Benthic foraminiferal assemblages as pollution proxies along the coastal fringe of the Monastir Bay (Tunisia)

Accepted Manuscript Benthic foraminiferal assemblages as pollution proxies along the coastal fringe of the Monastir Bay (Tunisia) Mohamed Damak, Fabrizio Frontalini, Boubaker Elleuch, Monem Kallel PII:

S1464-343X(18)30354-6

DOI:

https://doi.org/10.1016/j.jafrearsci.2018.11.013

Reference:

AES 3368

To appear in:

Journal of African Earth Sciences

Received Date: 13 April 2018 Revised Date:

11 November 2018

Accepted Date: 13 November 2018

Please cite this article as: Damak, M., Frontalini, F., Elleuch, B., Kallel, M., Benthic foraminiferal assemblages as pollution proxies along the coastal fringe of the Monastir Bay (Tunisia), Journal of African Earth Sciences (2018), doi: https://doi.org/10.1016/j.jafrearsci.2018.11.013. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT 1

Benthic foraminiferal assemblages as pollution proxies along the coastal fringe of the

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Monastir Bay (Tunisia)

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Mohamed Damak1, 2*, Fabrizio Frontalini3, Boubaker Elleuch1, Monem Kallel1

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Sfax, BP 1173, 3038 Sfax (Tunisia)

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Association Notre Grand Bleu (NGO), Cap Marina, 5000 Monastir (Tunisia)

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Dipartimento di Scienze Pure e Applicate, Università degli Studi di Urbino "Carlo Bo",

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Campus Scientifico Enrico Mettei, 61029 Urbino (Italy)

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* [email protected]

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Laboratoire de Génie de l’Environnement et Écotechnologie (GEET), ENIS, Université de

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Abstract

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The Monastir Bay is one of the most important resources of marine diversity in Tunisia. The

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marine biodiversity quality of its coastal area has been however affected by several industrial,

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fishing and fish-farming activities. A multidisciplinary characterization based on geochemical

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analyses of sediment and benthic foraminifera was undertaken to evaluate the environmental

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quality of marine sediments. The geochemical data combined with the statistical results

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suggests an overall contamination of sediment mainly by Zn, Ni and Cu and the identification

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of an area particularly polluted. This zone corresponds to the area in front of the Khniss drain

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that has been historically affected by the presence of multiple sources of pollution. The site is

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also characterized by a poorly diversified benthic foraminiferal assemblage, reflecting the

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poor environmental conditions. Some species such as Quinqueloculina seminula and

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Vertebralina striata appear to be positively related to EF and might be considered as tolerant

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taxa to pollution in the Monastir Bay. The present study further reinforces the application of

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benthic foraminifera as proxies of pollution and as bioindicators of the environmental quality

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and represents among the first contributions in a Tunisian coastal marine area based on living

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benthic foraminifera as bioindicators.

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1. Introduction

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Benthic foraminifera are unicellular organisms with a widespread distribution from marine

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to transitional marine environments (Murray, 2006). Many benthic foraminiferal studies have

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proven the considerable value of these protists as bioindicators and have therefore been

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widely applied to biomonitoring (i.e., Alve, 1995; Armynot du Châtelet and Debenay, 2010;

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Frontalini and Coccioni, 2011, for review). Because of their widespread distribution, short life 1

ACCEPTED MANUSCRIPT and reproductive cycles, high biodiversity, great abundance, and specific ecological

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requirements, benthic foraminifera have been successfully used as bioindicators in coastal

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marine environments (Frontalini and Coccioni, 2008). In this context, benthic foraminifera

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have been used as bioindicators in areas affected by natural and/or anthropic stress including

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salinity and temperature fluctuations, high organic matter input, low oxygen availability as

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well as organic and inorganic pollutants (Alve, 1995; Yanko et al., 1999). Benthic

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foraminifera commonly respond to adverse environmental conditions by changing the

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assemblages’ composition and parameters (i.e., Alve, 1995).

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Although benthic foraminifera have been widely applied to assess the environmental

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quality in the Mediterranean Sea areas (i.e., Debenay, 2001; Frontalini and Coccioni, 2008;

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Coccioni et al., 2009), only a few studies have been performed in Tunisian coastal areas,

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namely in the Gabes Gulf (Aloulou et al., 2012; Ayedi et al., 2015), in the northern coast of

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the Sfax city (Mkawar et al., 2007) and Bizerte (Martins et al., 2015, 2016) and Djerba

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lagoons (El Kateb et al., 2018). Traditionally, the environmental quality of Tunisian coastal

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areas has been mainly assessed by considering the physico-chemical characteristics, heavy

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metal, organic matter and hydrocarbon contents in sediments. The Monastir Bay is situated on

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the eastern coast of Tunisia and is one of the most important resources of marine resource and

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biodiversity along the Tunisian coast. However, a significant increase in industrial, fishing

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and fish farming activities has severely affected the environmental quality (i.e., Sassi et al.,

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1998a,b; Nouira et al., 2013a,b; Challouf et al., 2017). Several environmental investigations

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have been carried out to monitor the heavy metal (Sassi et al., 1998b), organic matter (Sassi et

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al., 1998a), polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs)

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(Nouira et al., 2013a) as well as polycyclic aromatic hydrocarbons (PAHs) (Nouira et al.,

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2013b) along the Monastir coast.

