Farmed Atlantic salmon (Salmo salar L.) avoid intrusive objects in cages: The influence of object shape, size and colour, and fish length

Abstract

Underwater vehicles and other mobile platforms are seeing increased use as tools within fish farming, particularly due to current trends towards Precision Farming practices, and more exposed farming sites. Although many of the applications of such tools (e.g., net cleaning and inspection) have become well established industrial practices, it is largely unknown how much such operations disturb the fish and the consequence of this disturbance. In this study, we explored this by exposing Atlantic salmon in commercial net cages to intrusive objects and monitoring the distribution of fish around these using on-board 360-degree sonars. Six different object designs were tested covering variations in size, shape, and colour, which are important static characteristics of underwater vehicles/platforms. The sonar data was first aggregated into images containing the Cumulative Fish Presence over 1-, 5- and 10-min periods to provide a more robust foundation for further analyses. By training a deep learning based method using UNet++ architecture to automatically segment the fish distribution patterns, the mean distance between the inner perimeter of the fish distribution and the object was assessed. Results from the study implied that fish keep greater distances to larger objects. There was, however, no clear impact of the shape. Regarding the effect of colour, fish kept greater distances to yellow than to white objects. When comparing results from tests on fish of different size, data indicate a positive linear relationship between fish weight (age) and distance to an object, that can be expressed as an avoidance distance of an average 3.8 body-lengths. Our findings provide new fundamental knowledge on the dynamics between the fish and objects such as vehicles or other mobile platforms in fish farms, and thus provides valuable insights that can be useful when designing such tools specifically for aquaculture.