Allometric equations for aboveground biomass estimation by size class for Pinus brutia Ten. trees growing in North and South Aegean Islands, Greece

2010 ◽  
Vol 130 (2) ◽  
pp. 145-160 ◽  
Author(s):  
Dimitris Zianis ◽  
Gavriil Xanthopoulos ◽  
Kostas Kalabokidis ◽  
George Kazakis ◽  
Dany Ghosn ◽  
...  
2013 ◽  
Vol 71 (1) ◽  
pp. 101-112 ◽  
Author(s):  
Sergio de-Miguel ◽  
Timo Pukkala ◽  
Nabil Assaf ◽  
Zuheir Shater

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6782 ◽  
Author(s):  
Jose Navar ◽  
Felipa de Jesus Rodriguez-Flores ◽  
Julio Rios-Saucedo

Mesquite trees are the preferred dendroenergy sources in arid and semi-arid forests. In spite of their relative importance, regional aboveground biomass (AGB) equations for mesquite trees are scarce in the scientific literature. For that reason, the aims of this study were to: (a) harvest trees and develop regional biomass equations; (b) contrast measured data with equations developed previously; and (c) test the applicability of the fitted equation for mesquite trees in the arid and semi-arid forests of the Americas. We harvested 206 new mesquite trees from arid and semi-arid forests in northern Mexico (Coahuila, Nuevo Leon, and Tamaulipas) in addition to using two other previously compiled data sets from Mexico (N = 304) to develop a regional equation. To test the validity of this equation, for biomass equations reported for the rest of the country, as well as for North and South American mesquite trees, we contrasted AGB measurements with predictions of fitted equations. Statistical analysis revealed the need for a single, regional, semi-empirical equation as together the three data sets represented the variability of the aboveground biomass of mesquite trees across northern Mexico, as well as mesquite trees in America’s arid and semiarid regions. Due to the large quantity of mesquite trees harvested for sampling and their variability, the regional biomass equation developed encompasses all other North and South American equations, and is representative of mesquite trees throughout the arid and semi-arid forests of the Americas.


2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Damena Edae Daba ◽  
Teshome Soromessa

Abstract Background Application of allometric equations for quantifying forests aboveground biomass is a crucial step related to efforts of climate change mitigation. Generalized allometric equations have been applied for estimating biomass and carbon storage of forests. However, adopting a generalized allometric equation to estimate the biomass of different forests generates uncertainty due to environmental variation. Therefore, formulating species-specific allometric equations is important to accurately quantify the biomass. Montane moist forest ecosystem comprises high forest type which is mainly found in the southwestern part of Ethiopia. Yayu Coffee Forest Biosphere Reserve is categorized into Afromontane Rainforest vegetation types in this ecosystem. This study was aimed to formulate species-specific allometric equations for Albizia grandibracteata Tuab. and Trichilia dregeana Sond. using the semi-destructive method. Results Allometric equations in form of power models were developed for each tree species by evaluating the statistical relationships of total aboveground biomass (TAGB) and dendrometric variables. TAGB was regressed against diameter at breast height (D), total height (H), and wood density (ρ) individually and in a combination. The allometric equations were selected based on model performance statistics. Equations with the higher coefficient of determination (adj.R2), lower residual standard error (RSE), and low Akaike information criterion (AIC) values were found best fitted. Relationships between TAGB and predictive variables were found statistically significant (p ≤ 0.001) for all selected equations. Higher bias was reported related to the application of pan-tropical or generalized allometric equations. Conclusions Formulating species-specific allometric equations is found important for accurate tree biomass estimation and quantifying the carbon stock. The developed biomass regression models can be applied as a species-specific equation to the montane moist forest ecosystem of southwestern Ethiopia.


Author(s):  
Kun Xu ◽  
Jinghe Jiang ◽  
Fangliang He

Accurate estimation of forest biomass is essential to quantify the role forests play at balancing terrestrial carbon. Allometric equations based on tree size have been used for this purpose worldwide. There is little quantitative understanding on how environmental variation may affect tree allometries. Even less known is how to incorporate environmental factors into such equations to improve estimation. Here we tested the effects of climate on tree allometric equations and proposed to model forest biomass by explicitly incorporating climatic factors. Among the five major Canadian timber species tested, the incorporation of climate was not found to improve the allometric models. For trembling aspen and tamarack, the residuals of their conventional allometric models were found strongly related to frost-free period and mean annual temperature, respectively. The predictions of the two best climate-based models were significantly improved, which indicate that trembling aspen and tamarack store more aboveground biomass when growing in warmer than in colder regions. We showed that, under the RCP4.5 modest climate change scenario, there would be a 10% underestimation of aboveground biomass for these two species if the conventional non-climate models would still be in use in 2030. This study suggests the necessity to proactively develop climate-based allometric equations for more accurate and reliable forest biomass estimation.


2020 ◽  
Author(s):  
Admassu Merti ◽  
Teshome Soromessa ◽  
Tura Bareke

Abstract Background: Allometric equations which are regressions linking the biomass to some independent variables are used to estimate tree components from the forest. The generic equation developed by many authors may not adequately reveal the tree biomass in a specific region in tropics including in Ethiopia. Therefore, the use of species specific allometric equations is important to achieve higher levels of accuracy because trees of different species may differ. The objective of the study was to develop species-specific allometric equations for Apodytes dimidiata, Ilex mitis, Sapium ellipticum and shrubs (Galiniera saxifraga and Vernonia auriculifera) using semi-destructive method for estimating the aboveground biomass (AGB). For purpose of sampling trees, individual species were categorized into trees whose Diameter at breast height (DBH) is ≥ 5 cm.Results: All the necessary biomass calculations were done, and biomass equations were developed for each species. The regression equations relate AGB with DBH, height (H), and density (ρ) were computed and the models were tested for accuracy based on observed data. The best model was selected based higher adj R2 and lower residual standard error and Akaike information criterion than rejected models. The relations for all selected models are significant (p<0.000), which showed strong correlation AGB with selected dendrometric variables. Accordingly, the AGB was strongly correlated with DBH and was not significantly correlated with wood density and height individually in Ilex mitis. In combination, AGB was strongly correlated with DBH, height; DBH and wood density; are better for carbon assessment than general equations.Conclusions: The specific allometeric equation developed for the Gesha-Sayilem Afromontane Forest which can be used in similar moist forests in Ethiopia for the implementation of Reduced Emission from Deforestation and Degradation (REDD+) activities to benefit the local communities from carbon trade.


2020 ◽  
Author(s):  
Getaneh Gebeyehu ◽  
Teshome Soromessa ◽  
Tesfaye Bekele ◽  
Demel Teketay

Abstract 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 (R2). The model selection and validation was based on statistical significance of model parameter estimates, Akaike Information Criterion (AIC), adjusted coefficient of determination (R2), residual standard error (RSE) and mean relative error (MRE). Results: The results showed that the AGB correlated significantly with diameter at breast height (R2 > 0.944, P < 0.001), and tree height (R2 > 0.742, P <0.001). The species-specific allometric models, which include DBH, H and WD predicted AGB with high-model fit (R2 > 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 (R2 > 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 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.


2016 ◽  
Vol 3 (1) ◽  
Author(s):  
Solichin Manuri ◽  
Cris Brack ◽  
Fatmi Noor’an ◽  
Teddy Rusolono ◽  
Shema Mukti Anggraini ◽  
...  

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