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Using a naive Bayes classifier to explore the factors driving the harmful dinoflagellate Karenia selliformis blooms in a southeastern Mediterranean lagoon

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Abstract

The blooms of the toxic dinoflagellate Karenia selliformis can be predicted with accuracy derived from knowledge of the main forcing variables. A naive Bayes classifier modeling framework, a member of the Bayesian network family, is used to identify the phytoplankton community and the physical and meteorological parameters involving K. selliformis blooms in the eutrophic Boughrara Lagoon (BL), Tunisia. The proposed model takes into account the physical environment parameters (salinity, water temperature, tide amplitude), meteorological constraints (evaporation, air temperature, insolation, rainfall, atmospheric pressure, and humidity), phytoplankton groups (diatoms, dinoflagellates, cyanobacteria, Euglenophyceae), and the sampling months on K. selliformis blooms. The shift to highest salinity and atmospheric pressure, associated with reduced tide, are the most favorable conditions for K. selliformis blooms in BL. The results show that K. selliformis formed nearly monospecific blooms. A shift in species composition was pointed out between the bloom and non-bloom conditions. The Euglenophycea and some dinoflagellates like Peridinium minimum, Prorocentrum minimum, Prorocentrum micans, Prorocentrum gracile, Protoperidinium minutum, and Scrippsiella trochoidea appeared during blooms, whereas diatoms, diazotrophic cyanobacteria, and dinoflagellates (Akaskiwo sanguinea, Karlodinium veneficum, Gyrodinium spirale, Oxyrrhis marina, Polykrikos kofoidii) were observed under non-bloom conditions. This study highlighted the most favorable physical and meteorological conditions for K. selliformis bloom occurrences and also pointed out species indicators for bloom establishment and others for non-bloom conditions. Monitoring the dynamics of these species with the associated physical and meteorological variability offers valuable information to plan for the best options for prediction of potentially toxic blooms of K. selliformis and associated dystrophic consequences.

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Abbreviations

BL:

Boughrara Lagoon

HABs:

Harmful algal blooms

GLMM:

Generalized linear mixed-effect model

NB:

Naive Bayes classifier

CPT:

Conditional probability table

INM:

Tunisian National Meteorological Institute

SamIam:

Sensitivity Analysis, Modeling, Inference And More software

G. spirale :

Gyrodinium spirale

K. selliformis. Ks:

Karenia selliformis

K. mikimotoi :

Karenia mikimotoi

K. brevis :

Karenia brevis

K. veneficum :

Karlodinium veneficum

P. micans :

Prorocentrum micans

P. minimum :

Prorocentrum minimum

S. trochoidea :

Scrippsiella trochoidea

MTDs:

Mixotrophic dinoflagellates

HTDs:

Heterotrophic dinoflagellates

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Acknowledgments

The authors wish to thank Dr. Anja KREINER from National Marine Information and Research Centre, Swakopmund, Namibia, for having edited the English of this paper.

Funding

This work was supported by the EMORI (L’Education, la MObilité, la Recherche et l’Innovation)/MOBIDOC (MOBIlisation de DOCteur pour la réalisation de Travaux de recherche dans l’entreprise) funded project (post-doctoral grant for the first author) 2018–2020.

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Authors and Affiliations

  1. Institut National des Sciences et Technologies de la Mer, Centre de Sfax, Rue Madagascar, BP 1035, 3018, Sfax, Tunisia

    Wafa Feki-Sahnoun, Asma Hamza & Mabrouka Mahfoudi

  2. Faculté des Sciences Économiques et de Gestion de Sfax, Route de l’Aéroport Km 4, 3018, Sfax, Tunisia

    Hasna Njah

  3. Laboratoire de Multimedia, InfoRmation Systems and Advanced Computing Laboratory, Pôle technologique de Sfax, Route de Tunis Km 10, BP 242, 3021, Sfax, Tunisia

    Hasna Njah

  4. Institut National des Sciences et Technologies de la Mer (INSTM), 28 rue 2 mars 1934, 2025, Salammbô, Tunisia

    Nouha Barraj & Malika Bel Hassen

  5. Centre de Biotechnologie de Sfax, Route Sidi Mansour Km 6, BP 802, 3019, Sfax, Tunisia

    Ahmed Rebai

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  1. Wafa Feki-Sahnoun
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  2. Hasna Njah
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  3. Asma Hamza
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Correspondence to Wafa Feki-Sahnoun.

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Feki-Sahnoun, W., Njah, H., Hamza, A. et al. Using a naive Bayes classifier to explore the factors driving the harmful dinoflagellate Karenia selliformis blooms in a southeastern Mediterranean lagoon. Ocean Dynamics 70, 897–911 (2020). https://doi.org/10.1007/s10236-020-01365-5

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  • DOI: https://doi.org/10.1007/s10236-020-01365-5

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