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Séminaire

The Art and Science of Zooglider

 

Claudine Arendt / Sven Gastauer / Mark D. Ohman (Luxembourg and The Netherlands / Thünen Institute for Sea Fisheries/Scripps Institution of Oceanography): The Art and Science of Zooglider

Sorbonne Université  4 place Jussieu  75005  Paris  Sorbonne Université LOCEAN Couloir 45-55 4e étage pièce 417

Date 24/11/2023
Organisateur LOCEAN

Description

Zooglider, an autonomous underwater robot, samples the ocean for us rain, hail, or shine. Diving down to depths of about 400 m in a passive mode, Zooglider listens to the ambient sounds produced by fish and marine mammals, before rising back to the surface with all sensors activated. Equipped with a shadowgraph imaging camera, an active acoustic Zonar (echosounders at 200 and 1000 kHz), a passive acoustic hydrophone, and a pumped CTD plus Chl-a sensor, Zooglider senses the composition and behavior of zooplankton communities and the 4-dimensional ocean environment with which they interact.  Most recently Zooglider was part of the BioSWOT-Med campaign in the NW Mediterranean Sea in spring 2023, aimed at better understanding of the bio-physical coupling of ocean fronts and plankton communities, guided by the novel, high resolution SWOT satellite data. Asking the question how we look into the ocean, visual artist Claudine Arendt developed methods to render tangible the acoustic signature and optical images of key zooplankton groups through a porcelain cast, inspired by and using information from various Zooglider missions. Creating a full service of porcelain dinnerware, we can sit comfortably at our dinner table, at the top of the food chain, looking down all the way to the bottom of the food chain.  Currently Claudine Arendt is working out new ways of interpreting and visualising data from the BioSWOT-Med campaign.

Informations dates et horaires

Date & Time: Fri Nov 24 2023 11:00:00 GMT+0100 (Central European Standard Time)
Room: salle du LOCEAN, couloir 45-55, 4ème étage, pièce 417

. Lien zoom:
https://cnrs.zoom.us/j/95379701117?pwd=UnpwQjhNZ0pnY3lKaGZkNzRWMS84Zz09