Biofouling prediction in seaweed aquaculture

Project title: Biofouling prediction as a tool for spatial planning and yield optimisation in seaweed aquaculture

Seaweed production is an environmentally sustainable, zero-input industry that provides jobs and services arising from derived human food, agri-feed, fertilisers, biostimulants, products for cosmetics, and pharmaceuticals. Seaweed farming in Europe has significant potential for growth but is still in its early stages compared to Asian countries where the industry is mature and highly profitable.

In the nutrient-rich waters of the North Atlantic, biofouling in early (seed ropes) and late (harvest) seaweed growth can have unpredictable and devastating impacts on product yield and quality. Seaweed biofouling occurs when larval planktonic organisms settle on fronds and grow into adult forms (e.g., bryozoans, hydrozoans, tunicates). In the summer months, when seaweed are growing rapidly, biofouling can expand and completely cover seaweed within a period of 10 days, leaving a very narrow window for farmers to identify the problem and act.

In addition, although biofouling affects all seaweed farms across the North Atlantic coast, there is significant variation of the biofouling species and severity from site to site as well as from year to year. It is important to thus capture this variability using a network of sites spread across a wide geographical area that encompasses diverse environmental conditions.

This knowledge is crucial for understanding how the marine environment drives biofouling and for producing actionable, user-friendly tools for predicting biofouling species in space and time. This project unites a large consortium of seaweed producers, from the south of the UK to the Swedish and Norwegian coasts, technology providers and leading academic institutions to provide new planning tools and guidelines to the seaweed aquaculture industry.

Our partner network will monitor environmental conditions, plankton dynamics and emerging seaweed biofouling across a full seaweed production cycle on their farms. We will deploy extensive microscopic, molecular (eDNA), sensor-based (temperature, salinity, light) and analytical (nutrients, chlorophyll-a) techniques combined with novel experimental interventions on coastal aquaria to unravel the role of physical and chemical environment, plankton diversity and blade biofilm on biofouling formation.

Crucially, this information will be used to train state-of-the-art machine learning models that can help farmers predict the risk of biofouling species and timing on existing and planned farm locations. This knowledge can help farmers accurately plan their harvest time for maximising growth and implement targeted anti-fouling strategies depending on the predicted fouling species.

By providing this user-friendly predictive tool our project aims to help farms eliminate the excessive costs entailed in post-hoc processing of seaweed and farm monitoring (e.g., gas, boat time, staff time) and instead rely on accurate early warning using low-cost data feeds from existing in-situ automatised sensors. Our project also aims to help technology providers of seaweed farms understand which physical and chemical variables are most critical for biofouling prediction to help design marine sensors and software that are fit-for-purpose.

By fostering a North Atlantic network of farmers, solution providers and food safety experts, we aim to maximise benefits to the industry via knowledge exchange, technology transfer and policy development.