Assessment of the ecological status of transitional waters in Sicily (Italy): First characterisation and classification according to a multiparametric approach

Marine Pollution Bulletin 60 (2010) 1682–1690

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Assessment of the ecological status of transitional waters in Sicily (Italy): First characterisation and classification according to a multiparametric approach Gabriella Caruso a,*, M. Leonardi a, L.S. Monticelli a, F. Decembrini a, F. Azzaro a, E. Crisafi a, G. Zappalà a, A. Bergamasco a, S. Vizzini b a b

National Research Council, Institute for Coastal Marine Environment, Spianata S. Raineri, 98122 Messina, Italy Department of Ecology, University of Palermo, Sicily, Italy

a r t i c l e

i n f o

Keywords: Transitional areas Water Framework Directive Ecological quality status Trophic conditions Microbial decomposition Sicily

a b s t r a c t A 1-year cycle of observations was performed in four Sicilian transitional water systems (Oliveri-Tindari, Cape Peloro, Vendicari and Marsala) to characterise their ecological status. A panel of variables among which trophic and microbial (enzyme activities, abundance of hetetrophic bacteria and of bacterial pollution indicators) parameters, were selected. Particulate organic carbon (POC) and nitrogen (PON) and chlorophyll-a (Chl-a) contents defined the trophic state, while microbial hydrolysis rates and abundance gave insights on microbial community efficiency in organic matter transformation and on allochthonous inputs. To classify the trophic state of examined waters, the synthetic trophic state index (TRIX) was calculated. Microbial hydrolysis rates correlated positively with POC and Chl-a, which increased along the eutrophication gradient. The significant relationships among TRIX, trophic and microbial parameters suggested the use of leucine aminopeptidase, alkaline phosphatase and POC as suitable parameters to implement the Water Framework Directive when assessing the ecological status of transitional water systems. Ó 2010 Elsevier Ltd. All rights reserved.

1. Introduction Transitional water systems, such as lagoons, estuaries and coastal lakes, are very complex ecosystems located at the interface between land and sea, characterised by confined circulation and weak hydrodynamism, shallow depth, strong variations in temperature and light regimes, high productivity, high potential biodiversity, high vulnerability to anthropic pressure. The assessment of the health status of these water systems is a major issue for accurate management and preservation of their integrity. The Water Framework Directive (WFD, 2000/60/CE Directive) requires Member States to classify their water bodies according to a number of indicators or ‘‘quality elements”, including physico-chemical, hydromorphological and biological elements. However, as recognised by recent studies (Devlin et al., 2007), the monitoring criteria indicated in the WFD fail to accurately describe the ecological status of all the different typologies of water bodies. For this reason one of the most technically challenging issues in the implementation of the WFD concerns the development of innovative classification tools and approaches for ecological quality status assessment. Great research efforts are being made across Europe with this aim, with an increased interest in the revision of the indicators of trophic state and environ-

* Corresponding author. Tel.: +39 090 669003; fax: +39 090 669007. E-mail address: [email protected] (G. Caruso). 0025-326X/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.marpolbul.2010.06.047

mental quality currently in use (Dell’Anno et al., 2002; Pusceddu et al., 2003). The need to implement the WFD is particularly urgent for transitional environments, due to the inadequacy of the ecological descriptors currently used (Fabiani, 2005). In fact, despite their economical and ecological importance as natural microcosms suitable for studying ecological processes, little attention has been given to the development of indicators and indices for assessing trophic status and quality in transitional water systems (Basset et al., 2006). Zaldívar et al. (2008) reported a comprehensive review on indicators and tools for assessing eutrophication; nevertheless, microbial processes which act at the basis of the food web should not be neglected in this context, in order to obtain a more comprehensive scenario of natural dynamics. In Italy, Sicilian inland areas are still poorly known in their physical, chemical and biological features, as well as in terms of trophic inputs and anthropic pressure. The little existing data concerns only some water systems such as Oliveri-Tindari and Marsala, where both the trophic and biological characteristics were investigated during previous studies (Caruso et al., 2005; Crisafi et al., 1981; Leonardi et al., 2000; Leonardi and Giacobbe, 2001; Sarà et al., 1999). In 2005 the Regional Agency for Environmental Protection (ARPA Sicily) started a multidisciplinary program aimed at the first characterisation of Sicilian water bodies; in this framework, a comparative study of Cape Peloro, Oliveri-Tindari, Vendicari and Marsala water systems was undertaken as representative of the second cluster of Italian lagoons, e.g., xero-Mediterranean lagoons

G. Caruso et al. / Marine Pollution Bulletin 60 (2010) 1682–1690

(Tagliapietra and Volpi Ghirardini, 2006), also in the perspective of establishing quality criteria. The aim of this study was to assess the ecological status of the main transitional areas of Sicily through the use of a new integrated approach based on measurements of both trophic (suspended organic matter, particulate organic carbon and nitrogen, chlorophyll-a, nutrients) and microbial (enzyme activity and bacterial abundances) parameters in parallel with the main physicochemical ones (temperature, salinity, and dissolved oxygen). Here the results of a 1-year cycle of observations (2005–2006) are reported.

