Plankton community ecology and ecosystem research is currently hampered by the bottleneck of acquiring species-level information from the communities due to the slow analysis with traditional microscopy. The FASTVISION-plus consortium will combine front-line plankton imaging instrumentation and taxonomic expertise of the Finnish Environment Institute and the computer vision and image analysis excellence of the Lappeenranta-Lahti University of Technology.
The project will use images of microscopic plankton provided by automated imaging instruments and other measurements to train image recognition software for species identification using multimodal machine learning approaches that produce interoperable data across instruments and habitats. This big data of plankton community composition, collected through experimental and field studies with an unprecedented high resolution, will be applied to testing key hypotheses in plankton community ecology, biodiversity and ecosystem functioning.