Response of benthic macrofauna to multiple anthropogenic pressures in the shallow coastal zone south of Sfax (Tunisia, central Mediterranean Sea)

Environmental Pollution 253 (2019) 474e487

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Response of benthic macrofauna to multiple anthropogenic pressures in the shallow coastal zone south of Sfax (Tunisia, central Mediterranean Sea)* Nawfel Mosbahi a, *, Mohamed Moncef Serbaji b, Jean-Philippe Pezy c, Lassad Neifar a, Jean-Claude Dauvin c a b c

Laboratoire de Biodiversit
e Marine et Environnement, Facult
e des Sciences de Sfax, Universit
e de Sfax, BP 1171, 3038, Sfax, Tunisia National School of Engineers of Sfax, Water, Energy and Environment Laboratory L3E, University of Sfax, BP 1173, 3038 Sfax, Tunisia ^ti Normandie Univ., UNICAEN, CNRS, UMR 6143 M2C, Laboratoire Morphodynamique Continentale et Co ere, 2-4 Rue des Tilleuls, 14000 Caen, France

a r t i c l e i n f o

a b s t r a c t

Article history: Received 10 February 2019 Received in revised form 7 June 2019 Accepted 21 June 2019 Available online 6 July 2019

Anthropogenic activities including coastal industries, urbanization, extensive agriculture and aquaculture as well as their cumulative impacts represent major sources of perturbation of marine coastal systems. Macrobenthic communities are useful ecological indicators for monitoring the health status of marine environments (or polluted environments). The present study reports, for the first time, the response of benthic macrofauna sampled during two years survey (2015e2016) to multiple anthropogenic pressures on the coastal zone south of Sfax (Tunisia). A total of 12 stations were monitored seasonally at locations downstream from the main potential sources of disturbance. 106 macrobenthos taxa, belonging to six animal phyla and 70 families, were identified with a dominance of polychaetes (42%), crustaceans (35%) and molluscs (18%). We used an ANOVA test and cluster analysis to identify spatial gradient linked to environmental and anthropogenic factors, including depth, sedimentary texture and anthropogenic activities (i.e. phosphogypsum discharges).The macrofauna present lowest species number and abundance on stations undergoing anthropogenic inputs, which are extremely polluted by heavy metals (Cd, Cu, F and N) and excess of organic matter. Univariate parameters reveal a general trend of increasing species diversity with increasing distance from the pollution source. The polluted stations are strongly dominated by carnivores, and selective deposit feeders, and more closely linked to the availability of trophic resources than to anthropogenic constraints. The seasonal changes in macrobenthic abundance, diversity indices and community structure are mainly linked to the biological cycle (e.g. recruitment events) of the dominant species. Biotic indices (AMBI and BO2A) classified the coastal zone south of Sfax as moderate and good ecological status. This study suggests that initiating a long-term monitoring programme would improve our understanding of the temporal changes of macrobenthic communities of this ecosystem, contributing to the assessment of effective management and conservation measures in this disturbed area. © 2019 Published by Elsevier Ltd.

Keywords: Soft-bottom communities Benthic indicators Anthropogenic pressures AMBI BO2A

1. Introduction Coastal ecosystems are complex environments known for their importance in terms of biodiversity. But they are also extremely sensitive, because they were exposed to several anthropogenic pressures (e.g. pollution, tourism, overfishing, sediment discharge,

* This paper has been recommended for acceptance by Wei Shi. * Corresponding author. E-mail address: [email protected] (N. Mosbahi).

https://doi.org/10.1016/j.envpol.2019.06.080 0269-7491/© 2019 Published by Elsevier Ltd.

shipping, industrial and urban developments). These anthropogenic disturbances were directly and/or indirectly responsible for the deterioration of marine habitats and the decline of costal marine resources, thus causing serious economic problems (Ellis et al., 2000; Rees et al., 2006; Johansen et al., 2018). To estimate the impact of anthropogenic pressures on coastal marine ecosystems, it is necessary to conduct continuous monitoring programmes on the quality and health status of these ecologically and economically important habitats (Zulfa et al., 2016). In the world, many biological compartments were selected to assess the environmental quality of

