The USDA-Agricultural Research Service Central Plains Experimental Range (CPER) is a Long-Term Agroecosystem Research (LTAR) network site located ~20 km northeast of Nunn, in north-central Colorado, USA. In 1939, scientists established the Long-term Grazing Intensity study (LTGI) with four replications of light, moderate, and heavy grazing. Each replication had three 129.5 ha pastures with the grazing intensity treatment randomly assigned. Today, one replication remains. Light grazing occurs in pasture 23W (9.3 Animal Unit Days (AUD)/ha, targeted for 20% utilization of peak growing-season biomass), moderate grazing in pasture 15E (12.5 AUD/ha, 40% utilization), and heavy grazing in pasture 23E (18.6 AUD/ha, 60% utilization). British- and continental-breed yearling cattle graze the pastures season-long from mid-May to October except when forage limitations shorten the grazing season. Individual raw data on cattle entry and exit weights, as well as weights every 28-days during the grazing season are available from 2000 to 2019. Cattle entry and exit weights are included in this dataset. Weight outliers (± 2 SD) are flagged for calculating summary statistics or performing statistical analysis.

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.

These data were generated to evaluate the effects of compound hydroclimatic extremes – a deluge during drought – on production and carbon cycling in a semi-arid (shortgrass steppe) grassland in Colorado (USA). The study experimentally imposed an extreme drought and then interrupted this drought with either a single extreme deluge event or the equivalent amount of precipitation provided in several smaller events. This design, focused on how the combined effects of extreme drought and deluge altered productivity and carbon cycling relative to a control treatment receiving ambient rainfall and a drought treatment that received an equal amount of precipitation delivered as events more typical of contemporary rainfall regimes. Research was conducted at the 6,500 ha USDA-Central Plains Experimental Range (CPER), which is part of the Long-Term Agroecosystem Research network (LTAR; 2012-present; https://ltar.ars.usda.gov/), a former Long-Term Ecological Research station (LTER, 1983-2012), and located in the shortgrass steppe of north-central Colorado, USA. Additional information and referenced materials about many of the long-term studies initiated on the CPER can be found: https://dx.doi.org/10.25675/10217/81141. During the 2019 growing season (May-Aug), four precipitation treatments were randomly assigned to forty 1 m^2 plots spaced 2 m apart (n = 10 per precipitation treatment). Precipitation was excluded during the growing season by installing clear plastic roofs (2.2 x 2.2 m) over each plot and then added water to simulate four precipitation treatments: 1. a control treatment (“CON”; based on the exact pattern and amount that occurred at the site in 1989 – a year with an average precipitation regime, see below), 2. a drought treatment (“DRT”; a 77.5% reduction in each event added to the control plots), 3. a drought plus deluge treatment (“DRT+DEL”; the DRT treatment with a 60 mm deluge added mid-July) and 4. a drought plus small events treatment (“DRT+SE”; the DRT treatment, with a total of 60 mm of precipitation added to nine events from mid-July through mid-August). Over the course of the experiment, four response variables were measured: soil moisture, greenness, carbon fluxes, and productivity. Soil moisture was measured weekly from 0-100 cm at 10 cm increments using a Sentek Diviner probe on a subset of plots (n=3 per treatment), using a site-based calibration to calculate volumetric water content. Weekly plot canopy greenness was estimated using repeat digital photography, by calculating the average green chromatic coordinates (GCC) of the pixels in each photograph. Carbon flux measurements were conducted on a subset of plots (n = 5) using a custom portable flux chamber (0.5 x 0.5 x 0.5 m) attached to a LI-6400. During each measurement, data were logged over a 2 min period to collect the light measurement (net ecosystem exchange; NEE), then the chamber was vented for 7 sec and another measurement was taken during a 2 min period of darkness imposed by an opaque chamber cover (ecosystem respiration; ER). After collection, the data were processed, and the last 30 sec of the measurement were averaged to produce a single value for NEE and ER per measurement. Gross primary production (GPP) was calculated as GPP = NEE – ER. Aboveground net primary production (ANPP) was measured in all plots (n = 10 per treatment) at the end of the growing season (mid-September). In each plot, all plant material from two 0.1 m^2 subplots was harvested to ground height. Belowground net primary production (BNPP) was estimated as fine root mass production measured using root ingrowth cores. Net primary production (NPP) was estimated by summing ANPP and BNPP from each plot.

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.

Find and download NLCD data as prepackaged data types and years. You can also interactively view and choose your own download geography and data in a viewer.

