Biomass accumulation and Carbon Sequestration Potential of Shorea robusta and Lantana from Doon Valley

157 International Journal of Environmental Biology 2014; 4(2): 157-169
ISSN 2277–386X
Original Article
Biomass accumulation and carbon sequestration potential of Shorea robusta
and Lantana camara from the dry deciduous forests of Doon Valley,
western Himalaya, India
Gautam Mandal*1
and S. P. Joshi1
* Corresponding author: gautam231@gmail.com
Phone No: +91-9459695429
1 Ecology Research Laboratory, Department of Botany, DAV (PG) College, Dehradun, Uttarakhand, India
Received 02 April 2014; accepted 05 May 2014
Abstract
The present study was conducted to quantify that dry deciduous forests of Doon Valley have enormous carbon
sequestration potential and therefore, biomass estimation of invasive shrub like Lantana along with dominant Sal trees can
provide more accurate information about the forest biomass and carbon stock assessment. Variables like DBH and plant
height for both Sal and Lantana were found to be more suitable for allometric equation and therefore used in the present
study. The maximum Sal biomass was recorded from Thano forest (597.41 Mg ha-1
) with a carbon density of
280.78 MgC ha-1
. The minimum Sal biomass was recorded from Golatappar forest (392.05 Mg ha-1
) with carbon density of
184.26 MgC ha-1
. The mean total biomass of Sal was 494.65 Mg ha-1
with mean carbon density 232.48 Mg ha-1
from all
study sites. The maximum shrub biomass (11.15 Mg ha-1
) was recorded from Rajpur Forest periphery with a carbon
density of 5.24 MgC ha-1
. The minimum shrub biomass (6.74 Mg ha-1
and carbon density (3.16 MgC ha-1
) was recorded
from Lachchiwala forest periphery. The total mean biomass of both Sal and Lantana accounted for 502.80 Mg ha-1
(494.65
Mg ha-1
+ 8.15 Mg ha-1
) with the carbon density of 236.32 MgC ha-1
(232.48 MgC ha-1
+ 3.83 MgC ha-1
).
© 2014 Universal Research Publications. All rights reserved
Keywords: - Above Ground Biomass, Carbon Density, Allometric equations, invasive shrub, Tree Basal Area, Tree
Volume.
Introduction
Forests provide a wide range of goods and services. Goods
include timber, fuelwood, as well as food products and
fodder. As regards important services, forests and trees play
a role in the conservation of ecosystems, in maintaining
quality of water, and in preventing or reducing the severity
of floods, landslides, erosion, and drought. Forests provide
a wide range of economic and social benefits, such as
employment, forest products, and protection of sites of
cultural value.
Forests, like other ecosystems, are affected by
climate change. The impacts due to climate change may be
negative in some areas, and positive in others. However,
forests also influence climate and the climate change
process mainly effecting the changes in the quantum of
carbon dioxide in the atmosphere. They absorb CO2 from
atmosphere, and store carbon in wood, leaves, litter, roots
and soil by acting as “Carbon Sinks”. Carbon is released
back into the atmosphere when forests are cleared or
burned. Forests by acting as sinks are considered to
moderate the global climate. Estimates made for Forest
Resources Assessment [1] show that the world‟s forests
store 289 gigatonnes (Gt) of carbon in their biomass alone.
While sustainable management, planting and rehabilitation
of forests can conserve or increase forest carbon stocks,
deforestation, degradation and poor forest management
reduce them. For the world as a whole, carbon stocks in
forest biomass decreased by an estimated 0.5 Gt annually
during the period 2005–2010, mainly because of a
reduction in the global forest area.
The biomass carbon stock in India‟s forests was
estimated at 7.94 MtC during 1880 and nearly half of that
after a period of 100 years [2]. The first available estimates
for forest carbon stocks (biomass and soil) for the year
1986 are in the range of 8.58 to 9.57 GtC [3, 4]. Needless
to say, that the present state of forest carbon stocks owes its
origin to the drive of plantation forestry in India started in
the late 1950s and supplemented later by the social and
farm forestry initiatives of the 1980s and early 1990. The
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International Journal of Environmental Biology
Universal Research Publications. All rights reserved

compounded annual growth rate of CO2 emissions in India
is 4.2 per cent. Some may consider this to be higher than
the desired, but the absolute value of these emissions is still
one sixth that of the United States and lowest for the per
capita GHG emissions [5].
Majority of the forests of Uttarakhand, India can
be broadly divided into six types: subtropical forests, dry
deciduous forests, moist deciduous forests, tropical
coniferous forests (Pine), temperate broad leaved, and
temperate coniferous forests. Biomass values of forest
stands in the Himalaya tend to cluster around two very
different levels – from a low approximately 200t ha-1
for
early successional communities such as chir pine, to a high
of about 400t ha-1
for late successional communities such as
oaks and Sal [6].
Out of the 2 factors of habitat, climate and soil, the
former decides the general distribution of Sal trees (Shorea
robusta) among the climatic factors; rainfall is by far the
most important. Annual precipitation normally comes with
a dry season lasting 4 – 8 months (monsoon climate). At
higher elevations, S. robusta can be damaged by frost. S.
robusta occurs in both deciduous dry and moist forests and
in evergreen moist forest. It accounts for about 14% of the
total forest area in India. For example, southwest Bengal
harbours luxuriant S. robusta forests. Fire is normally
responsible for its frequent occurrence in pure stands or as
the dominant species of mixed stands, as S. robusta is
better equipped to survive conflagration than other tree
species.
Estimation of above-ground biomass (AGB) is an
essential aspect of studies of carbon stocks and the effects
of deforestation and carbon sequestration on the global
balance and also provides valuable information for many
global issues. Estimating AGB is a useful measure for
comparing structural and functional attributes of forest
ecosystems across wide range of environmental conditions.
By using information on biomass, content of carbon,
energy and nutrient could be estimated rapidly. With this
information, detrimental effects of harvesting can be
assessed and compensatory programmes for nutrient
replacement through fertilization can be considered. This is
also important for evaluation and improvement of site and
these form the bases for sound forest management. Forest
can be a carbon source and sink. Therefore, the
management of the forests can affect the global carbon
cycle and climate change.
The method generally used for non-destructive
calculation of biomass is through allometric equations
relating destructively measured tree biomass and field
measurements of circumference at breast height (CBH) or
diameter at breast height (DBH) [7]. This method also
poses a significant problem for regional scale comparisons
because the coefficients a (intercept) and b (slope) in the
allometric equations vary from species to species and site
to site [7]. Therefore, for the study of regional variations in
tree biomass estimates, those aspects of forest structure that
vary significantly at regional scales should be used in the
estimator. In this study we used the allometric equation to
calculate the non-destructive biomass of the dominant Sal
trees from different study sites of Doon Valley.
