Environ Earth Sci (2015) 74:1331–1341
DOI 10.1007/s12665-015-4122-3
ORIGINAL ARTICLE
Ecological quality assessment based on macrobenthic assemblages
indices along West Port, Malaysia coast
Seyedeh Belin Tavakoly Sany • Rosli Hashim
Aishah Salleh • Majid Rezayi • Omid Safari
•
Received: 10 March 2014 / Accepted: 24 January 2015 / Published online: 10 February 2015
Ó Springer-Verlag Berlin Heidelberg 2015
Abstract Macrobenthic communities are useful biological indicators for monitoring the health status of marine
environments. In this context, biological indices have been
widely developed based on macrobenthic communities in
order to distinguish the ecological status of marine environments. In this study, results from several indices such as
Shannon–Weiner, AZTI Marine Biotic Index, Multimetric
AZTI Marine Biotic Index, and BENTIX were compared
and evaluated. The effects of environmental factors on the
benthic communities were also studied. Results from these
indices revealed significant differences in ecological status
between sampling stations, which were probably due to the
different structures of benthic communities and their state
successions. The results consistently emphasized the
anthropogenic effects and natural variability caused by
these variations in spatial scales.
Keywords Ecological integrity Macrobenthic
communities Biological indices West Port Malaysia coast
S. B. T. Sany (&) R. Hashim A. Salleh
Institute of Biological Sciences, University of Malaya,
50603 Kuala Lumpur, Malaysia
e-mail: belintavakoli332@gmail.com
S. B. T. Sany M. Rezayi
ACECR Mashhad Branch, Food Science and Technology
Research Institute, Mashhad, Iran
M. Rezayi
Department of Chemistry, Faculty of Science,
University Malaya, 50603 Kuala Lumpur, Malaysia
O. Safari
Faculty of Natural Resources and Environment,
Ferdowsi University of Mashhad, Mashhad, Iran
Introduction
Over the past few years, many researches have been conducted to select practical biological indicators and indices
that can be implemented in the monitoring process and that
are able to provide practical information related to the
specific question of environmental assessment, which are
applied in making strategic management decisions
(Baracchi et al. 2010; Hakanson and Blenckner 2008; Pinto
et al. 2009; Tavakoly Sany et al. 2014b). In sediments,
macrobenthic organisms are important biological indicators to evaluate environmental changes and chemical
contaminates effects because of their close relation to
sediments, high sensibility to chemicals contaminates, and
their ability to absorb and accumulate different kinds of
compounds especially heavy metals (Neary 2008; Pinto
et al. 2009; Rezayi et al. 2014; Tavakoly Sany et al.
2014b).
The abundance of a specific species is one of the common indicators for measuring the degree of pollution; for
example, the Bllan indices, based on characterizing the
dominant species, is known as a sign of organic pollution in
environments with species such as amphipods and polychaetes (Bellan 1967, 1980; Jørgensen et al. 2005). Most
authors do not recommend these indicators because the
density of some indicator species may change naturally,
and there is no credible method to determine whether the
significant change in the indicator species of a population
was due to pollutants or whether it occurred naturally
(Jørgensen et al. 2005; Tavakoly Sany et al. 2014b).
Despite these criticisms, AMBI index (Borja et al. 2000,
2003), BENTIX index (Simboura and Zenetos 2002), and
Ecological Evaluation Index (EEI) (Orfanidis et al. 2003)
were updated based on the information between the presence of a species stating a non-polluted condition and of
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1332
species stating a kind of pollution in an aquatic area. Results
from these indices are classified benthic organisms into
several ecological groups based on their respective responses to types of pollutants. These indices have been
successfully applied as a practical tool for detecting the type
of anthropogenic pollutants (especially organic matter and
heavy metals) by the European Water framework directive
(EU-WFD) (Jørgensen et al. 2005; Kitsiou and Karydis
2011; Saadati et al. 2013; Tavakoly Sany et al. 2014b;
Zaldı́var et al. 2008). Biodiversity indices, such as Shannon–Wienner index, Margalef, Simpson, and K-dominance,
have also been frequently applied to describe the biological
variety in marine environments (Jørgensen et al. 2005).
Statistical multivariate methods have been used to calculate these indices based on simple formulas, so these
indices provide a widely logical concept based on diversity
measure, which can quantify and clarify the relationship
between the diversity of biological organisms and disturbances, which may act as stressors (Kitsiou and Karydis
2011).
