CSR1 Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Watkinsville, Georgia

Rarámuri Criollo cows have behavioral traits that are desirable for rangelands in arid environments, but calves from this biotype are difficult to market through conventional methods. One strategy to improve marketability is to crossbreed these cows with traditional beef breed bulls. However, it is unclear whether crossbred calves will achieve marketable weights and carcass qualities on rangeland and whether they will retain the desirable grazing behaviors of their mothers. We evaluated these traits for two cohorts of Rarámuri Criollo (JRC), Mexican Criollo (MC), and Criollo × beef-breed crossbred (XC) steers. Final live and carcass weights of XC were greater than JRC and MC, but all three groups were market ready at 30-mo after finishing on grass. Carcass quality and average daily gain did not differ among biotypes. Both JRC and XC steers exhibited grazing patterns similar to those previously observed in JRC cows. These results suggest JRC, MC, and XC steers can achieve desirable slaughter weights in 30 months using a rangeland-based grass-fed protocol, and JRC and XC steers retain desirable grazing behaviors of JRC cows.

The USDA-Agricultural Research Service High Plains Grasslands Research Station (HPGRS) is located in Cheyenne, Wyoming, USA. In 1982, a long-term stocking rate study on northern mixed-grass prairie was initiated with season-long (early June to October) grazing. Stocking rates defined as light (35% below NRCS recommended rate, 15 yearlings per 80 ha), moderate (NRCS recommended rate, 4 yearlings per 12ha), and heavy (33% above NRCS recommended rate, 4 yearlings per 9 ha). British- and continental-breed yearling cattle were used throughout the study years. When forage supply was limited due to drought, grazing seasons were shortened or cattle were not grazed for that season. Individual raw data on cattle entry and exit weights are available from 1982 to 2022. No grazing occurred in the years 1989, 2000, and 2002 due to drought conditions. Weight gain outliers (± 2 sd of treatment mean) were removed from the dataset.

Established in 1912, the Northern Great Plains Research Laboratory (NGPRL) is a USDA Agricultural Research Service facility located in Mandan, Morton County, North Dakota. In 1916, NGPRL scientists established a long-term rangeland management research project focusing on developing the most appropriate stocking rates for rangelands in the region. The research project ran for 100 years and included pasture 62, a heavily stocked pasture, and 66, a moderately stocked pasture for the entire time. Also, in 1931, pasture 37 was converted from smooth bromegrass to crested wheatgrass, which was both lightly and moderately stocked. NGPRL's grazing season is traditionally May-October which reflects the surrounding region. Animals may be put on slightly later or pulled earlier due to extreme weather conditions or events (e.g. drought, blizzard). The legacy livestock production data from these pastures include 100 years (1916-2016) of livestock production data from pastures 62 and 66 and 84 years (1932-2016) from pasture 37. Pasture 37 was fertilized annually in spring with 40 pounds nitrogen urea [46-0-0] per acre until 2010 and after that it was fertilized intermittently. Grazing treatments on these pastures were applied with stocking rates calculated in 1916 based on 600 lb. animal. Stocking rates were adjusted when pasture sizes were decreased, and this information is included in the data dictionary for the stocking rate and AUM data table. Please note data is missing from 1984 and 1985 from all the pastures. Johnson Thatcher Sarvis established the experiment in 1915 and managed it until 1940. The experiment was continued by George Rogler from 1940 to 1952, Russell Lorenz and George Rogler from 1953 to 1973, Russell Lorenz from 1974 to 1979, Lenat Hofmann from 1980 to 1992, and James Karns from 1993 to 2002. Numerous technicians and part-time students were also involved in the day-to-day management and conduct of the experiment. We would like to recognize these scientists and support staff for their extraordinary foresight and determination in skillfully managing and continuing this experiment into the twenty-first century. Thanks also to Holly Johnson at the Northern Great Plains Research Laboratory for organizing, cataloging, and annotating the publications from the long-term experiment.

