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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Main Author: Petras Rupšys
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5176318?pdf=render
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spelling doaj-2bdd616b6d6949ca8f11c8650d383cbd2020-11-25T02:05:17ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-011112e016850710.1371/journal.pone.0168507New Insights into Tree Height Distribution Based on Mixed Effects Univariate Diffusion Processes.Petras RupšysThe 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.http://europepmc.org/articles/PMC5176318?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Petras Rupšys
spellingShingle Petras Rupšys
New Insights into Tree Height Distribution Based on Mixed Effects Univariate Diffusion Processes.
PLoS ONE
author_facet Petras Rupšys
author_sort Petras Rupšys
title 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_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_sort new insights into tree height distribution based on mixed effects univariate diffusion processes.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2016-01-01
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.
url http://europepmc.org/articles/PMC5176318?pdf=render
work_keys_str_mv AT petrasrupsys newinsightsintotreeheightdistributionbasedonmixedeffectsunivariatediffusionprocesses
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