Corrigendum to: Effects of sewage discharges on microbial components in tropical coastal waters...

CSIRO PUBLISHINGCorrigendum

Marine and Freshwater Research, 2008, 59, 838–839 www.publish.csiro.au/journals/mfr

Effects of sewage discharges on microbial componentsin tropical coastal waters (Senegal, West Africa)

Marc Bouvy, Enora Briand, Maimouna M. Boup, Patrice Got,Christophe Leboulanger, Yvan Bettarel and Robert Arfi

Marine and Freshwater Research 59, 614–626. doi:10.1071/MF07244

The authors wish to alert readers to the following error:

The incorrect figures were used for Figs 2 and 4. They shouldappear as follows.

�10 �50 �10 �5 �1�5 �1

N2

N1 S3 N1

N2

N3

N5

N4

N8 N9N10

N11

N7N6

S2

S1

I1

S3

I2 I3

I4I5

I6

S2

I1

N3

N4

N5

N6

N7N8

N9

N10

N11I4

Chlorophyll Chlorophyll

N1

�10 000 �1000 �100 �100 000 �10 000 �1000 �100

N2

N3

N4

N5

S2

S1

I3

I5

I6

N10

N11

I2

I4

I1

N2

N1

N3

N4

N5

TTC

N6N7

N8N9

N6

N7 N8

I4

N9

N10

N11

I6

TTC

N5

N6N7

N8N9 N10

N4

N3

N2N1

�10 µM �1 µM �0.1 µM

I1

S1

S2S3

I2

I3

May 2004

NH4

I4I5

I6

N11

N1

N2

N3

N5

N6

N7N8 N9 N10

N11

I6

S3

I1

I2

I3

I4

N4

�100 µM �10 µM �1 µM

November 2004

NH4

Fig. 2. Distribution of ammonia concentrations, thermo-tolerant coliforms (TTC) (expressed in colony forming units; CFU 100 mL−1) and totalphytoplankton abundances (expressed in equivalent chlorophyll a) in May and November 2004. N, near shore; I, intermediate; S, sea-shore.

© CSIRO 2008 10.1071/MF07244 1323-1650/08/090838

Corrigendum Marine and Freshwater Research 839

S3

N8N9

N4

CRYPTI4 I3

I5I6

I1N10

NO3

N1

N2

N7N5

N3

BACIL

CYANOT-BACT

C-BACT

CHLOR

TTC

FS

PO4

T-PHYTO

HNF

NH4

NH4

S2

S1N4 N6

N5

N2

N11I1

I3I2I4

S3I5 N7

I6 HNF

CYANO

T-PHYTO

BACIL

PO4

NO3

N9

N8

N1

N10

N6N11

I2S2 S1

�4 �2 0Axis 1 (66.7%)

2 4 6

NOVEMBER 2004

MAY 2004

�4 �2 0 2

Axis 1 (62.8%)

4 6

T-BACT

C-BACTCHLOR

CRYPT

TTC N3

FS

3(a)

(b)

2

1

0

Axi

s 2

(17.

7%)

Axi

s 2

(25.

2%)

�1

�2

�3

�4

4

2

0

�2

�4

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�5�6

Fig. 4. Principal component analysis (PCA) on the two first axes in May and November 2004.Eigenvalues for each axis of the PCA are reported. Stations are identified as inTable 1. See Discussionsection for the differentiation of the groups of parameters studied. N, near shore; I, intermediate;S, sea-shore.

CSIRO PUBLISHING

Marine and Freshwater Research, 2008, 59, 614–626 www.publish.csiro.au/journals/mfr

Effects of sewage discharges on microbial componentsin tropical coastal waters (Senegal, West Africa)

Marc BouvyA,E, Enora BriandB, Maimouna M. BoupC, Patrice GotA,Christophe LeboulangerA, Yvan BettarelC and Robert ArfiD

AIRD UR 167, UMR ECOLAG, Université Montpellier II, Case 093, Place Eugène Bataillon,34095 Montpellier Cedex 5, France.

BUSM505, Écosystèmes et interactions toxiques, Muséum National d’Histoire Naturelle,57 rue Cuvier, case 39, 75231 Paris Cedex 05, France.

CIRD UR 167, Centre IRD-ISRA, BP 1386 Dakar, Senegal.DIRD UR 167, Centre d’Océanographie de Marseille, 13007 Marseille, France.ECorresponding author. Email: [email protected]

Abstract. Coastal ecosystems are frequently submitted to anthropogenic pressure but little is known about how thedynamics of aquatic communities can be altered. The impact of urban and industrial discharges on microbial planktonwas studied in Hann Bay near Dakar (Senegal) on the Atlantic Ocean. Spatial patterns were studied using three transects,with a total of 20 stations, during two periods in May and November (before and after the seasonal upwelling), revealinga clear contrast between near shore stations and the intermediate and seaward stations. In November, phytoplankton wereassociated with dissolved nutrient availability (e.g. with nitrate, r = 0.76) whereas in May, phytoplankton were morecorrelated with microbial variables (e.g. with heterotrophic nanoflagellates, r = 0.63). Most samples (40) failed to meetthe quality levels for the faecal indicator bacteria (FIB) defined by the European Union bathing water quality directive.The topography plays a major role in water circulation explaining the presence of FIB at the seaward stations. The highprevalence of FIB during the two periods suggests chronic pollution and a potential risk to recreational swimmers andfish consumers in Hann Bay. Thus, as demonstrated in various temperate systems, the decline of water quality constitutesa serious problem in many West African countries.

Additional keywords: coastal bay, faecal indicator bacteria, microbial loop, nutrient.

