4.0 Article

Allometric models for height and aboveground biomass of dominant tree species in South African Mistbelt forests

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TAYLOR & FRANCIS LTD
DOI: 10.2989/20702620.2016.1225187

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biomass density; correction factor; diameter-height relationship; minimal destructive sampling; Mistbelt forests

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  1. National Research Foundation of South Africa

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Novel species-specific equations for the estimation of height and aboveground biomass were established for four dominant tree species (Syzygium gerrardii Burtt Davy, Combretum kraussii Hochst., Trichilia dregeana Sond. and Croton sylvaticus Hochst.), in the Northern Mistbelt Forests of South Africa. A non-destructive sampling methodology was applied, which was based on measuring standing trees, selecting smaller branches and taking core samples. The species-specific aboveground biomass equations were fitted using predictor variables such as diameter at breast height (DBH) and total height (H). The relative error of estimation was used to examine the accuracy of a pantropical biomass equation versus our established specific model. Biomass values were afterwards up-scaled from tree to stand level for each species, based on the selected models and the forest inventory data. As expected, the DBH-height relationship varied among studied species. The incorporation of both DBH and H in the biomass models significantly improved their precision. A model with DBH2 x H as a single variable was suitable for three out of the four studied species, with more than 98% of explained variance. An existing pantropical biomass equation for moist forests showed larger relative error of estimation, especially in the upper range of tree diameter. The estimated aboveground biomass density varied significantly among studied species, with the highest values recorded for S. gerrardii (87.7 +/- 15.4 Mg ha(-1)), followed by T. dregeana (29.4 +/- 14.7 Mg ha(-1)), C. sylvaticus (24.3 +/- 11.5 Mg ha(-1)) and C. kraussii (20.1 +/- 6.7 Mg ha(-1)). It is also found that species-specific production of biomass at the tree level is not always sufficient to reflect the stand-level biomass density. The results from this study contribute to accurately predict aboveground biomass, thereby improving the reliability of the estimates of forest biomass and carbon balance.

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