U.S. flag

An official website of the United States government

The Ag Data Commons is migrating

The Ag Data Commons is migrating to a new institutional portal on Figshare. The current system is available for search and download only. The new platform is open for submission with assistance from Ag Data Commons curators. Please contact NAL-ADC-Curator@usda.gov, if you need to publish or update your datasets.

Long Term Agroecosystem Research Overview

In pursuit of sustainable U.S. agriculture, the U.S. Department of Agriculture (USDA) launched the Long-Term Agroecosystem (LTAR) network. The LTAR network is composed of 18 locations distributed across the contiguous United States working together to address national and local agricultural priorities and advance the sustainable intensification of U.S. agriculture.

The LTAR network represents a range of major U.S. agroecosystems, including annual row cropping systems, grazinglands, and integrated systems representative of roughly 49 percent of cereal production, 30 percent of forage production, and 32 percent of livestock production in the United States. Furthermore, the LTAR sites span geographic and climatic gradients representing a variety of challenges and opportunities to U.S. agriculture.

The LTAR network uses experimentation and coordinated observations to develop a national roadmap for the sustainable intensification of agricultural production. While the LTAR network is a new network, experimentation and measurements began at some LTAR sites more than 100 years ago, while other locations started their research as recently as 19 years ago.

A primary goal of LTAR is to develop and to share science-based findings with producers and stakeholders. Tools, technologies, and management practices resulting from LTAR network science will be applied to the sustainable intensification of U.S. agriculture. Technical innovations, including new production techniques, genetics, and sensor infrastructure applied at the farm/ranch level can increase the capacity for adaptive management, reduce time and operational costs, and increase profits and the quality of life for producers.

For full list of LTAR sites, view the sites matrix at https://ltar.ars.usda.gov/sites/.

For more information about the LTAR network visit: https://ltar.ars.usda.gov

Filter by Program

Filter by author name

Filter by Funding Source

Filter by user-supplied tag

Filter by Ag Data Commons keyword

LTAR Research Sites

Data from the following LTAR sites are presented. They are related to topics such as agricultural sustainability, climate change, ecosystem services, and natural resource conservation at the watershed or landscape scale.

  • Archbold Biological Station (ABS), Venus, FL
  • Cook Agronomy Farm (CAF), Pullman, WA
  • Central Mississippi River Basin (CMRB), Columbia, MO
  • Central Plains Experimental Range (CPER), Cheyenne, WY; Fort Collins, CO; Nunn, CO
  • Eastern Corn Belt (ECB), Columbus, OH; West Lafayette, IN
  • Gulf Atlantic Coastal Range (GACP), Tifton, GA
  • Great Basin (GB), Boise, ID; Burns, OR
  • Jornada Experimental Range (JER), Las Cruces, NM
  • Kellogg Biological Station (KBS), southwestern MI
  • Lower Mississippi River Basin (LMRB), Oxford, MS; AR; LA; MO
  • Northern Plains (NP), Mandan, ND
  • Platte River-High Plains Aquifer (PRHP), Lincoln, NE
  • Southern Plains (SP), El Reno, OK
  • Texas Gulf (TG), Riesel, TX
  • Upper Chesapeake Bay (UCB), University Park, PA
  • Upper Mississippi River Basin (UMRB), Ames, IA; MN; WI
  • Walnut Gulch Experimental Watershed (WGEW), Tucson, AZ; Tombstone, AZ
  • Lower Chesapeake Bay (LCB), Beltsville, MD

    • Datasets

    634 datasets

    PhenoCam images from JERNOVEL site, Jornada Experimental Range, New Mexico, USA since 2019

      This data set consists of repeat digital imagery from the tower-mounted digital cameras (hereafter, PhenoCams) at the Jornada Experimental Range. JER is a member of the PhenoCam network, which has as its mission to serve as a long-term, continental-scale, phenological observatory. Imagery is uploaded to the PhenoCam server every 30 minutes. The archived images provide a permanent record that can be visually-inspected to determine the phenological state of the vegetation at any point in time. Vegetation greenness metrics (e.g., GCC) derived from the ratio of the green color band to sum of red, green, and blue color bands serve as proxies for vegetation greenness. Greenness metrics can be extracted from the images using simple image processing methods in 1-day or 3-day increments.

