Petroleum contamination impact on macrobenthic communities under the influence of an oil refinery: Integrating chemical and biological multivariate data

Available online at www.sciencedirect.com

Estuarine, Coastal and Shelf Science 78 (2008) 457e467 www.elsevier.com/locate/ecss

Petroleum contamination impact on macrobenthic communities under the influence of an oil refinery: Integrating chemical and biological multivariate data Natalia Venturini a,*, Pablo Muniz b, Ma´rcia C. Bı´cego a, Ce´sar C. Martins a,d, Luiz Roberto Tommasi c a

Instituto Oceanogra´fico da Universidade de S~ao Paulo (IOUSP), Prac¸a do Oceanogra´fico 191, Cidade Universita´ria, 05508-900 S~ao Paulo, SP, Brazil b Seccio´n Oceanologı´a, Departamento de Ecologı´a, Facultad de Ciencias, Igua´ 4225, 11400 Montevideo, Uruguay c Fundac¸~ao de Estudos e Pesquisas Aqua´ticas (FUNDESPA), Av. Afraˆnio Peixoto 412, 05507-000 S~ao Paulo, SP, Brazil d Centro de Estudos do Mar da Universidade Federal do Parana´ (UFPR), Caixa Postal 50.002, Pontal do Sul, 83255-000, Pontal do Parana´, PR, Brazil Received 1 February 2006; accepted 18 January 2008 Available online 1 February 2008

Abstract Petroleum contamination impact on macrobenthic communities in the northeast portion of Todos os Santos Bay was assessed combining in multivariate analyses, chemical parameters such as aliphatic and polycyclic aromatic hydrocarbon indices and concentration ratios with benthic ecological parameters. Sediment samples were taken in August 2000 with a 0.05 m2 van Veen grab at 28 sampling locations. The predominance of n-alkanes with more than 24 carbons, together with CPI values close to one, and the fact that most of the stations showed UCM/resolved aliphatic hydrocarbons ratios (UCM:R) higher than two, indicated a high degree of anthropogenic contribution, the presence of terrestrial plant detritus, petroleum products and evidence of chronic oil pollution. The indices used to determine the origin of PAH indicated the occurrence of a petrogenic contribution. A pyrolytic contribution constituted mainly by fossil fuel combustion derived PAH was also observed. The results of the stepwise multiple regression analysis performed with chemical data and benthic ecological descriptors demonstrated that not only total PAH concentrations but also specific concentration ratios or indices such as C24:
1. Introduction Coastal areas are directly subjected to anthropogenic impacts mainly derived from industrial and urban activities. Although * Corresponding author. E-mail address: [email protected] (N. Venturini). 0272-7714/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.ecss.2008.01.008

hydrocarbons presence in the marine environment can originate from natural sources such as forest fires, natural petroleum seeps and post-depositional transformations of biogenic precursors, a large proportion can be attributed to human activities. Urban runoff, sewage disposal, industrial effluents, oil production and transportation are some of the most important sources of anthropogenic hydrocarbons (Kim et al., 1999).

458

N. Venturini et al. / Estuarine, Coastal and Shelf Science 78 (2008) 457e467

Particularly, polycyclic aromatic hydrocarbons (PAH) are a ubiquitous category of pollutants, which are rarely found as biosynthetic products and have a high toxicity for organisms due to their carcinogenic and mutagenic potential (UNEP, 1991). PAH derive mainly from anthropogenic sources such as the combustion of fossil fuels and the direct release of oil and oil products, with a smaller contribution from forest fires and agricultural burn-off (Law and Biscaya, 1994). Once they entered in the marine environment, oil-derived hydrocarbons tend to adsorb on to particulate material and deposit in the sediments, where they can accumulate to high concentrations and persist for many years, mainly under anoxic conditions (Readman et al., 2002). Petroleum is one of the most world-wide spread contaminants and its components can produce adverse effects at different levels of biological organisation. Moreover, severe petroleum introduction causes changes to the structure of benthic communities, which are necessary to study and quantify in order to evaluate the effects of contaminants on a particular ecosystem (Heip, 1992). Many chemical studies on both aliphatic and polycyclic aromatic hydrocarbon levels, distribution and probable sources have been conducted in different areas around the world (e.g., Kim et al., 1999; Commendatore et al., 2000; Nishigima et al., 2001; Notar et al., 2001; Yunker et al., 2002). Chemical parameters such as indices, ratios and the occurrence of certain compounds can be used to establish levels of pollution, discriminate between biogenic or anthropogenic inputs and estimate the risk of harmful effects of hydrocarbons on benthic communities (Long et al., 1995; Commendatore et al., 2000; Hyland et al., 2000). Due to their low mobility, benthic organisms integrate the effects of contaminants over time; therefore, they have been extensively used in marine pollution monitoring programmes. Furthermore, trying to explain the effects of different types of contaminants on macrobenthic communities, total hydrocarbon concentrations are usually included in wide environmental data sets, and together with biological matrices, subjected to multivariate analyses (Rakocinski et al., 2000; Belan, 2003; Venturini et al., 2004; Muniz et al., 2005). Nevertheless, there are still few studies in coastal areas of South America that had performed an integrative analysis of chemical parameters and biological multivariate data. Previously, Guerra-Garcı´a et al. (2003) used indices and concentration ratios in multivariate analyses to assess hydrocarbon pollution effects on macrobenthic assemblages, focusing only on aliphatic hydrocarbons. Todos os Santos Bay with an area of approximately 927 km2 is the largest embayment on the Brazilian coast. Since 1950, the area around Todos os Santos Bay has been under the influence of increasing industrialisation and exploitation of its natural resources (GDB, 2000). Nowadays, effluents from 29 industries drain into the bay and are responsible, together with urban and port activities, for considerable pollution problems. An oil refinery of the PETROBRAS Brazilian Company (Landulhpo Alves-Mataripe Refinery; RLAM) is located adjacent to the northeast portion of Todos os Santos Bay, and the resultant effluents are discharged into the bay. Petroleum extraction, transportation and refining

