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10th Scientific Meeting of Classification and Data Analysys Group of Italian Sociery of Statistics
S.Margherita di Pula (Cagliari), Italy - October 8-10, 2015
Case studies in Data Mining from Ligurian companies
Statistical methods for the analysis of Ostreopsis ovata bloom events from meteo-marine data
Ennio Ottaviani (OnAIR srl)
Andrea Pedroncini (DHI Italia)
Valentina Asnaghi, Mariachiara Chiantore (DISTAV, Univ.Genova)
Rosella Bertolotto (ARPAL)
Ostreopsis ovata, a benthic toxic marine dinoflagellate, has been recorded along Italian coasts since
the '90 but large bloom events have been reported only in recent years. In 2005, a monitoring
programme has been set up and a time series of cell abundances has been collected for several sites
along the Ligurian coast, together with a range of related environmental variables. Ostreopsis
identification and counting requires a great deal of taxonomic expertise and is time consuming and
impractical for processing a large number of samples in a monitoring perspective. On the contrary,
the environmental variables can be sampled daily and everywhere by exploiting large datasets of
available meteo-marine data, derived from measurements or from numerical models. For this reason,
one of the main objectives of the pan-Mediterranean project M3-HABs (Risk Monitoring,
Modelling and Mitigation of Benthic Harmful Algal Blooms along Mediterranean coasts) funded by
EU in the framework of the ENPI-CBCMED Programme is to provide a predictive modelling tool,
able to forecast Ostreopsis cells abundance as a function of meteo-marine data. The tool will be
able to predict expected cell abundances along the coast (regression mode) and to alert the Regional
Agency when/where a given alarm threshold is probably exceeded (classification mode), in order to
trigger the emergency procedures. In the present work, we compared several statistical models for
the correlation between cell abundances and the related environmental variables, in order to
implement the first prototype of the automatic tool for the prediction and classification of
Ostreopsis ovata blooms.