alexa Development of Biomass Expansion Factor (BEF) and Estimation of Carbon Pool in Ailanthus excelsa Roxb Plantation | Open Access Journals
ISSN: 2157-7048
Journal of Chemical Engineering & Process Technology
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Development of Biomass Expansion Factor (BEF) and Estimation of Carbon Pool in Ailanthus excelsa Roxb Plantation

Nishita Giri, Rajdeo Kumar*, Laxmi Rawat and Pramod Kumar
Forest Ecology and Environment Division, Forest Research Institute, Dehradun, India
Corresponding Author : Rajdeo Kumar
Forest Ecology and Environment Division
Forest Research Institute
Dehradun-248006 (Uttarakhand), India
Tel: +91-8591473231
E-mail: [email protected]
Received July 25, 2014; Accepted September 22, 2014; Published September 25, 2014
Citation: Giri N, Kumar R, Rawat L, Kumar P (2014) Development of Biomass Expansion Factor (BEF) and Estimation of Carbon Pool in Ailanthus excelsa Roxb Plantation. J Chem Eng Process Technol 5:210. doi:10.4172/2157-7048.1000210
Copyright: © 2014 Giri N, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Abstract

The article presents biomass and carbon stock for Ailanthus excelsa plantation in Dehradun Forest Division, Uttarakhand, India. Destructive sampling was used to calculate the biomass and carbon content of A. excelsa and Biomass Expansion Factor (BEF) was also developed for the species. The total biomass of A. excelsa was calculated as 126.07 t ha-1 with above ground biomass (AGB) 102.96 t ha-1 and below ground biomass (BGB) 23.11 t ha-1. Carbon content in A. excels was 58.52 t ha-1 i.e. 48.3 t ha-1 in AGB and 10.22 t ha-1 in BGB and soil organic carbon (SOC) was 46.27 t ha-1. Total carbon content (t ha-1) in different tree components were in the order: 40.27 (bole)>10.22 (root)>5.36 (branch)>1.61 (bark)>0.73 (leaf)>0.33 (twig). BEF value calculated for the species was 1.23.

