Improved allometric models to estimate the aboveground biomass of tropical trees

Abstract

Terrestrial carbon stock mapping is important for the successful implementation of climate change mitigation policies. Its accuracy depends on the availability of reliable allometric models to infer oven-dry aboveground biomass of trees from census data. The degree of uncertainty associated with previously published pantropical aboveground biomass allometries is large. We analyzed a global database of directly harvested trees at 58 sites, spanning a wide range of climatic conditions and vegetation types (4004 trees ≥ 5 cm trunk diameter). When trunk diameter, total tree height, and wood specific gravity were included in the aboveground biomass model as covariates, a single model was found to hold across tropical vegetation types, with no detectable effect of region or environmental factors. The mean percent bias and variance of this model was only slightly higher than that of locally fitted models. Wood specific gravity was an important predictor of aboveground biomass, especially when including a much broader range of vegetation types than previous studies. The generic tree diameter-height relationship depended linearly on a bioclimatic stress variable E, which compounds indices of temperature variability, precipitation variability, and drought intensity. For cases in which total tree height is unavailable for aboveground biomass estimation, a pantropical model incorporating wood density, trunk diameter, and the variable E outperformed previously published models without height. However, to minimize bias, the development of locally derived diameter-height relationships is advised whenever possible. Both new allometric models should contribute to improve the accuracy of biomass assessment protocols in tropical vegetation types, and to advancing our understanding of architectural and evolutionary constraints on woody plant development.

Tissue carbon concentration of 175 Mexican forest species

“…For instance, Martin et al (2015) suggest that variations in C concentration between tissues of the same species are less important than variations between species for modelling C dynamics in forest ecosystems. Improvement and validation of models for given ecosystems could be a viable solution, using wood density as an independent variable as suggested by some authors (Urquiza-Haas et al 2007, Chave et al 2014). Reliable C concentration estimations are crucial for determining the role of forests in the global C cycle (Bombelli et al 2009).…”

Biodiversity and Carbon Stock in the SODECAO Agroforestry System of Center Region of Cameroon: Case of Talba Locality

“…The allometric equation developed by Chave [38] takes into account the tree's diameter, the wood density and the environmental index "E", which includes seasonal temperature, drought intensity and the seasonality of precipitation are recommended but in the context of this study data about environmental index could not be recorded. It is for this reason that the allometric equation developed by Chave [39] was used for aboveground biomass estimation of cocoa shrubs and associated trees.…”

An overview of existing and promising technologies for national forest monitoring

“…Last, but not least, a significant part of the uncertainties associated with biomass or volume estimation is due to their calculation from allometric equations (Molto et al 2013;Chave et al 2014). Here, we show that some new technologies, such as terrestrial LiDAR or stereo-photogrammetry may be a promising way to improve significantly tree volume or biomass estimation without any destructive measurement.…”