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Due to the larger spatial extension of the Marsala area, three points (northern, central and southern) were sampled instead of one. All samples were taken using sterile Niskin bottles, which were kept at +4 °C until laboratory analysis. A conductivity, temperature and depth (CTD) probe Sea-Bird 19plus were used to provide in situ measurements of conductivity and temperature. Salinity values were calibrated through comparison with laboratory measurements made with an induction salinometer AutoSal Guildline Model 8004B. Dissolved oxygen (O2) content was estimated through Winkler’s method. 2.3. Trophic parameters

2. Materials and methods 2.1. Description of the study areas The four areas examined during this study, Cape Peloro, OliveriTindari, Vendicari and Marsala, are transitional water systems between terrestrial and marine environments (Fig. 1). Their detailed description is given by Mazzola et al. (2010). According to their geomorphological characteristics, Cape Peloro (which includes two water bodies, Ganzirri and Faro) and Oliveri-Tindari (which consists of four water bodies, Marinello, Mergolo, Porto and Verde) can be classified as coastal brackish areas. The Vendicari area consists of three shallow water bodies (Roveto, Grande and Piccolo) and Marsala is a semi-enclosed area under hydrodynamic exchange with the adjacent open sea (Fabiano et al., 2001). 2.2. Samples collection From June 2005 to May 2006, surface water samplings were performed monthly in each of the 10 water bodies belonging to the four analysed water systems. For every water body, only one station, located at the deepest point of each site, was sampled and this was considered representative for the whole area (Fig.1).

Nutrient concentrations (nitrite, NO2, nitrate, NO3, and orthophosphate, PO4, ions) were determined according to Genovese and Magazzù (1969); ammonia (NH4) concentrations according to Aminot and Chaussepied (1983). Total N and P were measured according to Strickland and Parsons (1972). Particulate organic carbon (POC) and nitrogen (PON) amounts were estimated by filtering 500 ml of water samples on precombusted Whatman GF/F filters. After a 6-h HCl fumes exposition to eliminate the inorganic carbon, the filters were processed at 980 °C in a Perkin–Elmer CHN-Autoanalyzer 2400, using acetanilide as the standard (Iseki et al., 1987). Chlorophyll-a (Chl-a) concentration was measured after water filtration on Whatman GF/F filters and extraction in 90% acetone of the recovered material; readings were carried out in a Varian Eclypse spectrofluorometer, previously calibrated with serial standard dilutions of Chl-a from Anacistis nidulans (Sigma) (Lazzara et al., 1990). 2.4. Microbial parameters Microbial enzyme activity rates (leucine aminopeptidase, LAP; alkaline phosphatase, AP) as markers of the potential ability of the microbial community to decompose peptides and organic

Fig. 1. Sicilian transitional water systems and sampling stations.

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phosphates (Caruso, 2010), were determined. Ten milliliters of unfiltered sample were incubated, in triplicate, with fixed volumes of L-leucine-4-methylcoumarinylamid hydrochloride (Leu-MCA) or methylumbelliferyl (MUF)-phosphate (Sigma) as specific fluorogenic substrates for LAP and AP, respectively, according to the Hoppe (1993) multi-concentration method. The final concentrations of substrates used in this study ranged from 20 to 200 lmol l 1. The fluorescence released by substrate hydrolysis was measured with a F-2000 Hitachi spectrofluorometer at time 0, immediately after substrate addition, and 3 h after incubation at ‘‘in situ” temperature. Calibration was performed with concentrations from 200 to 800 nmol l 1 of 7-amino-4-methylcoumarin or methylumbelliferone used as the standards for LAP or AP, respectively. Data was reported as the maximum velocity of hydrolysis (Vmax) and expressed in terms of nanomoles of Leucine or PO4 (nmol l 1 h 1) potentially released per litre and per hour from Leu-MCA or MUF-phosphate, respectively. Culturable heterotrophic aerobic marine bacteria were counted using the spread plate method on Marine agar (Difco) incubated at 20 °C for 7 days. For an auxiliary characterisation of the allochthonous inputs present in the area, faecal coliforms (FC) and enterococci (ENT) were determined using membrane filters according to the Standard Methods (APHA 1992). 2.5. Trophic state indices The TRIX index, as an indicator of the trophic state, was calculated for each water body and at each sampling time, according to the equation TRIX = log [Chl-a  O2 (%)  N  P] [ 1.5]/1.2. For the classification of the waters according to TRIX index, the threshold values reported by the Italian Decree Law no. 152/99 – Annex 1, were applied. This classification defines four categories of trophic status: High: 2 < TRIX < 4; Good: 4 6 TRIX < 5; Moderate: 5 6 TRIX < 6; Poor: 6 6 TRIX < 8. C:N and N:P stoichiometric ratios were also calculated according to Redfield (1934). 2.6. Statistical analysis The values recorded for each parameter were reported as the mean ± standard deviation. The coefficient of variation (CV) was also calculated. Differences between mean values of the parameters were tested by analysis of variance (ANOVA). The significance of association between pairs of variables was assessed by means of Pearson correlation. Regression analysis of POC and LAP data vs. the TRIX index was carried out. Statistical elaboration of data was also performed using the multi-dimensional scaling (MDS) coupled with cluster analysis carried out by the Bray–Curtis similarity coefficient (Primer v5 program), which evaluated the degree of similarity among the studied areas according to the environmental and microbiological characteristics. 3. Results 3.1. Trophic parameters The annual mean nutrient concentrations measured in the studied water systems, with minimum, maximum and CV, are shown in Table 1. The NO3 ions were predominant within the dissolved inorganic N (DIN = NH4 + NO2 + NO3) pool of all the examined water bodies. The highest values of NH4, NO2 and NO3 occurred in Piccolo, belonging to the Vendicari area, where the mean values were, respectively, about 5, 10 and 3 times higher than those measured