activities have been carried out in this area for more than 40 years. Venturini and Tommasi (2004) reported the occurrence of petrogenic contamination with a pyrolytic input in sediments of Todos os Santos Bay. In addition, they detected functional changes in polychaete assemblages related to PAH concentrations in this area. The aim of this work was to evaluate petroleum contamination impact on macrobenthic communities in the northeast portion of Todos os Santos Bay, combining chemical parameters (aliphatic and polycyclic aromatic hydrocarbon indices and concentration ratios) with benthic ecological parameters (macrofauna abundance, number of species and diversity) in multivariate analyses. 2. Study area Todos os Santos Bay is a broad depositional marine system that gets deeper through its centre and presents a strait at the mouth between Itaparica Island and Salvador City (Fig. 1). Water circulation within Todos os Santos Bay is mainly controlled by the semidiurnal tides, with high tidal currents flowing towards north-northeast (NNE) and low tidal currents towards south-southwest (SSW) (GDB, 2000). This region is influenced by tropical climate with a well defined rainy season from April to June. During summer, predominant winds are from the SE, whereas during winter they blow predominantly from the NE (Ponce and Correa, 1980). The study area is located between 12 420 e12 450 S and 38 320 e38 360 W in the northeast portion of Todos os Santos Bay (Fig. 1). It is a shallow area with depth varying from 0.6 to 10 m. Besides the discharge of the oil refinery effluents, three rivers flow into the northeast portion of Todos os Santos Bay, the Caı´pe River, the Mataripe River and the S~ao Paulo River. All of them run through zones with mangrove vegetation and carry wastes from several industries and urban centres (GDB, 2000). 3. Materials and methods Sediment samples were taken in August 2000 with a 0.05 m2 van Veen grab at 28 sampling locations (Fig. 1). Top centimetres (0e2 cm depth) were taken from the grabs for hydrocarbon analysis. Samples were kept frozen (15  C) in aluminium containers. After drying in an oven at 50  C until constant weight, 25 g of each sediment sample were Soxhlet extracted during 8 h with a 50% mixture of hexane and dichloromethane according to UNEP (1991). The sample extracts and blanks were spiked with a surrogate recovery standard mixture (SUPELCO), consisting of naphthalene-d8, acenaphthene-d10, phenanthrene-d10, chrysene-d12, and perylene-d12 for PAH and hexadecane and eicosene for aliphatic hydrocarbons, prior to solvent extraction. Recoveries of surrogates ranged from 64.8% to 104.0% (PAH) and from 76.3% to 101.4% (aliphatic hydrocarbons) of the spiked concentration. Concentrations of all analytes were corrected for surrogate recoveries. The extracts were concentrated using a rotary evaporator, desulphurised with activated cooper and

N. Venturini et al. / Estuarine, Coastal and Shelf Science 78 (2008) 457e467

459

BRAZIL BAHIA

PACIFIC OCEAN

TODOS OS SANTOS BAY

ATLANTIC OCEAN

nd

Salvador

sla

aI

c ari

p

Ita

ATLANTIC OCEAN

38°36'

38°32' N W

MATARIPE RIVER

CAIPE RIVER

RLAM ETDI S

1

6 7

8

9 10

15 14

13

12

MADRE DE DEUS ISLAND

16

11

22

12°42'

5

4

3

2

E

SÃO PAULO S RIVER

21

20

TEMADRE

19

18

17 26 25 24

27 28

23

1 km

MARÉ ISLAND 12°45'

Fig. 1. Map of the northeast portion of Todos os Santos Bay, showing the 28 sampling locations. RLAM, oil refinery; S, water-oil separator; ETDI, effluent treatment station; TEMADRE, marine terminal.

fractionated by silicaealumina gel chromatography into aliphatic and aromatic hydrocarbons. Aliphatic fractions were determined by injecting 2 ml of the concentrated extracts into a HP 5890A Series II gas chromatograph (GC) with a flame ionisation detector (FID). Aromatic fractions were determined by injecting 1 ml of the concentrated extracts on a Fisons Trio 1000 GC, with a mass spectrometry (MS) detector, and detection operated under the SIM (selected ion monitoring) mode. The instrument detection limit was based on the lowest concentration of a calibration standard mixture and it was 0.01 ng g1 for CG-MS and 0.10 ng g1 for CG-FID. The capillary column used was a HP Ultra II (25 m long, 0.32 mm i.d., 0.25 mm film thickness) programmed from 40e60  C at 20  C min1, 60e 300  C at 4  C min1 and held at 300  C for 10 min. The analytical program was conducted under controlled laboratory conditions, following a laboratory quality assurance protocol. In order to evaluate the accuracy and the precision of the analysis two replicates of the National Institute of Standards (NIST) standard reference sediment SRM 1941a (Organics in Marine Sediment) were analysed. The average concentrations agreed with the certified concentrations for all compounds analysed. The relative standard deviation (RSD) of

the replicates ranged from 0.3% to 12.8%. For aliphatic hydrocarbons, regular analyses of reference material from the International Atomic Energy Agency (IAEA-383) gave satisfactory results. The average concentrations agreed with the available certified concentrations for selected compounds (n-C17, n-C18, pristine, phytane), total n-alkanes and resolved aliphatics. The RSD of the two replicates ranged from 9.4% to 24.6%. Detection limits (DL) in sediments ranged between 0.31 and 1.23 ng g1 dry weight for PAH analytes and between 0.10 and 7.41 ng g1 for n-alkanes and isoprenoids. They were calculated as three times the mean concentration of method blanks for each PAH (Citac/Eurachem Guide, 2002). Since natural samples consist of complex hydrocarbon mixtures, several parameters in addition to absolute concentrations were used as distinct tracers to identify possible sources of aliphatic and aromatic hydrocarbons in sediments. Faunal samples were also taken using a 0.05 m2 van Veen grab. Three replicate (pooled) samples were taken at each station; the material was sieved on a 0.5 mm mesh and preserved in 4% buffered formaldehyde. Benthic organisms from sediments were sorted, identified to the lowest possible taxonomic level and counted. Most taxa were identified to the species level.

N. Venturini et al. / Estuarine, Coastal and Shelf Science 78 (2008) 457e467

460

A correlation-based PCA ordination was performed using the computer software PRIMER (Clarke and Warwick, 1994) to identify any meaningful pattern from the samples in relation to the percentage of fine sediments (silt þ clay), total hydrocarbon concentrations and chemical parameters. To avoid the problem of comparing variables with different units, and therefore, with different scales of variation, data were previously standardised (xi  m/s) (Zar, 1996). Density was estimated as the total number of individuals (N ) per unit area (0.15 m2) and species richness as the total number of species (S ). Diversity (H0 , loge) was estimated by the Shannone Wiener index (Shannon and Weaver, 1963) and evenness (J0 ) according to Pielou (1966). In order to determine which of the chemical parameters used explained best the variation in community descriptors (S, density and H0 ), a stepwise multiple regression analysis was applied using the computer programme STATISTICAÒ (StatSoft Inc, 1995). This analysis compares the relative importance of the independent variables (chemical ones) in explaining the variance of the dependent variables (biological ones); through the construction of a multilinear model (Zar, 1996). The relationship between multivariate environmental data and biological data (species abundance matrix) was achieved applying the BIO-ENV procedure

