Journal of Ecology and Environment

한국생태학회 (The Ecological Society of Korea)
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The US National Ecological Observatory Network and the Global Biodiversity Framework: national research infrastructure with a global reach

  • Katherine M. Thibault (National Ecological Observatory Network) ;
  • Christine M, Laney (National Ecological Observatory Network) ;
  • Kelsey M. Yule (Arizona State University, School of Life Sciences) ;
  • Nico M. Franz (Arizona State University, School of Life Sciences) ;
  • Paula M. Mabee (National Ecological Observatory Network)
  • 투고 : 2023.10.25
  • 심사 : 2023.11.15
  • 발행 : 2023.12.31
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초록

The US National Science Foundation's National Ecological Observatory Network (NEON) is a continental-scale program intended to provide open data, samples, and infrastructure to understand changing ecosystems for a period of 30 years. NEON collects co-located measurements of drivers of environmental change and biological responses, using standardized methods at 81 field sites to systematically sample variability and trends to enable inferences at regional to continental scales. Alongside key atmospheric and environmental variables, NEON measures the biodiversity of many taxa, including microbes, plants, and animals, and collects samples from these organisms for long-term archiving and research use. Here we review the composition and use of NEON resources to date as a whole and specific to biodiversity as an exemplar of the potential of national research infrastructure to contribute to globally relevant outcomes. Since NEON initiated full operations in 2019, NEON has produced, on average, 1.4 M records and over 32 TB of data per year across more than 180 data products, with 85 products that include taxonomic or other organismal information relevant to biodiversity science. NEON has also collected and curated more than 503,000 samples and specimens spanning all taxonomic domains of life, with up to 100,000 more to be added annually. Various metrics of use, including web portal visitation, data download and sample use requests, and scientific publications, reveal substantial interest from the global community in NEON. More than 47,000 unique IP addresses from around the world visit NEON's web portals each month, requesting on average 1.8 TB of data, and over 200 researchers have engaged in sample use requests from the NEON Biorepository. Through its many global partnerships, particularly with the Global Biodiversity Information Facility, NEON resources have been used in more than 900 scientific publications to date, with many using biodiversity data and samples. These outcomes demonstrate that the data and samples provided by NEON, situated in a broader network of national research infrastructures, are critical to scientists, conservation practitioners, and policy makers. They enable effective approaches to meeting global targets, such as those captured in the Kunming-Montreal Global Biodiversity Framework.

키워드

과제정보

The National Ecological Observatory Network is a program sponsored by the US NSF and operated under cooperative agreement by Battelle. This material is based in part upon work supported by the US NSF through the NEON Program.

