TROLL 4.0: representing water and carbon fluxes, leaf phenology, and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 1: Model description

<p>TROLL 4.0 is an individual-based forest dynamics model that is capable of jointly simulating forest structure, diversity, and ecosystem functioning, including the ecosystem water balance and productivity, leaf area dynamics, and the tree community functional and taxonomic composition. It re...

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Bibliographic Details
Main Authors: I. Maréchaux, F. J. Fischer, S. Schmitt, J. Chave
Format: Article
Language:English
Published: Copernicus Publications 2025-08-01
Series:Geoscientific Model Development
Online Access:https://gmd.copernicus.org/articles/18/5143/2025/gmd-18-5143-2025.pdf
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Summary:<p>TROLL 4.0 is an individual-based forest dynamics model that is capable of jointly simulating forest structure, diversity, and ecosystem functioning, including the ecosystem water balance and productivity, leaf area dynamics, and the tree community functional and taxonomic composition. It represents ecosystem flux processes in a manner similar to dynamic global vegetation models, while adopting a representation of plant community structure and diversity at a resolution consistent with that used by field ecologists. Specifically, trees are modelled as three-dimensional individuals with a metric-scale spatial representation, providing a detailed description of ecological processes such as competition for resources and tree demography. Carbon assimilation and plant water loss are explicitly represented at tree level using coupled photosynthesis and stomatal conductance models, depending on the micro-environmental conditions experienced by trees. Soil water uptake by trees is also modelled. Physiological and demographic processes are parameterized using plant functional traits measured in the field. Here we provide a detailed description and discussion of the implementation of TROLL 4.0. An evaluation of the model at two tropical forest sites is provided in a companion paper (Schmitt et al., 2025). TROLL 4.0's representation of processes reflects the state of the art, and we discuss possible developments to improve its predictive capability and its capacity to address challenges in forest monitoring, forest dynamics, and carbon cycle research.</p>
ISSN:1991-959X
1991-9603