Cargando…

Biomass allometric models for Larix rupprechtii based on Kosak’s taper curve equations and nonlinear seemingly unrelated regression

The diameter at breast height (DBH) is the most important independent variable in biomass allometry models based on metabolic scaling theory (MST) or geometric theory. However, the fixed position DBH can be misleading in its use of universal scaling laws and lead to some deviation for the biomass mo...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Dongzhi, Zhang, Zhidong, Zhang, Dongyan, Huang, Xuanrui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9868817/
https://www.ncbi.nlm.nih.gov/pubmed/36699831
http://dx.doi.org/10.3389/fpls.2022.1056837
_version_ 1784876628980006912
author Wang, Dongzhi
Zhang, Zhidong
Zhang, Dongyan
Huang, Xuanrui
author_facet Wang, Dongzhi
Zhang, Zhidong
Zhang, Dongyan
Huang, Xuanrui
author_sort Wang, Dongzhi
collection PubMed
description The diameter at breast height (DBH) is the most important independent variable in biomass allometry models based on metabolic scaling theory (MST) or geometric theory. However, the fixed position DBH can be misleading in its use of universal scaling laws and lead to some deviation for the biomass model. Therefore, it is still an urgent scientific problem to build a high-precision biomass model system. A dataset of 114 trees was destructively sampled to obtain dry biomass components, including stems, branches, and foliage, and taper measurements to explore the applicability of biomass components to allometric scaling laws and develop a new system of additive models with the diameter in relative height (DRH) for each component of a Larch (Larix principis-rupprechtii Mayr) plantation in northern China. The variable exponential taper equations were modelled using nonlinear regression. In addition, applying nonlinear regression and nonlinear seemingly unrelated regression (NSUR) enabled the development of biomass allometric models and the system of additive models with DRH for each component. The results showed that the Kozak’s (II) 2004 variable exponential taper equation could accurately describe the stem shape and diameter in any height of stem. When the diameters in relative height were D(0.2), D(0.5), and D(0.5) for branches, stems, and foliage, respectively, the allometric exponent of the stems and branches was the closest to the scaling relations predicted by the MST, and the allometric exponent of foliage was the most closely related to the scaling relations predicted by geometry theory. Compared with the nonlinear regression, the parameters of biomass components estimated by NSUR were lower, and it was close to the theoretical value and the most precise at forecasting. In the study of biomass process modelling, utilizing the DRH by a variable exponential taper equation can confirm the general biological significance more than the DBH of a fixed position.
format Online
Article
Text
id pubmed-9868817
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-98688172023-01-24 Biomass allometric models for Larix rupprechtii based on Kosak’s taper curve equations and nonlinear seemingly unrelated regression Wang, Dongzhi Zhang, Zhidong Zhang, Dongyan Huang, Xuanrui Front Plant Sci Plant Science The diameter at breast height (DBH) is the most important independent variable in biomass allometry models based on metabolic scaling theory (MST) or geometric theory. However, the fixed position DBH can be misleading in its use of universal scaling laws and lead to some deviation for the biomass model. Therefore, it is still an urgent scientific problem to build a high-precision biomass model system. A dataset of 114 trees was destructively sampled to obtain dry biomass components, including stems, branches, and foliage, and taper measurements to explore the applicability of biomass components to allometric scaling laws and develop a new system of additive models with the diameter in relative height (DRH) for each component of a Larch (Larix principis-rupprechtii Mayr) plantation in northern China. The variable exponential taper equations were modelled using nonlinear regression. In addition, applying nonlinear regression and nonlinear seemingly unrelated regression (NSUR) enabled the development of biomass allometric models and the system of additive models with DRH for each component. The results showed that the Kozak’s (II) 2004 variable exponential taper equation could accurately describe the stem shape and diameter in any height of stem. When the diameters in relative height were D(0.2), D(0.5), and D(0.5) for branches, stems, and foliage, respectively, the allometric exponent of the stems and branches was the closest to the scaling relations predicted by the MST, and the allometric exponent of foliage was the most closely related to the scaling relations predicted by geometry theory. Compared with the nonlinear regression, the parameters of biomass components estimated by NSUR were lower, and it was close to the theoretical value and the most precise at forecasting. In the study of biomass process modelling, utilizing the DRH by a variable exponential taper equation can confirm the general biological significance more than the DBH of a fixed position. Frontiers Media S.A. 2023-01-09 /pmc/articles/PMC9868817/ /pubmed/36699831 http://dx.doi.org/10.3389/fpls.2022.1056837 Text en Copyright © 2023 Wang, Zhang, Zhang and Huang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Wang, Dongzhi
Zhang, Zhidong
Zhang, Dongyan
Huang, Xuanrui
Biomass allometric models for Larix rupprechtii based on Kosak’s taper curve equations and nonlinear seemingly unrelated regression
title Biomass allometric models for Larix rupprechtii based on Kosak’s taper curve equations and nonlinear seemingly unrelated regression
title_full Biomass allometric models for Larix rupprechtii based on Kosak’s taper curve equations and nonlinear seemingly unrelated regression
title_fullStr Biomass allometric models for Larix rupprechtii based on Kosak’s taper curve equations and nonlinear seemingly unrelated regression
title_full_unstemmed Biomass allometric models for Larix rupprechtii based on Kosak’s taper curve equations and nonlinear seemingly unrelated regression
title_short Biomass allometric models for Larix rupprechtii based on Kosak’s taper curve equations and nonlinear seemingly unrelated regression
title_sort biomass allometric models for larix rupprechtii based on kosak’s taper curve equations and nonlinear seemingly unrelated regression
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9868817/
https://www.ncbi.nlm.nih.gov/pubmed/36699831
http://dx.doi.org/10.3389/fpls.2022.1056837
work_keys_str_mv AT wangdongzhi biomassallometricmodelsforlarixrupprechtiibasedonkosakstapercurveequationsandnonlinearseeminglyunrelatedregression
AT zhangzhidong biomassallometricmodelsforlarixrupprechtiibasedonkosakstapercurveequationsandnonlinearseeminglyunrelatedregression
AT zhangdongyan biomassallometricmodelsforlarixrupprechtiibasedonkosakstapercurveequationsandnonlinearseeminglyunrelatedregression
AT huangxuanrui biomassallometricmodelsforlarixrupprechtiibasedonkosakstapercurveequationsandnonlinearseeminglyunrelatedregression