Introduction

In a context of anthropogenic pressure, damage to coastal ecosys-tems has increased over the past decades, but little is knownabout how the structure and function of aquatic communitiesare being altered (Vitousek et al. 1997). Coastal water eutrophi-cation, one of the greatest problems facing aquatic ecosystemstoday, is aggravated by increased inputs of land-derived nitrogenand phosphorus that are linked to increasing urban and agricul-tural activities (Scialabba 1998). In addition to high nutrientavailability, which causes significant changes in coastal nutri-ent concentrations (Conley 2000), continental waters are oftenpolluted by pathogenic microorganisms from recreational mari-nas, sewage disposal sites, septic tanks, rainfall runoff fromurban areas and other diffuse sources (Lipp et al. 2001; Aslan-Yilmaz et al. 2004). Microorganisms are effective descriptors forevaluating and predicting the environmental impact of humanactivities. However, the composition and structure of microbialcommunities (e.g. phytoplankton blooms, high heterotrophicactivity of bacteria) are also basic indicators of ecosystem status(Ducklow 1992; Paerl et al. 2002; Newton and Mudge 2005;Snow and Adams 2007).

Faecal indicator bacteria (FIB) including thermo-tolerantcoliforms (TTC) and faecal streptococci (FS) are used as

surrogates for human and animal pathogens in assessing waterquality. In epidemiological studies, FIB are documented as beingassociated with an increased risk of contracting gastrointestinaland respiratory illnesses after contact with waters with high con-centrations (Haile et al. 1999; Bonilla et al. 2006). Their originwas always presumed to be anthropogenic (e.g. sewage, agricul-tural and urban runoff). One important criterion for assessingthe potential health risk of recreational waters is the FIB den-sity. Although they do not necessarily induce illness, they areoften associated with pathogenic bacteria, viruses and parasitesin domestic sewage. Microbial water quality also varies accord-ing to the magnitude of all inputs and the flow and dispersion oforganisms as a result of near-shore hydrodynamics such as tidesand currents (Davies-Colley et al. 1994; Bordalo 2003).

Anthropogenic inputs affect ocean water quality more dra-matically in developing countries than in other locations becauseof increasing urbanisation in coastal areas where industrial anddomestic runoffs are generally not treated. Environmental pol-lution linked to the socioeconomic characteristics of the regionhas caused eutrophication of marine waters in the coastal zoneof the Gulf of Guinea (West Africa) (Sheren et al. 2002). Morethan 30% of the population of West Africa from Mauritania toCameroon (nearly 180 million) live in urban coastal settlements

© CSIRO 2008 10.1071/MF07244 1323-1650/08/070614

Effects of sewage on microbial components in a tropical bay Marine and Freshwater Research 615

100 km

100 km

SenegalDakar

5 km Atlantic Ocean

Hann Bay

Dakar City

14°40�N

17°25�W

S1 S2 S3

I1I2 I3

I4I5

I6

N2N3

N4N5

N6

N1

N10

N11

N9N7 N8

Thiaroye City

Industrialareas

D1

D2

D3D4 D5

D6

Cap Vert Peninsula

Dyke

Residential andindustrial areas

Gorée Island

Dakar harbor

Bel Air industrial area

West Africa

Fig. 1. Location of Senegal in West Africa and of the twenty stations studied in Hann Bay near Dakar City. D1–D6, sewers; I1–I6, intermediatestations; N1–N11, near shore stations; S1–S3, seaward stations.

and 60–80% of industrial production takes place in the mainharbours (Sheren et al. 2002). In Senegal, more than 80% ofSenegalese industry is located in Hann Bay because it is closeto Dakar.

Industrial development started in the 1950s when there wereno urban planning regulations or collective and/or individualwater treatment facilities. The consequences were accentuatedby strong demographic pressure (in 1976 there were 37 000 peo-ple living along the shore in the Bay and this had increased to over100 000 in 2002; UNEP 1999). These factors now contribute tothe advanced state of degradation in the Bay owing to domesticand industrial sewage water being discharged through severalsewers along the shore (hydrocarbon and chemical residues,uncontrolled and unauthorised discharge of liquid and solidwaste from domestic and industrial sources) (UNEP 1999). Oneof the most polluted areas in the world, Hann Bay, Dakar, is nowrecognised as a problem zone inWestAfrica in terms of industrialand urban pollution (www.blacksmithinstitute.org). Few studieshave reported on the impact of waste water release in tropi-cal coastal areas although the release of untreated wastewatersdirectly in tropical coastal waters occurs frequently owing to theabsence of wastewater treatment facilities in most of the largecities in developing countries (Sheren et al. 2002; Troussellieret al. 2004).

The main aim of the present study was to assess the impact ofthese various outfalls on autochthonous microbial communitiesof a tropical coastal bay, in terms of inputs and dispersion of FIBas well as the relationship to the microbial food web. For this,spatial patterns (three transects, 20 stations in total) and temporal

patterns (before and after the seasonal upwelling) were studiedusing chemical and biological indicators (13 descriptors). Sev-eral research questions were addressed: do sewage dischargescause an increase of FIB in the vicinity of the sewage outfallsand what are their dispersion levels at the Bay scale? What are theimpacts of sewage discharges on the structure of phytoplanktoncommunities and also on the nature of the relationships betweenthe microbial components?

