Biological, Hydrological, and Water Quality Data Inputs for Alabama Ecohydrology Study (10-01-1999 to 09-30-2014)

We used 14 years (10-01-1999 to 09-30-2014) of biological data (benthic macroinvertebrate and stream fish community data and complementary biological metrics) that was collected from Alabama streams confined to the Mobile River basin and other Gulf Coast drainages in conjunction with land use data and process-based model hydrological (i.e., Precipitation-Runoff Modeling System; PRMS), and water quality (i.e., Spatially Referenced Regression On Watershed Attributes, SPARROW) outputs to explore the effects of land use-driven high and low flow conditions on resource limited taxa abundances and three biological metrics across two landscapes. A landscape consisted of all level III ecoregions above or below the geological feature referred to as the fall line across Alabama. We created two taxa-specific datasets for each landscape by connecting taxa-specific biological samples and the corresponding biological metrics to NHDPlus COMIDs and then used this spatial reference to relate these data to PRMS stream segments. This process enabled us to compile hydrologic metrics, long-term estimates of urban and agricultural land use, and water quality gradients for each biological sample. Biological datasets were compiled from samples collected by two Alabama state agencies: the Alabama Department of Environmental Management (ADEM) and the Geological Survey of Alabama (GSA). ADEM collected all benthic macroinvertebrate samples, while GSA collected all stream fish samples. All ADEM's benthic macroinvertebrate samples included raw community data, along with biological condition gradient (BCG) and Ephemeroptera, Plecoptera, and Trichoptera scores. GSA's stream fish samples included the raw community data and fish index of biological integrity scores. For all biological samples, NHDPlus COMIDs, and PRMS segments we also integrated the following attributes into each of our four datasets; for each biological sample we included its collection date, site ID, and geographic coordinates (decimal degrees); for each COMID, we included its cumulative drainage area (square kilometers) and slope (percentage) and identified the segment’s relevant level III ecoregion; and for each PRMS segment we included its cumulative drainage area (square kilometers). For each of the four datasets, we used PRMS predicted daily streamflow data to calculate 171 biologically relevant hydrologic metrics for each PRMS stream segment and used SPARROW long-term annual, COMID-specific estimates of total nitrogen, total phosphorus, and suspended sediment to generate standardized water quality gradients by incorporating these variables into principal component analyses. We then used annual land cover datasets (2001, 2004, 2005, 2006, 2008, 2011, 2012, 2013, and 2014) to calculate long-term averages of the percentages of urban and agricultural land use associated with each PRMS stream segment, and then estimates were used to identify high and low flow metrics that were only significantly correlated with either land use type. We then integrated the standardized water quality gradients, subsets of hydrologic metrics, and taxa-specific community data into community models to identify resource-limited taxa that were responsive to land use- driven flow conditions. Finally, we used these resource-limited taxa, the three biological metrics, standardized water quality gradients and subsets of hydrologic metrics to evaluate the impact of land use-driven flow conditions on aquatic communities native to Alabama streams. References: Olden, J. D., & Poff, N. L. (2003). Redundancy and the choice of hydrologic indices for characterizing streamflow regimes. River research and applications, 19(2), 101-121. LaFontaine, J.H., Hay, L.E., and Farmer, W.H., 2019, Model Input and Output for Hydrologic Simulations of the Southeastern United States for Historical and Future Conditions: U.S. Geological Survey data release, https://doi.org/10.5066/F74X56PH. Roland, V.L., II, and Hoos, A.B., 2020, SPARROW model inputs and simulated streamflow, nutrient and suspended-sediment loads in streams of the Southeastern United States, 2012 Base Year: U.S. Geological Survey data release, https://doi.org/10.5066/P9A682GW. ADEM. 2005. Standard operating procedures and quality assurance manual, Volume II -- biological. Field Operations Division, Alabama Department of Environmental Management, Montgomery, Alabama. O’Neil, P.E., Shepard, T.E. 2007, Delineation of ichthyoregions in Alabama for use with the index of biotic integrity: Alabama Geological Survey Open-File Report 0711, 34 p. O’Neil, P.E., Shepard, T.E., and Cook, M.R., 2006, Habitat and biological assessment of the Terrapin Creek watershed and development of the Index of Biotic Integrity for the Coosa and Tallapoosa River systems: Alabama Geological Survey Open-File Report 0601, 210 p. Wickham, J., Stehman, S.V., Sorenson, D.G., Gass, L., and Dewitz, J.A., 2021, Thematic accuracy assessment of the NLCD 2016 land cover for the conterminous United States: Remote Sensing of Environment, v. 257, art. no. 112357, at https://doi.org/10.1016/j.rse.2021.112357 Jessup, B.K., and J. Gerritsen. 2014. Calibration of the Biological Condition Gradient (BCG) for Fish and Benthic Macroinvertebrate Assemblages in Northern Alabama. Prepared for Alabama Department of Environmental Management, Montgomery, AL. Stamp, J., and B. Jessup. 2016. Calibration of the Biological Condition Gradient (BCG) for Fish and Benthic Macroinvertebrate Assemblages in the Coastal Plain of Alabama. Tetra Tech, Inc.- Center for Ecological Sciences. Montpelier, Vermont. Prepared for USEPA Office of Water, Office of Science and Technology and the Alabama Department of Environmental Management. Montgomery, Alabama.

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  "010:12"
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[
  "geospatial"
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