Rosa Reboreda

Isabel Caçador
email: micacador@fc.ul.pt

Enzymatic Activity in the Rhizosphere of Spartina maritima: Potential Contribution for Phytoremediation of metals

Keywords: enzyme activity, halophytes, metals, phytoremediation, salt marsh, Spartina maritima EEA (extracellular enzyme activity), -N-acetyl-glucosaminidase

Extracellular Enzymatic Activity (EEA) of five enzymes (peroxidase, phenol oxidase, β-glucosidase, β-N-acetylglucosaminidase and acid phosphatase) was analysed in sediments colonised by Spartina maritima in two salt marshes (Rosário and Pancas) of the Tagus estuary (Portugal) with different characteristics such as sediment parameters and metal contaminant levels. Our aim was a better understanding of the influence of the halophyte on microbial activity in the rhizosphere under different site conditions, and its potential consequences for metal cycling and phytoremediation in salt marshes. Acid phosphatase and β-N-acetylglucosaminidase presented significantly higher EEA in Rosário than in Pancas, whereas the opposite occurred for peroxidase.

This was mainly attributed to differences in organic matter between the two sites. A positive correlation between root biomass and EEA of hydrolases (β-glucosidase, β-Nacetylglucosaminidase and acid phosphatase) was found, indicating a possible influence of the halophyte in sediment microbial function. This would potentially affect metal cycling in the rhizosphere through microbial reactions.

Introduction

Salt marshes usually receive high inputs of contaminants coming from nearby urban areas, river transport and tidal inundation. They are considered to act as sinks for contaminants, namely heavy metals (review by [START_REF] Williams | Metal accumulation within salt marsh environments: a review[END_REF][START_REF] Doyle | Organism-induced accumulation of Fe, Zn and AS in wetland soils[END_REF]. Metals accumulate mainly in the sediments, especially in vegetated areas of the marsh [START_REF] Caçador | Accumulation of Zn, Pb, Cu and Ni in sediments between roots of the Tagus estuary salt marshes, Portugal[END_REF].

It has been shown that halophytes have a dominant role in the metal cycling in salt marshes [START_REF] Otte | A survey of Zn, Cu and Cd concentrations in salt marsh plants along the Dutch coast[END_REF][START_REF] Caçador | Seasonal variation of Zn, Pb, Cu and Cd concentrations in the roots-sediment system of Spartina maritima and Halimione portulacoides from Tagus estuary salt marshes[END_REF]. The roots take up metals, which are mainly accumulated in root tissues and only a small fraction is translocated to the above ground parts of the plants [START_REF] Alberts | Metal concentrations in tissues of Spartina alterniflora (Loisel.) and sediments of Georgia salt marshes[END_REF]. When plants die, litter decomposition leads to the mobilisation of metals and their return to sediment, at a rate that is dependent on the type of tissue but also on plant species [START_REF] Windham | Uptake and distribution of metals in two dominant salt marsh macrophytes, Spartina alterniflora (cordgrass) and Phragmites australis (common reed)[END_REF]. Apart from direct uptake of metals, wetland plants contribute to metal removal through other important processes such as substrate stabilization, rhizosphere oxidation and supply of organic matter for microorganisms [START_REF] Kosolapov | Microbial processes of heavy metal removal from carbon-deficient effluents in constructed wetlands[END_REF].

Microbial activity in sediments is involved in several processes useful for bioremediation of metals, like metal precipitation by sulphate reduction and redox transformations of metals among others [START_REF] Kosolapov | Microbial processes of heavy metal removal from carbon-deficient effluents in constructed wetlands[END_REF]. Wetland plants interact with microorganisms of the rhizosphere by supplying organic matter that is required for such reactions and thus providing an appropriate environment for metal cycling [START_REF] Jacob | Conflicting processes in the wetland plant rhizosphere: metal retention or mobilization? Water[END_REF]. For instance, stimulated sulphate reducing bacteria activity caused by S. maritima colonisation was thought to be one of the reasons for variations in metal sulphides in salt marshes of Ría de Ortigueira, Spain (Otero and Macías, 2002). In fact, some phytoremediation strategies involve inoculation of plants with rhizosphere microbiota and arbuscular mycorrhiza [START_REF] Khan | Role of soil microbes in the rhizospheres of plants growing on trace metal contaminated soils in phytoremediation[END_REF].