Materials and methodsStudy site and general water circulationin the oceanic zoneHann Bay (14◦34′N; 17◦29′W) is located in the south of theCap Vert peninsula along the east of Dakar (Senegal, Fig. 1).In this part of the Atlantic Ocean, the general oceanic circula-tion combines the Canary Current flowing southward, mostlyinfluencing the north coast of the peninsula, and the Equato-rial Counter Current flowing northward, mostly influencing thesouth of the peninsula. The water circulation pattern inducedby these two dynamic systems depends on the atmospheric andwind conditions: cold, rich ‘Canarian’ water predominates inthe Dakar area in winter, whereas warm, poor ‘Guinean’ waterdominates in summer. Rebert (1982) and Touré (1983) describedthis seasonal cycle locally as a cyclonic vortex with a coastwardflow of deep water and a seaward flow of surface water in winter(upwelling) and an anticyclonic vortex with the flow reversedin summer. The tidal currents seem to be linked to the coastalmorphology, with a negligible meridian component but a marked

616 Marine and Freshwater Research M. Bouvy et al.

Table 1. List of stations studied in Hann Bay (Senegal), with their geographical coordinatesMaximum depth and temperature of the water column are reported for the two surveys (May and November 2004)

Code Latitude Longitude May 2004 November 2004North West Depth Temperature Depth Temperature

(m) (◦C) (m) (◦C)

Near shore stationsN1 14◦42.430′ 17◦25.570′ 1.7 19.8 1.9 25.6N2 14◦42.575′ 17◦25.757′ 1.0 19.3 0.8 25.2N3 14◦42.895′ 17◦25.840′ 0.9 19.5 1.0 25.2N4 14◦43.431′ 17◦25.619′ 2.6 18.9 3.2 25.1N5 14◦43.909′ 17◦25.035′ 1.7 18.2 1.6 24.8N6 14◦44.116′ 17◦24.360′ 1.6 17.6 1.4 24.6N7 14◦44.138′ 17◦24.328′ 1.4 17.7 1.5 24.5N8 14◦44.272′ 17◦23.860′ 1.9 17.6 1.6 24.2N9 14◦44.369′ 17◦22.197′ 1.8 17.4 1.6 24.2N10 14◦44.164′ 17◦20.925′ 3.3 17.2 3.2 24.1N11 14◦44.104′ 17◦20.655′ 3.1 17.3 2.8 24.2

Intermediate stationsI1 14◦43.160′ 17◦24.700′ 7.2 17.8 6.9 24.6I2 14◦43.530′ 17◦24.190′ 8.4 17.5 8.0 24.6I3 14◦43.790′ 17◦23.550′ 7.0 17.5 7.2 24.5I4 14◦43.900′ 17◦22.830′ 3.7 17.5 3.8 24.6I5 14◦43.810′ 17◦21.990′ 9.2 17.3 9.1 24.8I6 14◦43.620′ 17◦21.130′ 9.8 17.3 8.5 24.4

Seaward stationsS1 14◦42.800′ 17◦23.690′ 7.0 18.0 6.6 25.0S2 14◦43.080′ 17◦22.720′ 9.8 17.6 8.8 24.9S3 14◦42.880′ 17◦21.650′ 9.7 17.7 9.2 24.6

zonal component.The combination of the littoral orientation andwind direction should favour a coastal sweep and a general south-ward flow of the surface water. The ‘Canarian’water is observedduring the upwelling in boreal winter and spring (from Januaryto April with temperature >24◦C and salinity <35), whereasthe ‘Guinean’ water is observed during the boreal summer andautumn (fromAugust to November with temperature >24◦C andsalinity <35). Transitional conditions are observed fairly regu-larly in December and May (Touré 1983). In Hann Bay, highsea surface temperatures (SST) are recorded in July and August(between 26◦C and 29◦C), whereas low values of around 16◦Care reported in February (Rossignol 1973). Cooling may varyfrom year to year as a result of the high interannual variabilityof the Mauritania-Senegal upwelling (Arfi 1985).

Sample collection and processingThe present study was conducted at the beginning (November2004, temperature range: 24.1–25.6◦C) and at the end (May2004, temperature range: 17.2–19.8◦C) of the upwelling period.Samples were taken from three transects more or less parallelto the shoreline, in contrasting environmental conditions (seeabove). Six sewage discharges (‘D’ on Fig. 1) were identified asprobable major sources of contamination of the bay: two indus-trial sources (D3 and D6) and four urban or domestic sewers(canalised or diffuse input) serving small villages. Samples weretaken from twenty stations between 0800 and 1200 hours fromcoastal to offshore waters (Fig. 1 and Table 1). Eleven near-shore

stations (N1 to N11) were located around 5 m from the coastline(at a depth of 1–3 m) and six intermediate stations (I1 to I6) werelocated around 1 km from the shore (at a depth of 4–10 m). Asa result of the highly dynamic mixing processes prevailing inthis coastal area (Touré 1983) only three seaward stations (S1 toS3) were sampled, located around 2.5 km from the coastline (ata depth of 7–10 m).

Samples of seawater were taken using 2-L sterile acid-cleanedbottles at a depth of 0.5 m. Samples for dissolved nutrients (NH4-N, NO3-N, PO4-P) were previously filtered onto Whatman GF/Ffibreglass filters, stored at −20◦C and analysed according toStrickland and Parsons (1972). Sub-samples for determiningtotal bacterioplankton (T-BACT) and heterotrophic nanoflag-ellates (HNF) were fixed with buffered formalin (2% finalconcentration) and stained with 4′6′-diamidino-2-phenylindoledihydrochloride (DAPI) fluorochrome before counting by epi-fluorescence microscopy (Porter and Feig 1980; Sherr andSherr 1991). Culturable heterotrophic bacteria (C-BACT) werecounted by plating 100 µL of serial dilutions of each sample onmarine agar plates (Marine Agar; Difco, Detroit). After 7 days’incubation at room temperature (22◦C ± 3◦C) colony formingunits (CFU) were counted. Counts did not increase after pro-longed incubation. A membrane filtration method was used tocount thermo-tolerant coliform (TTC) and faecal streptococci(FS) as colony forming units per 100 mL of sample. TTC werecounted as the number of blue colonies of 1–2 mm developedon mFC medium (Sartorius, Goettingen) after 24 h incubationat 44.5◦C. Small red to reddish brown colonies of FS (∼1 mm)


