Spatial distributions of acoustic scattering groups during the warm-to-cold transition period in the Senegal coastal ecosystem and their relationships with environmental variables

Abstract

The coastal area of north-west (NW) Africa is a highly productive ecosystem due to the presence of a strong upwelling. This ecosystem supports large populations of small pelagic fish, such as sardinellas, which have significant socio-economic value for local populations. In this study, we analyzed the acoustic data collected during a one-month survey along the Senegalese coast at the beginning of the upwelling season. Hierarchical clusterings were performed to classify the acoustic data from the epipelagic zone (down to 120 m-depth) separately for daytime and nighttime. The analysis identified five echo-groups during the day and six at night. The resulting echo-groups were then compared to stratified midwater trawl samplings to support hypotheses about the organisms responsible for the echoes. Additionally, a remotely operated towed vehicle (called Scanfish) was used to monitor environmental variables down to 100 m depth. Two machine learning models were applied to link the classified echo-groups to the environmental data for both day and night. Each daytime echo group had a corresponding nighttime echo group, with also similar environmental preferences. Fish schools were mainly found in shallow coastal waters while dense sound-scattering layers detected at 38 kHz, likely composed of small fish or fish larvae, were observed in the temperature range of 17°-21 °C for both day and night. The other echo-groups were composed of fluid-like zooplankton or gas-bearing zooplankton. The sixth night echo-group corresponded to migrant organisms and was predominant at night. Overall, the analyses of the abiotic habitats for each echo-group allow us to better understand the organism distributions during the beginning of the NW Africa upwelling season.