Elaine Fileman is a senior plankton ecologist in the Marine Ecology & Society Group at PML. She has longstanding expertise in how zooplankton influence marine food webs and respond to environmental change. Her research began with a focus on the trophic role of microzooplankton, investigating predator–prey interactions across a wide range of marine environments including the NE Atlantic, Indian Ocean, Bellingshausen Sea, the Celtic Shelf, and coastal waters around Plymouth. This work helped to advance understanding of the ecological significance of microzooplankton in contrasting ecosystems.
Elaine’s interests have since expanded to include zooplankton feeding ecology, UV stress responses, interactions between plankton and microplastic particles and understanding pelagic biomass size spectra. In 2012 she led the development of PML’s FlowCam facility, establishing an automated plankton imaging capability that now supports long-term monitoring for the Western Channel Observatory – the longest near-continuous marine dataset in the world – as well as numerous postgraduate research projects, visiting scientists and commercial applications.
More recently, Elaine has contributed to the development of image-based and machine-learning approaches for plankton classification. She is part of the team delivering PML’s new automated offshore plankton imaging platform APICS (Automated, in situ Plankton Imaging and Classification System), which will deploy novel in situ camera systems (Imaging FlowCytobot and a Plankton Imager) automatically generating high-resolution images directly from a mooring 6 nautical miles south of Plymouth.
APICS itself will be a demonstrator project for the autonomous collection of high frequency biological data in the global coastal ocean, which will be critical for achieving the UN Decade of Ocean Science for Sustainability objective to have an ‘Observed Ocean’ in support of effective marine management.
Across her career, Elaine has been committed to improving how plankton communities are observed, classified and understood—integrating traditional taxonomy with emerging technologies to strengthen long‑term ecosystem monitoring.