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marine ecosystems (Borja et al., 2000). Among them, macrobenthic communities are used to develop a plethora of benthic indicators, since these organisms offer many advantages for assessing ecological quality status: (1) they are relatively sedentary; (2) they have relatively long life-spans; (3) they comprise diverse species that exhibit different sensitivities or tolerances to anthropogenic stressors; and (4) they play an important role in cycling nutrients and detritus between the underlying sediments and the overlying water column (Dauvin, 2007; Hale and Eltshe, 2008; Borja et al., 2008). s is now undergoing a high stress caused by The Gulf of Gabe intensive anthropogenic pressures due to trawling practices, while pollution (e.g phosphogypsum inputs, industrial waste) and shipping activity are causing more serious environmental problems. These anthropogenic activities impacting marine systems, cause a deterioration of seagrass beds, notably the Posidonia oceanica meadows, a decline in fisheries (Hattab et al., 2013), and change the structure functioning of benthic communities (Hattab et al., 2013; Ayadi et al., 2015; El Zrelli et al., 2018). These pressures favour the introduction and spread of many invasive species such as the blue swimmer crab Portunus segnis Forskal, 1775, which has caused many environmental and socio-economic impacts over the last few s (Rifi et al., 2014; Rabaoui et al., 2015; years in the Gulf of Gabe Deidun and Sciberras, 2016). The southern coastal area of Sfax has undergone increased anthropogenic pressures for many years (Gargouri et al., 2011; Aloulou et al., 2012; Zaghden et al., 2014; Drira et al., 2016). (Appendix A and B). Since the 1950s, the growth in manufacturing industries, the population increase and rapid urban development have resulted in the release of industrial and municipal wastewater, as well as heavy metal pollution, that have seriously contaminated the Sfax coastal marine environment (Gargouri et al., 2011; Drira et al., 2017a). Among these industrial developments, the phosphate treatment plant (SIAPE) produces huge amounts of phosphogypsum and associated organic and inorganic contaminants that have been discharged in this area for about 65 years, altering the marine environment and affecting its biodiversity (Aloulou et al., 2012; Zaghden et al., 2014). Several studies using bio-indicators such as benthic foraminifera (Aloulou et al., 2012), demersal fish (Barhoumi et al., 2012; Ben Salem and Ayadi, 2017), phytoplankton, ciliates and zooplankton (Rekik et al., 2013; Drira et al., 2017b) have assessed the ecological status of the coastal marine environment south of Sfax. Moreover, many studies have reported concentrations of anthropogenic substances in surface sediments (Gargouri et al., 2011; Zaghden et al., 2014), in coastal waters (Drira et al., 2016) and living organisms (toxicology) (Hamza-Chaffai et al., 1997; Barhoumi et al., 2012). These studies have shown the impact of this pollution on the diversity, the structure and the distribution of marine organisms. Likewise, this pollution has also caused the regression of Posidonia oceanica seagrass beds, the disappearance of many sensitive species, malformations of some benthic species and decreasing diversity of the benthic macroinvertebrates (Aloulou et al., 2012; El Zrelli et al., 2018). Based on these latter studies, and according to the results concerning sediments and water quality, the diversity patterns of macrobenthic fauna might be expected to be affected by these pollutants and environmental stressors, because these organisms live at the sediment-water interface, making them more easily influenced by accidental and chronic disturbances (Dauvin, 1993, 2007). The main objectives of the present study are (1) to investigate the structure, the spatiotemporal organization, and trophic structure of the benthic macrofauna communities, (2) to provide an assessment of the general ecological status of the shallow-bottom communities, and (3) to highlight the main environmental factors

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and anthropogenic pressures contributing to characterize the macrobenthic communities' structure. 2. Materials and methods 2.1. Study area The study area is located in the coastal zone south of Sfax s in (34
440 N. 10
460 E), in the northern part of the Gulf of Gabe south-east Tunisia (central Mediterranean Sea) (Fig. 1). The area extends along 15 km of coastline from the fishing port to Gargour (zone characterized by urban and industrial activities), including part of the city, the harbour, the solar saltern, the Madagascar and Sidi Salem industrial areas, the Sfax phosphate treatment plant
te
Industrielle d’Acide Phosphorique et (SIAPE in French: Socie d’Engrais) and the Thyna business park (Rekik et al., 2013; Drira et al., 2016). The SIAPE plant generates around 10.106 tons year1 of phosphogypsum containing high levels of impurities such as calcium sulphate (CaSO4), phosphate, chloride, fluorides, heavy metals and other trace elements and radionuclides (average values of 30.7 Bq$kg1 for 238U, 188 Bq$kg1 for 226Ra), 163 Bq$kg1for 210Pb) and 12.4 Bq$kg1 for 232Th) (Hammas et al., 2013). These chemical pollutants raise a major environmental issue since the measured values in the region of Sfax exceed the Maximum Allowable Discharge concentrations for wastewaters (Gargouri et al., 2011; Drira et al., 2017a). In addition, the coastal area of Sfax is impacted by intensive shipping activity associated with the commercial and fishing harbours of Sfax, by agricultural activities including salt marshes and the storage of olive oil wastes and numerous urban wastes attributable to the Thyna domestic waste landfill and municipal wastewater treatment plants (Gargouri et al., 2011; Zaghden et al., 2014). The marine area south of Sfax receives a wide variety of contaminants, including phosphates, trace metals and other trace elements, organic matter and hydrocarbons (0.41e5.6 mg/g dry weight) as well as polyphenolic and flavonoid compounds (Serbaji et al., 2012; Mezghani-Chaari et al., 2011; Zaghden et al., 2014). These contaminants may enter the southern coastal zone of Sfax through the Sidi Salem, Hakmouni and El Maou wadis (Serbaji et al., 2012; Louati et al., 2001) but also by runoff and atmospheric deposition (Fig. 1). Concerning climatic conditions, the Sfax region is characterized by a dry climate (mean annual precipitation of 210 mm), influenced by the hot southerly wind known as the Sirocco. The average water temperature is 14.9
C in winter and 32.3
C in summer, with salinity varying between 34.5 and 40 psm for the same period (Rekik et al., 2017). Waves and currents (0.2e0.3 m s1) follow a predominantly north-south direction (Louati et al., 2001) and the tide is semi-diurnal, with amplitudes ranging from 0.8 to 2.3 m (Sammari et al., 2006). 2.2. Macrofauna sampling and laboratory procedures Four sampling campaigns were carried out at 12 stations in front of the main prospective sources of disturbance and with a marked pollutant gradient (Fig. 1). Samples were collected during the period from April 2015 to January 2016 (5 April, 8 July, 10 October 2015 and 6 January 2016). Benthic macrofauna sampling was carried out using a Van Veen grab covering an area of about 0.05 m2 which penetrates approximately 0.1 m into the sediment. The station positions were accurately determined using a GPS (Global Positioning System, WGS84). For each season, five replicates were carried out at each station, four for biological analysis covering a total surface-area of 0.2 m2 and one for sediment analysis. Each biological sample was sieved on a 1 mm circular mesh and the

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Fig. 1. Map of the study area showing the location of sampling stations.

