CHAPTER IV
COMMUNITY STRUCTURE
INTRODUCTION
Communities are recurrent organized system of organism responding in a
related manner to changes in the environment (Legendre and Legendre, 1978).
Due to the concomitant and continuous interaction taking place between
individuals of different species and between the individuals and the environmental
factors, the community remains dynamic.
The changes taking place in the
biodiversity is a gauge of the structure of the community, whereas the changes in
production reflect its function. For aquatic ecosystems, indices of diversity are
basically an approach to biological quality, through the structure of the community
(Ismael and Dorgham, 2003). The conventional types of diversity indices such as
Shannon’s and Weaver’s diversity index (1963), Margalef’s richness index (1958)
and Pielou’s evenness index (1975) do not take into account whether the
assemblage within the same community comprises of species which are closely
related to each other taxonomically or whether they are only distantly related.
These indices are heavily dependent on sample size/effort and they do not reflect
the phylogenetic diversity. There is also no statistical framework for testing the
departure from expectation and the response of species richness to environmental
degradation is not monotonic. The newly introduced diversity measures (Warwick
and Clarke, 1995) do not have these demerits. Warwick and Clarke (1995 and
1998) and Clarke and Warwick (1998, 1999 and 2001) have proposed indices of
taxonomic diversity that take into account the “weighted” taxonomic differences
between species.
Very few investigations on phytoplankton diversity in Kerala have dealt
with the recent measures to understand the community structure.
Hence an
attempt is made in the present study to discriminate coastal brackish water
environments of Kodungallur using both conventional and recent methods of
diversity analysis.
91
REVIEW OF LITERATURE
A variety of literature is available on the relationship between
phytoplankton diversity and community function (Krebbs, 1994; Duarte et al.,
2006).
According to Faith (1992) and Mace et al. (2003) the biodiversity
contribution of a locality may depend less on conventional species counts and
more on the phylogenetic diversity. von Euler and Svesson (2001) interpreted the
phylogenetic structure of an assemblage as a measure of functional quality.
Ismael and Dorgham (2003) have used ecological tools for assessing pollution.
Their study revealed that the combination of univariate and multivariate analysis
provide a promising tool for the characterization of phytoplankton dynamics under
stress conditions.
Heino (2005) has studied the relationship between species
richness and taxonomic distinctness in freshwater organisms and underlined the
importance of considering a set of different measures in the assessment of
community-level biodiversity, as well as considering this variability in
determining anthropogenic effects in freshwater ecosystems.
Detailed reports are available on the spatial and temporal changes in the
phytoplankton indices in estuaries of peninsular India (Chandran, 1985; Devassy
and Goes, 1988; Sreekumar, 1996; Vareethiah and Haniffa, 1998; Akram, 2002;
Krishnakumari and John, 2003 and Joseph, 2006). Khan (2005) has discussed the
statistical methods used currently in the assessment of biodiversity of corals and
associated organisms. Jacob et al. (2008) have observed the species richness and
species dominance to be higher during the post monsoon season in the Cochin
backwaters.
93
MATERIALS AND METHODS
To provide information on community structure of the brackish water
bodies of Kodungallur, both traditional measures [e.g. Shannon’s diversity index
(1963), Margalef’s richness index (1958), Pielou’s evenness index (1966)] and the
recent measures such as average taxonomic distinctness index ∆+ (Delta+), total
phylogenetic diversity index (SΦ+) and variation in taxonomic distinctness Λ+
(Lamda+) have been used in the present study. The PRIMER (Plymouth Routines
in Multivariate Ecological Research) program was used to calculate traditional and
new indices.
1. Univariate Data Analyses - Traditional Measures
1.1.
Species Richness: Margalef index (d): This index is weighted towards
species richness and is the measure of the total number of species for a given
number of individuals.
Margalef’s index d = (S-1) / log N
Where,
d = Species richness
S = Total number of species in the community
N = Total number of individuals in the community
1.2.
Species Diversity: Shannon diversity index (H'): It measures how rare or
common the species are, in a community. It takes into account the number of
species and the evenness of species and is calculated as
H' = Σipiln (pi)
Where, pi is the proportion of the individuals in the total sample belonging to
the species i and ln is the natural logarithm.
1.3.
