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New Insights into Tree Height Distribution Based on Mixed Effects Univariate Diffusion Processes

The aim of this paper is twofold: to introduce the mathematics of stochastic differential equations (SDEs) for forest dynamics modeling and to describe how such a model can be applied to aid our understanding of tree height distribution corresponding to a given diameter using the large dataset provi...

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Autor principal: Rupšys, Petras
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5176318/
https://www.ncbi.nlm.nih.gov/pubmed/28002500
http://dx.doi.org/10.1371/journal.pone.0168507
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author Rupšys, Petras
author_facet Rupšys, Petras
author_sort Rupšys, Petras
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description The aim of this paper is twofold: to introduce the mathematics of stochastic differential equations (SDEs) for forest dynamics modeling and to describe how such a model can be applied to aid our understanding of tree height distribution corresponding to a given diameter using the large dataset provided by the Lithuanian National Forest Inventory (LNFI). Tree height-diameter dynamics was examined with Ornstein-Uhlenbeck family mixed effects SDEs. Dynamics of a tree height, volume and their coefficients of variation, quantile regression curves of the tree height, and height-diameter ratio were demonstrated using newly developed tree height distributions for a given diameter. The parameters were estimated by considering a discrete sample of the diameter and height and by using an approximated maximum likelihood procedure. All models were evaluated using a validation dataset. The dataset provided by the LNFI (2006–2010) of Scots pine trees is used in this study to estimate parameters and validate our modeling technique. The verification indicated that the newly developed models are able to accurately capture the behavior of tree height distribution corresponding to a given diameter. All of the results were implemented in a MAPLE symbolic algebra system.
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spelling pubmed-51763182017-01-04 New Insights into Tree Height Distribution Based on Mixed Effects Univariate Diffusion Processes Rupšys, Petras PLoS One Research Article The aim of this paper is twofold: to introduce the mathematics of stochastic differential equations (SDEs) for forest dynamics modeling and to describe how such a model can be applied to aid our understanding of tree height distribution corresponding to a given diameter using the large dataset provided by the Lithuanian National Forest Inventory (LNFI). Tree height-diameter dynamics was examined with Ornstein-Uhlenbeck family mixed effects SDEs. Dynamics of a tree height, volume and their coefficients of variation, quantile regression curves of the tree height, and height-diameter ratio were demonstrated using newly developed tree height distributions for a given diameter. The parameters were estimated by considering a discrete sample of the diameter and height and by using an approximated maximum likelihood procedure. All models were evaluated using a validation dataset. The dataset provided by the LNFI (2006–2010) of Scots pine trees is used in this study to estimate parameters and validate our modeling technique. The verification indicated that the newly developed models are able to accurately capture the behavior of tree height distribution corresponding to a given diameter. All of the results were implemented in a MAPLE symbolic algebra system. Public Library of Science 2016-12-21 /pmc/articles/PMC5176318/ /pubmed/28002500 http://dx.doi.org/10.1371/journal.pone.0168507 Text en © 2016 Petras Rupšys 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
Rupšys, Petras
New Insights into Tree Height Distribution Based on Mixed Effects Univariate Diffusion Processes
title New Insights into Tree Height Distribution Based on Mixed Effects Univariate Diffusion Processes
title_full New Insights into Tree Height Distribution Based on Mixed Effects Univariate Diffusion Processes
title_fullStr New Insights into Tree Height Distribution Based on Mixed Effects Univariate Diffusion Processes
title_full_unstemmed New Insights into Tree Height Distribution Based on Mixed Effects Univariate Diffusion Processes
title_short New Insights into Tree Height Distribution Based on Mixed Effects Univariate Diffusion Processes
title_sort new insights into tree height distribution based on mixed effects univariate diffusion processes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5176318/
https://www.ncbi.nlm.nih.gov/pubmed/28002500
http://dx.doi.org/10.1371/journal.pone.0168507
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