Enzymes activities are a useful index of microbial activity [START_REF] Sinsabaugh | Enzymatic analysis of microbial pattern and process[END_REF][START_REF] Ravit | A comparison of sediment microbial communities associated with Phragmites australis and Spartina alterniflora in two brackish wetlands of New Jersey[END_REF]. Enzymes can exist extracellularly in sediments, attached to clay minerals or complexed with humic colloids [START_REF] Burns | Enzyme activity in soil: location and a possible role in microbial ecology[END_REF]. Extracellular enzymes excreted by fungi and bacteria effectively metabolize humic compounds reducing their molecular weight, consequently increasing the solubility and mobility of these potential carriers of heavy metals [START_REF] Gramss | Degradation of soil humic extract by wood-and soil-associated fungi, bacteria and commercial enzymes[END_REF]. The enzyme activity assay gives the maximum potential activity of enzymes occurring in sediment rather than the actual enzyme activity (Alef and Nannipieri, 1995).

In this paper we compared the EEA (Extracellular Enzymatic Activity) of five enzymes in sediments colonised by Spartina maritima in two salt marshes of the Tagus estuary (Portugal) with marked differences in their characteristics such as sediment parameters and metal contaminant levels [START_REF] Caçador | Relationships between metal concentrations and organic matter content in the Tagus estuary salt marsh sediments[END_REF]. Our aim was to compare the possible influence of the plant on the microbial function of the rhizosphere under different site conditions. This would help to elucidate how halophytemicroorganism interactions may contribute for the potential use of halophytes in phytoremediaton of metal contaminated environments.

Materials and Methods

Site description

Between February-March 2005 five sediment cores were collected in areas colonised by Spartina maritima in each of two salt marshes of the Tagus estuary: Rosário (38º 40'N, 9º 01'W) and Pancas (38º 48'N, 8º 55'W). Rosário is a mature salt marsh [START_REF] Valiela | Role of salt marshes as part of coastal landscapes[END_REF] with muddy sediments located in the southern part of the estuary, in the vicinity of urbanised and industrial areas. Pancas is a young salt marsh [START_REF] Valiela | Role of salt marshes as part of coastal landscapes[END_REF] with muddy-sand sediments located in the northeast part of the estuary, within the Tagus Nature Reserve. Distance between these sites is about 18 km.

The studied salt marshes contain extensive intertidal mudflat areas colonised by halophyte plant communities dominated by Spartina maritima (Curtis) Fernald, Halimione portulacoides (L.) Aellen, Sarcocornia fruticosa (L.) A. J. Scott and Sarcocornia perennis (Mill.) A. J. Scott. These sites experience two tidal flushing a day (for a more detailed description of the estuary see [START_REF] Caçador | Accumulation of Zn, Pb, Cu and Ni in sediments between roots of the Tagus estuary salt marshes, Portugal[END_REF]). Rosário presents higher levels of metal contamination than Pancas (Table 1, after [START_REF] Caçador | Retention of Heavy Metals in Salt Marshes and Estuarine Water Quality Metals in the Environment: Analysis by Biodiversity[END_REF].

Sampling

Collection of samples was made at low tide. Sediment was removed using a stainless steel corer with 6.8 cm inner diameter and 50 cm depth. In the field, cores were sliced to separate the following segments: 0-5 cm, 10-15 cm and 40-45 cm. These segments were expected to be representative of surface sediment, sediment with high root biomass and deep sediment with little or inexistent root influence, respectively.