were counted on Slanetz and Bartley medium (Sartorius) after48 h incubation at 37◦C. The phytoplankton abundance was esti-mated in the field, using in vivo fluorescence measurement asa proxy, using a submersible fluorescence probe (FluoroProbe,bbe-Mouldaenke; Beutler et al. 2002) on vertical profiles. Theprobe was used to estimate the relative abundance (as chloro-phyll a-equivalent) of the total phytoplankton (T-PHYTO) andthe main phytoplankton groups (Bacillariophyceae, BACIL;Cyanobacteria, CYANO; Chlorophyceae, CHLOR; Crypto-phyceae, CRYPT) in natural communities (Leboulanger et al.2002). Briefly, this device is able to discriminate between themain phytoplankton groups on the basis of the relative fluores-cence intensity of chlorophyll a at 680 nm, following sequentiallight excitation by five light-emitting diodes (LEDs) emitting at450, 525, 570, 590 and 610 nm.

Data processingThe relationships between nutrients (ammonia, orthophos-

phate, and nitrate), chlorophyll a, bacteria and HNF abundances,culturable bacteria, faecal coliforms and streptococci, and phyto-plankton groups were studied using multivariate analysis. Sincedistributions of several variables did not meet normality, a non-parametric Mann–Whitney U-test was applied in order to searchfor median differences (Sigma Stat version 3.5). To synthe-sise the major sources of temporal and spatial variability inthe microbial communities, correlation between variables weretested. Parametric tests (two variables Bravais-Pearson correla-tions) and multivariable centred principal component analysis(PCA) were conducted on data log(x + 1) transformed in orderto meet normality requirements. A second step of data analysiswas based on a PCA conducted on the whole dataset. Clusteranalysis (Euclidean distance, Ward’s method) was applied to thescore of the two first components and provided a classification ofthe sampling station from a multivariable point of view.The opti-mised number of clusters was defined from the highest jump inthe linkage distance. Data were processed usingADE-4 software(Thioulouse et al. 1997).

Results

Twenty stations describing three transects were sampled, fromcoastal to offshore waters (Fig. 1). The near shore transect wasdefined by eleven stations that were directly affected by urbansewage and industrial effluent. Thus, nutrient concentrationswere generally higher at the near shore stations (Table 2). Nosignificant difference in orthophosphate was recorded in Mayand November at any of the stations along the three transects.However, ammonia concentrations were significantly greater inNovember at the near shore (P = 0.002) and intermediate sta-tions (P = 0.009). Very high values were recorded at the nearshore stations in November (210 and 118 µm at stations N3 andN10 respectively) whereas the values were lower in May (1 and24 µm, at these stations, Fig. 2). Nitrate concentrations were gen-erally low (average <2.6 µm at the near shore stations in May),and values were only significantly greater in May at the seawardstations (P = 0.002; Table 2).

The highest densities of T-BACT were recorded at the nearshore stations (around 1.0 × 107 cells mL−1) whereas the aver-age abundances were 2.3 and 2.5 × 106 cells mL−1 at the

seaward stations in May and November respectively. C-BACTconcentrations were higher at the near shore stations and lower atthe seaward stations, with values significantly higher in May forthe three transects. Of the FIB, thermo-tolerant coliforms (TTC)were very abundant at the near shore stations with maximum val-ues recorded at station N3 (19 200 and 239 000 CFU 100 mL−1

in May and November respectively). TTC concentrations werelower at the intermediate and seaward stations, with significantgreater values in November (P = 0.015; Table 2).

The same pattern was observed for the faecal streptococci(FS), with values significantly higher in November (P = 0.001)only at the seaward stations. FS concentrations measured inMay at the intermediate sites (L1 to L6) did not exceed 30 CFU100 mL−1, whereas samples taken near the shore (N1 to N11)showed an average of 3390 CFU 100 mL−1. The highest val-ues were recorded at stations N3 (10 500 CFU 100 mL−1) andN6 (21 000 CFU 100 mL−1). There was a significant correlationbetween the TTC and FS concentrations for all data (r = 0.8;P < 0.001) (Fig. 3).Average values were well above the EU guidelevel (for marine water quality) of 500 CFU 100 mL−1 for TTCand 100 CFU 100 mL−1 for FS. For coliforms, 50% and 70%of samples failed to comply with the EU guide, respectively, inMay and November.

Heterotrophic nanoflagellate abundance was higher inNovember at all stations with significant differences recordedbetween the near shore (P = 0.005) and the intermediate stations(P = 0.015; Table 2). The highest values for in vivo fluorescenceof the total phytoplankton expressed in equivalent chlorophyll a(T-PHYTO) were recorded in November, with a mean of11.6 µg L−1 at the near shore stations and 2.4 µg L−1 at the sea-ward stations. Higher concentrations were recorded at the nearshore stations in November with the maximum value recorded atstation N9. Significant higher values of T-PHYTO were recordedin November at the intermediate stations (P = 0.001; Table 2).The same result was recorded for the four main phytoplank-ton groups discriminated by the fluoroprobe (Chlorophyceae,Cyanobacteria, Bacillariophyceae and Cryptophyceae). How-ever, no significant difference in the concentration of thesephytoplankton groups was observed during the two sets of mea-surements for the seaward stations (Table 2).The dominant groupat all stations during both periods was Bacillariophyceae, with amean proportion of total fluorescence at the intermediate stationsranging from 51.6% in May to 83.4% in November. The secondgroup was represented by Cyanobacteria with a high concentra-tion at the seaward stations. There were only low percentages ofthe two other groups.