참고문헌

  1. Averill C, Werbin ZR, Atherton KF, Bhatnagar JM, Dietze MC. Soil microbiome predictability increases with spatial and taxonomic scale. Nat Ecol Evol. 2021;5(6):747-56. https://doi.org/10.1038/s41559-021-01445-9. 
  2. Blair J, Weiser MD, Kaspari M, Miller M, Siler C, Marshall KE. Robust and simplified machine learning identification of pitfall trap-collected ground beetles at the continental scale. Ecol Evol. 2020;10(23): 13143-53. https://doi.org/10.1002/ece3.6905. 
  3. Brown TB, Hultine KR, Steltzer H, Denny EG, Denslow MW, Granados J, et al. Using phenocams to monitor our changing Earth: toward a global phenocam network. Front Ecol Environ. 2016;14(2):84-93. https://doi.org/10.1002/fee.1222. 
  4. Buttigieg PL, Morrison N, Smith B, Mungall CJ, Lewis SE; ENVO Consortium. The environment ontology: contextualising biological and biomedical entities. J Biomed Semantics. 2013;4(1):43. https://doi.org/10.1186/2041-1480-4-43. 
  5. Carrasco L, Giam X, Papes M, Sheldon KS. Metrics of lidar-derived 3D vegetation structure reveal contrasting effects of horizontal and vertical forest heterogeneity on bird species richness. Remote Sens. 2019;11(7):743. https://doi.org/10.3390/rs11070743. 
  6. Choi DH, LaRue EA, Atkins JW, Foster JR, Matthes JH, Fahey RT, et al. Short-term effects of moderate severity disturbances on forest canopy structure. J Ecol. 2023;111(9):1866-81. https://doi.org/10.1111/1365-2745.14145. 
  7. Ciugulea I, Burroughs S, Defrancesco C, Spitale D, Charles DF, Lange-Bertalot H, et al. Adlafia neoniana (naviculaceae), a new diatom species from forest streams in Puerto Rico. Plant Ecol Evol. 2019;152(2):378-84. https://doi.org/10.5091/plecevo.2019.1616. 
  8. Convention on Biological Diversity. Decision adopted by the conference of the parties to the convention on biological diversity. 15/4. Kunming-Montreal Global Biodiversity Framework. 2022. https://www. cbd.int/doc/decisions/cop-15/cop-15-dec-04-en.pdf. Accessed 7 Sep 2023. 
  9. Digital Science & Research Solutions, Inc. Dimensions [Software]. 2018. https://neon.dimensions.ai/discover/publication. Accessed 7 Sep 2023. 
  10. Elmendorf SC, Jones KD, Cook BI, Diez JM, Enquist CAF, Hufft RA, et al. The plant phenology monitoring design for The National Ecological Observatory Network. Ecosphere. 2016;7(4):e01303. https://doi.org/10.1002/ecs2.1303. 
  11. Eloe-Fadrosh EA, Ahmed F, Anubhav, Babinski M, Baumes J, Borkum M, et al. The National Microbiome Data Collaborative Data Portal: an integrated multi-omics microbiome data resource. Nucleic Acids Res. 2022;50(D1):D828-36. https://doi.org/10.1093/nar/gkab990. 
  12. Gaffney R, Augustine DJ, Kearney SP, Porensky LM. Using hyperspectral imagery to characterize rangeland vegetation composition at process-relevant scales. Remote Sens. 2021;13(22):4603. https://doi. org/10.3390/rs13224603. 
  13. Global Biodiversity Information Facility (GBIF). What is GBIF? 2023a. https://www.gbif.org/what-is-gbif. Accessed 28 Sep 2023. 
  14. Global Biodiversity Information Facility (GBIF). Research uses and citations of NEON-provided biodiversity information accessed through the Global Biodiversity Information Facility's global infrastructure. 2023b. https://www.gbif.org/resource/search?contentType=literature&publishingOrganizationKey=e794e60e-e558-4549-99f8-cfb241cdce24. Accessed 28 Sep 2023. 
  15. Gorris ME, Bartlow AW, Temple SD, Romero-Alvarez D, Shutt DP, Fair JM, et al. Updated distribution maps of predominant Culex mosquitoes across the Americas. Parasit Vectors. 2021;14(1):547. https://doi.org/10.1186/s13071-021-05051-3. 
  16. Gries C, Gilbert EE, Franz NM. Symbiota - a virtual platform for creating voucher-based biodiversity information communities. Biodivers Data J. 2014;(2):e1114. https://doi.org/10.3897/BDJ.2.e1114. 
  17. Gries C, Hanson PC, O'Brien M, Servilla M, Vanderbilt K, Waide R. The Environmental Data Initiative: connecting the past to the future through data reuse. Ecol Evol. 2023;13(1):e9592. https://doi.org/10.1002/ece3.9592. 
  18. Heberling JM, Miller JT, Noesgaard D, Weingart SB, Schigel D. Data integration enables global biodiversity synthesis. Proc Natl Acad Sci U S A. 2021;118(6):e2018093118. https://doi.org/10.1073/pnas.2018093118. 
  19. Hobbie JE, Carpenter SR, Grimm NB, Gosz JR, Seastedt TR. The US long term ecological research program. BioScience. 2003;53(1):21-32.  https://doi.org/10.1641/0006-3568(2003)053[0021:TULTER]2.0.CO;2
  20. International Standards Organization (ISO). ISO 3166-1:2020. 2020. https://www.iso.org/standard/72482.html. Accessed 15 Sep 2023. 
  21. Jones M, O'Brien M, Mecum B, Boettiger C, Schildhauer M, Maier M, et al. Ecological Metadata Language (EML) version 2.2.0. KNB Data Repos. 2019. https://eml.ecoinformatics.org/. Accessed 11 Oct 2023. 
  22. Keller M, Schimel DS, Hargrove WW, Hoffman FM. A continental strategy for the national ecological observatory network. Front Ecol Environ. 2008;6:282-4.  https://doi.org/10.1890/1540-9295(2008)6[282:ACSFTN]2.0.CO;2
