Structuring factors of the spatio-temporal variability of macrozoobenthos assemblages in a southern Mediterranean lagoon: How useful for bioindication is a multi-biotic indices approach?

MPB-08098; No of Pages 13 Marine Pollution Bulletin xxx (2016) xxx–xxx

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Structuring factors of the spatio-temporal variability of macrozoobenthos assemblages in a southern Mediterranean lagoon: How useful for bioindication is a multi-biotic indices approach? Ines Khedhri a, Ahmed Afli a, Lotfi Aleya b,⁎ a b

Laboratoire de Biodiversité et Biotechnologies Marines, Institut National des Sciences et Technologies de la Mer, 28 rue du 2 mars 1934, 2025 Salammbô, Tunisie Université de Bourgogne Franche-Comté, Laboratoire de Chrono-Environnement, UMR CNRS 6249, Besançon, France

a r t i c l e

i n f o

Article history: Received 16 September 2016 Received in revised form 1 October 2016 Accepted 7 October 2016 Available online xxxx Keywords: Boughrara lagoon Benthic macrofauna Spatio-temporal variability Trophic structure Biotic indices Ecological status

a b s t r a c t The authors investigated the impact of the extension of the El Kantra Channel on the composition and structure of macrobenthic assemblages in Boughrara Lagoon (Gulf of Gabes, Tunisia along with the use of 4 biotic indices (AMBI, BENTIX, M-AMBI and TUBI). Thirteen stations were sampled seasonally in 2012–2013. Forty-one species were found in 2012–2013 not recorded in 2009–2010, including 20 species of polychaetes belonging to the trophic groups of deposit-feeders and carnivores which are expected to increase in areas disturbed by organic pollution. During the survey, we recorded a high fish mortality, essentially caused by the development of harmful algal blooms (HAB) which increased organic matter deposition, thus inducing polychaete development. This seems to weaken the bio-indicating power of biotic indices used here which, paradoxically, classified all sampled stations at a high ecological status. A review of these indices and their applicability to all marine environments is recommended. © 2016 Elsevier Ltd. All rights reserved.

1. Introduction Over the last few years theoretical ecologists (Aleya, 1991; Hubbell, 2001; Bell, 2005) have been intrigued by the relative roles played by habitat-specific selectivity and by random dispersal in building communities. Simultaneously, interest continues to grow, with increasingly contrasting results (Çinar et al., 2015; Van der Linden et al., 2016a, 2016b), in establishing biotic indices and indices based on species traits to provide early warning of potentially undesirable ecological shifts in anthropogenically stressed marine ecosystems. Indeed, the use of biotic indices, to assess ecological quality status (EcoQ) of marine waters, has become one of the important topics in the literature. According to Quintino et al. (2006); Zettler et al. (2007); Blanchet et al. (2008) and Lavesque et al. (2009), most of these biotic indices perform badly in semi-enclosed ecosystems, especially those composed of mud, enriched by organic matter and in which the instability of environmental parameters can affect the ecological monitoring of systems (Dauvin, 2007). More particularly, Blanchet et al. (2008) confirmed the limitations of these biotic indices and the poor decisions which they can induce. Muxika et al. (2005) showed that the Azti Marine Biotic Index (AMBI) was not a good indicator of physical disturbance within sediment deposits (Lavesque et al., 2009). ⁎ Corresponding author. E-mail address: lotfi[email protected] (L. Aleya).

However, in a recent study by Van der Linden et al. (2016a) the performance of AMBI and Multivariate Azti Marine Biotic Index (M-AMBI) was tested on the Basque coast and Bay of Biscay (France and Spain), with positive results. The findings at these sites, both affected by natural and anthropogenic disturbances (consumption of oxygen, organic-matter enrichment and discharge of urban and industrial wastewaters) showed that the 2 biotic indices were indeed able to assess the ecological status and the effects of anthropogenic disturbances of surficial sediments, whereas neither the Community-Weighted Mean trait values (CWM) nor Rao (trait diversity) indicated anthropogenic seafloor disturbances. In addition, CWM of multiple traits does not provide a single number indicating a quality status, which makes it a difficult tool to use and interpret, especially for managers. According to Van der Linden et al. (2016a), AMBI and M-AMBI are easier and more straightforward to use, which is why several European Community member states have used them in the first phase of Groundwater and Environmental Services (GES) assessment (European Commission, 2008). This intense discussion over the use and development of biotic indices thus created a good opportunity to study them closely. Boughrara Lagoon, a fragile and vulnerable Mediterranean ecosystem located off the Gulf of Gabes and affected by natural and anthropogenic constraints imposed by local demographics and industrial development (Khedhri et al., 2016), appeared as a likely study site. The lagoon is also subject to the strongest tides in the Mediterranean Sea (2 m) (Hattour et al., 2010) and experiences semi-diurnal tidal crests (Sammari et al.,

http://dx.doi.org/10.1016/j.marpolbul.2016.10.023 0025-326X/© 2016 Elsevier Ltd. All rights reserved.

Please cite this article as: Khedhri, I., et al., Structuring factors of the spatio-temporal variability of macrozoobenthos assemblages in a southern Mediterranean lagoon: How usef..., Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.10.023

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I. Khedhri et al. / Marine Pollution Bulletin xxx (2016) xxx–xxx

2006). It harmoniously fills and empties through two direct outlets to the open sea (Hattour et al., 2010; Brahim et al., 2014): the Ajim Jorf Channel (to the north-west) and the El Kantra Channel (to the east), the latter located at a point halfway along the Roman road that connects south-eastern Djerba Island to the mainland (Fig. 1). Compared to the Gulf of Gabes, the lagoon's tidal crests are much delayed due to the bathymetric resolution of the Ajim Channel, and their range is much greater (Hattour et al., 2010); the maximum tidal range in the El Kantra Channel is 56 cm (Brahim et al., 2014). The El Kantra Channel, originally a narrow passage 12.5 m across, was widened to 160 m between 2004 and 2007, thus increasing water exchange with the sea to about 6.9 million m3 per day, instead of 0.8 million m3 previously (Fig. 1) (DGPA, 2001). We therefore hypothesised that these hydrodynamic properties might influence the biological

communities living there. For example, we have shown that dinoflagellates can take advantage of the filling and emptying of the lagoon through its two outlets to spread along the shores of the Gulf of Gabes (Abdenadher et al., 2012; Feki et al., 2013). However, a knowledge gap persists as to the macroinvertebrate community known to play a crucial role in matter decomposition and nutrient recycling (Masero et al., 1999; Heilskov and Holmer, 2001; Mermillod-Blondin et al., 2005; Carvalho et al., 2007). In addition, within the European Water Framework Directive (WFD), invertebrates are used for assessment of the ecological quality status (EcoQ) of surface and transitional (lagoons) water bodies (Blanchet et al., 2008; Lavesque et al., 2009) due to their: (1) position at the sediment-water interface, which makes them powerful indicators of marine ecosystem health,

12.5 m 2.2 km 3

-1

0.8 mm d

160 m -1

6.9 mm3d

Fig. 1. Study area with location of sampling sites and the widening of the El Kantra Channel (before the widening: 12.5 m length; 0.8 mm3 d−1 of water exchange and after the widening: 160 m length; 6.9 mm3 d−1 of water exchange) (Google earth, 2016).

Please cite this article as: Khedhri, I., et al., Structuring factors of the spatio-temporal variability of macrozoobenthos assemblages in a southern Mediterranean lagoon: How usef..., Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.10.023

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(2) relatively long and sedentary life (Pearson and Rosenberg, 1978; Dauer et al., 2000) (indeed they are unable to escape disadvantageous conditions, thus making them useful in the evaluation of accidental and chronic variations) (Dauvin, 1993; Reiss and Kroncke, 2005) which allows relatively low-frequency surveys, and. (3) different levels of tolerance to stresses, various feeding guilds and a diversity of life-history traits (Glémarec and Grall, 2000).

