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The Efficiency of Sampling Methods for Dendrometric Estimates of Thinned Stands of Pinus taeda L. in Santa Catarina, Brazil

机译:巴西圣卡塔琳娜州针叶松稀疏林的树木密度测算方法的效率

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This study aimed to compare the efficiency of the sampling methods: Fixed Area, Bitterlich, Prodan and Modified Prodan to estimate the commercial volume and other dendrometric estimators for a 34 years old of Pinus taeda L. stands located in Campo Belo do Sul, Santa Catarina, Brazil. It were distributed a total of 10 sample units of the following methods: Fixed Area with 200, 400 and 500 m of area, Bitterlich, Prodan and Modified Prodan were distributed, both with 6, 7, 8, 9 and 10 trees. In addition to collecting dendrometric data, the installation time of the sample units was timed, whereby the relative efficiency for each method was calculated. The comparison between the harvest volumes and the volumes estimated by the methods was performed by the Skott Knott test, and the results that did not differ statistically were weighted by the parameters of relative error, relative efficiency and proximity to harvest. All variations of the Modified Prodan and Prodan methods had sample insufficiency. The number of trees per hectare presented higher values for the 200 m Fixed Area method and lower values for Prodan with 10 trees. Prodan with 6 trees got the shortest time. The Bitterlich method obtained sample adequancy at 10% error and presented the best result. Among the alternative methods to Fixed Area, Modified Prodan with 7 trees can be indicated for pilot inventory. However, when more precise results are needed, the Bitterlich method is indicated.
机译:这项研究旨在比较采样方法的效率:固定面积,Bitterlich,Prodan和Modified Prodan,以估算位于圣卡塔琳娜州Campo Belo do Sul的34岁Pinus taeda L.林分的商业规模和其他树木密度估计量。 , 巴西。通过以下方法总共分配了10个样本单元:分别分配了200、400和500 m的固定面积,Bitterlich,Prodan和Modified Prodan,并分别有6、7、8、9和10棵树。除了收集树木密度数据外,还对样品单元的安装时间进行计时,从而计算出每种方法的相对效率。收获量与通过该方法估算的量之间的比较是通过Skott Knott检验进行的,统计上没有差异的结果由相对误差,相对效率和接近收获的参数加权。改进的Prodan和Prodan方法的所有变体均存在样品不足。对于200 m固定面积方法,每公顷的树木数量显示较高的值,而对于10棵树木的Prodan,则表示较低的值。拥有6棵树的Prodan花了最短的时间。 Bitterlich方法在10%的误差下获得了足够的样品,并给出了最佳结果。在固定面积的替代方法中,可以指示具有7棵树的改良Prodan作为试点清单。但是,当需要更精确的结果时,可以使用Bitterlich方法。

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