Objectives

The overall objective of Phytoscope is to demonstrate the usefulness of high-resolved oceanographic data (in the 3 domains: spatial, temporal and taxonomical) for better discrimination of phytoplankton composition and dynamics, related to small and large scale processes. In order to overcome this challenge, different methodologies based on advanced observational technologies (i.e., hyperspectral optical sensors and high spatial-temporal resolution platforms) will be optimized by exploring two different approaches. A global-scale approach will be devoted to establish biogeochemical regions based on hyperspectral optical satellite data and retrievals of distribution of four major phytoplankton groups. A local-scale approach will investigate the short time-space scale variability of phytoplankton taxonomy, in particular in regions where the occurrence of toxic phytoplankton blooms have a critical environmental and socio-economical impact.

Specific objectives

1. Establishment of global biogeochemical (BGC) provinces based on the spatial and temporal distribution of four major phytoplankton groups derived via PhytoDOAS from satellite hyperspectral optical data

  • Evaluation of the global data derived via PhytoDOAS with the in situ data on pigment and optical properties.
  • Comparison of the PhytoDOAS-based BGC provinces with other methods deriving BGC provinces from satellite data.
  • Temporal variability assessment of the spatial distribution of the identified BGC provinces (year to year analysis).

 

2. Assessment of variability of phytoplankton biodiversity in local regions

  • Performance of intensive collections of high resolution physical and optical measurements in the local site of interest by using hyperspectral instruments and autonomous platforms (i.e., underwater AUVs and aerial UAVs).
  • Characterization of phytoplankton community composition by exploring in situ pigment data and optical properties.
  • Local assessment of the short time-space scale variability of phytoplankton dynamics.