It thus becomes essential to answer the following questions: (1) How susceptible are the macroinvertebrate communities to the onset of externally driven forces (here the widening of the El Kantra Channel which improved the exchange between the lagoon and the open sea)? (2) How will the functional organization of these assemblages be affected in habitats subject to repeated harmful algal blooms (HAB) caused by proliferation of the toxic dinoflagellates Alexandrium minutum and Karenia selliformis (Abdenadher et al., 2012; Feki et al., 2013) and which have led to the total disappearance of a significant number of fish species such as Thunnus thynnus (Linnaeus, 1758), Sparus aurata (Linnaeus), 1758), Sarpa salpa (Linnaeus, 1758), Mullus surmuletus (Linnaeus, 1758) and Octopus vulgaris (Cuvier, 1797) and have replaced them by other bio-indicator species of deteriorated areas (DGPA, 2001)? (3) Do the results match other recent findings (e.g., Van der Linden et al., 2016a) on ecological quality status of ecosystems as assessed by means of biotic indices?

2. Material and methods

3

Table 1 Characteristics of sampling stations. Stations

Number

Latitude (N)

Longitude (E)

Depth (m)

% Mud (N63 μm)

Aghir rejection El Kantra Gulf of Gabes Abattoir Desalination Ajim Harbour Fish farming Boughrara Harbour SAT Rsiffette Hassi Jalleba Karboub Wadi

1 2 3 4 5 6 7 8 9 10 11 12 13

10°55′52″ 10°55′32″ 10°44′16″ 10°50′00″ 10°50′35″ 10°44′37″ 10°45′42″ 10°41′29″ 10°14′21″ 10°54′52″ 10°56′23″ 10°52′44″ 10°42′21″

33°41′30″ 33°39′33″ 33°43′17″ 33°44′00″ 33°34′27″ 33°42′59″ 33°41′55″ 33°32′21″ 33°39′45″ 33°31′30″ 33°34′55″ 33°30′59″ 33°32′16″

0.5 2.3 1.1 0.5 0.5 1.0 1.0 3.1 0.2 0.3 0.5 0.3 10.5

0.77 4.08 0.65 1.85 0.44 1.42 2.36 0.51 0.50 3.80 7.93 37.94 11.76

(ammonium, nitrite, nitrate and phosphate) were analysed with a BRAN and LUEBBE type 3 auto-analyser; concentrations were determined colourimetrically using a UV–visible (JENWAY 6705) spectrophotometer (APHA, 1992). Chlorophyll a was determined using the spectrophotometric method of Lorenzen (1967) and following the procedure of Parsons et al. (1984) after 24 h, with extractions in 90% acetone carried out in the dark at −5 °C. Sediment samples for benthic macrofauna study were collected at the 13 sampling stations during the different seasons of 2012–2013 by scuba divers working within a defined quadrat (10 cm depth). The samples were sieved through a 1 mm mesh and preserved in a 7% formaldehyde/seawater solution. Three replicates were created at each station making a total sampling surface of 0.75 m2. In the laboratory, the macrofauna samples were washed with freshwater through 1 mm mesh and the collected animals were preserved in diluted alcohol (70%) before identification, up to species level for the most part.

2.1. Study site 2.3. Data analysis Boughrara Lagoon (500 km2) is located on the south-eastern coast of Tunisia in the governorate of Medenine (between 33°28′N and 33° 45′N and 10°40′E and 10°57′E) and is delimited by Djerba Island on the north and by the mainland elsewhere (Fig. 1). The lagoon's average depth is approximately 4 m, reaching a maximum of 16 m in the centre. Air temperature appears to play an important role in Boughrara Lagoon as it has a strong and instant influence on water temperature (Feki et al., 2013). The climate is dry (average annual precipitation of around 210 mm/ year) and sunny with strong easterly winds which transport particles into the sea (Brahim et al., 2014, 2015) and cause severe aeolian erosion. The most dominant winds are from the north-west (Brahim et al., 2014). An extremely hot and dry south or south-westerly wind may often occur in summer that, when sufficiently strong, raises clouds of fine dust (Brahim et al., 2014). Boughrara Lagoon is the outlet for three main streams draining an estimated total of 2394 km2 (Brahim et al., 2014) in the El Fje, Essamar and Bou Hamed watersheds, as shown in Fig. 1. Annual solid input into the lagoon is about 11 mm3 year−1, essentially from these main streams (Brahim et al., 2014). 2.2. Sampling and laboratory procedures Marine surveys were carried out seasonally (in February 2012, April 2012, August 2012, January 2013 and November 2013); 13 stations facing main disturbance sources (fishing ports, aquaculture farms, sewage outfalls, and industrial wastes) were sampled (Table 1). Water temperature was measured in situ by an electronic probe type WTW 197i, salinity by a salinometer type WTW Multi-340i, pH by a pH-meter type WTW 340 and dissolved oxygen by an oximeter type WTW. Water samples were collected in 1000-ml polypropylene bottles at the surface and preserved in an icebox at −4 °C. In the laboratory, nutrients

The main structural parameters of the benthic macrofauna determined at each station are specific richness S (number of species), abundance A (number of individuals/m2), the Shannon-Wiener index H′ (Shannon and Weaver, 1963) and Pielou's evenness J’ (Pielou, 1966). They were defined using the PRIMER v6 package. Identified species were classified into trophic groups according to Fauchald and Jumars (1979) and notably modified by Grall and Glémarec (1997), Hily and Bouteille (1999), Afli and Glémarec (2000), Pranovi et al. (2000) and Afli et al. (2008a): - Carnivores (C), predatory animals (i.e. mobile polychaetes, seaanemones), - Detritus feeders (DF), feeding on particulate organic matter, essentially vegetable detritus (mainly amphipods and tanaids), - Suspension-feeders (SF), feeding on suspended food in the water column (e.g. most bivalves), - Herbivores (H), feeding on benthic microalgae, phanerogams, bacteria and detritus (essentially polyplacophores and gastropods) and - Selective deposit feeders (SDF), feeding on organic particles settled on the sediment, e.g. most sedentary polychaetes and some bivalves and crustaceans.

Three currently available univariate biotic indices were used, namely AMBI (Azti Marine Biotic Index) (Borja et al., 2000), BENTIX (Simboura and Zenetos, 2002) and M-AMBI (Multivariate-AMBI). The first two were used to qualify the ecological status within a five-class scale of pollution, on the basis of the relative proportions of the 5 ecological groups established initially by Glémarec and Hily (1981): I: sensitive species; II: indifferent species, III: tolerant species, IV: second-order opportunistic

Please cite this article as: Khedhri, I., et al., Structuring factors of the spatio-temporal variability of macrozoobenthos assemblages in a southern Mediterranean lagoon: How usef..., Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.10.023

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species and V: first order opportunistic species. M-AMBI was calculated using AMBI, specific richness and the Shannon–Wiener index, combined with the use, in a further development, of factor and discriminant analyses, (Borja et al., 2004; Bald et al., 2005; Muxika et al., 2007). This method compares monitoring results with reference conditions (Borja and Tunberg, 2011), and was computed using AMBI software (http:// www.azti.es). At ‘high’ status, the reference condition may be regarded as an optimum where M-AMBI approaches 1. Under ‘bad’ status, the MAMBI value approaches zero. A new biotic index, TUBI (Turkish Benthic Index) (Çinar et al., 2015) was also calculated to assess the impact of organic enrichment on the benthic community structure. This new index has two metrics; the Shannon-Wiener's diversity index (metric 1) and the relative abundance of ecological groups (metric 2). TUBI scores vary from 0 to 5, and benthic quality status increases as TUBI scores rise. Statistically significant differences in the numerical values of abiotic − + 3− variables (temperature, salinity, pH, NO− 2 , NO3 , NH4 and PO4 ) and biotic indices (S, A, J′, H′, chlorophyll a, AMBI, BENTIX, M-AMBI and TUBI) were tested through analyses of variance (ANOVA) using STATISTICA 8 software. The normality of data was assumed; the ANOVA test was used when homogeneity of variance (Bartlett's test) was achieved. If significant heterogeneity was identified, data were log10(x + 1) transformed.

