Discovery of nitrogen-responsive microbial indicators as metrics of freshwater ecosystem health

Microorganisms represent the most taxonomically and functionally diverse components of freshwater environments. Whilst distinct microbial communities exist across freshwater habitats, such as the water column and sediments, epilithic and epiphytic biofilm communities are critical in performing key roles in biogeochemical cycling and freshwater food webs. Despite their biogeochemical and ecological importance, microorganisms are underrepresented in freshwater monitoring programmes and lack metrics to interpret complex ecological communities and assess ecosystem health. We developed a framework for identifying microbial indicators of ecosystem health by analysing 16S rRNA gene sequences from bacterial communities in 1574 freshwater biofilm samples collected from 694 sites across England's river networks. Tree-based machine learning regression was used to assess taxa importance, and threshold-indicator analysis was applied to identify pollutant concentrations that alter the composition of freshwater biofilm communities, providing a foundation for incorporating microbial data into ecosystem health metrics. We applied this framework to measure the response of bacterial communities within English freshwater biofilms to an oxidised nitrogen gradient. Our results demonstrate that bacterial taxa can predict a large proportion of the variance in oxidised nitrogen concentrations, and we identified specific concentrations at which sensitive and tolerant taxa respond. This study represents a step toward developing a microbial metric of ecosystem health, advancing the potential use of microbial indicators in future monitoring programs. This framework could enable investigation of new and emerging pressures by examining how environmental perturbations affect functional processes, potentially across various trophic levels, providing a more comprehensive view of environmental dynamics in biomonitoring.