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Data from: Switchgrass cultivar, yield, and nutrient removal responses to harvest timing

    Objectives for this study were to compare switchgrass yields from 2010–2011 on eight widely used and experimental upland and lowland genotype (whole plot) at two locations in Tennessee, to determine: (i) which harvest timing (split-plot) provides maximum yield; (ii) effects of harvest timing (mid-Sep, Oct, Nov, and late Oct) on overall total P and K removal; and, (iii) how results are affected by cultivar.

    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.

        Measured Annual Nutrient loads from AGricultural Environments (MANAGE) database

          The MANAGE (Measured Annual Nutrient loads from AGricultural Environments) database was developed to be a readily-accessible, easily-queried database of site characteristic and field-scale nutrient export data. Initial funding for MANAGE was provided by USDA-ARS to support the USDA Conservation Effects Assessment Project (CEAP) and the Texas State Soil and Water Conservation Board as part of their mission to understand and mitigate agricultural impacts on water quality. MANAGE contains data from a vast majority of published peer-reviewed N and P export studies on homogeneous cultivated, pasture/range, and forested land uses in the US under natural rainfall-runoff conditions, as well as artificially drained agricultural land. Thus MANAGE facilitates expanded spatial analyses and improved understanding of regional differences, management practice effectiveness, and impacts of land use conversions and management techniques, and it provides valuable data for modeling and decision-making related to agricultural runoff.

          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.

            APLE : Annual Phosphorus Loss Estimator Tool

              APLE is a Microsoft Excel spreadsheet model that runs on an annual time-step and estimates field-scale, sediment bound and dissolved P loss (kg ha−1) in surface runoff for agricultural field. APLE is intended to quantify P loss through process-based equations. It has been tested for its ability to reliably predict P loss in runoff for systems with machine-applied manure and for soil P cycling using data from a wide variety of agricultural fields and regions.