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This study, for the first time, aims to survey the environmental quality of marine surface

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sediment of the Monastir Bay coast by conventional chemical analyses coupled with benthic

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foraminiferal ones, also to determine the relationships among geo-chemical data and benthic

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foraminiferal distributions.

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2. Study area

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The study area, which is the littoral of Monastir-Teboulba (Monastir Bay), lies on the

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eastern shore of Tunisia. The Monastir Bay waters are characterized by a weak hydrodynamic

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regime due to the sub-marine topography (i.e., 3 m isobaths at ~2 km from the coastline of

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Khniss-Ksibet El Mediouni and at ~900 m from the coast of Lamta-Sayada) (Souissi et al., 2

ACCEPTED MANUSCRIPT 2004). In fact, the bathymetry, in the Monastir Bay, is irregular and extends in the major part

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of the bay as a shore-flat (Sassi et al., 1998a; Nouira et al., 2013b). The bay is delimited by

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two sandy shoals (Ras Dimes sand spit in the South-East of the bay, and El Enf sand spit in

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the North-West of the bay) this acts as physical barriers between the shore and the open sea

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(Fig.1).The shoal of Teboulba isolates more or less the bay from the open sea. The coastal

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fringe represents a receptacle of multiple wastewaters from the urban zone (five ports, two

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wastewater treatment plants, and the Khniss drain) as well as from active fish farms within the

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bay (Nouira et al., 2013a; Challouf et al., 2017). The drain of Khniss collects domestic and

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industrial wastewaters from riverine discharges and is considered as the main source of

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pollutants (Nouira et al., 2013a). These wastewaters are directly discharged in numerous

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points along the coast (Sassi et al., 1998a; Nouira et al., 2013a).

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The Monastir Bay is considered as a semi-enclosed lagoon (Nouira et al., 2013a; Challouf

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et al., 2017) and as a consequence of the confined conditions, nutrient-rich wastewaters have

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progressively promoted the eutrophication and the establishment of anoxic conditions in

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surface sediments (Sassi et al., 1998b).

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3. Materials and methods

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3.1 Field Sampling

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Sampling sites are placed along the coastal fringe of the bay from Monastir city to

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Bkalta city. In August 2015, superficial sediment samples were collected from 10 stations

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(Fig.1), at a water depth not exceeding 0.5 m, using 1-m2 quadrat. Sampling sites were

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selected from a presumed near and between the pollution sources and human activities. From

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each sampling site, 50 cm3 surface sediments were collected (upper 1 cm) in 3 replicates for

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foraminiferal analyses and were immediately treated with a Rose Bengal solution (2 g of Rose

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Bengal in 1 L of ethanol). Additionally, ca. 2 kg of sediment and 500 ml sea water were

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collected, immediately frozen on dry ice and transported in a dark container to the laboratory

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for grain-size and geochemical and physico-chemical analyses, respectively.

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3.2 Physico-chemical analysis of water

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The physico-chemical parameters of water such as conductivity, pH and total dissolved

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solids (TDS) were measured in the laboratory. The pH was measured by pH meter (model:

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WTW inoLab® pH 720) and conductivity by conduct meter (model: WTW inoLab® 7110).

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The TDS were measured following the method of Rodier et al. (2009).

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3.3 Grain-size analysis Grain-size analyses were performed using AFNOR mesh-type sieves (Ayedi et al., 2015).

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Briefly, before the analysis, about 100 g of sediments were digested with hydrogen peroxides

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(H2O2) solution to remove organic matter content (Folk, 1974 ) and then dried in an oven at

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40°C. The grain-size was then classed as very coarse sand (2 mm-1 mm), coarse sand (1 mm-

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500 µm), medium sand (500 µm-250 µm), fine sand (250 µm-125 µm), very fine sand (125

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µm-63 µm) and silt and clay (<63 µm) (USDA-NRCS, 2002).

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3.4 Organic matter

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Approximately 1 g of <2 mm dried sediment was finely grounded with mortar and pestle

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for total organic carbon (TOC) and total nitrogen (TN) analyses. The TOC analysis was

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performed following the Walkley and Black methodology which involves the titration with

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ferrous ammonium sulfate of the dichromate left after a wet oxidation of the samples with

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potassium dichromate (Walkley and Black, 1933). On the other hand, Kjeldahl digestion is

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used for TN determination, following MA.300-NTPT2.0. The total phosphorous (TP)

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contents were analyzed as orthophosphate following the Murphy and Riley (1962)

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spectrophotometric method, after samples digesting and transformation of phosphorylated

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compounds into orthophosphate. The digested solutions are attacked by sulphonitric acid and

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in the presence of ammonium molybdate forming a complex phosphomolybdic anion, which

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after reaction with ascorbic acid gives a blue color. The optical density was measured by

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colorimetry at 880 nm and expressed in mg/g.

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3.5. Trace metal analysis

Concentrations of selected trace metals were analyzed in the sediment fraction <63 µm,

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after digestion, in three replicates to minimize error, in a sequence of heating steps using a

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ratio of 10:5 ml nitric acids (HNO3, 65 %) and hydrochloric acids (HCl, 36 %), respectively.

