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A predictive nondestructive model for the covariation of tree height, diameter and stem volume scaling relationships

机译:树高,直径和茎体缩放关系的预测无损模型

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Metabolic scaling theory (MST) posits that the scaling exponents among plant height H, diameter D, and biomass M will covary across phyletically diverse species. However, the relationships between scaling exponents and normalization constants remain unclear. Therefore, we developed a predictive model for the covariation of H, D, and stem volume V scaling relationships and used data from Chinese fir (Cunninghamia lanceolata) in Jiangxi province, China to test it. As predicted by the model and supported by the data, normalization constants are positively correlated with their associated scaling exponents for D vs. V and H vs. V, whereas normalization constants are negatively correlated with the scaling exponents of H vs. D. The prediction model also yielded reliable estimations of V (mean absolute percentage error?=?10.5?±?0.32 SE across 12 model calibrated sites). These results (1) support a totally new covariation scaling model, (2) indicate that differences in stem volume scaling relationships at the intra-specific level are driven by anatomical or ecophysiological responses to site quality and/or management practices, and (3) provide an accurate non-destructive method for predicting Chinese fir stem volume.
机译:代谢缩放理论(MST)定位植物高度H,直径D和生物质M之间的缩放指数将在语言中的细节中进行Covary。然而,缩放指数与标准化常数之间的关系仍然不清楚。因此,我们为江西省江西省杉木(Cunninghamia Lanceolata)开发了H,D和STEM卷V扩展关系和使用数据的预测模型。如模型的预测并由数据支持,标准化常数与D对V和H与V的相关缩放指数呈正相关,而归一化常数与H与H的缩放指数负相关。预测模型还产生了V的可靠估计v(平均绝对百分比误差?= 10.5?±0.32 SE,跨越12型校准点)。这些结果(1)支持完全新的协变量缩放模型,(2)表明,特定于特定级别的茎体积缩放关系的差异由对现场质量和/或管理实践的解剖或生态学反应以及(3)提供一种准确的非破坏性方法,用于预测中国FIR茎体积。

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