Articles | Volume 18, issue 16
https://doi.org/10.5194/gmd-18-5205-2025
https://doi.org/10.5194/gmd-18-5205-2025
Model evaluation paper
 | 
25 Aug 2025
Model evaluation paper |  | 25 Aug 2025

TROLL 4.0: representing water and carbon fluxes, leaf phenology, and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 2: Model evaluation for two Amazonian sites

Sylvain Schmitt, Fabian J. Fischer, James G. C. Ball, Nicolas Barbier, Marion Boisseaux, Damien Bonal, Benoit Burban, Xiuzhi Chen, Géraldine Derroire, Jeremy W. Lichstein, Daniela Nemetschek, Natalia Restrepo-Coupe, Scott Saleska, Giacomo Sellan, Philippe Verley, Grégoire Vincent, Camille Ziegler, Jérôme Chave, and Isabelle Maréchaux

Data sets

PLUMBER2: forcing and evaluation datasets for a model intercomparison project for land surface models v1.0 A. Ukkola https://doi.org/10.25914/5FDB0902607E1

ERA5-Land hourly data from 1950 to present J. Muñoz Sabater https://doi.org/10.24381/cds.e2161bac

LBA-ECO CD-10 Forest Litter Data for km 67 Tower Site, Tapajos National Forest A. H. Rice et al. https://doi.org/10.3334/ORNLDAAC/862

Leaf age-dependent LAI seasonality products (Lad-LAI) over tropical and subtropical evergreen broadleaved forests X. Yang et al. https://doi.org/10.6084/m9.figshare.21700955.v4

Data from: Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests J. Wu et al. https://doi.org/10.5061/dryad.8fb47

Tapajos K67 tropical forest seasonal flux tower data N. Restrepo-Coupe et al. https://doi.org/10.5061/dryad.d51c5b08g

Model code and software

sylvainschmitt/rcontroll: GMD preprint Sylvain Schmitt et al. https://doi.org/10.5281/zenodo.14012116

TROLL 4.0 Isabelle Maréchaux et al. https://doi.org/10.5281/zenodo.14013147

sylvainschmitt/troll_eval: GMD preprint Sylvain Schmitt https://doi.org/10.5281/zenodo.14012085

Short summary
We evaluate the capability of TROLL 4.0, a simulator of forest dynamics, to represent tropical forest structure, diversity, dynamics, and functioning in two Amazonian forests. Evaluation data include forest inventories, carbon and water fluxes between the forest and the atmosphere, and leaf area and canopy height from remote sensing products. The model realistically predicts the structure and composition as well as the seasonality of carbon and water fluxes at both sites.
Share