(Clarke and Ainsworth, 1993). The best matches of abiotic and biotic (dis)similarity matrices were measured using the weighted Spearman rank correlation coefficient (rw). Macrofauna species abundance data were previously four-root transformed and the BrayeCurtis similarity measurements used for the construction of the biotic matrix. A one-way analysis of similarities (ANOSIM) was performed to test the differences in macrobenthic species abundance among the groups of stations obtained in the PCA (Clarke and Green, 1988). To establish which species contributed the most to differences observed among groups, the similarity percentages analysis (SIMPER) was applied. 4. Results 4.1. Aliphatic and aromatic hydrocarbons Mean concentration of total aliphatic hydrocarbons within the study area was 34.90 mg g1 dry weight. Lowest concentrations were recorded at stations 1 and 2 (1.56 and 1.76 mg g1, respectively) and highest values at stations 9 and 12 (236.42 and 246.91 mg g1, respectively) (Table 1). Total n-alkanes varied from 0.86 to 39.94 mg g1 with a predominance of n-alkanes with more than 24 carbons as indicated by

Table 1 Percentage of fine sediments (<0.63 mm), concentrations and values of the evaluation indices applied to aliphatic and aromatic hydrocarbons detected in sediment samples of Todos os Santos Bay. Aliph, total aliphatic hydrocarbons; n-alk, total n-alkanes; UCM, unresolved complex mixture; R, resolved aliphatics; UCM:R, unresolved complex mixture/resolved aliphatic hydrocarbons ratio; alkanes 3n-C24:
Silt þ clay (%)

Aliph (mg g1)

n-alk (mg g1)

UCM (mg g1)

R (mg g1)

UCM:R

C24:
CPI

PAH (ng g1)

An/178

Fl/FlþPy

IP/IPþBghiP

LMW/HMW

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

0.10 4.20 0.20 9.10 91.60 92.40 22.30 89.60 91.20 0.20 93.20 91.70 95.70 94.60 0.10 89.60 0.20 93.60 98.40 96.60 93.00 0.10 10.80 0.10 92.50 79.40 85.20 9.50

1.76 1.56 48.14 43.89 199.36 112.74 56.34 75.82 236.42 25.96 41.95 246.91 37.99 112.79 70.15 163.15 38.77 68.46 39.25 43.32 50.17 5.15 24.01 2.93 23.78 113.88 75.97 34.90

0.86 1.15 2.74 6.42 14.12 8.04 6.35 2.46 6.82 1.73 1.57 5.83 5.33 5.93 8.65 8.15 5.22 7.93 5.47 6.05 9.63 3.16 1.14 1.38 15.17 39.94 3.78 1.93

n.d. n.d. 40.05 35.72 119.70 93.68 40.32 50.96 131.67 22.97 36.96 189.01 18.31 55.22 67.67 143.84 33.52 49.09 26.95 29.30 31.61 n.d. 21.43 n.d. 6.27 57.09 63.24 25.56

1.76 1.56 8.09 8.16 79.66 19.06 16.02 24.86 104.75 2.98 4.98 57.89 19.68 57.56 2.48 19.32 5.25 19.37 12.30 14.02 18.56 5.15 2.58 2.93 17.51 56.79 12.73 9.34

e e 4.95 4.38 1.50 4.92 2.52 2.05 1.26 7.71 7.42 3.26 0.93 0.96 27.29 7.45 6.38 2.53 2.19 2.09 1.70 e 8.31 e 0.36 1.01 4.97 2.74

1.25 0.75 0.50 1.59 1.46 2.56 1.09 1.76 1.67 1.07 1.21 1.21 3.01 1.80 1.40 12.48 2.66 1.17 1.13 1.23 0.60 1.05 0.25 0.11 11.42 8.37 5.99 1.41

1.03 1.17 0.91 0.76 0.62 1.60 2.01 1.54 1.80 e 1.70 0.63 0.91 1.26 0.77 3.22 1.06 0.89 0.65 1.41 0.60 e e e 0.19 2.65 1.93 3.21

310.00 304.50 18.30 107.50 4163.00 283.40 94.86 1355.00 293.40 11.56 38.56 727.10 779.90 1614.00 547.10 888.10 32.29 2969.00 403.50 381.50 523.80 149.30 22.51 8.29 1043.00 773.40 1470.00 685.90

e e e 0.16 0.80 0.22 0.35 0.84 0.64 e e 0.67 0.65 0.72 0.02 0.04 e 0.21 0.29 0.48 0.48 e e e 0.08 0.43 0.08 0.05

0.50 0.49 0.23 0.23 0.22 0.48 0.33 0.54 0.43 0.36 e 0.50 0.46 0.09 0.44 0.51 0.20 0.58 0.64 0.49 0.44 0.68 0.55 0.54 0.64 0.44 0.39 0.44

0.62 0.34 0.46 0.25 0.75 0.39 0.23 0.74 0.39 0.40 0.38 0.87 0.89 0.86 0.95 0.92 0.72 0.82 0.38 0.48 0.38 0.90 0.26 e 0.38 0.91 0.44 0.85

13.34 4.72 1.14 0.22 0.47 0.13 0.55 0.22 0.28 0.10 0.25 0.39 0.37 0.20 15.57 0.09 0.21 0.54 0.16 0.23 0.27 0.13 0.08 0.29 0.32 0.13 0.17 1.38

N. Venturini et al. / Estuarine, Coastal and Shelf Science 78 (2008) 457e467

the C24:
for the whole area was 899.58 ng g1. The lowest value was recorded at station 24 (8.29 ng g1) and the highest at station 5 (4163 ng g1), which is located adjacent to the effluent’s treatment station of the oil refinery (Table 1). Spatially, PAH concentrations were higher at the stations situated in the centre and in the east region of the study area than in the others (Fig. 2). The anthracene/anthracene þ phenantrene ratio (An/ 178) varied between 0.02 and 0.84, and only stations 15, 16, 25, 27 and 28 showed values <0.10 (Table 1). Stations 3, 4, 5, 7, 10, 14, 17 and 27 showed fluoranthene/fluoranthene þ pyrene ratios (Fl/Fl þ Py) <0.40, whereas the others showed values between 0.40e0.50 or >0.50 (Table 1). Values of the indeno[1,2,3-c,d]pyrene/ indeno[1,2,3-c,d]pyrene þ benzo [g,h,i]perylene ratio (IP/IP þ BghiP) were >0.50 at stations situated in the centre and in the east region of the study area. The others showed values between 0.20 and 0.50 (Table 1). Based on Yunker et al. (2002), the isomer pair ratios An/ 178 and IP/IP þ BghiP were plotted against Fl/Fl þ Py to show how PAH distribute in relation to their possible sources. According to these ratios most of the samples are influenced primarily by petroleum and petroleum combustion sources (Fig. 3). The ratio between the volatile PAH with two to three aromatic rings and the high molecular weight PAH with four to six aromatic rings (LMW/HMW) was <1 at all of the stations except 1, 2, 3, 15, and 28 (Table 1). 4.2. Community analysis

RLAM

A total of 543 individuals were recorded that belong to 55 macrobenthic species. Polychaeta was the most abundant

ETDI S

12

11

17

18

19

20

21

22

15

14

13

24

23

16 25

27 26 28

An/178

10

A

6

7

8

9

5

4

3

2

1

Total PAH RLAM

10

13

12

11 21

20

6

7

8

9

5

4

3

2

1

19

14 18 23

15 17 24

16 25

27 26 28

IP/IP + BghiP

S

B

ETDI

Petroleum Combustion

Petroleum 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

Grass/wood/coal Combustion

Combustion

Petroleum 0

22

461

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Grass/wood/coal Combustion

Petroleum Combustion Petroleum 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Fl/Fl + Py Fig. 2. Maps showing the spatial distribution of total aliphatic hydrocarbons (mg g1 dry weight) and total polycyclic aromatic hydrocarbons (PAH) (ng g1 dry weight) in the northeast portion of Todos os Santos Bay.

