Improved estimates of biomass expansion factors for Sitka spruce.

Abstract

Allometric regressions for estimating forest biomass were developed and used to predict changes in biomass expansion factors (BEF) for a Sitka spruce chronosequence. Cross validation of the biomass models obtained from a USDA inventory data base and an Irish biomass data set indicated that stand and regional-specific allometric models need to be developed due to the influence of different management practices or climatic conditions. Analyses of the algorithms suggest that DBH, tree height and stand density should be used as inputs for biomass and BEF models to reduce the error of estimate. Based on the analyses presented in this work, BEF values could vary from 1.4 to 5.0 for a selected chronosequence depending on age, yield class and total stem biomass. Our results also suggest that recent carbon sequestration predictions for Sitka spruce forests may have been underestimated by 2 to 4-fold due to an underestimation of BEF, particularly for afforested stands planted since 1990.