Allometric biomass models for the most abundant fruit tree species of Bangladesh: A Non-destructive approach

Saha, Chameli; Hossain, Mahmood; Nayan, Subir Nandi Sarker; Siddique, Mohammad Raqibul Hasan; Abdullah, S. M. Rubaiot; Islam, Shams Ul; Iqbal, Md. Zaheer; Akhter, Mariam

doi:10.1016/j.envc.2021.100047

Cited by 10 publications

(4 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this investigation, we analyzed three nonlinear regression equations with these easily measurable field variables (D and H) to build stem biomass models. Generally, adjusted R 2 value has been used for selecting best-fit models, but it can also give misleading results [33,34]. To overcome this possibility of misleading and to avoid taking any biased decision, we selected our best-fit models considering not only adjusted R 2 but also residual standard error (RSE) values.…”

Section: Resultsmentioning

confidence: 99%

Allometric Aboveground Biomass Models for Northern Delhi Ridge Forest

Tripathi,

Joshi

2023

AJRAF

View full text Add to dashboard Cite

Bio energy obtained through forest biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gases to the atmosphere. India, a developing nation is also in the process of building forest biomass models to study the potential of forests in short and long - term carbon mitigation. Earlier, traditional and destructive sampling were the popular methods for the aforesaid purpose. Recently, non - destructive methods have been adopted applying different allometric equations mostly developed outside India. Thus, there was a need to develop non- destructive allometric aboveground (AGB) models complementing the Indian climate. Also, there was a scarcity of domestic/local AGB models for arid, semi- arid, northern tropical thorn forest of India. The objectives of this study were to develop site-specific and mixed- species allometric models to predict AGB, at the Northern Delhi Ridge Forest (NDRF) using nonlinear mathematical functions. The model has a wide scope and can be applied to adjoining areas as well having similar climatic conditions. Three allometric combinations were tried to fit the aboveground biomass data obtained from the ridge forest. A three- parametric Richard’s model (with predictor variable x=D2H) was best fitted to AGB (R2adj= 0.9463) values for larger trees. Meanwhile, for juvenile plants, a three- parametric Richard function was best fitted (R2adj= 0.9733) when (x = DH) was used as a predictor variable. Cross- validation of model parameters exhibited statistical stability.

show abstract

Section: Resultsmentioning

confidence: 99%

Allometric Aboveground Biomass Models for Northern Delhi Ridge Forest

Tripathi,

Joshi

2023

AJRAF

View full text Add to dashboard Cite

show abstract

“…Biomass = e a X b CF (3) where X is the independent variable (e.g., D), a and b are empirically estimated scaling factors, and CF is the correction factor. Several studies have referred to the allometric models frequently used to estimate biomass [9,21,[26][27][28]. The best allometric models were evaluated and selected based on the primary criteria as outlined by Chave et al [4].…”

Section: Allometric Model Development and Statistical Analysismentioning

confidence: 99%

Development of Allometric Equations to Determine the Biomass of Plant Components and the Total Storage of Carbon Dioxide in Young Mediterranean Argan Trees

Oumasst,

Tiouidji,

Tabi

et al. 2024

Sustainability

View full text Add to dashboard Cite

Morocco’s argan trees, native to forests, are now cultivated in large orchards within the Argan Biosphere Reserve, transforming “Arganiculture”. These orchards are anticipated to bolster carbon storage, but their precise contribution to carbon storage remains unclear. This study introduces for the first time allometric equations for estimating biomass in different components of argan plants within orchards. A total of 89 plant individuals, aged 2 to 6 years, were collected. Their diameter and total height were measured. The biomass, carbon content, and biomass carbon stock of each component were determined. The best-fit allometric equation incorporates diameter, height, growing years, and root-to-shoot ratio to estimate total biomass (R2 = 0.95). The estimated total carbon biomass stock ranged from 0.01 to 0.82 t CO2 ha−1 for plants, at a density of 200 plants ha−1. Between 2021 and 2023, the average annual carbon sequestration was 0.20 t CO2 ha−1 year−1. This model offers valuable tools for use when species-specific equations during the establishment growing stage are unavailable, enhancing carbon sequestration quantification for more reliable results and informing climate change mitigation strategies. The allometric parameters serve as benchmarks for trees resembling the argan tree. The methodology could be adapted for other forest plants undergoing conversion to orchard cultivation.

show abstract

“…Allometric equations are important for their application in forest biomass and carbon assessments both locally and nationally. Generalized pan-tropical models of biomass estimation equations have been developed by several researchers (Kenzo et al 2020;Virgulino-Júnior et al 2020;Romero et al 2020;Zhou et al 2021;Latifah et al 2021;Saha et al 2021). The adjustments to these equations were obtained by measuring multiple tree species and several distinct locations and are intended to be applied to a wide variety of tropical forests.…”

Section: Introductionmentioning

confidence: 99%

Dynamics of Biomass Stocks in Areas of Secondary Forest Located in Western Amazon Between 2016 and 2020

MOURA¹,

SANQUETTA²,

SANQUETTA³

et al. 2022

AgricultForest

View full text Add to dashboard Cite

Secondary forests are portions of forest areas that were previously deforested. In general, secondary forests are characterized by fast-growing species, an alternative for reducing net carbon emissions and mitigating climate change; However, these forest environments are still poorly studied. In this context, this work aimed to adjust predictive models of biomass concerning the height and diameter of trees, analyzing temporally and quantitatively the biomass stocks in areas of secondary vegetation located in Rondônia, Western Amazon, aiming at quantification of aerial biomass in these ecosystems and discuss the implication of abundance of individuals in the estimates. To adjust the allometric equations it was necessary to measure all trees with a circumference at breast height above 15 cm in plots with 200m². After the measurements, a plot tree representing the average diametric variable was selected and slaughtered to calculate its biomass. The adjusted equations presented adjusted r² ranging from 0.49 to 0.57, root means square error (RMSE) from 247 to 296 kg, and residual standard error (Syx) from 49 to 53 kg. In 2016, the plots had an average of 41.47 t.ha -1 of biomass, and 2020 recorded 81.66 t.ha -1 . In this sense, we observed a total increase of 96.92% between 2016 and 2020. Through biomass estimates it was possible to observe that secondary forests are a potentially significant biomass sink due to the rapid accumulation rates of this component. Therefore, biomass stocks were increased over the years of this study, demonstrating the capacity for biomass growth in forests undergoing restoration.

show abstract

Allometric biomass models for the most abundant fruit tree species of Bangladesh: A Non-destructive approach

Cited by 10 publications

References 21 publications

Allometric Aboveground Biomass Models for Northern Delhi Ridge Forest

Allometric Aboveground Biomass Models for Northern Delhi Ridge Forest

Development of Allometric Equations to Determine the Biomass of Plant Components and the Total Storage of Carbon Dioxide in Young Mediterranean Argan Trees

Dynamics of Biomass Stocks in Areas of Secondary Forest Located in Western Amazon Between 2016 and 2020

Contact Info

Product

Resources

About