Fig. 3. Plots for the PAH isomer pair ratios of the 28 sediment samples of Todos os Santos Bay based on Yunker et al. (2002): (A) An/178 versus Fl/ Fl þ Py and B) IP/IP þ BghiP versus Fl/Fl þ Py.

N. Venturini et al. / Estuarine, Coastal and Shelf Science 78 (2008) 457e467

S

Density

H0

J0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

4 1 2 3 0 6 6 1 7 12 5 2 3 2 8 3 13 3 4 6 5 13 10 4 2 2 3 8

25 4 201 15 0 10 7 1 11 27 10 4 4 3 34 4 27 4 6 8 8 40 22 8 3 2 7 44

0.92 e 0.21 0.63 e 1.61 1.75 e 1.85 2.27 1.50 0.56 1.04 0.64 1.40 1.04 2.39 1.04 1.33 1.73 1.56 2.20 1.92 1.32 0.64 0.69 0.96 1.68

0.66 e 0.31 0.57 e 0.90 0.98 e 0.95 0.91 0.94 0.81 0.95 0.92 0.67 0.95 0.93 0.95 0.96 0.97 0.97 0.86 0.83 0.95 0.92 1.00 0.87 0.81

group with 73.84% of the individuals, following by Mollusca and Crustacea with 14.54% and 9.57%, respectively. Species richness according to the total number of species ranged from 0 at station 5 to 13 at station 22 (Table 2). The highest density values (ind. 0.15 m2) were recorded at stations 1, 3, 4, 10, 15, 17, 22, 23 and 28. At station 3 the high density was exclusively by the presence in great abundance of the polychaete Ophelina sp. Diversity ranged from 0.21 at station 3 to 2.39 at station 17 and evenness varied between 0.31 to 1 (Table 2). In general, low diversity values corresponded to the stations situated in the centre and in the east region of the study area. Evenness´ lowest values corresponded to stations 1, 3 and 4 and they were related to the dominance of the polychaete Ophelina sp. in the former stations and Goniada littorea in the latter. 4.3. Hydrocarbons and macrofauna, multivariate analyses The results of the stepwise multiple regression analysis are shown in Table 3. When the number of species (S ) was considered as the dependent variable, significant partial correlation coefficients ( p < 0.05) were obtained with total PAH concentrations, the C24:
b

Independent variables that entered the modela

Dependent variable: S (number of species) PAH L0.39 UCM:R 0.26  C24:
R

R2

0.73

0.53

Dependent variable: D (density) Silt D clay Fl/Fl þ Py

L0.44 0.18

0.49

0.24

Dependent variable H0 (diversity) PAH

L0.49

0.49

0.25

a

Abbreviations are the same as in Table 1.

was obtained with the percentage of fine sediments (silt þ clay). In this case, the multiple correlation coefficient and the multiple determination coefficient were R ¼ 0.49 and R2 ¼ 0.24, respectively. Furthermore, a significant partial correlation coefficient between diversity (H0 ) and total PAH concentrations was also obtained, with R ¼ 0.49 and R2 ¼ 0.25. The PCA ordination performed with the chemical data and the percentage of muddy sediments resulted in the formation of three groups of stations (Fig. 4). The first component (PC1) explained 37.3% of the variance and the second component (PC2) 14.9%. The first axis showed negative correlation with the percentage of fine sediments (silt þ clay), aliphatic hydrocarbons, n-alkanes, UCM, the An/178 ratio and PAH concentrations, whereas, the second axis showed positive correlation with the UCM/resolved aliphatic ratio and negative correlation with the Fl/Fl þ Py ratio (Table 4). In general, stations of groups I and II presented higher aliphatic, UCM PC2 (14.9 %)

St.

Table 3 Results of the stepwise multiple regression analysis. Significant partial correlation coefficients ( p < 0.05) (b) are in bold. b, partial correlation coefficient; R, multiple correlation coefficient; R2, multiple determination coefficient

-

+

III 15 I

+ UCM:Resolved aliphatics

Table 2 Total number of species (S ), density (ind. 0.15 m2), diversity (H0 loge) and Pielou’s evenness (J0 ) of the 28 samples of Todos os Santos Bay

Fl/Fl+Py

462

16 II

12 9 26 14 5

11

6

28 7

27 20 18 8 13 21

17 3 4

10 23 1 2 22

24

19 25

+

-

PC1 (37.3 %)

Silt+clay, aliphatics, n-alkanes, UCM, An/178, PAH

Fig. 4. PCA ordination diagram of the 28 sampling stations of Todos os Santos Bay based on chemical data and the percentage of muddy sediments.

N. Venturini et al. / Estuarine, Coastal and Shelf Science 78 (2008) 457e467 Table 4 Results of the principal component analysis (PCA) performed with chemical data of the 28 sediment samples of Todos os Santos Bay Eigenvalues PC1 PC2

3.73 1.49

%Variation

Cum. % Variation

37.3 14.9

37.3 52.2

Eigenvectors PC1

PC2

Silt þ clay Aliph n-alk UCM CPI UCM:R PAH An/178 Fl/Fl þ Py IP/IP ¼ BghiP

0.392 0.454 0.261 0.415 0.217 0.059 0.336 0.395 0.06 0.277

0.288 0.172 0.045 0.292 0.25 0.664 0.197 0.276 0.357 0.232

a

Abbreviations are the same as in Table 1.