retained fractions were preserved in 5% formaldehyde saline solution. In the laboratory, after staining with Rose Bengal, samples were sorted, and individuals identified to the lowest possible taxonomic level and counted. In addition, temperature (T
C), salinity (Sal), pH and dissolved oxygen concentration (mg.L1) are measured using thermometer (WTW LF 196), a salinometer (WTW LF 196), and a pH-meter (WTW 3110) and oximeter type WTW respectively at each station and for each seasonal campaign. Chlorophyll a concentration (Chl a: mg.L1) was estimated from 1 L of water, which was collected and transported in the dark and at low temperature to the laboratory and then filtered on GFC filters and extracted using 100% acetone. The absorbance was measured with a spectrophotometer at 630 nm, 647 nm, 664 nm and 750 nm and the concentration was estimated according to Rodier et al. (1996). 2.3. Sediment analysis For granulometric analysis, the fine fraction (<63 mm) was measured by wet sieving and rinsed with fresh water to remove the salt. Other sediment fractions were sieved on a sieve shaker. The sediment material was sieved through a six-sieve column (2, 1, 0.5, 0.250, 0.125 and 0.063 mm) (for detail see Mosbahi et al., 2016). The sediment was classified according to Wentworth's sedimentary nomenclature (Wentworth, 1922). The organic matter was determined by the loss on ignition method (oven drying for one week at 60
C, measurement of dry weight, ashing in an oven at 500
C for 5 h followed by measurement of ashed weight) (for detail see Mosbahi et al., 2016). Contents of heavy metals (Pb, Zn, Cd and Cu), Phosphorus (P), Fluorine (F) and Nitrogen (N) were determined after digesting the powder sample in aqua regia (HCl, HNO 3 , H2O) at 95
C, and analysis by Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES) and Mass Spectrometry (ICP-MS).

2.4. Data analysis 2.4.1. Ecological indicators In the present study, two biotic indices are considered for each sample according to the station and season. AMBI (AZTI Marine Biotic Index, Borja et al., 2000) and BO2A (Benthic Opportunistic Annelids Amphipods index; Dauvin and Ruellet, 2009; Dauvin et al., 2016). AMBI is calculated using the AZTI list (www.azti.es) according to the recommendations of Borja and Muxika (2005). The BO2A (Benthic Opportunistic Annelids Amphipods index) is based on the ratio between opportunistic annelids (i.e. annelids of ecological groups IV and V of the AMBI) and amphipods (Dauvin et al., 2016). For the assessment of environmental quality, collected species were assigned to the five ecological groups (available on web page: http://www.azti.es) (EGI: sensitive species; EGII: indifferent species, EGIII: tolerant species, EGIV: second order opportunistic species; and EGV: first order opportunistic species) according to Borja et al. (2000). 2.4.2. Univariate analysis The main structure parameters of the benthic macrofauna determined at each station are the richness species (S: number of taxa), abundance (A: number of individuals/m2), Shannon-Weaver diversity index (H0 ) (Shannon and Weaver, 1963), and Pielou's evenness (J0 ) (Pielou, 1966). Data analysis was performed using the PRIMER®-v6 software package (Plymouth Routines in Multivariate Ecological Research) (Clarke and Gorley, 2006). Species are classified into five trophic groups according to the recent literature: selective deposit feeders (SDF), detritus feeders (DF), suspension feeders (SF), carnivores (C), and micrograzers (mG) (for detail see Mosbahi et al., 2016). Regarding the seasonal parameters, a Shapiro-Wilk normality test and a Bartlett's test for homogeneity of variance are performed

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prior to each ANOVA to check whether the assumptions of ANOVA are met and if data transformation is necessary. Then, one-way ANOVAs are performed to assess the influence of the seasons on abiotic variables (temperature, salinity, pH, organic matter, dissolved oxygen and Chl a), diversity indices (S, A, H0 and J0 ) and biotic indices (AMBI and BO2A). A Tukey Honestly Significant Difference test is used to determine differences between the seasons and sites. These statistical procedures are performed with the R software. To visualize the inshore/offshore gradient, abiotic parameters are represented using version 9 of the Arc-Geographic Information Systems (GIS) software. 2.4.3. Multivariate analysis The original data consists of a ‘stations  species’ matrix, which is obtained after averaging data for the four seasons. Macrobenthic abundances are firstly square-root transformed to minimize the influence of the most dominant taxa. Cluster analysis based on the Bray-Curtis similarity allows us to assess differences in benthic assemblages between stations. A SIMilarity PERcentages (SIMPER) test is performed to determine which species contribute most to within-group similarity. The significance of differences between the obtained groups of samples is assessed by Analysis of similarities (ANOSIM). The structure of benthic assemblages between seasons and stations is compared by a two-way permutational multivariate analysis of variance (PERMANOVA), with Season (Se, four levels) and Stations (Si, twelve levels). To establish correlations between biological parameters and biotic similarity, the datasets are compared using PCA (Principle Components Analysis). Furthermore, to understand and identify the relations between faunal distributions and their habitat conditions, BIOtic and ENVironmental linking analysis (BIO-ENV) is performed using the dissimilarity matrix of benthic fauna and environmental variables data. All analyses are carried out using the PRIMER®-v6 software package (Clarke and Gorley, 2006). Pearson correlation coefficients are used to determine relationships between pollution proxies (e.g. heavy metals, organic matter) and biotic indicators (H0 , J0 , AMBI and BO2A). Pearson correlation coefficients are calculated by the SPSS Statistics 20 software. 3. Results 3.1. Environmental parameters The results of sediment analysis (sand and mud percentages) are reported in Table 1. The percentage of mud is high in the majority of stations (S1 to S8), in contrast to the last four stations (i.e. S9, S10, S11 and S12) which show a great sand content. Nevertheless, no seasonal variation can be observed according to sediment type (ANOVA; F ¼ 132.4; p ¼ 0.021). The organic matter and heavy metal concentrations in the sediment are very high for the stations closest to anthropogenic inputs (S1, S2, S3 and S4), and low at the deeper stations (S9, S10, S11 and S12). Heavy metal concentrations vary significantly between the stations (ANOVA; for all cases p < 0.001), but not according to the seasons (p ¼ 0.12) (see Table 2). Physicochemical parameters show high seasonal and spatial fluctuations (Table 1). The temperature varies between 12.2
C in winter (S8) and 32.4
C in summer (S2), and marked seasonal variations are recorded (ANOVA; F ¼ 356.8; p < 0.001). Salinity ranges from 34.8 in winter (S8) to 42 in autumn (S5). Similarly, salinity displays a significant seasonal pattern (ANOVA; F ¼ 3.3; p < 0.05). The level of dissolved oxygen is relatively low (2 mg.L1) in winter (S2) and high (16 mg L1) in spring (S12). Chlorophyll a concentrations vary from 0.8 mg L1 in winter (S1) to 16.40 mg L1 in spring (S12). The pH varies between 4.12 in summer (S1) and 8.60 in spring (S11). Dissolved oxygen, Chlorophyll a and pH show a significant seasonal