Hierarchical Clustering (HC), using the XLSTAT 2014 software based on the Bray-Curtis similarity measure, was applied to the main abiotic (Temperature, salinity, dissolved oxygen, pH, depth and nutrient salts) and biotic parameters (R, A, H′, J′, chlorophyll a, AMBI, M-AMBI, TUBI and BENTIX) in order to use them to examine station distribution. Similar stations were assembled in the trophic groups and characterised according to their principal variables by means of Principal Component Analysis (PCA). The software XLSTAT 2014 was used on data organised in a rectangular matrix, with the stations in the columns and the trophic groups on the lines. 3. Results 3.1. Physicochemical parameters The average values of abiotic variables in surface water in the seasonal samples taken at the 13 stations are given in Table 2. Temperature values varied from 35.8 °C at station 13 in summer to 14 °C at station 3 in winter 2013. Average salinity concentrations ranged from 29.6 at station 5 in autumn to 50 at station 12 in winter 2013. For dissolved oxygen, the minimal average concentration (1 mg l− 1) was recorded at

Table 2 − + 3 Spatio-temporal variations of main physicochemical factors (T: temperature; S: salinity; O2: dissolved oxygen; pH; NO− 2 : nitrite; NO3 : nitrate; NH4 : ammonium; PO4: phosphate) and chlorophyll a: Chl a over 5 seasons (W12: winter 2012; Sp: spring; S: summer; A: autumn; W13: winter 2013). Asteriks indicate absence of data. Stations

T (°C)

S

O2 (mg l−1)

pH

Chl a (μg l−1)

−1 NO− ) 2 (μg l

−1 NO− ) 3 (μg l

−1 NH+ ) 4 (μg l

PO3− (μg l−1) 4

W 12 Sp S A W 13 W 12 Sp S A W 13 W 12 Sp S A W 13 W 12 Sp S A W 13 W 12 Sp S A W 13 W 12 Sp S A W 13 W 12 Sp S A W 13 W 12 Sp S A W 13 W 12 Sp S A W 13

1

2

3

4

5

6

7

8

9

10

11

12

13

20.02 32.2 27.5 15.6 17.5 * * * 36.5 45.3 11.93 7.14 0.97 10.14 9.03 7.91 8.72 7.75 7.45 8.18 * * 4.05 * 1.05 * 0.08 0.28 0.42 0.21 * 3.21 3.56 3.27 1.26 * 7.65 3.06 1.80 3.53 * 0.32 0.13 0.90 0.20

17.2 25.3 28.4 17.4 20.3 * * * 35.3 47.3 10.35 6.54 7.55 9.7 8.58 7.83 8.02 8.14 8.07 7.6 * * 4.17 * 2.14 * 0.03 0.22 0.40 0.05 * 2.70 2.05 3.23 1.43 * 3.82 2.31 5.82 7.81 * 0.25 0.17 0.14 0.42

14.6 28.7 33.3 17.8 14 * * * 39.7 41.1 9.61 9.99 6.7 10.25 9.02 7.73 8.15 8.08 8.16 8.02 * * 3.07 * 2.31 * 0.12 0.16 0.45 0.18 * 1.39 2.41 1.91 2.26 * 3.79 3.44 2.82 6.01 * 0.30 0.24 1.51 0.40

21.3 34.4 28.6 18.9 18 * * * 33.0 47.0 14.67 14.72 4.2 8.39 9.78 8.06 9.202 7.99 7.03 8.07 * * 3.98 * 5.28 0.31 0.99 0.52 0.22 0.27 4.88 6.30 2.16 3.15 4.07 5.01 13.81 4.25 4.58 3.93 0.30 1.45 0.24 0.55 1.35

27.3 32.6 26 19.6 15 * * * 29.6 32.3 7.95 7.23 6.96 6.72 11.01 7.52 7.99 8.08 7.54 7.89 * * 4.72 * 3.15 0.24 * 0.70 23.54 0.46 2.51 * 1.15 67.59 3.34 0.27 * 3.34 3.36 1.73 0.27 * 0.24 1.04 0.16

16.3 29.8 33 18 15.3 * * * 37.7 42.9 12.55 14.31 8.81 12.57 10.34 8.69 8.37 8 8.22 8 * * 3.54 * 2.25 * 0.26 0.60 0.42 0.16 * 2.48 3.11 4.29 1.96 * 1.94 3.33 1.35 7.66 * 0.14 0.27 0.17 0.40

15.6 28.4 34.1 18 14.3 * * * 37.6 37.6 10.28 8.61 5.7 11.9 9.08 7.77 8.17 8.13 8.19 8.08 * * 3.98 * 2.39 * 0.29 0.21 0.42 0.07 * 3.12 3.62 3.72 1.33 * 2.35 3.53 2.76 6.09 * 0.14 0.16 0.68 0.26

16.1 27 26.9 18.4 15.2 * * * 47.0 45.2 10.22 8.08 8.18 9.63 9.63 7.84 8.16 8.1 8.29 8.26 * * 4.44 * 4.18 0.42 * 0.11 0.61 0.36 5.91 * 4.53 3.22 5.28 3.89 * 2.52 2.38 6.87 0.17 * 0.20 1.12 0.50

14.94 29.5 25.1 18 17.9 * * * 36.8 45.4 14.94 9.62 5.9 8.95 11.31 8.09 8.15 7.66 8.14 8.26 * * 4.31 * 2.46 * * 0.35 0.28 0.24 * * 3.52 2.86 4.21 * * 3.17 5.01 0.78 * * 0.21 0.12 0.29

21.5 31.9 35.5 19.2 19.7 * * * 38.8 42.8 10.74 9.58 7.26 9.84 10.53 7.84 8.43 8.3 8.21 7.99 * * 3.83 * 2.18 0.41 0.32 0.16 0.31 0.21 4.58 1.49 3.59 2.44 2.92 4.64 1.36 2.28 1.30 2.07 0.23 0.12 0.14 0.13 0.21

16.5 28.9 31.9 19.5 19.4 * * * 39.5 48.6 10.66 10.77 13.78 9.39 9.47 7.58 8.42 8.19 8.11 7.89 * * 4.49 * 3.71 0.50 0.12 0.12 0.15 0.24 4.86 1.23 2.32 2.07 1.19 4.69 2.61 4.22 1.25 0.53 0.77 0.28 0.19 0.40 0.17

20.5 31.1 32.3 18.8 18.6 * * * 36.7 50.0 11.31 8.94 7.27 10.01 10.96 7.83 8.32 8.27 7.98 7.99 * * 3.89 * 2.48 0.51 * 0.07 0.38 0.13 6.26 2.47 1.89 2.69 1.86 4.98 2.54 4.27 2.74 3.08 0.39 0.15 0.22 0.75 1.10

