Using freshwater mussel valvometry data as a real-time biological warning system for aquatic ecosystems

Quantifying the effects of external climatic and anthropogenic stressors on aquatic ecosystems is an important task for scientific and management progress in the field of water resources. In this study, we propose an innovative use of biotic communities as real-time indicators, which offers a promising solution for directly quantifying the impact of these external stressors on aquatic ecosystems. Specifically, we investigated the influence of natural river floods on biotic communities using freshwater mussels (FMs) as reliable bioindicators. Using a well-established valvometry technique, we measured the valve-opening behaviour of FMs, considering both amplitude and frequency. The valve gap movement of the FMs was monitored by installing a magnet on one valve and a Hall effect sensor on the other valve and recording the magnetic field between the magnet and the sensor itself using an Arduino board, which changes according to the distance between the two valves. The recorded data was then analysed using the Continuous Wavelet Transform (CWT) analysis to study the time-dependent frequency of the signals. The experiments were carried out in a laboratory flume and in the River Paglia (Italy). The laboratory experiments were carried out with FMs in two configurations: freely moving or immobilised on vertical bars. The immobilised configuration was necessary for the field application to prevent the FRMs from packing against the downstream wall of the protection cage during floods. These experiments allowed us to verify that immobilised mussels show similar responses to abrupt increases in flow conditions as free mussels, but produce more consistent and interpretable signals than free mussels due to the reduced number of features resulting from movement constraints. We then analysed the response of thirteen immobilised mussels in real river conditions during a moderate flood on 31 March 2022.  The FMs in the field showed a rapid and significant change in valve gap frequency as the flood escalated, confirming the laboratory results. These results highlight the effectiveness of using FMs as bioindicators for assessing flood impacts on aquatic ecosystems, and emphasise the utility of CWT as a powerful signal processing tool for analysing valvometric time series. The study proposes the integration of FM valvometry and CWT for the development of operational real-time Biological Early Warning Systems (BEWS) aimed to monitor and protect aquatic ecosystems.