Fig 1.
Survey area location off the southern part of the Canary Current Large Marine Ecosystem coast along nine transects (T1-T9) perpendicular to the coast.
Bathymetry data from ETOPO1 Global Relief Model (https://www.ncei.noaa.gov/products/etopo-global-relief-model).
Fig 2.
Histogram showing the sum (∑MVBS) of the mean volume backscattering strength (MVBS, in dB) between 120 and 38 kHz frequencies along the sampled transect (T3) with integration cells of three pings per meter.
Threshold at -119 dB (dotted line) distinguishing fish (FISH) and no fish (NO FISH) values.
Fig 3.
Bi-frequency (38 and 120 kHz) acoustic algorithm for discriminating Fluid-like (“FLUID”) and “Other” (i.e., fish and other scatters) groups using mean volume backscattering strength (MVBS, dB) summation and differences.
This method was applied to West African data (2014 AWA survey) to obtain a corrected “Fluid-like” echogram with no fish echo. Adapted from Ballón et al. [67].
Fig 4.
Histogram showing the difference (ΔMVBS) of the mean volume backscattering strength (MVBS, in dB) between 120 and 38 kHz frequencies applied on Fluid-like echograms.
The range of 2–7 dB corresponds to krill, while the 7–25 dB range corresponds to copepod.
Fig 5.
Size class contribution to Target Strength difference.
Histogram showing the percentage contribution of different size classes (in Equivalent Spherical Radius) to the target strength (TS, in dB) difference estimated using the fluid sphere model [48] on West African data.
Fig 6.
Copepod size vs. Target Strength. Copepod size ‘a’ (in Equivalent Spherical Radius, ESR in mm) vs. detected Target Strength (TS in dB) at frequencies of 38 kHz (full line) and 120 kHz (dotted line).
Fig 7.
Copepod Target Strength relationship.
The relationship between “ka” and the difference in copepod Target Strength (in dB) at 120 and 38 kHz. “k” is the acoustic wavenumber in surrounding water, and “a” is the radius of the animal body in mm. k = 2π fm / c, with c = speed of sound (in m s-1), fm = (f120*f38)0.5 (in kHz). The slope of the backscattering difference at low frequencies (small ka) is related to the size of the scatterers. The differences between 7.0 and 19.7 dB correspond to the size range of 0.5 and 3.1mm and the ka range of 0.14 to 0.81. The overlaid shadow area indicates the range at which the high-pass model provides safe radius estimates.
Fig 8.
Abundance and biomass percentages.
(a) Percentage of total abundance and biomass by zooplankton categories sampled with the Hydrobios MultiNet during the fisheries acoustics AWA sea survey off Senegal; (b) Percentage of total abundance and biomass at copepod level. Only organisms > 0.5 mm ESR are considered.
Fig 9.
Diel variations in copepod abundance.
Daytime and night-time variations of copepod abundance (> 0.5 mm Equivalent Spherical Radius) along the water column at four net stations in various depth layers sampled (from 10-25m to 100–200 m).
Fig 10.
Acoustic vs. MultiNet Abundance.
Comparison of copepod acoustic abundances (ind m-3) and MultiNet (ind m-3; only copepods > 0.5 mm Equivalent Spherical Radius considered) for eight stations per depth strata during a-d) night-time and e-h) daytime stations. Data from survey AWA 2014, West Africa.
Fig 11.
Scatterplots: Copepod acoustic vs. MultiNet estimates.
Scatterplots comparison for copepod acoustic and MultiNet estimates (Equivalent Spherical Radius > 0.5 mm) at eight stations: during daytime and night-time (AWA 2014 survey). (a) Abundance (ind m-3), (b) biomass (in μg m-3). r2: Multiple R-squared; Significant p-value < 0.03).
Fig 12.
Depth-Integrated biomass variation by diel period.
Minimal, maximal, median values and standard errors illustrate the Diel period-dependent variation in depth-integrated mean biomass from hydro acoustics.
Fig 13.
(Left) Observed copepod biomass (mg m-2) at net sampling stations along the transect in the southern Canary Current Large Marine Ecosystem (CCLME) based on the March 2014 hydroacoustic AWA sea survey data. (Right) Spatial distribution of interpolated copepod biomass (mg m-2) with ordinary kriging in the southern CCLME. The map images were created using the maps package in R, which sources its map data from the Natural Earth project (http://www.naturalearthdata.com/).