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Paper short abstract

This paper examines how knowledge of chemical contamination is produced within marine monitoring programmes facing growing regulatory pressure to produce data and the persistence of low policy outputs – underlining how actors use seawater as a theory machine (Helmreich 2011).

Paper long abstract

This presentation advances understanding of water as a site for knowledge-making by examining how chemical pollution in marine environments is monitored. While modern science has long relied on chemistry to stabilize water as an object of knowledge (Linton 2006), seawater contamination poses specific challenges: dilution and salinity make water samples unstable and politically fragile objects of measurement.

Drawing on ethnographic and archival research into French Mussel Watch programmes, we trace the shift from water-based sampling to biota. Mussels filter seawater and concentrate contaminants, making chemical pollution perceptible through assemblages of their tissues, sampling protocols, laboratory techniques, extrapolation laws, and regulatory frameworks. But what happens when mussels lack “muscle”?

Our analysis focuses on two monitoring networks: one deploys transplanted mussels under standardized conditions, the other samples mussels from natural reefs. For two decades, these divergent approaches have generated disputes over methodological robustness, particularly regarding mussel condition indices. We explore how these sociomaterial assemblages respond to recent advances in mass spectrometry - enabling detection of an expanding array of chemical compounds in seawater - and to regulatory pressures to extend monitoring offshore. Rather than simply enhancing monitoring capacities, these developments rework the infrastructures and problem definitions of monitoring. Some scientists and environmental agencies contest, on economic and moral grounds, the implementation of a “starving mussel watch,” given the low nutrient levels of open-sea waters. By examining this controversy, we demonstrate how analytical sensitivity and regulatory expectations influence what constitutes significant contamination and relevant data at the intersection of science and policy.