Keywords
Biomass; Carbon stock; Litter; Ailanthus excelsa roxb; Plantation ecosystem; Above ground biomass and below ground biomass
Introduction
Forests play an important role in global carbon cycling, since they are large pools of carbon as well as potential carbon sinks and sources to the atmosphere. Accurate estimation of forest biomass is required for greenhouse gas inventories and terrestrial carbon accounting. The needs for reporting carbon stocks and stock changes for the Kyoto Protocol have placed additional demands for accurate surveying methods that are verifiable, specific in time and space, and that cover large areas at acceptable cost [1-4]. Terrestrial ecosystems contain substantial carbon pools whose dynamics may impact and interact with atmospheric CO2 concentrations [5,6], potentially influencing climatic conditions [7]. A.excelsa is used for agroforestry and avenue plantation and having many medicinal uses as the leaves are used for the preparation of lotions for scabies. The bark is bitter, astringent, anthelmintic and it is used in diseases like dysentery, bronchitis, asthma, dyspepsia and ear ache. The bark is also utilized in indigenous veterinary practices [8].
As young forests develop, atmospheric CO2 is locked up into wood during growth and stored in litter layers and the soil. However, the carbon (C) sequestration potential of a forest ecosystem depends on initial soil organic carbon (SOC) content, stand growth rates, the site’s biological carrying capacity, stand age, and product utilization. In particular, C sequestration and storage may be increased significantly if forests are harvested and trees are converted into wood products [9]. AGB has been given the highest importance in carbon inventory and in most mitigation projects and is the most important pool for afforestation and reforestation CDM projects under the Kyoto Protocol as well as any inventory or mitigation project related to forest lands, agroforestry and shelterbelts in croplands, while in estimating total biomass, BGB showed an important carbon pool for many vegetation types and land-use systems and accounts for about 20% [10] to 26% [11] of the total biomass. Biomass expansion factors (BEFs) applicable to stand level inventory data can be developed and tested with the help of representative volume and biomass equations [12].
The article presents stand level or ecosystem level estimates of biomass by component. This is the first report of carbon stock / carbon pool estimation in AGB, BGB of A. excelsa species, as well as soil organic carbon (SOC) at ecosystem level in India along with development of BEF.
Material and Methods
Study area
The study was conducted in a 28 year old A.excelsa plantation in Jakhan block, Barkot Range of Dehradun Forest Division, Uttarakhand, India (Map 1), nearly 25 km east of Haridwar and 30 km South east side of Dehradun city. The area lies in the subtropical region at an altitude of 449 m mean sea level (msl) with 3004’37.2’’N latitude and 78°12’11.1’’E longitudes. The maximum, minimum and mean temperatures of the area (1980-2010) were 28.11°C, 13.52°C and 20.32°C, respectively. The mean annual rainfall during this period was 1901.03 mm when averaging monthly and approximately 80% of the rainfall occurred during the South-west monsoon period (June to September) (Figure 1).
Soil analysis
Texture: It is the proportion of particle size distribution (soil texture) into classified grades expressed as percentage of sand, silt and clay. After air drying of samples, big stones were removed and the soil was passed through 2 mm sieve. Part of the soil samples having particle size less than 2 mm were subjected for texture analysis by Hydrometric method [13] and percentage of different fractions namely: sand, silt and clay was estimated in each sample and textural class was determined using the Triangular diagram by U.S.D.A [13].
Soil moisture: Soil moisture percentage (%) was measured by means of moisture meter.
Soil bulk density: A metal core cylinder of known weight and volume was used to determine the soil bulk density [14]. Soil bulk density was determined by the following expression:
Bulk density (g cm3) = (W1-W2)/V
where,
W1=weight of cylinder + weight of soil
W2=weight of empty cylinder
V=volume of cylinder
Organic Carbon (OC): The organic carbon was determined as per by Walkey and Black (1934) [15] method.
Biomass estimation of Ailanthus excelsa
The stratified tree technique method of Art and Marks (1971) [16] was used to harvest the sample trees. Temporary sample plots (30 m × 30 m) were laid out in the plantation and the diameter at breast height (DBH at 1.3 m) of all the standing trees were recorded within the sample plots. The DBH range was divided into five different diameter classes i.e, 10 to 20 cm, 20 to 30 cm, 30 to 40 cm, 40 to 50 cm and 50 to 60 cm from which 2 trees were harvested from 10 to 20 cm diameter class, 3 trees from 20 to 30 cm, 2 trees from 30 to 40 cm, 1 from 40 to 50 cm and 1 from 50 to 60 cm and in this way 9 representative sample trees were selected for the study.
The tree components (leaves, twigs, branches, bark, bole and roots) were separated immediately after felling and their fresh weights recorded. Samples of all tree components (100 g of each component) were selected for oven dry weight estimation and chemical analysis for C content. The bole of each sample trees was cut into 2 m long sections (billets) for convenience of weighing.
Calculation of biomass by using stand volume and Biomass Expansion Factor (BEF)
Biomass could be calculated from the stand volume per hectare by first estimating the biomass of the inventoried volume and then expanding this value to take into account the biomass of the other aboveground components, using a biomass expansion factor (BEF) defined as “the ratio of aboveground oven-dry biomass of trees to ovendry biomass of inventoried volume” [17].
BEF was calculated as:
where, BEF = biomass expansion factor (dimensionless);
Wcrown = tree crown dry weight (kg), composed of foliage, thick and thin branches;
Wbole = tree bole dry weight (kg); and
Waboveground = Wcrown + Wbole (kg)
When BGB is considered in the clean development mechanism (CDM) project Root-to-shoot ratio (R) also should be taken into account and multiplied with the AGB to obtain the total BGB [18,19]. Calculation of R involves simply dividing the root biomass by the corresponding aboveground biomass as follows:
where, R=root-to-shoot ratio (dimensionless); and
Wroot=tree root dry weight (kg)
Biomass of the inventoried volume was calculated by multiplying the volume per hectare by the wood density defined as the oven-dry mass per unit of green volume and then multiplied by the BEF in order to include leaves, twigs, and branches, commonly not measured by the forest inventories. Wood density was 356 kg m-3 for A. excelsa [20].