Species Evenness: Pielou’s evenness index (J'): It expresses how evenly
the individuals are distributed among the different species. It is calculated as
J' = H'/ln S, Where ln S = H' max
H' max (the maximum value of Shannon diversity) is what H' would be if all
the species in the community had an equal number of individuals; S is the
number of species.
2. Univariate Data Analyses - Recent Measures
2.1.
Species Abundance (Dominance Curve): This method adopts the ranking of
species based on their importance in terms of abundance.
The ranked
abundances, expressed as percentage of the total abundance of all species, are
plotted against the relevant species rank.
95
2.2.
Average Taxonomic Distinctness (AvTD, ∆+): It is the average taxonomic
distance apart of every pair of individual in the sample chosen at random,
along the taxonomic tree drawn following the standard Linnaean classification,
conditional that they must belong to different species.
It is the discrete
distance between every pair of individual.
2.3.
Total Phylogenetic Diversity (SΦ+): Phylogenetic diversity has been defined
as the minimum total length of all the phylogenetic branches required to span a
given set of taxa on the phylogenetic tree.
2.4.
Variation in Taxonomic Distinctness (VarTD/Λ+): It estimates how similar
the upper levels (e.g. orders, classes) are, between samples (Clarke and
Warwick, 2001). To analyse data for VarTD a master list was prepared. The
master list represented the expected value for a defined phytoplankton group.
The master list was based on a compilation of species lists from the
investigated area. This list contained a total of 272 species that aggregated into
five levels, i.e., genera, families, classes, orders and divisions.
2.5.
Funnel Plots: Funnel plot, which measures the distinctness (both average
taxonomic distinctness, ∆+ and variation in taxonomic distinctness, Λ+) based
on presence/absence data of the species in the study stations, was drawn by
testing the distinctness of a sample of m species, from the distinctness value
obtained by taking m species from the master list (Clarke and Warwick, 1998).
The null hypothesis assumes that each sample contains species randomly
selected from the global list and that it should thus fall within the 95%
confidence intervals. Since the theoretical mean remains constant while the
96
variance decreases as number of species m increases, the 95% confidence
intervals take the form of a “funnel”.
3. Multivariate Methods
In order to assess the consistent changes in the abundance of phytoplankton
in various stations, multivariate analyses were conducted. Multivariate analyses
are accommodated under two collective terms, classification and ordinations.
Commonly used classification method is cluster analysis. It is often a satisfactory
coefficient for biological data on community structure (Clarke and Warwick,
2001). In ordination techniques, data were subjected to cluster analysis and nonmetric multidimensional scaling (MDS).
3.1.
Cluster Analysis:
Cluster analysis was done to find out the similarities
between stations. Bray-Curtis similarity index (Bray and Curtis, 1957) was
applied to species-abundance data to group the stations with similar
community composition. In PRIMER, abundance of phytoplankton in each
station was standardized and square root transformed prior to the calculations
of similarity matrices using the Bray-Curtis similarity coefficient.
3.2.
MDS (Non Metric Multi Dimensional Scaling): This method was proposed
by Sheppard (1962) and Kruskal (1964) and was used to find out the
similarities between each pair of entities to produce a ‘map’, which would
ideally show the interrelationships of all. This map, or configuration in a
specified number of dimensions visually displays the ranking of the similarity
matrix with the greatest ‘goodness of fit’ or lowest stress. In addition, it
combines the cluster results with ordination in order to further investigate
97
whether the combination was an effective way of checking the sufficiency and
mutual consistency of both representations. The data from the Bray-Curtis
similarity coefficient matrix were used to construct the ‘map’. The data were
ordinated using the MDS program in PRIMER. The stations were plotted on a
2 dimensional non Metric Multi Dimensional Scaling (MDS) based on the
similarity matrix.
98
RESULTS AND DISCUSSION
Seasonal variations in community pattern and diversity measures were
analysed for the ten stations investigated.
