Nikolaus Helmer

Methods of semi-automated and automated environmental monitoring using molluscs with a special focus on Dreissena

As part of the EU FET-Open project Robocoenosis, my PhD research focuses on automatic and autonomous water quality monitoring using organisms and sensors. In one sub-project I am analysing the behaviour of bivalve molluscs (especially shell movements) as indicators of environmental changes. For this purpose, I am developing new and improved sensor systems based on modern microcontrollers to record mussel behaviour (valvometry). These systems are used in the laboratory and in the field to analyse the response of mussels to different stressors (e.g. road salt, heavy metals, plant toxins or pharmaceuticals). In parallel, I am developing an optical system for the automatic detection of plankton communities in freshwater. Based on a shadowgraph and using AI-based analysis, species groups and specific species can be identified to draw conclusions about the condition of the water. The system can also be used to analyse movement patterns and attract photophilic species with light sources.