Results and Discussion
Physical attributes of soil
Soil texture was observed to be sandy loam in nature, soil moisture was higher (8.848%) in the deepest layer that is, 60 to 90 cm depth, lower (5.990%) in uppermost layer that is, 0 to 30 cm depth. The trend of bulk density in soil depths was in the order 60 to 90 cm > 30 to 60 cm > 0 to 30 cm (Table 1).
Biomass of A. excelsa species
The variation in diameter (15.5-55.09 cm) and height (8.85-20.2 m) of the trees had direct effect on their biomass and the total biomass ranged from 75.04 kg tree-1 to 759.56 kg tree-1. The variations in other tree components were: bole 40.21 kg to 551.48 kg, leaf 0.32 kg to 12.71 kg, twig 0.43 kg to 5.10 kg, branch 6.71 kg to 52.63 kg, barks 5.84 kg to 18.28 kg and root 21.27 kg to 119.36 kg among all sample trees. The total biomass of A. excelsa trees was estimated as 126.07 t ha-1, of which the AGB comprised 102.96 t ha-1 and the BGB comprised 23.11 t ha-1. The percentage contribution to the total biomass varied among dbh classes: 10 to 20 cm (4.52%), 21 to 30 cm (17.93%), 31 to 40 cm (27.98%), 41 to 50 cm (26.79%) and 51 to 60 cm (22.76%).
Total carbon content in A. excelsa tree species
Total carbon content (t ha-1) in different tree components were in the order: 40.27 (bole) >10.22 (root) > 5.36 (branch)>1.61 (bark)>0.73 (leaf)>0.33 (twig). On unit area basis the amounts of C content accumulated in total biomass of A. excelsa trees was 58.52 t ha-1.
Soil Organic Carbon (SOC)
Soil Organic Carbon was estimated as 46.27 t ha-1.
In A. excelsa plantation ecosystem, total biomass estimated was 134.05 t ha-1. Higher value of biomass was observed in bole (66.94%) followed by root (18.33%), branch (9.07%), bark (3.36%), leaves (1.59%) and twig (0.71%). A. excelsa tree species contribution in AGB was 102.96 t ha-1 and BGB estimation by the same species was 23.11 t ha-1. Pande et al. [21] have also estimated biomass of A. excelsa at different ages in Uttar Pradesh and considered the percentage contribution of components plant parts to AGB and showed bole contributed more than 50% followed by bark, 19.9% to 23.3%, branches 9.68% to 14.5% and contribution by root was 18.1% to 25%, the contribution of different tree components of the present study was also similar to the case of Pande et al. [21] as 66.94% contributed by bole, 9.07% by branch and 18.33% by root. The per cent contribution of AGB in the present study calculated as 81.67%. Some other studies conducted by Nascimento and Laurance [22] and Henry et al. [23] have also reported over story biomass contribution of 81.9 and 81%, respectively, but the percent value is low as compared to the report of Clark and Clark (2000) [24], who have reported 92.7 to 94% contribution of over story biomass/AGB.
In present study of A.excelsa plantation showed maximum concentration of carbon in the bole component (47.2%) followed by other tree components and minimum concentration in the twig (36.08%). Similar trend has been reported by Kraenzel et al. [25] and Ganeshaiya et al. [26] in teak plantations.
Biomass estimation by using Biomass Expansion Factor (BEF) values
Total biomass calculated from the BEF value worked out in the present study by using following formula:
By multiplying biomass of merchantable wood with the BEF value of A. excelsa trees, the biomass was estimated as:
Total AGB = Merchantable wood biomass × BEF
                  = 189.12 m3 ha-1 (volume) × 0.356 t m-3 (wood density of A. excelsa) × 1.23
                  = 82.81 t ha-1
Root biomass (BGB) was estimated by using root shoot ratio (R) of the felled trees and calculated as:
Root biomass = Total aboveground trees biomass × R: S
                      = 82.81 t ha-1 × 0.23
                      = 19.05 t ha-1
The total trees biomass (AGB+BGB) thus estimated to be 101.86 t ha-1, which showed 19.20% underestimation with the actual biomass i.e. (126.07 t ha-1) and total C content estimation was 50.93 t ha-1.
Soares and Tome [27] have found analogous trends and their study on effectiveness of BEF it has been concluded that estimates of total stand biomass (aboveground and root biomass) should be derived from allometric equations and if an expansion factor is used then age dependent BEFs are recommended. They also stated that the use of a constant BEF should be avoided because it yields inaccurate estimations.
Conclusion
The provision in the small scale modalities and procedures for land-based CDM projects adopts the approach of producing biomass through the involvement of low income communities with the underlying objective that financial and environmental benefits should accrue to the communities. Thus, substituting biomass for fossil fuels by establishing bioenergy type plantations within the framework of CDM has clear advantages over using it solely as a means to sequester carbon. It has been shown that India is capable of producing biomass sustainably [28].
Carbon sequestration can be achieved effectively through forest management and conservation. If one compares global warming to a fever of the planet, then forest does not only function as a potential remedy, but their destruction also contributes to further illness [29]. Needless to say those forests/plantations are known to bring about changes in edaphic, micro-climatic, floral, faunal and other components of the eco-system through bio-recycling of mineral elements, environmental modifications (including thermal and moisture regime) and changes in floral and faunal composition etc. [30].
Carbon sequestration rates and biomass a stock varies in time (temporal) and space (spatial). A young forest would sequester more carbon than an old forest. Similarly, forests associated with better quality of soils would yield higher carbon sequestration rates. Allocation to different components of trees (bole, branch, twig, leaf, stump root, lateral roots and fine roots) is the area which is less studied and requires a better understanding in the climate change scenario and for the development of BEFs.
Acknowledgement
Authors are thankful to the Director FRI for his kind permission to publish this research articles and Uttarakhand Forest Department for logistical and financial support for conducting the study. We also acknowledged the help of Mr. Rajendra kumar for providing all necessary chemicals, reagents etc.
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Tables and Figures at a glance

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Table 1

 

Figures at a glance

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Figure 1

 

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Map 1
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