and PAH mean concentrations than the stations of group III (Table 5). ANOSIM results (Global R ¼ 0.267, significance level (sl) ¼ 0.1%; pairwise tests: RI,III ¼ 0.449, sl ¼ 0.3%; RI,II ¼ 0.168, sl ¼ 4.5%; RII,III ¼ 0.197, sl ¼ 0.9%) showed the three groups of stations obtained in the PCA differing significantly in relation to their macrobenthic species abundance. The difference was high between groups I and III, but not for group II. In fact, group II showed mean species number and density values similar to those recorded at group I, and mean diversity similar to group III (Table 5). According to the SIMPER results the dissimilarity among the three groups was high. In group I the number of species and their relative abundance was lower than in group II and III (Table 6). The species that contributed the most to the dissimilarity between group I and III were Sigambra grubii and Dasybranchus cf. platyceps that occurred only in group I, Goniada littorea and Nematonereis schmardae that were absent in group I and Table 5 Means of the biological and chemical parameters in each of the three groups obtained in the PCA ordination. Abbreviations are the same as in Table 1

S Density (ind. 0.15 m2) H0 J0 Silt þ clay (%) Aliph (mg g1) n-alk (mg g1) UCM (mg g1) R (mg g1) UCM:R  C24:
Table 6 Relative abundances of macrobenthic species in the three groups of stations and average dissimilarities among them according to SIMPER results. Species which contributed most to differences among the groups are in bold. Average dissimilarity between Groups I & II ¼ 94.46. Average dissimilarity between Groups I & III ¼ 96.93. Average dissimilarity between Groups II & III ¼ 90.42 Species

Variablea

Group I

Group II

Group III

3 4 0.80 0.77 89.68 178.67 13.46 116.08 62.66 2.57 4.50 1.70 1409.83 0.55 0.37 0.78 0.26

4 6 1.10 0.83 93.00 58.61 7.09 41.04 12.73 2.42 3.21 1.08 1023.23 0.37 0.52 0.55 0.27

7 36 1.40 0.72 11.55 30.42 3.25 24.93 9.34 7.97 1.10 1.40 303.23 0.15 0.41 0.53 2.92

463

Pseudeurythoe ambigua Sigambra grubii Autolytus sp. Laeonereis culveri Goniada littorea Goniadides uncata Glycinde multidens Mooreonuphis nebulosa Eunice guanica Eunice (N.) imogena Eunice rubra Nematonereis schmardae Lumbrineris cf. tetraura Scoloplos (L.) dubia Scoloplos treadwelli Cirrophorus branchiatus Magelona variolamelata Poecilochaetus sp. Audouinia sp. Armandia agilis Ophelina sp. Sternaspis sp. Dasybranchus cf. platyceps Periclimenes americanus Alpheus sp. Ogyrides alphaerostris Processa bermudensis Processa hemphilli Trachypenaeus constrictus Paguristes sp. Panopeus lacustris Cyrtoplax spinidentata Pinnixa sayana Leptochelia sp. Cyathura sp. Amakusanthura sp. Leucothoe spinicarpa Heterophoxus videns Ischnochiton sp. Neritina virginea Olivella floralia Nucula semiornata Plicatula gibbosa Ctena pectinella Diplodonta punctata Trachycardium muricatum Tellina versicolor Tagelus plebeius Chione cancellata Anomalocardia brasiliana Callista maculata Corbula caribaea Thysanocardia sp. Lytechinus variegatus Branchiostoma platae

Relative abundance (%) Group I

Group II

Group III

e 19.23 e e e e e 7.69 e 7.69 e e 7.69 e 3.85 e e e e e e e 11.54 e 7.70 e e e e e e 3.85 e e e e e e e e e 3.85 e e 3.85 e 7.69 e 11.54 3.85 e e e e e

e e e 3.92 3.92 e 19.61 e e e e 1.96 e e e 7.84 1.96 1.96 1.96 e 1.96 e 1.96 1.96 7.84 1.96 e e e e e e e 1.96 1.96 1.96 3.92 e e e e 3.92 e e 3.92 e 7.84 e e 1.96 e 13.73 e e e

0.43 e 3.00 0.21 9.01 2.15 2.58 0.21 0.43 0.43 0.21 7.73 0.64 0.64 e 1.07 0.43 e 0.21 1.07 44.42 2.79 e e e e 0.43 0.21 0.21 0.64 0.21 e 0.64 1.72 0.64 2.15 0.43 0.86 0.43 1.72 0.64 0.43 0.86 1.07 0.21 0.64 0.86 1.07 0.86 1.07 0.21 1.72 0.43 0.21 1.72

464

N. Venturini et al. / Estuarine, Coastal and Shelf Science 78 (2008) 457e467

Ophelina sp., which occurred only in group III (Table 6). In addition, the polychaetes Goniada littorea, Glycinde multidens, Nematonereis schmardae, Ophelina sp., and the bivalve Corbula caribaea were the species with highest contribution to the difference between groups II and III. These species were recorded in both groups of stations; nevertheless, their relative abundance varied from one group to the other (Table 6). Moreover, Sigambra grubii and Chione cancellata were present in group I with a high relative abundance but were absent in group II, whereas with Glycinde multidens and Corbula caribaea the opposite was observed. These were the species that contributed the most to the dissimilarity between these two groups of stations. The results of the BIO-ENV procedure showed that silt þ clay, n-alkanes, PAH, An/178 and IP/IP þ BghiP (rW ¼ 0.424) was the combination of variables that best matched the biological data, but other combinations, which included only petroleum related variables showed similar values (Table 7). 5. Discussion 5.1. Hydrocarbons Concentrations of total aliphatic hydrocarbons in unpolluted intertidal and estuarine sediments are normally lower than 10 mg g1 (UNEP, 1991). In addition, total aliphatic hydrocarbon concentrations may reach values up to 100 mg g1 in organically enriched sediments with a significant n-alkanes source derived from higher plants (Volkman et al., 1992). However, values higher than this, such as those recorded at stations 5, 6, 9, 12, 14, 16 and 26 in the northeast portion of Todos os Santos Bay, are indicative of petroleum inputs (Volkman et al., 1992). Furthermore, total aliphatic hydrocarbon concentrations detected in this study are similar to those recorded in other highly contaminated areas on the Atlantic coast of South America (e.g. Nishigima et al., 2001; Muniz et al., 2004). In general, petroleum shows no predominance of odd or even carbon chains, although, long chain n-alkanes inputs from terrestrial plant can often obscure the petroleum derived signal (Volkman et al., 1992). In the present study, the predominance of n-alkanes with more than 24 carbons, together with CPI values close to one suggest the presence of both terrestrial plant material and petroleum products. Similar results were reported by Guerra-Garcı´a et al. (2003). The Table 7 Summary of the BIO-ENV results for the Todos os Santos Bay data. Only the best correlation are shown. Overall optimum weighted Spearman rank correlation coefficient (rw) is in bold. Abbreviations are the same as in Table 1 No. of variables

Best variable combinations (rw)

1 2 3 4 5

PAH (0.327) n-alk, PAH (0.413) n-alk, PAH, An/178 (0.406) n-alk, PAH, An/178, IP/IP þ BghiP (0.421) Silt D clay, n-alk, PAH, An/178, IP/IP D BghiP (0.424) Siltþclay, Aliph, n-alk, PAH, An/178, IP/IP þ BghiP (0.408)