Defining and characterising shrub is a complex
task; shrubs are the type of vegetal group with a specific
structure or appearance [8]. These non-trees, woody
formation of shrubs are of great significance to biophysical
and biodynamic processes of different ecosystems, and
have a direct impact on ecosystem dynamics and function
[9]. With all the vegetative structure and formations,
biomass is a key structure variable in invasive studies and
research into the dynamics of different ecosystems (sub-
tropical in this case), the type of bio – geographic
conditions and biodiversity they sustain, their role in the
atmospheric carbon cycle, and their resistibility [10].
In many studies the biomass analysis of shrub in
forest and other ecosystems has been obtained through
direct (destructive) or indirect (through dimensional
analysis of different attributes of plants) [11]. In the
destructive methods the plants are harvested and weighed
in the sample plots. This method gives very accurate
estimates of the biomass but harvesting and weighing a
large number of samples are very laborious and costly [12].
In the indirect methods the allometric and mathematical
models have been developed for estimation of total biomass
which are based on the measurements of different plant
attributes like shrub height, stem diameter at breast height
[13], crown diameter [14], crown area and crown volume
[15]. These methods give estimates that can reach to the
nearest prediction levels of the destructive methods and
allow us to observe a large number of physical parameters
at a relatively low cost [16].
Biomass study is very important for various
ecological works especially in relation with nutrient cycle,
fuel property and their adaptation to different climatic
conditions [17]. In addition, the calculation of above
ground biomass and other variables are primarily required
for the better forest, scrubland and grassland ecosystem
management, development and execution of different
models which help in the mapping of different
characteristics of forest fuels [18], effects of invasive
species on forest hydrological planning [19]. Large scale
evaluation, mapping and strategic values are necessary for
improving available knowledge and accurate modelling of
the dynamics of ecosystems [20]. Shrub biomass is an
important component of the total forest biomass, especially
in natural stands. Using the right and accurate allometric
equations for shrub biomass estimation in Doon Valley is
very essential for at least two reasons. First, Lantana is a
problem weed and the rapid growth of Lantana thickenings
are turning the grasslands into woodlands and woodlands
are becoming thicker also the periphery of Doon Valley
forests are heavily infested by this invasive weed, this has
finely raised its importance. Second, measurement of
carbon fluxes both at tree and shrub level, has local and
global importance in study of the CO2 cycle. Study of
forest biomass is very important for constructing the
coupling relationship between community processes and
flux observations and for authenticating and regulating flux
observations. Estimation of shrub biomass can help to
produce more accurate estimates of forest biomass.
Therefore, the objectives of the present study were to 1.
Calculate the biomass and carbon stock of the dominant Sal

trees from the dry deciduous forests of Doon Valley 2.
Calculate the biomass and carbon stock of invasive shrub
Lantana from the periphery of dry deciduous forests of
Doon valley 3. Combine the biomass and carbon stocks of
both Sal trees and Lantana and to assess their further
relevance in local and global carbon cycle.
Methods and Materials
Study Site
The Doon Valley is a part of Uttarakhand, India.
The state of Uttarakhand is situated in the northern part of
India and shares an international boundary with China in
the north and Nepal in the east. It has an area of 53,483 km2
and lies between latitude 28 43′ and 31° 28′ N and
longitude 77° 34′ and 81° 03′ E (Fig. 1) The state has a
temperate climate except in the plain areas, where the
climate is tropical. The average annual rainfall of the state
is 1550 mm and temperatures range from sub-zero to 43°C
[21]. Of the total geographical area of the state, about 19%
is under permanent snow cover, glaciers and steep slopes
where tree growth is not possible due to climatic and
physical limitations [21]. The recorded forest area of the
State is 34,691 km2
, which constitutes 64.79% of its
geographical area [22].
The study area was the Doon Valley Forest
Division which is a valley portion of the district Dehra Dun
and is located in the South-western part of the state of
Uttarakhand, India (Fig.1) The Doon Valley falls in the
western Siwalik Himalayas, lying between latitudes 2955’
and 3030’ N and longitudes 7735’ and 7824’ E. It is
about 20 km wide and 80 km long saucer-shaped valley
with a geographical area of ca. 2100 km2
. The study has
been conducted in the six forest ranges of Doon Valley
(Table 1) named (Lachchiwala range, Asarori range, Thano
range, Golatappar range, Jhajra and Selaqui range and
Rajpur forest range). A minimum of 10-30 Sample plots of
10  10 m were placed in all forest type within the above
said forest ranges, depending upon its area and then Sal tree
density was calculated.
Figure1: Pictorial representation of District Dehradun (Doon Valley) Map
(Source: www.mapsofindia.com)

Non destructive Biomass estimation of Sal trees
The various methods used in the study are as follows:
 The height of the tree was calculated with the help of
geometric method [23].
 DBH of the tree was measured by using the diameter
tape. The diameter tape does not measure diameter
directly, but instead measures the circumference of the
tree. Therefore we measured the circumference and
then it was converted to diameter by solving the
following DBH equation:
C = π ∗ DBH
Where:
C = circumference of tree
𝜋 = 3.14,
DBH = diameter at breast height,
Therefore, DBH = C/π
 To estimates the biomass of the Sal trees we used a
modified biomass equation which is a simple form of
allometric equation Y = a(DBH)b
suggested and
recommended in earlier study [24]. The modified
biomass equation used in the present study was Y=
0.0921 × (DBH) 2.5899
which was earlier used to
calculate the biomass of the high density primary
species such as Shorea spp., Hopea spp.,
Dipterocarpus spp. and Syzygium spp. from Ayer
Hitam Forest Reserves (AHFR) Malaysia [25]. In
addition, estimates of total carbon, Tree Basal Area,
Tree Volume and total CO2 content are also presented
in this study.
 Tree Basal Area (TBA) is the cross sectional area
cover the bark at breast height (1.3m above the
ground) measured in meter square (m2
). This helped us
to estimate the tree volume and stand competition. We
calculate the diameter at breast height in cm and
calculate the basal area (m2
) using an equation based
on the formula for the area of a circle (𝐴 = 𝜋𝑟2
)
Where, r = radius and 𝜋 = 3.14
Tree basal area (TBA) =
DBH
200
2
× 3.14
Where,
DBH= Diameter at Breast height in cm
π = 3.14
 We calculated tree volume by the following
formula;
Tree Volume m3
=
DBH
200
2
× 3.14 ×
Ht
3
Or Tree Volume =
TBA
3
× Ht
 Volume (m3
tree-1
) of each tree in a sampling quadrat
obtained is converted into the volume on hectare basis.
