俄勒冈州西部水源河岸森林n树距离抽样清查的评价

Zane Haxtema, H. Temesgen, Theresa Marquardt
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引用次数: 15

摘要

n树距离抽样(NTDS),也被称为k树抽样和点对树抽样,已被推广为一种实用的森林清查方法。本模拟研究评估了三种NTDS估算方法在估算俄勒冈西部水源河岸森林密度和基底面积方面的性能,并与固定样地采样和水平点采样进行了比较。当每个样本点至少捕获6棵树时,至少一个NTDS估计器对密度和基底面积的偏差都很低,但NTDS对密度估计的性能较差,表现为聚类模式。最后,我们对类似森林条件下NTDS对河岸区清查的统计效率提出了一些意见。
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Evaluation of n-tree distance sampling for inventory of headwater riparian forests of western Oregon
n-Tree distance sampling (NTDS), also known as k-tree sampling and point-to-tree sampling, has been promoted as a practical method for forest inventory. This simulation study evaluated the performance of three NTDS estimators, as compared with fixed plot sampling and horizontal point sampling, for estimating density and basal area in headwater riparian forests of western Oregon. Bias of at least one NTDS estimator was low for both density and basal area when at least six trees were captured at each sample point, but performance of NTDS for density estimation was poor on stem maps exhibiting a clustered pattern. We close with some comments regarding the statistical efficiency of NTDS for riparian area inventory in similar forest conditions.
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