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Extracts were then rinsed with an additional 2 ml HNO3, diluted 50 times with deionized

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water and filtered. The digested samples were aspirated for Fe, Cu, Zn, Cr, Ni and Pb

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elements through atomic absorption spectrometry (AAS).The detection limits (in ppm) were

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0.006 for Fe, 0.022 for Cu, 0.008 for Zn, 0.05 for Cr, 0.01 for Ni and 0.05 for Pb.

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In order to evaluate the trace metal sediment contamination, several indices, namely

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Enrichment Factor (EF), the Contamination Factor (CF) and the Pollution Load Index (PLI)

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of Tomlinson et al. (1980) were calculated.

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The EF is considered to compensate the differential variability of trace metals in sediment

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from geogenic (crustal) and anthropogenic (on-crustal) (Feng et al., 2004). Iron has been used

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as a reference element (Likuku et al., 2013; Schintu et al., 2016). The EFis calculated as: [





]

]

[

[





]

]

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=

[

where [Metal sample]/[Fe sample] is the ratio of concentration of metal element to iron in the

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sediment sample and [Metal background]/[Fe background] is the same ratio with background

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value of standard average Earth’s crust. Turekian and Wedepohl (1961) indicated the Earth

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metal background values (ppm) as following: Cr: 35; Pb: 7; Zn: 16; Cd: 0.02; Fe: 9800; Cu: 2

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and Ni: 2. The EF’s categories proposed by Sutherland et al. (2000) were considered (Table

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1):

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Following Likuku et al. (2013), the degree of sediment contamination by metals was also

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evaluated as CF defined as: =

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! "# ] -[

$ %&'()*+,]

The determination of CF is shown in Table 2.

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[

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The PLI compares the concentrations of elements in the environment with the ones expected

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when excluding anthropogenic contributions and is calculated as ./0 = √ 7

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2 3

3 3 …

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The PLI was calculated to estimate the metal contamination status (Table 3).

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+ where “n” represents the number of metals studied and the CF is the contamination factor.

3.6 Foraminiferal analysis

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Living benthic foraminifera fauna mirror present environmental conditions, whereas total

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fauna (live and dead) provide information on a longer time-scale (Jorissen et al., 2018). For

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this reason, and for the scope of this study, the environmental assessment was based only on

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the living benthic foraminifera. Immediately after sampling, sediments were treated with a

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Rose Bengal solution (2 g of Rose Bengal in 1 L of ethanol) to separate dead and living

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foraminifera (Schönfeld et al., 2012). Sediments were carefully washed, in the laboratory,

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through a set of sieves (63 µm, 125 µm and 500 µm) to remove coarse and mud fractions. 5

ACCEPTED MANUSCRIPT From each sample and replicate, three hundred living specimens, where possible, were picked

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from the 125 and 500 µm fraction. The taxonomic identification was based following

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previous studies on benthic foraminiferal assemblages (i.e., Loeblich and Tappan, 1987;

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Cimerman and Langer, 1991). Several foraminiferal parameters, namely species richness (S,

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number of species per sample), the Fisher α index (Fisher et al. 1943), dominance (D), the

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Shannon-Weaver index or information function (H) (Shannon and Weaver, 1963), evenness

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(J); and equitability (E) were calculated using the PAST - PAlaeontologicalSTatistics data

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analysis package (version 1.68, Hammer et al., 2001).

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3.7 Statistical analysis

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Prior to the statistical analysis the selected abiotic data including EFs, salinity, TN, TOC,

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TP, pH and mud (<63 µm) were logarithmically transformed to remove the effects of orders

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of magnitude difference between variables and normalize the data (Brakstad 1992; Manly,

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1997). A Q-mode Cluster Analysis (CA) was applied to study the similarities between the

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stations. The analysis was based on the Ward’s linkage method and the Euclidean distance.

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Additionally, both a Q- and an R-mode Principal Component Analysis (PCA) were conducted

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to reduce large data matrices composed of several variables to a small number of factors

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representing the main modes of variation. In the PCA, it is also possible to compute additional

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variables (relative abundance of benthic foraminiferal species>1% and diversity indices)

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which do not contribute to the results thereof. The ordination (CA) and multivariate (PCA)

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statistical techniques were performed using Statistica 7.0.

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4. Results

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4.1 Physico-chemical parameters of water, grain-size and organic matter The mean concentrations of physico-chemical parameters in water are summarized in

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Table 4. The pH value in the study area varied between 6.72 and 8.21. The water salinity

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ranged from 27.03 and 48.01. The lowest water salinity was recorded at BM1 station.

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In the entire bay region, the sediment samples were dominated by medium to fine sand (48

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- 86 %) with a very minor mud content (Table 4). However, mud (<63 µm) was observed on

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both sides downstream of Khniss drain (BM1 and BM2), in downstream of Oued El Souk in

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Lamta (BM5), and in rear port and in front of cornice conversion of Teboulba (BM7).

