Model support for treatment strategies in managing sea louse parasites and evolution of resistance on Atlantic salmon farms

Principal Investigator: Crawford Revie
Co-Investigators: Gregor McEwan, Maya Groner, Scott Bateman & Mark Fast

On salmon farms, the largest marine aquaculture industry in the world, sea lice are a major issue for producers. These parasites cause stress, reduced growth, and, sometimes, mortality in their hosts. They reduce farm output and profits, and may have adverse effects on nearby wild salmonid populations. Sea lice have evolved resistance to a number of commonly used chemical treatments in most major salmon-producing areas, and methods for managing this resistance are urgently needed.

This project investigated strategies for managing the evolution of resistance to chemical treatments by sea lice on salmon farms. While methods for slowing resistance evolution have been explored in terrestrial farm systems, this has not yet been done for aquatic systems. The lessons from terrestrial systems cannot be directly transferred, however, as aquatic environmental drivers (e.g. hydrodynamics, temperature, salinity) and treatment methods may create unique evolutionary processes.

We used both empirical and simulation methods to understand factors driving the evolution of sea lice resistance to chemical treatments. This included compiling and summarizing data on current treatment practices, as well as developing a software tool that models how treatments control sea lice, while tracking potential selection pressures for resistance. The tool can guide decision-makers with respect to available treatment options, expected outcomes, and uncertainty around those outcomes.