 Calculation of below ground tree Biomass for each
plot
To calculate the below ground tree biomass we used
the [26] and REDD + prescribed formula:
CBB = R ∗ CAB
Where, R = Root and shoot ratio
CBB = below ground biomass
CAB = above ground biomass
 Total Biomass was obtained by summing the
Aboveground Biomass, Belowground Biomass
and Dead Organic Matter.
(Total Biomass = AGB + BGB + Deadwood)
 The carbon storage for each species was computed
by multiplying total biomass with constant factor
0.50 [26]
C = TB  0.50
Where,
C = Carbon (Mg ha-1
)
TB = Total Biomass (Mg ha-1
)
Non-destructive estimation of shrub biomass
The dependent variable shrub biomass depends upon many
independent variables. The identified independent variables
to establish the allometric equation were total plant height
(H), maximum basal diameter (D1) and minimum basal
diameter (D2), maximum crown width (C1) and minimum
crown width (C2), which were measured to calculate the
average values before harvesting. Average values of crown
width was calculated by C = (C1+C2)/2 and used to
calculate plant canopy area (CA, m2
) and plant canopy
volume (CV, m3
) as (CA = πC2
/4), and (CV = CA×H).
However, average of D = (D1+D2)/2 was used to establish
the allometric equation along with the plant height. Dry
weight was already measured for each component by
keeping it in oven at 700
C for 72 hrs. The dry weight of
lantana with its diameter (D) and D2
H were tested in
different regression models. The following equations were
tested for its best fit for the calculation of shrub biomass
[27].
(1) y = a + bD + cD2
(2) 𝑙𝑛 y = a + bD
(3) 𝑙𝑛 y = a + b𝑙𝑛D
(4) y0.5
= a + bD
(5) 𝐲 = 𝐚 + 𝐛𝐃 𝟐
𝐇*
(equation used in the present
study)
(6) 𝑙𝑛 y = a + bD2
H
(7) y0.5
= a + bD2
H
(8) y = a + b(CA) + C(CA)2
(9) y = a + b(CV) + C(CV)2
In all the above equations y represents the biomass, D is the
diameter, H is the plant height, CA is canopy area, CV is
canopy volume and a, b, c are regression coefficients, and
ln indicates natural logarithm. The biomass of a single
Lantana shrub calculated with the above mentioned
equation was then converted to the biomass ha-1
by
multiplying the biomass of one shrub with the density of
Lantana ha-1
and likewise the carbon stock as well.
Data Analysis
All statistical analysis was done with the help of XLSTAT
(2011) for Microsoft windows 2010.
Result
We found that out of all the equations we considered for
the biomass calculation of Lantana, the equation (y = a +
bD2
H) was more accurate and fit into the criteria of
calculating shrub biomass. We established a correlation

between different measured parameters and biomass of
Lantana and received a positive relation with plant height
(R2
= 0.86), stem diameter at breast height (R2
= 0.91) and
when taken these two variable together in the form of D2
H
(R2
= 0.88). There were more criteria to choose the accurate
one i.e., the adjusted R2
, the Furnival index, computed F
value, RMSE and the significance level of the values at 5%.
The equation for the biomass calculation shall be
considered more accurate and best fit if it gives a lower
root mean square error (RMSE), higher value of adjusted
R2
and less value of Furnival index. When the computed
value of F was compared with the tabular value at (1, n – 2)
degrees of freedom we found that the calculated value of F
(137.59) were greater than the tabular value (4.41) at (1,
18) degrees of freedom at 5% level of significance (Table
2a, 2b). This concludes that the regression coefficient, β is
significantly different from 0 and the value is significant.
D2
H fit best on these criteria with adjusted R2
= 0.88
(maximum amongst all the equations), Furnival index =
0.04123 (lowest) and RMSE = 157 (lowest amongst all the
equations) (Table 2c). These results therefore, strongly
suggested us to choose the allometric equation with D2
H as
an important variable for the non-destructive calculation of
Lantana biomass. For the biomass calculation of Sal tree an
already tested and applied equation for the same condition
was taken which is described earlier in Methodology
section.
Detailed site wise biomass and carbon stock analysis are as
follows:
Thano Forest Range
The total biomass of Sal trees 597.41 Mg ha-1
was
calculated from Thano forest range which include AGB –
458.84 Mg ha-1
, BGB – 110.12 Mg ha-1
, and Deadwood –
28.44 Mg ha-1
. The site also recorded a total tree basal area
(TBA) 45.91 m2
ha-1
and tree volume (TV) of 502.55 m3
ha-1
. When the total biomass which includes
AGB+BGB+Deadwood was converted to the carbon stock
with the prescribed conversion factor, the site recorded a
carbon storage value of 280.78 MgC ha-1
. The avg. DBH of
the Sal trees was between 33cm – 42cm and the density of
Sal tree was 415trees ha-1
. The avg. height range of the tree
from all the plots was between 27m – 37m.
The mean shrub height recorded from this site was
219.65 cm with mean crown diameter of 141.95 cm. The
mean shrub canopy area was 1.65 m2
/plant. The density of
Lantana from this site was 15,600 plants ha-1
.Total biomass
of the shrub was 6.82Mg ha-1
from this site and the total
carbon stock estimated from this site was 3.20MgC ha-1
.
Some commonly growing dominant plant species from this
site were Milius avelutina (Dunal) Hook. F. & Thom,
Litsea glutinosa (Lour.) Robinson, Syzygium cumini (L.)
Skeels, Mallotus philippensis (Lam.) Muell.-Arg,
Colebrookia oppositifolia J. E. Smith, Asparagus
adscendens Buch.-Ham ex Roxb, Clerodendrum viscosum
Ventenat, Murraya koenigii (L.) Sprengel, Boehmeria
frutescens D. Don, Calotropis procera (Aiton) Dryander,
Cassia occidentalis L.
Lachhiwala Forest Range
In Lachhiwala forest the Sal density was 404 trees ha-1
with
an average height range of Sal trees between 30m – 37m
and average DBH range of 30 – 38cm. The site recorded a
total biomass of 504.17Mg ha-1
which included AGB –
387.23 Mg ha-1
, BGB – 92.93 Mg ha-1
, and Deadwood –
24.01 Mg ha-1
. A good quantity of carbon sequestered from
this site i.e., 236.96 MgC ha-1
. The site also recorded a
TBA of 40.04 m2
ha-1
and a total TV of 447.66 m3
ha-1
.