The West Port is located in the west coastal waters of
Malaysia and is a region of contact between the mangrove
forest and mudflats from the west side and harbors from east
side (Tavakoly Sany et al. 2012b; Yap 2005). The area is
important for tourism, fisheries, navigation, and transportation. In West Port, the first basic study on benthic
communities was conducted by several research organizations (the association of Southeast Asia nations, department
of environment in Selangor and environmental management
for the Malaysia east coastal water) from 1974 until 1994.
Based on their results, the West Port areas was dominated
by the class bivalvia and three invertebrate groups, including a few species of the class polychaetes, 30 species of
the class gastropods, and 45 species of subphylum crustacean, were also detected in this area (Yap 2005).
In the present study, several problems have been pointed
out and remedied in order to conduct research on the utility
of indices. First, the high natural variability in the study area
due to the tidal condition and strong marine current and the
northeast monsoon alters the morphological features, grain
sizes, and sedimentation at all spatial and temporal scales.
Second, there are no background and updated databases
available on potential presence and diversity of macrobenthic communities in the current study area.
Thus, in order to reduce the effect of these limitations
and increase the accuracy of the information about the
ecological conditions, it is essential to increase the number
of stations, temporal assessment, and multiple sediment
samplings during the north and south monsoon seasons.
Hence, this study tries to evaluate the ecological condition in spatial and temporal scales to recognize the possible adverse ecological effects on the biological
community due to the anthropogenic pollutants
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Environ Earth Sci (2015) 74:1331–1341
concentrated in West Port, and to describe the successional
development of the macrobenthic communities. Finally,
the results from this study will be applied in the form of the
managerial tools in order to control the pollution occurrence and protect living organisms to assure the safe future
of the marine environment of Peninsular Malaysia. Moreover, it can be practical as background data for future
studies.
Methodology
Sampling site location
West Port is surrounded by the west coast (03°000 N to
101°240 E) of peninsula Malaysia and by the Malacca Strait
in Southeast Asia (Tavakoly Sany et al. 2013a; Yap 2005)
(Fig. 1). In this research, nine stations were selected from
three transects parallel to the coastline with three different
distances (see Fig. 1; Table 1), as well as one station as a
control point selected 21 km far from the West Port in the
remote area. This port is the busiest port, and it is well
sheltered by several mangrove islands and mudflats,
forming a natural enclosure. The study area lies within
humid tropical part with rainy season (north monsoon,
November to March) and dry season (south monsoon, April
to October) (Tavakoly Sany et al. 2012a ; Yap 2005). Tidal
circulation is semidiurnal in the West Port; the level of the
surface water falls and rises with an average range of
1.4–4.2 m within approximately 12.5 h. The natural morphology of this area has changed dramatically since the end
of the nineteenth century following the development of
port infrastructures (Yap 2005). The container terminals
and an industrial complex, including cement industries and
food factory have been developed along the berth lines, are
recognized point source of pollutants. The harbor itself is
in use for massive cargo transport and fishing boats
(Tavakoly Sany et al. 2014a, c).
Sampling and experimental analysis
Sediment samples were collected using a Peterson grab
sampler (0.07 m2) at two dates per season: November 26,
27, 2011, February, 28, 29 2012, May 28, 29, 2012, and
August 15–17, 2012. For sediment parameters, the top
1 cm layers were removed with a stainless steel spoon from
a grab sample for the analysis of grain size and the total
organic carbon content of sediments. For macrobenthos
analysis, four replicates of grab samples were taken to
investigate the spatial and temporal distribution. Each
replicate was then sieved on a 0.5-mm mesh screen to sort
benthic organisms, including macroinfauna (greater than
0.5 mm). The organisms were then transferred into a
Environ Earth Sci (2015) 74:1331–1341
1333
Fig. 1 Location of study area and sampling stations
plastic container, preserved in a 99.9 % ethanol alcohol
with rose bengal, and stored to identify their lowest practical taxonomic level (i.e., organisms were identified as
species where possible and damaged organisms or juveniles were identified to the level of genus and family) by
using a dissecting microscope.
At high tides, general environmental parameters of
surfaces and bottom seawater condition were measured
using a multi-parameter probe (YSI, 556 digital) to obtain
the physical parameters measurements on site. Water
transparency was measured using a Secchi disk, and a fish
finder was used to measure the water depth at each station.
The current meter (RDI Ocean Surveyor ADCPsTM) was
used to measure current speed in this research.
In this study, the effects of the physicochemical parameters (including total organic carbon (TOC), fine fraction of sediment, depth, heavy metals, and polyaromatic
hydrocarbon (PAH) were evaluated on macrobenthic
communities.
