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Conventional ecological modeling and sampling frameworks frequently rely on a binary, isolated fine-root paradigm (e.g., a strict 2-mm diameter threshold) that treats fine roots as functionally homogeneous. This approach obscures the full structural aggregation patterns, emergent network complexity, and multi-scale scaling properties of root systems. To address these limitations, this study developed an irregular cylinder ( IC ) root model within a unified structural architecture framework. Tree root networks were modeled as hierarchical clusters of irregular cylinders governed by stable, long-axis orthographic 2D quadrilateral polygon shape constraints to facilitate systematic sampling, digital image processing, and cross-scale annotation. The framework was evaluated using empirical datasets compiled from Cunninghamia lanceolata across various forest developmental stages. The results demonstrate significant non-linear variations in size scaling ratios and scaling exponents, indicating a highly assembled branching architecture with pronounced structural redundancy rather than taproot dominance. Specifically, fine roots, absorptive roots, and second-order roots exhibited distinct shrinkage effects, with scaling exponents for total length, surface area, and volume decreasing sequentially as trait dimensionality increased. Maximum efficiency of nutrient absorption“ is inconsistent with the classic metabolic scaling model. Crucially, the established six-order diameter size classifier successfully reconciles conflicting traditional, functional, and order-based root definitions, serving as a reliable cross-scale operator. By integrating 3D phenotyping, recursive topological constraints, and functional scaling, this modeling framework provides a reproducible mechanism to bridge static structural traits with dynamic developmental processes. These advancements offer a rigorous foundation for refining belowground resource allocation parameterizations in dynamic terrestrial biosphere models (TBMs) under changing climate scenarios.
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Zhao et al. (2026) studied this question.
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