ABSTRACT
Background:
Korean pine ( Pinus koraiensis Siebold & Zucc.) is one of the primary plantation conifer species of economic and ecological importance in northeast China. Forest biomass estimation in the broader landscape has been receiving attention from researchers and forest managers. The development of forest stand biomass models is regarded an effective method to estimate forest biomass at large scales. This study was carried out for developing stand-level biomass models for Korean pine plantations. Four additive methods were compared: Aggregation 1, Aggregation 2, Adjustment, and Disaggregation. All the stand biomass additive modeling systems (i.e., total, root, stem, branch, and leaf) included both stand volume and biomass conversion and expansion factors (BCEFs) as predictors.
Results:
The predictive performance of the four additive methods and Constant BCEFs were ranked as follows: Aggregation 1 > Disaggregation > Adjustment > Aggregation 2 > Constant BCEFs. The prediction accuracy of the four additive methods was not consistent across the stand volume intervals.
Conclusion:
The model based on the Aggregation 1 method was recommended for predicting stand biomass. However, different additive method should be selected according to the stand volume intervals of the Korean pine plantations.
Keywords:
biomass conversion and expansion factors; additive methods; stand biomass
HIGHLIGHTS
Stand biomass models were developed for Korean pine plantations.
Four additive methods were evaluated in this study.
The biomass conversion and expansion factors (BCEFs) showed a significant non-linear relationship with the stand quadratic mean diameter.
The Aggregation 1 method was superior to other methods in estimating stand biomass.
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