On simplifying allometric analyses of forest biomass (original) (raw)
Related papers
Towards a functional and simplified allometry for estimating forest biomass
Forest Ecology and Management, 2006
Aboveground tree biomass (M) can be estimated using a power function in the form of M = aD b where a and b are the scaling coefficient and scaling exponent, respectively, and D the tree breast-height diameter. Both a and b are reported to vary with species, site and age. However West et al. [West, G.B., Brown, J.H., Enquist, B.J., 1999. A general model for the structure and allometry of plant vascular systems. Nature 400, 664-667] suggested that M should scale against D with a universal exponent (b = 8/3), because the scaling exponent would depend on an optimal tree architecture. Moreover a should be related with the wood density (r) [Enquist, B.J., West, G.B., Charnov, E.L., Brown, J.H., 1999. Allometric scaling of production and life-history variation in vascular plants. Nature 401, 907-911].
CAPITALIZING ON THE INFORMATION IN ALLOMETRIC EQUATION DATA BASES FOR FOREST BIOMASS ESTIMATION
In many countries, inventory data or biomass or volume equations are often incomplete or unavailable. Either taxonomic information is not accurate at the species level, or else no literature exist compiling particular allometric equations for some species. On the other hand, some species are represented by many alternative equations in the database. The vast quantity of information that allometric equation databases such as Globallometree can provide, can be capitalized to inform other, non-available species from the ranges and distributions of aboveground biomass estimates that other, better known species provide. In this study we provide an alternative method that takes those elements to estimate overall plot aboveground biomass from bootstrapping different equations belonging to a certain ecozone. Using a real inventory plot as an example, we prove that such estimates present error levels similar to those of generalized pantropical equations when a minimum set of rules for quality control has been added. This opens the possibility to establish more adequate quality control protocols that end up providing even better estimates than those published pantropical equations.
Agroforestry Systems, 2010
Fractal branching models can provide a non-destructive and generic tool for estimating tree shoot and root length and biomass, but field validation is rarely described in the literature. We compared estimates of above ground tree biomass for four indigenous tree used on farm in the Philippines based on the WanFBA model tree architecture with data from destructive sampling. Allometric equations for the four species varied in the constant (biomass at virtual stem diameter 1) and power of the scaling rule (b in Y = aD b), deviating from the value of 8/3 that is claimed to be universal. Allometric equations for aboveground biomass were 0.035 D 2.87 for Shorea contorta, 0.133 D 2.36 for Vitex parviflora, 0.063 D 2.54 for Pterocarpus indicus and 0.065 D 2.28 for Artocarpus heterophyllus, respectively. Allometric equations for branch biomass had a higher b factor than those for total biomass (except in Artocarpus); allometric equations for the leave ? twig fraction a lower b. The performance of the WanFBA model was significantly improved by introduction of a tapering factor ''s'' for decrease of branch diameter within a single link. All statistical tests performed on measured biomass versus biomass predicted from the WanFBA results confirm the viability of the WanFBA model as a non-destructive tool for predicting above-ground biomass equations for total biomass, branch biomass and the leaf ? twig fraction.
Forest Ecology and Management, 2001
Estimates of forest biomass are needed for tracking changes in C stocks, as well as for other purposes. A common method for estimating forest biomass is through use of allometric equations which relate the biomass of individual trees to easily obtainable non-destructive measurements, such as diameter. A common form is BaD b for biomass B, diameter D and parameters a and b. Field data collected in Sumatra and compared with previously published data show that the values of a and b vary between sites. This variation is likely to be the major source of uncertainty if biomass estimates are produced using equations that are not calibrated for individual sites. However, calibration by collection of B and D data for each site is unrealistic, requiring destructive measures. Methods of choosing values for a and b are, therefore, proposed that do not require destructive measurements. The parameter b can be estimated from the site-speci®c relationship between height (H) and diameter, HkD c as b2c. The parameter a can be estimated from the average wood density (r) at the site as arr, where r is expected to be relatively stable across sites. The allometric equation proposed is therefore BrrD 2c . #
Australian Journal of Botany, 2005
A fundamental tool in carbon accounting is tree-based allometry, whereby easily measured variables can be used to estimate aboveground biomass (AGB). To explore the potential of general allometry we combined raw datasets from 14 different woodland species, mainly eucalypts, from 11 sites across the Northern Territory, Queensland and New South Wales. Access to the raw data allowed two predictor variables, tree diameter (at 1.3-m height; D) and tree height (H), to be used singly or in various combinations to produce eight candidate models. Following natural log (ln) transformation, the data, consisting of 220 individual trees, were re-analysed in two steps: first as 20 species-site-specific AGB equations and, second, as a single general AGB equation. For each of the eight models, a comparison of the species-site-specific with the general equations was made with the Akaike information criterion (AIC). Further model evaluation was undertaken by a leave-one-out cross-validation technique. For each of the model forms, the species-site-specific equations performed better than the general equation. However, the best performing general equation, ln(AGB) = −2.0596 + 2.1561 ln(D) + 0.1362 (ln(H)) 2 , was only marginally inferior to the species-site-specific equations. For the best general equation, back-transformed predicted v. observed values (on a linear scale) were highly concordant, with a slope of 0.99. The only major deviation from this relationship was due to seven large, hollow trees (more than 35% loss of cross-sectional stem area at 1.3 m) at a single species-site combination. Our best-performing general model exhibited remarkable stability across species and sites, when compared with the species-site equations. We conclude that there is encouraging evidence that general predictive equations can be developed across sites and species for Australia's woodlands. This simplifies the conversion of long-term inventory measurements into AGB estimates and allows more resources to be focused on the extension of such inventories.
