Open AccessNEON terrestrial field observations: designing continental‐scale, standardized sampling
Author(s) -
Kao Rebecca Hufft,
Gibson Cara M.,
Gallery Rachel E.,
Meier Courtney L.,
Barnett David T.,
Docherty Kathryn M.,
Blevins Kali K.,
Travers Patrick D.,
Azuaje Elena,
Springer Yuri P.,
Thibault Katherine M.,
McKenzie Valerie J.,
Keller Michael,
Alves Luciana F.,
Hinckley Eve-Lyn S.,
Parnell Jacob,
Schimel David
Publication year - 2012
Publication title -
ecosphere
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.255
H-Index - 57
ISSN - 2150-8925
DOI - 10.1890/es12-00196.1
Subject(s) - neon , ecology , sampling (signal processing) , environmental science , climate change , global change , scale (ratio) , environmental resource management , ecosystem , geography , physical geography , computer science , biology , cartography , physics , filter (signal processing) , atomic physics , argon , computer vision
Rapid changes in climate and land use and the resulting shifts in species distributions and ecosystem functions have motivated the development of the National Ecological Observatory Network (NEON). Integrating across spatial scales from ground sampling to remote sensing, NEON will provide data for users to address ecological responses to changes in climate, land use, and species invasion across the United States for at least 30 years. Although NEON remote sensing and tower sensor elements are relatively well known, the biological measurements are not. This manuscript describes NEON terrestrial sampling, which targets organisms across a range of generation and turnover times, and a hierarchy of measurable biological states. Measurements encompass species diversity, abundance, phenology, demography, infectious disease, ecohydrology, and biogeochemistry. The continental‐scale sampling requires collection of comparable and calibrated data using transparent methods. Data will be publicly available in a variety of formats and suitable for integration with other long‐term efforts. NEON will provide users with the data necessary to address large‐scale questions, challenge current ecological paradigms, and forecast ecological change.