1. Univariate Data Analysis - Traditional Measures
1.1. Species richness: Margalef index (d): The seasonal mean of this diversity
index is depicted in Fig. 4.1a. The highest value for Margalef index recorded
during the premonsoon was 1.64 ± 0.78 (Station 7) and the least was 0.45 ± 0.53
(Station 4) and the mean value of this season was 0.88 ± 0.22 (Table 4.1). The
corresponding maximum and minimum range during the monsoon season was
2.14 ± 0.58 (Station 8) and 0.34 ± 0.16 (Station 4) respectively and the mean value
was 1.20 ± 0.32 (Table 4.1). During the postmonsoon, the highest value was 3.59
± 1.296 (Station 1) and the least was 1.29 ± 0.80 (Station 3) with an average of
1.97 ± 0.27 (Table 4.1). The highest annual mean was 2.163 ± 1.56 (Station 1)
and the minimum value was 0.71 ± 0.69 (Station 4) (Table 4.2). There was
significant variation in the species richness between stations (ANOVA, P<0.05)
and between seasons (ANOVA, P<0.001) (Table 4.3).
The seasonal mean values indicated that the oligo/mesohaline Stations 1, 7
and 8 had higher values of richness and meso/polyhaline Stations 3 and 4, located
on the Canoli canal, had lower richness values. The annual average of the stations
indicated that Station 1 was the richest with an annual value of 2.16 ± 1.56. The
Stations 4, 5 and 6 showed comparatively lower index of species richness. Station
3, with input from the slaughter house also had the low values of 0.97 ± 0.63
(Table 4.2). The species richness values were high in the postmonsoon season,
indicating that this season was the most favourable for the species abundance.
This observation agrees to that of Paniadima et al. (2006) from the Chinnathurai
coast.
1.2. Species Diversity: Shannon‘s diversity index (H'): The seasonal values of
Shannon’s diversity index is given in Fig. 4.1b. This ranges from 2.78 ± 1.14
bits/individuals (Station 7) to 1.10 ± 1.06 bits/individuals (Station 4) with a mean
of 1.96 ± 0.22 bits/individuals during the premonsoon (Table 4.1). During the
monsoon season the highest value recorded was 3.54 ± 0.31 bits/individuals
(Station 8) and the least value was 1.62 ± 0.81 bits/individuals (Station 7) (Fig.
4.1b) and the mean was 2.36 ± 0.24 bits/individuals (Table 4.1). The maximum
value recorded during the postmonsoon was 3.93 ± 0.43 bits/individuals (Station
1) minimum was 2.35 ± 1.03 bits/individuals (Station 4) (Fig. 4.1b) and mean 3.20
± 0.33 bits/individuals (Table 4.1). The highest annual mean value was recorded
100
at Station 8 (3.33 ± 0.84 bits/individuals), the least annual mean was at Station 4
(1.58 ± 1.00 bits/individuals). Station 6 and Station 3 also exhibited low values
(Table 4.2).
The diversity as measured by the Shannon index H' showed
significant difference between stations (ANOVA, P<0.0I). Similar variation was
exhibited between seasons also (P<0.00I) (Table 4.4).
Balloch et al. (1976) considered the diversity index (H') to be a suitable
indicator for water quality, but Hughes (1978) was of the view that this index,
although valuable for community structure, alone was not enough for assessing
environmental quality. However, applying Margalef’s (1968) interpretation, to the
phytoplankton diversity index during the present study, it could be assumed that,
Stations 1, 8 and 10 which have diversity index >3 are in the later stages of
succession. Also, as Shannon’s index of 1 to 2.5 units indicates eutrophication, it
can also be concluded that all the stations investigated have undergone
eutrophication.
It has also been established that the value of the diversity index of a
community will be higher in less polluted waters (Gao and Song, 2005). Hence it
is perceived that the Stations 1, 8 and 10 are comparatively less polluted and the
lower diversity recorded at Station 4 and 6 may be due to the highly polluted
condition existing there owing to retting.
The high diversity during the
postmonsoon indicates that this season is the most suitable for plankton growth,
offering the most favourable salinity regime.
The observation of maximum
diversity during the postmonsoon agrees to the reports of De et al. (1994) from
Hubli Estuary, Illangovan (1987), Vareethiah and Haneefa (1998) from Vellar
101
Estuary and Krishnakumari and John (2003) from Mandovi-Zuari Estuary.
Vareethiah and Haniffa (1997) have recorded phytoplankton diversity ranging
from 1.72 to 5.01 bits/individual.
Chandran (1985) reported a diversity index ranging from 0.3 to 4.3
bits/individual with higher values during summer and premonsoon in Vellar
Estuary. Diversity indices ranging from 0.49 to 4.2 bits/individual in surface
waters at Mandovi and 1.1 to 4.1 bits/individual in Zuari has been reported
(Devassy and Goes, 1988).
