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Data from: Convergence and variation in tree growth trends at the aggregate level

Shu, Shumiao1; Wang, Xiaodan2

Published Nov 04, 2025 on Dryad. https://doi.org/10.5061/dryad.1c59zw495

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Nov 04, 2025 version files 2.47 MB

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Abstract

Individual trees in natural forests often exhibit complex, inconsistent, and variable growth trajectories influenced by genetics, climate change, and uneven stand structure. These growth divergences pose a challenge in predicting the overall growth trend of trees at the aggregate level.

Here, we propose a radius-driven metabolic growth model (IGMR) to explain the radial growth of trees. The IGMR suggests that the best radial growth trajectory (BGT) at the aggregate level varies within a predictable range and can be derived from the maximum radius and total growth time of an individual tree.

Analyses based on a global database confirmed the applicability of the IGMR and found that the average radial growth trend closely follows half of the BGT, with the strength of this association potentially related to functional trait trade-offs.

Further analyses show that climate change and uneven stand structure may cause the overall growth trajectory to undergo more drifts (changes in growth rate only) than adaptations (changes in maximum size).

Synthesis: Our results reveal not only a convergent growth trajectory in tree size (or radius) at the aggregate level, but also suggest that climate regulates the tree growth–climate relationship by influencing the height (i.e., maximum radial growth rate) of this unimodal trajectory, whereas the length (i.e., with maximum tree radius) of the trajectory shows greater dependence on species. These findings further imply that climate change is more likely to affect the forest’s maximum carbon sequestration capacity through shifts in community composition, rather than through direct changes in individual tree growth rates.