Stand diameter distribution modelling and prediction based on Richards function

PLoS One. 2013 Apr 30;8(4):e62605. doi: 10.1371/journal.pone.0062605. Print 2013.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • China
  • Computer Simulation
  • Cunninghamia / anatomy & histology*
  • Cunninghamia / physiology
  • Models, Biological
  • Models, Statistical
  • Trees / anatomy & histology*
  • Trees / physiology

Grants and funding

The authors acknowledge the financial assistance provided by the national scientific and technological task for the 12th five-year plan in China (No. 2012BAD01B02, 2011AA100203). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.