1.3. Species Evenness:
Pielou’s evenness index (J'): The highest and least
values of species evenness Pielou‘s index J' recorded during the premonsoon were
0.90 ± 0.04 in Station 8 and 0.55 ± 0.43 in Station 4 (Fig. 4.2a). Mean evenness
value during the premonsoon was 0.74 ± 0.12 (Table 4.1). In the monsoon season,
maximum evenness observed was 0.90 ± 0.06 (Station 8) and minimum evenness
was 0.65 ± 0.18 (Station 7) (Fig. 4.2a). The mean value of the monsoon was 0.79
± 0.07 (Table 4.1). During the postmonsoon season the highest observed species
evenness value was 0.92 ± 0.02 (Station 8) and the least was 0.74 ± 0.25 (Station
7). Station 4 also had a similar range of evenness (0.74 ± 0.16) (Fig. 4.2a). The
mean value of this season was 0.84 ± 0.08 (Table 4.1).
Annual averages of various stations portray Station 7 as having the least
evenness value (0.71 ± 0.20) and Station 8 having the highest (0.90 ± 0.04) (Table
4.2).
102
There was no significant variation in species evenness between stations
(ANOVA, P>0.05), however, significant variation between seasons was observed
(ANOVA, P<0.05) (Table 4.5).
The evenness values observed during the present investigation were
generally >0.70, the highest seasonal value recorded being 0.90 at Station 8. The
higher values were recorded during the postmonsoon seasons.
According to
Pielou (1984), values closer to 1 indicate very even abundance of species. A
higher number of species and more even distribution increase the diversity. This
is very much true in the present study where Stations 1, 8 and 10 with higher
diversity also show higher evenness values. The variation in evenness is attributed
to the impact of ever fluctuating estuarine environment on the plankton
distribution by Sreekumar (1996). Whereas, Patrick (1973), opines that evenness
is the result of competition under optimum conditions or may be a response to
unfavourable conditions. Vareethiah and Haniffa (1998) are of the view that
absence of blooms could have prompted higher evenness values. Chandran (1985)
has recorded Evenness index as low as 0.113 during bloom conditions.
2. Univariate Data Analyses - Recent Measures
2.1. Species Abundance (Dominance Curve):
The dominance curve for the
different stations is depicted in Fig. 4.4. Except for the Stations 4, 5 and 6, which
exhibited higher dominance and lower diversity, the k-Dominance curves of other
stations were almost similar or overlapping. The cumulative dominance of the
Stations 4, 5 and 6 reached simultaneously cumulative 100%.
According to
Clarke and Warwick (2001), k-dominance curves are cumulative ranked
103
abundance, plotted against species rank or log transformed species rank. The most
elevated curves are considered to have the lowest diversity. In the present analysis
it is obvious that the cumulative dominance in the Stations 4, 5 and 6 reached
simultaneously cumulative 100% and are the most elevated curves of the
dominance plot (Fig. 4.4). Hence it can be concluded that these stations have low
species diversity and higher dominance of a few phytoplankton.
When a community is disturbed by pollution, it is the opportunistic ones
which are more preferably established than the conservative species.
These
opportunistic species may be fewer in number, but higher in dominance. Species
such as Nitzschia closterium, Synedra ulna, Bacillaria paradoxa, Protoperidinum
stenii and Aphanothece microspora were dominant in these stations and may be
considered as opportunistic species. The differences in the cumulative dominance
of the other stations were not strong due to higher species diversity. The curve for
less polluted stations (Station1) is flatter due to low dominance.
2.2. Average Taxonomic Distinctness (AvTD, ∆+): This is a measure of
biodiversity based on taxonomic distance between species, i.e., describes how
closely related the species are to each other. A community consisting of a group
of closely related species is believed to have a lower diversity than ones that have
the same number of distantly related taxa (Clarke and Warwick 1998). The value
of the Average taxonomic distinctness ∆+ (delta +) observed at Station 7 (85.97 ±
11.30) was the highest for the premonsoon and the least was 41.78 ± 39.21
(Station 4) (Fig. 4.2b). During the monsoon season the maximum value of this
index was 96.53 ± 6.94 (Station 4) and the minimum value was 62.01 ± 11.27
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(Station 10) (Fig. 4.2b). The ∆+ ranged from 85.01 ± 3.63 (Station 9) to 69.97 ±
13.23 (Station 4) during the postmonsoon (Fig. 4.2b).