6

occurrence of the unresolved complex mixture (UCM) and its magnitude are considered to be related to the presence of degraded oil and the degree of anthropogenic contribution (Commendatore et al., 2000). In most of the stations of the northeast portion of Todos os Santos Bay, the UCM represented between 60% and 96% of the total aliphatic hydrocarbons, and the UCM/resolved aliphatic hydrocarbons ratios (UCM:R) were higher than two, indicating a high degree of anthropogenic contribution and the presence of petroleum degraded residues. In addition, high values of the UCM, such as those recorded in the present study, have been previously reported as evidence of chronic oil-pollution (Gogou et al., 2000). Total PAH concentrations in surface sediments were similar to those recorded in other coastal areas that receive large anthropogenic inputs derived from urban and industrial activities (Kim et al., 1999; Soclo et al., 2000; Muniz et al., 2005). Highest values were recorded at the stations located in the centre and in the east region of the study area associated with muddy sediments. Since PAH are hydrophobic, they tend to be adsorbed or encapsulated by organic particles and to accumulate in fine sediments (Law and Biscaya, 1994; Yunker et al., 2002). Furthermore, among other organic particles, terrestrial plant detritus in the study area could act as both sources and favourable adsorption matrices of PAH in the sediments (Wang et al., 2001). According to Notar et al. (2001) total PAH concentrations higher than 500 ng g1 are indicative of relatively highly contaminated samples, and our data showed that at station 5 and at the stations situated in the centre and in the east region of Todos os Santos Bay this value was exceeded. PAH of molecular mass 178 and 202 (An/178 and Fl/ Fl þ Py ratios) are often used to distinguish between petroleum and combustion sources (Soclo et al., 2000). These isomer pair ratios showed that PAH in sediments of Todos os Santos Bay derive from both kinds of sources. Most of the stations showed An/178 ratios >0.10 indicating the dominance of combustion sources (Oros and Ross, 2004). Besides, stations 3, 4, 5, 7, 10, 14, 17 and 27 showed Fl/Fl þ Py < 0.40, whereas other stations showed values between 0.40 and 0.50, suggesting the dominance of petroleum (crude oil) and petroleum combustion sources, respectively. In areas located close to crude oil refineries, it is expected to find an important contribution of PAH produced by the refining process, which can enter the marine environment through air emissions and wastewater effluents (Oros and Ross, 2004). Furthermore, some of the stations presented Fl/Fl þ Py ratios >0.50, which according to Yunker et al. (2002) are values characteristic of grass, wood or coal combustion Regarding the IP/IP þ BghiP ratios, half of the stations showed the dominance of liquid fossil fuel (e.g. vehicles and crude oil) combustion sources with values between 0.20 and 0.50. The other half presented the dominance of PAH derived from the combustion of coal, grasses and wood. In general, these ratios showed that in sediment samples of Todos os Santos Bay PAH are derived from both, direct inputs of petroleum and combustion sources. In addition, LMW/HMW ratios <1 indicated the predominance

N. Venturini et al. / Estuarine, Coastal and Shelf Science 78 (2008) 457e467

of four to six aromatic ring or soot PAH derived from hightemperature combustion processes (Oros and Ross, 2004). The predominance of HMW PAH may be related to the slow degradation and high persistence of these compounds in marine sediments (Readman et al., 2002). Overall, the indices used to determine the origin of PAH indicated the occurrence of a petrogenic contribution (i.e. unburned petroleum) and a pyrolytic contribution constituted mainly by PAH derived from fossil fuel (petroleum) combustion in sediment samples of Todos os Santos Bay. 5.2. Macrofauna and hydrocarbons relationships In general, the factors that determined the structure of benthic communities can be classified as abiotic (e.g. sedimentary characteristics, salinity, depth), biotic (e.g. food availability, interactions among species) and anthropogenic (e.g. derived from urban and industrial activities). They are inter-related and have synergic effects. The BIO-ENV procedure established that the combination of variables that best matched to the biological data was silt þ clay, n-alkanes, PAH, An/178 and IP/IP þ BghiP, although other combinations which included only petroleum related variables showed similar Spearman rank correlation values. Some studies have proposed that the distribution and partitioning of nonpolar organic contaminants, such as PAH to marine sediments is controlled by the amount of organic carbon, soot carbon, humic acid content, polarity and surface area of sediment particles (Burgess et al., 2001 and references therein). Certainly, hydrocarbon concentrations are influenced by sedimentary characteristics such as grain size and organic carbon content of the sediments, which in turn influence distributional patterns of macrofauna. However, the present study showed that hydrocarbon concentrations have a relevant influence on macrobenthic communities, and this was evident through the relationships between the abiotic indices and ratios employed and the biological patterns observed. Furthermore, the results of the stepwise multiple regression analysis performed with chemical data and benthic ecological descriptors demonstrated that, granulometry (content of muddy sediments) or total PAH concentrations are not the only parameters determining the structure of benthic communities. Besides, the number of species and diversity showed a relationship with specific concentration ratios or indices such as C24:
465

obtained between the C24:
466

N. Venturini et al. / Estuarine, Coastal and Shelf Science 78 (2008) 457e467

2000). Although the capitellid Dasybranchus cf. platyceps was not dominant in Todos os Santos Bay, it was mainly recorded at those stations with fine sediments and high hydrocarbon concentrations. Moreover, cirratulid species (like Adouina sp.) and Orbiniidae of the genera Scoloplos (like Scoloplos treadwelli) found in this study and more abundant in group II and I, respectively, are also characteristic species of sediments with high organic content (Pearson and Rosenberg, 1978). On the other hand, the carnivorous polychaete Goniada littorea was well represented in group III (excepting at station 3 were Ophelina sp. dominated). It was more abundant at stations 1, 2, 3 and 4 located near the mouth of Caı´pe and Mataripe rivers with the predominance of sandy sediment and low organic content. The subsurface deposit-feeder Ophelina sp. is a slender torpedo-shaped burrower opheliid commonly found in sandy sediments (Fauchald and Jumars, 1979). Nematonereis schmardae, the other sub-dominant species in group III, is a subsurface deposit feeder polychaete, which was more abundant at stations 15 with relatively higher aliphatic and UCM contents than the other stations of this group. Molluscs had a small representation in Todos os Santos Bay. The most abundant species were the filter-feeding bivalves Chione cancellata in group I with high hydrocarbon concentrations, and Corbula caribaea in group II with intermediate hydrocarbon concentrations. According to Baumard et al. (1998), filter-feeding bivalves are mainly exposed to the soluble and more bioavailable fraction of PAH. Due to the occurrence of petroleum-derived PAH present in solution or finely dispersed, the uptake and exposure to harmful PAH for these two species is supposed to be high within the study area. However, their occurrence at these groups of stations may be related to their limited capacity to metabolise PAH. Effects of PAH on organisms are often initiated through biotransformation of the compounds to toxic metabolites, mainly by activation of the cytochrome P450 enzymes. Generally, not considering interspecies variation, the capacity to metabolise PAH is best developed in fish, intermediate in crustaceans and least in molluscs (Knutzen, 1995). Therefore, they would be more protected against cancer induced by PAH metabolites and can accumulate PAH without apparent damaging effects (Law and Biscaya, 1994). Crustaceans had a minor representation within the study area and a high number of species occurred at the stations of group III characterised by less stressful conditions. In general, crustaceans, especially amphipods, are more sensitive to adverse environmental conditions such as organic enrichment, oil and heavy metal contamination than Polychaeta (Grall and Gle´marec, 1997). Based on this characteristic the polychaete/ amphipod ratio has been used as a good indicator of environmental impact (Dauvin and Ruellet, 2007). Even though this ratio was not calculated, the two amphipods recorded in this study Leucothoe spinicarpa and Heterophoxus videns were absent at the most impacted stations of group I, where opportunistic polychaetes such as Sigambra grubii and Dasybranchus cf. platyceps showed high relative abundances. Nevertheless, tolerance to contaminants could vary among different groups and among different species within a particular group (Knutzen, 1995) and crustaceans have been found at organically