477

and spatial trend throughout the sampling year (ANOVA; F ¼ 11.02; p < 0.01). The organic matter content (% OM) varies between 38.2% in spring (S2) and 4.2% in autumn (S10) and shows a significant spatial variation (ANOVA; F ¼ 132.04; p < 0.001) (Table 3). 3.2. Faunal composition: seasonal and spatial variation The taxonomic identification of the collected invertebrates yielded a list of 106 taxa. The seasonal variation of the diversity indices reveal that the taxonomic richness ranges from a minimum of 6 at S2 in winter to a maximum of 31 at S10 in autumn The taxonomic richness varies significantly between seasons (ANOVA; F ¼ 18.66; p < 0.05) and stations (ANOVA; F ¼ 23.46; p < 0.05). The abundance of benthic communities shows significant spatiotemporal fluctuations (ANOVA; F ¼ 112.5; p < 0.05), with maximum values in summer (10,866 ind.m2 in S10) and autumn (12,460 ind.m2 in S12) and minimum values in winter (546 ind.m2 in S1). Shannon's index, expressed in bits.ind1, varies from 2.89 (at S7) to 3.8 (at S10) in spring, from 2.78 (at S1) to 4.1 (at S8) in summer, from 2.85 (at S12) to 3.9 (at S8) in autumn and from 2.1 (at S3) to 3.1 (at S6) in winter. The highest values of Pielou's index are recorded during spring (0.90 at S10) and summer (0.94 at S12), while the lowest values are found in winter (0.51 at S2). Diversity indices show a significant spatio-temporal variation (ANOVA; F ¼ 12.2; p < 0.05) (Fig. 2). During the four seasons, selective deposit feeders (SDF) are dominant at the majority of stations. All year around, carnivores (C) dominate the stations (S1, S2, S3 and S4) closest to the phosphogypsum discharges. SDF dominate in winter (65%), in autumn (49%) and in spring (43%). The other trophic groups are more balanced in spring (12% C, 15% DF, 17% SF and 13 % mG) than in summer, when SDF clearly dominates (40%) followed by C (23%) and DF (18%), while in winter mG (14%) and SF (12%) are dominant (Fig. 3). The dendrogram allows to classify the 12 stations into two separate groups at a 50% level of similarity; using a similarity of 55%, the first group can be separated into two sub-groups (Fig. 4). Species contributions and abundance of these group and subgroups are represented in Table 4. The first sub-group (a) corresponds to four offshore stations (S9, S10, S11 and S12) located far from anthropogenic discharges. These stations are composed of medium to coarse sediment, poor in organic matter and with low heavy metal concentrations, covered by Posidonia oceanica seagrass. The second sub-group (b) corresponds to intermediate stations (S5, S6, S7 and S8) characterized by mud and fine to medium sand covered by the algae Ulva rigida and the seagrass Cymodocea nodosa. The second group (c) corresponds to four sampling stations close to the anthropogenic discharges (S1, S2, S3 and S4) characterized by unvegetated mud sediment with a high concentrations of organic matter and heavy metals. This group is strongly represented by numerous tolerant and opportunistic species (Table 4). ANOSIM analysis shows a significant difference between these three groups (RANOSIM ¼ 0.46; p < 0.001). 3.3. Linking macrobenthic fauna and environmental variables A PCA was performed for the 12 stations on each seasonal set of hydrological (e.g. temperature, salinity, pH, clearness of water, depth and dissolved oxygen), edaphic (organic matter and elemental concentrations) and biological variables (chlorophyll a and macrofauna benthic abundance) (Fig. 5). This analysis shows that the distribution of benthic organisms is linked to several environmental factors throughout the year. The first principal component (explaining 59.36% of the total inertia in spring, 68.33% in summer, 67.55% in autumn and 70.10% in winter) allows us to distinguish those stations closer to the phosphogypsum discharge

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Table 1 Main characteristics of sampling stations (average of the four seasons): Us: Ulva spp; Cp: Caulerpa prolifera, Cn: Cymodocea nodosa; Po: Posidonia oceanica, -: unvegetated sediment; M: Mud; FS: Fine Sand; MS: Medium Sand; CS: Coarse Sand; Q50: median grain size; Diss oxy: dissolved Oxygen; Chl a: Chlorophyll a; colours are as follows: red: Poor status; Yellow: Moderate; Green: Good; Blue: High.

Table 2 Annual mean pollutant concentrations in sediments collected from sampling stations in the coastal area south of Sfax. Stations

Heavy metals (ppm) Pb

Cd

Cu

Zn

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12

10.2 ± 0.1 7.7 ± 0.1 9.8 ± 0.1 8.4 ± 0.6 4.2 ± 0.2 2.6 ± 1.0 4.2 ± 0.5 3.9 ± 0.6 0.04 ± 0.1 1.0 ± 0.5 1.2 ± 0.1 1.0 ± 0.3

826 ± 121 964 ± 164 1.243 ± 202 1.480 ± 189 1.030 ± 102 992 ± 68 1.021 ± 128 860 ± 58 168 ± 43 582 ± 94 210 ± 42 118 ± 88