The mean average
taxonomic distinctness ∆+ calculated for all the stations was 68.10 ± 10.57, 82.27
± 5.00 and 76.18 ± 4.57 during premonsoon, monsoon and postmonsoon
respectively (Table 4.1).
The annual mean was highest 87.05 ± 32.02 (Station 7) and the least was
65.53 ± 10.71 (Station 4) (Table 4.2). There was no significant variation in
Average taxonomic distinctness ∆+ between stations (ANOVA, P>0.05), but
significant variation between seasons was observed (ANOVA, P<0.05)
(Table 4.6).
Higher average taxonomic distinctness (∆+) values in Stations 1, 2, 8 and 9
suggest the availability of large ecological niches with low environmental stress,
allowing the establishment of species populations with a high taxonomic diversity
and varied biological requirements. McCann (2000) is of the view that stability of
an ecosystem depends on the ability of the community to contain species or
functional groups that are capable of differential response. At the same time, as
taxonomic diversity is related to trophic diversity; the observed reduction in AvTD
at the retting stations (Stations 4 and 6) can represent a loss of functionality of the
phytoplankton assemblage in this station and it may affect the stability of the
water bodies. ∆+ value was high in Station 4 during the monsoon season and
species recorded viz. Scenedesmus obliquus, Nitzschia closterium, Lepocinclis
fusiformis, Trachelomonas superba, T. volvocina and Protoperidiniun steinii
105
belonged
to
four
different
classes
of
algae,
namely
Chlorophyceae
Bacillariophyceae, Euglenophyceae and Pyrrophyceae.
2.3. Total
Phylogenetic Diversity (SΦ+): The calculated highest total
phylogenetic diversity during the premonsoon was 754.17 ± 257.25 (Station 7)
and the least recorded was 241.67 ± 171.32 (Station 4) (Fig. 4.3a). During the
monsoon season the total phylogenetic diversity ranged from 862.5 ± 214.90
(Station 8) to 295.83 ± 115.77 (Station 7). During the postmonsoon season, the
highest value was 1283.333 ± 512.257 (Station 1) and the least was 541.67 ±
256.22 (Station 4) (Fig. 4.3a).
The averages of three seasons, premonsoon,
monsoon and postmonsoon were 431.66 ± 80.21, 555 ± 83.00 and 810.42 ± 118.06
respectively (Table 4.1). Annual averages indicated that for the Stations 4 and 6,
which are highly exposed to coir retting, Station 3 exposed to slaughterhouse
waste and Station 5 to municipal waste, the total phylogenetic diversity (SΦ+) is
generally low and is in the order of 362.50 ± 214.4, 431.94 ± 136.23, 470.83 ±
243.93 and 536.11 ± 207.66. Total phylogenetic diversity (SΦ+) was highest at
Station 1 (806.94 ± 509.73). There was significant variation between stations
(P<0.05) and also between seasons (P<0.001) (Table 4.7).
The seasonal mean SΦ+ values had a trend similar to that of ∆+ values.
Stations 1, 7 and 8 had higher values of SΦ+ and Stations 4 and 6 had lower
values. The annual averages indicated that, the total phylogenetic diversity (SΦ+)
is generally low at the Stations 3, 4, 5 and 6. Total phylogenetic diversity, (SΦ+)
was the highest at Station 1, followed by Stations 8, 9 and 10. Faith (1992 and
1994) regards larger PD values to correspond to greater expected diversity. von
106
Euler and Svesson (2001) have interpreted the phylogenetic structure of an
assemblage to be a measure of functional quality. In the present investigation,
higher total phylogenetic diversity (SΦ+) values were observed during the
postmonsoon season. SΦ+ values were also significantly correlated with diversity
indices (Table 4.10) thereby agreeing to the views of Faith (1992 and 1994) and
von Euler and Svesson (2001).
