首页> 外文期刊>Forest Systems >Modelling diameter distributions of Quercus suber L. stands in “Los Alcornocales” Natural Park (Cádiz-Málaga, Spain) by using the two-parameter Weibull function
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Modelling diameter distributions of Quercus suber L. stands in “Los Alcornocales” Natural Park (Cádiz-Málaga, Spain) by using the two-parameter Weibull function

机译:利用两参数威布尔函数,在“ Los Alcornocales”自然公园(西班牙加的斯-马拉加)中对栎属栎的直径分布进行建模

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Aim of study: The aim of this work was to model diameter distributions of Quercus suber stands. The ultimate goal was to construct models enabling the development of more affordable forest inventory methods. This is the first study of this type on cork oak forests in the area. Area of study : The area of study is “Los Alcornocales” Natural Park (Cádiz-Málaga, Spain). Material and methods : The diameter distributions of 100 permanent plots were modelled with the two-parameter Weibull function. Distribution parameters were fitted with the non-linear regression, maximum likelihood, moment and percentile-based methods. Goodness of fit with the different methods was compared in terms of number of plots rejected by the Kolmogorov-Smirnov test, bias, mean square error and mean absolute error. The scale and shape parameters in the Weibull function were related to the stand variables by using the parameter prediction model. Main results : The best fitting was obtained with the non-linear regression approach, using as initial values those obtained by maximum likelihood method, the percentage of rejections by the Kolmogorov-Smirnov test was 2% of the total number of cases. The scale parameter (b) was successfully modelled in terms of the quadratic mean diameter under cork ( R 2 adj = 0.99). The shape parameter (c) was modelled by using maximum diameter, minimum diameter and plot elevation ( R 2 adj = 0.40). Research highlights : The proposed model diameter distribution can be a highly useful tool for the inventorying and management of cork oak forests. Key words : maximum likelihood method; moment method; non linear regression approach; parameter prediction model; percentile method; scale parameter; shape parameter.
机译:研究目的:这项工作的目的是模拟栎木林分的直径分布。最终目标是构建模型,从而能够开发出更多可负担的森林清单方法。这是对该地区软木栎林的首次此类研究。研究领域:研究领域是“ Los Alcornocales”自然公园(西班牙加的斯-马拉加)。材料和方法:用两参数Weibull函数对100个永久样地的直径分布进行建模。分布参数采用非线性回归,最大似然,矩和基于百分位数的方法进行拟合。通过Kolmogorov-Smirnov检验拒绝的样图数量,偏差,均方误差和平均绝对误差,比较了不同方法的拟合优度。通过使用参数预测模型,Weibull函数中的比例和形状参数与林分变量相关。主要结果:使用非线性回归方法获得最佳拟合,以通过最大似然法获得的初始值作为初始值,Kolmogorov-Smirnov检验的拒绝率为病例总数的2%。比例参数(b)已根据软木塞下的二次平均直径(R 2 adj = 0.99)成功建模。形状参数(c)通过使用最大直径,最小直径和标高(R 2 adj = 0.40)进行建模。研究重点:建议的模型直径分布对于软木橡树林的盘存和管理可能是非常有用的工具。关键词:最大似然法矩法非线性回归法参数预测模型百分位数法比例参数形状参数。

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