U.S. flag

An official website of the United States government

Data from: Quality controlled research weather data – USDA-ARS, Bushland, Texas

    The dataset contains 15-minute mean weather data from the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU) research weather station, Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL) for all days in 2016. The data are from sensors deployed at standard heights over grass that is irrigated and mowed during the growing season to reference evapotranspiration standards.

    Data from: Agro-environmental consequences of shifting from nitrogen- to phosphorus-based manure management of corn.

      This experiment was designed to measure greenhouse gas (GHG) fluxes and related agronomic characteristics of a long-term corn-alfalfa rotational cropping system fertilized with manure (liquid versus semi-composted separated solids) from dairy animals. Different manure-application treatments were sized to fulfill two conditions: (1) an application rate to meet the agronomic soil nitrogen requirement of corn (“N-based” without manure incorporation, more manure), and (2) an application rate to match or to replace the phosphorus removal by silage corn from soils (“P-based” with incorporation, less manure). In addition, treatments tested the effects of liquid vs. composted-solid manure, and the effects of chemical nitrogen fertilizer. The controls consisted of non-manured inorganic N treatments (sidedress applications). These activities were performed during the 2014 and 2015 growing seasons as part of the Dairy Coordinated Agricultural Project, or Dairy CAP, as described below. The data from this experiment give insight into the factors controlling GHG emissions from similar cropping systems, and may be used for model calibration and validation after careful evaluation of the flagged data.

      Effort Versus Reward: Preparing samples for fungal community characterization in high-throughput sequencing surveys of soils

        This data set consists of four data files. The FASTA file, Representative OTU sequences.fa, contains representative sequences from the operational taxonomic units (OTUs) shown in the OTU table. FASTA files can be opened in simple text editors, and sequences can be aligned using the BLAST tool (http://blast.ncbi.nlm.nih.gov/Blast.cgi) or open source software, like AliView (http://www.ormbunkar.se/aliview/). There are two Excel data files: OTU table and heatmaps.xlsx and Diversity Indexes.xlsx. The former contains the raw abundance data for the observed OTUs from the different experimental sites. The latter is a breakdown of various diversity indices that are grouped based on experimental characteristics, such as extraction volume, extraction method, etc. Excel_Archive.zip is a compressed version of the two Excel data files that have been converted to more archival-friendly formats using Excel Archival Tool.

        USDA-ARS Colorado Maize Water Productivity Dataset 2012-2013

          The USDA-Agricultural Research Service carried out an experiment on water productivity in response to seasonal timing of irrigation of maize (*Zea mays* L.) at the Limited Irrigation Research Farm (LIRF) facility in northeastern Colorado (40°26’ N, 104°38’ W) starting in 2012. Twelve treatments involved different water availability targeted at specific growth-stages. This dataset includes data from the first two years, which were complete years with intact treatments. Data includes canopy growth and development (canopy height, canopy cover and LAI), irrigation, precipitation, and soil water storage measured periodically through the season; daily estimates of crop evapotranspiration; and seasonal measurement of crop water use, harvest index and crop yield. Hourly and daily weather data are also provided from the CoAgMET, Colorado’s network of meteorological information.

          Rapid Carbon Assessment (RaCA)

            The Rapid Carbon Assessment (RaCA) was initiated by the USDA-NRCS Soil Science Division in 2010 with the following objectives: * To develop statistically reliable quantitative estimates of amounts and distribution of carbon stocks for U.S. soils under various land covers and to the extent possible, differing agricultural management. * To provide data to support model simulations of soil carbon change related to land use change, agricultural management, conservation practices, and climate change. * To provide a scientifically and statistically defensible inventory of soil carbon stocks for the U.S.