Optimizing data quantity and quality for side-looking echosounder surveys in large rivers

Abstract

The increased use of side-looking echosounder surveys in large rivers necessitates the creation and evaluation of standardized sampling protocols to effectively sample these habitats. Using data from five Ohio River pools, we evaluated the effects of habitat and transect direction on the quality and quantity of mobile, side-looking, split-beam echosounder data to determine how these factors may affect survey design in large rivers. Split beam echosounder data were collected using two multiplexing 200 kHz transducers offset in angle to maximize water column coverage. Using mixed-effects models, we evaluated the effects of habitat (main channel vs. tributary) and transect direction (upstream vs. downstream movement of the vessel) on fish density and the number of targets per fish track (series of acoustic targets from an individual fish). We also used a skewness test in conjunction with a Kolmogorov-Smirnov test to determine the distribution of fish orientations relative to the transducer and examine differences in the distribution of fish orientations among habitats, transect directions, and years. Mean fish densities were greater in tributary habitat relative to main channel habitat, whereas main channel habitat had a higher mean number of targets per fish track when compared to tributaries. Upstream-facing transects had greater mean fish density estimates and mean number of targets per fish track than downstream-facing transects. Although most fish were oriented perpendicular to the transducer, we identified habitat, transect direction, and annual differences in the distribution of fish orientations. These results suggest that researchers and managers that plan to use side-looking echosounders to assess fish populations in large rivers should ensure that standardized protocols include main channel and tributaries, and are expanded to encompass other relevant habitats (e.g., backwaters and side channels). Further, managers should use fish orientation data to select or develop TS-L equations that best matches the fish orientation distribution of each survey to ensure accurate density and size estimates.