The data set covers a 101-year period (1915-2016) of quadrat-based plant sampling at the Jornada Experimental Range in southern New Mexico. At each sampling event, a pantograph was used to record the location and perimeter of living plants within permanent quadrats. Basal area was recorded for perennial grass species, canopy cover area was recorded for shrub species, and all other perennial species were recorded as point data. The data set includes 122 1m by 1m permanent quadrats, although not all quadrats were sampled in each year of the study and there is a gap in monitoring from 1980-1995. These data provide a unique opportunity to investigate changes in the plant community over 100 years of variation in precipitation and other environmental conditions. We provide the following data and data formats: (1) the digitized maps in shapefile format; (2) data table containing coordinates (x,y) of perennial species within quadrats, including cover area for grasses and shrubs; (3) data table of counts of annual plant individuals per quadrat; (4) species list indicating growth form and habit of recorded species; (5) table of dates when each quadrat was sampled; (6) table of the pasture each quadrat was located within (note that pasture boundaries have changed over time). Additional data to help characterize plant-scale factors related to vegetation dynamics at the quadrat locations are: (7) data table of depth to caliche layer; (8) data table of soil particle size analysis and sand fractionation; and (9) data table of local and patch topography. This data package was created to support a specific data paper. Data are also available in data packages knb-lter-jrn.210351001, knb-lter-jrn.210351002, and knb-lter-jrn.210351003. Pantograph sampling is currently conducted at 5 year intervals by USDA-ARS staff, and new data will be added to those data packages periodically.

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.

Introduction Preservation and management of semi-arid ecosystems requires understanding of the processes involved in soil erosion and their interaction with plant community. Rainfall simulations on natural plots provide an effective way of obtaining a large amount of erosion data under controlled conditions in a short period of time. This dataset contains hydrological (rainfall, runoff, flow velocity), erosion (sediment concentration and rate), vegetation (plant cover), and other supplementary information from 272 rainfall simulation experiments conducted on 23 rangeland locations in Arizona and Nevada between 2002 and 2013. The dataset advances our understanding of basic hydrological and biological processes that drive soil erosion on arid rangelands. It can be used to quantify runoff, infiltration, and erosion rates on a variety of ecological sites in the Southwestern USA. Inclusion of wildfire and brush treatment locations combined with long term observations makes it important for studying vegetation recovery, ecological transitions, and effect of management. It is also a valuable resource for erosion model parameterization and validation. Instrumentation Rainfall was generated by a portable, computer-controlled, variable intensity simulator (Walnut Gulch Rainfall Simulator). The WGRS can deliver rainfall rates ranging between 13 and 178 mm/h with variability coefficient of 11% across 2 by 6.1 m area. Estimated kinetic energy of simulated rainfall was 204 kJ/ha/mm and drop size ranged from 0.288 to 7.2 mm. Detailed description and design of the simulator is available in Stone and Paige (2003). Prior to each field season the simulator was calibrated over a range of intensities using a set of 56 rain gages. During the experiments windbreaks were setup around the simulator to minimize the effect of wind on rain distribution. On some of the plots, in addition to rainfall only treatment, run-on flow was applied at the top edge of the plot. The purpose of run-on water application was to simulate hydrological processes that occur on longer slopes (>6 m) where upper portion of the slope contributes runoff onto the lower portion. Runoff rate from the plot was measured using a calibrated V-shaped supercritical flume equipped with depth gage. Overland flow velocity on the plots was measured using electrolyte and fluorescent dye solution. Dye moving from the application point at 3.2 m distance to the outlet was timed with stopwatch. Electrolyte transport in the flow was measured by resistivity sensors imbedded in edge of the outlet flume. Maximum flow velocity was defined as velocity of the leading edge of the solution and was determined from beginning of the electrolyte breakthrough curve and verified by visual observation (dye). Mean flow velocity was calculated using mean travel time obtained from the electrolyte solution breakthrough curve using moment equation. Soil loss from the plots was determined from runoff samples collected during each run. Sampling interval was variable and aimed to represent rising and falling limbs of the hydrograph, any changes in runoff rate, and steady state conditions. This resulted in approximately 30 to 50 samples per simulation. Shortly before every simulation plot surface and vegetative cover was measured at 400 point grid using a laser and line-point intercept procedure (Herrick et al., 2005). Vegetative cover was classified as forbs, grass, and shrub. Surface cover was characterized as rock, litter, plant basal area, and bare soil. These 4 metrics were further classified as protected (located under plant canopy) and unprotected (not covered by the canopy). In addition, plant canopy and basal area gaps were measured on the plots over three lengthwise and six crosswise transects. Experimental procedure Four to eight 6.1 m by 2 m replicated rainfall simulation plots were established on each site. The plots were bound by sheet metal borders hammered into the ground on three sides. On the down slope side a collection trough was installed to channel runoff into the measuring flume. If a site was revisited, repeat simulations were always conducted on the same long term plots. The experimental procedure was as follows. First, the plot was subjected to 45 min, 65 mm/h intensity simulated rainfall (dry run) intended to create initial saturated condition that could be replicated across all sites. This was followed by a 45 minute pause and a second simulation with varying intensity (wet run). During wet runs two modes of water application were used as: rainfall or run-on. Rainfall wet runs typically consisted of series of application rates (65, 100, 125, 150, and 180 mm/h) that were increased after runoff had reached steady state for at least five minutes. Runoff samples were collected on the rising and falling limb of the hydrograph and during each steady state (a minimum of 3 samples). Overland flow velocities were measured during each steady state as previously described. When used, run-on wet runs followed the same procedure as rainfall runs, except water application rates varied between 100 and 300 mm/h. In approximately 20% of simulation experiments the wet run was followed by another simulation (wet2 run) after a 45 min pause. Wet2 runs were similar to wet runs and also consisted of series of varying intensity rainfalls and/or run-on inputs. Resulting Data The dataset contains hydrological, erosion, vegetation, and ecological data from 272 rainfall simulation experiments conducted on 12 sq. m plots at 23 rangeland locations in Arizona and Nevada. The experiments were conducted between 2002 and 2013, with some locations being revisited multiple times.

