Jarl Giske

Aquaculture of Atlantic salmon Salmo salar is in transition to precision fish farming and digitalization. As it is easier, cheaper and safer to study a digital replica than the system itself, a model of the fish can potentially improve monitoring and prediction of facilities and operations and replace live fish in many what‐if experiments. Regulators, consumers and voters also want insight into how it is like to be a salmon in aquaculture. However, such information is credible only if natural physiology and behaviour of the living fish is adequately represented. To be able to predict salmon behaviour in unfamiliar, confusing and stressful situations, the modeller must aim for a sufficiently realistic behavioural model based on the animal's proximate robustness mechanisms. We review the knowledge status and algorithms for how evolution has formed fish to control decisions and set priorities for behaviour and ontogeny. Teleost body control is through genes, hormones, nerves, muscles, sensing, cognition and behaviour, the latter being agentic, predictive and subjective, also in a man‐made environment. These are the challenges when constructing the digital salmon. This perspective is also useful for modelling other domesticated and wild animals in Anthropocene environments.