Re-evaluation of individual diameter: height allometric models to improve biomass estimation of tropical trees

Alicia Ledo, Thomas Cornulier, Janine B Illian, Yoshiko Iida, Abdul Rahman Kassim, David F R P Burslem

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22 Citations (Scopus)
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Accurate estimation of tree biomass is necessary to provide realistic values of the carbon stored in the terrestrial biosphere. A recognized source of errors in tree aboveground biomass (AGB) estimation is introduced when individual tree height values (H) are not directly measured but estimated from diameter at breast height (DBH) using allometric equations. In this paper, we evaluate the performance of 12 alternative DBH : H equations and compare their effects on AGB estimation for three tropical forests that occur in contrasting climatic and altitudinal zones. We found that fitting a three-parameter Weibull function using data collected locally generated the lowest errors and bias in H estimation, and that equations fitted to these data were more accurate than equations with parameters derived from the literature. For computing AGB, the introduced error values differed notably among DBH : H allometric equations, and in most cases showed a clear bias that resulted in either over- or under-estimation of AGB. Fitting the three-parameter Weibull function minimized errors in AGB estimates in our study and we recommend its widespread adoption for carbon stock estimation. We conclude that many previous studies are likely to present biased estimates of AGB due to the method of H estimation.

Original languageEnglish
Pages (from-to)2376-2382
Number of pages7
JournalEcological Applications
Issue number8
Early online date19 Oct 2016
Publication statusPublished - Dec 2016

Bibliographical note

The first author was supported by the European Union under a IEF Marie-Curie Action. We thank Helene Muller-Landau and S. Joseph Wright for providing data on tree heights for some trees in Panama and for comments that helped to develop this study.


  • bias
  • biomass
  • error
  • inaccurarcy
  • modelling
  • tropical forest


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