3D crown shape and tree ring development are autobiographies of the growth conditions. With advancements in terrestrial laser scanning, modeling growth from 3D crown structure offers insights into trees’ structural and functional responses in a non-destructive and repetitive way. However, how the trees in different growing conditions respond in 3D structure and manifest their responses into tree rings remains unexplored, which would help to better explain tree-level growth dynamics and forest management. To enhance this understanding, we tested a set of hypotheses: (HI) that 3D crown shape (CS) and tree ring (width) patterns (TRP) are correlated across different growing conditions or forest stands like monospecific, provenances trials, and mixed forest stands; (HII) that stand types influence the CS-TRP link; and (HⅢ) local neighborhood competition (LNC) modulates the CS-TRP link. (HⅣ) 3D crowns manifest local growth conditions; therefore, 3D crown structures can be used to predict tree ring growth. We assessed these hypotheses by employing terrestrial laser scanning-based 3D crown shape and dendrochronology-based tree ring width patterns from Norway spruce ( [L.] Karst.) trees growing in pure spruce (unthinned and thinned), provenances trial, and mixed-species trial (with European Beech, [L.]) stands covering a large-scale competition gradient. We first show that 3D crown shape and TRP metrics differed significantly across forests (p<0.05) but were correlated (p<0.05). Neighborhood competition among the forest types influences the link between 3D crowns and tree rings. Pathway-based analyses revealed that neighborhood competition indirectly influences ring variability by modifying crown structure (p<0.05), suggesting local growth conditions are mostly manifested into crown shapes, leading to 3D crown shape-based low-error growth predictions (0.44 mm) across forest types. However, incorporating competition legacy information (competition over the last 30 years) in the model slightly improved the prediction performance (error reduced to 0.41 mm), further explaining that the crown likely loses growth information due to growing conditions (competition it faces and species with it is growing). This study reveals how trees in different growing conditions differed structurally and mechanized their responses in tree rings, providing crucial insights into tree-level growth dynamics and management.

中文翻译：

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邻里竞争调节单种林和混交林中树冠结构和树木年轮变异之间的联系

3D树冠形状和树轮发育是生长条件的自传。随着地面激光扫描的进步，3D 树冠结构的生长建模可以以非破坏性和重复的方式深入了解树木的结构和功能反应。然而，不同生长条件下的树木如何在 3D 结构中做出反应以及如何将其反应体现在树木年轮上仍有待探索，这将有助于更好地解释树木生长动态和森林管理。为了加深这种理解，我们测试了一组假设：(HI) 3D 树冠形状 (CS) 和树木年轮（宽度）模式 (TRP) 在不同的生长条件或林分（如单一物种、种源试验和混交林）中相关站立; (HII) 站点类型影响 CS-TRP 链路； (HⅢ)本地邻里竞争(LNC)调节CS-TRP链路。 (HIV) 3D牙冠显示局部生长情况；因此，3D 树冠结构可用于预测树木年轮的生长。我们通过采用基于地面激光扫描的 3D 树冠形状和基于树木年代学的树轮宽度模式来评估这些假设，这些模式来自生长在纯云杉（未间伐和间伐）中的挪威云杉（[L.] Karst.）树木、种源试验和混合云杉。物种试验（欧洲山毛榉，[L.]）覆盖了大规模的竞争梯度。我们首先表明，3D 树冠形状和 TRP 指标在不同森林之间存在显着差异 (p<0.05)，但相关 (p<0.05)。森林类型之间的邻域竞争影响 3D 树冠和树木年轮之间的联系。基于路径的分析表明，邻域竞争通过改变冠结构间接影响环变异性（p<0.05），表明局部生长条件主要表现为冠形状，从而导致基于 3D 冠形状的低误差生长预测（0.44 mm）森林类型。然而，在模型中纳入竞争遗留信息（过去 30 年的竞争）略微提高了预测性能（误差减少到 0.41 毫米），进一步解释了树冠可能由于生长条件（它面临的竞争和物种）而丢失了生长信息。它正在增长）。这项研究揭示了不同生长条件下的树木如何在结构上有所不同，并机械化其对树木年轮的反应，为树木生长动态和管理提供了重要的见解。