AndreaBozzo/ceres-open-data-index huggingface dataset:
Data from: Integrated Crops and Livestock in Central North Dakota, USA: Agroecosystem Management to Buffer Soil Change

<p dir="ltr">Integrated crop-livestock systems have been identified as having positive agronomic and environmental outcomes, but information documenting their long-term impact on soil properties is lacking. An integrated crop-livestock study was conducted to evaluate the effects of residue management, frequency of hoof traffic, season, and production system (integrated annual cropping vs. perennial grass) on soil properties at the 0-7.5 cm depth from 2001 through 2008. The study was conducted at the USDA-ARS Northern Great Plains Research Laboratory, Mandan, North Dakota, USA. Soil bulk density, electrical conductivity, soil pH, extractable N and P, potentially mineralizable N, soil organic carbon, and total nitrogen were measured 3, 6, and 9 years after treatment establishment. Electrical conductivity and pH were estimated from a 1:1 soil-water mixture. Soil nitrate-N and ammonium-N were determined from 1:10 soil-KCl (2 M) extracts using cadmium reduction followed by a modified Griess-Ilosvay method and indophenol blue reaction. Plant-available soil P was estimated by bicarbonate extraction. Potentially mineralizable N was estimated from the ammonium-N accumulated after a 7-d anaerobic incubation. Total soil carbon and nitrogen were determined by dry combustion. Values for soil properties were incorporated into a soil quality index to assess production system effects on soil condition using the Soil Management Assessment Framework. Data may be used to understand integrated crop-livestock system impacts on near-surface soil properties. Data are generally applicable to cropland under a semiarid continental climate for the following USDA soil types: Grassna, Linton, Mandan, Temvik, Williams, and Wilton.</p>

Tags: integrated-agricultural-systems, soil-change, soil-quality
Organization: Department of Agriculture
<b>Data from: Water quality of an integrated crop–livestock system in the northern Great Plains</b>

<p dir="ltr">Integrated crop-livestock (ICL) systems can potentially increase agricultural productivity in an environmentally sustainable manner. Impacts of ICL systems on water quality, however, have not been adequately studied. Rainfall simulations were used to examine effects of cropland and grass pasture vegetation types on surface runoff and water infiltrating into soil in a long-term ICL study near Mandan, ND USA. Simulations were conducted before and after grazing over a two-year period (August 2017 – May 2019). Water quality parameters included nitrate-N, nitrite-N, ammonia-N, phosphate-P, and total suspended solid (TSS) concentrations and loads in surface and infiltration waters. Water N and P compounds were determined using an AQ1 Discrete Analyzer, while TSS concentrations were determined by mass difference after passing a known sample volume through filter paper and drying to a constant mass. Surface runoff loads for N and P compounds were calculated by the sum of sample concentrations multiplied by sample volumes for all samples collected during each simulation event. As a supplement to water quality parameters, plant biomass and litter samples were collected, and percent cover of living vegetation, vegetation litter, and bare ground were estimated within a representative area of the sample site. Data may be used to understand ICL system impacts on water quality and are generally applicable to cropland and rangeland under a semiarid continental climate for the following soil types: Grassna, Linton, Mandan, Temvik, Williams, and Wilton.</p>

Tags: infiltration, integrated-agricultural-systems, northern-plains, rainfall-simulations, runoff
Organization: Department of Agriculture
Soil - Plant - Atmosphere - Water Field & Pond Hydrology

<p><a href="https://www.nrcs.usda.gov/wps/portal/nrcs/detailfull/national/water/manage/drainage/?cid=stelprdb1045331">SPAW is a daily hydrologic budget model</a> for agricultural fields and ponds (wetlands, lagoons, ponds and reservoirs). Included are irrigation scheduling and soil nitrogen. Data input and results are graphical screens.</p>
<p>The <a href="https://hrsl.ba.ars.usda.gov/SPAW/Index.htm">SPAW</a> (Soil-Plant-Air-Water) computer model simulates the daily hydrologic water budgets of agricultural landscapes by two connected routines, one for farm fields and a second for impoundments such as wetland ponds, lagoons or reservoirs. Climate, soil and vegetation data files for field and pond projects are selected from those prepared and stored with a system of interactive screens. Various combinations of the data files readily represent multiple landscape and ponding variations. </p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Soil Water Characteristics - Equations.</p> <p>File Name: Soil Water Characteristics-Equations.xls</p></li><br><li><p>Resource Title: Instructions for Access to USDA / NRCS Soils Data.</p> <p>File Name: Accessing USDA Soils Data.pdf</p></li><br><li><p>Resource Title: Evaporation default files for USA.</p> <p>File Name: SPAW Evaporation Default Files.zip</p><p>Resource Description: These *.djvu files require a free reader plug-in available from : <a href="http://www.djvuzone.org/download.html" target="_blank">http://www.djvuzone.org/download.html</a>.</p></li></ul><p></p>