Red Bluff Research Ranch is a 13,750-acre ranch is part of the Montana Agricultural Experiment station, and associated with Montana State University in Bozeman, MT. The ranch occupies most of the once thriving late 19th- to early 20th-century gold mining community in the Hot Springs Mining District, which was second only in gold production to Alder Gulch. The ranch nearly surrounds the town of Norris. Historically about 900 head of sheep were maintained year-round at the research ranch. The livestock, as well as the rangeland, are used for both teaching and research. Sheep nutrition studies included nutrition levels, management practices and sheep behavior. Animal scientists look at breeding as a major way to improve livestock production. Hybridization was studied in sheep to help predict staple length, open faces, smoothness and body conformation related to better and more meat. These data include ewe and lamb body condition, breeding and production data from 1960-2012. Supported/funded by Montana State University College of Agriculture, Montana Agricultural Research Service, Montana Wool Lab., and the USDA Agricultural Research Service.

Global Warming Potential Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Mandan, North Dakota No long-term evaluation of net global warming potential (GWP) for grassland ecosystems in the northern Great Plains (NGP) of North America has been reported. Given this need, we sought to determine net GWP for three grazing management systems located within the NGP. Grazing management systems included two native vegetation pastures (moderately grazed pasture [MGP], heavily grazed pasture [HGP]) and a heavily grazed crested wheatgrass [Agropyron desertorum (Fisch. ex. Link) Schult.] pasture (CWP) near Mandan, ND. Factors evaluated for their contribution to GWP included (i) CO2 emissions associated with N fertilizer production and application, (ii) literature-derived estimates of CH4 production for enteric fermentation, (iii) change in soil organic carbon (SOC) over 44 yr using archived soil samples, and (iv) soil–atmosphere N2O and CH4 fl uxes over 3 yr using static chamber methodology. Analysis of SOC indicated all pastures to be significant sinks for SOC, with sequestration rates ranging from 0.39 to 0.46 Mg C ha−1 yr−1. All pastures were minor sinks for CH4 (<2.0 kg CH4–C ha−1 yr−1). Greater N inputs within CWP contributed to annual N2O emission nearly threefold greater than HGP and MGP. Due to diff erences in stocking rate, CH4 production from enteric fermentation was nearly threefold less in MGP than CWP and HGP. When factors contributing to net GWP were summed, HGP and MGP were found to serve as net CO2equiv. sinks, while CWP was a net CO2equiv. source. Values for GWP and GHG intensity, however, indicated net reductions in GHG emissions can be most eff ectively achieved through moderate stocking rates on native vegetation in the NGP.

NatureScot has commissioned a new dataset of mountain woodland locations across Scotland; to be used to inform landscape scale restoration, 30x30 goals, Nature Networks, UK and European Reporting and Area based casework, and training data for habitat mapping. A total of 128 mountain woodland restoration sites have been compiled across Scotland, covering a total gross area of 10,844 ha. There are a total of 57 sites which contain a component targeting Annex 1 Habitat H4080, 4 sites which contain a component targeting H5130, and 8 sites which target both. Contributing organisations have participated in a purely voluntary capacity and the dataset will therefore not be an absolute list of all restoration work across Scotland. It is recommended that this new dataset is updated every three to five years.This dataset contains the following fields:UID: Unique IdentifierORG: Who was/is responsible for the restoration projectLOCATION: Name of the geographical areaSITE_NAME: Unique name for the restoration siteSTATUS: Current/Proposed/Unknown i.e. an older site which may not have been recently assessedAREA: Area of the polygon (in ha), or total area combined if the site is composed of multiple polygonsFENCED: Yes/NoPOLY_FENCE: Does the polygon show the location of a fenceline? - Yes - No (within a larger fenced area): the fenced area is larger than the given polygon - No (within a larger proposed fenced area): the proposed fenced area is larger than the given polygon - No (smaller fenced areas are within this larger polygon): the polygon given is the larger restoration project area which contains several smaller unmapped fenced sites - N/A: Area is not fencedFENCE_NOTE: Further details on fencing, such as the date installed and the type of fencingMANAGEMENT: Fencing/planting/regeneration/low interventionTARGET_HAB: General description of the intended habitat as an outcome of restoration management at the siteEUNIS_2017: Intended habitat type classed using the EUNIS habitat classification given by Strachan (2017)EUNIS_2021: Intended habitat type classed using the EUNIS habitat classification revised in 2021NVC: Intended habitat type classed using NVC codes given by Averis et al. (2004)UK_BAP: Intended habitat type classed using UK Biodiversity Action Plant habitatsANNEX1: Intended habitat type classed using EU Habitats Directive Annex 1 definitions (if applicable)DATE_PLANT: Date or date range when tree planting took place (if applicable)TARGET_SP: Tree or shrub species featuring in the restoration project, either by planting and/or as the focus of natural regenerationINFO_PLANT: Details on the numbers of trees planted per species (if known).SPECIALIST_SP: List of specialist montane scrub species included in the project (if applicable)PRO_MS_SP: The provenance of planted arctic-alpine willows (if applicable)NOTES_MAN: Any other key management details of the restoration project not already given in previous columns Complete metadata document on spatialdata.gov.scot.