in the other water bodies. The same was observed for the concentration of total N, which in Piccolo was twice of that recorded in Roveto. This last site was also characterised by high amounts of total P and PO4. Moderate nutrient concentrations (range: NH4: 10.85–15.87 lg l 1; NO2: 52.42–90.55 lg l 1; NO3: 4.55–7.14 lg l 1; and PO4: 10.84–11.69 lg l 1) were found in Oliveri-Tindari and Cape Peloro. In the first area, the highest DIN, total N and P concentrations were recorded in Verde, while the highest PO4 concentrations were found in Mergolo. In the Cape Peloro area, Ganzirri showed concentrations of total N and P higher than those of Faro, while this latter was richer in NH4, NO3 and PO4. Marsala was a nutrient-poor area, referring to the lowest values of total N and P, DIN and PO4 detected in its waters. POC and PON concentrations demonstrated the spatial heterogeneity of organic loads among the water bodies, as well as their temporal variability (Table 1). According to POC content, Roveto and Verde were classified as hypereutrophic environments, with Roveto showing the highest mean POC values, about one magnitude higher than the other sites. Lower POC amounts (3000– 1500 lgC l 1) were recorded in Grande and Piccolo, identified as eutrophic sites; while even lower levels (1500–200 lgC l 1) were recorded in Faro, Ganzirri, Marinello, Mergolo, Porto, Northern and Central Marsala, included in the group of mesotrophic sites. The lowest mean POC value (166.49 lgC l 1) was recorded in Southern Marsala, that was defined as oligotrophic. PON distribution reflected closely that of POC. The Chl-a mean concentration in the ponds (Table 1) showed a trophic gradient varying from oligotrophy (0.41 ± 0.15 lg l 1 in Southern Marsala) to eutrophy (19.13 ± 15.47 lg l 1 in Roveto). Peak values of 51.43 and 40.15 lg l 1 were recorded in Roveto and in Verde, respectively. The trophic categories defined by Chla values described a gradient quite consistent with the annual averages of POC, except for Roveto and Verde. 3.2. Microbial parameters The marked trophic diversification of the ten examined water bodies was reflected by the various ranges of enzyme patterns found also at a low spatial scale (i.e., within the same ecosystem). The mean LAP values measured in the studied areas, with minimum and maximum, are shown in Table 2. Faro and Marsala, identified as oligotrophic environments, were characterised by low LAP activity; conversely, in Roveto and Verde, the highest activity levels were detected. Intermediate LAP values were observed in Marinello and Ganzirri, reflecting their characteristics of mesotrophic environments. Mean AP values were at their minimum in Porto, Central and Southern Marsala while maximum AP activity was measured in Roveto. Values ranging in the same magnitude order as Roveto were found in Verde and Piccolo (Table 2). In the oligotrophic and mesotrophic sites, such as Porto and Marsala, enhanced AP activity was recorded in late spring (May or June), while the other meso- and eutrophic environments always displayed high enzyme values, peaking in the warmest months (August–October) (data not shown). The abundances of heterotrophic bacteria, faecal coliforms and enterococci are reported in Table 2. The highest heterotrophic bacteria counts were recorded in Grande and Roveto, the lowest in Marsala. The abundance of faecal pollution indicators was, on average, in the order of 101–102 CFU 100 ml 1 for faecal coliforms, with the highest densities in Marinello, Verde and Roveto. Enterococci ranged in the same order of magnitude as faecal coliforms, with the highest average concentrations in Marinello, Verde and Grande. Faecal coliform counts were high during summer, particularly at Ganzirri, Marinello and Verde, whereas enterococci were abundant

Table 1 Trophic parameters (nutrients, Chl-a, POC, PON) and indices (C:N, N:P) measured in the transitional areas under study: x: mean value; CV: coefficient of variation and range of variation (minimum–maximum). Abbreviations: NH4, ammonia; NO2, nitrite; NO3, nitrate; total N, total nitrogen; PO4, orthophosphate; total P, total phosphorus; Chl-a, chlorophyll-a; POC, particulate organic carbon; PON, particulate organic nitrogen; C:N ratio (derived from POC and PON data). Study area

Ganzirri Faro

Oliveri-Tindari

Marinello Mergolo Verde Porto

Vendicari

Piccolo Grande Roveto

Marsala

Northern Central Southern

NH4 (lg l

1

)

NO2 (lg l

1

)

NO3 (lg l

1

)

Total N (lg l 1)

PO4 (lg l

1

)

Total P (lg l 1)

Chl-a (lg l 1)

POC (lg l

1

)

