A semantic model for overall welfare assessment of Atlantic salmon reared in sea cages is presented. The model, called SWIM 1.0, is designed to enable fish farmers to make a formal and standardized assessment of fish welfare using a set of selected welfare indicators. In order to cover all welfare relevant aspects from the animals’ point of view and to create a science‐based tool we first identified the known welfare needs of Atlantic salmon in sea cages and searched the literature for feasible welfare indicators. The framework of semantic modelling was used to perform a structured literature review and an evaluation of each indicator. The selected indicators were water temperature, salinity, oxygen saturation, water current, stocking density, lighting, disturbance, daily mortality rate, appetite, sea lice infestation ratio, condition factor, emaciation state, vertebral deformation, maturation stage, smoltification state, fin condition and skin condition. Selection criteria for the indicators were that they should be practical and measureable on the farm, that each indicator could be divided into levels from good to poor welfare backed up by relevant scientific literature. To estimate each indicator’s relative impact on welfare, all the indicators were weighted based on their respective literature reviews and according to weighting factors defined as part of the semantic modelling framework. This was ultimately amalgamated into an overall model that calculates welfare indexes for salmon in sea cages. More importantly, the model identifies how each indicator contributes (negatively and positively) to the overall index and hence which welfare needs are compromised or fulfilled.

In this study, we demonstrate how an event that is initially frightening to Atlantic salmon is turned to a positive stimulus through habituation and associative learning. The study was carried out in four commercial sized tanks (5 m 3 ) with near industry densities ([550 fish, 16 kg m -3 ), using a delay conditioning procedure with an aversive flashing light as the conditioned stimulus and food reward as the unconditioned stimulus. By using video image analysis of the distribution of the fish in the tanks, the changes in behaviour from trial to trial could be documented in great detail. The current study documents the change in behaviour across the individual conditioning trials, clearly showing the step-by-step nature of the transition. The salmon needed more than 26 trials to become fully habituated to the flashing light but showed clear anticipatory behaviour already after about 19 trials. This demonstrates that the learning process is a combination of habituation and associative learning.

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Basic knowledge about learning capacities and awareness in fish is lacking. In this study we investigated which temporal gaps Atlantic cod could tolerate between two associated events, using an appetitive trace-conditioning paradigm with blinking light as conditioned stimulus (CS) and dry fish food as unconditioned stimulus (US). CS-US presentations were either temporally overlapping (delay conditioning, CS duration 24 s, interstimulus interval 12 s) or separated by 20, 60, or 120 s (trace conditioning, CS duration 12 s) or 2 h (control, CS duration 12 s). The percentage of fish in the feeding area increased strongly during CS presentation in all delay, 20 s, and 60 s trace groups and in one out of two 120 s trace groups, but not in the control groups. In the 20 and 60 s trace procedures, the fish crowded together in the small feeding area during the trace interval, showing strong anticipatory behaviour. In all the conditioned groups, the fish responded to the CS within eight trials, demonstrating rapid learning. At 88 and 70 days after the end of the conditioning experiments, the delay and 20 s trace groups, respectively, were presented the CS six times at 2-h intervals without reward. All groups responded to the light signal, demonstrating memory retention after at least 3 months. This study demonstrates that Atlantic cod has an impressively good ability to associate two time-separated events and long time retention of learnt associations.

SUMMARYAluminum (Al) toxicity occurs frequently in natural aquatic ecosystems as a result of acid deposition and natural weathering processes. Detrimental effects of Al toxicity on aquatic organisms are well known and can have consequences for survival. Fish exposed to Al in low pH waters will experience physiological and neuroendocrine changes that disrupt homeostasis and alter behavior. To investigate the effects of Al exposure on both the brain and behavior, Atlantic salmon (Salmo salar) kept in water treated with Al (pH5.7, 0.37±0.04μmol1 −1 Al) for 2weeks were compared with fish kept in under control conditions (pH6.7, <0.04μmol1 −1 Al). Fish exposed to Al and acidic conditions had increased Al accumulation in the gills and decreased gill Na + , K + -ATPase activity, which impaired osmoregulatory capacity and caused physiological stress, indicated by elevated plasma cortisol and glucose levels. Here we show for the first time that exposure to Al in acidic conditions also impaired learning performance in a maze task. Al toxicity also reduced the expression of NeuroD1 transcript levels in the forebrain of exposed fish. As in mammals, these data show that exposure to chronic stress, such as acidified Al, can reduce neural plasticity during behavioral challenges in salmon, and may impair the ability to cope with new environments.