Abstract
Freshwaters face increasing pressures from chemical, hydrological and climatic changes, yet tools for assessing their condition remain limited. River biofilms, composed of diverse microbial communities, integrate environmental signals over space and time, making them sensitive indicators of river health. Using 16S rRNA gene sequencing of more than 1600 biofilms collected across a national river network, we quantified bacterial diversity and community composition and applied network analysis to identify ecologically cohesive sub-communities with keystone taxa underpinning community stability. Alkalinity, dissolved oxygen, nitrate-nitrogen and temperature were among the principal gradients shaping community composition. Threshold indicator analyses identified taxa with breakpoints along these gradients, revealing interpretable ecological thresholds. Our results demonstrate the potential for microbiome-based monitoring frameworks that could complement existing biotic indices, enabling early detection of ecological changes and supporting the integration of genomic indicators into routine ecosystem assessment. This scalable approach offers a powerful strategy for managing freshwaters under accelerating anthropogenic pressures.