The two PCAs were performed on the whole datasets (20stations and 13 descriptors).The first two eigenvalues of the PCAanalysis accounted for 80.5% and 91.9% of the total variabilityin May and November 2004 respectively.The analysis, therefore,only considered these two axes to highlight the relation betweendescriptors along a spatial distribution of samples. In May, thetwo dissolved nutrients (NO3-N and NH4-N) were opposed to allother variables on the second axis. Bacterial variables (T-BACT,C-BACT, TTC and FS) were linked to PO4-P concentrations, aswas also demonstrated by the significant correlations betweenthem (Table 3). The abundance of the total phytoplankton (T-PHYTO) was linked to the Bacillariophyceae (BACIL) and thesetwo variables were opposed to the nutrient concentrations. HNF


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C5

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L3

L4

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L6

C11

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C3

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�10 µM �1 µM �0.1 µM �100 µM �10 µM �1 µM

�100 000 �10 000 �1000 �100�1000 �100

�50 �10 �5 �1�5 �1

C2

C3

C4

C5

C6

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O3

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C1 O3

O2

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L2 L3

L4

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L5

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C8

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C5

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C3

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C5

C6

C7 C8

L4

C9

C10

L6

C11

L1

O1

O2O3

L2

L3

May 2004 November 2004

NH4NH4

chlorophyll chlorophyll

TTCTTC

L4L5

L6

C11

Fig. 2. Distribution of ammonia concentrations, thermo-tolerant coliforms thermo-tolerant coliforms (TTC) (expressed in colony forming units; CFU100 mL−1) and total phytoplankton abundances (expressed in equivalent chlorophyll a) in May and November 2004.


Total coliforms (CFU 100 mL�1)

100

106

105

104

103

102

Fae

cal s

trep

toco

cci (

CF

U 1

00 m

L�1 )

101

100

10�1

101 102

May 2004

November 2004

103 104 105 106

Fig. 3. Thermo-tolerant coliforms (TTC) v. faecal streptococci in May andNovember 2004. Horizontal and vertical lines are European Union standardsfor bathing waters.

Table 3. Bravais Pearsons correlation coefficients between the 13 chemical and biological variables studied during the two surveys, May andNovember 2004

Significant values are given in bold (∗P < 0.05; ∗∗P < 0.01). T-BACT, total bacteria; C-BACT, culturable bacteria; TTC, thermo-tolerant coliforms; FS, faecalstreptococci; HNF, heterotrophic nanoflagellates; CHLOR, Chlorophyceae; CYANO, Cyanobacteria; BACIL, Bacillariophyceae; CRYPT, Cryptophyceae;

T-PHYTO, total phytoplankton

May 2004

PO4 NH4 NO3 T-BACT C-BACT TTC FS HNF CHLOR CYANO BACIL CRYPT T-PHYTO

PO4 1.000 0.042 0.127 0.409 0.624∗ 0.656∗ 0.676∗ 0.398 0.323 0.500 0.321 −0.053 0.397NH4 1.000 0.602∗ 0.016 0.173 0.193 0.296 0.082 −0.081 0.132 −0.064 0.030 −0.028NO3 1.000 0.276 0.144 0.146 0.237 0.114 −0.276 0.264 −0.015 0.247 0.018T-BACT 1.000 0.759∗ 0.774∗ 0.770∗ 0.490 0.139 0.533∗ 0.496 0.228 0.549∗C-BACT 1.000 0.907∗∗ 0.868∗ 0.512 0.296 0.749∗ 0.493 0.312 0.605∗TTC 1.000 0.890∗∗ 0.462 0.431 0.780∗ 0.518 0.297 0.664∗FS 1.000 0.503 0.417 0.691∗ 0.495 0.250 0.604∗HNF 1.000 0.014 0.463 0.651∗ 0.052 0.634∗CHLOR 1.000 0.383 0.025 0.113 0.204CYANO 1.000 0.636∗ 0.473 0.785∗BACIL 1.000 0.091 0.964∗∗CRYPT 1.000 0.259T-PHYTO 1.000

November 2004

PO4 NH4 NO3 T-BACT C-BACT TTC FS HNF CHLOR CYANO BACIL CRYPT T-PHYTO

PO4 1.000 0.459 0.833∗ 0.409 0.295 0.338 0.059 0.299 −0.454 0.412 0.565∗ −0.618∗ 0.567∗NH4 1.000 0.421 0.612∗ 0.567∗ 0.559∗ 0.370 0.420 −0.351 0.454 0.427 −0.566∗ 0.461NO3 1.000 0.390 0.328 0.244 −0.038 0.521 −0.349 0.644∗ 0.763∗ −0.556∗ 0.758∗T-BACT 1.000 0.926∗∗ 0.797∗ 0.719∗ 0.364 −0.204 0.737∗ 0.483 −0.465 0.548∗C-BACT 1.000 0.812∗ 0.784∗ 0.433 −0.044 0.672∗ 0.385 −0.367 0.454TTC 1.000 0.793∗ 0.153 0.094 0.531 0.234 −0.232 0.303FS 1.000 0.119 0.128 0.495 0.137 −0.084 0.205HNF 1.000 −0.225 0.494 0.504 −0.506 0.517CHLOR 1.000 −0.314 −0.450 0.409 −0.441CYANO 1.000 0.872∗∗ −0.397 0.911∗∗BACIL 1.000 −0.558 0.995∗∗CRYPT 1.000 −0.537T-PHYTO 1.000

abundances were linked to the phytoplankton (T-PHYTO) andnot to the bacteria.

