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dc.contributor.authorSilva, Edson
dc.contributor.authorCounillon, Francois Stephane
dc.contributor.authorBrajard, Julien
dc.contributor.authorPettersson, Lasse H
dc.contributor.authorNaustvoll, Lars Johan
dc.date.accessioned2023-05-31T11:12:04Z
dc.date.available2023-05-31T11:12:04Z
dc.date.created2023-05-11T09:31:33Z
dc.date.issued2023
dc.identifier.issn1568-9883
dc.identifier.urihttps://hdl.handle.net/11250/3069481
dc.description.abstractDinophysis acuminata produces Diarrhetic Shellfish Toxins (DST) that contaminate natural and farmed shellfish, leading to public health risks and economically impacting mussel farms. For this reason, there is a high interest in understanding and predicting D. acuminata blooms. This study assesses the environmental conditions and develops a sub-seasonal (7 - 28 days) forecast model to predict D. acuminata cells abundance in the Lyngen fjord located in northern Norway. A Support Vector Machine (SVM) model is trained to predict future D. acuminata cells abundance by using the past cell concentration, sea surface temperature (SST), Photosynthetic Active Radiation (PAR), and wind speed. Cells concentration of Dinophysis spp. are measured in-situ from 2006 to 2019, and SST, PAR, and surface wind speed are obtained by satellite remote sensing. D. acuminata only explains 40% of DST variability from 2006 to 2011, but it changes to 65% after 2011 when D. acuta prevalence reduced. The D. acuminata blooms can reach concentration up to 3954 cells l−1 and are restricted to the summer during warmer waters, varying from 7.8 to 12.7 °C. The forecast model predicts with fair accuracy the seasonal development of the blooms and the blooms amplitude, showing a coefficient of determination varying from 0.46 to 0.55. SST has been found to be a useful predictor for the seasonal development of the blooms, while the past cells abundance is needed for updating the current status and adjusting the blooms timing and amplitude. The calibrated model should be tested operationally in the future to provide an early warning of D. acuminata blooms in the Lyngen fjord. The approach can be generalized to other regions by recalibrating the model with local observations of D. acuminata blooms and remote sensing data.en_US
dc.language.isoengen_US
dc.titleForecasting harmful algae blooms: Application to Dinophysis acuminata in northern Norwayen_US
dc.title.alternativeForecasting harmful algae blooms: Application to Dinophysis acuminata in northern Norwayen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.volume126en_US
dc.source.journalHarmful Algaeen_US
dc.identifier.doi10.1016/j.hal.2023.102442
dc.identifier.cristin2146859
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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