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Biomass Functions and Carbon Content Variabilities of Natural and Planted Pinus koraiensis in Northeast China

The population of natural Korean pine (Pinus koraiensis) in northeast China has sharply declined due to massive utilization for its high-quality timber, while this is vice versa for Korean pine plantations after various intensive afforestation schemes applied by China’s central authority. Hence, mor...

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Autores principales: Widagdo, Faris Rafi Almay, Dong, Lihu, Li, Fengri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910931/
https://www.ncbi.nlm.nih.gov/pubmed/33494503
http://dx.doi.org/10.3390/plants10020201
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author Widagdo, Faris Rafi Almay
Dong, Lihu
Li, Fengri
author_facet Widagdo, Faris Rafi Almay
Dong, Lihu
Li, Fengri
author_sort Widagdo, Faris Rafi Almay
collection PubMed
description The population of natural Korean pine (Pinus koraiensis) in northeast China has sharply declined due to massive utilization for its high-quality timber, while this is vice versa for Korean pine plantations after various intensive afforestation schemes applied by China’s central authority. Hence, more comprehensive models are needed to appropriately understand the allometric relationship variations between the two origins. In this study, we destructively sampled Pinus koraiensis from several natural and plantation sites in northeast China to investigate the origin’s effect on biomass equations. Nonlinear seemingly unrelated regression with weighted functions was used to present the additivity property and homogenize the model residuals in our two newly developed origin-free (population average) and origin-based (dummy variable) biomass functions. Variations in biomass allocations, carbon content, and root-to-shoot ratio between the samples obtained from plantations and natural stands were also investigated. The results showed that (1) involving the origin’s effect in dummy variable models brought significant improvement in model performances compared to the population average models; (2) incorporating tree total height (H) as an additional predictor to diameter at breast height (D) consistently increase the models’ accuracy compared to using D only as of the sole predictors for both model systems; (3) stems accounted for the highest partitioning proportions and foliage had the highest carbon content among all biomass components; (4) the root-to-shoot ratio ranged from 0.18–0.35, with plantations (0.28 ± 0.04) had slightly higher average value (±SD) compared to natural forests (0.25 ± 0.03). Our origin-based models can deliver more accurate individual tree biomass estimations for Pinus koraiensis, particularly for the National Forest Inventory of China.
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spelling pubmed-79109312021-02-28 Biomass Functions and Carbon Content Variabilities of Natural and Planted Pinus koraiensis in Northeast China Widagdo, Faris Rafi Almay Dong, Lihu Li, Fengri Plants (Basel) Article The population of natural Korean pine (Pinus koraiensis) in northeast China has sharply declined due to massive utilization for its high-quality timber, while this is vice versa for Korean pine plantations after various intensive afforestation schemes applied by China’s central authority. Hence, more comprehensive models are needed to appropriately understand the allometric relationship variations between the two origins. In this study, we destructively sampled Pinus koraiensis from several natural and plantation sites in northeast China to investigate the origin’s effect on biomass equations. Nonlinear seemingly unrelated regression with weighted functions was used to present the additivity property and homogenize the model residuals in our two newly developed origin-free (population average) and origin-based (dummy variable) biomass functions. Variations in biomass allocations, carbon content, and root-to-shoot ratio between the samples obtained from plantations and natural stands were also investigated. The results showed that (1) involving the origin’s effect in dummy variable models brought significant improvement in model performances compared to the population average models; (2) incorporating tree total height (H) as an additional predictor to diameter at breast height (D) consistently increase the models’ accuracy compared to using D only as of the sole predictors for both model systems; (3) stems accounted for the highest partitioning proportions and foliage had the highest carbon content among all biomass components; (4) the root-to-shoot ratio ranged from 0.18–0.35, with plantations (0.28 ± 0.04) had slightly higher average value (±SD) compared to natural forests (0.25 ± 0.03). Our origin-based models can deliver more accurate individual tree biomass estimations for Pinus koraiensis, particularly for the National Forest Inventory of China. MDPI 2021-01-21 /pmc/articles/PMC7910931/ /pubmed/33494503 http://dx.doi.org/10.3390/plants10020201 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Widagdo, Faris Rafi Almay
Dong, Lihu
Li, Fengri
Biomass Functions and Carbon Content Variabilities of Natural and Planted Pinus koraiensis in Northeast China
title Biomass Functions and Carbon Content Variabilities of Natural and Planted Pinus koraiensis in Northeast China
title_full Biomass Functions and Carbon Content Variabilities of Natural and Planted Pinus koraiensis in Northeast China
title_fullStr Biomass Functions and Carbon Content Variabilities of Natural and Planted Pinus koraiensis in Northeast China
title_full_unstemmed Biomass Functions and Carbon Content Variabilities of Natural and Planted Pinus koraiensis in Northeast China
title_short Biomass Functions and Carbon Content Variabilities of Natural and Planted Pinus koraiensis in Northeast China
title_sort biomass functions and carbon content variabilities of natural and planted pinus koraiensis in northeast china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910931/
https://www.ncbi.nlm.nih.gov/pubmed/33494503
http://dx.doi.org/10.3390/plants10020201
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