15.7 27.2 35.8 19.2 14.7 * * * 39.1 43.6 10.65 7.95 6.27 9.12 9.65 7.86 8.2 8.19 8.24 8.15 * * 4.62 * 3.08 0.73 0.14 0.24 0.58 0.07 3.73 3.13 1.99 4.89 0.83 4.35 3.97 3.34 3.67 2.87 0.74 0.11 0.10 0.84 0.30

Please cite this article as: Khedhri, I., et al., Structuring factors of the spatio-temporal variability of macrozoobenthos assemblages in a southern Mediterranean lagoon: How usef..., Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.10.023

I. Khedhri et al. / Marine Pollution Bulletin xxx (2016) xxx–xxx

station 1; for all other stations, however, values ranged from 4.2 mg l−1 (station 4) in summer 2012 to 14.94 mg l−1at station 9 in winter 2012. Low (7.03) and maximal (9.2) pH values were recorded at the same station (station 4) in both autumn and spring. Sampling season effects were significant for salinity, dissolved oxygen and pH, though sampling station effects for these abiotic variables were not. However, season and station effects, when considered separately, were significant only for temperature (Table 3). The nutrient concentrations in 2012–2013 did not differ significantly among seasons and stations (Table 2). It is noteworthy that the stations − + with the lowest average nutrient concentrations (NO− 2 , NO3 , NH4 and PO3− ) were in the lagoon's southern part. In contrast, the highest aver4 age concentrations were recorded in the northern part (Table 2). Average nitrite concentrations varied from 0.045 (μg l− 1) at station 2 in winter 2013 to 23 μg l−1 at station 5 in autumn. Generally the nitrite concentration contents did not exceed 1 μg l−1 except at station 5 in autumn. Average nitrate concentrations ranged from 0.826 μg l−1 (station 13 in winter 2013) to 67.59 μg l−. Average ammonium concentrations ranged from 0.26 to 13.8 μg l−1 at station 4 in spring. Phosphate concentrations did not reach 2 μg l−1 at the sampled stations in any season. Chlorophyll a concentrations varied in winter 2013 from 1.05 (station 1) to 4.72 μg l−1 in summer (station 5).

3.2. Benthos macrofauna The taxonomic structure of the collected invertebrates produced a list of 65 taxa belonging to 5 zoological groups. Molluscs are dominant (67% of the total number of taxa), followed by crustaceans (24.63%), annelid polychaetes (4.55%), cnidarians and echinoderms. All species recorded are among the typical fauna of Mediterranean lagoons. The taxa Cerithium vulgatum, Sphaeroma serratum, Perinereis cultrifera, Abra alba, Cerastoderma glaucum, Ruditapes decussates, Phylo foetida adjimensis and Bittium reticulatum were found at all stations in all seasons (Table 4). The faunistic parameters show a wide range of variability of taxa: - Abundance: from 2534 (station 5 in winter 2012) to 1 (station 1 in autumn) ind m−2, - Specific richness: 1 (station 9 in spring and station 1 in autumn) to 17 (station 8 in spring), - Evenness: 0 (station 13 in summer and autumn) to 1 (stations 1 and 6 in autumn), and

5

- Shannon index (H′): 0 (stations 9 and 13 in spring and summer) to 3.14 (station 8 in spring) bits ind−1 (Fig. 2).

The samples showed a statistically significant difference between seasons and stations for the specific richness and H′. For abundance, the difference is significant only between seasons and for evenness (J’) among all stations (Table 3). Trophic structure analysis shows that the majority of stations are strongly represented by selective deposit feeders SDF (46%), followed by herbivores H (25.78%), suspension feeders SF (20.33%), carnivores (6.65%) and detritus feeders DF (6.65%) (Fig. 3). In terms of abundance, selective deposit feeders species were abundant in winter 2012 (299 ind m−2), while during the other seasons their abundance did not exceed 50 ind m−2 (summer 2012). Their dominance was mainly at the lagoon's southern (stations 10, 11 and 12) and northern stations (4, 5 and 6) where it exceeded an average of 90%. The herbivore group dominated with 43% in winter 2013, but was more abundant in winter 2012. The spatial distribution of herbivorous species shows that they were essentially concentrated in places sheltered from sea currents (stations 5, 9, 10 and 12). Suspension feeders SF occupied the first position only in spring 2012 with 42% (40 ind m−2) and the second position in summer 2012. Carnivores were more present in autumn 2013 when they were ranked second after the selective deposit feeders with 32% (23 ind m−2). During the other seasons, they were less represented, 3% in winter 2012 and 14% in the spring. The strong abundance of carnivores were recorded near the main passages (stations 1, 3, 4, 6 and 7). Detritus feeders were found sporadically, with no clear pattern (Fig. 3). The AMBI, BENTIX and M-AMBI indices are consistent with the results classifying all stations as having a high and good ecological status, however, the TUBI index appears to show more severe conditions, classifying all stations in moderate to good ecological status (Fig. 4). In fact, the majority of stations were strongly dominated by sensitive species (I). ANOVA indicates a significant difference for these biotic indices through all the seasons (Table 3). 3.3. Multivariate analysis The Hierarchical Clustering (HC) applied to the main abiotic parameters (temperature, salinity, dissolved oxygen, pH, depth and nutrients), the biotic parameters (R, A, H′, J′, chlorophyll a, AMBI, M-AMBI, TUBI and BENTIX) which were based on the Bray-Curtis

Table 3 − + 3− ANOVA, mean squares (MS) and their significance levels (P) for main abiotic (temperature; salinity; O2: dissolved oxygen; pH; NO− 2 : nitrites; NO3 : nitrates; NH4 : ammonium; PO4 : phosphates) and biotic factors (Chla a: chlorophyll a; S: specific richness; A: abundance; H′: Shannon-Wiener index; J′:evenness; AMBI: azti marine biotic index; BENTIX; M-AMBI: multivariate-ambi; TUBI: Turkish benthic index). NO− 3

PO3− 4

df

MS

P

MS

P

MS

P

MS

P

MS

P

Stations Seasons

12 3

10,92 8904

0,353 0,473

77,52 71,71

0,447 0,45

5597 3887

0,315 0,54

0,135 0,352

0,428 0,023

0,845 10,36

0,758 b0,001

Main effects

df

Temperature MS P 10,06 0,998 601,7 b0,001

Salinity MS 25,62 257,4

P 0,643 b0,001

pH MS 0,06 0,363

P 0,864 0,003

O2 MS 6164 32,38

P 0,435 b0,001

S MS 34,98 47,13

P 0,011 0,027

A MS 122 654

P 0,646 b0.001

J′ MS 719 265

P 0,001 0,509

H′ MS 1,81 1,99

P 0,003 0,040

AMBI MS 0,763 2784

P 0,257 b0.001

BENTIX MS 2075 21,12

P 0,731 b0.001

M-AMBI MS 0,045 0,039

P 0,052 0,032

Stations Seasons

12 4

Main effects

df

Stations Seasons

12 4

Main effects

df

Stations Seasons

12 4

NO2

NH+ 4

Main effects

Chl a

TUBI MS 0,418 1046

P 0,267 0,013

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I. Khedhri et al. / Marine Pollution Bulletin xxx (2016) xxx–xxx

Table 4 List of principal species collected in the lagoon of Boughrara during the 5 seasons of 2012–2013.

Phylum

Species

1

2

1–30 ind.m−2,

Absent,

3

4

5

6

30–200 ind.m−2,

Stations 7

8

9

≥200 ind.m−2.

