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Research Article | Open Access

Higher planting density accelerates structural heterogeneity and shifts growth dominance earlier toward large trees in Chinese fir plantations

Yihang Jianga,bJun ChenaThomas J. DeancJianguo ZhangaXiongqing Zhanga,b( )
State Key Laboratory of Efficient Production of Forest Resources, Key Laboratory of Tree Breeding and Cultivation of the National Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
Collaborative Innovation Center of Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
School of Renewable Natural Resources, Louisiana State University Agricultural Center, Baton Rouge, LA 70803, USA

Peer review under the responsibility of Editorial Office of Forest Ecosystems.

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Abstract

Growth dominance (GD) is an important indicator of structure—function coupling that describes how trees of different sizes contribute to stand growth. It plays a key role in understanding stand competition structure, resource-use patterns, and density regulation mechanisms in plantations. Although planting density strongly drives structural differentiation and competitive hierarchy formation, the dynamic coupling among density, structural heterogeneity, and GD remains insufficiently quantified. In this study, we used long-term density-control experiments of Chinese fir (Cunninghamia lanceolata) across Fujian, Jiangxi, Guangxi, and Sichuan provinces, and fitted generalized additive mixed models (GAMMs) incorporating plot-level random effects and autoregressive model of order 1 (AR (1)) temporal structures to analyze the temporal dynamics of GD under different planting densities. We quantified key competitive time characteristics—transition point of GD change (t0), peak rate of GD change (t*), and the structural–functional relationship between GD and diameter inequality (Gini index (GI)). The results showed that (1) stand GI exhibited a "decline–rise" pattern with age. The minimum GI (AgeGI-min) occurring at 8–10 years and was strongly negatively correlated with the natural logarithm of planting density (N0) (R2 = 0.86, P < 0.05), indicating that higher planting densities led to earlier structural convergence; (2) GD shifted from negative to positive with stand development and was significantly affected by age, planting density, and their interaction. The turning point of GD (t0) was strongly negatively correlated with lnN0, suggesting earlier transition to large-tree–dominated growth under higher densities; (3) GD and GI showed a significant "inverted U-shaped" relationship, with maximum GD occurring at intermediate levels of structural heterogeneity; (4) the optimal structure (GI*), at which GD was maximized, increased monotonically with planting density, indicating that stands at higher planting densities were characterized by higher levels of structural differentiation when GD reaches its maximum, reflecting stronger competition and enhanced size differentiation; (5) mean GI and mean GD were highly positively correlated with lnN0 (r = 0.997 and 0.900), whereas t0 showed strong negative correlations (r = −0.943 and −0.804), reinforcing that planting density regulates GD formation by altering structural development and the timing of competitive shift. Overall, planting density shapes the trajectories of diameter-structure evolution and GD formation, thereby modifying size-dependent growth allocation within stands. This study reveals a density-driven GI–GD co-evolution mechanism in Chinese fir plantations and provides scientific guidance for density management, timing of first thinning, and structure-oriented plantation management.

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Cite this article:
Jiang Y, Chen J, Dean TJ, et al. Higher planting density accelerates structural heterogeneity and shifts growth dominance earlier toward large trees in Chinese fir plantations. Forest Ecosystems, 2026, 15(2). https://doi.org/10.1016/j.fecs.2026.100437

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Received: 30 December 2025
Revised: 28 January 2026
Accepted: 07 February 2026
Published: 01 April 2026
© 2026 The Authors.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).