Recent USDA/ARS patented technologies on bioenergy and the environment that are available for licensing are described, including summary, contact, benefits, and applications. Updated June 2018.

Simulated rainfall and overland-flow experiments are useful for enhancing understanding of surface hydrologic and erosion processes, quantifying runoff and erosion rates, and developing and testing predictive quantitative models. This extensive dataset (1021 experimental plots) consists of rainfall simulation (1300 plot runs, 0.5 m2 to 13 m2 scales) and overland flow (838 plot runs, ~9 m2 scale) experimental plot data coupled with associated measures of vegetation, ground cover, and surface soil properties across point to hillslope scales. The data were collected at three woodland-encroached sagebrush (Artemisia spp.) rangelands in the Great Basin, USA, under undisturbed/untreated conditions and 1 yr to 9 yr following fire and/or mechanical tree-removal treatments. The methodology employed and resulting experimental data contribute to quantifying and understanding scale-dependent surface hydrologic and erosion processes for Great Basin woodlands and sagebrush rangelands before and after tree removal and for sparsely vegetated sites elsewhere. The dataset is a valuable source for developing and testing hydrology and erosion models for applications to diverse vegetation and ground cover conditions. Lastly, the series of repeated measures in the dataset for some sites over time provides a valuable dataset for exploring long-term landscape vegetation and hydrologic and erosion responses to various land management practices and disturbances. The resulting collective dataset of 1021 experimental plots contains vegetation, ground cover, soils, hydrology, and erosion data collected across multiple spatial scales, diverse cover and surface conditions, three study sites, and five different study years. The collective dataset contains 57 plots at the hillslope scale (site characterization plots), 528 small-rainfall plots, 146 large-rainfall plots, and 290 overland-flow plots. The hydrology and erosion experiments yielded time series datasets for small-rainfall plot, large-rainfall plot, and overland-flow plot simulations. Some time series hydrographs and sedigraphs from rainfall and overland flow simulations were excluded due to various equipment failures. The final time series datasets consist of 1020 small-rainfall, 280 large-rainfall, and 838 overland-flow plot run hydrographs and sedigraphs, not excluding plots without runoff. Restricting the data to plots that generated runoff results in 749 small-rainfall, 251 large-rainfall, and 719 overland-flow plot simulation hydrographs and sedigraphs. Overall, the hydrology and erosion time series dataset amounts to 2138 hydrographs/sedigraphs including plots with zero runoff and 1719 hydrographs/sedigraphs for plots that generated runoff. Field experiments and data management were conducted as part of the Sagebrush Steppe Treatment Evaluation Project (SageSTEP, (www.sagestep.org) funded by the US Joint Fire Science Program, US Department of Interior (USDI) Bureau of Land Management, and US National Interagency Fire Center. This dataset is contribution number 134 of the Sagebrush Steppe Treatment Evaluation Project. See README file for information regarding experimental design and methods.