10

11

12

13

Abra alba (W. Wood, 1802) Bittium depauperatum Watson, 1897

Mollusca

Annelida

Arthropoda

Bittium latreilli (Payraudeau, 1826) Bittium reticulatum (da Costa, 1778) Calliostoma zizyphinum (Linnaeus, 1758) Callochiton septemvalvis (Montagu, 1803) Cerastoderma edule (Linnaeus, 1758) Cerastoderma glaucum (Bruguière, 1789) Cerithium scarbidium (Philippi, 1848) Cerithium vulgatum (Bruguière, 1792) Chiton (Rhyssoplax) olivaceus Spengler, 1797 Conus ventricosus (Gmelin ,1791 ) Gastrana fragilis (Linnaeus, 1758) Hexaplex trunculus (Linnaeus, 1758) Loripes lucinalis (Lamarck, 1818) Mytilaster minimus (Poli, 1795) Mytilus galloprovincialis Lamarck, 1819 Nassarius Duméril, 1805 Nassarius pygmaeus (Lamarck, 1822) Neverita delessertiana (Récluz, 1843) Neverita josephinia (Risso, 1826) Nucula nucleus (Linnaeus, 1758) Pinctada imbricata radiata (Leach, 1814) Polititapes aureus (Gmelin, 1791) Ruditapes decussatus (Linnaeus, 1758) Tellina planata Linnaeus, 1758 Arenicola cristata Stimpson, 1856 Branchiomma sp. Capitella sp. Capitallidae unidentified Dasybranchus caducus (Grube, 1846) Euclymene droebachiensis (Sars, 1872) Eunice vittata (Delle Chiaje, 1828) Glycera alba (O.F. Müller, 1776) Glycera tridactyla Schmarda, 1861 Lagis koreni Malmgren, 1866 Lumbrineris japonica (Marenzeller, 1879) Megalomma claparedei (Gravier, 1906) Microclymene tricirrata Arwidsson, 1906 Micronereis variegata Claparède, 1863 Naineris setosa (Verrill, 1900) Nephthydidae unidentified Perinereis cultrifera (Grube, 1840) Phylo foetida adjimensis (Fauvel, 1924) Timarete filigera (Delle Chiaje, 1828) Travisia forbesii Johnston, 1840 Travisia sp. Carcinus aestuarii Nardo, 1847 Chthamalus stellatus (Poli, 1791) Cymadusa filosa Savigny, 1816 Echinogammarus sp. Idotea chelipes (Pallas, 1766) Idotea granulosa Rathke, 1843 Metapenaeus monoceros (Fabricius, 1798) Necallianassa truncata (Giard & Bonnier, 1890) Orchestia mediterranea Costa, 1853 Pagurus bernhardus (Linnaeus, 1758) Paramysis (Longidentia) nouveli Labat, 1953

Cnidaria

Penaeidae unidentified Sp1 Sphaeroma serratum (Fabricius, 1787) Paranemonia cinerea (Contarini, 1844)

Echinodermata

Holothuria tubulosa (Gmelin, 1791)

similarity index and measured in 2012–2013 at every station (Fig. 5) enabled us to illustrate the environmental and faunistic affinities of the sampled stations.

The abiotic parameters studied appear to be homogeneous as they allowed the 13 stations to be grouped according to a similarity exceeding 80%. They bring together a northern station (station 5) and stations

Please cite this article as: Khedhri, I., et al., Structuring factors of the spatio-temporal variability of macrozoobenthos assemblages in a southern Mediterranean lagoon: How usef..., Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.10.023

Specific richness

1

2

3

4

5

7

Abundance

21 18 15 12 9 6 3 0

2700 2400 2100 1800 1500 1200 900 600 300 0

A (ind/m2)

S (number of species)

I. Khedhri et al. / Marine Pollution Bulletin xxx (2016) xxx–xxx

6

7

8

9

10 11 12 13

1

2

3

4

5

6

7

8

9 10 11 12 13

Stations Stations

Shannon-Wiener index

Evenness 3,5

1

3

0,8

0,6

H'

J'

2,5 2

1,5

0,4

1

0,2

0,5 0

0 1

2

3

4

5

6

7

8

9

10

11

12

13

Stations

1

2

3

4

5

6

7

8

9

10

11

12

13

Stations

Fig. 2. Spatial and seasonal variability of the principal benthic macrofauna parameters in Boughrara Lagoon (S: specific richness; A: abundance; H′: Shannon-Wiener index; J′: evenness).

in direct communication with the sea (1, 2, 3, 6 and 7), though southern stations are included in the same group (stations 10, 11 and 12). The biotic parameters do not show this consolidation; they group together stations situated in and around the two lagoon-sea passages (2, 3 and 6), while stations far to the south (8, 12 and 13) and in the north (stations 5 and 9) are grouped separately. The PCA analysis of the main physicochemical parameters, along with the trophic groups sampled in all seasons of 2012–2013, seen on the plane formed by the first two factors (47.60% of eigenvalues) (Fig. 6), shows the trophic groups as consolidated, with all the stations collected in 2 closed groups. This concerns the southern stations (10, 11 and 12) and stations influenced by the channels (1, 2, 3, 6, 7 and 9). While stations 5 and 8 look completely isolated, the first one appears to correspond to suspension feeders (SF) and the second to herbivores (H). 4. Discussion 4.1. Physicochemical factors The role of the sedimentary texture, one of the keys in the structuring of benthic communities, is minimised in this study due to the homogeneity of the sediment at the sampled stations, as it consisted exclusively of fine-grained sediments, mainly sand (Khedhri et al., 2016). The temperature in Boughrara Lagoon is typical of that in coastal Mediterranean waters (Dhib et al., 2016). In contrast, salinity reached values (up to 50) usually found only in solar salterns (Khemakhem et al., 2010), except for station 5 which was located near a desalination plant. The temperature at this station was especially high due to the discharge of hot water. The pH during this period was always high; this could also be attributed to the high temperature recorded at the majority of stations. Dissolved oxygen increased, particularly at station 9 (fish

farm station) where concentrations varied from 2 mg l− 1 in 2010 to 14.94 mg l−1 in 2013 (Khedhri et al., 2015). This appears to stimulate phytoplankton growth, as indicated by the rise in of chlorophyll a at certain stations (5.27 μg l−1 at station 4). Compared with the chlorophyll concentration in Bizerte Lagoon (4.2 to 8.5 μg l− 1), values are even lower (Bejaoui et al., 2010). Concentrations in nitrite, nitrate, ammonium and phosphate are lower than those observed by Khedhri et al. (2015) in the same lagoon in 2009–2010. Except for station 5 (23.53 μg l−1 of NO− 2 ), the values do not exceed 1 μg l−1 for nitrites and phosphates. Nitrates and ammonium did not attain 7 μg l−1 through the seasons except at station 5 (desalination plant) where a concentration of 67.59 μg l−1 was recorded due to the discharge by the plant of waters containing a high concentration of nitrogenous compounds. Comparable values of nutrient concentration have been observed in other Mediterranean lagoons such as Orbetello Lagoon in Italy (Specchiulli et al., 2008) and Bizerte Lagoon (400 km to the north) (Bejaoui et al., 2010); nitrite and phosphate levels are below 1 μg l−1, nitrates and ammonium are approximately 0.50– 1.46 μg l−1 and 1.47–2.91 μg l−1, respectively. Our findings show that the widening of El Kantra Channel has had a beneficial effect on the ecological balance of Boughrara Lagoon. Compared to the results of 2009–2010 (Khedhri et al., 2015) at the same lagoon, monitoring of the physicochemical parameters of the surface water of Boughrara Lagoon in 2012–2013 shows that water quality has improved, the nutrient level has declined (average phosphate values, for example, varied from 160.9 μg l−1 in 2009 to 0.4 μg l−1 in 2013) and the concentration of dissolved oxygen has increased. 4.2. Macrobenthic community During the study period, the macrobenthic community was subject to Boughrara Lagoon's predictable seasonal changes. The main

