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AraDiv: a dataset of functional traits and leaf hyperspectral reflectance of Arabidopsis thaliana

Authors :
Maria Stefania Przybylska
Cyrille Violle
Denis Vile
J. F. Scheepens
Benoit Lacombe
Xavier Le Roux
Lisa Perrier
Lou Sales-Mabily
Mariette Laumond
Mariona Vinyeta
Pierre Moulin
Gregory Beurier
Lauriane Rouan
Denis Cornet
François Vasseur
Source :
Scientific Data, Vol 10, Iss 1, Pp 1-8 (2023)
Publication Year :
2023
Publisher :
Nature Portfolio, 2023.

Abstract

Abstract Data from functional trait databases have been increasingly used to address questions related to plant diversity and trait-environment relationships. However, such databases provide intraspecific data that combine individual records obtained from distinct populations at different sites and, hence, environmental conditions. This prevents distinguishing sources of variation (e.g., genetic-based variation vs. phenotypic plasticity), a necessary condition to test for adaptive processes and other determinants of plant phenotypic diversity. Consequently, individual traits measured under common growing conditions and encompassing within-species variation across the occupied geographic range have the potential to leverage trait databases with valuable data for functional and evolutionary ecology. Here, we recorded 16 functional traits and leaf hyperspectral reflectance (NIRS) data for 721 widely distributed Arabidopsis thaliana natural accessions grown in a common garden experiment. These data records, together with meteorological variables obtained during the experiment, were assembled to create the AraDiv dataset. AraDiv is a comprehensive dataset of A. thaliana’s intraspecific variability that can be explored to address questions at the interface of genetics and ecology.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20524463
Volume :
10
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Scientific Data
Publication Type :
Academic Journal
Accession number :
edsdoj.b9688a6d3b4313a17607d155c25773
Document Type :
article
Full Text :
https://doi.org/10.1038/s41597-023-02189-w