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The TOC content varied between 0.5 % and 5.25 % (Table 4) with a relative higher values

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in BM1, BM5 and BM7. The TN ranged between 0.33 % and 1.67 % (Table 4) whereas TP

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from 0.02 to 0.344 mg/g (Table 4). 6

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4.2 Concentration and distribution of trace metals The concentrations of metals along the coastal fringe of the bay of Monastir are reported in

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Table 4. The highest concentration of Cr, Ni, Cu, Pb and Zn were found in BM1, BM2 and

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BM7 sites that are located between the mouth of Khniss drain (BM1 and BM2) and to the

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West of port of Teboulba (BM7). The distribution pattern of EF exhibited a minimal to

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moderate enrichment of Cr and Pb in all stations; a significant enrichment of Pb was only

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observed in BM5. Moreover, moderate to significant enrichments of Zn have been

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documented in the entire coastal fringe. However, a significant enrichment of Ni and Cu in

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the entire coastal fringe of the bay and a very high enrichment of Cu were documented in

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BM5 (Fig.2).

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The results of CFs show a low contamination of Pb and Cr along the coastal fringe. On the

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other hand, a moderate contamination with Zn element was identified in BM1, BM2, BM3

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and BM7 and a moderate contamination of Ni in BM1, BM2, BM3, BM4, BM7 and BM9. A

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considerable contamination of Cu was instead observed in BM1, BM2, BM3 and BM7

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(Fig.3).

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In order to reduce the effects of peaks of individual elements, an assessment of sediment

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quality was carried out using PLI (Fig.4). The overall contamination of sediment along the

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coastal fringe, based on the PLI values indicates a deterioration of site quality of sediment in

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BM1, BM2 and BM3. Furthermore, baseline levels of pollution are shown from BM5 to BM9

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and BM0.

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4.3 Foraminiferal distribution

A total of 37 species were recognized in the living assemblages along the coastal fringe of

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Monastir Bay. Twenty-eight species (7 hyaline, 18 porcelaneous and one agglutinated)

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exceeded 1 % of the assemblage in one sample (Fig. 5). Living assemblages were largely

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dominated by Ammonia tepida (7.84 % on average), Quinqueloculina seminula (33.45 % on

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average), Peneroplis planatus (10.6 % on average), Vertebralina striata (13.2 % on average)

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and subordinately by Ammonia parkinsoniana and Elphidium crispum.

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Species richness (S) varied from 8 (BM2 station) to 26 (BM1 station). The highest density

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was found in BM0 station (2362 specimens per 50 cm3). Whereas the diversity, using Fisher α

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index, ranges from 1 (BM2 station) to 5 (BM1 station; Fig.6).

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4.4 Statistics 7

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The Q-mode CA resulted in the grouping of samples into two main clusters (A and B)

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according to the bottom water and sediment characteristics (Fig. 7). The Cluster B is

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represented by four stations (BM1, BM2, BM5 and BM7) resulting in those with higher level

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of pollutants. All the other stations are grouped in Cluster A (Fig. 7). The PCA shows that ~66.4 % of the data variance can be explained by the first two

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principal components (factors). The sediment characteristics (< 63 µm, TN and TP) and

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salinity are the predominant elements in the first component, while the contributions to the

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second component are mainly due to EFs and pH (Fig. 8). By projecting onto the

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environmental components, the plotted position of the benthic foraminiferal assemblages’

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parameters (Fig.8a) and species (Fig. 8b) as secondary or additional variables, it appears that

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most of these biotic variables are influenced by the sediments’ characteristics. In particular,

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benthic foraminiferal diversity indices are negatively related to EFs, whereas FD is somewhat

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positively related to the mud fraction, TP and TN (Fig. 8a). Additionally, most of the species

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particularly E. crispum, Elphidium complanatum, Rosalina bradyi, Adelosina ciliarensis, and

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Adelosina pulchella are negatively related to EFs, only Q. seminula and Vertebralina striata

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appear somewhat positively related to EF. Elphidum advenum and A. tepida are negatively

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related to the first component so to the salinity gradient but positively related to TN, TP, EF

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of Cr and mud fraction.

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The Q-mode PCA groups stations mainly follow their environmental conditions in approximately the same groups obtained with the Q-mode CA (Fig. 9).

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5. Discussion

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Geochemical and benthic foraminiferal data were compiled and integrated to characterize

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the sediment quality in the coastal fringe of the Monastir Bay. The area has been deeply

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shaped by coastal development and affected by different human activities including the

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discharge of multiple effluent sources for several years that have severely promoted stressful

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conditions in the marine ecosystem (Sassi et al., 1998a,b; Zaouali and Ben Charrada, 2010;

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Nouira et al., 2013a,b). Monastir Bay is considered as one of the most important resources of

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marine species diversity with a high extent of the seagrass meadows, Posidonia oceanica L.,

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within the Tunisian territorial waters (El Asmi et al., 2003; Zaouali and Ben Charrada, 2010).

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The water quality represents one of the most important factors in the aquatic ecosystem for

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biotic proliferation and can be impacted by anthropogenic activities. The lowest water salinity

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recorded in BM1 station is attributed to the proximity of the freshwater input through Khniss

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drain. The artificial drain of Khniss is considered as one of the most important terrestrial

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ACCEPTED MANUSCRIPT inputs of water in the region. In addition to fluvial waters, this drain collects domestic and

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industrial wastewaters from riverine agglomerations (Nouira et al., 2013b). The Khniss drain

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also plays an important role in the environmental setting evolution of the Monastir Bay

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coastal fringe where its discharges effect the physic-chemical sediment parameters . In fact,

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BM1 station recorded high values of organic matter parameters such as TN, TP and TOC. The

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organic carbon, buried and preserved in marine sediments, depends on several factors such as