9.8 ± 1.0 4.1 ± 0.9 5.7 ± 1.0 18.5 ± 2.3 3.7 ± 0.1 11.0 ± 1.2 21.0 ± 2.1 4.8 ± 0.1 16.5 ± 1.1 18.1 ± 2.0 12.0 ± 1.6 4.0 ± 0.1

2.925 ± 226 5.725 ± 174 5.725 ± 167 3.675 ± 211 1.420 ± 178 1.182 ± 265 988 ± 106 1.040 ± 162 76 ± 24 60 ± 28 124 ± 8 164 ± 9

P (ppm)

F (%)

N (%)

3.422 ± 412 4.212 ± 390 3.131 ± 289 2.720 ± 268 660 ± 168 724 ± 126 564 ± 88 428 ± 65 125 ± 80 198 ± 76 248 ± 60 165 ± 49

0.5 ± 0.1 1.0 ± 0.1 3.0 ± 0.2 5.0 ± 1.0 0.6 ± 0.02 1.0 ± 0.01 4.0 ± 0.1 1.2 ± 0.1 0.1 ± 0.02 2.2 ± 0.8 2.0 ± 0.1 3.8 ± 0.1

0.4 ± 0.01 0.6 ± 0.06 1.0 ± 0.09 0.9 ± 0.01 0.1 ± 0.02 0.9 ± 0.05 2.0 ± 0.15 0.5 ± 0.08 3.0 ± 0.02 1.2 ± 0.11 2.0 ± 0.08 2.7 ± 0.05

(S1, S2 and S3) High concentrations of organic matter, heavy metal and other trace elements are correlated with these edaphic factors during the four seasons. On the contrary, stations situated away from the anthropogenic releases are positively correlated mainly with physico-chemical parameters, chlorophyll a, depth and clearness of water. The results of the BIOENV analysis (Table 5) indicate that the best correlations occur with variables related to dissolved oxygen, pH and Phosphorus.

and tolerant species (EGIII) including Amphicteis gunneri, Dexamine spiniventris and Melinna palmata. The average values of biotic indices AMBI and BO2A are significantly different between stations (ANOVA; p < 0.05). Biotic indices suggest higher environmental quality in the offshore stations compared with stations in front of the anthropogenic inputs. These indices show a significant correlation with organic matter and heavy metal contamination, mainly with Pb, Zn, and P (Table 6).

3.4. Ecological status

4. Discussion

Stations in front of the anthropogenic discharges (i.e. S1, S2, S3 and S4) can be classified by both indices AMBI and BO2A as having poor and moderate status (Fig. 6). These stations are dominated by tolerant species (EGIII) such as Platynereis dumerilii, Perinereis cultrifera, Nereis spp. and Corophium insidiosum as well as opportunistic species (EGIV and EGV) such as Cirratulus cirratus, Hediste diversicolor and Capitella capitata. Contrariwise, stations away from anthropogenic inputs are classified by both biotic indices as having good ecological status (unpolluted). These stations with low levels of chemical contamination and organic matter are strongly dominated by the sensitive species (EGI) Euclymene oerstedi, Cymadusa filosa, Gammarus insensibilis, Amphitritides gracilis, Melita palmata, the indifferent species (EGII) Lumbrineris tetraura, Drilonereis filum

The coastal zone south of Sfax has become one of the most damaged Mediterranean coasts, leading to significant degradation of the environment by diverse anthropogenic urban and industrial pressures (Drira et al., 2016, 2017a,b; Naifar et al., 2018). These activities cause various environmental impacts including the local appearance of red tides, unbalanced local benthic communities (Rabaoui et al., 2015; Naifar et al., 2018), degradation of marine habitats (Zaghden et al., 2014; Drira et al., 2016), malformations in different benthic fauna (Ayadi et al., 2015) and the disappearance of some marine species (El Kateb et al., 2016). The recorded levels of metallic/organic contaminants in coastal sediments south of Sfax are higher than values observed in other s, i.e. Kneiss Islands (Mosbahi et al., 2015), parts of the Gulf of Gabe

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Table 3 Results of two-way ANOVAs with factors for season. Zone and season-zone interaction for the 17 parameters (*: significant variation). Parameters

Factors

F

p

Cd

season zone season:zone season zone season:zone season zone season:zone season zone season:zone season zone season:zone season zone season:zone season zone season:zone season zone season:zone season zone season:zone season zone season:zone season zone season:zone season zone season:zone season zone season:zone season zone season:zone season zone season:zone season zone season:zone season zone season:zone

0.024 72.89 0.606 1.78 1.88 1.14 0.71 0.85 0.23 0 257 0 0.73 1.98 0.31 0.18 47.5 0.27 0.11 11.07 0.11 4.47 83.1 0.41 2.73 242.9 1.31 0.60 97.8 0.55 0.43 47.9 0.16 3.31 0.45 1.18 0.18 47.5 0.27 356.8 0.62 1.68 0.41 283.2 0.35 0.94 132.4 1.32 0.85 86.6 1.37

0.86 <0.001* 0.72 <0.001* <0.001* <0.01* 0.55 0.44 0.96 1 <0.001* 1 0.54 0.15 0.93 0.91 <0.001* 0.94 0.95 <0.001* 0.99 <0.001* <0.001* 0.86 0.06 <0.001* 0.28 0.62 <0.001* 0.76 0.73 <0.001* 0.98 <0.01* 0.64 0.34 0.91 <0.001* 0.94 <0.001* 0.54 0.15 0.74 <0.001* 0.90 0.43 <0.001* 0.27 0.47 <0.001* 0.25