In November, the presence of HNF appeared to be unrelatedto the bacterial variables on the second axis. Bacterial variables(T-BACT, C-BACT, TTC and FS) were linked to NH4-N con-centrations as also demonstrated by the significant correlationsbetween them (Table 3). Total phytoplankton (T-PHYTO) waslinked to Bacillariophyceae (BACIL). However, contrary to thesituation described in May, the development of phytoplanktonseemed to be linked in November to the high concentrationsof nitrate and orthophosphate. Chlorophyceae (CHLOR) andCryptophyceae (CRYPT) were opposed to other phytoplanktongroups on the first axis.

For both sets of measurements, the positions for each sta-tion were distinctly different on the first axis, depending onthe location in the Bay (intermediate and seaward stations v.near shore stations) and the type of discharge. In May, stationsN6 and N11 were characterised by high nutrient concentrationslinked to the direct industrial effluent (Fig. 4). Station N1 located


3(a)

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C8

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C7

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O1

C1

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2 4 6

�5�6 �4 �2 0 2

Axis 1 (62.8%)

November 2004

May 2004

4 6

Fig. 4. Principal component analysis (PCA) on thetwo first axes in May and November 2004. Eigenval-ues for each axis of the PCA are reported. Stations areidentified as in Table 1. See Discussion section for thedifferentiation of the groups of parameters studied.

near the harbour was characterised by high algal concentrations,explaining its special position on the second axis. The other nearshore stations (N2 to N9) were characterised by high concen-trations of FIB (TTC and FS) linked directly to diffuse urbansewage. In November, the distribution of the stations by transectwas less distinctive. However, station N3 was always associatedwith high concentrations of FIB, C-BACT and T-BACT, whereasthe positions of the stations N8, N10 and N11 were explainedby the presence of dissolved nutrients and a high concentra-tion of phytoplankton. Finally, the highest values for chemicaland microbial parameters were all associated with the near shore

stations, except for the two minor phytoplankton groups (CRYPTand CHLOR).These two groups characterised the phytoplanktonin November at the seaward stations (S1 and S2).

For the two sets of measurements, hierarchical classificationdifferentiated four clusters with 85% similarity (Fig. 5). The pre-dominant cluster (A in Fig. 5) was formed by 12 stations sampledin November and included mainly the intermediate and seawardstations. The second cluster (B) was formed by nine stationsin May only and included only intermediate and seaward sta-tions. The two other clusters (C and D) included almost all nearshore stations sampled in November and May, reflecting both


N1N2

N3

N4

N5

N6

N7N8

N9

N10N11

I1I2I3

I4

I5I6

S1S2S3

N1-N

N2-N

N3-N

N4-N

N5-N

N6-N

N7-N

N8-N

N9-N

N10-NN11-N

I1-NI2-N

I3-N

I4-NI5-N

I6-NS1-N

S2-NS3-N

0 10025 50 75Linkage distance

A

B

C

D

Fig. 5. Hierarchical classification showing similarityamong sampling stations based on the 13 parameters stud-ied. Stations sampled in November are noted with –N,the others sampled in May. Cluster A includes all of theintermediate and seaward stations sampled in November.Cluster B only includes intermediate and seaward stationssampled in May. Clusters C and D include almost all nearshore stations (except 3) sampled in May and Novem-ber without great differentiation. Broken line delimits thelinkage distance to define an optimised number of clusters.

the continuous and diffuse characteristics of the urban and indus-trial effluent. These results confirmed the difference between thenear shore environment and that of the intermediate and seawardstations.

DiscussionDistribution of nutrients and FIB in Hann BayIn a regional study of the Gulf of Guinea, Sheren et al. (2002)concluded that the assessment of pollution sources revealedthat domestic sewage was the major contributor of solid waste,whereas industry discharged substantial amounts of hazardouswaste. Hann Bay has distinctive spatial and temporal patterns,characterised by chemical and microbial descriptors that fluc-tuate according to the sewage source and the distance from theoutfall. The increase in the abundance of FIB is one of mostfrequently reported effects of sewage discharge in marine water(Lucena et al. 2004). The major sewage source in Hann Bay

was identified in D1, explaining the highest TTC and FS con-centrations observed (especially in November) in the near shorearea between N1 and N3. This source was identified as a hugetank receiving urban sewage collected by trucks. Other sourceslocated in D3 were the sewer of an industrial dyeing facility,carrying a mixture of dissolved nutrients (PO4-P and NH4-N)and FIB to the shoreline. Other sources of contamination werea chemical plant (ammonia factory) and a refinery (near D6)which explained the high ammonia concentrations measuredat the near shore stations N10 and N11. The phosphate andnitrogen enrichment noted at the near shore stations was, there-fore, associated with both urban (D1 and D3) and industrialdischarges (D6).

