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Nonlinear mixed-effects modeling of variable-exponent taper equations for lodgepole pine in Alberta, Canada

机译:加拿大艾伯塔省黑松的变指数锥度方程的非线性混合效应建模

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Four variable-exponent taper equations and their modified forms were evaluated for lodgepole pine (Pinus contorta var. latifolia Engelm.) trees in Alberta, Canada. A nonlinear mixed-effects modeling approach was applied to account for within- and between-tree variations in stem form. Even though a direct modeling of within-tree autocorrelation by a variance-covariance structure failed to achieve convergence, most of the autocorrelation was accounted for when random-effects parameters were included in the models. Using an independent data set, the best taper equation with two random-effects parameters was chosen based on its ability to predict diameter inside bark, whole tree volume, and sectioned log volume. Diameter measurements from various stem locations were evaluated for tree-specific calibrations by predicting random-effects parameters using an approximate Bayesian estimator. It was found that an upper stem diameter at 5.3 m above ground was best suited for calibrating tree-specific predictions of diameter inside bark, whole tree volume, and sectioned log volume.
机译:对加拿大艾伯塔省的五倍子松(Pinus contorta var。latifolia Engelm。)树木评估了四个变指数锥度方程及其修正形式。应用了非线性混合效应建模方法来说明茎内树内和树间的变化。即使通过方差-协方差结构对树内自相关进行直接建模无法实现收敛,但是当将随机效应参数包括在模型中时,大多数自相关都是考虑在内的。使用一个独立的数据集,根据其预测树皮内直径,整棵树的体积和切片的原木体积的能力,选择了具有两个随机效应参数的最佳锥度方程。通过使用近似贝叶斯估计器预测随机效应参数,评估了来自各个茎位置的直径测量值,以进行树木特定的校准。结果发现,离地面5.3 m处的上部茎直径最适合用于校准树皮内树皮直径,整棵树的体积和断木体积的树状预测。

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