Eriksen et al., 2018) were obtained from the Norwegian Marine Data Centre (Institute of Marine Research, Norway).

Raw data were read using the pyEcholab python (version 3.7) package (https://github.com/CI-CMG/pyEcholab) and processed using the Echopy python package (https://github.com/open-ocean-sounding/echopy). Processing included identifying seabed (and removing detections at and below it), subtracting background noise, removing pings that were attenuated or that included transient noise, masking impulse noise (interference from other sound sources) and removing data that contained false bottom echoes (Ryan et al., 2015). Processed data were checked visually by plotting echograms for all surveys. Nautical-area-scattering coefficient (NASC, m2 nmi-2: average received echo energy over a given depth range scaled up to a square nautical mile) values were computed for the remaining data averaged over 1 km along track intervals (station data were not analysed) between 15 m (maximum vessel draft plus echosounder near-field for all surveys, vessels and frequencies) and 400 m (lower extent of SE2E model domain).

NASC values at 18 kHz were used as a proxy for fish biomass. At this frequency, the contribution of smaller scatterers, such as zooplankton is expected to be < 1%. Fish, which contain gas-bladders, are very strong acoustic targets and will likely make up the majority of the received echo energy at this frequency (Proud et al., 2019). NASC values at 120 kHz and where NASC 120 kHz > 38 kHz > 18 kHz (i.e. Rayleigh scattering from small targets such as zooplankton) were used as a proxy for macro-zooplankton biomass (similar methods are used to discriminate Antarctic krill/zooplankton from fish in the Southern Ocean, see Brierley et al., 1998).

Mean NASC values for both fish and macro-zooplankton over the period (2011-2016) were computed for each of the 12 locations where acoustic data were available (using NASC within 50 km of each location and weighted by 1/distance) for comparison with ECOSMO, and for both the Inshore and Offshore domains for comparison with SE2E. Bootstrap sampling was used to calculate confidence intervals (sample size was set to number of NASC values in dataset for each partition and number of iterations to 1000). NASC values were binned into a 0.5 by 0.5-degree grid and averaged to map the spatial distribution of fish and macro-zooplankton.

Data collection:

Instrument: Simrad EK60 echosounder data (18, 38 and 120 kHz).

Software: 'pyEcholab' python package (version 3.7) (https://github.com/CI-CMG/pyEcholab) and processed using the 'echopy' python package (https://github.com/open-ocean-sounding/echopy).

Data quality:

Data were calibrated (as per Demer et al., 2015) and noise removed using standard methods.