The variation of these parameters in West Port is previously published (Tavakoly Sany et al. 2012c , 2013a) and
summarized in the Table 1.
123
123
55.47
44.77
Pb
V
a
19.50
44.83
7.53
457.40
36.08
52.67
64.02
8.64
174.20
0.18
7,422.70
11.69
46.50
0.83
9,337.70
50.96
2 (WCE500)
7.80
62.8
11.83
507.45
37.77
52.15
53.63
10.21
331.84
0.21
4,606.5
14.59
49.13
0.90
11,139.00
68.55
3 (WCE1000)
The sediments grain size lower than 64 micrometer
CP control point
12.50
11.53
Ni
Depth (m)
206.70
Mn
52.50
0.27
Hg
10.27
4,436.1
Fe
Silt (%)a
16.28
Cu
TOC (lg g-1)
58.66
Cr
49.22
0.68
Cd
698.9
9,478.9
Al
PAHs (ng g-1)
35.76
As
Zn
1 (WCE100)
Heavy metals
(lg g-1)
13.30
55.58
8.89
623.70
37.04
57.81
39.39
13.69
247.11
0.26
4,693
13.93
36.83
0.28
10,547
66.62
4 (WL100)
20.30
41.02
7.30
543.49
32.58
53.45
30.21
12.28
185.51
0.31
4,410.3
12.60
37.60
0.23
8,660.5
44.54
5 (WL500)
8.80
70.11
12.75
1,448.80
35.49
56.87
53.31
15.70
264.80
0.32
5,498.20
15.76
46.95
0.61
13,024
49.84
6 (WL1000)
15.50
52.61
10.71
3,446.90
50.63
71.53
80.95
13.96
279.18
0.28
8,413.70
17.01
62.50
0.90
18,698
93.24
7 (WC100)
Table 1 Variation of physicochemical parameters in different stations (Tavakoly Sany et al. 2012c , 2013a)
21.10
50.73
10.00
573.59
33.60
53.33
44.71
9.52
259.82
0.21
6,868.0
12.26
42.60
0.74
12,830
57.76
8 (WC500)
0.69
68.39
14.91
594.48
40.67
71.88
69.11
13.51
355.05
0.28
7,596
17.16
45.83
1.29
17,520
79.12
9 (WC1000)
13.28
55.40
10.47
988.30
39.23
58.35
53.34
12.12
256.02
0.26
5,993.83
14.59
47.40
0.72
12,359.46
60.71
Mean
6.74
9.98
2.46
968.99
6.51
7.81
15.82
2.33
61.61
0.05
1,582.13
2.09
8.60
0.33
3,594.38
18.03
Standard
deviation (SD)
0.43
51.6
10.46
100.3
29.52
31.18
21.14
5.76
84.38
0.15
4,009.5
8.87
18.69
0.53
9,745.9
27.57
10 (CP)a
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Environ Earth Sci (2015) 74:1331–1341
A standard solution of the 16 United State Environmental
Protection Agency (US EPA) priority PAHs and a fivesurrogate standard were purchased from Ultra Scientific Inc
(North Kingstown, RI, USA). A standard reference material
(SRM 1941) of PAHs was obtained from the National Institute of Standards and Technology (NIST, Gaithersburg,
MD, USA). The extraction procedure was performed based
on the Soxhelt extracted method (SW-846 EPA). Cleanup
and fraction analyses were conducted based on the alumina/
silica gel column (1:2). PAHs were obtained by diluting
with 60 mL of hexane/dichloromethane (1:1). The PAH
fraction was concentrated again using a rotary evaporator
and under a stream of filtered purified nitrogen gas, and the
volume was concentrated to 0.2 mL. An aliquot of 0.2 mL
of each extract was applied to gas chromatography–mass
spectrometry (GC–MS) analysis. Similarly, hexamethyl
benzene was added as an internal standard prior to the GC–
MS analysis. All PAHs were identified and quantified according to the EPA modified method of 8270. For each
sample, a procedural method of blanks, sample duplicates,
spiked matrices, and standard reference materials was used
to assess the quality control and assurances. Percentages of
relative standard deviation (RSD) for all the individual
PAHs were less than 20.0 % in the replicates used to measure the DL, as well as the fortification experiments. The
average recoveries of surrogate standards ranged between
63.28 and 96.75. Recoveries of all the PAHs and RSD fall
within the range of 78.4–95.2 and 2.6–13.5 %, respectively.
