Published September 23, 2022 | Version 1.0
Dataset Open

Quantitative Representativeness and Constituency of the Long-Term Agroecosystem Research Network

  • 1. Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
  • 2. USDA-ARS, Southeast Watershed Research Laboratory, Tifton, Georgia, USA
  • 3. USDA-ARS, Cropping Systems and Water Quality Research Unit, Columbia, Missouri, USA
  • 4. Department of Natural Resources and the Environment, University of Arizona, Tucson, AZ, USA
  • 5. USDA-ARS, National Sedimentation Laboratory, Oxford, MS, USA
  • 6. USDA Forest Service, Southern Research Station, Asheville, NC, USA

Description

Data Description:

The USDA Long-Term Agroecosystem Research (LTAR) Network coordinates agricultural research across 18 research sites in the conterminous United States (CONUS). However, it is unclear how well these sites represent the totality of agricultural working lands within the CONUS. Therefore, we performed a quantitative analysis of the 18 sites, based on 15 climatic and edaphic characteristics, to produce maps of representativeness and constituency across the CONUS. Representativeness shows how well the combination of environmental drivers at each CONUS location was represented by the LTAR sites’ environments, while constituency shows which LTAR site was the closest match for each location.

Files in collection (22):

Collection contains 11 geospatial rasters and 11 PNGs visualizing them.

TIF files:

├── conus_ltar_constituency_workinglands.tif                            [Constituency of LTAR network]
├── conus_ltar_representativeness_workinglands.tif                  [Representativeness of LTAR network]
├── conus_ltar_v5.pc1.tif                                                             [Principal Component 1]
├── conus_ltar_v5.pc2.tif                                                             [Principal Component 2]
├── conus_ltar_v5.pc3.tif                                                             [Principal Component 3]
├── conus_ltar_v5.pc4.tif                                                             [Principal Component 4]
├── conus_ltar_v5.pc5.tif                                                             [Principal Component 5]
├── conus_ltar_v5.pc6.tif                                                             [Principal Component 6]
├── conus_ltar_v5.pc7.tif                                                             [Principal Component 7]
├── LTAR_NEON_LTER_bestnetwork_workinglands.tif              [Raster identifying best network, among LTAR, NEON, LTER, representing the location]
└── LTAR_NEON_LTER_representativeness_workinglands.tif   [Representativeness of combined LTAR + NEON + LTER networks]

PNG files:

├── conus_ltar_constituency_workinglands.png                            [Constituency of LTAR network]
├── conus_ltar_representativeness_workinglands.png                  [Representativeness of LTAR network]
├── conus_ltar_v5.pc1.png                                                             [Principal Component 1]
├── conus_ltar_v5.pc2.png                                                             [Principal Component 2]
├── conus_ltar_v5.pc3.png                                                             [Principal Component 3]
├── conus_ltar_v5.pc4.png                                                             [Principal Component 4]
├── conus_ltar_v5.pc5.png                                                             [Principal Component 5]
├── conus_ltar_v5.pc6.png                                                             [Principal Component 6]
├── conus_ltar_v5.pc7.png                                                             [Principal Component 7]
├── LTAR_NEON_LTER_bestnetwork_workinglands.png              [Raster identifying best network, among LTAR, NEON, LTER, representing the location]
└── LTAR_NEON_LTER_representativeness_workinglands.png   [Representativeness of combined LTAR + NEON + LTER networks]

Data format:

Geospatial files are provided in Geotiff format in Lat/Lon WGS84 EPSG: 4326 projection at 30 arc second resolution, while the geospatial visualizations are provided in PNG format.

Geospatial projection

GEOGCS["GCS_WGS_1984",
    DATUM["D_WGS_1984",
        SPHEROID["WGS_1984",6378137,298.257223563]],
    PRIMEM["Greenwich",0],
    UNIT["Degree",0.017453292519943295]]
(base) [jbk@theseus ltar_regionalization]$ g.proj -w
GEOGCS["wgs84",
    DATUM["WGS_1984",
        SPHEROID["WGS_1984",6378137,298.257223563]],
    PRIMEM["Greenwich",0],
    UNIT["degree",0.0174532925199433]]

Category labels for Constituency data:

 
Cat LTAR Siite
1 Archbold-University of Florida
2 Central Mississippi River Basin
3 Central Plains Experimental Range
4 Eastern Corn Belt
5 Great Basin
6 Gulf Atlantic Coastal Plain
7 Jornada Experimental Range
8 Kellogg Biological Station
9 Lower Chesapeake Bay
10 Lower Mississippi River Basin
11 Northern Plains
12 Platte River High Plains Aquifer
13 R.J. Cook Agronomy Farm
14 Southern Plains
15 Texas Gulf
16 Upper Chesapeake Bay
17 Upper Mississippi River Basin
18 Walnut Gulch Experimental Watershed

Paper describing data and methods:

Kumar, J., Coffin, A. W., Baffaut, C., Ponce-Campos, G. E., Witthaus, L., & Hargrove, W. W. (2023). Quantitative Representativeness and Constituency of the Long-Term Agroecosystem Research Network and Analysis of Complementarity with Existing Ecological Networks. In Environmental Management. Springer Science and Business Media LLC. https://doi.org/10.1007/s00267-023-01834-9

 

Files

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