A reporting format for leaf-level gas exchange data and metadata

Kim S. Ely, Alistair Rogers, Deborah A. Agarwal, Elizabeth A. Ainsworth, Loren P. Albert, Ashehad Ali, Jeremiah Anderson, Michael J. Aspinwall, Chandra Bellasio, Carl Bernacchi, Steve Bonnage, Thomas N. Buckley, James Bunce, Angela C. Burnett, Florian A. Busch, Amanda Cavanagh, Lucas A. Cernusak, Robert Crystal-Ornelas, Joan Damerow, Kenneth J. DavidsonMartin G. De Kauwe, Michael C. Dietze, Tomas F. Domingues, Mirindi Eric Dusenge, David S. Ellsworth, John R. Evans, Paul P.G. Gauthier, Bruno O. Gimenez, Elizabeth P. Gordon, Christopher M. Gough, Aud H. Halbritter, David T. Hanson, Mary Heskel, J. Aaron Hogan, Jason R. Hupp, Kolby Jardine, Jens Kattge, Trevor Keenan, Johannes Kromdijk, Dushan P. Kumarathunge, Julien Lamour, Andrew D.B. Leakey, David S. LeBauer, Qianyu Li, Marjorie R. Lundgren, Nate McDowell, Katherine Meacham-Hensold, Belinda E. Medlyn, David J.P. Moore, Robinson Negrón-Juárez, Ülo Niinemets, Colin P. Osborne, Alexandria L. Pivovaroff, Hendrik Poorter, Sasha C. Reed, Youngryel Ryu, Alvaro Sanz-Saez, Stephanie C. Schmiege, Shawn P. Serbin, Thomas D. Sharkey, Martijn Slot, Nicholas G. Smith, Balasaheb V. Sonawane, Paul F. South, Daisy C. Souza, Joseph Ronald Stinziano, Ellen Stuart-Haëntjens, Samuel H. Taylor, Mauricio D. Tejera, Johan Uddling, Vigdis Vandvik, Charuleka Varadharajan, Anthony P. Walker, Berkley J. Walker, Jeffrey M. Warren, Danielle A. Way, Brett T. Wolfe, Jin Wu, Stan D. Wullschleger, Chonggang Xu, Zhengbing Yan, Dedi Yang

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
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Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by the many publications that reuse and synthesize gas exchange data, however the lack of metadata and data reporting conventions make full and efficient use of these data difficult. Here we propose a reporting format for leaf-level gas exchange data and metadata to provide guidance to data contributors on how to store data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data and metadata that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. Extensive consultation with data collectors, data users, instrument manufacturers, and data scientists was undertaken in order to ensure that the reporting format met community needs. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format is published in the U.S. Department of Energy's ESS-DIVE data repository, with documentation and future development efforts being maintained in a version control system.

Original languageEnglish
Article number101232
Number of pages10
JournalEcological Informatics
Early online date24 Jan 2021
Publication statusPublished - Mar 2021

Bibliographical note

Funding Information:
KSE and AR were supported by Environmental Systems Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) community funds, through the Office of Biological and Environmental Research in the Department of Energy, Office of Science. Further support was received from several additional projects funded by the Office of Biological and Environmental Research, including the Next Generation Ecosystem Experiments -Arctic (NGEE-Arctic) and -Tropics (NGEE-Tropics) projects and through the United States Department of Energy contracts No. DE-SC0012704, DE-AC02-05CH11231, and DE-AC05-00OR22725 to Brookhaven National Laboratory, Lawrence Berkeley National Laboratory, and Oak Ridge National Laboratory. In addition, ASS was supported by Alabama Agricultural Experiment Station and the Hatch program of the National Institute of Food and Agriculture, U.S. Department of Agriculture; BJW was supported by the Division of Chemical Sciences, Geosciences and Biosciences, Office of Basic Energy Sciences of the United States Department of Energy [Grant DE-FG02-91ER20021]; JK was supported by the Biotechnology and Biological Sciences Research Council UK, grant reference BB/T007583/1; MJA was supported by the U.S. Department of Agriculture - National Institute of Food and Agriculture (Award number: 2019-67013-29161). SCR was supported by US Department of Defense (RC18-1322) and the USGS Ecosystems Mission Area. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Publisher Copyright:
© 2021 The Authors


  • Carbon dioxide
  • Data reporting format
  • Data standard
  • Irradiance
  • Metadata
  • Photosynthesis

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Modelling and Simulation
  • Ecological Modelling
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Applied Mathematics


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