Detection limits ranged from 0.095 to 1.018 ng/g.
Plasma mass spectrometry (ICP/MS) was used for the
chemical analysis of heavy metals (Al, As, Cd, Cr, Cu, Fe,
Mn, Ni, Pb, V, and Zn). The samples were digested based on
EPA method 3052 (EPA 1996; Ilander and Väisänen 2007).
Mercury was estimated by both ICP/MS and with a milestone
mercury analyzer (DMA-80 model) to produce an accurate
result. The procedure for TOC analysis follows Fang and
Hong (1999). Standard reference materials 2702 and matrix
spike recoveries were applied to assess the quality control
and assurances. The percentage recovery was between 91.54
and 104.66. The standard methods suggest warning limits for
matrix spike recoveries from 87 to 113 %. Therefore, the
range of recovery was reasonable in this study (IDEM 2002;
Willie and May 2002). Total organic carbon (TOC) was
determined in surface sediments using a carbon analyzer
(Horbia Model 8210). The procedure for TOC analysis follows Fang and Hong (1999). Sediment grain size was determined using a multi-wavelength particle size analyzer
(model LS 13 320) (Rauret 1998; Tessier et al. 1979).
Data analysis
Among the indices available, we selected four indices including Shannon–Weiner (Shannon and Wiener 1963),
1335
AMBI (Borja et al. 2000), M-AMBI (Muxika et al. 2007;
Pinto et al. 2009), and BENTIX. AMBI, M-AMBI, and
BENTIX are defined according to specific ecological
groups. These indices were designed to classify the ecological quality of the estuary and coastal water according to
the response of soft-bottom macrobenthic population to
changes in water quality (Jørgensen et al. 2005; Neary
2008). The benthic organisms were divided into five ecological groups GI, GII, GIII, GIV, and GV, based on their
sensitivity to an increasing anthropogenic stresses gradient
as per regularly updated list published by AZTI laboratory
(Borja et al. 2000). The scales of these indices were explained in Table 2. The formulas that express these indices
are estimated by the following equations:
AMBI ¼ ðð0 %GIÞ þ ð1:5 %GIIÞ þ ð3 %GIIIÞ
þ ð4:5 %GIVÞ þ ð6 %GVÞÞ=100
ð1Þ
BENTIXðBIÞ ¼ ð6 %GS þ 2 %GTÞ=100
ð2Þ
The AMBI was calculated following the guidelines of
Borja et al. (2003). Based on the AZTI reports, group I is
the relative abundance of species that are very sensitive to
pollution and are present under unpolluted areas, group II is
the relative abundance of species indifferent to organic
enrichment, group III is the relative abundance of species
tolerant of excessive organic enrichment, group IV is the
relative abundance of second-order opportunistic species
and mainly small-sized polychaete, and group V is the
relative abundance of first-order opportunistic species.
These selective or non-selective deposit-feeders belong to
the specialized families such as Cirattulides Polychaetes,
Spionids, Eunicids, and Capitellids (Rosenberg and
Blomqvist 2004; Borja et al. 2000). %GS in the BI is the
relative abundance of %GI ? %GII as sensitive groups,
and %GT is the relative abundance of %GIII ? %GIV ? %GV as tolerant species.
In the present study, Shannon–Wiener index was used
(Shannon and Wiener 1963) to assess the diversity of
benthic organisms. Shannon diversity is frequently used to
compare the diversities between various ecological systems
(Clarke and Warwick 2001). This index is based on the
theory that individual species are randomly sampled from
indefinitely large populations, and it also assumes that all
of the species are represented in the sample (Jørgensen
et al. 2005). The index takes the form of:
X
H0 ¼ pi log 2pi
ð3Þ
pi is the proportion of individuals found in the species
i based on bits per individual. It is equal to the ratio
between the numbers of individuals of the species I and the
total number of individuals. The value of index can be
between 0 and 5 (Table 2). According to the literature,
low index values are considered to be indications of
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Environ Earth Sci (2015) 74:1331–1341
Table 2 Summary of indices
scales and classifications
AMBI
M-AMBI
BI
H0
Dominating
ecological group
Disturbance classification
0.0 \ AMBI B 1.2
[0.82
0–1
[4
I
Unpolluted
1.2 \ AMBI B 3.3
0.62–0.82
1–2
4–3
III
Slightly polluted
3.3 \ AMBI B 5
0.41–0.61
2–4
3–2
IV–V
Moderately polluted
5.0 \ AMBI B 6
0.21–0.4
4–6
2–1
V
Heavily polluted
6.0 \ AMBI B 7.0
\0.2
6–7
1–0
Azoic
Extremely polluted
contamination. Multivariate AMBI (M-AMBI) is designed
to better define the ecological quality status in study area
based on the benthic community integrity (abundance,
biomass, or diversity measures) (Pinto et al. 2009; Tavakoly Sany et al. 2014b). Zettler et al. (2007) indicated that
this index ‘‘is combination of the proportion of disturbance-sensitive taxa through the use of the Shannon–
Wiener index, which overcome the need to use more than
one index to evaluate the overall state and quality of
continental shelf and oceanic water bodies’’. These factors
were integrated through the use of discriminative analysis
(DA) and factorial analysis (FA) techniques. The final
values describe the relationship between the observed
values and reference condition value (Muxika et al. 2007;
Pinto et al. 2009). All these indices are estimated by the
software, which can be downloaded at http://www.azti.es
(Pinto et al. 2009).