Tags: ars, data-gov, ecological-assessment, np211, soil-data, soil-reports, soil-water-characteristics, spaw
Organization: Department of Agriculture
Data from: Short-term soil responses to late-seeded cover crops in a semi-arid environment

<p dir="ltr">Cover crops can enhance desirable agricultural outcomes such as improved nutrient-use efficiency, soil tilth, reduced pests, and increased yield and yield stability. Documentation of soil property responses to cover crops in semiarid cropping systems, however, is limited. A study was conducted to evaluate soil responses to late-summer seeded cover crops in a no-tillage cropping system under semiarid conditions. The study was conducted over three years on the Area IV Soil Conservation Districts Cooperative Research Farm near Mandan, ND, USA. Cover crops were seeded into dry pea residue in mid- to late August in 19-cm rows. Cover crop metrics included aboveground biomass, while soil metrics included soil water content, soil nitrate-N, near-surface soil properties, and soil coverage by residue. Cover crop biomass was measured immediately before a killing frost. Soil water content was measured before cover crop seeding, immediately after a killing frost, and the following spring using a neutron soil moisture meter. Soil nitrate-N was measured before cover crop seeding and the following spring using 1:10 soil-KCl extracts and the cadmium reduction method. The cover crop growing period ranged from 56 to 70 d. Data may be used to understand soil responses to late-summer seeded cover crops under rainfed conditions in a semiarid continental climate. Applicable USDA soil types include Grassna, Linton, Mandan, Temvik, Williams, and Wilton.</p>

Tags: aboveground-biomass, cover-crops, dryland-cropping-systems, microbial-biomass-carbon, northern-great-plains, particulate-organic-matter-carbon, soil-nitrate-n, soil-water
Organization: Department of Agriculture
<b>Data from: ‘Field measurement of wind erosion flux and soil erodibility factors as affected by tillage and seasonal drought’</b>

<p dir="ltr">There are very few reports in the literature with field measurements of wind erosion flux associated with different forms of tillage management. Measurements of wind erosion flux were conducted to quantify the effects of soil tillage disturbance on wind erosion at a site in south central North Dakota USA in 2003 and 2004. The study was conducted on the Area IV Soil Conservation Districts Research Farm. The study site consisted of gently rolling topography (0-3%) with Temvik-Wilton silt loam soils (USDA: Fine-silty, mixed, superactive frigid Typic and Pachic Haplustolls). Three tillage treatments were included in the study: no-tillage (NT), an intermediate level of disturbance, one-pass tandem disk tillage (TDT), and a heavier level of disturbance, two-pass offset disk tillage (ODT). Erosion flux was measured with sediment samplers of the Big Spring Number Eight type from May through September each year. Sediment samplers were positioned near the peripheries of plots and captured soil flux between 5 and 10 cm height. Vertical flux profile was determined by stacked sediment samplers capturing flux at five heights between 5 and 100 cm. Measurements were applied to soil wind erodibility factors, including multiple within-season determinations of prostrate residue coverage (including live material) by marked cable technique, standing residue by photographic means, soil surface roughness by chain method, and twice per season determinations of aggregate size distribution by compact rotary sieve. Data associated with this study should be of interest to soil conservationists, soil scientists, earth scientists, agronomists and others interested in the increased erosion hazards occurring as result of global climate change. Data are generally applicable to croplands under a semiarid Continental climate for the following soil types: Grassna, Linton, Mandan, Temvik, Williams, and Wilton.</p>

