Many different biological, environmental, and social parameters influence the behaviour of salmon when farmed in sea cages. Parasites, such as sea lice, are a biological example that can cause behavioural changes to farmed salmon in order to combat infestation. Sea lice are concentrated near the surface, and methods to limit fish surface time have been a focus of farm mitigation activities. Salmon have been observed to prefer deeper depths once highly infested to avoid further infestation. Temperature and dissolved oxygen (DO) are an example of environmental parameters that affect behaviour of Atlantic salmon. For example, Atlantic salmon will distribute themselves according to preferred temperature range, 8--18C, with changes in behaviour occurring above and below the threshold. Similarly, DO is an important parameter affecting fish behaviour as concentrations below the optimal range cause physiological stress and related behavioural changes such as a reduction in feeding. Light intensity is another major contributor to fish behaviour by changing vertical distribution. During daylight hours, when light intensity is at its greatest, fish tend to swim deeper in net pens to avoid surface predators. It has been hypothesized ascent towards the surface during nighttime is a photo-regulatory behaviour to maintain schooling as light fades. Furthermore, seasonal variation in light availability changes vertical distribution with winter swimming depths generally shallower than summer swimming depths. However, this diel seasonal pattern changes when surface-mounted artificial lights are installed in net pens. Populations have also been observed to remain in the upper half of net pens, under normal stocking densities, to avoid large piscivorous fish present under net pens. Additionally, hydrodynamic conditions, such as waves and currents, will affect vertical distribution with stronger waves encouraging fish towards the surface.

We explored these myriad factors in our recent paper (O'Donncha et. al. 2021). In that paper, we collected data at three salmon farms in Norway, Scotland, and Canada. For each site, a number of environmental sensors were deployed monitoring a range of parameters, including temperature, DO, and current speed. These were complemented with weather data from in-situ weather stations or model-generated reanalysis from IBM Environmental Intelligence Suite available through their public API. Reanalysis is a scientific method for developing a comprehensive record of how weather and climate are changing over time. In it, observations and a numerical model that simulates one or more aspects of the Earth system are combined objectively to generate a synthesized estimate of the state of the system. It serves a critical purpose for scientific investigation as it provides a consistent, long-term representation of system dynamics.

Information on fish response in the cage was collected by hydroacoustic sensors. Hydroacoustic methods provide a proxy measure for density and distribution of marine animals in form of acoustic backscattering. The fundamental principle is based on emitting a signal of known type and power level from a transducer. As it encounters regions of the medium with differing properties, also called heterogeneities, the sound is generally redistributed or scattered, in all directions. This makes possible detection of the scattered sound with transducer and suitable receiver electronics. Advantages linked to hydroacoustic sampling techniques include high spatial and temporal resolution, autonomous long-term sampling duration, range (especially during poor visibility when visual-based methods tend to fail), and a non-invasive surveying approach. Given these advantages, hydroacoustics is increasingly used to characterise animal behaviour in the marine environment and is considered a promising system to improve the management of aquaculture farms.

Broadly speaking, processed hydroacoustic data generates two metrics: volume backscattering strength S_v, is often considered as a proxy for fish biomass; while target strength (TS) is an acoustic measure of fish length. TS is a measure of the acoustic reflectivity of a fish, which varies depending on the presence of a swim bladder and on the size, behavior, morphology, and physiology of the fish.  These outputs can be used to generate estimates of fish density and biomass within a cage.

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