The mean shrub height from this site was 223.9cm and the
mean crown diameter was 141.48cm. The mean shrub
canopy area was 1.67 m2
/plant. The density of Lantana
from this site was 15, 300 plants ha-1
. The total
phytovolume of Lantana (75,927.76 m3
ha-1
) and coverage
(33.16%) was recorded from this site. Total biomass of the
shrub was 6.74 Mg ha-1
from this site and the total carbon
stock estimated from this site was 3.17MgC ha-1
. Some of
the commonly growing plant species from the study sites
are Phlogacanthus thyrsiflorus (Roxb.) Nees, Solanum
erianthum D. Don, Ziziphus mauritiana Lam., Urena
lobata L., Amaranthus viridis L., Argemone Mexicana L.,
Murraya koenigii (L.) Spreng, Randia uliginosa (Retz.)
Poiret, Glycosmis pentaphylla auct. mult. non DC.
Asarori Forest Range
The Asarori forest recorded a Sal density of 372 trees ha-1
.
The average height range recorded from different plots was
between 26m – 37m and DBH range between 27cm –
38cm. The total biomass of Asarori forest site was 416.48
Mg ha-1
which includes AGB – 319.88 Mg ha-1
, BGB –
76.77 Mg ha-1
and Deadwood – 19.83 Mg ha-1
. Total basal
area was 33.79 m2
ha-1
and tree volume was 371.83 m3
ha-1
.
When the biomass was used in the conversion of total
atmospheric carbon sequestered per hectare, the value was
195.79 MgC ha-1
.
The mean shrub height from this site was
258.15cm and the mean crown diameter was 159.13cm.
The mean shrub canopy area was 2.17m2
/plant. A mean
shrub canopy projected volume of 5.27 m3
/plant was
recorded from this site. The density of Lantana from this
site was 16,600 plants ha-1
. The total phytovolume of
Lantana from this site was recorded as 87,528.48m3
ha-1
and
coverage of 36.10%. Total biomass of the shrub from this
site was 7.03Mg ha-1
and the total carbon stock estimated
from this site was 3.30MgC ha-1
. Some of the commonly
growing plant species from this site was Alternanthera
sessilis (L.) R. DC., Eupatorium odoratum L., Opuntia
dillenii (Ker Gawl.) Haw., Parthenium hysterophorus L.,
Phylanthus emblica L., Xanthium indicum Koenig., Sida
cordifolia L., Murraya koinigii L. Spreng., Woodfordia
fruticosa L.
Rajpur Forest range
Rajpur forest recorded a total Sal trees biomass of 478.18
Mg ha-1
which include AGB – 367.27 Mg ha-1
, BGB –
88.14 Mg ha-1
and Deadwood 22.77 Mg ha-1
. The tree basal
area from this site was 38.07 m2
ha-1
and tree volume was
439.65 m3
ha-1
. However, the total carbon storage capacity
of the site due to the Sal forest was 224.75MgC ha-1
. The
shrub height from this site was the maximum and a mean
shrub height of 508cm was recorded. The mean crown
diameter was 180.28cm. The mean shrub canopy area was
2.64m2
/plant. The mean shrub canopy projected volume of
13.79m3
/plant was recorded from this site. The density of
Lantana from this site was 14,600 plants ha-1
. The total

TABLE (1): CHARACTERISTICS OF VARIOUS STUDY SITES IN DOON VALLEY
Table 2(a): ANOVA table for the regression analysis using the model y = a + b D2
H
Table 2(b): Estimates of regression coefficients along with the standard error for the regression model y = a + b D2
H
Regression coefficient Estimated Regression coefficients Standard Error of Estimated coefficients
a 0.21162 0.02191
b 0.00010 8.55566
Table 2(c): estimates of Adjusted R2
and Furnival index for the model y = a + b D2
H
Regression Statistics
Multiple R 0.940381
R Square 0.884316
Adjusted R Square 0.877889
Standard Error 0.041585
Furnival index 0.041231
Observations 20
Table (3): Comparison of AGB, BGB, Deadwood, Total Biomass and total carbon sequestration potential of Sal (Shorea robusta) tree
from different sites
(AGB = Above Ground Biomass, BGB = Below Ground Biomass, TB = Total Biomass, TBA = Tree Basal Area, TV = Tree Volume)
Table (4): Comparative account of calculated biomass and carbon density of Lantana from all the sites of Doon Valley
Study Sites Sites Blocks Dominant Species Point Coordinates Elevation
Land
Use
Avg.
DBH
(cm)
Avg. Tree
height (m)
Asarori Forest
Range
Mohabbewala Shorea, Syzygium E 780
58'41.8" & N 300
15'22.6" 2024 ft Forest 25.87 22.19
Chandrabani Shorea, Syzygium E 780
58'36.8" & N 300
15'24.9" 2034 ft Forest 27.31 26.06
Thano Forest
Range
Thano Shorea robusta E 780
11'39.5" & N 300
14'51.3" 2411 ft Forest 28.98 28.01
Kalusidh Shorea robusta E 780
10'54.9" & N 300
13'45.0" 2093 ft Forest 22.91 23.13
Selaqui &
Jhajra Range
Jhajra Shorea, Syzygium E 770
55'9.25" & N 300
20'53.3" 1942 ft Forest 25.66 28.33
Rajawala Shorea, Terminalia E 770
56'42.2" & N 300
21'22.7" 2060 ft. Forest 26.13 28.67
Golatappar
Forest Range
Golatappar Shorea, Ehertia E 780
13'10.5" & N 300
02'31.4" 1100 ft. Forest 27.12 24.65
Laltappar Shorea, Ehertia E 780
12'10.4" & N 300
02'12.5" 1456 ft. Forest 27.87 23.88
Rajpur Forest
Rajpur Shorea, Lantana E 780
05'07.8 & N 300
23'08.6" 3015 ft. Forest 24.56 26.37
Malsi Shorea robusta E 780
04'57.4" & N 300
23'28.3" 3347 ft. Forest 25.87 25.55
Lachhiwala
Forest Range
Lachhiwala Shorea, Syzygium E 780
06'38.6" & N 300
13'37.2" 1955 ft. Forest 23.02 25.15
Song Syzygium, Shorea E 780
07'56.0" & N 300
12'48.9" 1719 ft. Forest 22.86 22.33
ANOVA
