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Stand diameter distribution modelling and prediction based on Richards function

Duan, Ai-guo ; Zhang, Jian-guo ; Zhang, Xiong-qing ; He, Cai-yun Rapallo, Fabio

PloS one, 2013-04, Vol.8 (4), p.e62605-e62605 [Periódico revisado por pares]

United States: Public Library of Science

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  • Título:
    Stand diameter distribution modelling and prediction based on Richards function
  • Autor: Duan, Ai-guo ; Zhang, Jian-guo ; Zhang, Xiong-qing ; He, Cai-yun
  • Rapallo, Fabio
  • Assuntos: Agriculture ; Algorithms ; Biology ; China ; Computer Science ; Computer Simulation ; Cunninghamia - anatomy & histology ; Cunninghamia - physiology ; Cunninghamia lanceolata ; Data processing ; Forestry economics ; Goodness of fit ; Kurtosis ; Laboratories ; Mathematics ; Maximum likelihood estimates ; Maximum likelihood method ; Modelling ; Models, Biological ; Models, Statistical ; Parameter estimation ; Plantations ; Rejection rate ; Relativity ; Skewness ; Studies ; Test procedures ; Trees ; Trees - anatomy & histology ; Trees - physiology
  • É parte de: PloS one, 2013-04, Vol.8 (4), p.e62605-e62605
  • Notas: ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
    content type line 23
    Competing Interests: The authors have declared that no competing interests exist.
    Conceived and designed the experiments: A-GD J-GZ. Performed the experiments: A-GD. Analyzed the data: A-GD. Contributed reagents/materials/analysis tools: A-GD X-QZ C-YH. Wrote the paper: A-GD.
  • Descrição: 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.
  • Editor: United States: Public Library of Science
  • Idioma: Inglês
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