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This article appeared in a journal published by Elsevier. The attachedcopy is furnished to the author for internal non-commercial researchand education use, including for instruction at the authors institution
and sharing with colleagues.
Other uses, including reproduction and distribution, or selling orlicensing copies, or posting to personal, institutional or third party
websites are prohibited.
In most cases authors are permitted to post their version of thearticle (e.g. in Word or Tex form) to their personal website orinstitutional repository. Authors requiring further information
regarding Elsevier’s archiving and manuscript policies areencouraged to visit:
In the maritime state of West Bengal, situated in the
northeast coast of India, the adverse impact of salinity on the
growth of mangrove species has been documented [10,11].
Salinity, therefore, greatly influences the overall growth and
productivity of the mangroves [12]. The Indian Sundarbans
exhibits two significantly different salinity regimes due to
siltation that prevent the flow of GangaeBhagirathieHooghly
water to the central region. This has made the ecosystem a
unique test bed to observe the impact of salinity on the
biomass and allometric trait of the mangrove species.
2. Methodology
2.1. The study area
The Sundarban mangrove ecosystem covering about
10,000 km2 in the deltaic complex of the Rivers Ganga, Brah-
maputra andMeghna is shared between Bangladesh (62%) and
India (38%) and is the world’s largest coastal wetland. Enor-
mous load of sediments carried by the rivers contribute to its
expansion and dynamics.
A unique spatial variation in terms of hydrological pa-
rameters is observed in Indian part of Sundarbans. The
western region of the deltaic lobe receives the snowmeltwater
of Himalayan glaciers after being regulated through several
barrages (primarily Farakka) on the way. The central region on
the other hand, is fully deprived from such supply due to
heavy siltation and clogging of the Bidyadhari channel in the
late 15th century [13]. Such variation caused sharp difference
in salinity between the two regions [11,14]. Ten sampling
stations were selected in this geographical locale (Fig. 1). The
stations in the western region (stations 1e5) lie at the
confluence of the River Hooghly (a continuation of Gang-
aeBhagirathi system) and Bay of Bengal. In the central region,
the sampling stations (stations 6e10) were selected adjacent
to the tide fed Matla River. Study was undertaken in both
these regions through three seasons (pre-monsoon, monsoon
and post-monsoon) during 2008e2010.
In both regions, selected forest patches were even-aged
(w 9 years old during the initial year 2008). In each station,
15 sample plots (10 m � 10 m) were established (in the river
bank) through random sampling in the various qualitatively
classified biomass levels and sampling was carried out in the
low tide period.
2.2. Above-ground biomass estimation
Above-ground biomass (AGB) in mangrove species refers to
the sum total of stem, branch and leaf biomass that are
exposed above the soil.
The stem volume of five individuals from each species in
each of the 15 plots per station (n ¼ 5 individuals � 15
plots ¼ 75 trees/species/station) was estimated using the
Newton’s formula [15].
V ¼ h=6 ðAb þ 4Am þ AtÞwhere V is the volume (in m3), h the height measured with
laser beam (BOSCH DLE 70 Professional model), and Ab, Am,
and At are the areas at base, middle and top respectively.
Specific gravity (G) of the wood was estimated taking the stem
cores by boring 7.5 cm deep with mechanized corer. This was
converted into stem biomass (BS) as per the expression
BS ¼ GV. The stem biomass of individual tree was finally
multiplied by the number of trees of each species in 15
selected plots (per station) in bothwestern and central regions
of the deltaic complex and expressed in t ha�1.
The total number of branches irrespective of size was
counted on each of the sample trees. These branches were
categorized on the basis of basal diameter into three groups,
viz. <6 cm, 6e10 cm and >10 cm. The leaves on the branches
were removed by hand. The brancheswere oven-dried at 70 �Covernight in hot air oven in order to remove moisture content
if any present in the branches. Dry weight of two branches
from each size group was recorded separately using the
equation of Chidumaya [16].
Bdb ¼ n1bw1 þ n2bw2 þ n3bw3 ¼ S nibwi
where Bdb is the dry branch biomass per tree, ni the number of
branches in the ith branch group, bwi the average weight of
branches in the ith group and i ¼ 1, 2, 3, ., n are the branch
groups. The mean branch biomass of individual tree was
finally multiplied with the number of trees of each species in
all the 15 plots for each station and expressed in t ha�1.
