Hydrologic metrics, biological metrics, R scripts, and model archives associated with regression analyses used to quantify relations between altered hydrological and biological responses in rivers of Minnesota, 1945-2015
The U.S. Geological Survey (USGS) and the Minnesota Pollution Control Agency (MPCA) conducted a cooperative study to develop linear regression models that quantify relations among 173 hydrologic explanatory metrics in five categories (duration, frequency, magnitude, rate-of-change, and timing) computed from streamgage records and 132 biological response metrics in six categories (composition, habitat, life history, reproductive, tolerance, trophic) computed from fish community samples collected from the 1996-2015 water years (WYs). In addition, linear relations were quantified between hydrologic metrics, fish-based indices of biotic integrity (FIBI) scores, and FIBI scores normalized to the impairment threshold of the corresponding stream class (FIBI_BCG4), resulting in a total of 134 regression equations per hydrologic dataset. Three hydrologic datasets were used to examine relations between altered hydrology and fish community responses at different temporal scales. First, the period-of-record (POR) dataset was created by computing hydrologic metrics using all complete WYs of streamflow record (1945WY and later) and ending with the WY of corresponding biological sample collection. Next, datasets representing long-term changes (LTC) and short-term changes (STC) in hydrology were created using ratios of hydrologic metrics computed for different time periods. The LTC ratios were obtained by dividing hydrologic metrics computed from available streamflow records from the 1981WY through the WY of biological sample collection by hydrologic metrics computed from available streamflow records during the 1945-79WYs. The STC ratios were obtained by dividing hydrologic metrics computed from the last 10 water years up to the WY of biological sample collection by hydrologic metrics computed from the POR for each streamgage. The POR, LTC, and STC datasets included 54, 39, and 48 hydrologic and biological site pairs, respectively. Results of regression analyses are described in a companion publication (https://doi.org/TBD). A subset of the best regression models based on pseudo-R2 values is published in the companion publication, but all 134 final regression models for each of the three datasets are published in this data release. Model archives of best subset and left-censored linear regression models are provided and include readme files, raw data files, R scripts used to compute regression analyses, and model outputs. Daily streamflow data were retrieved from the National Water Information System (NWIS; at https://waterdata.usgs.gov/nwis). A minimum of 10 years of complete daily streamflow record was required for computing hydrologic metrics to pair with biological metrics. RStudio (version 3.5.0) and the EflowStats (version 5.0.0) and NWCCompare (version 5.0) packages were used to compute hydrologic metrics. Biological metrics used in described datasets were computed by and obtained from the MPCA (MPCA, 2016). Similar hydrologic statistics were computed using the EflowStats package and published in a previous data release (https://doi.org/10.5066/P9ND1NPT).
|Hydrologic metrics, biological metrics, R scripts, and model archives associated with regression analyses used to quantify relations between altered hydrological and biological responses in rivers of Minnesota, 1945-2015
|Aliesha L Krall, Jeffrey R Ziegeweid, Gregory D Johnson, Sara B Levin
|USGS Digital Object Identifier Catalog
|Upper Midwest Water Science Center