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the rich contributions of terrestrial input that is commonly more refractory, sediment

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metabolic activity (humification), bottom-water O2 concentration and sediment particles

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(Canfield, 1994; Burdige, 2007). The highest TOC value (5.25 %) recorded in BM5 station

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might be attributed to different factors such as the discharge of wastewaters through the

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treatment plant of Lamta, the input from the Oued El Souk in Lamta, sub-marine topography

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and a weak hydrodynamic regime. The combination of these natural and anthropogenic

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factors promotes the eutrophication and the enrichment of the organic carbon. The TOC and

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TN values recorded in the coastal fringe of the Monastir Bay, are relatively higher than those

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measured by Ayadi et al. (2016) in the southern coast fringe of Gabes Gulf with TOC and TN

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ranging between 1.95 and 2.7 % and between 0.029 and 0.058 %, respectively. However,

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Sassi et al. (1998b) assumed that the organic matter level in this zone could be due not only to

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the high algal proliferation, but also due to the domestic wastewater discharges or to the

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aquaculture stations.

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According to Donnici et al. (2012), the high values of organic matter, which are

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geochemical carriers of metals as a result of its adsorption capacity, might correspond to high

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values of heavy metals. In order to assess the contamination and to compensate for

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mineralogy and grain-size differences, heavy metals content in the sediment sample are

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commonly normalized to Fe by calculating enrichment factors (EFs) (Donnici et al., 2012).

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The EFs support the definition of the distribution of anthropogenic sediment pollution by

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confirming the high values of trace element EF in the Monastir Bay with significant

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enrichments in Ni (between 4 and 17) and Cu (between 4 and 27) in the entire coastal bay.

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Except for Ni and Cu, these values are relatively higher than those measured in the northern

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coast of Gabes Gulf by Aloulou et al. (2012) and in the south coast of Gabes Gulf (for Cu) by

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Ayadi et al. (2016). In our study, Ni and Cu EFs did not show any direct correlation with

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organic matter and muddy sediment. Additionally, to evaluate the sediment contamination

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degree by trace element, a contamination factor (CF) was determined. The overall sediment

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contamination in the studied sites, based on the CF values, indicated that sediments were

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moderately contaminated (1≤CF<3) by Ni and a considerable contamination (3≤CF<6) by Cu

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ACCEPTED MANUSCRIPT was instead observed in BM1, BM2, BM3 and BM7. On the basis of the Pollution Load Index

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(PLI) values, BM1, BM2 and BM3 site exhibited quality deterioration. In fact, BM1, BM2

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and BM3 stations represent the coastline from Khniss to Ksibet El Mediouni. This

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deterioration results from the discharge of Khniss drain, dumped treatment plant wastewaters

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of El Frina, aquaculture station and drift movement caused by swells dominating sections

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North-Northeast, Northeast and East-Northeast (Sassi and al., 1998b).

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The Q-mode CA statistical analyses showed two well-defined groups of samples according

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to their pollution degree. Specifically, cluster B includes all the stations with higher content of

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combined trace elements and organic matter, and can therefore be defined as the polluted

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ones. This cluster group includes BM1, BM2, BM5 and BM7 stations, however, cluster A

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includes all the remaining stations with relative lower level of pollutants than cluster B. The

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sediment pollution of cluster B stations could be the result of the dumping in the sea of

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treatment plant wastewaters that are enriched in organic matter and whose preservation is

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enhanced by the weak hydrodynamic regime (Sassi et al, 1998b). Although cluster A includes

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all stations that are relatively low or not polluted, it also encloses BM3 that exhibits a

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moderate deterioration of sediment quality according to PLI value (1.40). This result may be

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explained by the fact that Q-mode CA accounts for all physico-chemical parameters.

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The sediment quality of the Monastir Bay was not only evaluated by geochemical analyses,

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but also by checking the characteristics of benthic foraminiferal assemblages and their

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parameters. Numerous foraminiferal studies have considered heavy metal, organic matter and

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water salinity to be important factors affecting benthic foraminiferal distribution and

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assemblage change and underlined the suitability of benthic foraminifera in environmental

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biomonitoring (Coccioni et al., 2009; Donnici et al., 2012; Schintu et al., 2016). Benthic

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foraminifera generally respond to adverse environmental conditions by mainly undergoing

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local disappearance, assemblage changes both in composition and parameters (i.e., diversity

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and density), dwarfism, and possibly the development of test abnormalities (e.g. Alve, 1995;

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Yanko et al., 1994; Frontalini and Coccioni, 2008). Although benthic foraminifera have been

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widely applied as proxy of pollution, some areas have been poorly explored. In fact, this study

327

represents, to our knowledge, among the first contributions on benthic foraminifera as

328

bioindicators in the Monastir Bay. Similarly, the Tunisian coast has generally been

329

understudied and the only few contributions, mostly from transitional environments, are from

330

Gabes Gulf (Aloulou et al., 2012; Ayadi et al., 2016), the northern coast of Sfax city (Mkawar

331

et al., 2007), the Bizerte (Martins et al., 2015, 2016) and Djerba (El Kateb et al., 2018)

332

lagoons.