Source df SS MS F Significance F
Regression 1 0.237949459 0.237949 137.596 7.27159E-10
Residual 18 0.031127942 0.001729
Total 19 0.269077401
Name of the sites
Average
Crown
Diameter
(cm)
Average
Shrub
Canopy
Area
(plant/m2
)
Density of
Lantana ha-1
Biomass
(Mg ha-1
)
Carbon
Density
(Mg ha-1
)
Phytovolume
(m3
ha-1
)
Carbon
Dioxide
(Mg ha-1
)
Thano Forest Range 141.95 1.65 15,600 6.82 3.20 75,988.74 25.00
Lachchiwala Forest Range 141.48 1.67 15,300 6.74 3.16 75,927.76 24.71
Asarori Forest 159.13 2.17 16,600 7.03 3.30 87,528.48 25.80
Selaqui/Jhajra Forest 150.40 1.94 16,600 7.35 3.45 93,001.50 26.96
Rajpur Forest 180.28 2.65 14,600 11.15 5.24 201,363.20 40.89
Golatappar 176.63 2.33 17,000 9.80 4.61 120,496.00 35.96
Name of the Sites
AGB
AGB (Mg)
BGB (Mg)
Deadwood
(Mg)
TB
(Mg)
TBA
(m2
ha-1)
TV
(m3
ha-1
)
Total Carbon
(Mg ha-1
)
Thano Forest Range 458.841 110.122 28.448 597.411 45.919 502.549 280.783
Lachhiwala Forest Range 387.230 92.935 24.008 504.173 40.046 447.668 236.962
Asarori Forest Range 319.883 76.772 19.833 416.487 33.798 371.832 195.749
Selaqui and Jhajra Forest Range 445.171 106.841 27.601 579.612 43.894 513.204 272.418
Rajpur Forest Range 367.267 88.144 22.771 478.182 38.068 439.657 224.745
Golatappar Forest Range 301.117 72.26 18.669 392.05 31.52 324.19 184.265
Mean 379.918 91.179 23.555 494.653 38.874 433.183 232.487

Table (5): Comparison of Biomass and Carbon pools of various forest types of India with the present study
Forest Type
Biomass
(Mg ha-1
)
Carbon
(Mg ha-1
)
Source
Tropical Dry Forest, Varanasi, India 239.80 119.90 Singh, 1975
Sub Tropical Humid Forest, India 220.00 110.00 IPCC, 2006
Sub-Tropical Dry Forest, India 130.00 65.00 IPCC, 2006
Evergreen Forest, Eastern Ghats, India 307.30 153.65 Ramachandran et al. 2007
Deciduous Forest, Eastern Ghats, India 251.65 125.82 Ramachandran et al. 2007
Secondary Deciduous Forest ,
Eastern Ghats, India
241.77 120.88 Ramachandran et al. 2007
Scrub , Eastern Ghats, India 57.50 28.75 Ramachandran et al. 2007
Semi Evergreen, Western Ghats, India 202.60 101.30 Kale et al. 2009
Mixed Moist Deciduous,Western Ghats, India 209.30 104.65 Kale et al. 2009
Tropical Semi Evergreen, PauriGarhwal, India 324.0 162.0 Baishya et al. 2009
Mixed Forest, Chattisgarh, India 78.31 39.11 Bijalwan et al. 2010
Teak Mixed Forest, Chattisgarh, India 66.34 33.17 Bijalwan et al. 2010
Degraded Forest, Chattisgarh, India 45.94 22.97 Bijalwan et al. 2010
Sal Mixed Forest, Chattisgarh, India 66.54 33.27 Bijalwan et al. 2010
Dry Siwalik Sal Forest, Pauri Garhwal, India 180.80 83.20 Sharma et al. 2010
Dry deciduous Sal Forest , Pauri Garhwal, India 162.00 74.50 Sharma et al. 2010
Moist Bhabhar Sal Forest, Pauri Garhwal, India 346.50 159.40 Sharma et al. 2010
Pinus roxburghii, Pauri Garhwal, India 159.40 73.30 Sharma et al. 2010
Present study
Pure Sal (Shorea robusta) Forest of
(Doon Valley), India
494.65 232.49 Present study
Invasive Shrub (Lantana) from the forest of
(Doon Valley), India
8.15 3.83 "
phytovolume of Lantana from this site was recorded as
201, 363.20m3
ha-1
with coverage of 38.63%. Total biomass
of the shrub was 11.15 Mg ha-1
from this site and the total
carbon stock estimated from this site was 5.24MgC ha-1
.
Some commonly growing plant species of this site were
Adhatoda zeylanica L., Asparagus adscendens Buch.-
Ham. ex Roxb., Bambusa arundinacea Willd., Calotropis
procera (Aiton) Dryander., Caryopteris grata (Wallich)
Benth., Baliospermum montanum (Willd.) Muell.-Arg.,
Desmodium gangeticum (Linn.) DC., Indigofera
atropurpurea Ham ex Ham., Dendrolobium triangulare
(Retz.) Sch., Glycosmis pentaphylla auct. mult. non DC.,
Jasminum multiflorum (Burm. f.) Andrews.
Selaqui and Jhajra Forest Range
From Selaqui and Jhajra forest region the total biomass of
Sal tree was 579.61Mgha-1
which include AGB – 445.17
Mg ha-1
, BGB – 106.84 Mg ha-1
and Deadwood 27.60 Mg
ha-1
. Amongst all the forest study sites this obtained the
maximum total biomass. This site recorded a maximum
TBA of 43.89 m2
ha-1
and a TV of 513.20 m3
ha-1
. Since
biomass has a direct role in determining the total carbon
therefore, the Sal forest recorded a maximum carbon stock
of 272.41MgC ha-1
from this site.
The mean shrub height as obtained from this site
was 280.5cm and the mean crown diameter was 150.40cm.
The mean shrub canopy area was 1.93m2
/plant. The mean
shrub canopy projected volume of 5.60m3
/plant was
recorded from this site. The density of Lantana from this
site was 16,600plants ha-1
. The total phytovolume of
Lantana from this site was recorded as 93,001.50m3
ha-1
whereas the coverage was of 32.14%. Total biomass of the
shrub was 7.35 Mg ha-1
from this site and the total carbon
stock estimated was 3.45MgC ha-1
. Some abundantly found
species from this site were Murraya koinigii L. Spreng.,
Parthenium hysterophorus L., Xanthium indicum Koenig.,
Jasminum nudiflorum Lindl., Colebrookea oppositifolia
Smith., Alternanthera sessilis (L.) R. DC., Phlogacanthus
thyrsiflorus (Roxb.) Nees., Pogostemon benghalense
(Burm. f.) Kuntze., Ziziphus mauritiana Lam., Androsace
umbellata (Lour.) Merrill, Anisomeles indica (L.) Kuntze,
Asparagus racemosus Willd.
