Exploration of geostatistical methods for mapping and estimating acoustic biomass of pelagic fish in the Gulf of St. Lawrence: size of echo-integration unit and auxiliary environmental variables

Daytime 38 kHz mean volume backscattering strength (MVBS) of small pelagic fish in the Gulf of St. Lawrence was recorded at 60-m intervals along a regular network of 11 parallel transects in August 1991. Profiles of temperature, salinity, density and transmittance were collected on a grid of 44 punctual stations along the transects. The MVBS was contagiously distributed and autocorrelated for al1 transects. No significant monotone relationship with any of the environmental variables was evidenced, except that the highest concentrations of fish were located over shallow bottoms. The anisotropic variogram of MVBS indicated three different scales of spatial structures: an unresolved small-scale variability, which accounted for only 7.7% of variance, and two structure components of along-transect scales of ~500 m (~40%) and 15 km (~50%). The theoretical variograms deduced for larger echo-integration units (EIUs) than the recorded 60-m unit, provided a good fit to the corresponding experimental variograms up to EIU of 1920-m, when the disturbing effect of outliers on the variograms was removed. Global estimates and maps produced with 240-m and 1920-m EIU data were almost identical, showing that no significant loss of information was caused by increasing the EIU. Asymmetric confidence intervals of the global estimates are obtained using two variograms, one controlled for the effect of the outliers, the other one not controlled. In an effort to take the relation of MVBS with the bottom depth into account, four different kriging methods were compared: ordinary kriging, kriging with the bottom depth or its indicator-transform as external drift, and 3-D ordinary kriging with depth as the third dimension. Because of the weak relation of MVBS with the bottom depth, ordinary kriging had the best performance. Results are discussed in the context of applications of geostatistics to estimation and mapping of acoustic survey data