NatureScot has commissioned this new dataset of mountain woodland locations across Scotland; to be used to inform landscape scale restoration, 30x30 goals, Nature Networks, UK and European Reporting and Area based casework, and training data for habitat mapping. A total of 18,538 point records have been compiled across 24 tree and shrub taxa that feature in mountain woodland habitats in Scotland. From these records, there are a total of 324 that qualify for Annex 1 H4080, and a total of 210 that qualify for Annex 1 H5130. However, some geographical areas have had higher recording effort than others. It is recommended that this new dataset is updated every three years, or annually for the Nationally Rare/Scarce arctic-alpine willows and scrub specialist species. The BSBI DDb will be the primary source of information for updates.This dataset contains the following fields:UID: Unique IdentifierTAXON: Latin name, as given in Stace (2019)COMMON_NAME: The common name used in the Scottish contextGROUP: Mountain woodland species; classed into the following categories:Arctic-alpine specialist willows: Nationally Rare or Scarce component species of Sub-Arctic Salix scrub/Montane willow scrub (H480). These records cover any altitudeSub-montane willows: Can form a secondary component of Sub-Arctic Salix scrub/Montane willow scrub (H4080), usually at the lower end of the altitudinal range of the habitat. These records are at altitudes ≥ 400mScrub specialists: Nationally Scarce taxa which feature in upland scrub habitats. These records cover any altitudeSecondary montane/sub-montane trees or shrubs: Taxa which feature in lower altitude woodland or scrub habitats, but can grow at sub-montane and montane altitudes. These records are at altitudes ≥ 400mJuniper: A key component of H5130 habitat. These records are at altitudes ≥ 400m, so only apply to the habitat where it is found in the uplandsMountain broadleaves: Occurrences of Birch or Rowan at higher altitudes. These records are at altitudes ≥ 600mTreeline scrub: Records retained from the OMSD (Original Montane Scrub Database)RECORDER: Person(s) who made the record (if known)PLACENAME: Named location of the recordEASTING: 6-figure British National Grid Easting, including the 100km x 100km prefixNORTHING: 6-figure British National Grid Northing, including the 100km x 100km prefixPRECISION: Record precision (1km, 100m, 10m or 1m)DATE: When the record was madeHABITAT_DIRECTIVE_H4080: Annex 1 Habitat assigned to either “H4080” or “Potential H4080” using the definitions in Table 1 (if applicable)HABITAT_DIRECTIVE_H5130: Annex 1 Habitat assigned to either “H5130” or “Potential H5130” using the definitions in Table 2 (if applicable)COMMENTS: Further notes about the record, if given by the recorder(s)ADUNDANCE: Notes on the abundance of plants, if given by the recorder(s)SOURCE: Where the record was obtained fromURL: Link to the record on the BSBI DDb (if applicable)Complete metadata document on spatialdata.gov.scot.