Golatappar Forest Range
Minimum biomass (392.05 Mg ha-1
) was recorded from
Golatappar, due to its open patches of Sal trees. This
includes a combined value of AGB – 301.12 Mg ha-1
, BGB
– 72.26 Mg ha-1
and Deadwood18.67 Mg ha-1
. TBA of
31.52 m2
ha-1
and TV of 324.19 m3
ha-1
was recorded from
this site. The total amount of atmospheric carbon which
was sequestered due to Sal forest was 184.27MgC ha-1
.
The mean shrub height from this site was 296.8cm
and the mean crown diameter was 170.63cm. The mean
shrub canopy area was 2.33m2
/plant. The mean shrub
canopy projected volume of 7.08m3
/plant was recorded
from this site. The density of Lantana from this site was
17,000plants ha-1
. The total phytovolume of Lantana from
this site was recorded as 120,496.00 m3
ha-1
with coverage
of 39.64%. Total biomass of the shrub was 9.80Mg ha-1
from this site and the total carbon stock estimated from this
site was 4.61MgC ha-1
. Some dominant plant species of the
site were Adenostemma lavenia L. Kuntze, Curculigo

orchioides Gaertn., Kyllinga monocephala Rottb.,
Alloteropsis cimicina (L.) Stapf, Argemone mexicana L.,
Artemisia nilagirica C.B. Clarke, Brachiaria reptans (L.)
Gardner & C. E. Hubbard, Solanum hispidum Persoon,
Pogostemon benghalense (Burm. f.) Kuntze, Flemingia
paniculata Wall. ex Benth., Clerodendrum viscosum
Ventenat, Jard. Malm., Coffea benghalensis Heyne ex
Roemer & Schultes, Calotropis procera (Aiton) Dryander,
Asparagus adscendens Buch.- Ham. ex Roxb., Adhatoda
zeylanica Medikus, Caryopteris grata (Wallich) Benth.
From all the forest range of the present study, a
mean Sal biomass of 494.65 Mg ha-1
was recorded this
include mean AGB – 379.91 Mg ha-1
, mean BGB – 91.17
Mg ha-1
and a mean Deadwood of 23.55 Mg ha-1
.The mean
total carbon stock of Sal trees from all the sites was
232.48MgC ha-1
(Table 3).
From all the forest periphery range of the study, a
total mean Lantana biomass of 8.14 Mg ha-1
was recorded,
which was 1.90 % of the total Sal biomass. Mean total
carbon stock of Lantana was 3.82 MgC ha-1
from all the
sites (Table 4).
DISCUSSION
Numerous biomass equations have been reported for
estimating forest biomass for a given species under various
conditions. However, many of these equations have been
presented inconsistently in terms of their form and
regression parameters, and this inconsistency has
complicated their application. In the current study a number
of biomass equations were considered and has chosen the
most suitable approach for evaluating the biomass through
allometric equations, which is already tested for its
accuracy and used accordingly in a similar condition and
for the similar tree species. However, the allometric
equation chosen for the biomass calculation of Lantana was
adopted from FAO statistics manual for Asia pacific to
calculate the biomass of shrubs and trees. The particular
equation used in this study was tested for its relevance and
accuracy to the present condition, which is discussed in the
result section.
The present study is focused in calculating the
biomass and carbon stock of dominant Sal trees and the
noxious, invasive woody shrub Lantana from the periphery
of different forest sites chosen for the present study and
also to give suitable and accurate method for the
calculation of shrub biomass as this aspect of shrub is
always neglected by researchers. In the present study we
chose the equation with variables like DBH and plant
height to calculate the biomass of both Sal trees and
Lantana but in some of the studies other attributes like
north and south aspects of the trees, biomass of different
components (bole, branch, twig, foliage, stump roots,
lateral roots, and fine roots) in different girth classes were
also calculated separately from its measured circumference
to calculate the biomass [28]. In some studies the tree
height, basal area of the tree and importantly the WSG
(Wood Specific Gravity) of the trees were used to calculate
the biomass and carbon stock [29, 30]. Some studies
reported that the density of carbon per unit volume is
highly correlated with WSG and, therefore, WSG has direct
applied importance for estimating ecosystem carbon
storage and fluxes [31].WSG is expected to be greater in
less fertile soils with drought stress conditions [32].
The AGB carbon pool consists of all living
vegetation above the soil, inclusive of stems, stumps,
branches, bark, seeds and foliage. The most comprehensive
method to establish the biomass of this carbon pool is
destructive sampling, whereby vegetation is harvested,
dried to a constant mass and the dry-to-wet biomass ratio
established. Destructive sampling of trees, however, is both
expensive and somewhat counter-productive in the context
of promoting carbon sequestration and in Indian context the
destructive sampling is not legal as well. According to
some worker both tropical and temperate forests, biomass
calculated through such diameter measurements explain
more than 95% of the variation in tree biomass [33].
There are a number of database and publications,
presenting default regression equations, stratified by
rainfall regime and region [26, 34]. These default
equations, based on a large sample of trees, are commonly
applied, as the generation of local allometric equations is
often not feasible. However, the application of default
equations tends to reduce the accuracy of the biomass
estimate. Sometime as the elevation increases, potential
evapo – transpiration of the trees decreases, making the
forest wetter at a given rainfall, thus a regression equation
applied to highland forest may give inaccurate biomass
estimates.
The BGB (Below Ground Biomass) carbon pool
consists of the biomass contained within live roots of trees.
Although with AGB (Above Ground Biomass), for which
less data exists, regression equations from root biomass
data have been formulated which predict root biomass
based on above-ground biomass carbon [33, 35]. A review
of 160 studies covering tropical, temperate and boreal
forests found a mean root-to-shoot (RS) ratio of 0.26,
ranging between 0.18 and 0.30 [35]. The wood carbon pool
includes all non-living woody biomass and includes
standing and fallen trees, roots and stumps with diameter
over 10cm [35].
The Root Shoot (RS) ratios were constant between
latitude (tropical, temperate and boreal), soil texture (fine,
medium and coarse), and tree-type, both angiosperm and
gymnosperm [35]. Roots are believed to depend on climate
and soil characteristics [36]. As with AGB, the application
of default RS ratios represents a trade-off between costs of
time, resources and accuracy. BGB can also be assessed
locally by taking soil cores from which roots are extracted;
the oven dry weight of these roots can be related to the
cross-sectional area of the sample, and so to the BGB on a
per area basis [37]. Often ignored, or assumed in
equilibrium, this carbon pool can contain 10% - 20%of that
in the AGB pool in mature forest [38]. However, in
immature forests and plantations both standing and fallen
dead wood are likely to be insignificant in the first 30-60
years of establishment.