PON (lg l

C:N

N:P

1

)

x (CV) min–max x (CV) min–max

10.93 (88.7) 1.79–37.60 20.80 (95.1) 3.24–58.02

7.51 (72.3) 0.41–17.78 6.77 (120.2) 0.28–29.59

80.58 (91.3) 13.76–219.06 100.52 (94.7) 2.10–328.98

248.19 (48.0) 68.49–425.60 219.31 (48.6) 68.40–418.61

7.85 (62.5) 1.12–16.15 15.54 (80.6) 2.23–46.45

41.66 (53.2) 17.39–95.50 36.57 (65.2) 10.37–84.02

4.37 (66.0) 1.22–9.07 0.79 (63.0) 0.23–2.10

1119.66 (62.0) 407.5–2458 397.48 (35.0) 153.67–596

191.44 (61.0) 66.5–396 74.38 (8.0) 33.3–112.7

5.88 (10) 4.7–6.89 5.36 (12.0) 4.25–6.12

18 (88.0) 1.98–51.09 14.12 (126.1) 1.35–50.61

x (CV) min–max x (CV) min–max x (CV) min–max x (CV) min–max

6.87 (57.0) 2.97–13.30 7.77 (94.3) 0.43–22.19 21.81 (92.1) 1.76–52.37 6.95 (58.9) 1.49–16.51

3.11 (125.8) 0.18–14.09 1.42 (87.3) 0.07–3.73 10.36 (161.6) 0.35–53.69 3.33 (80.1) 0.32–8.99

35.29 (221.9) 0.28–269.51 20.79 (98.7) 0.49–69.71 132.15 (91.9) 25.13–362.04 21.44 (90.8) 7.23–76.37

251.19 (52.4) 99.08–533.48 222.42 (34.7) 83.62–320.32 412.25 (41.5) 117.47–690.10 122.50 (45.3) 29.96–203.14

8.31 (52.2) 1.76–15.19 13.28 (86.2) 2.80–41.45 11.83 (60.8) 1.70–21.23 9.95 (127.8) 2.37–47.62

34.81 (42.4) 15.79–64.88 28.53 (33.7) 16.57–52.70 53.89 (36.4) 34.48–100.75 25.51 (65.3) 10.85–71.61

2.67 (93.0) 0.16–6.83 1.34 (45.0) 0.38–2.05 15.90 (79.0) 2.33–40.15 1.71 (160) 0.15–8.07

679.45 (40.0) 303–1085 957.35 (27.0) 573–1342 8171.47 (53.0) 1698.7–13196 549.5 (59.0) 281–1242

120.86 (43.0) 58.7–207 166.35 (22.0) 117.3–216 1219.57 (54.0) 266.7–2144 79.42 (55.0) 37–171

5.73 (14.0) 4.14–7.27 5.72 (12.0) 4.82–6.68 6.72 (11.0) 5.62–8.04 6.96 (16.0) 4.58–8.43

5.86 (163.3) 0.87–34.33 5.40 (136.8) 0.32–24.24 32.24 (141.5) 3.31–125.47 5.98 (104.2) 0.89–20.21

x (CV) min–max x (CV) min–max x (CV) min–max

97.78 (130.6) 19.76–452.48 55.11 (113.9) 3.87–160.52 22.91 (146.4) 2.17–100.66

68.45 (154.9) 0.36–362.64 15.24 (115.6) 1.33–53.18 7.89 (104.0) 0.14–25.85

319.31 (98.3) 11.98–887.65 146.58 (113.2) 14.35–451.50 108.54 (70.8) 15.51–231.56

684.04 (67.5) 368.68–1802.51 520.17 (25.5) 349.52–676.39 374.62 (43.9) 165.07–620.12

11.92 (49.8) 4.66–23.68 9.46 (40.5) 3.24–14.04 14.33 (47.8) 3.58–25.25

39.13 (47.2) 16.54–66.63 55.71 (28.8) 33.04–79.66 98.28 (37.7) 54.35–156.18

1.98 (156.0) 0.12–9.49 5.57 (122.0) 0.04–20.48 19.13 (81.0) 3.98–51.43

1722.43 (84.0) 402–4186 2615.19 (33.0) 638–3344 10129.09 (79.0) 2324–26053.8

249.57 (84.0) 55–608 441.79 (35.0) 119.8–642 1707.68 (71.0) 442–4107.7

7.03 (10.0) 6.15–8.18 6.01 (20.0) 4.84–8.62 5.80 (13.0) 4.88–7.01

43.36 (72.6) 5.19–91.37 34.88 (141.2) 3.57–155.00 17.92 (128.5) 4.06–66.33

x (CV) min–max x (CV) min–max x (CV) min–max

9.78 (115.5) 0.02–34.96 6.36 (142.9) 0.02–32.75 9.09 (127.8) 0.02–36.56

1.17 (40.2) 0.44–1.93 1.34 (79.1) 0.41–4.45 1.27 (40.1) 0.60–2.12

20.58 (104.7) 4.43–78.43 8.83 (52.5) 3.00–17.17 15.86 (76.5) 1.72–43.82

165.22 (22.3) 123.42–259.31 179.67 (26.3) 118.16–268.42 170.64 (37.4) 73.33–271.22

