Inferences based on diatom compositions improve estimates of nutrient concentrations in streams

Nutrient concentrations in streams vary strongly with flow conditions, and routinely gathered field measurements of nutrients reflect this variability. Diatom assemblage composition has been used in previous studies to infer nutrient concentrations, and because diatoms integrate nutrient concentrations over longer periods of time, diatom inferences may be less susceptible to fluctuations in streamflow. We tested this hypothesis by leveraging differences in the flashiness of streams across a large continental data set. More specifically, we tested whether the variabilities of direct measurements and diatom inferences of dissolved phosphorus and nitrate were greater in flashy versus non-flashy streams. We further considered whether models linking landscape predictor variables to nutrient concentrations yielded consistent results across flashy and non-flashy streams. Our analysis indicated that measured nutrient concentrations were more variable in flashy compared to non-flashy streams and that landscape models identified different important predictors of nutrient concentrations when fit using data from flashy vs. non-flashy streams. In contrast, variabilities of diatom-inferred nutrient concentrations were similar among stream types, as were the important predictor variables (e.g., manure application rates for nitrate and number of wet days for dissolved phosphorus). These analyses indicate that use of diatom-inferred nutrient concentrations can potentially improve efforts to quantify stream nutrient concentrations. [Display omitted] •Diatom metabarcoding data are used to infer nutrient concentrations in streams.•Nutrient concentrations in flashy streams are more variable than in non-flashy streams.•Inferred concentrations are less variable than direct measurements of nutrients.•Nutrient concentrations are predicted from watershed characteristics.•Predictive models yield more consistent results when calibrated with inferences.