2.4. Variation in Taxonomic Diversity (VarTD, Λ+):
The highest value of
variation in taxonomic diversity Λ+ (Lambda +) during the premonsoon was
751.95 ± 577.60 (Station 9) and the least value was 319.56 ± 250.66 (Station 6)
(Fig. 4.3b). During the monsoon, the variation in taxonomic diversity (Λ+) was
highest in Station 1 (934.617 ± 247.33) and least in Station 4 (241.127 ± 482.25)
(Fig. 4.3b). During the postmonsoon, the values ranged from 728.81 ± 156.09
(Station 1) to 496.68 ± 243.02 (Station 3) (Fig. 4.3b). The seasonal average of Λ+
for the brackish waters of Kodungallur was 442.06 ± 128.31 for premonsoon,
552.08 ± 104.64 in the monsoon and 616.19 ± 71.64 in postmonsoon (Table 4.1).
Annual average of each station indicated that Stations 4 and 5 had the least
values 394.37 ± 404.67 and 436.99 ± 250.33 and Stations 8 and 1 had the highest
values 668.03 ± 250.44 and 661.11 ± 359.43 (Table 4.2).
No significant
difference was observed between stations and between seasons (ANOVA, P>0.05)
(Table 4.8).
The variation in taxonomic distinctness (VarTD), also called Lambda+,
emphasises how similar the upper levels (e.g. orders, classes) are between
samples.
According to Mouillot et al. (2005) “Variation in taxonomic
107
distinctness” is more related to the environmental variability. High VarTD means
high eutrophication and high environmental variability and human impact. The
funnel plot for Λ+ reveals that Stations 2, 3, 4, 5 and 9 lie above the master species
list mean Λ+ line (dotted) suggesting an overall increase in complexity based on
low numbers of species widely dispersed in higher taxa.
2.5. Funnel Plots: In funnel plots, both taxonomic distinctness (∆+) and variation
in taxonomic diversity (Λ+) values of each study stations were compared to the
theoretical mean. Most stations had lower distinctness values than theoretical
mean obtained from the master species list. Average taxonomic distinctness (∆+)
for all stations, except for Station 7 was on the lower part of the confidence funnel
(Fig. 4.5). Stations 1, 2, 3, 4, 8 and 9 have fallen within the 95% confidence
funnel. However, the station affected by retting (Station 6) and the estuarine site
(Station 10) fell extremely below the confidence funnel due to the less diverse
community.
Variation in taxonomic diversity (Λ+) was above the 95% mean confidence
funnel, at all stations, except in Station 7 (Fig. 4.6). The station identified for
retting (Station 6) is positioned extremely above all stations and has significantly
fallen out of the funnel, in which 95% simulated values lie, suggesting a departure
from the expectation. Stations 1 and 8 also have fallen out side the confidence
funnel, but to a lesser extent.
3. Multivariate Methods
3.1. Cluster Analysis: The results of the comparison of the community at the
species level using cluster analysis based on the Bray Curtis index of similarity is
108
given in Table 4.9. Stations 2 and 3 had a similarity value of 46.57, whereas
between Stations 7 and 5 the similarity value was just 9.66. From the dendrogram
(Fig 4.7), it is apparent that Stations 1, 7 and 8 can be grouped together and
Stations 2, 3, 4 and 6 form another cluster. Stations 9 and 10 form a third group.
Stations 1, 7 and 8 which are grouped together in the dendrogram (Fig. 4.7)
are the oligohaline stations, Stations 2, 3, 4 and 6 forming the other cluster are
stations located on the Canoli canal and are affected to varying degree by
anthropogenic activities. The third group comprising of Stations 9 and 10 though
belong to different water bodies are euhaline stations, the former being close to the
latter (estuarine station).
3.2. MDS (Non Metric Multi Dimensional Scaling): The ordination depicted
from the similarity matrix (Fig. 4.8) revealed the same pattern as seen in the
cluster analysis, with Station 5 being apart from the other groups. The stress value
(0.1) obtained in MDS indicates that the data are fairly well represented. The
retting stations (Stations 4 and 6) and the slaughterhouse station (Station 3)
occupied left bottom side of the map. The extreme bottom of the map was
occupied by the brackish water site (Station 9) and estuarine site (Station 10).
