TY - JOUR
T1 - Harnessing the NEON data revolution to advance open environmental science with a diverse and data-capable community
AU - Nagy, R. Chelsea
AU - Gill, Nathan
N1 - Funding Information:
Open science principles and methods (e.g., making samples, data, workflows, software, publications freely available) are changing the field of ecology (Hampton et al. 2015 ). As a key tenet of the NEON mission at the outset, this commitment to open science has the potential to accelerate ecological research and increase the diversity of scientists involved by removing barriers to access. The diversity and number of data products (NEON 2021 ), tutorials (NEON 2021 ), and analytic tools (neonUtilities (Lunch et al. 2021 ) and geoNEON (NEON 2020 ) packages in R) that NEON provides are a key resource for open ecological research. In addition, NSF requires all scientists funded by Macrosystems Biology and NEON Enabled Science grants to archive their data with the Environmental Data Initiative (EDI; EDI 2021 ) to promote data discovery and use. An extended commitment of the scientists using these resources to make their data, code, and workflows open will increase efficiency and facilitate greater coordination across a larger collaborative community. Key opportunities that are expected to bring added value to open NEON data include the following: harmonization with other observation networks (such as the Long‐Term Ecological Research (LTER), Long‐Term Agroecosystem Research (LTAR), Critical Zone Observatory (CZO), AmeriFlux, USA‐NPN National Phenology Network, and others) and data sources, open science contributions from the NEON user community, and facilitation, training, and curation that lead to a robust and popular NEON software toolbox. c d
Funding Information:
R. C. Nagy and J. K. Balch contributed equally to the work reported here and were co-lead authors. Funding for the 2019 NEON Science Summit was provided by NSF Award #DBI 1906144. Additional funding was provided by Earth Lab through the University of Colorado, Boulder’s Grand Challenge Initiative, the Cooperative Institute for Research in Environmental Sciences (CIRES), and the North Central Climate Adaptation Science Center (NC CASC). AKS was supported by the University of Zurich’s University Research Priority Programme on Global Change and Biodiversity. We are grateful to all of those who helped make the 2019 NEON Science Summit a success: Dawn Umpleby, Linda Pendergrass, David Zakavec, Rebecca Stossmeister, Alycia Crall, Kate Thibault, Claire Lunch, Megan Jones, Katie Weeman, Katy Human, Ally Faller, Lauren Herwehe, Jenny Palomino, Tim Dunn, Nathan Campbell, Nan Regnier, Elizabeth Woolner, Katie Lamb, Troy Burke, Jim Lee, Jay Burghardt, and Michelle Meighan. Several co-authors on this paper including Christopher R. Florian, Robert T. Hensley, Katherine D. Jones, Courtney L. Meier, John Musinsky, Stephanie M. Parker, Michael SanClements, and Eric R. Sokol are currently employed by Battelle and the National Ecological Observatory Network. The findings and conclusions in this manuscript are those of the authors and should not be construed to represent any official U.S. Government determination or policy.
Funding Information:
R. C. Nagy and J. K. Balch contributed equally to the work reported here and were co‐lead authors. Funding for the 2019 NEON Science Summit was provided by NSF Award #DBI 1906144. Additional funding was provided by Earth Lab through the University of Colorado, Boulder’s Grand Challenge Initiative, the Cooperative Institute for Research in Environmental Sciences (CIRES), and the North Central Climate Adaptation Science Center (NC CASC). AKS was supported by the University of Zurich’s University Research Priority Programme on Global Change and Biodiversity. We are grateful to all of those who helped make the 2019 NEON Science Summit a success: Dawn Umpleby, Linda Pendergrass, David Zakavec, Rebecca Stossmeister, Alycia Crall, Kate Thibault, Claire Lunch, Megan Jones, Katie Weeman, Katy Human, Ally Faller, Lauren Herwehe, Jenny Palomino, Tim Dunn, Nathan Campbell, Nan Regnier, Elizabeth Woolner, Katie Lamb, Troy Burke, Jim Lee, Jay Burghardt, and Michelle Meighan. Several co‐authors on this paper including Christopher R. Florian, Robert T. Hensley, Katherine D. Jones, Courtney L. Meier, John Musinsky, Stephanie M. Parker, Michael SanClements, and Eric R. Sokol are currently employed by Battelle and the National Ecological Observatory Network. The findings and conclusions in this manuscript are those of the authors and should not be construed to represent any official U.S. Government determination or policy.
Funding Information:
The skills needed to effectively work with NEON and other large data sets are not currently taught in most curricula, which struggle to keep pace with changes in technology and data processing. Education and training opportunities for students, educators, researchers, and community partners are key to building a vibrant and diverse community (Fig. 4 ). An example of a workshop that provides such opportunities is the “Critical Skills to Scale Up Ecology: An ESA SEEDS and NEON Workshop,”—an intensive week‐long training designed to introduce ecological data skills to graduate students with underrepresented backgrounds (originally scheduled for June 2020 and postponed due to the COVID‐19 pandemic). Another example is the Earth Lab Earth Data Science Corps (EDSC), funded by the NSF. The EDSC provides students at Tribal and other schools serving historically underrepresented groups in STEM with data skills training, mentorship, and a paid summer internship where they work on a real‐world project: One Tribal student in the 2020 internship used NEON lidar data to evaluate forest structural diversity in the western United States. Improved access to these types of opportunities will also require financial support for those such as K‐12 teachers, contingent university faculty, and non‐academic professionals. Providing funding for early‐career scientists and underrepresented populations can encourage participation at in‐person training opportunities. Furthermore, the development of hybrid or remote conference and workshop opportunities make these events accessible to a broader population, especially for people who face obstacles to travel, such as families, resource constraints, and heavy teaching loads. Finally, the identification and development of tools that improve accessibility of NEON data, such as GUIs (graphical user interfaces), and IDEs (integrated development environments), and creation of teaching modules that help build the skills necessary to engage with NEON data can be promoted across the NEON user community.
Publisher Copyright:
© 2021 The Authors. Ecosphere published by Wiley Periodicals LLC on behalf of The Ecological Society of America
PY - 2021/12
Y1 - 2021/12
N2 - It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on >100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building.
AB - It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on >100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building.
M3 - Article
SP - ecs2.3833
JO - Ecosphere
JF - Ecosphere
ER -