Sea lice are currently the main obstacle to increasing production in marine salmon aquaculture across Europe. Treatments for sea lice are also one of the largest contributors to fish mortality and a major factor in the industry's carbon footprint. As ocean temperatures rise due to climate change, sea lice are expected to become an even greater challenge, with faster development rates, increased egg production, and higher infection pressure.
Current models used to guide sea lice management are helpful at the regional level but fall short when applied to individual farms. They are unable to accurately simulate future scenarios that involve changes in climate, farm locations, or production practices, limiting their practical use for producers.
Within the OCCAM project (https://occamproject.eu/), Case Study 3 seeks to address these challenges through the development of a Decision support tool (DST) for sea lice management. This tool combines a sea lice population model, already used by the Faroese salmon industry, with a hydrodynamic particle tracking system (FarCoast + LADiM) that will be further integrated into climate models. This enables realistic simulations of how lice larvae move and develop under changing environmental conditions.
The Faroe Islands provide an ideal test case due to the limited number of farms and consistent third-party sea lice data, allowing for accurate model validation.
With this DST, salmon farmers will be able to optimise operations by evaluating farm location, stocking density, production cycle length, and timing—all while accounting for environmental change. In parallel, the tool will support policymakers in setting more effective sea lice thresholds and improving marine spatial planning. This solution offers a practical, science-based approach to controlling sea lice sustainably in a warming world.
The initial model development and our first prototype will be presented.