When scientists monitor plankton, they usually have to do this manually on site. An automated technique could therefore significantly improve the frequency, duration and range of plankton monitoring. At the Plymouth Marine Laboratory, this might soon become a reality.

As part of a £6.6 million Natural Environment Research Council (NERC) funding package for UK environmental science equipment, PML has been awarded £651k for a bespoke ‘Automated, in situ Plankton Imaging and Classification System’ (APICS) to help radically improve the understanding of how environmental changes are affecting plankton, the microscopic organisms at the foundation of the marine food chain which also play a vital role in generating oxygen for the planet.

The new automated system, which uses renewable energy to power the equipment, is designed for remote deployment in the Western Channel Observatory (the marine biodiversity reference site in the Western English Channel). By utilising two submersible devices (an Imaging FlowCytobot and a Plankton Imager), the system will be able to record a step change in the frequency and range of marine plankton measurements. By gathering images of these organisms at varying sizes, the system can then be automatically classified using machine learning software.

Dr James Clark, Marine Ecosystem Modeller at Plymouth Marine Laboratory said: “For the first time in the world, APICS will enable autonomous, long-term, broad size-spectrum measurements of plankton to be made at sub-daily time scales.”

“In addition to the two camera systems, this will be made possible through machine learning software, which will permit the data to be collected and processed at speeds which are orders of magnitude faster than manual processing procedures. This will allow sub-daily changes – for example, relating to day-night or tidal cycles – to be resolved while also dramatically reducing operating costs,” he added.

The APICS system is expected to start operating in early 2023 at the Western Channel Observatory. The researchers hope that the system will help them study trends in plankton abundance in fine detail, ultimately leading to a better understanding of plankton community dynamics and relationships.

Photography courtesy of Pixabay.

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