Genome analysis of the ubiquitous boxwood pathogen Pseudonectria foliicola: A small fungal genome with an increased cohort of genes associated with loss of virulence

Boxwood plants are affected by many different diseases caused by fungi. Some boxwood diseases are deadly and quickly kill the infected plants, but with others, the plant can survive and even thrive when infected. The fungus that causes volutella blight is the most common of these weak boxwood pathogens. Even the healthiest boxwood plants are infected by the volutella fungus, and often there are no signs that the plants are hurt by the infection. In order to understand why the volutella blight fungus is such a weak pathogen and to understand the genetic mechanisms it uses to interact with boxwood, the complete genome of the volutella fungus was sequenced and characterized. These datasets are generated from the genome sequence of Pseudonectria foliicola, strain ATCC13545, the fungus responsible for volutella disease of boxwood. Datasets include the nuclear genome and mitochondrial genome assemblies (sequenced using Illumina technology), the predicted gene model dataset generated using MAKER, the multiple sequence alignment of single-copy orthologs used for phylogenetic analysis, CMAP files generated from SimpleSynteny analysis of mitogenomes, and high quality photographic images.

Genomics and Genetics

Data from: Soil organic carbon and isotope composition response to topography and erosion in Iowa

The dataset includes topographic information, soil properties, and 137Cs levels collected from a 15 ha cropland under soybean/maize (C3/C4) rotation in June 2002. The cropland is located in the central-western part of the Walnut Creek watershed, Story County, Iowa. 128 sampling locations were collected and three soil samples were obtained using a 3.2 cm-diameter push probe from the 0 to 30 cm soil layer within a 1 m × 1 m quadrat at each sampling location. Deeper soil samples were collected from 30 to 50 cm layers in locations where sediment deposition was observed. The three samples from each sampling location were mixed and analyzed to determine soil properties, SOC content and its carbon (C) isotope composition (C12 to C13 ratio), and 137Cs levels. For landscape topography of each sampling location, topographic metrics were derived from a digital elevation mode using LiDAR (Light Detection and Ranging) data. These data are useful in investigating the fate of eroded SOC in croplands and its responses to landscape topography.

Agroecosystems & Environment

VegScape - Vegetation Condition Explorer

VegScape https://nassgeodata.gmu.edu/VegScape/ delivers interactive vegetation indices so that web users can explore, visualize, query, and disseminate current vegetative cover maps and data without the need for specialized expertise, software, or high end computers. New satellite-based data are loaded on a weekly basis during the growing season. One can compare year-to-year change since the year 2000, compare conditions at a given times to mean, median and ratio vegetative cover, and can overlay a crop mask to help identify crop land versus non-crop land, among many functions. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), and mean, median, and ratio comparisons to prior years have proven useful for assessing crop condition and identifying the land area impacted by floods, drought, major weather anomalies, and vulnerabilities of early/late season crops. The National Aeronautics Space Administration's MODIS satellite is used for this project and provides imaging at 250 meter (15 acres) per pixel resolution. Additionally, the data can be directly exported to Google Earth for mashups or delivered to other applications via web services.

Agroecosystems & Environment

NASS Data Visualization

NASS Data Visualization provides a dynamic web query interface supporting searches by Commodity (e.g. Cotton, Corn, Farms & Land, Grapefruit, Hogs, Oranges, Soybeans, Wheat), Statistic type (automatically refreshed based upon choice of Commodity - e.g. Inventory, Head, Acres Planted, Acres Harvested, Production, Yield) to generate chart, table, and map visualizations by year (2001-2016), as well as a link to download the resulting data in CSV format compatible for updating databases and spreadsheets.

Agricultural Products

NASS - Quick Stats

The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by the USDA National Agricultural Statistics Service (NASS). It allows you to customize your query by commodity, location, or time period. You can then visualize the data on a map, manipulate and export the results as an output file compatible for updating databases and spreadsheets, or save a link for future use. Quick Stats contains official published aggregate estimates related to U.S. agricultural production. County level data are also available via Quick Stats.

Agricultural Products

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.

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Data from: Identifying Critical Life-Stage Transitions for Vincetoxicum Biological Control, Long-lived Perennial Invaders

This dataset includes data on 25 transitions of a matrix demographic model of the invasive species Vincetoxicum nigrum (L.) Moench (black swallow-wort or black dog-strangling vine) and Vincetoxicum rossicum (Kleopow) Barb. (pale swallow-wort or dog-strangling vine) (Apocynaceae, subfamily Asclepiadoideae), two invasive perennial vines in the northeastern U.S.A. and southeastern Canada. The matrix model was developed for projecting population growth rates as a result of changes to lower-level vital rates from biological control although the model is generalizable to any control tactic.

Agroecosystems & Environment

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.

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Natural Resource and Genomics Data System

This application represents the public facing presence for Greenhouse Gas Reduction through Agricultural Carbon Enhancement Network (GRACEnet) and Resilient Economic Agricultural Practices (REAP). Other projects such as Agricultural Antibiotic Resistance (AgAR), Nutrient Use and Outcome Network (NUOnet), and others will be added to this application in the future.

Agroecosystems & Environment