Chlorophyll a

Cu

Depth

F

Mud

N

Oxy

P

Pb

pH

Salinity

Sand

Temperature

Transparency

OM

Zn

Kerkennah Islands (Aloui-Bejaoui and Afli, 2012), Boughrara Lagoon (Khedhri et al., 2014, 2016) or on the north coast of Tunisia such as Bizerte lagoon (Afli et al., 2009) and in many other Mediterranean areas (Magni et al., 2005; Smaoui-Damak et al., 2006). These higher levels of heavy metals, fluoride and phosphorus were previously recorded by El Zrelli et al. (2018) and Ayadi et al. (2015) s and Ghannouch in zones exposed to in the areas of Skhira, Gabe various pollution sources for many years. The different types of effluents are discharged as untreated industrial wastes and mainly via phosphogypsum outfalls. Recently, Naifar et al. (2018) have studied the spatial distribution and contamination of heavy metals in marine sediments on the southern coast of Sfax. These authors show that the surface marine sediments in this zone are heavily polluted by elements such as Cd, Cu, Zn, Pb and P mostly derived from anthropogenic sources. Due to their toxicity, nonbiodegradability and accumulative behaviors, heavy metals are

Tukey test coasts intermediate s offshore stations

coasts intermediate s offshore stations

coasts intermediate s offshore stations

coasts intermediate s offshore stations wintersautumnssprings summer coasts intermediate s offshore stations

coasts intermediate s offshore stations

coasts intermediate s offshore stations

coasts intermediate s offshore stations wintersautumnsspringssummer

coasts intermediate s offshore stations wintersspringssummersautumn

coasts intermediate s offshore stations

coasts intermediate s offshore stations

coasts intermediate s offshore stations

generally considered as dangerous environmental pollutants (Billah et al., 2017). These elements play a role in many biological and geochemical cycles because of their presence in both solid and dissolved form. Marine coastal sediments of Sfax are usually dominated by terrigenous particles and shell debris. These sediments are considered as a reservoir able to store a wide range of pollutants such as heavy metals (Naifar et al., 2018). Besides, metal enrichment of seawaters causes the accumulation of these pollutants in sediments and marine organisms, which in turn leads to their biomagnification in the trophic chains of marine systems a human health risks (Rabaoui et al., 2017; El Zrelli et al., 2018). The structure of communities on the coast south of Sfax is similar to that observed in other parts of the Mediterranean ecosystem, dominated mainly by polychaetes, crustaceans, molluscs, cnidarians and echinoderms (Khedhri et al., 2014; Mosbahi et al., 2016; Boudaya et al., 2019). In terms of species richness and

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Fig. 2. Box plots of seasonal variability of the principal benthic macrofauna from spring 2015 to winter 2016: (a) number of species, (b) abundance (ind.m2), (c) Shannon-Weaver diversity index (bits.ind1) and (d) Pielou's evenness.

abundance, the macrobenthic community on the coast south of Sfax is similar to that in the Bay of Skhira (Boudaya et al., 2019), the lagoon of Boughrara (Khedhri et al., 2014, 2016) and the lagoon of Smir (Chaouti and Bayed, 2011), with an average of 9e25 species per 0.2 m2 and 546 ind.m2 to 12,460 ind m2. Nevertheless, the species richness, abundance and diversity indices of macrobenthic fauna recorded south of Sfax appears low compared to other s, such as the Kneiss neighboring ecosystems of the Gulf of Gabe Islands (Mosbahi et al., 2016) and Skhira Bay (Boudaya et al., 2019) which possess a high biodiversity. This difference seems to be related to the influence of anthropogenic factors (i.e. phosphogypsum outfall and diverse polluted water discharges) in the Sfax marine ecosystem. In fact, the intense industrial, urban and maris has time development along the western coast of the Gulf of Gabe led to an increase of pollution, impacting marine systems and changing the biodiversity, the structure and functioning of benthic communities (Hamza et al., 2000). Many studies pointed out that marine pollution enhances the re-suspension of sediments and the accumulation of organic matter, resulting in multiple problems such as a decrease in clearness of water, increased turbidity and a decrease in bottom oxygen, along with a lowering of primary production as well as algal and seagrass biomass (that rely on light for photosynthesis). Moreover, pollution has been shown to cause

changes in benthic community diversity, food web structure and mortality of aquatic organisms (especially sensitive species) (see Islam and Tanaka, 2004). On the coast of south of Sfax, three distinct benthic invertebrate assemblages are identified. These assemblages are correlated with dissimilarities of environmental variables during the sampling year. The first assemblage group (a) corresponds to offshore stations located far from the anthropogenic inputs, composed of medium to coarse sand covered by Posidonia oceanica beds, characterized by high diversity indices with relatively low organic matter and heavy metal contents. This group is essentially represented by sensitive and tolerant species such as the polychaetes Lumbrineris tetraura, Amphicteis gunneri, Melinna palmata, Euclymene oerstedi and the amphipods Cymadusa filosa, Dexamine spiniventris and Gammarus insensibilis. The second group (b) corresponds to stations also located relatively far from anthropogenic inputs. This group is characterized by shallow waters and muddy sediment, and is dominated by the polychaete species Cirratulus cirratus, Euclymene lombricoides, Perinereis cultrifera, Glycera tridactyla and Lumbrineris tetraura, as well as the amphipods Gammarus insensibilis and Dexamine spiniventris. The third group (c) corresponds to stations sampled closer to anthropogenic inputs, characterized by muddy sediment with enrichment in organic matter and high

N. Mosbahi et al. / Environmental Pollution 253 (2019) 474e487

481

Fig. 3. Seasonal variation of the percentages of the main trophic groups: C, carnivores; SDF, selective deposit-feeders; DF, detritus feeders; mG, micrograzers; SF, suspension feeders; a, b and c; three benthic assemblages identified by cluster.

Fig. 4. Dendrogram showing hierarchical clustering of the 12 sites, using group average linking of Bray-Curtis similarities on standardized and square-root-transformed abundance data.