Modelling of Allometric Equations for Biomass Estimate in Deciduous Forest
FLORESTA, 2018
This paper aimed to test and adjust allometric models to estimate biomass in a Deciduous Forest. The data were obtained from seven 12 x 12 m plots, from which 91 trees were cut down. Only trees with diameter at breast height (DBH) greater than 5 cm were measured, and the fitting of the models was performed based on the DBH, total height (H) and total dry biomass (DAB) for each individual tree. The adjusted equations with no stratification presented adjusted determination coefficients (R 2 aj) ranging from 0.726 to 0.972 and standard errors in percentage (Syx%) from 33.5 to 119.6. The best adjusted model for nonstratified dataset was obtained by the Stepwise procedure, leading to the equation: DAB = β0 + β1.(DBH 3) + β2.H + β3.(DBH 3 .H), with 0.954 of R 2 aj and 44.0 of Syx%. For stratified dataset, only the diameter class higher than 15 cm presented acceptable results, with 0.968 of R 2 aj and 26.5 of Syx%. The current database has shown good quality measurements for fitting stochastic models to estimate the biomass of each tree.
Ecological Applications, 2016
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.
Allometric Equations for Aboveground Biomass Estimations of Four Dry Afromontane Tree Species
2020
Background: Tree species based developing allometric equations are important because they contain the largest proportion of total biomass and carbon stocks of forests. Studies on developing and validating the species-specific allometric models (SSAM) remain insufficient that may result to biomass estimation errors in the forests. The purpose of this study is to determine the wood density of four tree species and develop and validate the accuracy of allometry for biomass estimations. A total of 103 sample trees representing four species were harvested semi-destructively. The species specific allometric equations (SSAM) were developed using aboveground biomass (AGB in kg) as dependent variable, and three of the predictor's variables: diameter at beast height (DBH in cm), height (H in m) and wood density (WD in g cm-3). The relation between dependent and independent variables were tested using multiple correlations (R 2). The model selection and validation was based on statistical significance of model parameter estimates, Akaike Information Criterion (AIC), adjusted coefficient of determination (R 2), residual standard error (RSE) and mean relative error (MRE). Results: The results showed that the AGB correlated significantly with diameter at breast height (R 2 > 0.944, P < 0.001), and tree height (R 2 > 0.742, P <0.001). The species-specific allometric models, which include DBH, H and WD predicted AGB with high-model fit (R 2 > 93.6%, P < 0.001). These models for biomass estimations produced small MRE (1.50-3.40%) and AIC (-7.04-12.84) compared to a single predictor (MRE:-0.4-20.1%; AIC:-7.25-35.29). The SSAM also predicted AGB against predictors with high-model fit (R 2 > 93.6%, P < 0.001) and small MRE: 1.50-3.40% compared to existing general allometric models (MRE:-31.3-11.31%). Conclusions: The research confirmed that the inclusion of DBH, H, and WD in the SSAM predicted AGB with small bias than a single or two predictors. The wood density values of those studied species can be used as the references for biomass estimations using general allometric 2 equations. The study contributes to species-specific allometric models for understanding the total biomass estimation of species. Therefore, the application of species-specific allometric models should be considered in biomass estimations of forests.
Journal of Forestry Research, 2018
Allometric equations are important for quantifying biomass and carbon storage in terrestrial forest ecosystems. However, equations for dry deciduous woodland ecosystems, an important carbon sink in the lowland areas of Ethiopia have not as yet been developed. This study attempts to develop and evaluate species-specific allometric equations for predicting aboveground biomass (AGB) of dominant woody species based on data from destructive sampling for Combretum collinum, Combretum molle, Combretum harotomannianum, Terminalia laxiflora and mixed-species. Diameter at breast height ranged from 5 to 30 cm. Two empirical equations were developed using DBH (Eq. 1) and height (Eq. 2). Equation 2 gave better AGB estimations than Eq. 1. The inclusion of both DBH and H were the best estimate biometric variables for AGB. Further, the equations were evaluated and compared with common generic allometric equations. The result showed that our allometric equations are appropriate for estimating AGB. The development and application of empirical species-specific allometric equations is crucial to improve biomass and carbon stock estimation for dry woodland ecosystems.