Tags: northern-great-plains, residue-coverage, sediment-flux, soil-roughness, wind-erosion
Organization: Department of Agriculture
Systemic production of grapevine phenolics in response to mixed infections by wood-colonizing fungi

<p>This data is collected from two experiments, one in 2018 and one in 2019, that left untreated or inoculated grapevines with Diplodia seriata, Neofusicoccum parvum, Phaeomoniella chlamydospora, or mock-inoculated, and then two months later inoculated with one of the three pathogens. Grapevine stem phenolic levels were measured at the time of the second inoculation on a different branch, and comparisons were made between pathogen infected plants or those left non-inoculated. Lesion sizes of the second inoculations also were compared to examine the effects on the first inoculation on these. Lesion lengths were measured in mm, and all phenolic compound levels were measured in mg/g FW amounts. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Fungal Pathogen Induction of Grapevine Stem Phenolics.</p> <p>File Name: Fungal Pathogen Induction of Stem Phenolics.xlsx</p><p>Resource Description: Data from experiments conducted in 2018 and 2019, available on different tabs. Data from 2018 was from an experiment that had potentially compromised effects due to loss of greenhouse environmental controls and issues establishing fungal canker pathogen infections. Lesion lengths are provided in mm, and all phenolic levels are provided in mg/g FW stem tissues.</p></li></ul><p></p>

Tags: ars, chemical-ecology, data-gov, flavonoids, fungal-pathogens, grapevine, np303, phloem-chemistry, stilbenoids, systemic-acquired-resistance, xylem-chemistry
Organization: Department of Agriculture
Data from: Whole-genome sequence data and analysis of a Staphylococcus aureus strain SJTUF_J27 isolated from seaweed

<p>The complete genome sequence data of <em>S. aureus</em> SJTUF_J27 isolated from seaweed in China is reported here. The size of the genome is 2.8 Mbp with 32.9% G+C content, consisting of 2614 coding sequences and 77 RNAs. A number of virulence factors, including antimicrobial resistance genes (fluoroquinolone, beta-lactams, fosfomycin, mupirocin, trimethoprim, and aminocoumarin) and the egc enterotoxin cluster, were found in the genome. In addition, the genes encoding metal-binding proteins and associated heavy metal resistance were identified. Phylogenetic data analysis, based upon genome-wide single nucleotide polymorphisms (SNPs), and comparative genomic evaluation with BLAST Ring Image Generator (BRIG) were performed for SJTUF_J27 and four <em>S. aureus</em> strains isolated from food. The completed genome data was deposited in NCBI's GenBank under the accession number CP019117, <a href="https://www.ncbi.nlm.nih.gov/nuccore/CP019117">https://www.ncbi.nlm.nih.gov/nuccore/CP019117</a>. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: NCBI GenBank Accession CP019117.1: Staphylococcus aureus strain SJTUF_J27 chromosome, complete genome.</p> <p>File Name: Web Page, url: <a href="https://www.ncbi.nlm.nih.gov/nuccore/CP019117">https://www.ncbi.nlm.nih.gov/nuccore/CP019117</a> </p><p>With an average of 331-fold sequencing coverage, a genome size of 2,804,759 bp constituting 32.9% of G+C content was generated. RAST annotation of the genome revealed a total of 399 subsystems, 2614 coding sequences (80 of them related to virulence, disease and defense), and 77 RNAs. PathogenFinder showed the probability of this strain being a human pathogen was 98%.  Bacteria and source DNA available from Xianming Shi, 800 Dongchuan Road, Shanghai, China, 200240. Annotation was added by the NCBI Prokaryotic Genome Annotation Pipeline (released 2013).</p></li></ul><p></p>

Tags: ars, data-gov, seaweed, sjtuf_j27
Organization: Department of Agriculture
Data from: Genome analyses of fungal pathogens Neonectria faginata and Neonectria coccinea

