Estimation of biomass in various components of Pinus koraiensis based on Bayesian methods DOI Creative Commons
Hui Liu, Xibin Dong, Ying Zhang

et al.

Frontiers in Forests and Global Change, Journal Year: 2024, Volume and Issue: 7

Published: June 17, 2024

Introduction Pinus koraiensis is a dominant tree species in northeastern China. Estimating its biomass required for forest carbon stock monitoring and accounting. Methods This study investigates estimation methods P. components. A Bayesian approach was used to synthesize the parameter distributions of 298 models as prior information estimate trunk, branch, leaf, root . The results were compared with non-informative minimum least squares (MLS). Results indicated that outperformed other regarding model fit prediction error. In addition, responses different components height varied. trunk exhibited smaller response height, whereas those branches leaves showed larger height. parameters yield precise estimations. Discussion sum, this highlights potential estimating proposes further enhancements improve accuracy.

Language: Английский

Estimation of biomass in various components of Pinus koraiensis based on Bayesian methods DOI Creative Commons
Hui Liu, Xibin Dong, Ying Zhang

et al.

Frontiers in Forests and Global Change, Journal Year: 2024, Volume and Issue: 7

Published: June 17, 2024

Introduction Pinus koraiensis is a dominant tree species in northeastern China. Estimating its biomass required for forest carbon stock monitoring and accounting. Methods This study investigates estimation methods P. components. A Bayesian approach was used to synthesize the parameter distributions of 298 models as prior information estimate trunk, branch, leaf, root . The results were compared with non-informative minimum least squares (MLS). Results indicated that outperformed other regarding model fit prediction error. In addition, responses different components height varied. trunk exhibited smaller response height, whereas those branches leaves showed larger height. parameters yield precise estimations. Discussion sum, this highlights potential estimating proposes further enhancements improve accuracy.

Language: Английский

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