Tropical forests have a strong vertical structure,
with much of the leaf biomass and fruits in the brightly lit
canopy, seed germination, seedling growth, and juvenile
recruitment in the dark understory [39]. Tropical forest
canopies have a layered structure. Tall trees comprise the

upper layer, followed by a main canopy layer, and a sub
canopy of smaller trees and shrubs near the ground level
[40]. Trees in tropical forests have relatively large leaves
and are often characterized by buttresses, palms, climbing
plants, epiphytes and hemi-epiphytes [41]. In contrast to
tropical evergreen forests, tree species diversity is lower in
tropical deciduous forests. Furthermore, canopies are
shorter and the structure is more open compared to the
tropical rainforests. Tropical forests contain more than half
of the Earth‟s terrestrial species [42]. Furthermore, tropical
forests predominantly contribute to global biodiversity
„hotspots‟ or the areas which are featuring exceptional
concentrations of endemic species and experiencing
exceptional loss of habitat. Biodiversity is generally high
but little is known as tropical forests are extensive, highly
variable and generally more difficult to study than any
other vegetation type [43]. About 44% of the world‟s
relatively undisturbed forest lies in the tropics [44].
In India, as much as 86% of the forest area is
under tropical forest, of which 53% is dry deciduous, 37%
moist deciduous and the rest evergreen [45]. Terrestrial
ecosystems of India are extensively studied for point
biomass and productivity estimations using ecological
methods [46, 47, 48]. There is need to perform extensive
studies for biomass estimation in order to know the role of
forest in carbon cycle patterns. Creation of reliable biomass
data requires region-specific allometric equations to
estimate the biomass and carbon stock and the values of
which can be further extrapolated to the local and regional
levels using appropriate techniques.
From the present result it is clear that Golatappar
range is an open canopy forest where the density of the Sal
trees is also very less, this is the most probable reason why
Golatappar has shown the least per hectare biomass (392.05
Mg ha-1
). The maximum total biomass was recorded from
Thano range (597.41 Mg ha-1
). These results are in relation
with the early findings of the ecosystem valuation services
and forest governance [49]. In some previous work it was
shown that biomass values of forest stands in the Himalaya
tend to cluster around two very different levels – from a
low approximately 200t ha-1
for early successional
communities such as chir pine, to a high of about 400Mt ha-
1
for late successional communities such as oaks and Sal
[6].
Tree biomass in excess of 700t ha-1
has been
reported for old growth Sal in the Himalayan foothills as
well as mixed oak forests at mid altitudes which are higher
than biomass values reported for many tropical rain forests
[6]. In addition, old growth forests have high levels of soil
carbon making, while late successional Himalayan forests
are very valuable in terms of carbon storage potential. This
finding again supports the present result where a large
amount of biomass (494.65 Mg ha-1
) is recorded from the
salforest of Doon Valley. Carbon storage in the
Uttarakhand Himalayan forests range from an average of
about 175t C ha-1
for chir pine forests to approximately
300t C ha-1
for oak and Sal dominated forests [6]. Whereas,
the present result shows that from the Sal dominated dry
deciduous forest 232.84 MgC ha-1
carbon is sequestered.
Some worker reported that above ground biomass had
48.30 Mg ha-1
C to 97.30 Mg ha-1
C (approximately 50% of
the biomass) in tropical deciduous forests of India [50]. The
carbon storage in the present study is much similar to in
range as compared to the estimates made in different
tropical forests [51, 52]. Estimate also state that the carbon
storage was from 94.30 to 190.96 Mg ha-1
C in semi-
evergreen forests of Karnataka, India [52].
Some other previously obtained data shows that
the biomass of subtropical Sal forests of the entire
Himalayan foothills was 10.10 Mt C [6] but in this case the
carbon stock was calculated by using a conversion factor
0.63 and not with the IPCC default. However, in the
present study a carbon conversion factor 0.47 [26, 34] is
used instead of 0.63 [6]. In Uttarakhand, community
forestry has been strongly institutionalized; issues of
ecosystem services can directly affect their economic
condition and processes leading to the empowerment of
local people. However, in the current scenario the forests of
Doon valley are heavily infested by invasive shrub species
like Lantana which is also a great source of carbon sink
from the atmosphere. But this woody shrub was never
considered for its immense carbon storage property.
Though Lantana pretence several serious threat to the
environment but apart from the threat if we can consider
Lantana as a good carbon sequestering agent along with the
subtropical forests (dominated by Sal trees) as in the case
of the present study, it will always be a better alternative to
the sequestration of carbon from the atmosphere of
developing countries like India, where the situation is
alarming. The present study shows that an average Lantana
biomass (8.15 Mg ha-1
) and an average carbon density 3.83
MgC ha-1
are recorded from the forest periphery of Doon
Valley.
Though many workers reported shrub biomass in
their studies from different parts of globe [14, 15, 20, 53,
54] but never for invasive shrub like Lantana from the
Doon Valley. Therefore information on Lantana biomass
and its role in global carbon sequestration would be helpful
in near future. Given that, there are large areas infested
with this plant, it is reasonable to consider if large scale use
could be made of its biomass. From the present and
previous research work it is clearly revealed that Lantana is
a problem weed across the country and globe as it has
many negative impacts on the biodiversity but despite their
negative impacts this weed can also be considered as one of
the very good source of carbon sink from the atmosphere,
as it is equally contributing in the eradication of CO2 along
with the deciduous forests.
The C balance of a tropical forest based on
atmospheric, eddy covariance or ground based studies may
differ among each other [55]. The global CO2 flux caused
by the land use changes, however, is dominated by tropical
deforestation as about 13 million hectare tropical forest are
felled or grazed each year [56].
Workers reported the aboveground biomass values
for tropical forests between 2,250 and 32,450 g C m−2
[57].
Estimates for the aboveground C ranges between 2,250 and
20,300 g C m−2
for mature tropical forests, and between
2,300 and 27,300 g C m−2
for mature seasonally dry
tropical forests [58]. In general, values for aboveground

live biomass range between 1,800 and 26,600 g C m−2
, and
those for the root biomass between 400 and 5,700 g C m−2
for moist tropical forests [59, 60].
The average biomass of natural tropical forests is
estimated at 9,400 g C m−2
[61]. Average above-ground
biomass estimates for tropical forests of Africa range from
85 Mg ha−1
for closed deciduous forests to 251 Mg ha−1
for
swamp forests [62]. The estimate of average carbon content
(in the biomass and forest soil) in Indian forests is 126 Mg
C/ha of which 36% (45.8 Mg C ha-1
) is in biomass and 64%
(79.8 Mg C ha-1
) in forest soils [63]. The results of the base
scenario show that Indian forests and forest sector activities
in 1994 are a source of 12.8 Tg C.
