J. For. Sci., 2020, 66(4):133-149 | DOI: 10.17221/141/2019-JFS

Retrieval of among-stand variances from one observation per standOriginal Paper

Steen Magnussen^*,1, Johannes Breidenbach²

¹ Natural Resources Canada, Canadian Forest Service, Pacific Forestry Centre, Victoria BC, Canada

² Norwegian Institute of Bioeconomy Research, Ås, Norway

Forest inventories provide predictions of stand means on a routine basis from models with auxiliary variables from remote sensing as predictors and response variables from field data. Many forest inventory sampling designs do not afford a direct estimation of the among-stand variance. As consequence, the confidence interval for a model-based prediction of a stand mean is typically too narrow. We propose a new method to compute (from empirical regression residuals) an among-stand variance under sample designs that stratify sample selections by an auxiliary variable, but otherwise do not allow a direct estimation of this variance. We test the method in simulated sampling from a complex artificial population with an age class structure. Two sampling designs are used (one-per-stratum, and quasi systematic), neither recognize stands. Among-stand estimates of variance obtained with the proposed method underestimated the actual variance by 30-50%, yet 95% confidence intervals for a stand mean achieved a coverage that was either slightly better or at par with the coverage achieved with empirical linear best unbiased estimates obtained under less efficient two-stage designs.

Keywords: coverage; heteroscedasticity; one-per-stratum; quasi systematic; stand mean; two-stage sampling

Published: April 30, 2020  Show citation