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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

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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

    272 datasets

    PhenoCam images from JERSHRUBLAND2 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 JERSHRUBLAND 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 JERWERN site, Jornada Experimental Range, New Mexico, USA since 2017

          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 JERNOVEL2 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 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.