Sal mixed forest in Chattisgarh, India had
recorded the carbon stock of 33.27 MgC ha-1
[64], while in
the present study dry deciduous forest which has the largest
share of S. robusta has recorded a carbon stock of 232.48
MgC ha-1
. This might be due to the forests of Chattisgarh,
not being fully mature as compare to the forests in the
present study which resulted in higher carbon storage
(Table 5).
Carbon stock of 159.40 MgC ha-1
from the Shorea
robusta forest of moist Bhabhar region in India was
calculated [65] while in the present study, 232.48 MgC ha-1
of carbon stock was recorded from all the Sal dominated
dry deciduous forest. Carbon density (74.50 MgCha-1
) was
reported from the dry-sub deciduous forest of Bhabhar
region [65] while in the present study, the carbon density of
232.48MgC ha-1
was recorded from the dry-deciduous
forests of Doon Valley (Table 5).
Some workers studied the carbon sequestration
potential in India by considering three distinct scenarios –
Business as usual, conservation and plantation forestry
[66]. They used Land use and Carbon Sequestration
(LUCS) model with software developed at the World
Resources Institute, Washington DC, USA. It was
estimated that under business as usual scenario 6.65 bt
(billion tonnes) of carbon (or 13.3mt of carbon annually)
and under plantation scenario 6.94 bt of carbon (or 13.88
mt of carbon annually) will be sequestered during 2000-
2050.
From the undisturbed Himalayan foothill Sal forests in
Doon valley, some recorded 2.95 t C ha-1
yr-1
under natural
forests, 6.7 t C ha-1
yr-1
in planted forest and 9.05 t C ha-1
yr-1
for growing stand [67], while in another study [68] the
carbon sequestration potential for natural Sal forest has
been estimated as 5.45 t C ha-1
yr-1
. The old growth forest
of Sal and high altitude oak (Quercus semicarpifolia) are
demonstrated to sequester respectively 3.33 t C ha-1
yr-1
and
4.51 t C ha-1
yr -1
from above ground component with
major contribution (75.8 % for the former and 71 % for the
latter) from bole [69]
In India, CO2 emissions from forest diversion or
loss are largely offset by carbon uptake due to forest
increment and afforestation. Many authors concluded that
for the recent period, the Indian forests are nationally a
small source with some regions acting as small sinks of
carbon as well [3, 4, 70]. The improved quantification of
pools and fluxes related to the forest carbon cycle is
important for understanding the contribution of Indian
forests to net carbon emissions as well as their potential for
carbon sequestration in the context of the Kyoto Protocol
[4]. It was estimated that under this options 4.936 mt
(million tonnes) of carbon would be sequestered over a 40
years period of time. A sustainable forestry scenario
(baseline) and a commercial scenario (meeting biomass
demands through plantation and restoring forests)needs to
be developed for better forestry in India [70].
Estimation of carbon content in forest woody biomass is
important with regard to Greenhouse effect mitigation, and
regarding mandatory reporting about carbon dioxide (CO2)
emissions and removals in forestry sector for countries
which signed the Kyoto treaty. Plants in their growth
process like photosynthesis absorb CO2 from the air and in
such a manner sequester carbon through biomass, and thus
decreasing the concentration of this quantitatively most
significant greenhouse gas (GHG) in the air. For this
reason, forest stands are called carbon Pool or carbon sinks.
The carbon sequestration function of forests has
been well researched during the last 20 years, and forest
ecosystems, depending on their capacity, have been found
to be the biggest carbon sinks among all other terrestrial
ecosystems. The discussion above shows that, instead of
being linear and wholesome, „constant‟ constructs, Indian
forests (like any other tropical forests) are part of a larger,
dynamic, and ever-changing socio-political and socio-
ecological discourse and can contribute immensely in
global carbon cycle along with its trees and invasive
shrubs.
Conclusion
Our study provides relevant information on total biomass
and carbon stocks in different forest types of Doon Valley.
The results of the present study will be helpful for
understanding the patterns of carbon storage in Sal forest
types and the invasive woody species of sub-tropical
regions in other parts of India and the Globe having similar
species composition. The following are the conclusion of
the present study:
1. The mean biomass of Sal forest from Doon Valley is
507.58 Mg ha-1
and the carbon density is 238.56 MgC
ha-1
. This is higher than the previously recorded value
from similar forest in different parts of India.
2. The total volume, total biomass and total carbon stock
of Sal trees when compared with the previous studies,
found far more than in all the forest types wherever
Sal existed.
3. Non destructive method of biomass calculation
through allometric equation is found the best method
not only for trees but also for shrubs because it is less
laborious, less time consuming and more accurate.
The measured attributes like, DBH and plant height
for both Sal tree and Lantana were the best variables
to analyse the regression and to derive the allometric
equation for non-destructive biomass calculation.
4. The allometric equation (y = a + bD2
H) was found
more accurate for calculating the non destructive
biomass of Lantana from the deciduous forests of
Doon Valley
5. The mean biomass of invasive shrub Lantana from
Doon Valley forest is 8.15 Mg ha-1
and the carbon

density is 3.83 MgC ha-1
.
6. The total mean biomass of both Sal tree and Lantana
accounted of 502.80 Mg ha-1
(494.65 Mg ha-1
+ 8.15
Mg ha-1
) with the carbon density of 236.32 MgC ha-1
(232.48 MgC ha-1
+ 3.83 MgC ha-1
).
7. The periphery of the forest is heavily infested by
Lantana but a shrub level carbon sequestration was
never calculated from Doon Valley (especially an
invasive shrub) and therefore, Lantana‟s carbon
storage potential can also be used in a positive way
despite the fact that Lantana is a threat to the
biodiversity, along with the Sal forest of Doon Valley
especially when the Sal trees shed of their leaves.
The results of the present study will help the
policy-makers at both National and International levels to
find most efficient solutions to the problems that are
threatening the similar ecologically fragile regions. It is
therefore, necessary to obtain more accurate and precise
biomass estimation of Doon Valley forests in order to
improve our understanding of the role of Doon Valley
forests in the global carbon cycle.
Acknowledgements
We are thankful to the department of Botany and
National forest library, ICFRE, Dehradun for providing
both laboratory and literary facilities. We extend our thanks
to the Department of Botany, DAV (PG) College,
Dehradun, India for providing the laboratory and statistical
facility. We also thank APEX laboratory services,
Dehradun, India for helping in the soil analysis and also
thank the Forest Survey of India (FSI), Dehradun for
providing the necessary forest inventory data and the State
Forest Reports.
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Source of support: Nil; Conflict of interest: None declared

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