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Long-term microphytoplankton variability patterns using multivariate analyses: ecological and management implications

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Abstract

Microphytoplankton data along the southern Tunisian coasts have been monitored weekly since 1995. This study used the data collected during the period 2000–2007 to determine the temporal variability patterns and to characterize the geographical structures of microphytoplankton populations. The methodological approach consisted in isolating the temporal variability common to all sampled sites and in analyzing the “residual” site-specific component. Multivariate ordination methods were used to determine the seasonal and interannual variability. The temporal pattern shared by all sites was highlighted and the seasonal cycle of the most frequent phytoplankton communities contrasted the diatoms winter-spring species to the dinoflagellates summer-fall species. Multitable comparison allowed the identification of three areas exhibiting similar phytoplankton population variability. The results, despite the coastal location of sampling sites, indicated that hydrodynamic and geomorphologic properties of the different areas as well as anthropogenic activities play a key role in the structure of the phytoplankton communities.

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Authors and Affiliations

  1. Faculté des Sciences de Sfax, Université de Sfax, Route soukra Km 3,5, BP 802, CP 3018, Sfax, Tunisia

    Wafa Feki-Sahnoun

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

    Wafa Feki-Sahnoun, Asma Hamza & Mabrouka Mahfoudi

  3. Institut National des Sciences et Technologies de la Mer, 28 rue 2 mars 1934, Salammbô, 2025, Tunisia

    Malika Bel Hassen

  4. Centre de Biotechnologie de Sfax, Route Sidi Mansour Km 6, BP 1177, 3018, Sfax, Tunisia

    Ahmed Rebai

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  1. Wafa Feki-Sahnoun
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  2. Asma Hamza
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  3. Mabrouka Mahfoudi
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  4. Ahmed Rebai
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  5. Malika Bel Hassen
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Correspondence to Malika Bel Hassen.

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Feki-Sahnoun, W., Hamza, A., Mahfoudi, M. et al. Long-term microphytoplankton variability patterns using multivariate analyses: ecological and management implications. Environ Sci Pollut Res 21, 11481–11499 (2014). https://doi.org/10.1007/s11356-014-3009-2

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  • DOI: https://doi.org/10.1007/s11356-014-3009-2

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