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Stand Diameter Distribution Modelling and Prediction Based on Richards Function

The objective of this study was to introduce application of the Richards equation on modelling and prediction of stand diameter distribution. The long-term repeated measurement data sets, consisted of 309 diameter frequency distributions from Chinese fir (Cunninghamia lanceolata) plantations in the...

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Autores principales: Duan, Ai-guo, Zhang, Jian-guo, Zhang, Xiong-qing, He, Cai-yun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3640060/
https://www.ncbi.nlm.nih.gov/pubmed/23638124
http://dx.doi.org/10.1371/journal.pone.0062605
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author Duan, Ai-guo
Zhang, Jian-guo
Zhang, Xiong-qing
He, Cai-yun
author_facet Duan, Ai-guo
Zhang, Jian-guo
Zhang, Xiong-qing
He, Cai-yun
author_sort Duan, Ai-guo
collection PubMed
description The objective of this study was to introduce application of the Richards equation on modelling and prediction of stand diameter distribution. The long-term repeated measurement data sets, consisted of 309 diameter frequency distributions from Chinese fir (Cunninghamia lanceolata) plantations in the southern China, were used. Also, 150 stands were used as fitting data, the other 159 stands were used for testing. Nonlinear regression method (NRM) or maximum likelihood estimates method (MLEM) were applied to estimate the parameters of models, and the parameter prediction method (PPM) and parameter recovery method (PRM) were used to predict the diameter distributions of unknown stands. Four main conclusions were obtained: (1) R distribution presented a more accurate simulation than three-parametric Weibull function; (2) the parameters p, q and r of R distribution proved to be its scale, location and shape parameters, and have a deep relationship with stand characteristics, which means the parameters of R distribution have good theoretical interpretation; (3) the ordinate of inflection point of R distribution has significant relativity with its skewness and kurtosis, and the fitted main distribution range for the cumulative diameter distribution of Chinese fir plantations was 0.4∼0.6; (4) the goodness-of-fit test showed diameter distributions of unknown stands can be well estimated by applying R distribution based on PRM or the combination of PPM and PRM under the condition that only quadratic mean DBH or plus stand age are known, and the non-rejection rates were near 80%, which are higher than the 72.33% non-rejection rate of three-parametric Weibull function based on the combination of PPM and PRM.
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spelling pubmed-36400602013-05-01 Stand Diameter Distribution Modelling and Prediction Based on Richards Function Duan, Ai-guo Zhang, Jian-guo Zhang, Xiong-qing He, Cai-yun PLoS One Research Article The objective of this study was to introduce application of the Richards equation on modelling and prediction of stand diameter distribution. The long-term repeated measurement data sets, consisted of 309 diameter frequency distributions from Chinese fir (Cunninghamia lanceolata) plantations in the southern China, were used. Also, 150 stands were used as fitting data, the other 159 stands were used for testing. Nonlinear regression method (NRM) or maximum likelihood estimates method (MLEM) were applied to estimate the parameters of models, and the parameter prediction method (PPM) and parameter recovery method (PRM) were used to predict the diameter distributions of unknown stands. Four main conclusions were obtained: (1) R distribution presented a more accurate simulation than three-parametric Weibull function; (2) the parameters p, q and r of R distribution proved to be its scale, location and shape parameters, and have a deep relationship with stand characteristics, which means the parameters of R distribution have good theoretical interpretation; (3) the ordinate of inflection point of R distribution has significant relativity with its skewness and kurtosis, and the fitted main distribution range for the cumulative diameter distribution of Chinese fir plantations was 0.4∼0.6; (4) the goodness-of-fit test showed diameter distributions of unknown stands can be well estimated by applying R distribution based on PRM or the combination of PPM and PRM under the condition that only quadratic mean DBH or plus stand age are known, and the non-rejection rates were near 80%, which are higher than the 72.33% non-rejection rate of three-parametric Weibull function based on the combination of PPM and PRM. Public Library of Science 2013-04-30 /pmc/articles/PMC3640060/ /pubmed/23638124 http://dx.doi.org/10.1371/journal.pone.0062605 Text en © 2013 Duan et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Duan, Ai-guo
Zhang, Jian-guo
Zhang, Xiong-qing
He, Cai-yun
Stand Diameter Distribution Modelling and Prediction Based on Richards Function
title Stand Diameter Distribution Modelling and Prediction Based on Richards Function
title_full Stand Diameter Distribution Modelling and Prediction Based on Richards Function
title_fullStr Stand Diameter Distribution Modelling and Prediction Based on Richards Function
title_full_unstemmed Stand Diameter Distribution Modelling and Prediction Based on Richards Function
title_short Stand Diameter Distribution Modelling and Prediction Based on Richards Function
title_sort stand diameter distribution modelling and prediction based on richards function
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3640060/
https://www.ncbi.nlm.nih.gov/pubmed/23638124
http://dx.doi.org/10.1371/journal.pone.0062605
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