For leaf biomass estimation, one tree of each species per
plot was randomly considered. All leaves from nine branches
(three of each size group) of individual trees of each species
were removed and oven dried at 70 �C and dryweight (species-
wise) was estimated. The leaf biomass of each tree was then
calculated by multiplying the average biomass of the leaves
per branch with the number of branches in that tree. Finally,
the dry leaf biomass of the selected mangrove species (for
each plot) was recorded as per the expression:
Ldb ¼ n1Lw1N1 þ n2Lw2N2 þ.niLwiNi
where Ldb is the dry leaf biomass of selectedmangrove species
per plot, n1 . ni are the number of branches of each tree of
three dominant species, Lw1 . Lwi are the average dry weight
of leaves removed from the branches and N1 . Ni are the
number of trees per species in the plots. This exercise was
performed for all the stations in each region and the results
were finally expressed in t ha�1.
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2.3. Below-ground biomass estimation
Below-ground biomass (BGB) in this study refers to root
biomass, which excludes the pneumatophores, prop roots and
stilt roots that are exposed above the soil. An excavation
method [17] was used to estimate root biomass of the same
trees that were selected for above-ground biomass (AGB) es-
timate. According to our observation, very few roots in our
sampling plotswere distributed deeper than 1m in sediments.
We also found canopy diameter of these trees was usually
smaller than 2 m. Most roots of the selected species were
distributed within the projected canopy zone. Therefore, for
below-ground biomass (BGB, referring to root biomass in this
study), we excavated all roots (of 1 trees/species/station) in
1 m depth within the radius of 1 m from the tree center, and
thenwashed the roots.We excavated all the sediments within
the sampling cylinder (2 m in diameter � 1 m in height) and
washed them with a fine screen to collect all roots. The roots
were sorted into four size classes: extreme fine roots (diam-
eter <0.2 cm), fine roots (diameter 0.2e0.5 cm), small roots
(diameter 0.5e1.0 cm), and coarse roots (diameter >1 cm). We
did not separate live or dead roots. The roots after thorough
washing were oven dried to a constant weight at 80 � 5 �C and
biomass was estimated for each species. The method is a
destructive one and therefore we estimated the root biomass
of those trees that were almost on the edge of the river bank
facing erosion. In 2009, we evaluated the below ground
biomass of uprooted trees due to severe super cyclone, Aila in
the lower Gangetic delta.
2.4. Salinity
The surface water salinity was recorded by means of an op-
tical refractometer (Atago, Japan) in the field and cross-
checked in laboratory by employing MohreKnudsen method
[18]. The correction factor was found out by titrating the silver
nitrate solution against standard seawater (IAPO standard
seawater service Charlottenlund, Slot Denmark, chlorini
ty ¼ 19.376 psu). The average accuracy for salinity (in
connection to our triplicate sampling) is �0.42 psu
(1 psu ¼ 1 g kg�1) [19].
2.5. Statistical analysis
Spatial and temporal differences of aquatic salinity and
biomass of selectedmangrove specieswere evaluated through
ANOVA. The influence of aquatic salinity on mangrove
biomass was assessed by correlation coefficient (r) values
Fig. 1 e Map showing location of the sampling stations.
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computed separately for each species and region (western/
central Indian Sundarbans). Finally the species-wise allome-
tric equations for each region were determined (n ¼ 90 per
species) as a function of most easily measured parameter
(DBH), considering total biomass (TB) as dependent variable.
The precision of the model in predicting individual tree
biomass value was determined by the magnitude of the R2
value of the simple regression and percentage difference of
predicted and observed dry weight biomass values of indi-
vidual trees. All statistical calculations were performed with
SPSS 9.0 for Windows.
3. Results
3.1. Relative abundance
A total of seventeen species of mangroves were recorded in
the selected plots of the study area. It is observed that stations
4 (Lothian island), 5 (Prentice island) and 7 (Sajnekhali)
exhibited relatively more species diversity compared to other
stations. This may be attributed to magnitude of anthropo-
genic pressure, intense human activities or salinity profile of
the area. On the basis of relative abundance the species Son-
neratia apetala, E. agallocha and Avicennia alba were found
dominant in the study site (Table 1) constituting 48.41% of the
total species. The selected species were w11 years old during
our last phase of sampling in 2010, but high salinity in the
central region probably stunted the growth of S. apetala.
3.2. Salinity
In the western region, the salinity of surface water ranged
from 3.65 psu (at station 1 during monsoon, 2010) to 29.10 psu
(at station 4 during pre-monsoon, 2008) and the average
salinity was 16.38 � 7.53 psu. In the central region, the lowest
salinity was recorded at station 6 (3.12 psu during monsoon,
2008) and the highest salinity was recorded at station 9
(30.02 psu during pre-monsoon, 2010) with an average value of
17.55 � 7.63 psu (Tables 2e4). The relatively lower salinity in
the western region may be attributed to Farakka barrage that
release fresh water on regular basis through Gang-
aeBhagirathieHooghly River system. The central region, on
contrary does not receive the riverine discharge due to
massive siltation of the Bidyadhari River that blocks the fresh
water flow in the Matla River eventually making it a tide fed
river.