2.53 (95.2) 0.30–7.33 2.12 (92.9) 0.18–5.43 2.37 (81.8) 0.41–5.53

18.93 (64.9) 6.29–45.86 15.57 (70.6) 5.02–39.02 17.79 (69.9) 5.84–45.11

0.52 (40.0) 0.28–0.99 0.46 (35.0) 0.27–0.76 0.41 (37.0) 0.17–0.68

212.84 (38.0) 139.6–429.3 201.95 (35.0) 122.4–363.4 166.49 (32.0) 101.5–275.5

33.93 (38.0) 20.8–62. 7 29.1 (18.0) 23.4–39.0 25.71 (29.7) 14.5–40. 3

6.40 (17.0) 4.79–8.23 7.04 (39.0) 5.23–15.40 6.59 (21.4) 4.87–9.86

41.50 (186.5) 0.80–282.78 17.99 (83.8) 0.70–42.33 23.65 (92.6) 0.44–58.80

G. Caruso et al. / Marine Pollution Bulletin 60 (2010) 1682–1690

Cape Peloro

Water body

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Table 2 Microbial parameters measured in the transitional areas under study: x, mean value; CV, coefficient of variation and range of variation (minimum–maximum). Study area Cape Peloro

Water body Ganzirri Faro

Oliveri-Tindari

Marinello Mergolo Verde Porto

Vendicari

Piccolo Grande Roveto

Marsala

Northern Central Southern

Leucine aminopeptidase (nmol l 1 h 1)

Alkaline phosphatase (nmol l 1 h 1)

Heterotrophic bacteria (102 CFU ml 1)

Faecal coliforms (CFU 100 ml 1)

Enterococci (CFU 100 ml

x (CV) min–max x (CV) min–max

141.08 (39.6) 101.01–294.52 122.13 (15.2) 101.99–162.21

78.77 (127.6) 1.48–251.29 64.24 (170.6) 0.10–303.01

62.1 (116.4) 6.40–233 63.9 (109.5) 5.15–212

21 (114.3) 0–56 3 (200) 0–18

9 (122.2) 0–30 3 (200) 0–18

x (CV) min–max x (CV) min–max x (CV) min–max x (CV) min–max

133.14 (35.2) 100.27–265.29 135.43 (20.8) 102.48–198.04 192.78 (62.3) 100.49–471.74 130.61 (40.6) 102.50–281.55

127.22 (140.4) 5.23–541.88 114.82 (118.3) 9.71–444.11 209.18 (125.3) 22.17–726.64 38.70 (128.7) 0.48–135.57

204 (102.3) 10.9–670 65.2 (193.2) 2.35–437 105 (72.4) 13–232 43.9 (121.4) 4.20–168

31 (296.7) 0–308 5 (120) 0–17 100 (63.0) 28–253 3 (233.3) 0–22

43 (313.9) 0–450 12 (191.6) 0–76 46 (100) 16–180 3 (166.6) 0–12

x (CV) min–max x (CV) min–max x (CV) min–max

141.11 (36.6) 100.05–233.25 175.09 (63.0) 101.26–407.02 294.34 (83.5) 118.14–756.27

202.77 (142.7) 5.59–825.88 63.56 (172.1) 2.77–342.29 280.70 (160.9) 5.01–1222.41

98.6 (120.7) 6.60–400 1230 (218.7) 4.65–8300 608 (95.7) 8.35–1540

8 (287.5) 0–73 6 (250) 0–48 24 (258.3) 0–188

7 (171.4) 0–33 22 (168.2) 0–120 22 (95.4) 0–71

x (CV) min–max x (CV) min–max x (CV) min–max

118.36 (29.3) 100.46–225.32 141.76 (48.1) 100.15–336.66 120.70 (17.8) 101.50–165.51 43.07 9.19–107.31

89.00 (179.2) 0.84–535.74 58.75 (128.3) 0.61–237.49 52.46 (205.8) 2.24–369.94 131.06 84.73–187.46

16.6 (71.1) 5.05–49.0 13.9 (52.4) 3.0–28.0 32.2 (100) 1.0–101.0 141.88 67.60–293.31

0 (0) 0–1 0 (0) 0–0 0 (0) 0–0 252.36 151.21–346.41

2 (300) 0–22 0 (0) 0–1 0 (0) 0–5 189.07 84.05–281.46

Mean C.V. among sites min–max

in autumn–winter months particularly in Mergolo and Grande. Faecal coliforms and enterococci were almost always found in low concentrations in Marsala. 3.3. Trophic state indices The TRIX values pointed out that the studied environments covered a wide range of trophic conditions (Table 3). Verde and Roveto were identified as ‘‘poor” quality water bodies; Ganzirri, Marinello, Piccolo, Grande, Mergolo were classified as ‘‘moderate” quality water bodies, while Marsala, Porto and Faro were identified as ‘‘good” quality water bodies. The annual averages of C:N ratio (Table 1) discriminated two different groups of water bodies. In particular, the predominance of heterotrophic biomasses within POM, evidenced by C:N values lower than 6, was observed in Ganzirri, Faro, Marinello, Mergolo and Roveto. Conversely, the C:N mean values ranging from 6 to 8, recorded in all the other water bodies, indicated the autotrophic

1

)

origin of POM, often associated with a more marked seasonal variability. The N:P ratio (Table 1) showed values close to the theoretical Redfield ratio (N:P = 16:1) in Ganzirri, Faro, Roveto and Central Marsala; Verde, Piccolo, Grande and Northern Marsala were in conditions of P depletion, while Marinello, Mergolo, Porto were N-depleted water bodies.

