Modelling of Atlantic salmon (Salmo salar L.) behaviour in sea-cages: A Lagrangian approach

Abstract

We constructed a Lagrangian (individual-based) model of the behaviour of Atlantic salmon in sea-cages. The behaviour of individual fish was affected by a set of environmental factors and the other individuals in the population. The model was based on behavioural parameters derived from literature and comparisons between model performance and published quantitative data sets. Simulations demonstrated that the model was able to predict the circular schooling patterns familiar to caged Atlantic salmon based on social interactions among the individuals and a motivation to keep a certain distance to the cage wall. The model accurately predicted the vertical distribution patterns of salmon over 24 h within a sea-cage when verified against three detailed observational data sets from autumn, implying that the model closely replicated behavioural responses toward the combined effects of temperature and light. Deviations seen in the comparisons were possibly due to unmodelled features in the feeding response. Potential uses of the model include: 1) increasing understanding of how environmental factors affect fish behaviour; 2) coupling with measurements in a model-based estimator structure to accurately estimate biomasses within sea-cages; and 3) predicting the welfare status of fish in sea-cages under specific environmental conditions.

Introduction

The importance of aquaculture production of marine finfish as a source of marine protein for human consumption is steadily increasing. Since its introduction to aquaculture in the 1970s, Atlantic salmon has become an important species in sea-cage mariculture with more than 1.3 million tons produced in 2006 (FAO, 2008). Improving production of salmon is a constant focus of the industry, both to reduce costs and reduce environmental impacts. The diverse physical and biological influences experienced by caged salmon ultimately affect growth rates and welfare (Juell and Westerberg, 1993, Fernö et al., 1995, Huntingford, 2004). Models that predict the behaviour of fish under particular environmental conditions may therefore be useful tools in managing production.

Fish in captivity are subject to a range of varying environmental conditions. High densities of fish (up to 25 kg m^− 3) within the confined space of sea-cages which are typically between 10,000 and 20,000 m³ in volume at Norwegian sea-farms (Sunde et al., 2003) means that social interactions between fish may have a strong influence on their behaviour. Traditionally two different kinds of modelling paradigms have been used to portray biological phenomena. Lagrangian (individual-based) models replicate each individual as an instance of the same model, though often with different parameters yielding a heterogeneous population (e.g. Reuter and Breckling, 1994, Kunz and Hemelrijk, 2003). In contrast, Eulerian models represent populations by differential equations and scalar fields rather than as distinct individuals (e.g. Flierl et al., 1999).

Typical environmental conditions caged salmon are exposed to include food, light, temperature, salinity and oxygen levels, which may vary over short (minutes, hours) and long (days, seasons) time scales (Juell, 1995). Addition of food greatly affects salmon behaviour, with a switch in swimming behaviour, speed and depth within cages (Andrew et al., 2002, Juell and Fosseidengen, 2004). Light levels influence swimming depths of salmon; avoidance of high light intensity has been observed and is probably an inherent predator-avoidance strategy (Fernö et al., 1995). Salmon seem to prefer a particular range of ambient temperatures (Oppedal et al., 2007), resulting in changes in prevailing swimming depth when subjected to temperatures outside their preferred range in a thermally stratified water column. Excessively high or low temperatures may be physically harmful (Saunders et al., 1975, Wilkie et al., 1997). Oxygen and salinity levels have recently been demonstrated to vary greatly within sea-cages at different depths and different times, however, whether salmon within cages actively respond to varying oxygen and salinity levels remains unknown (Johansson et al., 2006).

The social aspect of salmon behaviour is probably stronger in sea-cages than in the wild due to the unnaturally high densities. Caged salmon tend to maintain a certain distance to neighbouring fish and the cage itself (Juell, 1995). During non-feeding periods, salmon generally exhibit a uni-directional circular swimming pattern, tracing the inner perimeter of the cage wall (Fernö et al., 1995).

The main goal of this study was to simulate vertical migration patterns shown by caged populations of Atlantic salmon since vertical movement is of interest both in terms of fish welfare and cage management strategies (e.g. depth of artificial light sources, feeding regimes). We therefore built a Lagrangian model of fish behaviour based on quantitative data and qualitative knowledge on the behaviour of Atlantic salmon in Norwegian fish farms from the literature and then verified the model against three different scenarios from Johansson et al. (2006). The individual-based approach was chosen since it is better suited for modelling small-scale behaviours of individuals. Furthermore, this approach enables a greater degree of individual variation and provides model outputs on both individual and population levels.