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Applied simulations and Integrated modeling for the understanding of toxic and harmful algal blooms


Harmful algal blooms are known to periodically produce toxicity in shellfish and to kill farmed fish throughout Europe. The Atlantic coast of Europe is often affected by such blooms causing devastation to aquaculture industries due to closures of farms and large scale fish kills. The management of shellfish toxicity is well developed along the Atlantic margin in response to EU Directives, and the caged fish culture has also developed protocols to react to harmful blooms. Identification of the origins of HAB events are essential to policy makers and industry since the only mitigation action possible lies in their prediction as these are naturally occurring. Having the ability to forecast when such events might occur to give advanced warning of the impending problem to the aquaculture industry could be a very valuable tool. Many studies have elucidated the ocean circulation patterns along Europe’s Atlantic coast and today, mathematical models produce acceptable hindcasts of previously observed circulation patterns and short term prognostic forecasts. Satellite remotely sensed images of chlorophyll and temperature are also extremely valuable in detecting high biomass surface blooms of plankton and the oceanic features that often delimit their extent. Using a combination of both modeling and satellite image analysis the ASIMUTH project will produce short-term forecasts of harmful algal events along the European Atlantic coasts and deliver these data using mobile phone and internet technology. Aquaculturalists will be able to use these forecasts to plan harvesting operations or to alter husbandry practices at finfish sites temporarily while a harmful algal bloom passes through a particular area.

Call for proposal

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P75 AX07 Bantry

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Ireland Southern South-West
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Administrative Contact
Julie Maguire (Dr.)
EU contribution
€ 304 000,00

Participants (11)