      PhenoCam images from JERGRASSLAND2 site, Jornada Experimental Range, New Mexico, USA since 2022

        This data set consists of repeat digital imagery from the tower-mounted digital cameras (hereafter, PhenoCams) at the Jornada Experimental Range. JER is a member of the PhenoCam network, which has as its mission to serve as a long-term, continental-scale, phenological observatory. Imagery is uploaded to the PhenoCam server every 30 minutes. The archived images provide a permanent record that can be visually-inspected to determine the phenological state of the vegetation at any point in time. Vegetation greenness metrics (e.g., GCC) derived from the ratio of the green color band to sum of red, green, and blue color bands serve as proxies for vegetation greenness. Greenness metrics can be extracted from the images using simple image processing methods in 1-day or 3-day increments.

        PhenoCam images from JERGRASSLAND site, Jornada Experimental Range, New Mexico, USA since 2019

          This data set consists of repeat digital imagery from the tower-mounted digital cameras (hereafter, PhenoCams) at the Jornada Experimental Range. JER is a member of the PhenoCam network, which has as its mission to serve as a long-term, continental-scale, phenological observatory. Imagery is uploaded to the PhenoCam server every 30 minutes. The archived images provide a permanent record that can be visually-inspected to determine the phenological state of the vegetation at any point in time. Vegetation greenness metrics (e.g., GCC) derived from the ratio of the green color band to sum of red, green, and blue color bands serve as proxies for vegetation greenness. Greenness metrics can be extracted from the images using simple image processing methods in 1-day or 3-day increments.

          PhenoCam images from JERSAND site, Jornada Experimental Range, New Mexico, USA since 2014

            This data set consists of repeat digital imagery from the tower-mounted digital cameras (hereafter, PhenoCams) at the Jornada Experimental Range. JER is a member of the PhenoCam network, which has as its mission to serve as a long-term, continental-scale, phenological observatory. Imagery is uploaded to the PhenoCam server every 30 minutes. The archived images provide a permanent record that can be visually-inspected to determine the phenological state of the vegetation at any point in time. Vegetation greenness metrics (e.g., GCC) derived from the ratio of the green color band to sum of red, green, and blue color bands serve as proxies for vegetation greenness. Greenness metrics can be extracted from the images using simple image processing methods in 1-day or 3-day increments.

            Data from: Threshold Behavior of Catchments with Duplex Hillslope Soils Feeding Soil Pipe Networks

              This dataset corresponds with two published studies conducted on loess covered catchments in northern Mississippi, USA within the Goodwin Creek Experimental Watershed that contain extensive networks of soil pipes and corresponding collapse features. These loess soils contain fragipan layers that were found to perch water, thereby initiating the piping processes. The dataset contains data from two papers, specifically these include: (i) the spatial distribution of soil pipe collapses and their size measurements from the Wilson et al. (2015) paper, and (ii) hydrologic measurements of perched water tables on hillslopes, water levels of selected soil pipe locations, and precipitation from the Wilson et al. (2017) paper.

              Choptank Experimental Watershed Soil Moisture Network

                A network of soil moisture and soil temperature profiles as well as solar radiation and precipitation gages are distributed throughout the central region of the DelMarVa peninsula to capture variability of these parameters to give a broad understanding of agricultural conditions in this domain. Soil profile data is captured at depths of 5, 10, 20, and 50 cm below the surface and recorded hourly at locations on the edges of agricultural fields, not inside the production fields.

                Data from: USDA ARS Northern Great Plains Research Laboratory (NGPRL) legacy livestock production (1916-2016) under various rangeland managements with stocking rate and seeded crested wheatgrass

                  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. 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.

                  Gridded 20-Year Parameterization of a Stochastic Weather Generator (CLIGEN) for South American and African Continents at 0.25 Arc Degree Resolution

                    CLImate GENerator (CLIGEN) is a stochastic weather generator that produces daily and sub-daily timeseries of weather variables. The resulting timeseries are statistically similar to observed timeseries considering various temporal scales and climate factors. This dataset consisting of CLIGEN inputs may be used to generate timeseries at any point in a 0.25 arc degree resolution grid covering South American and African continents.