Plankton imaging


Plankton imaging yields abundance and biomass information of marine phytoplankton and zooplankton. As it generates a digital copy of a plankter, plankton imaging allows to retroactively go back in time and work on unchanged samples not subject to decay or disintegration. The strength of plankton imaging is seen in the fast processing, allowing for a quick detection of ongoing changes in the marine environment.  

Organisms of interest

Zooplankton and phytoplankton are two key groups of small aquatic organisms which play important roles in shallow coastal waters. Phytoplankton, consisting of microscopic algae, are primary producers that form the base of the food web in these ecosystems. Zooplankton, a diverse group of small animals, feed on phytoplankton and, in turn, serve as a food source for higher aquatic species. The dynamics of phytoplankton and zooplankton communities are closely linked to the health and functioning of shallow coastal waters and are sensitive to environmental pressures such as climate change, pollution, and habitat degradation. 




Typically, imaging sensors are classified in two groups: in-situ imaging sensors and laboratory-based sensors. 

In-situ imaging sensors are deployed in the field by towing them behind a research vessel or by attaching the sensor to a fixed mooring in the water. Three sensors are considered, the Video Plankton Recorder (VPR), the CPICS (Continuous Particle Imaging Classification System) and the Flow Cytometer (FCM). The strength of these techniques is the real-time data collection: particles are photographed in the water in their natural environment. Simultaneous to each picture, field measurements (e.g., seawater temperature, salinity, turbidity, pressure, ...), essential measurements of the depicted particles (e.g. length, height, circularity…) and classification data (e.g., name of the particle that has been photographed) are stored as well. This yields an especially strong dataset important to both marine biologists and geologists. 

Laboratory-based imaging sensors are deployed in a laboratory and processes collected samples. Two sensors are considered, the ZooSCAN and the FlowCAM (Flow Cytometer and Microscope). Both sensors generate high resolution pictures or vignettes which are analyzed by semi-automatic computer processing: all organisms/particles from the samples are annotated to several taxonomic groups (e.g. Appendicularia, Gammaridae, Calanoida, etc.), but also debris, sand, plastics, etc. The latest machine learning algorithm allows high recognition levels; complementary manual sorting is recommended to achieve a high number of taxonomic groups. Although the resolution of the digitized zooplankton images is lower than that of the images obtained using a binocular microscope, the techniques have proven to be more than adequate for large sample sets. 


Spatial coverage

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Plankton imaging is a crucial part of the LifeWatch campaigns. During monthly campaigns, zooplankton is sampled at 9 onshore stations; during seasonal campaigns, zooplankton is sampled at 17 on and offshore stations. These samples brough back to OIS and are processed shortly after collecting. All protocols used for plankton imaging are described (Mortelmans et al., 2019; Amadei Martinez et al., 2020) and data is available via the LifeWatch data explorers on zooplankton and phytoplankton. Finally, fixed datasets are released on a yearly basis further contributing to FAIR data, accessible for zooplankton and phytoplankton. LifeWatch further contributes by providing experience to users of the infrastructure. 

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