Statistical methods
Statistical analyses were performed using Microsoft Excel
and SPSS 17 software (SPSS, Chicago, IL) to estimate statistical tests on monitoring and bioassays data. The methods
were selected based on the results of the Shapiro–Wilk
normality test, the Levene test for homogeneity of variances,
and the Bartlett tests of equal variances. According to these
methods, the data did not pass the tests of normality and
homogeneity. Thus, significant differences between the data
were evaluated via Kruskal–Wallis one-way nonparametric
ANOVA (level of significant is 0.05). Nonparametric correlation method (Kendall’s tau-b) was used to obtain the
correlation coefficient and to observe the influence of the
physicochemical parameters on biological samples.
Results
Several ecological indices were applied to assess the
sediments quality based on the response of the soft-bottom
macrobenthic structure to changes in the environment.
Average abundance, richness, and diversity were significantly higher at stations 10 (2,144.5 ± 543, H: 4.41, j:
25, p [ 0.05) and 6 (1,736 ± 313.39, H: 4, j: 28,
p [ 0.05), whereas the lowest abundance, richness, and
diversity were observed at stations 1 (0, H: 00.0, j: 00.0,
p [ 0.05). Generally, stations located along the mangrove
edge (3, 6, and 9) showed higher average values in terms of
the total number of individuals, diversity, or richness
compared to other stations that were close to the berth line
(2, 7, and 8) (Table 3).
Generally, West Port is classified as moderately polluted
(BI 3, AMBI 3.47, M-AMBI 0.53). Based on biological
indices analysis, the pollution level in the stations 1, 2, 7,
and 8 varied between moderately to extremely polluted. At
Table 3 Summary results of ecological indices to assess pollution level based on the benthic responds to disturbance in different stations
Stations
Abundance individual (m-2)
Diversity (H0 )
Richness
BI
AMBI
M-AMBI
Disturbance classification
1
0
0.00
0.00
7
7.00
-0.05
Extremely disturbed
2
786.25
2.89
11.00
3
3.88
0.48
Moderately disturbed
3
1,231.25
3.33
18.00
2
2.48
0.68
Slightly disturbed
4
1,241
3.42
21.00
2
2.46
0.72
Slightly disturbed
5
566
3.03
17.00
2
1.81
0.68
Slightly disturbed
6
1,736
4
28.00
2
1.76
0.85
Slightly disturbed
7
1,075
2.64
8.00
3
4.01
0.42
Moderately disturbed
8
885
2.75
10.00
3
3.80
0.46
Moderately disturbed
9
1,386.76
3.13
16.00
2
3.3
0.63
Slightly disturbed
Avg
989.69 ± 506.72
2.79 ± 1.13
14.33 ± 8.14
3 ± 1.62
3.47 ± 1.61
0.53 ± 0.26
Moderately disturbed
CP
2,144.5 ± 411.34
4.41 ± 0.45
25.00 ± 2.45
1 ± 0.2
0.36 ± 0.12
0.96 ± 0.25
Undisturbed
Avg average
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1337
Fig. 2 Range of ecological group percentage for different stations
and average percentage of ecological groups across 1 year
Fig. 3 Range of ecological group percentage for different sampling
times
these stations, the benthic community was dominated
(48.9–62.5 %) by ecological group IV and V (opportunistic
species). Other stations are classified as slightly polluted,
and the community was dominated (68.43–85.24 %) by
groups II and I. Station 1 was only classified as extremely
polluted (BI 7, AMBI 7, M-AMBI -0.05) as there is no
benthic community present at these stations (Fig. 2). Ecological group III (tolerant to pollution) was not found in the
West Port, which had an unbalanced benthic composition.
