New case study: SAVED - improving sea lice modelling for sustainable salmon farming

Understanding sea lice behaviour, dispersion and control

Sea lice remain a challenge in salmon farming and understanding how lice spread and behave is essential for sustainable aquaculture.

The SAVED (Sustainable Aquaculture: Validating Ectoparasite Dispersal) project set out to improve this understanding by creating a tool to validate sea lice dispersal models used by industry, researchers, and regulators. Valued at over £200k, the partners were the University of Strathclyde, Mowi Scotland, Scottish Government’s Marine Directorate, Norwegian Institute of Marine Research, SEPA, Firum, Scottish Sea Farms, Bakkafrost Scotland, and The NW Edge.

These models predict how lice move through the water, helping farmers plan treatments and regulators assess environmental risks. SAVED aimed to compare different models against real-world data to ensure accuracy and consistency across salmon-producing regions, including Scotland, Norway, and the Faroe Islands. The seven-month project focused on four areas:

• Data collection: gathering information on lice levels, environmental conditions, and wild fish populations.
• Model standardisation: creating a common format for sharing model outputs and metadata.
• Validation: comparing model predictions with field data from sentinel cages, plankton surveys, and farm lice counts.
• Testbench development: building a user-friendly platform to run comparisons.

Despite challenges such as limited data sharing and technical barriers, the project achieved several milestones:

• Developed a new mathematical model linking lice density in water to infection rates in fish, offering a faster and more efficient alternative to complex simulations.
• Created a prototype software tool for data exchange and validation.
• Published a standard framework for describing datasets to improve future collaboration.

The project highlighted key lessons: the need for better data infrastructure, clear sharing protocols, and specialised tools for annotating metadata. While SAVED did not fully deliver a universal validation tool, it laid the groundwork for future research and practical applications in lice management.

Next steps include publishing findings, securing funding for further development, and contributing to initiatives like SLIPd, which aim to improve sea lice modelling and support sustainable salmon farming worldwide.he full title of this project is ‘SAVED: validating models to predict and measure sea lice on salmon’.

Read the case study