Quantifying relations between altered hydrology and fish community responses for streams in Minnesota

Abstract Background Altered hydrology is a stressor on aquatic life, but quantitative relations between specific aspects of streamflow alteration and biological responses have not been developed statewide scale in Minnesota. Best subsets regression analysis was used to develop linear models that quantify among five categories hydrologic metrics (i.e., duration, frequency, magnitude, rate-of-change, timing) computed from streamgage records six composition, habitat, life history, reproductive, tolerance, trophic) fish-community samples, as well fish-based indices biotic integrity (FIBI) scores FIBI normalized an impairment threshold the corresponding stream class (FIBI_BCG4). Relations fish community were examined using three datasets represented periods record, long-term changes, short-term changes flow regimes streams Results Regression demonstrated significant explanatory response metrics, with strongest explained over 70% variability metric variables. Tolerance-based metrics. The most commonly related bankfull flows variability. Conclusions Final represent paired samples throughout State Minnesota encompass differences orders, landscape units, watershed sizes. Presented methods can support evaluations communities facilitate targeted efforts improve health communities. Methods also be applied locations outside continuous data samples.