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Models for predicting tree and stand development on larch plantations in Hallormsstaour, Iceland

机译：冰岛Hallormsstaour落叶松人工林树木和林分发育的预测模型

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摘要

The aim was to model the growth of Siberian larch ( Larix sibirica Ledeb.) and Russian larch ( Larix sukaczewii Dyl., syn. L. sibirica var. sukaczewii) plantations in Hallormsstaour, Iceland. The field inventory was carried out in eastern Iceland in June 2006. Models were constructed for predicting dominant height, total tree height and 5-year diameter increment. Several linear and non-linear forms of models were tested in preliminary analyses to find the equations that fitted the modelled characteristics best. Due to the spatially hierarchical correlation structure of the data ( stands, plots and trees), the assumption of non-correlated error terms did not hold. Therefore, a random parameter modelling approach was adopted using mixed models when the estimates obtained for the random effects were statistically significant. The variance estimates for the random effects can be further used to calibrate the models. The models generated here performed well with independent test data and were consistent with the forest growth theory. They can be used to evaluate site quality and to estimate the growth and yield of larch stands in eastern Iceland in connection with forest planning.
机译：目的是模拟冰岛哈洛姆施陶尔的西伯利亚落叶松（Larix sibirica Ledeb。）和俄罗斯落叶松（Larix sukaczewii Dyl。，syn。L. sibirica var。sukaczewii）人工林的生长。实地调查是在2006年6月在冰岛东部进行的。构建了用于预测主要树高，总树高和5年直径增量的模型。在初步分析中测试了几种线性和非线性形式的模型，以找到最适合模型特征的方程式。由于数据（林分，地块和树木）在空间上具有层次结构，因此，不相关误差项的假设不成立。因此，当获得的随机效应估计值具有统计学意义时，采用混合模型的随机参数建模方法。随机效应的方差估计值可以进一步用于校准模型。此处生成的模型在独立测试数据的基础上表现良好，并且与森林生长理论一致。它们可用于评估场地质量，并估计冰岛东部与森林规划相关的落叶松林的生长和产量。

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