Hydrologic controls on basin- scale distribution of benthic invertebrates

Streamflow variability is a major determinant of basin-scale distributions of benthic invertebrates. Here we present a novel procedure based on a probabilistic approach aiming at a spatially explicit quantitative assessment of benthic invertebrate abundance as derived from near-bed flow variability. Although the proposed approach neglects ecological determinants other than hydraulic ones, it is nevertheless relevant in view of its implications on the predictability of basin-scale patterns of organisms. In the present context, aquatic invertebrates are considered, given that they are widely employed as sensitive indicators of fluvial ecosystem health and human-induced perturbations. Moving from the analytical characterization of site-specific probability distribution functions of streamflow and bottom shear stress, we achieve a spatial extension to an entire stream network. Bottom shear stress distributions, coupled with habitat suitability curves derived from field studies, are used to produce maps of invertebrate suitability to shear stress conditions. Therefore, the proposed framework allows one to inspect the possible impacts on river ecology of human-induced perturbations of streamflow variability. We apply this framework to an Austrian river network for which rainfall and streamflow time series, river network hydraulic properties, and local information on invertebrate abundance for a limited number of sites are available. A comparison between observed species density versus modeled suitability to shear stress is also presented. Although the proposed strategy focuses on a single controlling factor and thus represents an ecological minimal model, it allows derivation of important implications for water resource management and fluvial ecosystem protection. Key Points Hydrologic variability is a major control of invertebrate habitat suitability New analytical basin-scale approach for pdfs of ecohydrological key features Austrian river basin used for ecohydrological data-model comparison