Accurate modelling of sea lice dispersal is crucial for the planning of new aquaculture sites.
Photo: SAIC.
Researchers from Scotland, Norway, and the Faroe Islands have launched a collaborative project to improve the accuracy of sea lice dispersion predictions, vital for maintaining fish health in aquaculture.
The initiative, named SAVED – Sustainable Aquaculture: Validating Ectoparasite Dispersal (Models) – aims to develop a benchmark testing tool that will validate the outcomes of existing sea lice dispersion models.
SAVED's objective is to create a system for verifying the accuracy of various dispersion models used by industry professionals, academics, and regulators.
By introducing a standardized approach to model evaluation, the project seeks to enhance the reliability of predictions regarding sea lice risks to wild fish populations.
Currently, the aquaculture sector uses several dispersal modelling tools to tackle the problem of sea lice, and to plan new aquaculture sites. However, these models often yield different results due to differing assumptions, researchers point out.
The new benchmark tool produced by SAVED aims to provide a universally accepted method for comparing these models and their data, resulting in more precise and reliable predictions.
“Different sea lice dispersal models use varying complex mathematical techniques, but it is important to ensure that the same set of input data returns a valid result, no matter which product is used," said Dr Meadhbh Moriarty, senior aquatic epidemiological modeller for the Scottish Government’s Marine Directorate, in a press announcement.
Sea lice attached to salmon skin.
Photo: Norwegian Institute of Marine Research.
“To reduce the variability, we are creating a bespoke Python script that can be applied to each model and ensure it is fit for purpose," Moriarty explained. "Another important aspect is the development of a ‘data dictionary’ which can help to guarantee that everyone using these models is interpreting the figures in the same way."
"Having input from so many partners across three of the major salmon-producing nations, each with its own governance system, is a big bonus for the project. We hope that the end result will be adopted by the aquaculture sector at scale, helping to better manage the threat of sea lice," Moriarty added.
The proposed free online tool will incorporate elements from existing physical and behavioral models, considering factors such as wind, tides, sea lice movement, and their response to light.
By merging data from Scotland, Norway, and the Faroe Islands, researchers aim to understand the uncertainties in each nation's model results.
The project, which recently received additional funding from Scotland's Sustainable Aquaculture Innovation Centre (SAIC), is run by a consortium composed of the University of Strathclyde, Mowi Scotland, Scottish Sea Farms, Bakkafrost Scotland, the Scottish Government’s Marine Directorate, the Norwegian Institute of Marine Research, Firum Aquaculture Research Station of the Faroes, and The NW Edge, with the Scottish Environment Protection Agency (SEPA) involved as an observer.
“In recent years we have seen growing demand for data-driven practices to mitigate fish health concerns, including sea lice modelling. However, valuable insight can only be based on quality data, so the tools must return dependable results that can be interpreted consistently," said Heather Jones, CEO of SAIC, one of the main funders.
"This project is a fantastic example of international collaboration for the greater good. The benchmark could have significant benefits in terms of helping bring about proportionate regulation and enabling the future growth and development of farming," she added.
Philip Gillibrand, oceanographer and hydrodynamic modeller at Mowi, added: “We hope that this project will provide a tool to make the cross-comparison of different sea lice dispersal models, and their evaluation against observations, as consistent, rigorous, transparent and streamlined as possible.”