Nitrogen Source Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Mandan, North Dakota Use of dietary amendments to reduce nitrogen (N) in excreta represents a possible strategy to decrease greenhouse gas (GHG) emissions from livestock. In this regard, ingestion of small amounts of condensed quebracho tannin has been found to reduce N concentration in livestock urine. In this study, we sought to quantify the effects of tannin-affected cattle urine, normal cattle urine, and NH4NO3 in solution on greenhouse gas flux. Carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) flux was measured using static chamber methodology from the three N treatments and a no application control over a six-week period in a mixed grass prairie in west-central North Dakota, USA. Over the course of the study, average CO2 emission was greatest from normal urine (335 ± 8 mg C m-2 hr-1) and least from the control (229 ± 19 mg C m-2 hr-1), with intermediate fluxes for the tannin urine and NH4NO3 treatments (290 ± 27 and 286 ± 54 mg C m-2 hr-1, respectively). Methane uptake was prevalent throughout the study, as soil conditions were predominantly warm and dry. Uptake of CH4 was greatest within the control (-30 ± 2 µg C m-2 hr-1) and least in the tannin urine treatment (-12 ± 4 µg C m-2 hr-1). Uptake of CH4 was over 40% less within the tannin urine treatment as compared to normal urine, and may have been repressed by the capacity of tannin to bind monooxygenases responsible for CH4 oxidation. Average N2O emission from NH4NO3 solution was more than twice that of all other treatments. Though the tannin urine treatment possessed 34% less N than normal cattle urine, cumulative N2O emission between the treatments did not differ. Results from this study suggest the use of condensed quebracho tannin as a dietary amendment for livestock does not yield GHG mitigation benefits in the short-term.

Note: To download this raster dataset, go to ArcGIS Open Data Set and click the download button, and under additional resources select any of the download options. Data can also be downloaded from the FSGeodata Clearinghouse.More information about rangeland productivity and the effects of drought are available in this StoryMap; additional drought and rangeland products from the Office of Sustainability and Climate are available in our Climate Gallery. Time enabled image service showing estimates of annual production of rangeland vegetation.Production data were generated using the Normalized Difference Vegetation Index (NDVI) from the Thematic Mapper Suite from 1984 to 2021 at 250 m resolution. The NDVI is converted to production estimates using two regression formulas depending on the level of the NDVI; there is one equation for lower values (and thus lower production values) and one for higher values. This raster dataset yields estimates of annual production of rangeland vegetation and should be useful for understanding trends and variability in forage resources. This raw lbs/acre data that the Z-scores were derived from as well as the Z-scores dataset can be downloaded from: https://data.fs.usda.gov/geodata/rastergateway/rangelands/index.phpMore information about rangeland productivity and the effects of drought are available in this story map.

Production data were generated using the Normalized Difference Vegetation Index (NDVI) from the Thematic Mapper Suite from 1984 to 2021 at 250 m resolution. The NDVI is converted to production estimates using two regression formulas depending on the level of the NDVI; there is one equation for lower values (and thus lower production values) and one for higher values.This raster dataset yields estimates of annual production of rangeland vegetation and should be useful for understanding trends and variability in forage resources.The Rangeland Productivity data can be downloaded here:https://data.fs.usda.gov/geodata/rastergateway/rangelands/index.php

Quick Stats is the National Agricultural Statistics Service's (NASS) online, self-service tool to access complete results from the 1997, 2002, 2007, and 2012 Censuses of Agriculture as well as the best source of NASS survey published estimates. The census collects data on all commodities produced on U.S. farms and ranches, as well as detailed information on expenses, income, and operator characteristics. The surveys that NASS conducts collect information on virtually every facet of U.S. agricultural production.

Quick Stats API is the programmatic interface to the National Agricultural Statistics Service's (NASS) online database containing results from the 1997, 2002, 2007, and 2012 Censuses of Agriculture as well as the best source of NASS survey published estimates. The census collects data on all commodities produced on U.S. farms and ranches, as well as detailed information on expenses, income, and operator characteristics. The surveys that NASS conducts collect information on virtually every facet of U.S. agricultural production.