109
Table 4.1 Variation in the seasonal mean of diversity indices of phytoplankton
in the brackish waters of Kodungallur
Diversity
Indices
Pre Monsoon
Monsoon
Post Monsoon
M
Sd
M
Sd
M
Sd
d`
0.88
0.22
1.20
0.32
1.97
0.27
H`
1.96
0.22
2.36
0.24
3.20
0.33
J`
0.74
0.12
0.79
0.07
0.84
0.08
Delta+
68.10
10.57
82.27
5.00
76.18
4.57
sPhi+
431.67
80.21
555.00
83.00
810.42
118.06
lamda+
442.06
128.31
552.09
104.64
616.19
71.64
Table 4.2 Variation in the annual mean of diversity indices of phytoplankton in
the brackish waters of Kodungallur
J`
H`
Delta+
sphi+
Lambda+
Station
d`
M
Sd
M
Sd
M
Sd
M
Sd
M
Sd
M
Sd
1
2.16
1.56
0.82
0.1
3.04
1.08
73.59
13.89
806.94
509.73
661.11
359.43
2
1.36
1.13
0.81
0.17
2.47
1.28
82.46
11.35
605.56
351
501.71
240.06
3
0.97
0.63
0.82
0.12
2.21
0.97
74.37
15.11
470.83
243.93
482.28
322.54
4
0.71
0.69
0.75
0.18
1.58
1
69.43
32.02
362.5
214.4
394.37
404.64
5
1.1
0.58
0.74
0.2
2.27
0.92
73.32
15.72
536.11
207.66
436.99
250.33
6
0.96
0.46
0.76
0.2
2.13
0.84
70
14.61
431.94
136.23
561.94
306.86
7
1.32
1.06
0.71
0.2
2.27
1.33
87.05
7.31
633.33
367.35
540.02
318.51
8
1.92
0.77
0.9
0.04
3.33
0.84
74.96
14.8
769.44
262.55
668.03
250.44
9
1.5
0.85
0.78
0.19
2.67
1
84.43
8.77
694.44
261.92
658.22
381.77
10
1.5
0.7
0.87
0.04
3.08
0.62
65.53
10.71
679.17
275.25
463.13
206.86
Table 4.3 ANOVA of seasonal variation in Margalef's index d in the
selected sites of Kodungallur
Source of
Variation
SS
df
MS
F
P-value
F crit
Stations
5.400418
9
0.600046
2.638003
0.038144
2.456282
Seasons
6.377602
2
3.188801
14.01903
0.000214
3.554561
Error
4.094322
18
0.227462
Total
15.87234
29
Table 4.4 ANOVA of seasonal variation in Shannon's diversity index H'
in the selected sites of Kodungallur
Source of
Variation
SS
df
MS
F
P-value
F crit
Stations
7.494608
9
0.832734
3.944952
0.006385
2.456282
Seasons
8.037153
2
4.018577
19.0374
3.62E-05
3.554561
Error
3.799594
18
0.211089
Total
19.33136
29
Table 4.5 ANOVA of seasonal variation in Pielou's evenness index J' in
the selected sites of Kodungallur
Source of
Variation
SS
df
MS
F
P-value
F crit
Stations
0.126533
9
0.014059
2.445466
0.05082
2.456282
Seasons
0.051664
2
0.025832
4.493244
0.02613
3.554561
Error
0.103483
18
0.005749
Total
0.28168
29
Table 4.6 ANOVA of seasonal variation in Average taxonomic distinctness
in the selected sites of Kodungallur
Source of
Variation
SS
df
MS
F
P-value
F crit
Stations
1650.762
9
183.418
2.038023
0.094929
2.456282
Seasons
1843.025
2
921.5125
10.23926
0.001073
3.554561
Error
1619.963
18
89.99796
Total
5113.750
29
Table 4.7 ANOVA of seasonal variation in Total phylogenetic diversity in
the selected sites of Kodungallur
Source of
Variation
SS
df
MS
F
P-value
F crit
Stations
579815.4
9
64423.93
2.731094
0.033273
2.456282
Seasons
746334.5
2
373167.25
15.81951
0.000108
3.554561
Error
424603
18
23589.06
Total
1750753
29
Table 4.8 ANOVA of seasonal variation in Variation in taxonomic
diversity in the selected sites of Kodungallur
Source of
Variation
SS
df
MS
F
P-value
F crit
Stations
263814.21
9
29312.6903
1.0300689
0.454128
2.45628229
Seasons
155124.67
2
77562.3358
2.725596
0.092463
3.55456109
Error
512226.33
18
28457.0183
Total
931165.21
29
Table 4.9 Bray-Curtis Similaity Index
Station 1
Station 2
Station 3
Station 4
Station 5
Station 6
Station 7
Station 8
Station 9
Station 1
Station 2
37.3158637
Station 3
28.2620123
46.5699925
Station 4
22.3024623
38.3516633
45.9257924
Station 5
18.6310568
23.985633
17.1310477
15.4332049
Station 6
29.9432912
40.645112
43.0308989
44.1434491
19.6573544
Station 7
31.9437896
27.2470058
22.1040484
18.0472318
