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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

    632 datasets

    Data from: Can measurements of foraging behaviour predict variation in weight gains of free-ranging cattle?

      This study examines whether four different ways of measuring daily foraging behaviour (grazing-bout duration, grazing time per day, velocity while grazing, and turn angle while grazing) were related to weight gain by free-ranging yearling steers grazing semiarid rangeland. Data include measurements interpreted from neck collars supporting a solar-powered device that measured GPS locations at 5 min intervals and an accelerometer to predict grazing activity at 4 sec intervals.

      ASRU Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Sidney, Montana

        Information is needed to mitigate dryland soil greenhouse gas (GHG) emissions by using novel management practices. We evaluated the effects of cropping sequence and N fertilization on dryland soil temperature and water content at the 0- to 15-cm depth and surface CO2, N2O, and CH4 fl uxes in a Williams loam (fi ne-loamy, mixed, superactive, frigid, Typic Argiustolls) in eastern Montana.

        Data from: Plant Tissue Characteristics of Miscanthus x giganteus v2

          As part of a study identifying relationships between environmental variables and insect distributions within a bioenergy crop, giant miscanthus (Miscanthus x giganteus) samples were collected in October 2016 at 33 locations within a field in southeast Georgia, USA. This dataset describes the chemical composition of giant miscanthus leaves and stems including the total carbon (TC) and nitrogen (TN) content, total macro- and micronutrients.

          Agricultural Collaborative Research Outcomes System (AgCROS)

            The Agricultural Collaborative Research Outcomes System (AgCROS) is a growing “network of networks” that presently consists of multiple agricultural data networks: Nutrient Uptake and Outcome Network (NUOnet), the Greenhouse gas Reduction through Agricultural Carbon Enhancement Network (GRACEnet), Resilient Economic Agricultural Practices (REAP), Dairy Agriculture for People and the Planet (DAPP; Dairy Grand Challenge), Soil Health Assessment Network (SHAnet), Agricultural Antibiotic Resistance (AgAR), and the Long-Term Agroecosystem Research (LTAR) Network. By integrating these diverse database networks, AgCROS facilitates the flow of information and increases the cooperation among researchers participating in these networks.

            Agricultural Collaborative Research Outcomes System (AgCROS)

              The Agricultural Collaborative Research Outcomes System (AgCROS) is a growing “network of networks” that presently consists of multiple agricultural data networks: Nutrient Uptake and Outcome Network (NUOnet), the Greenhouse gas Reduction through Agricultural Carbon Enhancement Network (GRACEnet), Resilient Economic Agricultural Practices (REAP), Dairy Agriculture for People and the Planet (DAPP; Dairy Grand Challenge), Soil Health Assessment Network (SHAnet), Agricultural Antibiotic Resistance (AgAR), and the Long-Term Agroecosystem Research (LTAR) Network. By integrating these diverse database networks, AgCROS facilitates the flow of information and increases the cooperation among researchers participating in these networks.