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Allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, Northeastern China

Understanding forest carbon budget and dynamics for sustainable resource management and ecosystem functions requires quantification of above- and below-ground biomass at individual tree species and stand levels. In this study, a total of 122 trees (9–12 per species) were destructively sampled to det...

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Autores principales: He, Huaijiang, Zhang, Chunyu, Zhao, Xiuhai, Fousseni, Folega, Wang, Jinsong, Dai, Haijun, Yang, Song, Zuo, Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5774681/
https://www.ncbi.nlm.nih.gov/pubmed/29351291
http://dx.doi.org/10.1371/journal.pone.0186226
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author He, Huaijiang
Zhang, Chunyu
Zhao, Xiuhai
Fousseni, Folega
Wang, Jinsong
Dai, Haijun
Yang, Song
Zuo, Qiang
author_facet He, Huaijiang
Zhang, Chunyu
Zhao, Xiuhai
Fousseni, Folega
Wang, Jinsong
Dai, Haijun
Yang, Song
Zuo, Qiang
author_sort He, Huaijiang
collection PubMed
description Understanding forest carbon budget and dynamics for sustainable resource management and ecosystem functions requires quantification of above- and below-ground biomass at individual tree species and stand levels. In this study, a total of 122 trees (9–12 per species) were destructively sampled to determine above- and below-ground biomass of 12 tree species (Acer mandshuricum, Acer mono, Betula platyphylla, Carpinus cordata, Fraxinus mandshurica, Juglans mandshurica, Maackia amurensis, P. koraiensis, Populus ussuriensis, Quercus mongolica, Tilia amurensis and Ulmus japonica) in coniferous and broadleaved mixed forests of Northeastern China, an area of the largest natural forest in the country. Biomass allocation was examined and biomass models were developed using diameter as independent variable for individual tree species and all species combined. The results showed that the largest biomass allocation of all species combined was on stems (57.1%), followed by coarse root (21.3%), branch (18.7%), and foliage (2.9%). The log-transformed model was statistically significant for all biomass components, although predicting power was higher for species-specific models than for all species combined, general biomass models, and higher for stems, roots, above-ground biomass, and total tree biomass than for branch and foliage biomass. These findings supplement the previous studies on this forest type by additional sample trees, species and locations, and support biomass research on forest carbon budget and dynamics by management activities such as thinning and harvesting in the northeastern part of China.
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spelling pubmed-57746812018-01-26 Allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, Northeastern China He, Huaijiang Zhang, Chunyu Zhao, Xiuhai Fousseni, Folega Wang, Jinsong Dai, Haijun Yang, Song Zuo, Qiang PLoS One Research Article Understanding forest carbon budget and dynamics for sustainable resource management and ecosystem functions requires quantification of above- and below-ground biomass at individual tree species and stand levels. In this study, a total of 122 trees (9–12 per species) were destructively sampled to determine above- and below-ground biomass of 12 tree species (Acer mandshuricum, Acer mono, Betula platyphylla, Carpinus cordata, Fraxinus mandshurica, Juglans mandshurica, Maackia amurensis, P. koraiensis, Populus ussuriensis, Quercus mongolica, Tilia amurensis and Ulmus japonica) in coniferous and broadleaved mixed forests of Northeastern China, an area of the largest natural forest in the country. Biomass allocation was examined and biomass models were developed using diameter as independent variable for individual tree species and all species combined. The results showed that the largest biomass allocation of all species combined was on stems (57.1%), followed by coarse root (21.3%), branch (18.7%), and foliage (2.9%). The log-transformed model was statistically significant for all biomass components, although predicting power was higher for species-specific models than for all species combined, general biomass models, and higher for stems, roots, above-ground biomass, and total tree biomass than for branch and foliage biomass. These findings supplement the previous studies on this forest type by additional sample trees, species and locations, and support biomass research on forest carbon budget and dynamics by management activities such as thinning and harvesting in the northeastern part of China. Public Library of Science 2018-01-19 /pmc/articles/PMC5774681/ /pubmed/29351291 http://dx.doi.org/10.1371/journal.pone.0186226 Text en © 2018 He et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
He, Huaijiang
Zhang, Chunyu
Zhao, Xiuhai
Fousseni, Folega
Wang, Jinsong
Dai, Haijun
Yang, Song
Zuo, Qiang
Allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, Northeastern China
title Allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, Northeastern China
title_full Allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, Northeastern China
title_fullStr Allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, Northeastern China
title_full_unstemmed Allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, Northeastern China
title_short Allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, Northeastern China
title_sort allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, northeastern china
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5774681/
https://www.ncbi.nlm.nih.gov/pubmed/29351291
http://dx.doi.org/10.1371/journal.pone.0186226
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