enriched sites (Frouin, 2000). The presence of decapods of the genera Alpheus exclusively at stations of groups I and II with high hydrocarbon concentrations, could be related to the living strategy of these organisms. According to Frouin (2000) the construction of galleries by Alpheus together with the animal displacement through them could reduce the exposure of these decapods to contaminants, making possible their occurrence even at impacted sites. The distribution of sediment particles and particle-associated contaminants in marine benthic environments results from the interaction of different processes such as physical mixing, degradation and bioturbation (Caradec et al., 2004). Moreover, borrow irrigation increases interstitial water circulation and oxygenation of sediments, which in turn could enhance the remobilisation and degradation of previously buried hydrocarbons and improve overall bottom conditions. 6. Conclusion Our results showed that macrobenthic communities in the northeast portion of Todos os Santos Bay are subjected to the impact of chronic oil pollution. This fact was reflected by profound changes observed such as species and diversity reduction, mainly in the centre and in the east region of the area. These results emphasise the importance of performing multivariate approaches combining chemical data (indices, concentration ratios and specific compound concentrations) with biological information to improve the assessment of anthropogenic impacts on marine ecosystems. Acknowledgements We thank the colleagues from the FUNDESPA (Fundac¸~ao de Estudos e Pesquisas Aqua´ticas) for their help in different stages of this work. The Conselho Nacional de Desenvolvimento Cientı´fico e Tecnolo´gico (CNPq) of the Brazilian Government is acknowledged for the MSc grant to N.V. This work was developed within the project ‘‘Diagno´stico Ambiental  Marinho da Area de Influeˆncia da Refinaria Landulpho Alves, Mataripe, Baı´a de Todos os Santos’’ a partnership between FUNDESPA and PETROBRAS (Petro´leo do Brasil, SA). We would like to thank M.Y. Yoshinaga for his comments and for correcting the English. The manuscript was improved by comments from two anonymous reviewers. References Baumard, P., Budzinski, H., Garrigues, P., Sorbe, J.C., Burgeot, T., Bellocq, J., 1998. Concentrations of PAHs (Polycyclic Aromatic Hydrocarbons) in various marine organisms in relation to those in sediments and to trophic level. Marine Pollution Bulletin 36, 951e960. Belan, T.A., 2003. Benthos abundance pattern and species composition in conditions of pollution in Amursky Bay (the Peter the Great Bay, the Sea of Japan). Marine Pollution Bulletin 46, 1111e1119. Burgess, R.M., Ryba, S.A., Cantwell, M.G., Gundersen, J.L., 2001. Exploratory analysis of the effects of particulate characteristics on the variation in partitioning of nonpolar organic contaminants to marine sediments. Water Research 35, 4390e4404.

N. Venturini et al. / Estuarine, Coastal and Shelf Science 78 (2008) 457e467 Caradec, S., Grossi, V., Hulth, S., Stora, G., Gilbert, F., 2004. Macrofaunal reworking activities and hydrocarbon redistribution in an experimental sediment system. Journal of Sea Research 52, 199e210. Citac/Eurachem Guide, 2002. Guide to Quality in Analytical Chemistry. Prepared jointly by: CITAC (The Cooperation on International Traceability in Analytical Chemistry) and EURACHEM (A Focus for Analytical Chemistry in Europe), 57 pp. Clarke, K.R., Green, R.H., 1988. Statistical design and analysis for a ‘biological effects´ study. Marine Ecology Progress Series 46, 213e226. Clarke, K.R., Ainsworth, M., 1993. A method of linking multivariate community structure to environmental variables. Marine Ecology Progress Series 92, 205e219. Clarke, K.R., Warwick, R.M., 1994. Change in Marine Communities: An Approach to Statistical Analysis and Interpretation. Plymouth Marine Laboratory, Plymouth, 144 pp. Commendatore, M.G., Esteves, J.L., Colombo, J.C., 2000. Hydrocarbons in coastal sediments of Patagonia, Argentina: Levels and probable sources. Marine Pollution Bulletin 11, 989e998. Dauvin, J.C., Ruellet, T., 2007. Polychaete/amphipod ratio revisited. Marine Pollution Bulletin 55, 215e224. Forbes, V.E., Forbes, T.L., Holmer, M., 1996. Inducible metabolism of fluoranthene by the opportunistic polychaete Capitella sp. Marine Ecology Progress Series 132, 63e70. Frouin, P., 2000. Effects of anthropogenic disturbances of tropical soft-bottom benthic communities. Marine Ecology Progress Series 194, 39e53. Fauchald, K., Jumars, P.A., 1979. The diet of worms: a study of polychaete feeding guilds. Oceanography and Marine Biology Annual Review 17, 193e284. GDB (Governo do Estado da Bahia), 2000. Report: Saneamento ambiental da Baı´a de Todos os Santos. Diagno´stico da qualidade das a´guas da BTS (Estudos preliminares, fontes de poluic¸~ao, legislac¸~ao e metodologia), Salvador, 257 pp. Gogou, A., Bouloubassi, I., Stephanou, E.G., 2000. Marine organic geochemistry of the Eastern Mediterranean: I. Aliphatic and polyaromatic hydrocarbons in Cretan Sea surficial sediments. Marine Chemistry 68, 265e282. Grall, J., Gle´marec, M., 1997. Using biotic indices to estimate macrobenthic community perturbations in the Bay of Brest. Estuarine, Coastal and Shelf Science 44 (Supplement A), 43e53. Guerra-Garcı´a, J.M., Gonza´lez-Vila, F.J., Garcı´a-Go´mez, J.C., 2003. Aliphatic hydrocabon pollution and macrobenthic assemblages in Ceuta harbour: a multivariate approach. Marine Ecology Progress Series 263, 127e138. Heip, C., 1992. Benthic studies: summary and conclusions. Marine Ecology Progress Series 91, 265e269. Hyland, J.L., Balthis, W.L., Hackney, C.T., Posey, M., 2000. Sediment quality of North Carolina estuaries: an integrative assessment of sediment contamination, toxicity and condition of benthic fauna. Journal of Aquatic Ecosystems Stress and Recovery 8, 107e124. Jewett, S.C., Dean, T.A., Smith, R.O., Blanchard, A., 1999. ‘‘Exxon Valdez’’ oil spill: impacts and recovery in the soft-bottom benthic community in and adjacent to eelgrass beds. Marine Ecology Progress Series 185, 59e83. Kim, G.B., Maruya, K.A., Lee, R.F., Lee, J.H., Koh, C.H., Tanabe, S., 1999. Distribution and sources of polycyclic aromatic hydrocarbons in sediments from Kyeonggi Bay, Korea. Marine Pollution Bulletin 38, 7e15. Knutzen, J., 1995. Effects on marine organisms from polycyclic aromatic hydrocarbons (PAH) and other constituents of waste water from aluminium smelters with examples from Norway. The Science of the Total Environment 163, 107e122. Law, R.J., Biscaya, J.L., 1994. Polycyclic aromatic hydrocarbons (PAH)Problems and progress in sampling, analysis and interpretation. Marine Pollution Bulletin 29, 235e241. Long, E.R., McDonald, D.D., Smith, S.L., Calder, F.D., 1995. Incidence of adverse biological effects within ranges of chemical concentrations in marine and estuarine sediments. Environmental Management 19, 81e97. McDonald, D.D., Carr, R.S., Calder, F.D., Long, E.R., Ingersoll, C.G., 1996. Development and evaluation of sediment quality guidelines for Florida coastal waters. Ecotoxicology 5, 253e278.