Please cite this article as: Khedhri, I., et al., Structuring factors of the spatio-temporal variability of macrozoobenthos assemblages in a southern Mediterranean lagoon: How usef..., Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.10.023

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Winter 12 100%

100%

80%

80%

60%

60%

40%

40%

20%

20%

0%

Spring

0% 1

2

3

4

5

6

7

8

9

10

11

12

13

1

2

3

4

5

Stations

6

7 8 Stations

9

6 7 8 Stations

9

10

11

12

13

10

11

12

13

Autumn

Summer

100%

100%

80%

80%

60%

60%

40%

40%

20%

20%

0%

0%

1

2

3

4

5

6

7

Stations

8

9

10

11

12

1

13

2

3

4

5

100% 80% 60%

Winter 13

40% 20% 0%

1

2

3

4

5

6

7

8

9

10 11 12 13

Stations

Fig. 3. Spatial and seasonal variability of trophic groups of the benthic macrofauna in Boughrara Lagoon. C: carnivores; SDF: selective deposit-feeders; DF: detritus feeders; H: Herbivores; SF: suspension feeders.

community structure parameters fluctuated according to the typical seasonal cycle of temperate coastal waters (Gravina et al., 1989). In comparison with previous studies (Zaouali, 1974; DGPA, 2001; Ghodhbane, 2002; Khedhri et al., 2015), the trends did not vary and molluscs remained the main zoological component of the lagoon's macrozoobenthos. Species richness shows seasonal variation at all stations, the maximum recorded in spring and winter, the minimum in summer and autumn. This seasonal variability can be attributed to environmental parameters and the biological cycles of the species which are related to cyclic fluctuations in climatic factors (Khedhri et al., 2015; Afli et al., 2009a). This infers that, due to the lagoon's arid climatic conditions, seasonal forcing still influences the development of the lagoon's organisms, despite the heavy constraint imposed. In 2009–2010, the lagoonal-marine stations (1, 2, 3 and 7) presented a relatively high specific richness compared to the other stations (Khedhri et al., 2015); the present study, however, shows that specific richness values have fallen sharply at the same stations (S = 0 in summer and winter), and some stations are even azoic. Seasonal variability of abundance (A) in 2012–2013 was also heterogeneous; the maximal A values were recorded during 2 winters and summers, the minimal values in spring and autumn. As with specific richness, abundance is lower at these stations. These areas constitute a transitional environment where the influences of both marine and lagoon fluctuations coexist and variations in physicochemical parameters are intense (Khedhri et al., 2015). This results in the exclusion

of sensitive species such as the gastropod Cerithium vulgatum and the bivalve Abra alba in favour of species tolerant of these parameters, such as the bivalve Cerastoderma glaucum that can live in this environment, favoured by the exclusion of sensitive rival species (Table 4). Borja et al. (2000) noted that, in coastal areas, the number of species decreases as the degree of disturbance rises. While this assertion can apply to many ecosystems, the physicochemical parameters recorded in this study reflect an improvement in the water and sediment quality following the widening of the lagoon-sea passage. Indeed, compared with Bizerte Lagoon in Northern Tunisia (Bejaoui et al., 2010) and Thau Lagoon in France (Gangnery et al., 2003), the hydrobiological conditions in Boughrara Lagoon have actually improved. For example, the increase in the chlorophyll a concentration and suspended particulate matter in the water can be seen in the increased abundance of suspension-feeders in spring. In addition, herbivores have benefited from the decay of macroalgae mats in the sediment since Boughrara Lagoon harbours several varieties of macrophytes including the phanerogam Cymodocea nodosa (Ascherson, 1870), which contributes 70% of the total phytomass, and the alga Caulerpa prolifera ((Forsskål) J.V. Lamouroux, 1809), which accounts for 20%. This may appear as the sign of a satisfactory ecosystem status, as reflected in the trophic organization of species communities, since they depend primarily on the available resources. Boughrara Lagoon nevertheless continues to suffer, particularly from increased temperature and salinity which play an important role in the structuring and organization of communities with,

Please cite this article as: Khedhri, I., et al., Structuring factors of the spatio-temporal variability of macrozoobenthos assemblages in a southern Mediterranean lagoon: How usef..., Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.10.023

4 3,5 3 2,5 2 1,5 1 0,5 0

12

10 8 6 4 2

0

1

2

3

4

5

6

7

8

9 10 11 12 13

1

2

3

4

Stations

0,8

TUBI

0,6 0,4 0,2 0 1

2

3

4

5

6

7

8

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6

7

8

9 10 11 12 13

Stations

1

M-AMBI

9

14

BENTIX

AMBI

I. Khedhri et al. / Marine Pollution Bulletin xxx (2016) xxx–xxx

9

10 11 12 13

5 4,5 4 3,5 3 2,5 2 1,5 1 0,5 0 1

Stations

2

3

4

5

6

7

8

9

10 11 12 13

Stations

Fig. 4. Spatial and seasonal variability of the biotic index in Boughrara Lagoon (AMBI: azti marine biotic index; BENTIX; M-AMBI: multivariate-ambi; TUBI: Turkish benthic index).

Afli et al. (2008c, 2009b) in Ghar El Melh Lagoon (Tunisia) and Lavesque et al. (2009) in Arcachon Bay (France). However, the numerical dominance of deposit-feeders is not completely systematic in the Tunisian and Mediterranean lagoons. To date, several studies show that most of the Tunisian and Mediterranean lagoons are dominated by a single trophic group or two trophic groups in certain cases. For example, carnivores dominate clearly in the Bizerte Lagoon, micrograzers in the southern Tunis Lagoon, selective deposit feeders in the of Ghar El-Melh lagoon (Afli et al., 2008a, 2009b) and detritus feeders in the Smir Lagoon (Chaouti and Bayed, 2011). With

Abiotic parameters

Similarity

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

8 13 1 7 12 9 5 11 4 6 2 3 10

Similarity

Biotic parameters 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

13 10 11 12 5 1 4 6 3 7 2 8 9

for example, the exclusion of certain species or groups of species from Tunisian lagoons in particular and from Mediterranean lagoons generally (Afli et al., 2008b, 2009a). In terms of trophic diversity, the macro-benthic community of Boughrara Lagoon is dominated by selective deposit feeders. Gastropods, mainly of the genus Cerithium, are generally spread over organically enriched sandy and muddy areas. These results confirm those of Paraskevopoulou et al. (2015) in Papapouli Lagoon (Greece), Carvalho et al. (2011) in Obidos Lagoon (Portugal), Rabaoui et al. (2015) in Gabes Gulf (Tunisia), Bazairi et al. (2005) in Smir Lagoon (Morocco),

Fig. 5. Hierarchical Clustering (HC) of Bray-Curtis similarities applied to the abiotic parameters (Temperature, salinity, dissolved oxygen, pH, depth and nutrient salts) and biotic parameters (S, A, H′, J), chlorophyll a, AMBI, BENTIX, M-AMBI and TUBI) in the seasonal samples.