<p>Protein predictions using Augustus web for the fungi <em>Neonectria coccinea</em> and <em>N. faginata</em>, as well as protein prediction of closely related species <em>N. ditissima</em>, and <em>Corinectria fuckeliana</em>. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Protein prediction dataset for Neonectria faginata isolate A.R. 4307.</p> <p>File Name: AR4307_augustusRev.fasta</p><p>Resource Description: Protein prediction dataset</p></li><br><li><p>Resource Title: Protein prediction data set for Neonectria ditissima isolate CBS 226.31.</p> <p>File Name: CBS22631_augustus.fasta</p><p>Resource Description: Protein prediction data set</p></li><br><li><p>Resource Title: Protein prediction file for Neonectria coccinea isolate CBS 119158.</p> <p>File Name: CBS119158_augustus.fasta</p><p>Resource Description: Protein prediction file</p></li><br><li><p>Resource Title: Protein prediction file of Corinectria fuckeliana isolate CBS 125109.</p> <p>File Name: CBS125109_augustus.fasta</p><p>Resource Description: Protein prediction file</p></li></ul><p></p>

Tags: ars, ascomycetous-fungi, beech, data-gov, disease, np303, proteome
Organization: Department of Agriculture
BEAST log data from: Characterizing a century of genetic diversity and contemporary antigenic diversity of N1 neuraminidase in IAV from North American swine

<p>These are the ".log" files from "Characterizing a century of genetic diversity and contemporary antigenic diversity of N1 neuraminidase in Influenza A virus (IAV) from North American swine" generated in BEAST and used to plot molecular substitution rates and calculate statistical distances between posterior distributions of these rates. The names of these files communicate information about the various BEAST runs using the following format: cladeOrLineageName_replicate_substitutionModel_treePrior_MCMCiterations_dateOfRunWithin2021.log where replicate is not always included  </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: BEAST log file for clade N1.C.2.1.</p> <p>File Name: N1C21_SRD06_strict_GMRF_200M<em>Nov9.log</em>.zip</p><p>Resource Software Recommended: Tracer v1.7.1,url: <a href="http://tree.bio.ed.ac.uk/software/tracer/">http://tree.bio.ed.ac.uk/software/tracer/</a> </p></li><br><li><p>Resource Title: BEAST log file for clade N1.C.2.</p> <p>File Name: N1C2_SRD06_strict_GMRF_200M<em>Nov2.log</em>.zip</p><p>Resource Software Recommended: Tracer v1.7.1,url: <a href="http://tree.bio.ed.ac.uk/software/tracer/">http://tree.bio.ed.ac.uk/software/tracer/</a> </p></li><br><li><p>Resource Title: BEAST log file for clade N1.C.3.1.</p> <p>File Name: N1C31_SRD06_strict_GMRF<em>200M.log</em>.zip</p><p>Resource Software Recommended: Tracer v1.7.1,url: <a href="http://tree.bio.ed.ac.uk/software/tracer/">http://tree.bio.ed.ac.uk/software/tracer/</a> </p></li><br><li><p>Resource Title: BEAST log file for clade N1.C.3.2.</p> <p>File Name: N1C32_SRD09_strict_GMRF_200M<em>May21.log</em>.zip</p><p>Resource Software Recommended: Tracer v1.7.1,url: <a href="http://tree.bio.ed.ac.uk/software/tracer/">http://tree.bio.ed.ac.uk/software/tracer/</a> </p></li><br><li><p>Resource Title: BEAST log file for clade N1.C.3.</p> <p>File Name: N1C3_r1_hkyGamma4_GMRF_200M<em>May20.log</em>.zip</p><p>Resource Software Recommended: Tracer v1.7.1,url: <a href="http://tree.bio.ed.ac.uk/software/tracer/">http://tree.bio.ed.ac.uk/software/tracer/</a> </p></li><br><li><p>Resource Title: BEAST log file for clade N1.P.</p> <p>File Name: N1P_SRD06_strict_GMRF_200M<em>Aug2.log</em>.zip</p><p>Resource Software Recommended: Tracer v1.7.1,url: <a href="http://tree.bio.ed.ac.uk/software/tracer/">http://tree.bio.ed.ac.uk/software/tracer/</a> </p></li><br><li><p>Resource Title: BEAST log file for the classical swine N1 lineage.</p> <p>File Name: N1classical_r1_SRD06_UCLN_GMRF_200M<em>May21.log</em>.zip</p><p>Resource Software Recommended: Tracer v1.7.1,url: <a href="http://tree.bio.ed.ac.uk/software/tracer/">http://tree.bio.ed.ac.uk/software/tracer/</a> </p></li></ul><p></p>

