When certain types of toxic algae grow in large quantities, they may create harmful algae blooms. Such blooms can make shellfish and mussels meant for consumption toxic. Predicting when and where algae will grow to harmful levels is beneficial for deciding on mitigation measures and prevent consumption. The Nansen Center has developed models to make such predictions possible for the entire Norwegian coast.
To limit the risk of consuming shellfish and mussels contaminated by toxins produced by different types of algae, the Norwegian Food Safety Authority conducts a national monitoring program once a week for 32 coastal locations and inform about levels of algae toxins in mussels. They also provide monthly information on measured toxins in shellfish. During times when the risk for harmful amounts of algae being present near shellfish farms is high, more frequent updates would be beneficial, as algae abundances can change quickly both in time and space under ideal environmental conditions.
In a recent study led by Edson Silva, researchers from the Nansen Center and the Institute for Marine Research developed a method to estimate the risk of harmful algae blooms based on measurements of the environmental water conditions – even for locations where no direct monitoring data is available. The developed method can be used to provide maps of when and where the different harmful algae species occur in the nearshore coastal waters. Edson Silva and his colleagues made use of machine learning techniques and different kinds of environmental data from satellite observations, models, and historical data from the national program monitoring the abundance of toxic algae.
The developed method is quality-controlled and can be employed for the entire Norwegian coast and can be adapted for any other waters where the relevant environmental and algae data are available. It has the potential to strengthen the current toxin monitoring and help aquaculture business actors to be better informed, and to provide support to mitigation actions against harmful algae blooms by combining the model with seasonal predictions. This method is therefore a promising tool to complement the monitoring program when the risk is increased and guide the public from shellfish poisoning as well as reduce economic losses from harmful algae blooms affecting shellfish farms.
Key researchers: Edson Silva, Julien Brajard, François Counillon, Lasse H. Pettersson
