U.S. flag

An official website of the United States government

Soil Series Classification Database (SC)

    The USDA-NRCS Soil Series Classification Database contains the taxonomic classification of each soil series identified in the United States, Territories, Commonwealths, and Island Nations served by USDA-NRCS. Along with the taxonomic classification, the database contains other information about the soil series, such as office of responsibility, series status, dates of origin and establishment, and geographic areas of usage.

    Data from: Starch and dextrose at 2 levels of rumen-degradable protein in iso-nitrogenous diets: Effects on lactation performance, ruminal measurements, methane emission, digestibility, and nitrogen balance of dairy cows.

      This feeding trial was designed to investigate two separate questions. The first question is, “What are the effects of substituting two non-fiber carbohydrate (NFC) sources at two rumen-degradable protein (RDP) levels in the diet on apparent total-tract nutrient digestibility, manure production and nitrogen (N) excretion in dairy cows?”. This is relevant because most of the N ingested by dairy cows is excreted, resulting in negative effects on environmental quality. The second question is, “Is phenotypic residual feed intake (pRFI) correlated with feed efficiency, N use efficiency, and metabolic energy losses (via urinary N and enteric CH4) in dairy cows?”. The pRFI is the difference between what an animal is expected to eat, given its level of productivity, and what it actually eats. The goal was to determine whether production of CH4, urinary N or fecal N is a driver of pRFI.

      Oncopeltus fasciatus hybrid genome assembly 1.0

        The milkweed bug, *Oncopeltus fasciatus*, was sequenced as part of the i5k pilot project from Baylor College of Medicine (Illumina data). To augment those resources, we present here a hybrid genome assembly with low coverage PacBio data, assembled with PBJelly: the *Oncopeltus fasciatus* Hybrid Genome Assembly v1.0.

        Data from: Range size, local abundance and effect inform species descriptions at scales relevant for local conservation practice

          This study describes how metrics defining invasions may be more broadly applied to both native and invasive species in vegetation management, supporting their relevance to local scales of species conservation and management. A sample monitoring dataset is used to compare range size, local abundance and effect as well as summary calculations of landscape penetration (range size × local abundance) and impact (landscape penetration × effect) for native and invasive species in the mixed-grass plant community of western North Dakota, USA.

          Data from: Data for the calculation of an indicator of the comprehensiveness of conservation of useful wild plants

            The datasets and code presented in this Data in Brief article are related to the research article entitled "Comprehensiveness of conservation of useful wild plants: an operational indicator for biodiversity and sustainable development targets". These data facilitate indicator assessments and serve as a baseline against which future calculations of the indicator can be measured. The data can also contribute to other species distribution modeling, ecological research, and conservation analysis purposes.

            Data from: The downed and dead wood inventory of forests in the United States

              The Forest Inventory and Analysis program of the United States (US) Forest Service has conducted an annual downed dead wood (DDW) inventory on all coterminous US forest land since 2002 (~1 plot per 38,850 ha), with a sample intensification occurring since 2012 (~1 plot per 19,425 ha). The data are organized according to DDW components and by sampling information which can all be linked to a multitude of auxiliary information in the national database.

              RF-CLASS: Remote-sensing-based Flood Crop Loss Assessment Service System

                The Remote-sensing-based Flood Crop Loss Assessment Service System (RF-CLASS) is an Earth Observation (EO) based flood crop loss assessment cyber-service system operated by the Center for Spatial Information Science and Systems (CSISS), George Mason University. RF-CLASS supports flood-related crop statistics and insurance decision-making.