The US National Ecological Observatory Network and the Global Biodiversity Framework: national research infrastructure with a global reach
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
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.
Abstract
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.
참고문헌 (44)
- Averill C, "Soil microbiome predictability increases with spatial and taxonomic scale", Nat Ecol Evol, 5(6), pp.747~756 (2021)[DOI]
- Blair J, "Robust and simplified machine learning identification of pitfall trap-collected ground beetles at the continental scale", Ecol Evol, 10(23), pp.13143~13153 (2020)[DOI]
- Brown TB, "Using phenocams to monitor our changing Earth : toward a global phenocam network", Front Ecol Environ, 14(2), pp.84~93 (2016)[DOI]
- Buttigieg PL, "The environment ontology: contextualising biological and biomedical entities", J Biomed Semantics, 4(1), pp.43~ (2013)[DOI]
- Carrasco L, "Metrics of lidar-derived 3D vegetation structure reveal contrasting effects of horizontal and vertical forest heterogeneity on bird species richness", Remote Sens, 11(7), pp.743~ (2019)[DOI]
- Choi DH, "Short-term effects of moderate severity disturbances on forest canopy structure", J Ecol, 111(9), pp.1866~1881 (2023)[DOI]
- Ciugulea I, "Adlafia neoniana(naviculaceae), a new diatom species from forest streams in Puerto Rico", Plant Ecol Evol, 152(2), pp.378~384 (2019)[DOI]
- "ecision adopted by the conference of the parties to the convention on biological diversity. 15/4. Kunming-Montreal Global Biodiversity Framework" (2022)[URL]
- (2018)[URL]
- Elmendorf SC, "The plant phenology monitoring design for The National Ecological Observatory Network", Ecosphere, 7(4), pp.e01303~ (2016)[DOI]
- Eloe-Fadrosh EA, "The National Microbiome Data Collaborative Data Portal:an integrated multi-omics microbiome data resource", Nucleic Acids Res, 50(D1), pp.D828~D836 (2022)
- Gaffney R, "Using hyperspectral imagery to characterize rangeland vegetation composition at process-relevant scales", Remote Sens, 13(22), pp.4603~ (2021)[DOI]
- "What is GBIF?" (2023)[URL]
- "Research uses and citations of NEON-provided biodiversity information accessed through the Global Biodiversity Information Facility’s global infrastructure" (2023)[URL]
- Gorris ME, "Updated distribution maps of predominant Culex mosquitoes across the Americas", Parasit Vectors, 14(1), pp.547~ (2021)[DOI]
- Gries C, "Symbiota - a virtual platform for creating voucher-based biodiversity information communities", Biodivers Data J, (2), pp.e1114~ (2014)[DOI]
- Gries C, "The Environmental Data Initiative : connecting the past to the future through data reuse", Ecol Evol, 13(1), pp.e9592~ (2023)[DOI]
- Heberling JM, "Data integration enables global biodiversity synthesis", Proc Natl Acad Sci U S A, 118(6), pp.e2018093118~ (2021)[DOI]
- Hobbie JE, "The US long term ecological research program", BioScience, 53(1), pp.21~32 (2003)
- "ISO 3166-1:2020" (2020)[URL]
- "Ecological Metadata Language (EML) version 2.2.0. KNB Data Repos" (2019)[URL]
- Keller M, "A continental strategy for the national ecological observatory network", Front Ecol Environ, 6, pp.282~284 (2008)
- Kenney G, "Hurricane Michael altered the structure and function of longleaf pine woodlands", J Geophys Res Biogeosci, 126(12), pp.e2021JG006~ (2021)[DOI]
- Loescher HW, "Building a global ecosystem research infrastructure to address global grand challenges for macrosystem ecology", Earth’s Future, 10(5), pp.e2020EF001~ (2022)[DOI]
- Meier CL, "Spatial and temporal sampling strategy connecting NEON Terrestrial Observation System protocols", Ecosphere, 14(3), pp.e4455~ (2023)[DOI]
- Meyer R, "The founding charter of the Omic Biodiversity Observation Network (Omic BON)", GigaScience, 12, pp.giad068~ (2023)[DOI]
- Musinsky J, "Spanning scales : the airborne spatial and temporal sampling design of the National Ecological Observatory Network", Methods Ecol Evol, 13(9), pp.1866~1884 (2022)[DOI]
- National Research Council, "Grand challenges in environmental sciences", pp.107~ (2001), The National Academies Press
- O’Brien M, "ecocomDP : a flexible data design pattern for ecological community survey data", Ecol Inform, 64, pp.101374~ (2021)[DOI]
- Parker SM, "Temporal design for aquatic organismal sampling across the National Ecological Observatory Network", Methods Ecol Evol, 13(9), pp.1834~1848 (2022)[DOI]
- Paull SH, "Tick abundance, diversity and pathogen data collected by the National Ecological Observatory Network", Gigabyte (2022)[DOI]
- Quinn Thomas R, "The NEON ecological forecasting challenge", Front Ecol Environ, 21(3), pp.112~113 (2023)[DOI]
- Ratnasingham S, "bold: The Barcode of Life Data System (http:", Mol Ecol Notes, pp.2007, 7(3)[DOI]
- Schimel DS, "National Ecological Observatory Network 2011 science strategy: enabling continental-scale ecological forecasting", pp.56~ (2011), National Ecological Observatory Network, Inc
- Soghigian J, "Phylogenomics reveals the history of host use in mosquitoes", Nat Commun, 14(1), pp.6252~ (2023)[DOI]
- "National Ecological Observatory Network (NEON) biorepository sample use policy. NEON. DOC.000027 version C" (2022)[URL]
- "NEON breeding landbird point counts" (2023)[URL]
- Thorpe AS, "Introduction to the sampling designs of the National Ecological Observatory Network Terrestrial Observation System", Ecosphere, 7(12), pp.e01627~ (2016)[DOI]
- Vannan S, "Data sets are foundational to research. Why don’t we cite them?", Eos, 101 (2020)[DOI]
- Weiser MD, "Robust metagenomic evidence that local assemblage richness increases with latitude in ground-active invertebrates of North America", Oikos, 2022(8), pp.e08791~ (2022)[DOI]
- Wieczorek J, "Darwin Core : an evolving community-developed biodiversity data standard", PLoS One, 7(1), pp.e29715~ (2012)[DOI]
- Wilkinson MD, "The FAIR Guiding Principles for scientific data management and stewardship", Sci Data, 6(1), pp.6~ (2019)[DOI]
- Will K, "Two new species of Mecyclothorax Sharp, 1903(Coleoptera : Carabidae : Moriomorphini)from the Island of Hawai‵i", Pan-Pac Entomol, 98(1), pp.1~17 (2022)[DOI]
- Yilmaz P, "Minimum information about a marker gene sequence(MIMARKS)and minimum information about any(x)sequence(MIxS)specifications", Nat Biotechnol, 29(5), pp.415~420 (2011)[DOI]