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Fitting diameter distribution models to data from forest inventories with concentric plot design
Technical University of Madrid.
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
2017 (English)In: Forest Systems, ISSN 2171-5068, E-ISSN 2171-9845, Vol. 26, no 2, UNSP e01SArticle in journal (Refereed) Published
Abstract [en]

Aim: Several national forest inventories use a complex plot design based on multiple concentric subplots where smaller diameter trees are inventoried when lying in the smaller-radius subplots and ignored otherwise. Data from these plots are truncated with threshold (truncation) diameters varying according to the distance from the plot centre. In this paper we designed a maximum likelihood method to fit the Weibull diameter distribution to data from concentric plots. Material and methods: Our method (M1) was based on multiple truncated probability density functions to build the likelihood. In addition, we used an alternative method (M2) presented recently. We used methods M1 and M2 as well as two other reference methods to estimate the Weibull parameters in 40000 simulated plots. The spatial tree pattern of the simulated plots was generated using four models of spatial point patterns. Two error indices were used to assess the relative performance of M1 and M2 in estimating relevant stand-level variables. In addition, we estimated the Quadratic Mean plot Diameter (QMD) using Expansion Factors (EFs). Main results: Methods M1 and M2 produced comparable estimation errors in random and cluster tree spatial patterns. Method M2 produced biased parameter estimates in plots with inhomogeneous Poisson patterns. Estimation of QMD using EFs produced biased results in plots within inhomogeneous intensity Poisson patterns. Research highlights: We designed a new method to fit the Weibull distribution to forest inventory data from concentric plots that achieves high accuracy and precision in parameter estimates regardless of the within-plot spatial tree pattern.

Place, publisher, year, edition, pages
INIA , 2017. Vol. 26, no 2, UNSP e01S
Keyword [en]
expansion factors, forest growth and yield, National Forest Inventory, spatial point pattern, Weibull
National Category
Probability Theory and Statistics Forest Science
Identifiers
URN: urn:nbn:se:umu:diva-131311DOI: 10.5424/fs/2017262-10486ISI: 000413335800012OAI: oai:DiVA.org:umu-131311DiVA: diva2:1073514
Available from: 2017-02-10 Created: 2017-02-10 Last updated: 2017-11-15Bibliographically approved

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Sjöstedt de Luna, Sara
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CiteExportLink to record
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Citation style
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