Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/99187
Type of publication: Straipsnis Clarivate Analytics Web of Science ar/ir Scopus / Article in Clarivate Analytics Web of Science or / and Scopus (S1)
Field of Science: Miškotyra / Forestry (A004);Matematika / Mathematics (N001)
Author(s): Rupšys, Petras
Title: Modeling dynamics of structural components of forest stands based on trivariate stochastic differential equation
Is part of: Forests. Basel : MDPI AG, 2019, vol. 10, iss. 6
Extent: p. 1-24
Date: 2019
Note: art. no. 506
Keywords: Quadratic mean diameter;Mean height;Number of trees per hectare;Basal area per hectare;Stand volume per hectare;Trivariate diffusion process;Trivariate probability density function
Abstract: Research Highlights: Today’s approaches to modeling of forest stands are in most cases based on that the regression models and they are constructed as static sub-models describing individual stands variables. The disadvantages of this method; it is laborious because too many different equations need to be assessed and empirical choices of candidate equations make the results subjective; it does not relate to the stand variables dynamics against the age dimension (time); and does not consider the underlying covariance structure driving changes in the stand variables. In this study, the dynamical model defined by a fixed-and mixed effect parameters trivariate stochastic differential equation (SDE) is introduced and described how such a model can be used to model quadratic mean diameter, mean height, number of trees per hectare, self-thinning line, stand basal area, stand volume per hectare and much more. Background and Objectives: New developed marginal and conditional trivariate probability density functions, combining information generated from an age-dependent variance-covariance matrix of quadratic mean diameter, mean height and number of trees per hectare, improve stand growth prediction, and forecast (in forecast the future is completely unavailable and must only be estimated from historical patterns) accuracies. Materials and Methods: Fixed-and mixed effect parameters SDE models were harmonized to predict and forecast the dynamics of quadratic mean diameter, mean height, number of trees per hectare, basal area, stand volume per hectare, and their current and mean increments. The results and experience from applying the SDE concepts and techniques in an extensive whole stand growth and yield analysis are described using a Scots pine (Pinus sylvestris L.) experimental dataset in Lithuania
Internet: https://www.vdu.lt/cris/bitstream/20.500.12259/99187/2/ISSN1999-4907_V_10.N_6.AN_506.pdf
https://hdl.handle.net/20.500.12259/99187
https://doi.org/10.3390/f10060506
Affiliation(s): Vytauto Didžiojo universitetas
Appears in Collections:1. Straipsniai / Articles
Universiteto mokslo publikacijos / University Research Publications

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