467

Muniz, P., Danulat, E., Yannicelli, B., Garcı´a-Alonso, J., Medina, G., Bı´cego, M.C., 2004. Assessment of contamination by heavy metals and petroleum hydrocarbons in sediments of Montevideo Harbour (Uruguay). Environment International 29, 1019e1028. Muniz, P., Venturini, N., Pires-Vanin, A.M., Tommasi, L.R., Borja, A., 2005. Testing the applicability of a Marine Biotic Index (AMBI) to assessing the ecological quality of soft-bottom benthic communities, in the South America Atlantic region. Marine Pollution Bulletin 50, 624e637. Nilsson, H.C., Rosenberg, R., 1994. Hypoxic response of two marine benthic communities. Marine Ecology Progress Series 115, 209e217. Nishigima, F.N., Weber, R.R., Bı´cego, M.C., 2001. Aliphatic and aromatic hydrocarbons in sediments of Santos and Canane´ia, SP, Brazil. Marine Pollution Bulletin 42, 1064e1072. Notar, M., Leskovsek, H., Faganeli, J., 2001. Composition, distribution and sources of polycyclic aromatic hydrocarbons in sediments of the Gulf of Trieste, northern Adriatic Sea. Marine Pollution Bulletin 42, 36e44. Oros, D.R., Ross, J.R.M., 2004. Polycyclic aromatic hydrocarbons in San Francisco Estuary sediments. Marine Chemistry 86, 169e184. Pearson, T.N., Rosenberg, R., 1978. Macrobenthic succession in relation to organic enrichment and pollution of the marine environment. Oceanography and Marine Biology Annual Review 16, 229e311. Pielou, E.C., 1966. Shannon’s formula as a measure of species diversity: its use and misuse. American Naturalist 100, 463e465. Ponce, V.R., Correa, C.I., 1980. Contribuic¸~ao a` sedimentologia da Baı´a de Todos os Santos-Parte leste. Anais Hidrogra´ficos 37, 113e139. Rakocinski, C.F., Brown, S.S., Gaston, G.R., Heard, R.W., Walker, W.W., Summers, J.K., 2000. Species-abundance-biomass responses by estuarine macrobenthos to sediment chemical contamination. Journal of Aquatic Ecosystems Stress and Recovery 7, 201e214. Readman, J.W., Fillmann, G., Tolosa, I., Bartocci, J., Villeneuve, J.P., Catinni, C., Mee, L.D., 2002. Petroleum and PAH contamination of the Black Sea. Marine Pollution Bulletin 44, 48e62. Shannon, C.E., Weaver, W., 1963. The mathematical theory of communication. University of Illinois, Urbana, 111 pp. StatSoft Inc, 1995. STATISTICA for the Windows Operating System. Release 5. StatSoft Inc., Tulsa, OK, USA. Soclo, H.H., Garrigues, P.H., Ewald, M., 2000. Origin of polycyclic aromatic hydrocarbons (PAHs) in coastal marine sediments: case studies in Cotonou (Benin) and Aquitaine (France) Areas. Marine Pollution Bulletin 40, 387e396. UNEP (United Environmental Programme), 1991. Determinations of Petroleum Hydrocarbons in Sediments. Reference Methods for Marine Pollution Studies. No. 20. Venturini, N., Tommasi, L.R., 2004. Polycyclic aromatic hydrocarbons and changes in the trophic structure of polychaete assemblages in sediments of Todos os Santos Bay, Northeastern, Brazil. Marine Pollution Bulletin 48, 97e107. Venturini, N., Muniz, P., Rodrı´guez, M., 2004. Macrobenthic subtidal communities in relation to sediment pollution: the phylum-level meta-analysis approach in a south-eastern coastal region of South America. Marine Biology 144, 119e126. Volkman, J.K., Holdsworth, D.G., Neill, G.P., Bvor Jr., H.J., 1992. Identification of natural, anthropogenic and petroleum hydrocarbons in aquatic sediments. The Science of the Total Environment 112, 203e219. Wang, X.C., Zhang, Y.X., Chen, R.F., 2001. Distribution and partitioning of polycyclic aromatic hydrocarbons (PAHs) in different size fractions in sediments from Boston Harbor, United States. Marine Pollution Bulletin 11, 1139e1149. Yunker, M.B., Macdonald, R.W., Vingarzan, R., Mitchell, R.H., Goyette, D., Sylvestre, S., 2002. PAHs in the Fraser River basin: a critical appraisal of PAH ratios as indicators of PAH source and composition. Organic Geochemistry 33, 489e515. Zar, J.H., 1996. Biostatistical analysis, Third edition. Prentice Hall, New Jersey, 663 pp.