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ACCEPTED MANUSCRIPT On the northern coast of Gabes Gulf from Sfax city to Skhira Gulf, Aloulou et al. (2012)

334

applied the benthic foraminiferal assemblages as proxies of pollution. A total of sixty-eight

335

benthic foraminiferal taxa were identified and statistically related to heavy metal EFs and

336

total hydrocarbons. Lower values of density and diversity, and an increase in values of the

337

opportunistic species A. tepida and Haynesina germanica were associated with contaminated

338

sediments. Ayadi et al. (2016) documented the distribution of benthic foraminifera and the

339

sediment quality along the coastline of Skhira and Gabes (southern coast of Gabes Gulf). A

340

barren zone corresponding to the most polluted area and increasing values of diversity away

341

from this area were reported and some tolerant and sensitive species were identified.

342

Unfortunately, both these two papers due to the low number of living specimens consider the

343

total assemblages (living + dead) and represent the only ones, to our knowledge, in Tunisian

344

coastal environments.

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A total of 37 species were recognized in the living assemblages along the coastal fringe of

346

Monastir Bay. This diversity value is comparable to the one documented in the southern coast

347

of Gabes Gulf (34 taxa) (Ayadi et al., 2016), but lower than those found in the northern part

348

of the same Gulf (68 taxa) (Aloulou et al., 2012). In the Monastir Bay coastal fringe, the

349

living foraminiferal density varied from 44 to 2362 reaching a maximum value at BM0

350

station. Low foraminiferal density, diversity and specific richness were recognized (BM2,

351

BM5 and BM7 stations) which belong to cluster B of Q-mode CA that are also characterized

352

by the highest pollution level. A PCA ordination diagram confirms these results. In fact,

353

benthic foraminiferal diversity indices are negatively related to EFs, and specifically to EFs

354

of Zn, Cu, Pb and Ni. Foraminiferal density also seems to be positively related to the mud

355

fraction, TP and TN. Similar results showing a diversity and density decrease were also found

356

in some areas receiving high heavy metal concentration such as El Mex bay, Egypt (Samir

357

and El-Din, 2001), the southern coast of Gabes Gulf, Tunisia (Ayadi et al., 2016) and the port

358

of Cagliari, Sardinia (Schintu et al., 2016). According to Coccioni et al. (2009), decreasing

359

diversity indices and species richness are expected in areas particularly affected by pollution.

360

In addition, benthic foraminifera might positively benefit from the organic matter input that

361

represent a source of nutrients and this might be the case of the positive relation between FD

362

and the mud fraction, TP and TN. Accordingly, Murray (1973) and Debenay et al. (1996)

363

have reported that an increase in pollution might lead to the presence of high individual

364

numbers belonging to a few opportunistic species. Numerous studies have focused on the

365

relationship between grain size and benthic foraminifera (i.e., Debenay et al., 1996; Samir and

366

El-Din, 2001). A positive correlation between muddy sediment and foraminiferal density

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ACCEPTED MANUSCRIPT 367

(Fig.8a) was also observed in the present studied area. Armynot du Châtelet et al. (2009)

368

explained this positive relation by the reduced nutrients’ availability in coarse sediments that

369

are also in agreement with the results of Alve and Murray (1999), Samir and El-Din (2001)

370

and Aloulou et al. (2012). This study also displays the wide distribution of Q. seminula along the coastal fringe of

372

Monastir Bay. Quinqueloculina seminula has been reported as a dominant species in the

373

Mediterranean lagoons, continental shelves and marshes (Murray, 2006; Langlet et al., 2014).

374

Moreover, this species has been inferred to be tolerant of low levels of oxygen and periods of

375

anoxia (Bernhard and Gupta, 1999; Martins et al., 2011; Martins et al., 2013; Langlet et al.,

376

2014). This study documents high percentages of Q. seminula at stations of cluster A of the

377

Q-mode CA, with a positive relationship with metals enrichment (Fig. 8, b). Most of

378

porcelaneous taxa are reported to be stress-sensitive to pollution but not Q. seminula (Barras

379

et al., 2014). Following the PCA plot, Q. seminula seems to be negatively affected by EFs of

380

several heavy metals and the total hydrocarbon in the northern coast of Gabes Gulf (Aloulou

381

et al., 2012). Vertebralina striata is the dominant species in the Monastir Bay and positively

382

related to anthropogenic environmental stress, which correlates positively with the majority of

383

heavy metals EFs. The dominance of A. tepida in our study might be linked to its tolerance to

384

relatively low salinity conditions and to pollution. In fact, A. tepida has been shown to be

385

tolerant of chemical pollution, hydrocarbons, fertilizing products, low salinity, and a high

386

concentration of trace elements (Coccioni et al., 2009; Frontalini et al., 2013). This taxon is

387

commonly encountered in transitional environments under stress (Yanko et al., 1994, 1999;

388

Alve, 1995; Debenay et al., 2001; Armynot du Châtelet et al., 2004; Frontalini et al., 2014;

389

Martins et al., 2014) and is frequently considered as a species tolerant to stress. According to

390

that, A. tepida is the dominant species at BM1 station, where high concentrations of organic

391

matter, heavy metals, and low water salinity values were recorded. Furthermore, A. tepida

392

was also positively correlated with mud fraction, TP, TN and EF.Cr. Ammonia tepida was

393

considered as a bioindicator of pollution in sediments from the Naples harbor (Ferraro et al.,