3.4. Statistical analysis CV values of the POC pool (Table 1) showed that the highest monthly variability occurred in Roveto (CV = 79%), the lowest in Southern Marsala (CV = 32%). High temporal variability of Chl-a was found in all the examined water bodies; the highest CV values were recorded in Porto and in Piccolo (160% and 156%, respectively), the lowest in Marsala (36% on average) (Table 1).

Table 3 Transitional areas groups, as identified by cluster analysis, and variables selected on the basis of their relationships with the trophic state. Abbreviations: similarity coefficient values, S%; CV, coefficient of variation; n, number of samples. Transitional areas

Clusters

Roveto (Vendicari)-Verde (Oliveri-Tindari)

I

Grande-Piccolo (Vendicari)

II

Ganzirri (Cape Peloro) Mergolo-Marinello (Oliveri-Tindari) Faro (Cape Peloro) Porto (Oliveri-Tindari)

III

Northern, Central, Southern (Marsala)

IV

V

POC (lgC l Mean CV (%) n Mean CV (%) n Mean CV (%) n Mean CV (%) n Mean CV (%) n

9052.4 67.2 20 2145.3 58.4 19 918.8 52.2 33 469.9 53.4 22 193.8 36.4 36

1

)

Chl-a (lg l 17.4 78.9 20 3.7 146 19 2.8 89.7 33 1.2 158.5 22 0.5 37.7 36

1

)

LAP (nmol l 238.5 76.9 20 157.2 53.4 19 136.5 32.1 33 126.4 30.9 22 126.9 36.1 36

1

h

1

)

AP (nmol l 241.4 145.5 20 136.8 167.2 19 106.9 130.1 33 51.5 163.3 22 78.2 151.4 36

1

h

1

)

TRIX

S%

6.26 6.0 20 5.38 13.0 19 5.1 9.3 33 4.5 11.4 22 4.3 8.0 36

94.4

86.2

90.4

90.3

95.6

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The spatial variability of LAP values was higher than the temporal variability (maximum CV, 107.31 vs. 83.5, Table 2). Compared to LAP, AP activity rates displayed higher spatial variability (CV range: 84.73–187.46, Table 2); also the temporal variability of AP was high everywhere, as shown by CV values exceeding 100%. Heterotrophic bacteria showed higher spatial (maximum CV 293.31) than temporal variability (average CV 218.7) (Table 2). The CV values of faecal pollution indicators suggested a strong variability in the spatial and temporal distribution of faecal coliforms (maximum CV 346.41 vs. 296.7, respectively), as well as of enterococci (maximum CV 281.46 vs. 313.9, respectively). ANOVA test of POC data showed a number of significant differences among the studied water bodies. Grande and Marsala showed the highest F values (F range = 50.93–108.44, P < 0.01), being statistically very different from all the other sites, and also from each other. Significant differences were also evidenced by the ANOVA analysis of mean Chl-a concentrations. In oligotrophic areas such as Marsala, Chl-a content was very different from that of the most eutrophic environments such as Roveto (F range = 17.7– 17.9, P < 0.001) or Verde (F range = 10.2–18.0, P < 0.001). ANOVA confirmed that, according to LAP values, Verde and Roveto were both statistically different from the other water bodies, particularly from Faro and Southern Marsala (F Verde = 5.09; 5.72, respectively; F Roveto = 5.42; 6.09, respectively), while they were similar to each other. In spite of the strong dissimilarity among the water bodies, POC distribution closely reflected that of Chl-a, as suggested also by the significant correlations found between Chl-a and POC, as well as PON (r = 0.989 and 0.984, P < 0.01, n = 128, respectively). LAP values closely reflected those of Chl-a too, as confirmed by Pearson’s r (0.922, P < 0.01, n = 130). In Ganzirri and Roveto, LAP was significantly related to Chl-a content (r = 0.622, P < 0.05 and 0.811, P < 0.01, respectively), while in Faro and Verde it correlated to DON, calculated as the difference TN-DIN (r = 0.729 and 0.617, P < 0.05, respectively). Significant relationships between POC and PON data (r = 0.989, P < 0.01, n = 130), as well as between Chl-a content and total P (r = 0.889, P < 0.01, n = 130) were observed. From overall data, significant relationships were found comparing POC as well as PON contents to TRIX index values (Fig. 2a and b, R2 = 0.7328, 0.7577, P < 0.01, n = 128). LAP activity rates plotted vs. the TRIX index (Fig. 2c, R2 = 0.1274, n = 130, P < 0.01), pointed out

