Study of fish swimming activity using acoustical Doppler velocimetry (ADV) techniques

Abstract

The suitability of using acoustic Doppler velocimetry (ADV) to study fish swimming activity is evaluated in this study. ADV makes it possible to detect and quantify the relationship between fish density and the turbulence generated by fish swimming activity and to show differences in fish swimming patterns during the scotophase (dark period) and photophase (light period), which has been previously described by other authors. Turbulence was evaluated using the root mean square of velocity (RMS) as an indicator of fish swimming activity, and an ADV probe with an internal sampling rate of 100Hz, which took 25 velocity data per second.Experiments at the laboratory scale using zebra fish showed a positive correlation between turbulence (RMS), caused by fish swimming activity, and density. The relationship between density and RMS was strongly linear (r2=0.964). In an ongrowing farm, daily turbulence patterns caused by fish swimming activity were evaluated with sea bass at two densities: 35.5kgm−3 (average weight of 48g), and 11.8kgm−3 (average weight of 11.7g). Greater activity was detected during the photophase, indicating that light has a substantial affects sea bass swimming activity. Average RMS at a density of 35.5kgm−3 was 3.632 and 2.428cms−1 during photophase and scotophase, respectively, while working at a density of 11.8kgm−3, average RMS was 1.728 and 1.419cms−1 during the photophase and scotophase, respectively.ADV is a rapid and reliable method to evaluate fish swimming activity at laboratory scales as well as at commercial facilities. However, ADV configuration parameters must be properly chosen in order to obtain the highest possible number of good velocity data. Data post-processing was done by filtering velocity data using correlation (COR>70), signal-to-noise ratio (SNR>5) and despiking filters. COR provides a measure of quality of each velocity data, ranging from 0 to 100, and SNR indicates the intensity of the reflected acoustic signal expressed in dB. Finally, despiking filter eliminates spikes generated by fish located near the probe or between the probe and point of measurement. Post-processing showed that COR filter eliminated the higher number of velocity data.