Details of Award
NERC Reference : NE/X006018/1
Automated in situ Plankton Imaging and Classification System (APICS)
Grant Award
- Principal Investigator:
- Dr J R Clark, Plymouth Marine Laboratory, Plymouth Marine Lab
- Co-Investigator:
- Mrs C Widdicombe, Plymouth Marine Laboratory, Plymouth Marine Lab
- Co-Investigator:
- Professor JR Fishwick, Plymouth Marine Laboratory, Plymouth Marine Lab
- Co-Investigator:
- Mrs ES Fileman, Plymouth Marine Laboratory, Plymouth Marine Lab
- Grant held at:
- Plymouth Marine Laboratory, Plymouth Marine Lab
- Science Area:
- Marine
- Overall Classification:
- Unknown
- ENRIs:
- Biodiversity
- Environmental Risks and Hazards
- Global Change
- Natural Resource Management
- Science Topics:
- Biodiversity
- Invasive species
- Marine communities
- Microbes
- Population dynamics
- Succession
- Trophic structures
- Community Ecology
- Survey & Monitoring
- Biodiversity
- Coastal ecosystems
- Ecosystem management
- Food webs
- Ecosystem Scale Processes
- Microorganisms
- Plankton
- Plankton recorders
- Survey & Monitoring
- Abstract:
- Marine plankton are defined as organisms with zero or small swimming velocities, which move passively with ocean currents. The definition covers a taxonomically and morphologically diverse group of organisms that span many phyla and tens of thousands of species. In size alone, plankton span many orders of magnitude, ranging from sub-micron scale unicellular life forms up to large jelly fish that can measure up to a meter in diameter. Plankton sustain all other forms of multicellular life in the ocean. Photosynthetic members account for approximately 50 % of global primary production. The energy captured by photosynthetic plankton is passed up the food chain through predatory interactions, where it supports the growth of commercially important species of fish and shellfish. Plankton also regulate Earth's climate, through their role in the global carbon cycle. Key to understanding the ecology of plankton and the functional role they play in marine ecosystems, is the ability to follow how plankton abundances and community composition change in time. This usually requires that organisms be visualised and classified. Historically, such measurements have been made aboard research vessels in often remote locations. The measurements are expensive and time consuming to make. The potential benefits of automating the process have been appreciated for years. However, it has taken time for suitable, commercially available instruments to become available. In this project, we will configure an Automated, in situ Plankton Imaging and Classification System (APICS) for studying plankton dynamics at a long-term time series site, Station L4 in the Western English Channel. Images will be automatically classified using machine learning software and made publicly available. The system will enable a 100-fold increase in the frequency at which plankton data is collected. Furthermore, through automation, the system will dramatically reduce operating costs compared to current, manual ship-based sampling and classification procedures. In a world first, APICS will automatically acquire image data in situ for plankton spanning 3-4 orders of magnitude in size, ranging from 10 microns up to 20 mm. Embedded within the Western Channel Observatory (WCO), where other physical and chemical variables are routinely measured, it will provide a unique system for studying high-frequency temporal changes in the marine environment. Over the past 30 years, data from the WCO have shown marked changes in plankton abundances, with reductions in the number of diatoms and large copepods, and an increase in the number of meroplankton. APICS will enable such trends to be studied in fine detail, leading to improved understanding of plankton community dynamics, and the relationship between plankton and marine ecosystems as a whole.
- NERC Reference:
- NE/X006018/1
- Grant Stage:
- Completed
- Scheme:
- Capital
- Grant Status:
- Closed
- Programme:
- Capital Call
This grant award has a total value of £651,197
FDAB - Financial Details (Award breakdown by headings)
| DI - Equipment |
|---|
| £651,198 |
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