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RCA Report - Interactive Data Viewer

    This site supports the Soil and Water Resources Conservation Act (RCA) by providing data from a variety of sources, including data on the status and trends of natural resources, conservation efforts (funding and conservation practices applied), and the agricultural sector. Reports can be created at the State, Regional, or National level.

    Invasive and Exotic Species of North America - Invasive.org

      [Invasive.org](https://www.invasive.org/) is a joint project between University of Georgia's Bugwood Network and the U.S. Department of Agriculture. Over 8,300 images, including over 1,000 new images of invasive/exotic/noxious plant, insect, pathogen and other species (including many weeds) and their biological control agents, taken by over 250 photographers. Most images were digitized from high-resolution 35mm slides. Multiple levels of jpeg format images are downloadable and may be copied and used for any non-profit, educational purpose with appropriate credit and copyright notice. Although most images are North American in nature, the system also contains images of organisms that are "Non-U.S. Natives", or are considered to be "U.S. Invasives."

      Data from: Transcriptomes of bovine ovarian follicular and luteal cells

        Gene 1.0 ST Array RNA expression analysis was performed on four somatic ovarian cell types: the granulosa cells (GCs) and theca cells (TCs) of the dominant follicle and the large luteal cells (LLCs) and small luteal cells (SLCs) of the corpus luteum. The normalized linear microarray data was deposited to the NCBI GEO repository (GSE83524). Subsequent ANOVA determined genes that were enriched (≥2 fold more) or decreased (≤−2 fold less) in one cell type compared to all three other cell types, and these analyzed and filtered datasets are presented as tables. Genes that were shared in enriched expression in both follicular cell types (GCs and TCs) or in both luteal cells types (LLCs and SLCs) are also reported.

        Data from: Underestimation of N2O emissions in a comparison of the DayCent, DNDC, and EPIC 1 models

          Process-based models are increasingly used to study mass and energy fluxes from agro-ecosystems, including nitrous oxide (N2O) emissions from agricultural fields. This data set is the output of three process-based models – DayCent, DNDC, and EPIC – which were used to simulate fluxes of N2O from dairy farm soils. The individual models' output and the ensemble mean output were evaluated against field observations from two agricultural research stations in Arlington, WI and Marshfield, WI. These sites utilize cropping systems and nitrogen fertilizer management strategies common to Midwest dairy farms.

          Ricebase

            Ricebase ([https://ricebase.org](https://ricebase.org)) is an integrative genomic database for rice (Oryza sativa) with an emphasis on combining datasets in a way that maintains the key links between past and current genetic studies. Ricebase includes DNA sequence data, gene annotations, nucleotide variation data and molecular marker fragment size data.

            Data from: Comparative farm-gate life cycle assessment of oilseed feedstocks in the Northern Great plains

              This MS Word document contains the oilseed feedstock farm-gate model inventories, results, and uncertainty analyses for the Northern Great Plains discussed in Moeller et. al 2017. Analysis was conducted using IPCC GHG standardized emissions. Methodology is detailed in the associated publication (doi: 10.1007/s41247-017-0030-3). The supplementary information contains the names of the ecoinvent inventories; oilseed yield, seeding rates, and fertilization rates per USDA crop management zone (CMZ); climate change, freshwater eutrophication, and marine eutrophication percent contributions ReCiPe results per CMZ; Monte Carlo uncertainty results per CMZ; and farm-gate energy balance analysis results per CMZ.

              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.