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

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Abstract
Accurate assessment of leaf functional traits is crucial for a diverse range of applications from crop phenotyping to parameterizing global climate models. Leaf reflectance spectroscopy offers a promising avenue to advance ecological and agricultural research by complementing traditional, time-consuming gas exchange measurements. However, the development of robust hyperspectral models for predicting leaf photosynthetic capacity and associated traits from reflectance data has been hindered by limited data availability across species and environments. Here we introduce the Global Spectra-Trait Initiative (GSTI), a collaborative repository of paired leaf hyperspectral and gas exchange measurements from diverse ecosystems. The GSTI repository currently encompasses over 7500 observations from 397 species and 41 sites gathered from 36 published and unpublished studies, thereby offering a key resource for developing and validating hyperspectral models of leaf photosynthetic capacity. The GSTI database is developed on GitHub (https://github.com/plantphys/gsti, last access: 4 January 2026) and published to ESS-DIVE https://doi.org/10.15485/2530733, Lamour et al., 2025). It includes gas exchange data, derived photosynthetic parameters, and key leaf traits often associated with traditional gas exchange measurements such as leaf mass per area and leaf elemental composition. By providing a standardized repository for data sharing and analysis, we present a critical step towards creating hyperspectral models for predicting photosynthetic traits and associated leaf traits for terrestrial plants.
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Funding Information
  • U.S. Department of Energy (DE-AC02-05CH11231)
  • Natural Sciences and Engineering Research Council of Canada (n/a)
  • University of Toronto (n/a)
  • John Fell Fund, University of Oxford (n/a)
  • Agence Nationale de la Recherche (ANR-17-CE32-0001-01)
  • Agence Nationale de la Recherche (ANR-16-IDEX-0006)
  • Agence Nationale de la Recherche (ANR-10-LABX-25-01)
  • Agence Nationale de la Recherche (Amazonian Landscapes in Transition ANR project (ALT))
  • National Aeronautics and Space Administration (80NSSC21K1707)
  • National Aeronautics and Space Administration (80NSSC24K0135)
  • National Aeronautics and Space Administration (80NSSC21K1713)
  • Bill and Melinda Gates Foundation (57248)
  • Foundation for Food and Agriculture Research (n/a)
  • Foreign, Commonwealth and Development Office (OPP11722157)
  • National Institute of Food and Agriculture (2022-67013-36205)
  • Biological and Environmental Research (n/a)
  • Australian National University (n/a)
  • University of Western Australia (n/a)
  • University of Sydney (n/a)
  • University of New England (n/a)
  • Cooperative Research Centres, Australian Government Department of Industry (P2-023)
  • National Natural Science Foundation of China (31922090)
  • National Natural Science Foundation of China (32471573)
  • University of Hong Kong (n/a)
  • National Science Foundation (1951647)
  • Deutsche Forschungsgemeinschaft (390686111)
  • Louisiana NASA EPSCoR (n/a)

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