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Table 4 Cluster analysis of groups, showing similarities between 12 stations sampled between 2015 and 2016 for the most representative species contributing within-group similarity (C%) determined by SIMPER analysis with species mean abundance A (ind.m2) for each assemblage. Sub-group a

Sub-group b

Group c

Station 9; 10; 11; 12

Stations 5; 6; 7; 8

Stations 1; 2; 3; 4

Species

C (%)

A

Species

C

A

Species

C (%)

A

Lumbrineris tetraura Amphicteis gunneri Melita palmata Melinna palmata Euclymene oerstedi Cymadusa filosa Dexamine spiniventris Gammarus insensibilis Cirratulus cirratus

51.9 49.1 46.3 43.5 39.9 35.0 29.3 23.3 16.1

158 158 158 204 280 323 338 410 1.455

Lumbrineris tetraura Glycera tridactyla Cymadusa filosa Perinereis cultrifera Euclymene lombricoides Hilbigneris gracilis Dexamine spiniventris Gammarus insensibilis Cirratulus cirratus

51.6 48.2 44.6 41.0 37.3 32.8 27.2 21.4 12.7

108 114 119 134 140 179 190 283 409

Perinereis cultrifera Glycera tridactyla Drilonereis filum Eunice vittata Dexamine spiniventris Euclymene lombricoides Scrobicularia plana Cirratulus cirratus Cerithium scabridum

53.6 50.1 46.1 42.1 37.1 31.3 25.4 19.0 9.50

66 78 80 98 226 115 131 185 188

Fig. 5. Principal Component Analysis (PCA) (axis 1 and 2), season by season, of biological parameters and selected environmental variables at the 12 sampling stations.

concentrations of heavy metals and trace elements. During the whole year, stations located close to anthropogenic discharges (S1, S2, S3 and S4) appear to be the most disturbed (polluted), showing positive correlations with high metal contamination and organic matter content. These polluted stations are mostly dominated by tolerant and opportunist species such as the carnivorous polychaetes Capitella capitata, Eunice vittata, Hediste diversicolor, Drilonereis filum and Euclymene lombricoides, as well as the introduced (or exotic) gastropod Cerithium scabridum and their presence

appears to be linked to the availability of trophic resources (e.g. dead animal corpses, organic waste). These opportunist species proliferate in response to the excess organic matter at polluted stations (Afli et al., 2009; Aloui-Bejaoui and Afli, 2012; Dauvin et al., 2017). Otherwise, the number and density of macrobenthic communities increases at increasing distance from environmental stresses. Likewise, the most dominant species show a significant variation along the pollution gradient. We can clearly see that benthic diversity on the coast south of Sfax is influenced by

N. Mosbahi et al. / Environmental Pollution 253 (2019) 474e487 Table 5 Results of BIOENV analysis showing the ten highest Spearman rank correlations based on numerous environmental factors: Oxy: oxygen; P: Phosphorus; OM: organic matter; Pb: lead; Transp: clearness of water; depth and pH. Number of variables

Variables

Spearman Correlation (r w)

2 2 2 3 3 3 4 4 4 4

Oxy-pH Oxy-P pH-P Oxy-pH-P Oxy-pH-OM Oxy-pH-Pb Oxy-pH-P-OM Transp-Oxy-pH-P Oxy-pH-P-Pb Depth-Oxy-pH-P

0.837 0.821 0.854 0.864 0.829 0.829 0.840 0.835 0.834 0.825

anthropogenic inputs. The ecological status ECoQS of the south coast of Sfax is assessed here using biotic indices, i.e. H0 , J', AMBI and BO2A, which show significant differences between stations. The diversity and biotic indices increase with distance from the pollution source. The various biotic indices are all correlated among themselves, with the community parameters at the twelve sampled stations showing a certain similarity; all the stations are classified as having moderate to good ecological status. However, stations closest to the anthropogenic discharges (e.g. phosphogypsum waste outfalls) appear to be the most disturbed, being strongly dominated by pollution indicators such as the tolerant species P. cultrifera, Platynereis dumerilii and Nereis spp., as well as opportunistic species such as the polychaetes C. capitata, C. cirratus, C. chrysoderma, Heteromastus filiformis and H. diversicolor. These species are almost the same dominant species as those recorded by Dauvin et al. (2017) in Algerian harbours. These authors show that these benthic species are indeed adapted to occupying highly stressful or unstable habitats, which are also perturbed and/or denuded (Dauvin et al., 2017). However, the deeper stations far from pollution constraints display a good ecological status, with some being mostly dominated by sensitive (EGI) and indifferent species (EGII) in habitats having a high quality status. Biotic indices reveal a significant correlation with heavy metal contents, mainly with Cd, Cu, F and N and organic matter, and have lower values at polluted stations (close to anthropogenic inputs). These results are consistent with several previous studies showing that diversity and biotic indices are generally influenced by heavy metal pollution (Ruy et al., 2011;

483

Table 6 Pearson correlation coefficients (r) and associated significance values (P), for relationships between Shannon-Wiener diversity (H0 ), Pielou's evenness (J0 ), AZTI Marine Biotic Index (AMBI) and the Benthic Opportunistic Annelids Amphipods index (BO2A), as a function of the contents of four heavy metals and phosphorus, fluorine, nitrogen and organic matter in samples from the southern coast of Sfax. Significant correlations (p < 0.05) are highlighted in bold type. H0

