July 25, 2024
New tool developed to enhance sea lice dispersion predictions
Researchers from Scotland, Norway, and the Faroe Islands are developing a new tool to improve predictions about sea lice dispersion in water, aiming to enhance fish health through more accurate data, Global Seafood Alliance reported.
The project, known as SAVED – Sustainable Aquaculture: Validating Ectoparasite Dispersal (Models) – has recently received funding from the Sustainable Aquaculture Innovation Centre (SAIC). The goal is to create a system to validate the results of existing dispersion models used by producers, academics, and regulatory bodies.
"In recent years we have seen growing demand for data-driven practices to mitigate fish health concerns, including sea lice modelling," said Heather Jones, CEO of SAIC. "However, valuable insight can only be based on quality data, so the tools must return dependable results that can be interpreted consistently. The benchmark could have significant benefits in terms of helping bring about proportionate regulation and enabling the future growth and development of farming."
A variety of dispersal modelling tools are available to help manage sea lice and inform decisions about future aquaculture sites. However, each model operates with a different set of assumptions, leading to varying results.
A new standardised tool that allows for the comparison of these models and their data could create a more reliable evaluation method. This could lead to better predictions about the risk sea lice pose to wild fish populations.
"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 modeler for the Scottish government's Marine Directorate. "To reduce the variability, we are creating a bespoke Python script that can be applied to each model to ensure it is fit for purpose."
The free online tool will be informed by several existing physical and behavioural models, which include elements such as winds and tides, the movement of sea lice in the water, and their reaction to light exposure. Researchers will also combine data from Scotland, Norway, and the Faroe Islands to understand the differences and uncertainties in the results from each country.
With a new standardised approach, academics, producers, and regulators using any of the current models will be able to use the online benchmark tool to provide an additional level of validation, ensuring the output is as reliable as possible.
"Another important aspect is the development of a 'data dictionary' which can help guarantee that everyone using these models is interpreting the figures in the same way," said Moriarty. "Having input from partners across three major salmon-producing nations, each with its own governance system, is a big bonus for the project. We hope that the result will be adopted by the aquaculture sector at scale, helping to better manage the threat of sea lice."
- Global Seafood Alliance