  23. Kenney G, Staudhammer CL, Wiesner S, Brantley S, Bigelow S, Starr G. Hurricane Michael altered the structure and function of longleaf pine woodlands. J Geophys Res Biogeosci. 2021;126(12):e2021JG006452. https://doi.org/10.1029/2021JG006452. 
  24. Loescher HW, Vargas R, Mirtl M, Morris B, Pauw J, Yu X, et al. Building a global ecosystem research infrastructure to address global grand challenges for macrosystem ecology. Earth's Future. 2022;10(5): e2020EF001696. https://doi.org/10.1029/2020EF001696. 
  25. Meier CL, Thibault KM, Barnett DT. Spatial and temporal sampling strategy connecting NEON Terrestrial Observation System protocols. Ecosphere. 2023;14(3):e4455. https://doi.org/10.1002/ecs2.4455. 
  26. Meyer R, Davies N, Pitz KJ, Meyer C, Samuel R, Anderson J, et al. The founding charter of the Omic Biodiversity Observation Network (Omic BON). GigaScience. 2023;12:giad068. https://doi.org/10.1093/gigascience/giad068. 
  27. Musinsky J, Goulden T, Wirth G, Leisso N, Krause K, Haynes M, et al. Spanning scales: the airborne spatial and temporal sampling design of the National Ecological Observatory Network. Methods Ecol Evol. 2022;13(9):1866-84. https://doi.org/10.1111/2041-210X.13942. 
  28. National Research Council. Grand challenges in environmental sciences. Washington, D.C.: The National Academies Press; 2001. 107 p. 
  29. O'Brien M, Smith CA, Sokol ER, Gries C, Lany N, Record S, et al. ecocomDP: a flexible data design pattern for ecological community survey data. Ecol Inform. 2021;64:101374. https://doi.org/10.1016/j.ecoinf.2021.101374. 
  30. Parker SM, Utz RM. Temporal design for aquatic organismal sampling across the National Ecological Observatory Network. Methods Ecol Evol. 2022;13(9):1834-48. https://doi.org/10.1111/2041-210X.13944. 
  31. Paull SH, Thibault KM, Benson AL. Tick abundance, diversity and pathogen data collected by the National Ecological Observatory Network. Gigabyte. 2022. https://doi.org/10.46471/gigabyte.56. 
  32. Quinn Thomas R, Boettiger C, Carey CC, Dietze MC, Johnson LR, Kenney MA, et al. The NEON ecological forecasting challenge. Front Ecol Environ. 2023;21(3):112-3. https://doi.org/10.1002/fee.2616. 
  33. Ratnasingham S, Hebert PD. bold: The Barcode of Life Data System (http://www.barcodinglife.org). Mol Ecol Notes. 2007;7(3):355-64. https://doi.org/10.1111/j.1471-8286.2007.01678.x. 
  34. Schimel DS, Keller M, Berukof S, Kao B, Loescher HL, Powell H, et al. National Ecological Observatory Network 2011 science strategy: enabling continental-scale ecological forecasting. Boulder: National Ecological Observatory Network, Inc.; 2011. p. 56. 
  35. Soghigian J, Sither C, Justi SA, Morinaga G, Cassel BK, Vitek CJ, et al. Phylogenomics reveals the history of host use in mosquitoes. Nat Commun. 2023;14(1):6252. https://doi.org/10.1038/s41467-023-41764-y. 
  36. Tazik D, Franz N, Thibault KM, Yule K. National Ecological Observatory Network (NEON) biorepository sample use policy. NEON. DOC.000027 version C. 2022. https://drive.google.com/file/d/1UwUH5LcfdN7n-CLzFvxuaAQzRxo5lZp8/view. Accessed 11 Oct 2023. 
  37. Thibault KM, Simkin S, Benson A. NEON breeding landbird point counts. 2023. https://www.gbif.org/dataset/516eb7c0-3586-4dfcbc18-c1fc1e765b7f/project. Accessed 28 Sep 2023. 
  38. Thorpe AS, Barnett DT, Elmendorf SC, Hinckley ELS, Hoekman D, Jones KD, et al. Introduction to the sampling designs of the National Ecological Observatory Network Terrestrial Observation System. Ecosphere. 2016;7(12):e01627. https://doi.org/10.1002/ecs2.1627. 
  39. Vannan S, Downs RR, Meier W, Wilson BE, Gerasimov IV. Data sets are foundational to research. Why don't we cite them? Eos. 2020;101. https://doi.org/10.1029/2020EO151665. 
  40. Weiser MD, Siler CD, Smith SN, Marshall KE, McLaughlin JF, Miller MJ, et al. Robust metagenomic evidence that local assemblage richness increases with latitude in ground-active invertebrates of North America. Oikos. 2022;2022(8):e08791. https://doi.org/10.1111/oik.08791. 
  41. Wieczorek J, Bloom D, Guralnick R, Blum S, Doring M, Giovanni R, et al. Darwin Core: an evolving community-developed biodiversity data standard. PLoS One. 2012;7(1):e29715. https://doi.org/10.1371/journal.pone.0029715. 
  42. Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. https://doi.org/10.1038/sdata.2016.18. Erratum in: Sci Data. 2019;6(1):6. https://doi.org/10.1038/s41597-019-0009-6. 
  43. Will K, Liebherr JK. Two new species of Mecyclothorax Sharp, 1903 (Coleoptera: Carabidae: Moriomorphini) from the Island of Hawai‵i. Pan-Pac Entomol. 2022;98(1):1-17. https://doi.org/10.3956/2022-98.1.1. 
  44. Yilmaz P, Kottmann R, Field D, Knight R, Cole JR, Amaral-Zettler L, et al. Minimum information about a marker gene sequence (MIMARKS) and minimum information about any (x) sequence (MIxS) specifications. Nat Biotechnol. 2011;29(5):415-20. https://doi.org/10.1038/nbt.1823.