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F1 and F2: 47,60 % 1

F1 and F2: 47,60 %

SF-w12 SF-sp SF-w13

SDF-sp

DF-w13

C-w13

F2: 18,71 %

SDF-a

12 11

C-Sp

H-w13

0

3

DF-sp

DF-w12

C-s

H-s SDF-w12 H-w12 H-a H-sp

SDF-s

8

F2 :18,71 %

SDF-w13

0,5

6

SF-a

SF-s

DF-a C-w12 C-a DF-s

4 7

10

0

9

F1 :28,89 %

2 6

13 1

-0,5

5

3

-3 -5

-2

1

4

7

-1 -1

-0,5

0

0,5

1

F1: 28,89 %

Fig. 6. Principal Component Analysis (PCA) applied to the trophic groups (C: carnivores; SDF: selective deposit-feeders; DF: detritus feeders; H: Herbivores; SF: suspension feeders) in the seasonal samples (w12: winter 2012; sp.: spring; s: summer; a: autumn; w13: winter 2013).

regard to seasonal variability, suspension feeders dominate in spring 2012, while herbivores dominate in winter 2013 and all the other trophic groups are present all year round, and their densities seem to be linked to the availability of trophic resources. An intriguing finding in our study is the presence in 2012–2013 of 41 species not recorded in 2009–2010 (Khedhri et al., 2015), including 20 species of polychaetes belonging to trophic groups of deposit-feeders and carnivores and which are expected to increase in areas disturbed by organic pollution (Pearson and Rosenberg, 1978; Statzner and Bêche, 2010). Thus the presence of these species in 2012–2013 is related to their species characteristics too; in fact they are different and more tolerant species of the ecological groups II and III and proliferate in the presence of organic disturbances (Glémarec and Hily, 1981). Indeed, most of the recent species recorded (nine molluscs, one cnidarian, eleven crustaceans and twenty polychaetes) (Table 5) were observed in spring at stations enriched with organic matter, stations considered by Khedhri et al. (2016) to be imbalanced. We believe that this finding is of paramount importance because it clearly demonstrates that the widening of the El Kantra Channel favoured the development of HAB blooms visible during our survey, causing fish mortality which increased the amount of organic matter in the water, thus explaining the development of these polychaete communities. The various biotic indices show a certain degree of inter-correlation. Indeed, the majority of these indices classify all stations as having a high and good ecological status. However, a closer analysis of the ecological groups shows that the area is mostly represented by sensitive species, while the presence of first and second order opportunistic species indicative of polluted environments, suggest that the area may in the future be at risk of eutrophication if conditions do not improve. According to Afli et al. (2008b) and Labrune et al. (2006), these biotic indices based on ecological groups are dependent on the Pearson–Rosenberg model (Pearson and Rosenberg, 1978) and are thus related to the organic matter content gradient and not to other stressors such as physical disturbance (Carvalho et al., 2006). 5. Conclusion This study was conducted 5 years after the widening of the lagoonsea passage of El Kantra, with the aim to improve the quality of waters

and sediments and to rehabilitate the overall ecosystem of Boughrara Lagoon. Despite improvement in the overall environmental quality, benthic macrofauna assemblages appear to continue to suffer from these changing conditions. It was, however, beneficial for the growth and proliferation of toxic dinoflagellates which, along with extreme fluctuations in temperature and salinity, has caused the disappearance of the lagoon's principal and most sensitive species of macroinvertebrates. Only a few species have survived this change, suggesting that in an intermediate state of disturbance the food chain simplifies (Grime, 1973; Reynolds et al., 1993). We infer that HAB forcing still influences the development of the macroinvertebrates present in the lagoon, therefore weakening the bioindicator power of biotic indices which, paradoxically, classified all the sampled stations at a high ecological status. In fact AMBI and BENTIX are based on only one group of relative abundances of the ecological groups and may lead to an erroneous conclusion if the stations are, for example, dominated mainly by sensitive or opportunistic species (the case of sampled stations which include sensitive species). Thus, according to Borja and Muxika (2005), the precision of AMBI can also be reduced if sampled stations have a very low number of taxa and/or individuals. The recent study of Xianxiang et al. (2016) in the Huanghe estuary in China, which is under natural and anthropogenic stress, has confirmed our hypotheses and has shown that AMBI was insensitive to physical parameters (water depth and sediment texture). Therefore, to calculate M-AMBI, we must use only the species database on the AZTI web page (http://www.azti.es) and which is sometimes different from the database of the sampled species. However, Xianxiang et al. (2016) indicated that the M-AMBI was sufficiently robust to assess the ecological quality status and could distinguish degraded from undegraded conditions. The results of this study point to the need for further research to adapt these biotic indices to habitat specificities. These indices have been seen to work in fully open systems, but seem to be less efficacious in a semi-enclosed system such as Boughrara Lagoon. In addition to their intrinsic interest, our findings and their interpretations serve to illustrate that the biotic indices selected for screening stood out significantly by their sensitivity to the control imposed by the trophic web. Under the influence of HAB blooms, these biotic indices led to some novel departures from the ostensibly “normal” pattern of growth

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Table 5 Comparative table of macrobenthic species in the Bougharara Lagoon. C: carnicores; SF: suspension feeders; DF: detritus feeders; H: herbivores; SDF: selective deposit feeders. I: sensitive species; II: indifferent species, III: tolerant species, IV: second-order opportunistic species and V: first order opportunistic species. : Present in 2009–2010; : Present in 2012–2013. Phylum

Mollusca

Annelida

Arthropoda

Echinodermata Cnidaria Porifera

Species

Only present in 2009-2010

Recently present in 2012-2013

Trophic groups

Acanthocardia spinosa (Lightfoot, 1786) Antalis dentalis (Linnaeus, 1758) Antalis panorma (Chenu, 1843) Antalis vulgaris (da Costa, 1778) Bittium depauperatum Watson, 1897 Bittium incile Watson, 1897 Bulla striata Bruguière, 1792 Callochiton septemvalvis (Montagu, 1803) Chiton (Rhyssoplax) olivaceus Spengler, 1797 Columbellidae unidentified Corbula gibba (Olivi, 1792) Dosinia lupinus (Linnaeus, 1758) Euthria cornea (Linnaeus, 1758) Gibbula albida (Gmelin, 1791) Gibbula racketti (Payraudeau, 1826) Goniostoma paradoxa (Monterosato 1884) Haminoea navicula (da Costa, 1778) Liomesusarum sp. Mytilus galloprovincialis Lamarck, 1819 Nassarius granum (Lamarck, 1822) Nassarius incrassatus (Strøm, 1768) Nassarius mutabilis (Linnaeus, 1758) Nassarius pygmaeus (Lamarck, 1822) Nassarius reticulatus (Linnaeus, 1758) Nassarius sp. Neverita delessertiana (Récluz, 1843) Pinctada imbricata radiata (Leach, 1814) Pisania striata (Gmelin, 1791) Setia fusca (Philippi, 1841) Smaragdia viridis (Linnaeus, 1758) Tellina planata Linnaeus, 1758 Tellina pulchella Lamarck, 1818 Thracia phaseolina (Lamarck, 1818) Tricolia tenuis (Michaud, 1829) Trivia monacha (da Costa, 1778) Alitta succinea (Leuckart, 1847) Arenicola cristata Stimpson, 1856 Branchiomma sp. Capitallidae unidentified Capitella sp. Dasybranchus caducus (Grube, 1846) Euclymene droebachiensis (Sars, 1872) Eunice vittata (Delle Chiaje, 1828) Glycera alba (O.F. Müller, 1776) Glycera tridactyla Schmarda, 1861 Lagis koreni Malmgren, 1866 Lumbrineris japonica (Marenzeller, 1879) Megalomma claparedei (Gravier, 1906)

SF SDF SDF SDF H H H H H H SF SF C SDF SDF H C SF SF C C C C C C C SF C H H SDF SDF SF H C C

Microclymene tricirrata Arwidsson, 1906 Micronereis variegata Claparède, 1863 Naineris setosa (Verrill, 1900) Nephtydidae unidentified Nereis sp. Ophelia sp. Phylo foetida adjimensis (Fauvel, 1924) Polyophthalmus pictus (Dujardin, 1839) Sabella pavonina Savigny, 1822 Sabellaridae unidentified Serpulidae unidentified Timarete filigera (Delle Chiaje, 1828) Travisia forbesii Johnston, 1840 Travisia sp.

