Articles | Volume 13, issue 6
Research article
30 Mar 2016
Research article |  | 30 Mar 2016

Interannual variability of the Mediterranean trophic regimes from ocean color satellites

Nicolas Mayot, Fabrizio D'Ortenzio, Maurizio Ribera d'Alcalà, Héloïse Lavigne, and Hervé Claustre

Abstract. D'Ortenzio and Ribera d'Alcalà (2009, DR09 hereafter) divided the Mediterranean Sea into “bioregions” based on the climatological seasonality (phenology) of phytoplankton. Here we investigate the interannual variability of this bioregionalization. Using 16 years of available ocean color observations (i.e., SeaWiFS and MODIS), we analyzed the spatial distribution of the DR09 trophic regimes on an annual basis. Additionally, we identified new trophic regimes, exhibiting seasonal cycles of phytoplankton biomass different from the DR09 climatological description and named “Anomalous”. Overall, the classification of the Mediterranean phytoplankton phenology proposed by DR09 (i.e., “No Bloom”, “Intermittently”, “Bloom” and “Coastal”), is confirmed to be representative of most of the Mediterranean phytoplankton phenologies. The mean spatial distribution of these trophic regimes (i.e., bioregions) over the 16 years studied is also similar to the one proposed by DR09, although some annual variations were observed at regional scale. Discrepancies with the DR09 study were related to interannual variability in the sub-basin forcing: winter deep convection events, frontal instabilities, inflow of Atlantic or Black Sea Waters and river run-off. The large assortment of phytoplankton phenologies identified in the Mediterranean Sea is thus verified at the interannual scale, further supporting the “sentinel” role of this basin for detecting the impact of climate changes on the pelagic environment.

Short summary
The present manuscript provides an analysis of the interannual variability of the phytoplankton seasonality in the Mediterranean Sea, based on 16 years of ocean color data. Important interannual variabilities at regional scale were highlighted and related to environmental factors. Our results demonstrate also that seasonal patterns retrieved from satellite allow to identify the evolution of an oceanic area and to summarize the huge quantity of information that the satellite data offer.
Final-revised paper