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Data from: Gas emissions from dairy barnyards

    To assess the magnitude of greenhouse gas (GHG) fluxes, nutrient runoff and leaching from dairy barnyards and to characterize factors controlling these fluxes, nine barnyards were built at the U.S. Dairy Forage Research Center Farm in Prairie du Sac, WI (latitude 43.33N, longitude 89.71W). The barnyards were designed to simulate outdoor cattle-holding areas on commercial dairy farms in Wisconsin. Each barnyard was approximately 7m x 7m; areas of barnyards 1-9 were 51.91, 47.29, 50.97, 46.32, 45.64, 46.30, 48.93, 48.78, 46.73 square meters, respectively. Factors investigated included three different surface materials (bark, sand, soil) and timing of cattle corralling. Each barnyard included a gravity drainage system that allowed leachate to be pumped out and analyzed. Each soil-covered barnyard also included a system to intercept runoff at the perimeter and drain to a pumping port, similar to the leachate systems.

    Low-Disturbance Manure Incorporation

      The LDMI experiment (Low-Disturbance Manure Incorporation) was designed to evaluate nutrient losses with conventional and improved liquid dairy manure management practices in a corn silage (*Zea mays*) / rye cover-crop (*Secale cereale*) system. The improved manure management treatments were designed to incorporate manure while maintaining crop residue for erosion control. Field observations included greenhouse gas (GHG) fluxes from soil, soil nutrient concentrations, crop growth and harvest biomass and nutrient content, as well as monitoring of soil physical and chemical properties. Observations from LDMI have been used for parameterization and validation of computer simulation models of GHG emissions from dairy farms (Gaillard et al., submitted). The LDMI experiment was performed as part of the Dairy CAP.

      Manure application methods for alfalfa-grass

        The MAMA experiment (Manure Application Methods for Alfalfa-Grass), from the USDA-ARS research station in Marshfield, WI was designed to evaluate nutrient and pathogen losses with conventional and improved liquid dairy manure management practices for alfalfa-grass production. Observations from MAMA have also been used for parameterization and validation of computer simulation models of greenhouse gas (GHG) emissions from dairy farms.

        Effects of tannin in dairy cow diets and land application of manure on soil gas fluxes and nitrogen dynamics

          This experiment was designed to determine if tannin concentration and nitrogen (N) content of field-applied dairy cow manure influences greenhouse gas (GHG) emissions from soil, soil N mineralization, and plant productivity. The data presented include experimental design, soil physical characteristics, gas fluxes, soil nitrogen at 0-10 cm depth, soil nitrogen at 10-20 cm depth, chemical characteristics of dairy manure, and crop yield and biomass characteristics.

          Data from: Threshold Behavior of Catchments with Duplex Hillslope Soils Feeding Soil Pipe Networks

            This dataset corresponds with two published studies conducted on loess covered catchments in northern Mississippi, USA within the Goodwin Creek Experimental Watershed that contain extensive networks of soil pipes and corresponding collapse features. These loess soils contain fragipan layers that were found to perch water, thereby initiating the piping processes. The dataset contains data from two papers, specifically these include: (i) the spatial distribution of soil pipe collapses and their size measurements from the Wilson et al. (2015) paper, and (ii) hydrologic measurements of perched water tables on hillslopes, water levels of selected soil pipe locations, and precipitation from the Wilson et al. (2017) paper.

            Gridded Soil Survey Geographic Database (gSSURGO)

              This dataset is called the Gridded SSURGO (gSSURGO) Database and is derived from the Soil Survey Geographic (SSURGO) Database. SSURGO is generally the most detailed level of soil geographic data developed by the National Cooperative Soil Survey (NCSS) in accordance with NCSS mapping standards. The tabular data represent the soil attributes, and are derived from properties and characteristics stored in the National Soil Information System (NASIS). The gSSURGO data were prepared by merging traditional SSURGO digital vector map and tabular data into State-wide extents, and adding a State-wide gridded map layer derived from the vector, plus a new value added look up (valu) table containing "ready to map" attributes. The gridded map layer is offered in an ArcGIS file geodatabase raster format.

              United States General Soil Map (STATSGO2)

                The Digital General Soil Map of the United States or STATSGO2 is a broad-based inventory of soils and non-soil areas that occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped of 1:250,000 in the continental U.S., Hawaii, Puerto Rico, and the Virgin Islands and 1:1,000,000 in Alaska. The level of mapping is designed for broad planning and management uses covering state, regional, and multi-state areas. The U.S. General Soil Map is comprised of general soil association units and is maintained and distributed as a spatial and tabular dataset.