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 123 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 123 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 1334 Environ Earth Sci (2015) 74:1331–1341 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 123 1336 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 123 Environ Earth Sci (2015) 74:1331–1341 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 123 1338 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. 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