The ratio of total coliforms/faecal coliforms (TC/FC) hasbeen proposed as an index to assess the origin of faecal con-tamination (Jagals et al. 1995; Haile et al. 1999). In the lastfew years, total coliforms have been replaced by thermo-tolerantcoliforms (more tolerant to temperature) as criteria; thus, in thepresent study we discussed the ratio of TTC to FS. According


to Gleeson and Gray (1997), enterococci are more resistant thancoliforms when submitted to severe environmental conditionsand can survive longer in water, thus revealing longstandingfaecal contamination. On the other hand, a low ratio of TTC/FScan also mean that stations are subject to continuous contam-ination (Haile et al. 1999). In the present study, near shorestations had lower ratios (mean of 1.9 and 3.9 respectively inMay and November) associated with the type of source (D1and D3) that were typical of urban sewage discharge. FS sur-vival was also noticed at the seaward stations (∼2.5 km fromthe coastline), with a TTC/FS ratio of 2.8 and 10.6 in May andNovember respectively. These high enterococci survival ratesconfirm the results obtained in the Senegal River Estuary withresults showing: (1) high concentrations of FIB attributed tohuman activities; and (2) high survival rates of FIB in coastalseawater (Troussellier et al. 2004).

The pollution plume was generally localised in a relativelynarrow zone in the vicinity of the main sewage outfalls (D1, D3and D6). The topography of the coast at Dakar, with the Cap VertPeninsula as illustrated in Fig. 1, plays a major role in the localhydrodynamics and currents. Hann Bay can therefore be consid-ered as a semi-isolated bay with a general hydrodynamism fromsouth to north. The pollution plume generally moved northwardin the bay explaining, for example, the presence of FIB fromD1 at the near shore stations N1 and N2 relatively distant fromany outfall. Although there were no direct flows from the landnearby, stations N1 and N2 were polluted by the sewage fromstation N3 owing to the local water circulation in Hann Bay.This local hydrodynamism may also explain the presence of FIBat seaward stations, given that FIB can activate several survivalstrategies including starvation and tolerance to a large rangein salinity (Pommepuy et al. 1992; Troussellier et al. 2004).Multiple stresses (light, temperature, nutrient, salinity) favourthe activation/inactivation of the viability state and the loss ofcultivability (Colwell 2000). Despite the unfavourable environ-mental conditions encountered in Hann Bay (high salinity, highdirect illumination), FIB concentrations remain relatively highat the seaward stations (average: 641 CFU 100 mL−1 of TTC inNovember). This suggests a large potential source of FIB con-tamination with an input from sewage discharges high enoughto overcome dilution effects. The data presented here showedthat the dilution and the mortality processes are not sufficientlyimportant to avoid the presence of FIB in the seaward stations.These observations corroborate previous studies demonstratingthe presence of FIB in the Senegal River Estuary, far from thesewage source (Troussellier et al. 2004).

Standards and recommended guidelines based on indicatorssuch as bacteria concentrations have been drawn up to preventthe public being exposed to pathogenic enteric microorgan-isms. There are no guidelines and water directives in Senegalfor bathing waters and thus we have applied the values indi-cated in the EU directive. The results obtained in the presentstudy show that most samples failed to comply with the guide-line value of 500 CFU 100 mL−1 for TTC (imperative value of2000 CFU 100 mL−1) and 100 CFU 100 mL−1 for FS defined inthe European Union bathing water quality directive 76/160/EEC.However, the temporal and spatial patterns of FIB concentrationsfluctuated considerably in Hann Bay owing to the local hydro-dynamics that may have altered the pattern of horizontal and

vertical dispersion from the discharges. Physical forces such astides, wind and currents are probably of major importance inthe distribution of enteric bacteria (FIB), with a pollution plumeoften reaching other stations not linked to a discharge source butlying along the trajectory of the current.

Regulation of autochthonous microbial componentsThe present study also estimated the relative importance ofcontinental sewage discharges as sources of variability of theabundance of bacteria, HNF and phytoplankton. The statisticalanalysis showed that: (1) the highest abundances of microbialcommunities were observed along the shoreline; (2) the pres-ence of HNF appeared to be disconnected from the bacterialcommunities; (3) the phytoplankton community was mainlydominated by Bacillariophyceae and second by Cyanobacteria;and (4) the bacterioplankton seemed to be linked to phytoplank-ton in colder water in May but not obviously linked in warmerwater in November.

In marine environments, substrate availability and water tem-perature are considered to be important factors that regulatebacterial production (Pomeroy and Wiebe 2001). Several studieshave demonstrated that bacteria acquire a significant fraction oftheir N and/or P by uptake of inorganic forms and it is generallyassumed that the growth of marine bacterioplankton is limited bythe availability of inorganic phosphorus (Thingstad et al. 1998).Extracellular degradation and nutrient uptake profiles are closelyrelated to the quality and size of pool of dissolved organic carbon(Taylor et al. 2003). In the present study, bacterial distributionand orthophosphate concentration appeared to be correlated atthe near shore stations in May and with ammonia in November.As for the FIB and the total bacterial abundances, the abundanceof culturable heterotrophic bacteria increased in the vicinity ofthe outfalls. This may result from the direct urban discharge ofheterotrophic bacteria and the stimulation of the autochthonousmarine community by the release of sewage-derived organic sub-strates, as demonstrated by Cunha and Almeida (2006) in thecoastal region off Aveiro (north-west Portugal). In Hann Bay, thesource D1, identified as urban sewage, discharged water that washighly contaminated by FIB and ammonia (Fig. 2), explainingthe highest culturable heterotrophic bacteria values recorded inthe area (C-BACT), as reported by Cunha and Almeida (2006).However, bacterial dynamics also change relatively quickly inresponse to the growth and decay of different components ofthe phytoplankton community, indicating that dissolved organicmatter exuded from different algae may be selected by differentbacteria (Pinhassi et al. 2004). It may be possible to establisha causal relationship between the bacterial and phytoplanktonabundances in cold waters in May as an indication of strongbottom-up control over bacterial growth through substrate sup-ply (Cole et al. 1988). Additional nutrients may originate fromallochthonous sources such as sewage discharges. Despite thedifference in the in situ temperature in May and November(6–7◦C), no significant difference in total bacteria and FIB con-centrations was observed at the near shore stations in the two setsof measurements. It may, therefore, be argued that the major reg-ulator of bacterial distribution, especially at near shore stationsin Hann Bay, may be substrate supply rather than temperature.Pradeep Ram et al. (2003) reported that the variation in bacterial


growth efficiency was regulated by the quality of the substrates intropical coastal waters. At the oceanic scale, Rivkin and Legen-dre (2001) demonstrated that temperature alone explained 54%of the variation in bacterial growth efficiency and unexplainedvariance could be a result of seasonal differences in the qualityand quantity of organic substrates.

