Aboveground biomass allocation and additive allometric models of fifteen tree species in northeast China based on improved investigation methods

2022 ◽  
Vol 505 ◽  
pp. 119918
Author(s):  
Zhenzhao Xu ◽  
Wenxian Du ◽  
Guang Zhou ◽  
Lihou Qin ◽  
Shengwang Meng ◽  
...  
Keyword(s):  
Biomass Allocation ◽  
Aboveground Biomass ◽  
Tree Species ◽  
Northeast China ◽  
Allometric Models ◽  
Investigation Methods

scholarly journals Aboveground Biomass Allocation of Boreal Shrubs and Short-Stature Trees in Northwestern Canada

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 234
Author(s):  
Linda Flade ◽  
Christopher Hopkinson ◽  
Laura Chasmer
Keyword(s):  
Short Stature ◽  
Biomass Allocation ◽  
Aboveground Biomass ◽  
Leaf Biomass ◽  
Sectional Area ◽  
Plant Component ◽  
Cross Sectional ◽  
Allometric Models ◽  
Stem Biomass ◽  
Model Fits

In this follow-on study on aboveground biomass of shrubs and short-stature trees, we provide plant component aboveground biomass (herein ‘AGB’) as well as plant component AGB allometric models for five common boreal shrub and four common boreal short-stature tree genera/species. The analyzed plant components consist of stem, branch, and leaf organs. We found similar ratios of component biomass to total AGB for stems, branches, and leaves amongst shrubs and deciduous tree genera/species across the southern Northwest Territories, while the evergreen Picea genus differed in the biomass allocation to aboveground plant organs compared to the deciduous genera/species. Shrub component AGB allometric models were derived using the three-dimensional variable volume as predictor, determined as the sum of line-intercept cover, upper foliage width, and maximum height above ground. Tree component AGB was modeled using the cross-sectional area of the stem diameter as predictor variable, measured at 0.30 m along the stem length. For shrub component AGB, we achieved better model fits for stem biomass (60.33 g ≤ RMSE ≤ 163.59 g; 0.651 ≤ R2 ≤ 0.885) compared to leaf biomass (12.62 g ≤ RMSE ≤ 35.04 g; 0.380 ≤ R2 ≤ 0.735), as has been reported by others. For short-stature trees, leaf biomass predictions resulted in similar model fits (18.21 g ≤ RMSE ≤ 70.0 g; 0.702 ≤ R2 ≤ 0.882) compared to branch biomass (6.88 g ≤ RMSE ≤ 45.08 g; 0.736 ≤ R2 ≤ 0.923) and only slightly better model fits for stem biomass (30.87 g ≤ RMSE ≤ 11.72 g; 0.887 ≤ R2 ≤ 0.960), which suggests that leaf AGB of short-stature trees (<4.5 m) can be more accurately predicted using cross-sectional area as opposed to diameter at breast height for tall-stature trees. Our multi-species shrub and short-stature tree allometric models showed promising results for predicting plant component AGB, which can be utilized for remote sensing applications where plant functional types cannot always be distinguished. This study provides critical information on plant AGB allocation as well as component AGB modeling, required for understanding boreal AGB and aboveground carbon pools within the dynamic and rapidly changing Taiga Plains and Taiga Shield ecozones. In addition, the structural information and component AGB equations are important for integrating shrubs and short-stature tree AGB into carbon accounting strategies in order to improve our understanding of the rapidly changing boreal ecosystem function.

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

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.

Biomass Allocation Patterns and Allometric Models of Two Dominant Tree Species in Broad-leaved and Korean Pine Mixed Forest

2013 ◽  
Vol 19 (4) ◽  
pp. 718-722 ◽  
Author(s):  
Haijun DAI ◽  
Huaijiang HE ◽  
Xiuhai ZHAO ◽  
Chunyu ZHANG ◽  
Jinsong WANG ◽  
...  
Keyword(s):  
Biomass Allocation ◽  
Tree Species ◽  
Mixed Forest ◽  
Korean Pine ◽  
Allometric Models ◽  
Allocation Patterns

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

2020 ◽  
Author(s):  
Getaneh Gebeyehu ◽  
Teshome Soromessa ◽  
Tesfaye Bekele ◽  
Demel Teketay
Keyword(s):  
Wood Density ◽  
Aboveground Biomass ◽  
Tree Species ◽  
Model Fit ◽  
Allometric Equations ◽  
Biomass Estimation ◽  
Parameter Estimates ◽  
Total Biomass ◽  
Allometric Models ◽  
Species Specific

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.

scholarly journals Tree Species Diversity, Composition and Aboveground Biomass Across Dry Forest Land-Cover Types in Coastal Ecuador

2021 ◽  
Vol 14 ◽  
pp. 194008292199541
Author(s):  
Xavier Haro-Carrión ◽  
Bette Loiselle ◽  
Francis E. Putz
Keyword(s):  
Species Diversity ◽  
Land Cover ◽  
Community Composition ◽  
Aboveground Biomass ◽  
Tree Species ◽  
Dry Forest ◽  
Stem Density ◽  
Tree Species Diversity ◽  
Land Cover Types ◽  
Schizolobium Parahyba

Tropical dry forests (TDF) are highly threatened ecosystems that are often fragmented due to land-cover change. Using plot inventories, we analyzed tree species diversity, community composition and aboveground biomass patterns across mature (MF) and secondary forests of about 25 years since cattle ranching ceased (SF), 10–20-year-old plantations (PL), and pastures in a TDF landscape in Ecuador. Tree diversity was highest in MF followed by SF, pastures and PL, but many endemic and endangered species occurred in both MF and SF, which demonstrates the importance of SF for species conservation. Stem density was higher in PL, followed by SF, MF and pastures. Community composition differed between MF and SF due to the presence of different specialist species. Some SF specialists also occurred in pastures, and all species found in pastures were also recorded in SF indicating a resemblance between these two land-cover types even after 25 years of succession. Aboveground biomass was highest in MF, but SF and Tectona grandis PL exhibited similar numbers followed by Schizolobium parahyba PL, Ochroma pyramidale PL and pastures. These findings indicate that although species-poor, some PL equal or surpass SF in aboveground biomass, which highlights the critical importance of incorporating biodiversity, among other ecosystem services, to carbon sequestration initiatives. This research contributes to understanding biodiversity conservation across a mosaic of land-cover types in a TDF landscape.

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