9.6601484
20.1824742
Station 8
35.4435022
35.3110053
30.2342881
25.3413419
20.4251554
33.3031404
43.1303796
Station 9
27.7998105
29.4189756
30.8858452
29.4201912
21.3640726
37.4294214
19.1853676
28.6809091
Station 10 31.7937693 33.3262749
28.318938
24.1058035
22.7085902
26.8175448
18.485742
25.7984049
32.0610208
Station
10
Table 4.10 Correlation Analysis; ‘r’ values showing correlation
between various diversity indices
s
H
j
d
sPhi+
H
0.623***
j
0.637***
0.930***
d
0.223
0.735***
0.516**
0.705***
0.933***
0.982****
0.520**
Lamda+
0.314
0.633****
0.654***
0.338
0.639***
Delta+
0.04
0.079
0.122
0.152
0.218
sPhi+
P < 0.001 = ***
P < 0.001 = **
P < 0.05 = *
Lamda+
0.219
FIG. 4.1 Seasonal variations in Margalef's index d and Shannon's index H' for
phytoplankton in the selected sites of Kodungallur
FIG. 4.2 Seasonal variations in Pielou's Index J' and Average Taxonomic Distinctness
Delta+ for phytoplankton in the selected sites of Kodungallur
FIG. 4.3 Seasonal variations in Total Phylogenetic Diversity and Taxonomic
Diversity for phytoplankton in the selected sites of Kodungallur
FIG. 4.4 Cumulative Dominance Plots for Phytoplankton
FIG. 4.5 Funnel Plots for Average Taxonomic Distinctness (∆+) at the ten stations
Unbroken lines represent the simulated 95% limits. The broken lines indicates the mean of the ∆+ from the master list
FIG. 4.6 Funnel Plots for Variation in Taxonomic Distinctness (Λ+) at the ten stations
Unbroken lines represent the simulated 95% limits. The broken lines indicates the mean of the Λ+ from the master list
FIG. 4.7 Dendogram showing the clustering of stations based on Phytoplankton Abundance
FIG. 4.8 MDS Plot of Stations based on the Abundance of Phytoplankton
SUMMARY
The high species richness and diversity index during the postmonsoon
season indicates that this season is the most suitable for plankton growth and
species abundance offering the most favourable salinity regime.
From the phytoplankton diversity index and evenness values during the
present study, it can be assumed that, Stations 1, 8 and 10 are more or less stable
ecosystems.
Comparatively lesser diversity recorded from Stations 4 and 6 shall be
attributed to the highly polluted condition existing there due to retting.
The
cumulative dominance for the Stations 4, 5 and 6 reached simultaneously
cumulative 100% due to low species diversity and higher dominance of a few
phytoplankton.
The observed reduction in AvTD at the retting stations (Stations 4 and 6)
can represent a loss of functionality of the phytoplankton assemblage in this
station and it may affect the stability of the water bodies. Stations 1, 2, 3, 7, 8 and
9 are similar to what is to be expected from the test against the master species list.
Stations 5, 6 and 10 suggest a departure from expectation.
The funnel plot for Λ+ reveals that Stations 2, 3, 4, 5 and 9 has an overall
increase in complexity based on low numbers of species widely dispersed in
higher taxa.
The dendrogram shows that Stations 1, 7 and 8 can be grouped together.
These are oligohaline water bodies. Stations 2, 3, 4 and 6 form another cluster;
these stations are located on the Canoli canal. Stations 9 and 10 form a third
group; though they belong to two entirely different water bodies. They proximity
to each other may be the reason for their similariy. Station 5 is distinctly apart
though it also lies along the Canoli canal.
The Bray Curtis similarity coefficient indicates that Stations 2 and 3 are
comparatively more similar (range 47%) while Stations 7 and 5 are least
similar (9.6%).
111