Phytoplankton Diversity in the Mediterranean Sea From Satellite Data Using Self‐Organizing Maps

Abstract

We present a new method to identify phytoplankton functional types (PFTs) in the Mediterranean Sea from ocean color data (GlobColour data in the present study) and AVHRR sea surface temperature. The principle of the method is constituted by two very fine clustering algorithms, one mapping the relationship between the satellite data and the pigments and the other between the pigments and the PFTs. The clustering algorithms are constituted of two efficient self‐organizing maps, which are neural network classifiers. We were able to identify and estimate the percentage of six PFTs: haptophytes, chlorophytes, cryptophytes, Synechococcus, Prochlorococcus, and diatoms. We found that these PFTs present a peculiar variability due to the complex physical and biogeochemical characteristics of the Mediterranean Sea: Haptophytes and chlorophytes dominate during winter and mainly in the western Mediterranean basin, while Synechococcus and Prochlorococcus dominate during summer. The dominance of diatoms was mainly observed in spring in the Balearic Sea in response to deep water convection phenomena and near the coastline and estuaries due to important continental inputs. Cryptophytes present a weak concentration in the Aegean Sea in autumn. The validation tests performed on in situ matchups showed satisfying results and proved the ability of the method to reconstruct efficiently the spatiotemporal patterns of phytoplankton groups in the Mediterranean Sea. The method can easily be applied to other oceanic regions.

Impact of Climate Change on Surface Stirring and Transport in the Mediterranean Sea

“…Consistently with Table 1, the boundary strength map for = 30 days suggests the presence of more, smaller provinces with a denser boundary presence; on the contrary, for = 90 we can recognize larger provinces with associated sparser boundaries ( Figures S9 and S10). Moreover, note that the spatial patterns of boundary strength match qualitatively quite well eco-regionalization exercises (Ayata et al, 2018;Basterretxea et al, 2018;d'Ortenzio & Ribera d'Alcalà, 2009;El Hourany et al, 2019). This suggests that transport-based regionalization, like the one we provide, play a role in shaping plankton biogeography and biogeochemical regimes across the surface ocean.…”

Evidencing the Impact of Climate Change on the Phytoplankton Community of the Mediterranean Sea Through a Bioregionalization Approach

“…The phytoplankton community in the open waters of the Mediterranean Sea is dominated by nanophytoplankton types such as Haptophytes and Chlorophytes in winter and Synechococcus in summer (El Hourany, Abboud-Abi Saab, Faour, Mejia, et al, 2019;Navarro et al, 2014Navarro et al, , 2017. This is seen in the different EL HOURANY ET AL.…”

“…We observed a noticeable temperature increase in the surface layers of the Sea and surprisingly a constant Chla concentration over the studied period. The machine learning method in (El Hourany, Abboud-Abi Saab, Faour, Mejia, et al, 2019) allowed us to evidence a noticeable change in the PFT community composition so that Diatom and haptophyte dominations are replaced by Cyanobacteria development. The most affected bioregions by the diatom decrease are the marginal ones (C1, C2, C3, and C7).…”

Modelling mussel (<i>Mytilus spp.</i>) microplastic accumulation

“…Furthermore, it may be assumed that the adopted range (standard deviation is also multiplied by a factor of 2) includes also the smaller particles sized between 50 and < 330 µm, which have been found in mussel tissue (Digka et al, 2018a) but were overlooked during the seawater sampling due to the manta net's mesh size (> 330 µm). According to Enders et al (2015) the relative abundance of small particles (50-300 µm) compared to particles larger than 300 µm is approximately 50 %.…”