Developing generalized flow ecology relationships for stream salmonids: Providing a clearer empirical basis for minimum flow regulations

ABSTRACT Objective To provide a clearer empirical basis for guiding minimum flow regulations, we tested for a consistent relationship between the magnitude of stable flows and correlates of productive capacity for stream salmonids. Methods We extracted and analyzed data from 35 flow–ecology relationships related to salmonid productive capacity (defined by diverse ecological responses including abundance, density, growth, or survival) from 25 streams ranging in flow from 0.4 to 750 m3/s mean annual discharge (MAD). To facilitate comparison among studies, we rescaled flow to percentage of MAD and rescaled ecological responses to a 0–1 range (dividing by the largest value in each study) or units of standard deviation (dividing by the SD). To control for effects of season and flow regime, we classified studies into four common hydroecological contexts: summer low flows (rainfall dominant streams with dry summers), summer high flows (snowmelt/glacial runoff streams), winter low flows, and migration or spawning flows. Standardized ecological response was then modeled as a function of percent MAD, ecological context, and their interaction. Results The slope of ecological response–flow relationships was positive for summer or winter low-flow regimes and migration flows but negative in summer high-flow regimes, consistent with expectations from habitat simulation models of a unimodal relationship between flow and habitat availability. Generalized additive models and logistic regression indicated peak salmonid productive capacity at 57% MAD (approximate 95% CIs 39–93% MAD), and average low-flow regressions indicate an 82% loss of capacity from 57% MAD (optimal flow) to flow cessation (0% MAD). Conclusions Standardizing response and flow axes while controlling for context dependence (i.e., seasonal hydrology) provides a useful approach for extracting cryptic flow–ecology relationships from diverse data sets, allowing detection of generalized flow–ecology relationships with optimal rearing flows at intermediate discharge. These generic relationships can be used to predict population-average flow effects in data-deficient salmonid streams and guide landscape-level flow policy.