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Representing canopy structure dynamics within the LPJ-GUESS dynamic global vegetation model (revision 13221)

J. E. Stoebke et al · Copernicus Publications · 2026

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<p>The competition, especially for light, is a fundamental determinant of the structure and composition of a forest. Large-scale forest models must balance real-world complexity with computational demand and poorly constrained parameters. The LPJ-GUESS dynamic global vegetation model has a strong track record of simulating forest composition and tree demography with a simple representation of forest canopies. However, its current approach is limited in its ability to explore the functional coexistence of trees within forest patches or to represent the full implications of forest management actions that create heterogeneous light conditions on the forest floor. This is because LPJ-GUESS currently represents forest canopy light transmission with vertically overlapping crowns, neglecting any horizontal structural heterogeneity. Whilst computationally efficient, this scheme does not allow for a realistic representation of light distribution on forest floor following tree death or harvest.</p> <p>Here we describe the implementation of a new scheme with spatially explicit canopies, where tree cohorts have a fixed position within a patch, enabling simulation of forest floor light conditions that better captures spatial variation, especially following disturbances such as tree death or harvest. Additionally, we test a lower-complexity canopy scheme based on the perfect plasticity approximation.</p> <p>To evaluate these developments, we conducted four assessments. First, we evaluated the model's performance against field observations of aboveground woody biomass, mortality, and productivity across diameter size classes. Second, we examined their ability to represent tree functional coexistence. Third, we explored how forest harvest influenced the re-establishment of a woody understory. Lastly, we conducted two sensitivity tests.</p> <p>Results show that the spatially explicit canopy scheme improves the representation of forest tree size structure and dynamics across boreal, temperate, and tropical regions. It enables functional coexistence without the influence of large-scale disturbances, captures the interplay of forest gap dynamics with the establishment of a recruitment layer, and produces more realistic understory light environments and competitive interactions, capabilities not achievable with the standard canopy scheme. By capturing these dynamics without requiring explicit individuals, the scheme expands methodological options for bridging individual-based and cohort-based models, while avoiding abrupt canopy-layer transitions and enabling a more gradual and ecologically consistent representation of canopy reorganization. This improves the representation of stand structure and key demographic processes, enhancing the model's capacity to simulate forest dynamics, resource fluxes, and responses to<span id="page3596"/> environmental change, while improving alignment with observational data.</p>

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APA 7

al, J. E. S. E. (2026). Representing canopy structure dynamics within the LPJ-GUESS dynamic global vegetation model (revision 13221). https://doi.org/10.5194/gmd-19-3595-2026

MLA

al, J. E. Stoebke et. "Representing canopy structure dynamics within the LPJ-GUESS dynamic global vegetation model (revision 13221)." 2026. https://doi.org/10.5194/gmd-19-3595-2026.

Chicago

al, J. E. Stoebke et. 2026. "Representing canopy structure dynamics within the LPJ-GUESS dynamic global vegetation model (revision 13221).". https://doi.org/10.5194/gmd-19-3595-2026.

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al, J. E. S. E. 2026, Representing canopy structure dynamics within the LPJ-GUESS dynamic global vegetation model (revision 13221), Copernicus Publications, available at: https://doi.org/10.5194/gmd-19-3595-2026 [Accessed 28 Jun. 2026].

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Título
Representing canopy structure dynamics within the LPJ-GUESS dynamic global vegetation model (revision 13221)
Autor / colaboradores
J. E. Stoebke et al
Editorial
Copernicus Publications
Año de publicación
2026
ISSN
1991-959X
ISSN
1991-959X
Idioma
eng
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