SDF C SDF C C

Amphi sp. Ampithoe rubricata (Montagu, 1818) Carcinus aestuarii Nardo, 1847 Corophium volutator (Pallas, 1766) Cymadusa filosa Savigny, 1816 Cymodoce truncata Leach, 1814 Dexamine spinosa (Montagu, 1813) Echinogammarus sp. Elasmopus rapax Costa, 1853 Ericthonius punctatus (Bate, 1857) Gammarus aequicauda (Martynov, 1931) Gammarus locusta (Linnaeus, 1758) Gammarus sp. Gammarus Fabricius, 1775 Hyale schmidti (Heller, 1866) Idotea chelipes (Pallas, 1766) Idotea granulosa Rathke, 1843 Leucothoe spinicarpa (Abildgaard, 1789) Lysianassina longicornis (Lucas, 1846) Maera inaequipes (Costa, 1857) Medigidiella chappuisi (Ruffo, 1952) Metapenaeus monoceros (Fabricius, 1798) Mysis sp. Necallianassa truncata (Giard & Bonnier, 1890) Orchestia mediterranea Costa, 1853 Pagurus bernhardus (Linnaeus, 1758) Pagurus cuanensis Bell, 1846 Paramysis (Longidentia) nouveli Labat, 1953 Penaeidae unidentified Talitrus saltator (Montagu, 1808) Tanis sp. Theostoma oerstedi (Claparede, 1864) Asterina gibbosa (Pennant, 1777) Ocnus syracusanus (Grube, 1840) Panning, 1949 Sp. Aplysina aerophoba Nardo, 1833

DF DF C SDF H DF SF SDF DF DF DF DF DF DF DF DF DF SDF DF SDF DF C DF

SF SDF SDF SDF SDF C C C SDF DF SF

SDF SF SF SF SF DF SDF SDF

SDF DF DF C DF DF SF C DF

Ecological groups III I I I I I I I IV I I I II I II II II II II II

I I I I III III I V V V I II II II III II II I III II II III

V I I I I I I I I III III I I III I I I I I I I II II I I I

I III I I II II II I I

SF

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responses found among many other macroinvertebrates. Indeed, the ambient forcing imposed will not enable the successional macrofauna assembly to proceed to a common pattern of increased species richness and complexity of interactions among the species present (Aleya, 1991; Margalef, 1997; McGill et al., 2007). New dredging programs between the El Kantra Channel and the stream (station 13) located in the lagoon centre will be necessary to improve water mixing and sediment quality. Acknowledgements This study was undertaken as a part of the project ‘EBHaR’, financed by the Tunisian Ministry of Higher Education, Scientific Research, Information and Communication Technologies. It is the result of collaboration between the INSTM, Tunisia and the University of BourgogneFranche-Comté, Chrono-Environment Laboratory, National Centre for Scientific Research CNRS 6249, Besançon, France. We would also like to thank the editor Professor Charles Sheppard and the anonymous reviewers for the helpful recommendations on this manuscript. References Abdenadher, M., Hamza, A., Feki, W., Hannachi, I., Zouari-Belaaj, A., Bradai, N., Aleya, L., 2012. Factors determining the dynamics of toxic blooms of Alexandrium minutum during a 10-year study along the shallow southwestern Mediterranean coasts. Estuar. Coast. Shelf Sci. 106, 102–111. Afli, A., Glémarec, M., 2000. Fluctuation à long terme des peuplements macrobenthiques de la partie orientale du golfe du Morhiban (Bretagne, France). Cah. Biol. Mar. 41, 67–89. Afli, A., Ayari, R., Brahim, M., 2008a. Trophic organization of the macro-zoobenthic assemblages within coastal areas subjected to anthropogenic activities. J. Mar. Biol. Assoc. U. K. 88, 663–674. Afli, A., Ayari, R., Zaabi, S., 2008b. Ecological quality of some Tunisian coast and lagoon locations, by using benthic community parameters and biotic indices. Estuar. Coast. Shelf Sci. 80, 269–280. Afli, A., Boufahja, F., Sadraoui, S., Ben Mustpha, K., Aissa, P., Mrabet, R., 2009a. Functional organisation of the benthic macrofauna in the Bizerte lagoon (Sw Mediterranean Sea), semi-enclosed area subject to strong environmental/anthropogenic variations. Cah. Biol. Mar. 50, 105–117. Afli, A., Chakroun, R., Ayari, R., Aissa, P., 2008c. Response of the benthic macrofauna to seasonal natural and anthropogenic constraints within Tunisian lagoonal and coastal areas (south-western Mediterranean). Vie et Milieu 59, 21–30. Afli, A., Chakroun, R., Ayari, R., Aissa, P., 2009b. Seasonal and spatial variability of the community and trophic structure of the benthic macrofauna within Tunisian lagoonal and marine coastal areas (southwestern Mediterranean). J. Coast. Res. 25, 140–149. Aleya, 1991. The concept of ecological succession applied to an eutrophic lake through the seasonal coupling of diversity index and several parameters. Fundam. Appl. Limnol. 120, 327–343. APHA, 1992. American Public Health Association, 1992. Standard Methods for the Examination of Water and Wastewater. American Public Health Association, Washington, DC. Bald, J., Borja, A., Muxika, I., Franco, F., Valencia, V., 2005. Assessing reference conditions and physico-chemical status according to the European water framework directive: a case-study from the Basque Country (northern Spain). Mar. Pollut. Bull. 50, 1508–1522. Bazairi, H., Bayed, A., Hily, C., 2005. Structure et bioévaluation de l'état écologique des communautés benthiques d'un écosystème lagunaire de la côté atlantique marocaine. Comptes Rendus Biologiques 328, 977–990. Bejaoui, B., Ferjani, D., Zaaboub, N., Chapelle, A., Moussa, M., 2010. Caractérisation hydrobiologique saisonnière de la lagune de Bizerte (Tunisie). J. Water Sci. 23, 215–232. Bell, G., 2005. The co-distribution of species in relation to the neutral theory of community ecology. Ecology 86, 1757–1770. Blanchet, H., Lavesque, N., Ruellet, T., Dauvin, J.C., Sauriau, P.G., Desroy, N., Desclaux, C., Leconte, M., Bachelet, G., Janson, A.L., Bessineton, C., Duhamel, S., Jourde, J., Mayot, S., Simon, S., de Montaudouin, X., 2008. Use of biotic indices in semi-enclosed coastal ecosystems and transitional waters habitats – implications for the implementation of the European Water Framework Directive. Ecol. Indic. 8, 360–372. Borja, A., Muxika, I., 2005. Guidelines for the use of AMBI (AZTI's marine biotic index) in the assessment of the benthic ecological quality. Mar. Pollut. Bull. 50, 787–789. Borja, A., Tunberg, B.G., 2011. Assessing benthic health in stressed subtropical estuaries, eastern Florida, USA using AMBI and M-AMBI. Ecol. Indic. 11, 295–303. Borja, A., Franco, F., Muxika, I., 2004. The biotic indices and the water framework directive: the required consensus in the new benthic monitoring tools. Mar. Pollut. Bull. 48, 405–408. Borja, A., Franco, J., Pérez, V., 2000. A marine biotic index to the establish ecology quality of soft-bottom benthos within European estuarine coastal environments. Mar. Pollut. Bull. 40, 1100–1114.

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Please cite this article as: Khedhri, I., et al., Structuring factors of the spatio-temporal variability of macrozoobenthos assemblages in a southern Mediterranean lagoon: How usef..., Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.10.023