Simultaneous recording of filtration and respiration in marine organisms in response to short-term environmental variability

Climate change imposes unusual long-term trends in environmental conditions, plus some tremendous shifts in short-term environmental variability, exerting additional stress on marine ecosystems. This paper describes an empirical method that aims to improve our understanding of the performance of benthic filter feeders experiencing changes in environmental conditions, such as temperature, on time scales of minutes to hours, especially during daily cycles or extreme events such as marine heatwaves or hypoxic upwelling. We describe the Fluorometer and Oximeter equipped Flow-through Setup (FOFS), experimental design, and methodological protocols to evaluate the flood of data, enabling researchers to monitor important energy budget traits, including filtration and respiration of benthic filter-feeders in response to fine-tuned environmental variability. FOFS allows online recording of deviations in chlorophyll and dissolved oxygen concentrations induced by the study organism. Transparent data processing through Python scripts provides the possibility to adjust procedures to needs when working in different environmental contexts (e.g., temperature vs. pH, salinity, oxygen, biological cues) and with different filter-feeding species. We successfully demonstrate the functionality of the method through recording responses of Baltic Sea blue mussels (Mytilus) during one-day thermal cycles. This method practically provides a tool to help researchers exposing organisms to environmental variability for some weeks or months, to relate the observed long-term performance responses to short-term energy budget responses, and to explain their findings with the potential to generalize patterns. The method, therefore, allows a more detailed description of stress-response relationships and the detection of species' tolerance limits.

Automated summary

This paper introduces an empirical method using FOFS to enhance understanding of benthic filter feeders' performance under changing environmental conditions. Through online data recording and Python script processing, researchers can adjust experimental procedures in different environments to provide a detailed description of stress-response relationships and detect species' tolerance limits.