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Comparative efficiency and accuracy of variable area transects versus square plots for sampling tree diversity and density

机译:可变面积样带与正方形样带在采样树多样性和密度上的比较效率和准确性

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摘要

Agroforestry systems have been recognized as areas with high conservation potential, and there is a need to quickly assess the biodiversity and tree stocking density available in these systems. However, it is not clear if the commonly used fixed area plot is most efficient for sampling such landscapes, or if a different method could provide equivalent data with less effort. Thus, a field and simulation-based study was carried out to compare the efficiency and accuracy of a variable area transect versus the fixed area square plot. Field efficiency tests were carried out in three habitat types, robusta coffee plantations, arabica coffee plantations and a privately owned forest fragment, in Kodagu, southern India. A simulation study of bias, precision and accuracy of the two methods for tree density estimation also was carried out using various spatial distribution patterns and densities. The variable area transect was significantly more efficient per unit effort in the field than the fixed area square plot. In the simulation tests both methods performed equally well under random spatial distribution. However, under simulated aggregated distribution both methods were positively biased (square plot up to 12% at low density, variable area transect 9–12% at all densities), and under simulated regular distribution the variable area transect was slightly negatively biased (−5 to −7% at medium to high density). The variable area transect thus can be recommended over the square plot for rapid assessment of tree diversity and density, when the vegetation is expected to be randomly dispersed.
机译:农林业系统被认为是具有高度保护潜力的地区,因此需要快速评估这些系统中可用的生物多样性和树木种群密度。但是,尚不清楚常用的固定面积图对于采样此类景观是否最有效,或者其他方法是否可以以较少的努力提供等效数据。因此,进行了基于现场和模拟的研究,以比较可变面积样线与固定面积正方形图的效率和准确性。在印度南部的科达古,对三种生境类型(罗布斯塔咖啡种植园,阿拉比卡咖啡种植园和私有林地段)进行了田间效率测试。还使用各种空间分布模式和密度对两种树木密度估计方法的偏差,精度和准确性进行了仿真研究。可变面积样带在田间每单位工作量的效率明显高于固定面积正方形图。在模拟测试中,两种方法在随机空间分布下均表现良好。但是,在模拟的聚集分布下,两种方法都具有正偏向性(在低密度下,方图最高可达12%,在所有密度下可变面积横断面均为9-12%),而在模拟正则分布下,可变面积横断面则稍有负偏斜(-5到中密度到高密度为-7%)。因此,当预计植被将被随机分散时,可以在平方图上推荐可变面积的样条,以快速评估树木的多样性和密度。

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