
Standardized NEON organismal data for biodiversity research
Author(s) -
Li Daijiang,
Record Sydne,
Sokol Eric R.,
Bitters Matthew E.,
Chen Melissa Y.,
Chung Y. Anny,
Helmus Matthew R.,
Jaimes Ruvi,
Jansen Lara,
Jarzyna Marta A.,
Just Michael G.,
LaMontagne Jalene M.,
Melbourne Brett A.,
Moss Wynne,
Norman Kari E. A.,
Parker Stephanie M.,
Robinson Natalie,
Seyednasrollah Bijan,
Smith Colin,
Spaulding Sarah,
Surasinghe Thilina D.,
Thomsen Sarah K.,
Zarnetske Phoebe L.
Publication year - 2022
Publication title -
ecosphere
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.255
H-Index - 57
ISSN - 2150-8925
DOI - 10.1002/ecs2.4141
Subject(s) - workflow , biodiversity , data science , computer science , sampling (signal processing) , scope (computer science) , resource (disambiguation) , ecology , environmental resource management , database , biology , environmental science , filter (signal processing) , computer vision , programming language , computer network
Understanding patterns and drivers of species distribution and abundance, and thus biodiversity, is a core goal of ecology. Despite advances in recent decades, research into these patterns and processes is currently limited by a lack of standardized, high‐quality, empirical data that span large spatial scales and long time periods. The NEON fills this gap by providing freely available observational data that are generated during robust and consistent organismal sampling of several sentinel taxonomic groups within 81 sites distributed across the United States and will be collected for at least 30 years. The breadth and scope of these data provide a unique resource for advancing biodiversity research. To maximize the potential of this opportunity, however, it is critical that NEON data be maximally accessible and easily integrated into investigators' workflows and analyses. To facilitate its use for biodiversity research and synthesis, we created a workflow to process and format NEON organismal data into the ecocomDP (ecological community data design pattern) format that were available through the ecocomDP R package; we then provided the standardized data as an R data package (neonDivData). We briefly summarize sampling designs and data wrangling decisions for the major taxonomic groups included in this effort. Our workflows are open‐source so the biodiversity community may: add additional taxonomic groups; modify the workflow to produce datasets appropriate for their own analytical needs; and regularly update the data packages as more observations become available. Finally, we provide two simple examples of how the standardized data may be used for biodiversity research. By providing a standardized data package, we hope to enhance the utility of NEON organismal data in advancing biodiversity research and encourage the use of the harmonized ecocomDP data design pattern for community ecology data from other ecological observatory networks.