3.3. Above-ground biomass
The AGB of the mangrove species was relatively higher in the
stations of the western region (stations 1e5) compared to the
central region (stations 6e10) (Tables 2e4). It is observed that
the average AGB of the three dominant species in the stations
of western region are 71.08, 71.99 and 82.88 t ha�1 during pre-
monsoon 2008, 2009 and 2010 respectively; 81.69, 83.31 and
93.81 t ha�1 during monsoon 2008, 2009 and 2010 respectively
and 90.59, 95.12 and 102.85 t ha�1 during post-monsoon, 2008,
2009 and 2010 respectively. In the stations of central region
the values are 51.02, 58.11 and 67.72 t ha�1 during pre-
monsoon 2008, 2009 and 2010 respectively; 62.96, 67.87 and
79.92 t ha�1 during monsoon 2008, 2009 and 2010 respectively
and 72.91, 82.73 and 90.09 t ha�1 during post-monsoon 2008,
2009 and 2010 respectively. Worthy of mention here is that in
AGB of selected species, the stem constitutes 61%e64%, the
branch constitutes 23%e27% and 12%e14% of AGB is allocated
to leaf [11].
3.4. Below-ground biomass
The BGB comprising of the root portion of the mangrove was
higher in the western region compared to the central region.
Table 1 e Density of mangrove species (mean of 15 plots/station) in the study area; figures within bracket indicate therelative abundance in each station.
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predicted biomass, it appears that there is negligible deviation
of the model between the western and central regions. This is
contrary to the findings of Clough et al. [5] who found different
relationships in different sites, although Ong et al. [34] re-
ported similar equations applied to two different sites while
working on Rhizophora apiculata. This issue is important for
practical uses of allometric equations. If the equations are
segregated by species and site, then different equations
have to be determined for each site. In the present
study, althoughmodels Sw, Sc,Aw, Ac, Ew and Ec were developed
for different species and regions of Indian Sundarbans, the
estimation of biomass produced from thesemodels only differ
by 0.25e9.91%. Such a good agreement between these two
estimates (observed vs. predicted) supports the conclusion
that allometric regression models produced from the same
species of similar aged trees and similarmethodswill not vary
much.
The present study also confirms the tolerance of A. alba
and E. agallocha to higher salinity. The significant negative
correlation values between S. apetala biomass and ambient
salinity reflects the sensitivity of the species to high salinity.
Several mangrove tree species reach an optimum growth at
salinities of 5e25 psu of standard seawater [9,26,30,35,36]. The
pigments, being the key machinery in regulating the growth
and survival of the mangroves require an optimum salinity
range between 4 and 15 psu for proper functioning [35,37]. S.
apetala, the fresh water loving mangrove species prefers an
optimum salinity between 2 and 10 psu [10] and hence could
not accelerate the biomass with increasing salinity unlike A.
alba and E. agallocha.
5. Conclusion
Finally we list a few of our core findings:
- The Indian Sundarbans sustains luxuriant mangrove vege-
tation and a total of 17 species in association were recorded
from the plots of selected stations.
- Contrasting salinity profile exists in the deltaic complex,
which is primarily regulated by barrage discharge and
siltation.
- The waters in the western river (Hooghly) are freshening
due to barrage discharge, but the central river (Matla) and its
adjacent habitat is hypersaline owing to siltation that has
completely blocked the fresh water supply in the zone.
- The hyposaline habitat promotes the growth of S. apetala,
whereas A. alba and E. agallocha are adapted in the central
Indian Sundarbans in the hypersaline environment.
- In the above ground structures of the selected species, the
allocation of biomass ranges between 61 and 64% to stem,
23e27% to branch and 12e14% to leaf.
- The total biomass (TB) constituting both AGB and BGB of all
the three selected species is greater in the western region
than the central region.
- Common allometric equations may be used for same spe-
cies in different zones to predict the biomass from easily
measured variable DBH.
- It is clear that the future of Sundarban mangroves (partic-
ularly in the central region) hinges upon the efficiency of
managing the limited fresh water resources coupled with
appropriate selection of species for afforestation in context
to rising salinity. A. alba and E. agallocha are better suited in
the zone if the sea level rise due to climate change is
considered.
Acknowledgments
The financial assistance from the Ministry of Earth Science,
Govt. of India (Sanction No. MoES/11-MRDF/1/34/P/08, dated
18.03.2009), is gratefully acknowledged.
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