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首页> 外文期刊>Revista rvore >TAMANHO E FORMA DA UNIDADE AMOSTRAL PARA QUANTIFICA??O DA SERAPILHEIRA EM FRAGMENTO DE FLORESTA ESTACIONAL SUBTROPICAL1
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TAMANHO E FORMA DA UNIDADE AMOSTRAL PARA QUANTIFICA??O DA SERAPILHEIRA EM FRAGMENTO DE FLORESTA ESTACIONAL SUBTROPICAL1

机译：亚热带林段中凋落物量化的样本单元的尺寸和形状1

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摘要

To study the nutrient cycle in a forest, a precise estimation of the amount of litter produced and its fractions is necessary. Among the recognized ways to minimize variability between samples is the use of optimal sampling size units to litter collection. However, there are a few recommendations found in another studies for this parameter, which generates variation in the size of the sampling unit used in similar experiments. The aim of this work is to determine the optimal size and shape of the sampling unit for quantification of litter in a Subtropical Seasonal Forest fragment. For this purpose, five plots of 3.0 x 2.0 meters in each season were randomly allocated in the area, subdivided into 96 basic units of 0.25 x 0.25 meters. In each basic unit all organic matter above ground was collected and separated in the fractions leaves, twigs and waste. The estimative of the basic units optimal size was obtained by two different methods. It was observed that the coefficient of variation decreases as the size of the sample unit is increased; there are differences in the production variability of litter between the plots in the same collection station; rectangular sampling units are more homogeneous than the square ones; the use of sample units 0,40m2 (1.5m x 0.25m) is recommend for litter quantification produced in Subtropical Seasonal Forest fragment.
机译：为了研究森林中的营养循环，需要精确地估计所产生的凋落物和其级分。在最小化样本之间的可变性的认可方式中，使用最佳采样尺寸单元与垃圾收集。然而，在该参数的另一个研究中发现了一些建议，它产生了类似实验中使用的采样单元的尺寸的变化。这项工作的目的是确定亚热带季节性森林片段中凋落物的采样单元的最佳尺寸和形状。为此目的，在该地区随机分配了每季3.0 x 2.0米的五个地块，细分为0.25 x 0.25米的96个基本单位。在每个基本单元中，收集地面上面的所有有机物质并在馏分，树枝和废物中分离。通过两种不同的方法获得基本单位最佳尺寸的估计。观察到，随着样品单元的尺寸增加，变异系数降低;在相同收集站的地块之间的垃圾的生产变异性存在差异;矩形采样单元比方形的采样单元更加均匀;使用样品单元0,40M2（1.5M×0.25M）推荐用于亚热带季节性森林片段中生产的垃圾量化。

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