Redox potential (Eh) and pH values of fresh sediment were determined in situ using a HANNA pH/mV meter (HI 9025). The samples were placed in plastic bags and transported to the laboratory refrigerated. Those samples for determination of enzymatic activity were frozen at -20ºC until enzymatic analysis was carried out [START_REF] Kuperman | Soil heavy metal concentrations, microbial biomass and enzyme activities in a contaminated grassland ecosystem[END_REF]. Root biomass was determined in fresh sediment separating root material from sediment and then drying to constant weight at 70ºC [START_REF] Gross | Relationship between aboveground and belowground biomass of Spartina alterniflora (smooth cordgrass)[END_REF].

Sediment parameters

Sediment (~20 g) was dried 48 h at 60ºC and relative moisture calculated (percentage of fresh weight). In order to determine organic matter content (LOI, loss on ignition) 2g of dry sediment was burned at 600ºC for 2 hours.

Enzyme activities in sediment

Enzymatic activity of 5 enzymes (two oxidoreductases and three hydrolases)

was analysed: phenol oxidase, peroxidase, -glucosidase, acid phosphatase and -Nacetylglucosaminidase (chitobiase). These enzymes are involved in metabolic processes (5 mM) following the same procedure: 2 ml slurry + 2 ml substrate (adding 0.1 ml of 0.3% H 2 O 2 for peroxidase). Incubation time was 60 min for both enzymes, followed by centrifugation. Absorbance of supernatant was read on a TECAN Absorbance Microplate Reader (SPECTRA Rainbow) at 410 nm for pNP enzymes and at 460 nm for L-DOPA enzymes. Absorbance for phenol oxidase was substracted from absorbance of peroxidase total (which assay gives the activity of peroxidase + phenol oxidase) in order to calculate absorbance for peroxidase alone. Controls of sediment slurry and substrate were made, and their absorbance subtracted from the absorbance read for each sample. Enzymatic activity was expressed as moles product g dry wt -1 h -1 .

Statistic analyses

Significant differences in soil characteristics between sites were tested using one-way ANOVA. Significant differences in extracellular enzymatic activities between the two sites at the different depths were compared using one-way ANOVA. The same analysis was used to test differences with depth at each site separately. This was followed by a Tukey-HSD test when appropriate. Pearson's coefficient was calculated to test correlation between activities of different enzymes and correlation between enzymes activities and soil characteristics.

Results and discussion

Sediment characteristics (Eh, pH, LOI, relative moisture) and root biomass of S.

maritima in Rosário and Pancas are shown in Table 2. Sediment redox potential (Eh) was significantly higher (p<0.05) in Pancas, except on the surface, where Rosário showed significantly higher Eh. Organic matter (LOI) and moisture were significantly higher (p<0.05) in Rosário at every depth studied in areas colonised by S. maritima, whereas pH was significantly higher in Rosário only at the root depth (10-15 cm). Root biomass of S. maritima was significantly higher in Rosário than in Pancas (p<0.05).

The extracellular enzymatic activity (EEA) of peroxidase was much higher (up to 10 fold) than the EEA of the other four enzymes at every depth studied (Figure 1).

The dominance of peroxidase over hydrolytic enzymes may indicate the presence of refractory organic matter in the salt marsh [START_REF] Sinsabaugh | Soil microbial activity in a Liquidambar plantation unresponsive to CO 2 -driven increases in primary production[END_REF]. Gramss et al.

(1999) demonstrated that extracellular enzymes released by fungi and bacteria, as well as commercial enzymes including peroxidase and β-glucosidase, were able to effectively metabolize soil humic extracts (to which heavy metal ions and xenobiotics are potentially attached), reducing their molecular weight and consequently increasing their solubility and motility. Therefore, high extracellular activity of peroxidase in sediments colonised by S. maritima might influence the mobilization of metals in the studied salt marshes. In addition to supplying plant litter for decomposition, the halophyte may contribute to high EEA of peroxidase by the release of peroxidases from plant roots [START_REF] Salt | Phytoremediation[END_REF]. However, it should be taken into account that the EEA assay gives the maximum potential activity of enzymes occurring in sediment rather than the actual enzyme activity (Alef and Nannipieri, 1995).