There was no obvious coupling in either set of measurementsbetween HNF and bacterial variables, although HNF are the mostimportant bacterivorous protozoa in most aquatic environments(Sanders et al. 1992). The present study produced insufficientdata to determine the relationship between these two componentsbut bacterial growth, especially at the near shore stations, appearsto be bottom-up regulated in Hann Bay, considered as a nutrient-rich environment. Using empirical and experimental approaches,Gasol et al. (2002) demonstrated that bacterial growth wasregulated by top-down factors in the most nutrient-poor environ-ments and bottom-up factors in the nutrient-rich ones. Bacterialdynamics may also be regulated by viruses (Fuhrman 1999; Sut-tle 2005). In Hann Bay, viruses were reported to contribute tobetween 4 and 67% of bacteria mortality and may therefore bea promising means for controlling planktonic prokaryotes here(Bettarel, pers. comm.).

Traditionally, phytoplankton is in direct competition withbacterioplankton for the growth limiting nutrients (Caron et al.2000) and numerous studies on nutrient limitation of such com-munities have shown that bacteria outcompete phytoplanktonfor the uptake of dissolved inorganic P and N in marine waters(Kirchman 1994; Torreton et al. 2000). The phytoplankton com-munity of Hann Bay is overwhelmingly dominated by diatoms(especially Leptocylindrus danicus and Thalassiosira sp.) inall stations, the second largest community being Cyanobacte-ria (Synechoccocus sp.) (M. Bouvy, unpubl. data). The coastalenvironment and upwelling support the empirically-based prin-ciple that diatoms respond rapidly to episodic high-light andhigh-nutrient conditions (Cloern and Dufford 2005). It is recog-nised that diatoms are best able to exploit these conditions forfast population growth. However, picocyanobacteria (in this casemainly Synechococcus sp.) representing the Cyanobacteria in thepresent study are persistent and ubiquitous across large habi-tat gradients and can be defined as generalists in relation tomixing, light availability, salinity and temperature (Cloern andDufford 2005). The dynamics of these small cells result fromtight coupling between their production and consumption byfast-responding protists (Murrell and Hollibaugh 1998). How-ever, the Cyanobacteria abundance did not seem to be linked tothe HNF concentration in the Hann Bay whatever the environ-mental conditions (Table 3). There were few Cryptophyceae anddinoflagellates (mixotrophic species belonging to Protoperi-dinium and Ceratium) among the total phytoplankton in HannBay (Table 2). Little is known about the capacity of mixotrophsto acquire energy by heterotrophy, but this phytoplankton cantap the nutrient pool in the microbial biomass (Cloern and Duf-ford 2005). However, this algal group merits further attention inthe Bay since it may exploit the anthropogenic nutrient enrich-ment of coastal waters to create algal blooms with some harmfulspecies able to produce toxins and disrupt food webs (Paerl et al.2002).

Sewage discharges had a marked effect on chemical and bio-chemical processes in the near shore ecosystem and far less effect

in the seaward system. The near shore environment showed sim-ilar microbial processes in May and November (clusters C andD) whereas intermediate and seaward environment were char-acterised by distinct microbial patterns in November and May(clusters A and B respectively). Within the Bay, the distributionof FIB, total bacteria and orthophosphate concentrations werenot statistically different in the two sets of measurements, lead-ing to the conclusion that water quality of coastal waters maybe continuously affected by persistent local contamination fromurban and industrial sewers. Anthropogenic nutrient enrichmentcan interact with grazing pressure to cause even greater changesin phytoplankton communities. Hydrodynamics and physicalforcing by tides, currents and wind may be of major impor-tance in the distribution of FIB and nutrients, as demonstratedby Bordalo (2003). This author reported that the periodicity offaecal indicators in raw sewage, the tidal status and wind condi-tions dramatically influenced the water quality in urban coastalbeaches.

The deterioration of water quality caused by diffuse bacterial(e.g. FIB) and chemical material from urban sources affect thecoastal areas that can be important resources in terms of eco-logical, economic and recreational value (WHO 1998). In thiscontext, an interesting point to further explore is the good sur-vival of enteric bacteria in coastal waters, as already reported inSenegalese estuarine waters (Troussellier et al. 2004). It may beinteresting to study what are the factors that could influence andexplain the extended survival of these enterobacteria in coastalwaters. Such information may be helpful if the authorities wantto propose to limit the degradation of the sanitary conditions inSenegalese coastal waters knowing that African coastal waterssupport fisheries that are essential protein resources for manyAfrican countries (UNEP 1999).

AcknowledgementsThis work is a contribution to the program of IRD Research Unit 167. Wethank François Sanséo for the sea sampling, and Daniel Corbin for chem-ical analysis. The present study is part of the Aurélie Lemeur’s researchsupervised by M.B. We are grateful to the Editor and two reviewers for theircriticisms and constructive comments.

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Manuscript received 18 December 2007, accepted 13 May 2008

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