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also that LAP values increased exponentially with eutrophication rising. 3.5. Cluster analysis The extreme variability in the typologies of the examined water bodies led us to set up an integrated (abiotic + microbiological) approach, developing a panel of selected variables and assessing its suitability for the ecological characterisation of transitional water bodies. Four chemical and biological variables were chosen as selective descriptors of the ecological status of waters. In particular, the set included: POC and Chl-a as direct or strictly related proxies of productive processes, LAP and AP as indicators of the microbial metabolic activity involved in carbon and phosphorus cycling. Particularly, AP was selected due to its high temporal and spatial variability, and LAP due to the significant relationship between the rate of protein decomposition and the trophic level of the waters. For the elaboration of the database, the mean value of each environment was used. Data was subjected to multi-dimensional scaling (MDS) and cluster analysis. Five main clusters were identified from cluster analysis, grouped with different percentages of Similarity; their main characteristics are reported in Table 3. Cluster 1 included both Roveto and Verde; this cluster was characterised by the highest Chl-a and POC values. The high CV values found for the parameters related to particulate matter confirmed the wide variation in organic inputs. The highest LAP and AP rates were observed here. Cluster 2 included Piccolo and Grande, where high POC concentrations were associated with a discrete development of phytoplankton biomass. Microbial decomposition through LAP and AP was an active process. High variability was observed in the temporal distribution of Chl-a and AP. Cluster 3 included Ganzirri, belonging to Cape Peloro, as well as Marinello and Mergolo, belonging to Oliveri-Tindari water system. In these water bodies, Chl-a and POC concentrations, as well as LAP and AP activities, were quite moderate. Cluster 4 included Faro and Porto. Both were characterised by oligotrophy, as indicated by low Chl-a and POC values and reduced LAP and AP activities. Cluster 5 consisted of the three sectors of Marsala. This cluster was characterised by the lowest Chl-a and POC inputs, confirming

Fig. 2. (a–d) Regression analysis of particulate organic carbon (POC) (a) and nitrogen (PON) (b), LAP (c) and AP (d) vs. trophic state (TRIX) index values.

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the typical oligotrophy of this area. Low AP activity rates were also observed.

4. Discussion Transitional water systems are very complex ecotones due to high spatial and temporal variability of physico-chemical characteristics and productivity patterns; the physical variability determines the biological variability and in turn, biological features can be proposed and used as ecological descriptors. The present study aimed at characterising the main Sicilian transitional areas as representative of the second cluster of Italian lagoons (e.g., xero-Mediterranean lagoons, Tagliapietra and Volpi Ghirardini, 2006), but also in the perspective of establishing quality criteria which could be transferred to similar water bodies; this research aimed at contributing to the implementation of the WFD about the transitional waters classification. In fact, to date, no exhaustive method for the evaluation of the trophic status of water is available, that strictly meets the WFD requirements (Pettine et al., 2007). Moreover, while a plethora of methodologies with indices, metrics and evaluation tools have been developed for the benthic compartment classification of both coastal and transitional water systems (see Blanchet et al., 2008; Borja et al., 2000, 2004, 2008a,b; Borja and Dauer, 2008 and references herein; Dauvin et al., 2009; Dell’Anno et al., 2002; Mistri et al., 2008; Munari and Mistri, 2008; Munari et al., 2009; Pusceddu et al., 2007; Vezzulli and Fabiano, 2006; Viaroli et al., 2004), only little attention has been given to the pelagic domain (Giordani et al., 2009; Zaldívar et al., 2008). In addition, the application to transitional waters of the use of the TRIX index – firstly introduced by Vollenweider et al. (1998) to characterise the trophic conditions of Adriatic waters and currently adopted by Italian laws (Decree 152/99 and its upgrading 159/06) – could be reductive or inadequate at a right evaluation of these peculiar environments. The levels of uncertainty about the mechanisms and processes occurring in coastal areas, as well as in other transitional water systems, make it difficult to infer any principles for their management from the assessment of their ecological status (Cognetti and Maltagliati, 2008). For these water systems, it could also be unsuitable to apply the concept of ecological quality status included in WFD (Dauvin, 2007). However, the WFD is still a dynamic Directive, which should allow the incorporation of new methodologies including integrated approaches for monitoring and assessing the status of aquatic systems (Borja, 2005). In this research, high levels of biological abundance and activity characterised the most eutrophic water bodies (Roveto and Verde), in agreement with periodical phytoplankton blooms occurring in their waters. Conversely, low bacterial abundances and activity rates – such as those found in Marsala – reflected lower values of organic inputs. Intermediate values of nutrients and organic inputs were found in the water bodies belonging to Oliveri-Tindari and Cape Peloro. The values of microbial activities, heterotrophic bacteria and particulate organic matter measured in these areas during this study fall within a range similar to that previously recorded (Caruso et al., 2005; Leonardi et al., 2000). Microbial decomposition rates were strictly related to the trophic state, as shown by the close relationship observed between LAP and TRIX, confirming their potential use as surrogate parameters to detect the presence of organic inputs. The different functionality of the studied water bodies was well described by both the trophic (POC, Chl-a) and microbial (LAP, AP) parameters; therefore, the use of these parameters, in association with those already included in the WFD, could represent a promising approach to better characterise the ecological status of the transitional systems. Also Chrost and Siuda (2006) suggested the determination of

