基于爱沙尼亚森林研究样地网络数据的林分基面积毛生长模型

Q4 Agricultural and Biological Sciences
Allar Padari, Andres Kiviste, Diana Laarmann, Ahto Kangur
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引用次数: 0

摘要

摘要利用林分水平总积增量模型对未来林分产量进行估算。通常,在实际使用的模型中,林分生长和产量是由树的体积增量来描述的,其中包括直径生长函数,树高和茎尖作为输入变量。爱沙尼亚目前使用的林分体积增量函数还包括林分相对密度作为一个额外的输入变量。在本研究中,我们基于爱沙尼亚森林研究样地网络(ENFRP)的周期性测量数据开发了一个基底面积增量函数。与先前Priit Kohava开发的林分体积增量模型一样,在当前模型中,树种基底面积增量是针对纯林分开发的,而对于混合林分,则使用树种基底面积的比例。我们的数据测试表明,在主楼树种份额变化的情况下,周期增量预测具有很好的拟合性,并且与芬兰和瑞典同事的早期研究相吻合。对于大多数树种和林分相对密度,所建立的基础面积增量模型的预测结果均高于已有的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The model of stand basal area gross growth on the data of the Estonian Network of Forest Research Plots
Abstract The stand level gross volume increment models are used to estimate the future production of tree stands. Very often, the stand growth and yield in the models used in practice are described by the tree volume increment that includes the diameter growth function with the tree height together with stem taper as the input variables. The currently used function of stand volume increment in Estonia included also stand relative density as an additional input variable. In the current study, we developed a basal area increment function based on the periodic measurement data of the Estonian Network of Forest Research Plots (ENFRP). As in the earlier model of stand volume increment developed by Priit Kohava, in the current model the basal area increment of tree species is developed for a pure stand, and for mixed stands, the proportion of the tree species’ basal area is used. The tests in our data indicated that the periodic increment prognosis had good fit in the case of variable share of tree species in the main storey and coincide with the earlier studies by Finnish and Swedish colleagues. The developed model of basal area increment predictions are expectedly higher than the earlier model predictions for the most tree species and stand relative densities.
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来源期刊
Forestry Studies
Forestry Studies Agricultural and Biological Sciences-Forestry
CiteScore
0.70
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0.00%
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