394

2006), in Augusta Harbor (Romano et al., 2009), along the coastal area of the Adriatic Sea

395

(Frontalini and Coccioni, 2008) as well as in different Tunisian environments such as the

396

lagoon of Bizerte (Martins et al., 2015, 2016), Gulf of Gabes (Aloulou et al., 2012). Ammonia

397

tepida and Q. seminula are considered to be quite tolerant of environmental stress (Debenay

398

et al., 2000; Debenay and Guillou, 2002), and these two species have been regarded as the

399

primary pioneers in several transitional environments (Debenay et al., 2009). On the other

400

hand, Ammonia parkinsoniana appears to be the species most affected by heavy metals and

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ACCEPTED MANUSCRIPT organic matter, as revealed by the negative relation in the PCA plot (Fig. 8b). This taxon is

402

typical of coastal shallow environments and has been reported to prefer relatively clean

403

environments (Seiglie, 1975; Frontalini and Coccioni, 2008). Additionally, most of the

404

species and in particular E. crispum, E. complanatum, R. bradyi, A. ciliarensis, and A.

405

pulchella are negatively related to EFs indicating that they are, at least in this area, sensitive

406

taxa.

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407 408

Conclusion

The present work contributes to the evaluation of the environmental quality of the coastal

410

fringe of Monastir Bay by using an integrated approach based on geochemical analyses of

411

sediment and benthic foraminifera living therein. The geochemical data combined with

412

statistical results suggest an overall contamination of sediment mainly by Zn, Ni and Cu and

413

the identification of an area particularly impacted by metals. This zone corresponds to the area

414

in front of the Khniss drain that has been historically affected by the presence of multiple

415

sources of pollution. The site is also characterized by a poorly diversified benthic

416

foraminiferal assemblages that would reflect the poor environmental conditions. Some species

417

such as Ammonia tepida, Elphidium crispum, Elphidium complanatum, Rosalina bradyi,

418

Adelosina ciliarensis, and Adelosina pulchella are negatively related to EFs and can be

419

inferred as very sensitive taxa. On the other hand, Quinqueloculina seminula and Vertebralina

420

striata appear to be positively related to EF and might be considered as tolerant taxa to

421

pollution in the Monastir Bay. The present study further reinforces the application of benthic

422

foraminifera as proxies of pollution and as bioindicators of the environmental quality and

423

represents the first contribution on a coastal marine area based on living benthic foraminifera

424

as bioindicators.

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Acknowledgements

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The authors are very grateful to the Editor-in-Chief Dr. Damien Delvaux, Ph.D and two

428

anonymous reviewers for their thoughtful and valuable comments that have greatly improved

429

the paper. This work was conducted as part of the project financed by Critical Ecosystem

430

Partnership Fund (CEPF) under the direction of “Notre Grand Bleu” association. The authors

431

would like to thank Dr Manel Ben Ismail (Director of Notre Grand Bleu and Doctor in

432

Biological Sciences and Biotechnology) and Dr Leïla Chaari for their encouragement,

433

technical support and assistance in the field and laboratory.

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Yanko, V., Ahmad, M., Kaminski, M., 1999. Morphological deformities of benthic foraminiferal tests in

595

response to pollution by heavy metals: implications for pollution monitoring. Journal of Foraminiferal Research,

596

28. 177–200.

597

Yanko, V., Kronfeld, J., Flexer, A., 1994. Foraminifera as Environmental Condition Indicators in Todos os

598

Santos Bay (Bahia, Brazil). Journal of Foraminiferal Research. 24. 1-17.

599

Zaouali, J., Ben Charradar, 2010. Impact des actions anthropiques sur le phytobenthos de la baie de monastir.

600

Proceedings of the 4th mediterranean symposium on marine vegetation. UNEP, MAP, RAC/SPA. 135-140.

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ACCEPTED MANUSCRIPT Figures and Table captions

603

Figure 1. Geographical map of the study areas and sampling stations (BM).

604

Figure 2. Trace metal enrichment factors distribution in coastal fringe of the Bay of Monastir.

605

Figure 3. Contamination factor distribution in the coastal fringe of the Bay of Monastir.

606

Figure 4. PLI values in the coastal fringe of the Bay of Monastir.

607

Figure 5. Relative abundance (%) of benthic foraminiferal taxa in coastal fringe of the Bay of Monastir.

608

Figure 6. Distribution of foraminiferal parameters in the study area (a: foraminiferal density, b: Species richness,

609

c: Dominance, d: Shannon-Weaver, e: Evenness, f: Fisher α, j: Equitability).

610

Figure 7. Sampling stations plotted on Q-mode CA.

611

Figure 8. R-mode PCA ordination diagram of samples based on the environmental components and benthic

612

foraminiferal assemblages’ parameters (a) and species (b).

613

Figure 9. Q-mode PCA ordination of stations with cluster as defined by Q-mode CA.

614

Table 1.Enrichment factors for metals and terminologies (Sutherland et al.,2000).

615

Table 2. Contamination factors (Likuku et al., 2013).

616

Table 3. Pollution Load Index description (Tomlinson et al., 1980).

617

Table 4: Sediment and water parameters.

SC

M AN U

AC C

EP

TE D

618

RI PT

602

20

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619 620

Fig. 1: Geographical map of the study areas and sampling stations (BM).

