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

Autor

Adam R. Martin
Alain Paquette
Alexander W. Cheesman
Alistair Rogers
Amrutha Vijayakumar
Andreas P.M. Weber
Andrés Rojas-González
Angela C. Burnett
Antonia Debora Placido
Boya Cui
Bruno O. Gimenez
Carl J. Bernacchi
Charles D. Southwick
Christopher Doughty
Christopher M. Montes
Christopher Y.S. Wong
Claire Fortunel
Clément Dauvissat
Clément Stahl
Courtney M. Siegert
Daisy C. Souza
David Heckmann
Dedi Yang
Diane R. Wang
Elizabeth Ainsworth
Etsushi Kumagai
Fengqi Wu
Giacomo Sellan
Guangqin Song
Han Wang
Heidi J. Renninger
Holly Croft
Ilona Clocher
Iolanda Filella
Isabelle Maréchaux
Jean Baptiste Féret
Jeremiah Anderson
Jin Wu
Jing Wang
Joan Llusià
John R. Evans
Josep Penuelas
Joshua S. Caplan
Joy Ojo
Julien Lamour
Jérôme Chave
Kaiyu Guan
Katherine Meacham-Hensold
Kelvin T. Acebron
Kenneth J. Davidson
Kim S. Ely
Leeladarshini Sujeeun
Liangyun Liu
Lingli Liu
Loren P. Albert
Mallory L. Barnes
Maquelle Garcia
Marcelo Vilas-Boas
Marney Isaac
Michael Alonzo
Milagros Rodriguez-Caton
Nicolas Barbier
Ninon Besson
Onoriode Coast
Owen K. Atkin
Patrick Heuret
Peng Fu
Regison Oliveira
Robert T. Furbank
Romà Ogaya
Sabrina Coste
Shan Kothari
Shawn P. Serbin
Sheng Wang
Shengbiao Wu
Shuwen Liu
Thu Ya Kyaw
To Chia Ting
Troy Magney
Urte Schlüter
Vicente Vasquez
Viridiana Silva-Perez
Xiaojin Qian
Xin Wang
Yanjun Su
Yingyi Zhao
Zhengbing Yan
Zhengfei Guo

Resumen

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repository currently encompasses over 7500 observations from 397 species and 41 sites gathered from 36 published and unpublished studies, thereby offering a key resource for developing and validating hyperspectral models of leaf photosynthetic capacity.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.

autores

http://vivoweb.org/ontology/core#FacultyMember
Posada Hostettler, Juan Manuel Roberto

VIVO
VIVO

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

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