Table 4 and Fig. 3 summarize the temporal variations of
the ecological groups over a year. The abundance, diversity, and richness changed in small seasonal patterns, with
an upward trend from November 2011 until August 2012.
There was no significant temporal change in the ecologic
indices, and the macrobenthic communities varied without
an obvious temporal pattern.
The correlation analysis agrees with the assessment
of benthic response to the type variation in contaminants.
In the West Port, significant negative correlation
(-0.4 \ r \ -0.5) was found between benthic abundance
and certain parameters such as As, Cd, and Cu, while only
PAH components have significant negative correlations with
the diversity and richness of the benthic structure. Fe, Mn,
fine fraction, and TOC demonstrated a significant positive
correlation with the macrobenthic community (Table 5).
Discussion
Disturbance on macrobenthic community and their
biological response
More efforts have been made to explore the correlation
between sediments and the distributions of benthic communities, leading to the belief that a complex interaction
of multiple parameters can either directly or indirectly
control the distribution of the benthic communities (Borja
et al. 2003; Pinto et al. 2009; Rezayi et al. 2013; Rosenberg et al. 2009). These parameters include concentrations
of organic compounds, salinity, oxygen levels, sediment
type, hydrodynamic environment, food availability, and
anthropogenic stress, which is the primary parameter
constraining the structure of a benthic community (Leonardsson et al. 2009; Nasher et al. 2013; Pacheco et al.
2010; Rosenberg 1976; Rosenberg et al. 2009). The response of benthic communities to these multiple parameters is further complicated in spatial and temporal
scales. In this research, there were no temporal changes in
richness or the abundance of dominant species, but a
significant variation in the macrobenthic composition was
found in the spatial scales.
Table 4 Summary results of ecological indices to assess pollution level based on the benthic responds to disturbance in different sampling times
Seasons
Abundance individual (m-2)
Diversity
Richness
BI
AMBI
M-AMBI
Disturbance classification
November 2011
899.53
2.55
12
3
3.58
0.48
Moderately disturbed
February 2012
908.17
2.84
13
3
3.41
0.68
Moderately disturbed
919.38
2.86
15
3
3.35
0.68
Moderately disturbed
1228.57
2.9
16
3
3.33
0.53
Moderately disturbed
May 2012
August 2012
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Environ Earth Sci (2015) 74:1331–1341
Table 5 Correlation coefficient between benthic community and
physicochemical parameters of sediment at different sites
Physicochemical
parameters
West Port
Abundance
Richness
Diversity
Al
0.24
-0.029
-0.01
As
-0.45
-0.09
-0.01
Cd
Cr
-0.48
0.14
-0.09
-0.24
-0.14
-0.21
Cu
-0.40
0.20
0.21
Fe
0.58
Hg
0.28
0.24
0.17
Mn
0.65
-0.067
-0.039
-0.1
0.11
Ni
0.35
-0.06
-0.019
Pb
0.23
-0.12
-0.07
V
0.32
-0.14
-0.13
Zn
0.12
0.16
0.11
Fine fraction
0.58
0.53
0.55
TOC
0.52
0.54
0.53
PAHs
-0.38
-0.57
-0.46
Depth
-0.51
-0.52
-0.54
The strong correlation between macrobenthic composition (the abundance, diversity, and richness) and some
environmental parameters (e.g., TOC, particle size, and
depth) showed that these parameters controlled the spatial
distribution of benthic species in the West Port (Table 5).
Over a study period of a year, stations near the berth line
supported relatively lower abundance, diversity, and richness compared to stations near the mangrove edge. Every
sampling location along the mangrove edge (3, 6, and 9)
had a similar configuration, with shallow water (6.8–8.8 m)
and high organic contents (10.63–15.49 %) in a soft and
muddy substratum (63.42–70.81) suitable for settlement by
diverse species; factors may cause species abundance to
increase. Data revealed that the high TOC along the
mangrove edge could not suppress the colonization of
benthic species in this area, as this organic enrichment is
not yet strong enough to result in serious oxygen depletion
and is only sufficient to provide a rich food source for the
benthic community. Additionally, the locations along the
mangroves are located far (1,500–2,000 m) from the point
sources of anthropogenic discharges, which is another
potential reason for their higher diversity. Additionally, Fe
and Mn showed significant positive correlations with
benthic abundance, implying that Fe and Mn cause to increase the abundance of macrobenthic species. Several
studies have frequently indicated that some metal ions,
such as Na, K, Ca, Fe, Mn, Co, Cu, Zn, and Mo, are
essential for biological systems when their concentration
levels do not exceed those required for correct nutrition
(Cardoso et al. 2012; Varol and Şen 2012).
