Allometric Equations for Aboveground Biomass Estimations of Four Dry Afromontane Tree Species

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.

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Allometric equation for aboveground biomass estimation in moist Afromontane forest in Gesha and Sayilem district in Kaffa zone, southwestern Ethiopia

10.21203/rs.3.rs-54064/v1 ◽

2020 ◽

Author(s):

Admassu Merti ◽

Teshome Soromessa ◽

Tura Bareke

Keyword(s):

Wood Density ◽

Aboveground Biomass ◽

Allometric Equation ◽

Allometric Equations ◽

Individual Species ◽

Biomass Estimation ◽

Regression Equations ◽

Strongly Correlated ◽

Afromontane Forest ◽

Species Specific

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.

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ALLOMETRIC MODELS FOR ESTIMATING ABOVEGROUND BIOMASS AND BIOMASS ALLOCATION OF CAPIXINGUI TREES (Croton floribundus Spreng.) IN AN AGRISILVICULTURAL SYSTEM

Revista Árvore ◽

10.1590/0100-67622016000200010 ◽

2016 ◽

Vol 40 (2) ◽

pp. 279-288 ◽

Cited By ~ 1

Author(s):

Maria Luiza Franceschi Nicodemo ◽

Marcelo Dias Muller ◽

Antônio Aparecido Carpanezzi ◽

Vanderley Porfírio-da-Silva

Keyword(s):

Aboveground Biomass ◽

Stem Diameter ◽

Distribution Model ◽

Biomass Estimation ◽

Total Biomass ◽

Biomass Distribution ◽

Residual Distribution ◽

Allometric Models ◽

Crown Diameter ◽

Bole Biomass

ABSTRACT The objective of this study was to select allometric models to estimate total and pooled aboveground biomass of 4.5-year-old capixingui trees established in an agrisilvicultural system. Aboveground biomass distribution of capixingui was also evaluated. Single- (diameter at breast height [DBH] or crown diameter or stem diameter as the independent variable) and double-entry (DBH or crown diameter or stem diameter and total height as independent variables) models were studied. The estimated total biomass was 17.3 t.ha-1, corresponding to 86.6 kg per tree. All models showed a good fit to the data (R2ad > 0.85) for bole, branches, and total biomass. DBH-based models presented the best residual distribution. Model lnW = b0 + b1* lnDBH can be recommended for aboveground biomass estimation. Lower coefficients were obtained for leaves (R2ad > 82%). Biomass distribution followed the order: bole>branches>leaves. Bole biomass percentage decreased with increasing DBH of the trees, whereas branch biomass increased.

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The accuracy of species-specific allometric equations for estimating aboveground biomass in tropical moist montane forests: case study of Albizia grandibracteata and Trichilia dregeana

Carbon Balance and Management ◽

10.1186/s13021-019-0134-8 ◽

2019 ◽

Vol 14 (1) ◽

Cited By ~ 2

Author(s):

Damena Edae Daba ◽

Teshome Soromessa

Keyword(s):

Forest Ecosystem ◽

Aboveground Biomass ◽

Forest Type ◽

Model Performance ◽

Allometric Equation ◽

Allometric Equations ◽

Coefficient Of Determination ◽

Biomass Estimation ◽

Moist Forest ◽

Species Specific

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.

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Climate-based Allometric Biomass Equations for Five Major Canadian Timber Species

Canadian Journal of Forest Research ◽

10.1139/cjfr-2020-0485 ◽

2021 ◽

Author(s):

Kun Xu ◽

Jinghe Jiang ◽

Fangliang He

Keyword(s):

Aboveground Biomass ◽

Forest Biomass ◽

Allometric Equations ◽

Accurate Estimation ◽

Biomass Estimation ◽

Change Scenario ◽

Mean Annual Temperature ◽

Timber Species ◽

Trembling Aspen ◽

Allometric Models

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.

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Allometric equations for aboveground biomass estimation of Diospyros abyssinica (Hiern) F. White tree species

Ecosystem Health and Sustainability ◽

10.1080/20964129.2019.1591169 ◽

2019 ◽

Vol 5 (1) ◽

pp. 86-97 ◽

Cited By ~ 4

Author(s):

Damena Edae Daba ◽

Teshome Soromessa

Keyword(s):

Aboveground Biomass ◽

Tree Species ◽

Allometric Equations ◽

Biomass Estimation

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Allometric Models for Aboveground Biomass of Six Common Subtropical Shrubs and Small Trees

10.21203/rs.3.rs-573830/v1 ◽

2021 ◽

Author(s):

Cheng Huang ◽

Chun Feng ◽

Yuhua Ma ◽

Hua Liu ◽

Zhaocheng Wang ◽

...

