https://dx.doi.org/10.1016/j.fecs.2024.100171">
 

Abstract

Volume is an important attribute used in many forest management decisions. Data from 83 fixed-area plots located in central New Brunswick, Canada, are used to examine how different measures of stand-level diameter and height influence volume prediction using a stand-level variant of Honer's (1967) volume equation. When density was included in the models (Volume=f(Diameter,Height,Density)) choice of diameter measure was more important than choice of height measure. When density was not included (Volume=f(Diameter,Height)), the opposite was true. For models with density included, moment-based estimators of stand diameter and height performed better than all other measures. For models without density, largest tree estimators of stand diameter and height performed better than other measures. The overall best equation used quadratic mean diameter, Lorey's height, and density (root mean square error = 5.26 m3 ha−1 1.9 % relative error). The best equation without density used mean diameter of the largest trees needed to calculate a stand density index of 400 and the mean height of the tallest 400 trees per ha (root mean square error = 32.08 m3 ha−1 11.8 % relative error). The results of this study have some important implications for height subsampling and LiDAR-derived forest inventory analyses.

Department

Natural Resources and the Environment

Publication Date

2-22-2024

Journal Title

Forest Ecosystems

Publisher

Elsevier BV

Digital Object Identifier (DOI)

https://dx.doi.org/10.1016/j.fecs.2024.100171

Document Type

Article

Rights

© 2024 The Authors

Comments

This is an open access article published by Elsevier BV in Forest Ecosystems in 2024, available online: https://dx.doi.org/10.1016/j.fecs.2024.100171

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