A multi-scale dataset combining 3D plant architecture, leaf gas exchange, and whole-plant fluxes in young oil palm under controlled climate scenarios
Abstract
Functional-structural plant models (FSPM) simulate plant responses to environmental conditions, but their development and evaluation are often limited by the lack of datasets combining detailed architectural and physiological measurements. Here, we present a comprehensive dataset acquired from four oil palm plants (Elaeis guinnensis) grown under controlled and contrasting climate scenarios. The dataset includes (i) three-dimensional reconstructions of plant architecture derived from terrestrial lidar point clouds, (ii) leaf-level gas exchange measurements used to parameterize photosynthesis and stomatal conductance models, and (iii) continuous plant-scale measurements of CO2 and H2O fluxes obtained in a microcosm under precisely monitored and manipulated environmental conditions (light, temperature, humidity, and CO2 concentration) across height climate scenarios. By combining detailed structural data with physiological measurements at both leaf and whole-plant scales, this database has been designed to build and evaluate digital twins (or shadows) of plants functioning under controlled conditions. It provides a valuable resource for calibrating biophysical models (light interception and photosynthesis), benchmarking model predictions across scales, and investigating the consistency between leaf-level parameterization and plant-level fluxes. All data and processing workflows are openly available, facilitating reuse for model development, evaluation, and intercomparison in plant and crop modelling communities.
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BibTeX
@article{perez2026multiscale,
title = {{A multi-scale dataset combining 3D plant architecture, leaf gas exchange, and whole-plant fluxes in young oil palm under controlled climate scenarios}},
author = {Raphael P. A. Perez and Valentin Torrelli and Sandrine Roques and Sébastien Devidal and Clément Piel and Damien Landais and Merlin Ramel and Thomas Arsouze and Julien Lamour and Jean-Pierre Caliman and Rémi Vezy},
journal = {Peer Community Journal},
year = {2026},
month = aug,
doi = {10.24072/pcjournal.773},
url = {https://hal.science/hal-04947042v6},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - A multi-scale dataset combining 3D plant architecture, leaf gas exchange, and whole-plant fluxes in young oil palm under controlled climate scenarios
AU - Raphael P. A. Perez
AU - Valentin Torrelli
AU - Sandrine Roques
AU - Sébastien Devidal
AU - Clément Piel
AU - Damien Landais
AU - Merlin Ramel
AU - Thomas Arsouze
AU - Julien Lamour
AU - Jean-Pierre Caliman
AU - Rémi Vezy
PY - 2026
DA - 2026/08/23
JO - Peer Community Journal
DO - 10.24072/pcjournal.773
UR - https://hal.science/hal-04947042v6
AB - Functional-structural plant models (FSPM) simulate plant responses to environmental conditions, but their development and evaluation are often limited by the lack of datasets combining detailed architectural and physiological measurements. Here, we present a comprehensive dataset acquired from four oil palm plants (Elaeis guinnensis) grown under controlled and contrasting climate scenarios. The dataset includes (i) three-dimensional reconstructions of plant architecture derived from terrestrial lidar point clouds, (ii) leaf-level gas exchange measurements used to parameterize photosynthesis and stomatal conductance models, and (iii) continuous plant-scale measurements of CO2 and H2O fluxes obtained in a microcosm under precisely monitored and manipulated environmental conditions (light, temperature, humidity, and CO2 concentration) across height climate scenarios. By combining detailed structural data with physiological measurements at both leaf and whole-plant scales, this database has been designed to build and evaluate digital twins (or shadows) of plants functioning under controlled conditions. It provides a valuable resource for calibrating biophysical models (light interception and photosynthesis), benchmarking model predictions across scales, and investigating the consistency between leaf-level parameterization and plant-level fluxes. All data and processing workflows are openly available, facilitating reuse for model development, evaluation, and intercomparison in plant and crop modelling communities.
SN - 2804-3871
SN - 2804-3871
ER -