123
Most of the sampling stations along the berth line (1, 4,
and 7) and in the middle of the strait (2, 5, and 8) are in
deeper waters (12.5–21.1 m) with high percentage
(46.42–58.89 %) of coarse sand (500 lm–2 mm), which
precipitated reduced species diversity especially at stations
in the vicinity of the cement outlets and the container
terminal berth. Anthropogenic stress such as heavy metals
and PAHs could be another reason of reduced benthic
structure because the stations along the berth line are adjacent to the anthropogenic discharges from port activities
and industrial outlets, which may suppress the benthic
community’s development. The results of our correlation
analysis supported a negative effect of these contaminates
on benthic composition (Table 5). According to these results, As, Cd, and Cu exhibited significant negative correlations with the abundance of the benthic community,
implying that increases in these metals could lead to a
decrease in abundance of benthic species, but that changes
in diversity and richness were independent of the concentrations of As, Cd, and Cu.
Similarly, the total concentration of PAHs exhibited a
significant negative correlation with the diversity and
richness of benthic species. The effect of PAHs on the
benthic community has been frequently examined in several studies, which indicated that opportunistic species
(ecological groups V and IV) with high abundances are
replaced with other ecological groups when the benthic
communities are exposed to PAH contamination (Qin et al.
2012; Rosenberg 1976; Schafer et al. 2010; Veiga et al.
2009). The results of our analysis of spatial distribution
indicated that the abundances of common opportunistic
species (Lumbricillus sp., Glycera alba, and Capitella
capitata) (Rosenberg and Blomqvist 2004; Borja et al.
2000) increased greatly at stations 2, 7, and 8, where
Lumbricillus sp. was a dominant species, while diversity
and richness of other species were significantly decreased.
Similarly, the AMBA analysis revealed that the benthic
community is moderately exposed to anthropogenic stress
at these stations (Table 3). High level of contamination was
observed in stations 1 and 2 in the vicinity of the cement
outlet. Macrobenthic organisms were not found in the
sediment sample of station 1 because high proportion of
cement compounds (more than 70 %) may hinder the development of benthic structures in this station. The results
of this study showed that the indices based on metrics have
ability to distinguish community structures, and viewing
them as the two main factors and forces these communities
together, these factors encompass the natural variability
and the anthropogenic impact.
All of the sediment samples in stations 2, 7, and 8 were
grouped by the high percentage of opportunistic species
from group IV and V, and by the low presence of the
groups I and II, while sediment samples in the control point
Environ Earth Sci (2015) 74:1331–1341
was grouped by the presence of ecological groups I and II.
Thus, the analysis of benthic indices could be considered as
metrics to detect the possible anthropogenic effect in West
Port, because their results agree with previous studies on
sediment quality (Tavakoly Sany et al. 2012b , 2013a).
According to the comparison results of the sediment
quality assessment with previous studies, stations 7 and 8,
in the vicinity of the container terminal, were significantly
polluted by heavy metals and PAHs, and were considered
to exhibit moderate to high adverse effects, whereas the
rest of the stations were considered to be moderately polluted with slight/moderate adverse biological effects, while
the control station was unpolluted (Tavakoly Sany et al.
2013a, b). These results are completely synchronous with
those of the biological indices analysis (AMBI, M-AMBI,
and BI) in this study.
Likewise, high percentage of ecological groups II and I
were found to be mangrove lines and control points (stations 3, 6, and 9). This might be precipitated by the extreme
natural variability (variation of TOC, grain size, and depth)
that is integrated into all of the system. This work seems to
imply that metrics are more beneficial than the indices they
are based upon, and this supposition is also supported by
several studies involving minor estuaries (Cardoso et al.
2012; Jordan and Vaas 2000).
According to the correlation analysis and metrics, the
variation of the macrobenthic community was primarily
related to sediment characteristics or natural variability
(TOC and fine particles size), and releases of anthropogenic pollution are secondary disturbances that hinder
benthic development, especially heavy metals and organic
compounds playing major roles in halting the development
of benthic communities.
