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Development and evaluation of height diameter at breast models for native Chinese Metasequoia

机译:中国水杉乳房模型的身高直径的建立和评估

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摘要

Accurate tree height and diameter at breast height (dbh) are important input variables for growth and yield models. A total of 5503 Chinese Metasequoia trees were used in this study. We studied 53 fitted models, of which 7 were linear models and 46 were non-linear models. These models were divided into two groups of single models and multivariate models according to the number of independent variables. The results show that the allometry equation of tree height which has diameter at breast height as independent variable can better reflect the change of tree height; in addition the prediction accuracy of the multivariate composite models is higher than that of the single variable models. Although tree age is not the most important variable in the study of the relationship between tree height and dbh, the consideration of tree age when choosing models and parameters in model selection can make the prediction of tree height more accurate. The amount of data is also an important parameter what can improve the reliability of models. Other variables such as tree height, main dbh and altitude, etc can also affect models. In this study, the method of developing the recommended models for predicting the tree height of native Metasequoias aged 50–485 years is statistically reliable and can be used for reference in predicting the growth and production of mature native Metasequoia.
机译:准确的树高和胸高直径(dbh)是生长和产量模型的重要输入变量。这项研究共使用了5503棵中国水杉树。我们研究了53个拟合模型,其中7个是线性模型,而46个是非线性模型。根据自变量的数量,将这些模型分为两类:单模型和多元模型。结果表明,以身高直径为自变量的树木高度的变长方程可以较好地反映树木高度的变化。另外,多元复合模型的预测精度高于单变量模型。尽管树龄不是研究树高与dbh之间关系的最重要变量,但是在模型选择中选择模型和参数时考虑树龄可以使树高的预测更加准确。数据量也是可以提高模型可靠性的重要参数。其他变量(例如树高,主dbh和海拔等)也会影响模型。在这项研究中,开发推荐模型以预测50-485岁的当地水杉的树高的方法在统计上是可靠的,可为预测成熟的当地水杉的生长和生产提供参考。

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