AQUASPECT

Plankton are drifting aquatic organisms that cannot swim actively against currents. They are incredibly diverse, ranging in size from sub-microns to several meters; the largest plankton can be over a million times bigger than the smallest.

Plankton form the foundation of marine food webs. Phytoplankton, plant-like plankton that carry out photosynthesis, generate around half of Earth’s primary production. Their organic material is eaten by herbivorous zooplankton, which in turn feed larger animals such as fish, marine mammals, and seabirds.

Because plankton respond quickly to changes in their environment, they serve as valuable indicators of water quality, ecosystem health, and environmental change at both local and global scales. Plankton and the particles they produce also play a major role in the global carbon cycle, helping transport carbon from the ocean surface to deeper waters, where it can be stored away from the atmosphere for centuries.

Due to their central role in ecosystem functioning and climate regulation, plankton biomass and diversity are recognized as Essential Ocean Variables (EOVs) and Essential Biodiversity Variables (EBVs). They are key indicators in marine ecosystem assessments under the Marine Strategy Framework Directive (MSFD), the EU’s legally binding framework for evaluating the environmental status of European waters.

Recognizing the importance of plankton, AQUASPECT will collect, harmonize, and integrate plankton data into the EU and regional DTOs, joining other EU digital twin initiatives (DTO-BioFlow, EDITO-Infra, BioDT, Iliad). 

Plankton are very difficult to study, given their huge size range and diversity, with different instruments and technologies needed to capture the full size spectrum. Quantitative imaging is currently the only approach that can consistently record individual plankton and particles at the spatial resolution and frequency needed to understand ecosystem functioning.

Quantitative imaging instruments work by capturing images of organisms and particles within a known volume of water. This makes it possible to calculate their abundance, biomass, biovolume, and the size distribution of all imaged objects. As these instruments produce huge amounts of images, machine learning can be used to classify plankton automatically, greatly reducing the time and effort required for manual plankton identification.

AQUASPECT uses several quantitative imaging instruments, including the Underwater Vision Profiler 6 and 6-micro (UVP6 and UVP6m) and the Continuous Plankton Imaging Counting and Sizing system (CPICS).