Succession stages
In 1978, Pearson and Rosenberg exemplified the acceptable
model (P–R) to clarify the effects of eutrophication on
benthic composition, which is applicable for coastal and
estuary waters worldwide (Calabretta and Oviatt 2008;
Shin et al. 2008). This model shows that the variation in the
concentration of organic compounds from low-to-high input leads to frequent successional stages in the macrobenthos from the normal structure of the benthic
community, with diverse species, to a transitional community structure with a high abundance of opportunistic
species, and finally to azoic sediment devoid of fauna
(Rosenberg and Blomqvist 2004). The P–R model logically
described a recovery pattern for an impacted macrobenthic
community. First, a few opportunistic species such as
polychaete and annelida species increase in abundance in
azoic sediments, which is regarded as a pioneer community. This community undergoes several successions to
1339
create an ‘‘intermediate community’’ and reaches a stable
final point, which is considered as the climax community
(Rosenberg and Blomqvist 2004; Rosenberg et al. 2009).
The climax community was recorded at a control point that
is free from contamination. Several factors affect the succession and recovery process in aquatic areas, such as
water circulation, rapid fluctuations of salinity, temperature, releases of toxic substances from the sediment,
topography, hydrodynamic conditions, water turbidity, and
water exchange patterns (Calabretta and Oviatt 2008;
Pacheco et al. 2010).
Benthic data that were collected during this research
showed a progression in the community of benthic assemblages from early successional stages to the azoic stage.
Most of the stations are in the early stage of succession,
including stations 3, 4, 5, 6, 9. AMBA analysis confirms
these results because all of the above stations were slightly
polluted, with a high abundance and diversity of ecological
groups I and II (sensitive species) such as Cerithium sp.,
Mactra luzonica, Nassarius jacksoniasus, and Alpheus sp.
(Table 3; Fig. 2). Stations 2, 7, and 8 were in the transitional stages of succession, with high abundances of ecological groups IV and V (opportunistic species) such as
Lumbricillus sp., Glycera alba, and Capitella capitata
(Rosenberg and Blomqvist 2004), and were moderately
polluted. Station 1 was in the azoic stage, whereas only
station 10 (control point) exhibited a normal benthic community composition, with high diversities and without opportunistic species. In the West Port, stations near the
cement outlet (1, 2, and 3) and container terminal (7, 8, 9)
closely follow this model, which is evidence that anthropogenic discharges from the cement factory and container
terminal likely affect the benthic community in this area.
In the West, the distribution of the benthic community
does not follow the gradient of organic compounds (1978).
In this area, there is an east–west gradient (from the
coastline to the mangrove edge) of increasing benthic diversity and decreasing opportunistic species, implying that
this pattern of benthic distribution is influenced by sediment
pollution, sediment type, and food availability, rather than
by organic compounds, because from the east to the west
side of the strait, there is a gradient of decreasing sediment
pollution (heavy metals and PAHs) and increasing finegrain-sized particles, total organic compounds, and food
availability. The increase in total organic compound from
east to west did not hinder the increase in benthic diversity.
The model of benthic faunal succession in the West Port
can be considered to represent the changes in the structure
of macrobenthic communities along a gradient of natural
and anthropogenic impacts, because the relationship between the general characteristics of macrobenthic communities in West Port and the mangrove system as a natural
habitat is clear.
123
1340
Environ Earth Sci (2015) 74:1331–1341
Conclusion
The outputs of indices in designated locations at the West
Port were differentiated from one another based on several
factors, such as biological indices using macrobenthic
communities, correlation analysis, and anthropogenic
levels of impacts. The whole idea behind this effort was to
categorize the states of ecology, which will inevitably lead
to the analysis of indices and its relation to marine
organisms.
According to the applied tools, only the sediment from
the control point can be regarded as an undisturbed place
with normal responses of the benthic community, with high
diversity and without opportunistic species, while the rest
of the stations are significantly disturbed, especially the
stations along the berth line. The P–R model of benthic
succession shows that most of the stations were at an early
stage and transitional stages of succession, while only
station 1 was in the azoic stage.
In a nutshell, apart from the anthropogenic effects that
act on the response of macrobenthic communities, the
natural variability of environmental factors are taken into
consideration, such as the TOC, depth, and grain size. The
biological indices (AMBI, M-AMBI, and BI) and correlation analyses are in good agreement, confirming the response of benthic communities to changes of contaminant
levels and the natural variability at different stations.
Acknowledgments The authors’ gratitude goes to support of
University Malaya High Impact Research grant (HIR) with project
number UM.C/625/1/HIR/270 and RP004A-SUS.
Conflict of interest
peting interests.
The authors declare that they have no com-
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