Aerial view of Killary Harbour with salmon aquaculture in foreground.


Sea lice model for the sustainable development of Atlantic salmon fisheries and aquaculture

Infestations of parasitic sea lice have a detrimental impact on both wild salmon stocks and farmed salmon (aquaculture). While sea lice pose little threat to Atlantic salmon in a natural setting, they can be a problem in more crowded situations, such as within or close to a salmon farm. Under such circumstances, sea lice numbers can increase dramatically, with transmission between fish more likely.

Supporting sustainable practice

Predictive modelling is a way of forecasting what might happen based on observed data. Following similar work in Norway and Scotland, we aim to develop a predictive model for Ireland using information collected on sea lice. The aim of this work is to support the sustainable development of aquaculture and wild salmon stock conservation by informing management practice and reducing the presence of sea lice and their negative impact.

International cooperation

Atlantic salmon move across international boundaries. Therefore, predictive models need to be standardized between countries where Atlantic salmon are found allowing us to optimise our practices. 

To predict, we first need to learn more

To build a predictive model, we collect real information on a number of important factors influencing sea lice and their environment. This includes information on their dispersal (how they move about), their distribution (where they are found) and their density (abundance within an area).  By including environmental data, such as information on local currents, depth, tides, salinity and temperature, we can learn more about what environmental factors influence sea lice the most. 

Making information go further

After collecting our data, we analyse it using statistical methods, a process which is commonly referred to as modelling. In simple terms, this means fitting the best mathematical formula possible to match the shape of the dataset. We can then experiment with the formula (model) to simulate possible scenarios and forecast outcomes. Modeling approaches like this make a small amount of information go a lot further and allows us to predict sea lice dispersal across large geographic areas without the need for intensive resource-heavy sampling.

LiceTrack is an EU-funded project sponsored by the North Atlantic Salmon Conservation Organisation (NASCO). This project is a collaboration between Inland Fisheries Ireland, the National University of Ireland Galway, the Norwegian Institute for Nature Research, Marine Scotland Science and the Institute of Marine Research in Norway.