Keyword(s):

Aboveground Biomass ◽

Tree Species ◽

Secondary Forests ◽

Optimal Model ◽

Allometric Model ◽

Small Tree ◽

Allometric Models ◽

Vegetative Biomass ◽

Species Specific ◽

Main Component

Abstract Background: The aboveground biomass (AGB) of shrubs and small trees is the main component for the productivity and carbon storage of understory vegetation in subtropical natural secondary forests. However, few allometric models exist for shrubs and small trees, even though they can accurately evaluate understory vegetative biomass. Methods: To estimate the ABG of six common shrub and small tree species, we utilized harvesting to sample 206 individuals, and developed species-specific and multi-species allometric models based on four predictors including height (H), stem diameter (D), crown area (Ca), and wood density (ρ). Results: As expected, these six shrub and small tree species possessed greater biomass in their stems in contrast to branches, with the lowest biomass in the leaves. Species-specific allometric models that employed D and the combined variables of D2H and ρDH as predictors, could accurately estimate the components and total AGB, with R2 values ranging from between 0.602 and 0.971. A multi-species shrub allometric model revealed that ρDH was the best predictor, with R2 values ranging from between 0.809 and 0.890. Conclusions: These results indicated that H and D were effective predictors for the models to estimate the AGB of the six shrub and small tree species, and the introduction of ρ improved their accuracy. The optimal model selected in this study could be applied to estimate the biomass of shrubs and small trees in the subtropical regions.

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Allometric Equation for Aboveground Biomass Estimation for Selected Trees Shrubs in Gesha - Sayilem Moist Afromontane Forest.

10.21203/rs.3.rs-210985/v1 ◽

2021 ◽

Author(s):

Admassu Addi Merti ◽

Teshome soromessa Soromessa ◽

Tura Bareke Kefle

Keyword(s):

Wood Density ◽

Standard Error ◽

Akaike Information Criterion ◽

Aboveground Biomass ◽

Information Criterion ◽

Allometric Equations ◽

Strongly Correlated ◽

Tree Biomass ◽

Afromontane Forest ◽

Species Specific

Abstract Background: Allometric equations which are regressions linking the biomass to some independent variables that 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 in size and biomass. 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) for estimating the aboveground biomass (AGB). Non-destructive sampling method was used for the measurement of tree biomass, accordingly the trees and shrubs whose Diameter at Breast Height (DBH) is ≥ 5 cm were sampled. For trees serial measurements of the height and diameter of trunk were done at 2 m intervals. For the determination of biomass of shrubs destructively sampled. Four branches were trimmed from tree and the trimmed branches were separated into leaves and wood and oven dried at 1050C and recorded to estimate the biomass of untrimmed small branches. Nested model was used and the best fit model was selected based on higher Adjusted R2, lower residual standard error and Akaike information criterion. 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 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.

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Forest Biomass Estimation Based on Forest Inventory Data in Middle and Last Scales

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.183-185.220 ◽

2011 ◽

Vol 183-185 ◽

pp. 220-224

Author(s):

Ming Ze Li ◽

Wen Yi Fan ◽

Ying Yu

Keyword(s):

Tree Species ◽

Forest Inventory ◽

Forest Biomass ◽

Biomass Estimation ◽

Total Biomass ◽

Inventory Data ◽

Biomass Equation ◽

Tree Species Composition ◽

Forest Inventory Data ◽

Ecosystem Carbon

The forest biomass (which is referred to the arbor aboveground biomass in this research) is one of the most primary factors to determine the forest ecosystem carbon storages. There are many kinds of estimating methods adapted to various scales. It is a suitable method to estimate forest biomass of the farm or the forestry bureau in middle and last scales. First each subcompartment forest biomass should be estimated, and then the farm or the forestry bureau forest biomass was estimated. In this research, based on maoershan farm region, first the single tree biomass equation of main tree species was established or collected. The biomass of each specie was calculated according to the materials of tally, such as height, diameter and so on in the forest inventory data. Secondly, each specie’s biomass and total biomass in subcompartment were calculated according to the tree species composition in forest management investigation data. Thus the forest biomass spatial distribution was obtained by taking subcompartment as a unit. And last the forest total biomass was estimated.

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