Pb Cd Cu Zn P F N OM

J0

AMBI

BO2A

r

p

r

p

r

p

r

p

- 0.865 - 0.473 0.152 - 0.907 - 0.939 0.029 0.545 - 0.910

0.0001 0.120 0.637 0.0001 0.0001 0.930 0.67 0.0001

- 0.923 - 0.506 0.183 - 0.910 - 0.931 0.158 0.625 - 0.967

0.0001 0.093 0.570 0.0001 0.0001 0.624 0.30 0.0001

0.822 0.415 - 0.231 0.930 0.917 0.011 - 0.561 0.897

0.001 0.180 0.469 0.0001 0.0001 0.973 0.058 0.0001

0.911 0.580 - 0.169 0.904 0.916 - 0.136 0.583 0.977

0.0001 0.048 0.599 0.0001 0.0001 0.674 0.047 0.0001

Tweedly et al., 2015). Various studies have demonstrated that benthic invertebrates can be used as bioindicators in marine monitoring, and biotic indices are commonly applied to assess the ecological quality of the environment (Muxika et al., 2005). However, several authors have reviewed the use of benthic indices (see Dauvin, 2007), concluding that they are unlikely to be universally applicable since organisms are not equally sensitive to all types of anthropogenic disturbance (such as physical disturbances or chemical pollution). Hence, the various indices are likely to respond differently to different types of perturbation because each index was originally developed for a single or very few stressors (Afli et al., 2008). For example, some biotic indices (such as AMBI) are not well adapted to study different types of pollution, such as physical pollution or metal contamination (Afli et al., 2008, 2009; Khedhri et al., 2016). According to Borja and Muxika (2005), the assessment of Ecological Quality Status with AMBI can be reduced if sampled stations have a very low number of taxa and/or individuals. Generally, AMBI is based on only one group of relative abundances of the ecological groups and may lead to an erroneous conclusion if the sites are dominated mainly by sensitive or opportunistic species (Khedhri et al., 2016). Consequently, as suggested by Salas et al. (2006), the use of various biotic indices (based on ecological/trophic/taxonomic groups) to assess environmental quality should be evaluated by combining a series of indices providing additional information. During the study period, the macrobenthic composition was subject to predictable seasonal

Fig. 6. Spatial-temporal variations of AMBI and BO2A; a, b and c: three benthic assemblages identified by cluster.

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changes. In fact, the diversity indices are higher during the spring and summer and low in winter. The seasonal variations in species number, abundance and community structure of the macrofauna communities are mainly caused by recruitment in spring and summer (Reiss and Kroncke, 2005; Afli et al., 2009). Likewise, the recruitment is known to be highly variable in space and time and mainly influenced by various environmental and climatic factors during the seasonal cycle such as water temperature, hydrodynamic regime, food availability, and predation (Butman, 1987; Snelgrove and Butman, 1994). Finally, the use of benthic macrofauna and biotic indices to determine the ecological quality of the shallow marine environment of the Sfax area reveals a spatial pattern with loss of diversity at stations close to anthropogenic inputs. These stations are also strongly affected by chemical contaminants and appear to have poor to moderate ecological status compared to offshore stations that yield a stable status, representing a temporary situation. In fact, the flow of water currents from the north appears to extend the influence and increase the transfer of hazardous pollutants towards the southern areas. These pollutants influence biodiversity at several levels, being accumulated by marine species and integrated into the food chains, thus eventually affecting human health. The findings of this research could be used as suitable reference for future studies and plans for environmental management of the

coast south of Sfax, in an area covering the Thyna salt marshes. This latter area is among the most important crossroads for migratory birds in the Mediterranean and has been classified as an IBA and RAMSAR site. These marshes are breeding areas for many bird species of different ecological status.

Conflicts of interest The authors declare that there are no conflicts of interest. Dr, Nawfel Mosbahi (on behalf of the authors)

Acknowledgements The authors would like to thank all persons who helped in field sampling, laboratory analyses and providing useful data for this study, M. Dlensi for the pictures and M. Carpenter for the English revision. They also thank the five reviewers for their very useful comments and suggestions on the first version of the typescript.

Appendix A

Multiple anthropogenic pressures in the coastal Sfax area (according to MEDD, 2013; Zaghden et al., 2014) (T: Tons (1000 kg); yr: years; d: day). Anthropogenic pressures

Activities

Anthropogenic wastes

Phosphoric Acid and Fertilizer industrial company (SIAPE)

Manufacture of phosphoric acid and Trisodium phosphate

Tannery and detergents industry

Manufacture of soaps. Detergents and cleaning products

Fertilizers company

Production of chemical fertilizers

Sewage treatment station

Management of sewage outfalls

Fishing harbour of Sfax

Fishing activities

Commercial harbour of Sfax

Shipping activities

Slaughterhouse

Processing and marketing of horas livestock

Public landfill

Urban discharges

Phosphogypsum wastes: 684.000T/yr Industrial wastewater discharge: 1.720 m3/d Fuel oil: 30.000 T/yr SOx: 9.850T/yr Fluorine: 750T/yr NOx: 188 T/yr CO:19T/yr Cd: 280 kg/yr F: 1.385 T/yr Cr: 40 kg/yr Dust:165/yr Fuel oil: 410 T/yr NOx: 3.4 T/yr SOx: 12.1 T/yr Special waste: 60 T/yr Fuel oil: 1.000T/yr NOx: 8.37 T/yr SOx: 29.64 T/yr Flux ¼ 21.000 m3/d Effluent ¼ 3.000 m3/d Treatment sludge: 4.750 T/yr COD: 406 T/yr BOD: 1.195 T/yr Suspended Matter: 12.3 T/yr Nt: 58.6T/yr Pt: 697.5 T/yr Sediment pollution: hydrocarbons (5.5 mg/kg). organic pollution and nutritients Sediment pollution: hydrocarbons (180e1.40 mg/g PAH of sediment). Water discharge: 250 m3/d Suspended Matter: 140 T/yr Wastewater discharge: 55 m3/d Special waste: 500 T/yr Total suspended matter >4.350 mg/L of TSM Urban wastewater: 320 m3/d BOD ¼ 300 mg/L COD ¼ 1.050 mg/L

N. Mosbahi et al. / Environmental Pollution 253 (2019) 474e487

Appendix B Different anthropogenic pressures in coastal zone south of Sfax (1, 2: phosphogypsum wastes. 3, 4: public landfill. 5, 6, 7, 8: wastewater discharge. 9, 10, 11: hydrocarbon inputs. 12: polluted

485

sediment) and pollution effects (13: green tidal. 14: massive mortality of crabs (Portunus segnis). 15: oiled bird (Egretta garzetta); beaching marine species, 16: turtle Caretta caretta, and 17: fish (Mugil cephalus).

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