AC C

EP

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M AN U

621

21

Fig. 2: Trace metal enrichment factors distribution in coastal fringe of the bay of Monastir.

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622 623

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AC C

EP

TE D

M AN U

624

22

625 626

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Fig. 3 : Contamination factor distribution in the coastal fringe of the bay of Monastir.

AC C

EP

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M AN U

627

23

628 629

Fig. 4: PLI values in the coastal fringe of the bay of Monastir.

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630

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631 632

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Fig. 5: Relative abundance (%) of benthic foraminiferal taxa in coastal fringe of the bay of Monastir.

AC C

EP

TE D

M AN U

633

25

RI PT

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M AN U

SC

634

AC C

EP

636

TE D

635

637 638

Fig. 6: Distribution of foraminiferal parameters in the study area (a: foraminiferal density, b: Species richness, c:

639

Dominance, d: Shannon-Weaver, e: Evenness, f: Fisher α, j: Equitability).

26

Fig. 7: Sampling stations plotted on Q-mode CA.

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640 641

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M AN U

642

27

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Fig. 8: PCA ordination diagram of samples based on the environmental components and benthic foraminiferal

645

assemblages’ parameters (a) and species (b).

AC C

EP

TE D

646

M AN U

643 644

28

Fig. 9: Dendrogram classification of stations produced by Q-mode.

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647 648

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AC C

EP

TE D

M AN U

649

29

ACCEPTED MANUSCRIPT EF Terminologies

EF < 2

Minimal enrichment

2 ≤ EF <5

Moderate enrichment

5 ≤ EF <20

Significant enrichment

20 ≤ EF <40

Very high enrichment

EF ≥ 40

Extremely high enrichment

Table 1: Enrichment factors for metals and terminologies (Sutherland et al., 2000).

RI PT

650

EF Classes

AC C

EP

TE D

M AN U

SC

651

30

ACCEPTED MANUSCRIPT CF Classes

652

CF Terminologies

CF < 1

Low contamination

1 ≤ CF <3

Moderate contamination

3 ≤ CF <6

Considerable contamination

CF ≥ 6

Very high contamination

Table 2: Contamination factors (Likuku et al., 2013).

AC C

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TE D

M AN U

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RI PT

653

31

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654

PLI

Description

<1

No pollution

1

Baseline levels of pollution

>1

Deterioration of site quality

Table 3: Pollution Load Index description (Tomlinson et al., 1980).

AC C

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TE D

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655

32

BM0

BM1

BM2

BM3

BM4

BM5

BM6

BM7

BM8

BM9

pH

7.37

7.56

7.68

7.74

6.72

7.37

7.53

7.47

8.21

8.04

Conductivity (ms/cm)

56.9

36.8

59.7

59.1

57

58

57.8

59.6

57.1

60.7

Salinity (mg/l)

44.06

27.03

44.81

46

44.37

45.14

44.96

46.45

44.13

48.01

Very coarse sand

1

2.78

12.00

0.24

0.42

0.43

1.11

0.44

0.31

1.00

Coarse sand

0.9

15.27

7.93

3.06

6.37

11.18

2.52

10.21

2.77

1.61

2.3

20.06

20.11

27.67

50.51

41.32

39.92

39.48

22.15

3.85

75.80

28.64

38.29

50.63

32.03

33.44

46.17

31.65

55.05

57.66

Very fine sand

19.4

30.23

19.91

17.79

10.22

12.72

9.84

16.60

18.63

35.81

Silt and clay

0.2

2.83

1.55

0.51

TN (%)

0.36

1.67

1.43

1.40

TOC (%)

0.5

3.75

2.5

2.75

TP (mg/g)

0.15

0.34

0.04

0.02

Cr (ppm)

0.54

13.96

12.00

0.00

Ni (ppm)

1.93

4.95

4.13

Fe (ppm)

2347.28

4147.76

3566.32

Cu (ppm)

2.11

8.23

7.08

Pb (ppm)

3.41

7.86

6.76

Zn (ppm)

13.12

46.16

39.69

PLI

0.36

1.67

1.43

Table 4: Sediment and water parameters.

M AN U

0.88

0.31

1.48

0.66

0.18

0.33

0.59

0.60

0.78

0.63

0.59

2.67

5.25

2.25

4.75

1.75

1.75

0.07

0.13

0.09

0.16

0.07

0.07

1.08

0.00

0.00

1.58

0.00

1.98

4.12

2.52

1.33

1.14

2.61

1.49

3.33

3948.37

760.44

385.55

845.05

2421.91

1036.03

1875.59

7.06

1.45

2.10

1.75

9.71

1.80

3.28

3.30

1.80

1.96

2.20

6.35

2.51

5.21

25.10

8.32

6.08

8.00

18.07

6.47

9.96

1.40

0.33

0.59

0.60

0.78

0.63

0.59

TE D

0.37

EP

Fine sand

%

AC C

Medium sand

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Stations

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ACCEPTED MANUSCRIPT Highlights:

2

Monastir Bay is one of the most important resources of marine species in Tunisia.

3

Trace metals pollution has detrimental effects on benthic foraminifera assemblages.

4

Geochemical and foraminiferal analyses reveal deteriorated conditions.

5

Foraminiferal taxa have the potential to be used as trace metals bioindicators.

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1