Zooplankton dynamics at high frequency by digital image analysis and Deep learning

The project in a nutshell

Zooplankton is essential for lake biodiversity, energy, and nutrient flows, including in Lake Geneva where it influences algal and fish stocks. However, these assumptions are supported mainly by indirect evidence. Traditional microscopic counting of zooplankton, conducted monthly, has been a time-consuming barrier. Digital imaging and Deep Learning now permit more frequent sample processing, enabling direct observation of zooplankton dynamics. While this method is not currently spreading in Oceanography, it has barely been used in lakes.

Team members

: Marie-Elodie PERGA – Researcher

: Nicolas ESCOFFIER – Postdoc

: Santona KHATUN – Postdoc

: Isabel HERR – PhD Student

: Jérémy KELLER – Master student

: Lucas NICOLLIER – Student assistant

: Dan ANDERSSON – Student assistant

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