Tags: ars, bayesian-statistics, beast, data-gov, evolution, influenza-a-virus, molecular-substitution-rate, neuraminidase, np103, phylogenetic, rate-of-evolution, swine
Organization: Department of Agriculture
Legume hyperspectral and <i>in-situ</i> biophysical/biochemical dataset collected in the Southern Plains

<p dir="ltr">A field experiment focused on three legumes (soybeans [<i>Glycine max</i>], mothbeans [<i>Vigna aconitifolia</i>], and tepary bean [<i>Phaseolus acutifolius</i>]) was conducted in El Reno, OK over a two year period (2018, 2019). The split-split plot design for the legumes were subject to various row spacing (38cm and 76cm) and irrigation regimes (irrigated and rainfed). Sampling of the plots took place a total of seven times over the two year period. Each of the samplings included an initial triplicate (averaged) hyperspectral readings using a spectroradiometer (350nm to 2500nm; FieldSpec Pro FR: Malvern Panalytical, Westborough, MA, USA), <i>in-situ</i> measurements (canopy cover [collected with the “Canopeo” app where a ratio of plant to ground pixels were calculated], chlorophyll content [collected with Chlorophyll Content Meter-300, Opti-Sciences, Hudson, NH, USA]), and biomass clipping for various laboratory analytics (dry weight, nitrogen/carbon content, crude protein, neutral detergent fiber, acid detergent fiber, in vitro true digestibility). Locations for sampling (n=334) within the 4m x 3m plots were chosen at random.</p>

Tags: hyperspectral, imaging, mothbeans, remote-sensing, soybeans, spectroradiometer, tepary-beans
Organization: Department of Agriculture
AmeriFlux ecosystem observation datasets - University of Nebraska, Lincoln, Agricultural Research Service irrigated continuous maize site

<p>The study site is one of three fields (all located within 1.6 km of each other) at the University of Nebraska Agricultural Research and Development Center near Mead, Nebraska. This site is irrigated with a center pivot system. Prior to the initiation of the study, the irrigated site had a 10-yr history of maize-soybean rotation under no-till. A tillage operation (disking) was done just prior to the 2001 planting to homogenize the top 0.1 m of soil, incorporate P and K fertilizers, as well as previously accumulated surface residues. Since the tillage operation, the site has been under no-till management until the harvest of 2005. Following harvest, a conservation-plow tillage operation was initiated where a small amount of N fertilizer is sprayed on the residue immediately prior to the plow operation. Approximately 1/3 of the crop residue is left on the surface. The post-harvest conservation-plow operation continues as the current practice.</p> <div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: GeoData catalog record.</p> <p>File Name: Web Page, url: <a href="https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/UniversityOfNebraska1_eaa_2015_March_17_1330" target="_blank">https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/UniversityOfNebraska1_eaa_2015_March_17_1330</a> </p></li></ul>

Tags: affiliation-id-72, agriflux, ars, ceptometer, croplands, data-gov, daylight, daymet, earth-science-agriculture-agricultural-plant-science-cropping-systems, earth-science-agriculture-soils-soil-temperature, earth-science-atmosphere-atmospheric-radiation, earth-science-atmosphere-atmospheric-radiation-incoming-solar-radiation, earth-science-atmosphere-atmospheric-temperature-air-temperature, earth-science-atmosphere-atmospheric-water-vapor, earth-science-atmosphere-atmospheric-water-vapor-humidity, earth-science-atmosphere-atmospheric-winds-surface-winds-wind-speed-wind-direction, earth-science-atmosphere-precipitation, earth-science-land-surface-land-use-land-cover-land-cover, earth-science-land-surface-soils-soil-temperature, eddy-covariance-flux, environment, farming, incident-shortwave-radiation-flux-density, maize, net-radiometers, open-path-co2-h2o-gas-analyzer, portable-photosynthesis-system, precipitation-gauge, pyranometers, pyrgeometers, site-951, snow-water, sonic-anemometer, soybeans, stream-gauges, temperature-humidity-probe, trace-gas-analyzer, us-ne1, water-vapor-pressure
Organization: Department of Agriculture