Evaluation of n-tree distance sampling for inventory of headwater riparian forests of western Oregon

Abstract

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.