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The Global Spectra-Trait Initiative: A database of paired leaf spectroscopy and functional traits associated with leaf photosynthetic capacity (v1.0.0)

Dataset ·
DOI:https://doi.org/10.15485/2530733· OSTI ID:2530733
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  1. Centre de Recherche sur la Biodiversité et l'Environnement (CRBE), Université de Toulouse
  2. Biospheric Sciences Laboratory, NASA Goddard Space Flight Center
  3. Climate and Ecosystems Sciences Division, Lawrence Berkeley National Laboratory
  4. Smithsonian Environmental Research Center
  5. University of Illinois Urbana-Champaign
  6. Forest Ecosystems and Society, Oregon State University
  7. Department of Environmental Science, American University
  8. Research School of Biology, The Australian National University
  9. AMAP, Univ Montpellier
  10. O'Neill School of Public and Environmental Affairs, Indiana University
  11. Advanced Research + Invention Agency
  12. Department of Architecture & Environmental Design, Temple University
  13. College of Science & Engineering, James Cook University
  14. School of Environmental and Rural Science, University of New England
  15. Université de la Guyane
  16. School of Biosciences, University of Sheffield
  17. Department of Physical and Environmental Sciences, University of Toronto
  18. AMAP, Université de Montpellier
  19. American Forests
  20. School of Informatics, Computing, and Cyber Systems, Northern Arizona University
  21. ARC Centre of Excellence for Translational Photosynthesis, Research School of Biology, Australian National University
  22. Université Montpellier
  23. Universitat Autonoma de Barcelona
  24. School of Plant, Environmental and Soil Sciences, Louisiana State University
  25. Department of Forest Ecosystems & Society, Oregon State University
  26. National Institute of Amazonian Research
  27. Institute for Sustainability, Energy, and Environment, University of Illinois Urbana-Champaign
  28. School of Biological Sciences, University of Hong Kong
  29. Bayer Crop Science
  30. Department of Renewable Resources, University of Alberta
  31. Institute for Agro-Environmental Sciences
  32. Aerospace Information Research Institute, Chinese Academy of Sciences
  33. Institute of Botany, Chinese Academy of Sciences
  34. Department of Forest and Wildlife Ecology, University of Wisconsin-Madison
  35. Department of Plant Sciences, University of California Davis
  36. Carl R Woese Institute for Genomic Biology, University of Illinois Urbana Champaign
  37. USDA-ARS Photosynthesis Research Unit
  38. Centre for Forest Research, Université du Québec à Montréal
  39. Biology Department, Universidad del Rosario
  40. Nanjing University of Posts and Telecommunications
  41. Department of Forestry, Mississippi State University
  42. Institute for Snow, Glaciers and Environmental Research, IANIGLA-CONICET,
  43. Facultad de Ciencias Exactas y Naturales, Universidad Nacional, Heredia, Costa Rica
  44. Institute for Plant Biochemistry, Heinrich Heine University Düsseldorf
  45. Oregon State University Department of Forest Ecosystems & Society
  46. UMR EcoFoG, AgroParisTech, Cirad, CNRS, INRAE, Université des Antilles, Université de la Guyane
  47. Agronomy Department, Purdue University
  48. School of Forestry, Fisheries and Geomatics, University of Florida
  49. Department of Agroecology, Aarhus University
  50. Department of Earth System Science, Tsinghua University
  51. School of Ecology, Shenzhen Campus of Sun Yat-sen University
  52. Institute for Plant Biochemistry, Heinrich Heine University
  53. Faculty of Forestry and Environmental Management, University of New Brunswick
  54. Faculty of Architecture, The University of Hong Kong
  55. Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory
+ Show Author Affiliations

The Global Spectra-Trait Initiative (GSTI) aims to generate generalizable spectra trait models using reflectance data to predict leaf traits associated with the photosynthesis capacity of leaves. It comprises a synthesized dataset of leaf trait data, input datasets and code. Leaf traits include the maximum carboxylation rate of rubisco (Vcmax), the maximum electron transport rate (Jmax), the dark respiration, as well as the prediction of leaf nitrogen, leaf mass per area (LMA), and leaf water content (LWC). The dataset comprises >7500 paired observations from around 400 species from a broad range of biomes. This dataset comprises a zip file of the GSTI GitHub repository (https://github.com/plantphys/gsti), the synthesized database (.csv) and database metadata files. This dataset was updated on 2025-12-12 with minor edits to mirror the accepted manuscript version and GitHub release (Version 1.0.0 (ESSD accepted version)). Edits included minor changes to the project documentation on GitHub and removal of 12 duplicate entries from the database.

Research Organization:
Next-Generation Ecosystem Experiments (NGEE) Tropics
Sponsoring Organization:
ESS-DIVE; U.S. DOE > Office of Science > Biological and Environmental Research (BER)
DOE Contract Number:
AC02-05CH11231
OSTI ID:
2530733
Country of Publication:
United States
Language:
English

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Related Subjects

54 ENVIRONMENTAL SCIENCES
EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > ECOSYSTEM FUNCTIONS > PHOTOSYNTHESIS
EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > ECOSYSTEM FUNCTIONS > RESPIRATION RATE
ESS-DIVE CSV File Formatting Guidelines Reporting Format
ESS-DIVE File Level Metadata Reporting Format
leaf spectral reflectance
related identifiers