microbial activity as an indirect proxy for assessing the trophic state in lakes. On the other hand, the study of bacteria-organic matter interactions is especially important for assessing the quality status of restricted areas, where micro-organisms are known to quickly react to environmental changes, adapting their metabolic profiles to allochthonous and autochthonous inputs (Caruso et al., 2005). In this study, trophic indices such as Chl:POC, N:P, and C:N, usually utilised for the sea waters, were also tested for their suitability to the transitional waters. In particular the Chl:POC ratio did not seem directly applicable to these environments without any correction factor, which employment needs further investigation. On the contrary, the C:N and N:P ratios, normally used in the sea waters (Redfield, 1934), have shown a good applicability also in the transitional systems. C:N ratio values vary in relation to the different occurrences of autotrophic and heterotrophic biomasses and detritus within the particulate organic matter (POM), defining its quality. Consequently, the space–time variability in C:N values give functional information on the trophic status of aquatic systems. Moreover, it was found that these variations can reflect key changes in the phytoplanktonic assemblage dynamics, also in transitional waters (Leonardi et al., 2006, 2009). Moreover, data obtained in this study suggest that the microbial community inhabiting the pelagic compartment responds directly to the inputs of organic matter in terms of POC and Chl-a, as observed also during previous studies (Caruso and Zaccone, 2000; La Ferla et al., 2005); this consideration could support the hypothesis that the pelagic compartment could have a behaviour different from that of the benthic one, where higher organic inputs are not always associated with a higher bacterial response with respect to abundance and frequency of dividing cells (Vezzulli and Fabiano, 2006). This probably reflects the different nature of these two compartments, being the pelagic one more subjected to short-term processes, while the benthic one is more conservative and not prone to rapid changes in its characteristics. Consequently, a different classification should be supposed for transitional areas, depending on their pelagic or benthic concern. This new integrated investigation approach (trophic + microbial) should be helpful in overcoming significant limitations that could arise when considering the TRIX index alone. One example is given by Verde, a water body characterised by a high trophic and metabolic functionality, as proved by Leonardi et al. (2000), which could be downgraded to ‘‘bad” quality water according to its TRIX value, in spite of its high potentiality. On the other hand, in this environment, all the biological processes – in terms of auto- and heterotrophic activities – are particularly stimulated in response to the high trophic supplies, allowing a dynamic nutrient recycling and an active biogeochemistry. The high functionality of this water body is also confirmed by the fact that dystrophic crises are only occasional events, which arise in concomitance of critical climatic conditions, such as high summer temperatures, high pressure, lack of wind (Marino et al., 2003). Therefore, the ‘‘poor” quality status assigned to some water bodies could also be the result of TRIX inadequacy for these peculiar environments, when it is used alone, without appropriate comparisons with other parameters. The inability of TRIX index alone to allow a right classification of different types of coastal waters was also suggested by previous studies (Pettine et al., 2007), which underlined that this index is based on an absolute trophic scale without any normalisation to type-specific reference conditions. In addition, another aspect that must be taken into account is that the shallowness of the water bodies, such as that typical of Vendicari area, which seasonally undergoes evaporation phenomena or is affected by sediment resuspension, hampers the use of ecological descriptors taking into

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account the parameter ‘‘water depth” or ‘‘water transparency” such as the trophic state index (TSI) calculated according to Carlson (1977) equation. Conversely, the classification resulting from the combined use of trophic (POC, C:N) and microbial parameters (LAP, AP), appeared to be quite satisfactory. Moreover, the cluster analysis by MDS, performed using POC, Chl-a, LAP and AP as the main descriptors, allowed to identify at least three main typologies of sub-systems which differed for their trophic conditions, from high (Roveto and Verde) to low (Marsala) and intermediate levels (all the remaining water bodies). Cluster grouping was also well related to the diversity in the geomorphological features of each site; in particular, Marsala was an area in open exchange with the sea, affected by hydrodynamism, while Cape Peloro and Oliveri-Tindari were identified as a separate group, since they displayed characteristics typical of coastal areas. Roveto and Verde, although being different for their own geomorphological nature, showed trophic loads that made them reciprocally similar. The diversity in the geomorphological features is supposed to have important consequences on the ecological and microbial processes that take place in each water body. 5. Conclusion The trophic patterns described by the cluster grouping – obtained on the basis of the new integrated (abiotic + microbial) approach – provided information rather comparable to that obtained by the trophic state (TRIX) index. This led us to consider the microbial variables as suitable descriptors of different environmental conditions. However, in spite of the quantitative information provided by TRIX index alone, which refers to phytoplankton only, and does not enable us to formulate a complete judgement of the ecological features, the panel of parameters proposed here gives a more comprehensive scenario of the trophic dynamics of transitional water systems and allow their more efficient characterisation. Incorporation of microbial variables into the conventional classification schemes developed for assessing the ecological status (Indicators and Methods for the Ecological status assessment under the WFD, EUR 22314EN) could also provide information on ecosystem functioning, that remains largely unknown (Borja et al., 2008a). This integrated approach can be considered as a very simple promising tool for assessing water quality and trophic status, which could also be transferred and applied to other transitional areas. Certainly, the validation of this approach on a broader scale is necessary, since in this study we only considered the Sicilian transitional areas as reference sites representative of xeroMediterranean lagoons. Notwithstanding, it may provide users with a simple tool that gives a comprehensive view of microbial processes and their effects on water biogeochemistry and productive processes. Acknowledgements The research has been funded by Sicilian Agency for Environmental Protection (ARPA-Sicilia) in the framework of the program ‘‘Studies applied to the set up of a Monitoring System devoted to the preliminary characterisation of surface water bodies of Sicilian Region”. The Authors are grateful to Mrs. A. Marini (CNR-IAMC, Messina) for assistance with the chemical analyses. Nutrient data of Marsala were provided by Dr. S. Vizzini-University of Palermo. References Aminot, A., Chaussepied, M., 1983. Manuel d’analyses chimiques en milieu marin. Centre National pour l’Exploration des Oceans, pp. 1–395.

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