NANO Alumni Yosra Khammeri and colleagues published the following article in the Journal of Sea Research:

Ultraphytoplankton community composition in Southwestern and Eastern Mediterranean Basin: Relationships to water mass properties and nutrients

Khammeri et al. (2020) Journal of Sea Research, DOI 10.1016/j.seares.2020.101875

Abstract

The composition, biomass, and spatial and vertical distribution of ultraphytoplankton (< 10 μm) were investigated at the single-cell level by flow cytometry during the INCOMMET oceanographic cruise carried out during the fall of November 2013, covering eleven stations spread out along coastal Tunisian waters at less than 100 m depth. Flow cytometry analysis of samples taken at different stations and depths allowed the determination of five major groups of ultraphytoplankton; among them two populations of pico-cyanobacteria Synechococcus and Prochlorococcus, picoeukaryotes, nanoeukaryotes and cryptophytes. In addition to these autotrophic groups, three unknown groups were resolved and were distinguished by their fluorescence and size signals. The unknown groups’ integrated biomass was larger than that of the other ultraphytoplankton components. The abundance of picoeukaryotes, nanoeukaryotes and cryptophytes increased gradually southwards towards the Gulf of Gabès, whereas Prochlorococcus were more abundant in the Gulf of Hammamet at more than 60 m depth. Structural equation modeling analysis showed weak links between most of the cell groups and nutrients concentrations. Clustering analysis based on the abundance of the phytoplankton groups resulted in aggregation into three clusters and two major zones, discriminating the Gulf of Gabès from the more northern Bays. The results suggest that the physical features,  essentially the water mass properties, were the main drivers shaping the ultraphytoplankton community composition and that the autotrophic biomasses were not determined by nutrient control.

Keywords

  • Ultraphytoplankton
  • Flow cytometry
  • Nutrients
  • Clustering
  • Structural equation modeling

Link for the publication here

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