Difficulties in accessing high-quality data on trace gas fluxes and performance of bioenergy/bioproduct feedstocks limit the ability of researchers and others to address environmental impacts of agriculture and the potential to produce feedstocks. To address those needs, the GRACEnet (Greenhouse gas Reduction through Agricultural Carbon Enhancement network) and REAP (Renewable Energy Assessment Project) research programs were initiated by the USDA Agricultural Research Service (ARS). A major product of these programs is the creation of a database with greenhouse gas fluxes, soil carbon stocks, biomass yield, nutrient, and energy characteristics, and input data for modeling cropped and grazed systems. The data include site descriptors (e.g., weather, soil class, spatial attributes), experimental design (e.g., factors manipulated, measurements performed, plot layouts), management information (e.g., planting and harvesting schedules, fertilizer types and amounts, biomass harvested, grazing intensity), and measurements (e.g., soil C and N stocks, plant biomass amount and chemical composition). To promote standardization of data and ensure that experiments were fully described, sampling protocols and a spreadsheet-based data-entry template were developed. Data were first uploaded to a temporary database for checking and then were uploaded to the central database. A Web-accessible application allows for registered users to query and download data including measurement protocols. Separate portals have been provided for each project (GRACEnet and REAP) at nrrc.ars.usda.gov/slgracenet/#/Home and nrrc. ars.usda.gov/slreap/#/Home. The database architecture and data entry template have proven flexible and robust for describing a wide range of field experiments and thus appear suitable for other natural resource research projects.
The Drought Calculator (DC), a spreadsheet-based decision support tool, was developed to help ranchers and range managers predict reductions in forage production due to drought. Forage growth potential (FGP), the fraction of historical average production, is predicted as a weighted average of monthly precipitation from January through June. We calibrated and evaluated the DC tool in the Great Plains of the United States, using FGP and precipitation data from Colorado (CO), North Dakota (ND), and Wyoming (WY). In CO, FGP was most sensitive to precipitation in April and May, in ND to precipitation in April and June, and in WY to precipitation in April, May, and June. Weights in these months ranged from 0.16 to 0.52. Prediction was better for CO and WY than for ND. When January-June precipitation was used, the tool correctly predicted 83% of the years with FGP reduced by drought for CO, 82% for WY, and only 67% for ND. Positive values of the True Skill Statistic (0.53 for CO, 0.42 for WY, and 0.17 for ND) indicate that FGP was classified as above or below average better than random selection. Predicting FGP earlier than April in CO and WY will require accurate forecasts of April-June precipitation. Use of the DC is most limited by insufficient forage data to determine the site-specific relationships between FGP and monthly precipitation. Even so, the decision tool is useful for discriminating drought effects on FGP classification being above or below the long-term average, and it provides a quantitative prediction to producers for their destocking decisions in drought years.
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