We are upgrading the repository! We will continue our upgrade in February 2025 - we have taken a break from the upgrade to open some collections for end-of-semester submission. The MS-GIST Master's Reports, SBE Senior Capstones, and UA Faculty Publications collections are currently open for submission. Please reach out to repository@u.library.arizona.edu with your questions, or if you are a UA affiliate who needs to make content available in another collection.
Quantitative Representativeness and Constituency of the Long-Term Agroecosystem Research Network and Analysis of Complementarity with Existing Ecological Networks
Name:
s00267-023-01834-9.pdf
Size:
10.39Mb
Format:
PDF
Description:
Final Published Version
Affiliation
School of Natural Resources and the Environment, University of ArizonaIssue Date
2023-06-16Keywords
AgroecoregionLong-Term Agroecosystem Research Network - LTAR
Network design
Regionalization
Representativeness
Upscaling
Metadata
Show full item recordPublisher
SpringerCitation
Kumar, J., Coffin, A.W., Baffaut, C. et al. Quantitative Representativeness and Constituency of the Long-Term Agroecosystem Research Network and Analysis of Complementarity with Existing Ecological Networks. Environmental Management 72, 705–726 (2023). https://doi.org/10.1007/s00267-023-01834-9Journal
Environmental ManagementRights
© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2023.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Studies conducted at sites across ecological research networks usually strive to scale their results to larger areas, trying to reach conclusions that are valid throughout larger enclosing regions. Network representativeness and constituency can show how well conditions at sampling locations represent conditions also found elsewhere and can be used to help scale-up results over larger regions. Multivariate statistical methods have been used to design networks and select sites that optimize regional representation, thereby maximizing the value of datasets and research. However, in networks created from already established sites, an immediate challenge is to understand how well existing sites represent the range of environments in the whole area of interest. We performed an analysis to show how well sites in the USDA Long-Term Agroecosystem Research (LTAR) Network represent all agricultural working lands within the conterminous United States (CONUS). Our analysis of 18 LTAR sites, based on 15 climatic and edaphic characteristics, produced maps of representativeness and constituency. Representativeness of the LTAR sites was quantified through an exhaustive pairwise Euclidean distance calculation in multivariate space, between the locations of experiments within each LTAR site and every 1 km cell across the CONUS. Network representativeness is from the perspective of all CONUS locations, but we also considered the perspective from each LTAR site. For every LTAR site, we identified the region that is best represented by that particular site—its constituency—as the set of 1 km grid locations best represented by the environmental drivers at that particular LTAR site. Representativeness shows how well the combination of characteristics at each CONUS location was represented by the LTAR sites’ environments, while constituency shows which LTAR site was the closest match for each location. LTAR representativeness was good across most of the CONUS. Representativeness for croplands was higher than for grazinglands, probably because croplands have more specific environmental criteria. Constituencies resemble ecoregions but have their environmental conditions “centered” on those at particular existing LTAR sites. Constituency of LTAR sites can be used to prioritize the locations of experimental research at or even within particular sites, or to identify the extents that can likely be included when generalizing knowledge across larger regions of the CONUS. Sites with a large constituency have generalist environments, while those with smaller constituency areas have more specialized environmental combinations. These “specialist” sites are the best representatives for smaller, more unusual areas. The potential of sharing complementary sites from the Long-Term Ecological Research (LTER) Network and the National Ecological Observatory Network (NEON) to boost representativeness was also explored. LTAR network representativeness would benefit from borrowing several NEON sites and the Sevilleta LTER site. Later network additions must include such specialist sites that are targeted to represent unique missing environments. While this analysis exhaustively considered principal environmental characteristics related to production on working lands, we did not consider the focal agronomic systems under study, or their socio-economic context. © 2023, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.Note
Open access articleISSN
0364-152XPubMed ID
37328644Version
Final Published Versionae974a485f413a2113503eed53cd6c53
10.1007/s00267-023-01834-9
Scopus Count
Collections
Except where otherwise noted, this item's license is described as © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2023.
Related articles
- Trends in land surface phenology across the conterminous United States (1982-2016) analyzed by NEON domains.
- Authors: Liang L, Henebry GM, Liu L, Zhang X, Hsu LC
- Issue date: 2021 Jul
- The LTAR Grazing Land Common Experiment at Platte River High Plains Aquifer.
- Authors: Khorchani M, Schmer M, Freidenreich A, Awada T, Birru G, Christofferson S, Drijber R, Erickson G, Jin V, McDermott R, Suyker A, Watson A, Woodbury B, Xiong Y, Hiller J, Sun X, Li L
- Issue date: 2024 Nov-Dec
- The LTAR Grazing Land Common Experiment at Northern Plains.
- Authors: Toledo D, Hendrickson J, Liebig M, Kobilansky C, Carrlson A, Kronberg S, Christensen R, Archer D, Branson D, Rand T, Campbell J, Igathinathane C
- Issue date: 2024 Nov-Dec
- Advancing the Sustainability of US Agriculture through Long-Term Research.
- Authors: Kleinman PJA, Spiegal S, Rigby JR, Goslee SC, Baker JM, Bestelmeyer BT, Boughton RK, Bryant RB, Cavigelli MA, Derner JD, Duncan EW, Goodrich DC, Huggins DR, King KW, Liebig MA, Locke MA, Mirsky SB, Moglen GE, Moorman TB, Pierson FB, Robertson GP, Sadler EJ, Shortle JS, Steiner JL, Strickland TC, Swain HM, Tsegaye T, Williams MR, Walthall CL
- Issue date: 2018 Nov
- The LTAR Cropland Common Experiment at the Texas Gulf.
- Authors: Yost JL, Smith DR, Adhikari K, Arnold JG, Collins HP, Flynn KC, Hajda C, Menefee D, Mohanty BP, Schantz MC, Thorp KR, White MJ
- Issue date: 2024 Nov-Dec