Improving individual crown biomass estimation by incorporating competition factors using mixed effect models for Pinus Kesiya

H., Li and M., Xu and Y., Leng and H., Xu and J., Wang and C., Li and A., Wei and Y., Lv and H., Xiong and G., Ou (2023) Improving individual crown biomass estimation by incorporating competition factors using mixed effect models for Pinus Kesiya. Journal of Tropical Forest Science (JTFS) (Malaysia), 35. pp. 249-259. ISSN 0128-1283

Due to the high uncertainty of tree crown biomass modeling, it is crucial to estimate individual tree crown biomass by incorporating competition factors using mixed effect models. The crown biomass of 128 sampling trees was investigated at three typical sites of the natural Pinus kesiya forest in Pu’er city of Yunnan province, China. Considering the random effects of the site index and incorporating competition factors, the branch and needle biomass models were constructed using the nonlinear mixed effect model. The results showed that: (1) the mixed effects models, including the fixed effect of competition factors, had a better fitting performance than the ordinary mixed model for branch biomass, however, mixed effects models without the fixed effect of competition factors had the best-fit performance for the needle biomass; (2) mixed effect models incorporating competition factors had better prediction ability because of the highest precision. The increase in accuracy varied from 49.87 to 70.27% for branch biomass and from 66.19 to 66.57% for needle biomass. Mixed-effects models, considering site effect and competition factors, may provide a flexible and powerful tool for individual crown biomass estimation.

Full text available from: Official URL: https://jtfs.frim.gov.my/jtfs/article/view/2419/19...

Abstract

Due to the high uncertainty of tree crown biomass modeling, it is crucial to estimate individual tree crown biomass by incorporating competition factors using mixed effect models. The crown biomass of 128 sampling trees was investigated at three typical sites of the natural Pinus kesiya forest in Pu’er city of Yunnan province, China. Considering the random effects of the site index and incorporating competition factors, the branch and needle biomass models were constructed using the nonlinear mixed effect model. The results showed that: (1) the mixed effects models, including the fixed effect of competition factors, had a better fitting performance than the ordinary mixed model for branch biomass, however, mixed effects models without the fixed effect of competition factors had the best-fit performance for the needle biomass; (2) mixed effect models incorporating competition factors had better prediction ability because of the highest precision. The increase in accuracy varied from 49.87 to 70.27% for branch biomass and from 66.19 to 66.57% for needle biomass. Mixed-effects models, considering site effect and competition factors, may provide a flexible and powerful tool for individual crown biomass estimation.

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Item Type:	Article
AGROVOC Term:	Pinus kesiya
AGROVOC Term:	forest mensuration
AGROVOC Term:	forest growth
AGROVOC Term:	forest ecology
AGROVOC Term:	sampling
AGROVOC Term:	data collection
AGROVOC Term:	trees
AGROVOC Term:	forest management
Geographical Term:	China
Depositing User:	Ms. Azariah Hashim
Date Deposited:	20 Nov 2025 07:29
Last Modified:	20 Nov 2025 07:29
URI:	http://webagris.upm.edu.my/id/eprint/1683

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