Benthic macroinvertebrate taxonomic data is the foundation of freshwater biomonitoring programs.around the world. Biological trait information has been proposed as an effective alternative or supplement to taxonomic data for ·biomonitoring purposes. Traits are simply measurable, heritable properties of an organism that interact with the environment. Trait data can expand the geographical scope of assessments as well as describe mechanistic relationships between environmental conditions and the biological community to diagnose impact severity and type of stressor. In riverine ecosystems, a change in the flow regime or hydrological alteration is considered the most significant environmental stressor because of the detrimental effects on biological communities and habitats as well as interactions with other stressors. To maintain ecological integrity, trait data can inform the benthic macroinvertebrate assemblage response to flow properties to support environmental flow management criteria. My objective was to define and evaluate traits and trait metrics that could be linked to hydrological conditions. Specifically, I investigated intra- and inter-tax on trait properties for body size and body shape, which are predicted to respond strongly to hydraulic and hydrologic scale variables. Multiple field sites were sampled several times over a five-year period in the unregulated Miramichi River Basin, New Brunswick, Canada to resolve the relationships between flow and ecology. I was able to demonstrate the importance of intraspecific trait variation and trait properties for characterizing the benthic assemblage. By measuring specimen body sizes and establishing body shape criteria using geometric morphometric analysis, I improved the accuracy of traits-based metrics and demonstrated a sizedependent bias in current taxonomic-based metrics. Using both traditional categorical trait states as well as high-resolution trait data, I was able to characterize relationships among aquatic insects and hydrological properties at nested spatial scales. Then I tested the performance of taxonomic and trait metrics to assess hydrological data over short (two-year) to moderate (five-year) temporal scales. High-resolution trait metrics demonstrated equal or greater association with hydrological factors than taxonomic or other trait metrics at these timescales. Trait information can add value to biomonitoring approaches by accurately describing trait expression, enabling stronger statistical inference, and increasing sensitivity and interpretability, which are essential for evaluating the complex relationship between benthic assemblages and their hydrological environment.
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