When comparing EEA's in sediments colonised by S. maritima in Rosário and Pancas, significant differences were observed for peroxidase, acid phosphatase and chitobiase (p<0.05) (Figure 1). Peroxidase presented higher EEA in Pancas than in Rosário, whereas acid phosphatase and chitobiase presented higher EEA in Rosário than in Pancas. Correlation coefficients between EEA's and sediment characteristics revealed that acid phosphatase and chitobiase activities were positively correlated with organic matter content and moisture (Table 3). In addition, chitobiase activity was positively correlated with pH. A negative correlation occurred between EEA of peroxidase and organic matter content. These results suggest that differences in the organic matter content between the two sites could partly explain the observed pattern in extracellular activities of the enzymes in areas colonised by S. maritima. Higher organic matter content and moisture in sediment from Rosário seemed to be related to higher EEA's of acid phosphatase and chitobiase (also influenced by higher pH) in this salt marsh, whereas peroxidase activity was higher in Pancas, where organic matter content of the sediment was lower. Results from [START_REF] Caçador | Carbon storage in Tagus salt marsh sediments[END_REF] showed that litter decomposition in Pancas was faster than in Corroios, another salt marsh with characteristics similar to Rosário (located about 12 Km to the southwest from this) [START_REF] Caçador | Relationships between metal concentrations and organic matter content in the Tagus estuary salt marsh sediments[END_REF]. This may be related to higher activities of peroxidase in Pancas, as it is involved in the degradation of complex organic compounds. There was no correlation between EEA's and redox potential of the sediment. This was surprising, especially for phenol oxidase, that needs O 2 for its activity. An oxygen limitation on phenol oxidase is associated with inhibition of hydrolytic enzymes in peatlands through accumulation of phenolic compounds [START_REF] Freeman | An enzymic 'latch' on a global carbon store[END_REF][START_REF] Freeman | A regulatory role for phenol oxidase during decomposition in peatlands[END_REF]). The low EEA observed for phenol oxidase (in the same order of magnitude as the hydrolases) is likely to be caused by O 2 limitation in the sediment, since it is expected to be scarce in salt marsh sediments. Although no reductive conditions were found in the sediments studied (positive Eh) it should be taken into account that it does not indicate abundance of O 2 , as other oxidant compounds could be present. Accumulation of phenolic compounds due to restricted phenol oxidase activity would have important consequences for the cycling of heavy metals in the salt marsh, since phenols are known to bind metals [START_REF] Ambrosi | Heavy metal ion complexes with a simple phenolic ligand. Solid state and solution studies[END_REF][START_REF] Mota | Influence of the sediment on lead speciation in the Tagus estuary[END_REF].

Hydrolytic enzymes activities ( -glucosidase, acid phosphatase and chitobiase)

were positively correlated with root biomass of S. maritima (Table 3). Microbial activity is stimulated around plant roots through exudation of organic anions and sugars [START_REF] Ryan | Function and mechanism of organic anion exudation from plant roots[END_REF]. Karjalainen et al. (2001) found that Lobelia dortmanna L., a submersed plant species, enhanced microbial activity and biomass in sediments through organic carbon release. Thus, it would be reasonable that higher root biomass would result in higher exudation of organic compounds, enhancing microbial activity around plant roots. [START_REF] Burke | Interactions among plant species and microorganisms in salt marsh sediments[END_REF] found a positive interaction between a group of Protobacteria and root biomass of Spartina patens and Phragmites australis in salt marsh sediments. The release of soluble sugars by roots supply the substrates needed by -glucosidase and chitobiase (β-N-acetylglucosaminidase), probably inducing the excretion of higher amounts of these enzymes by microorganisms [START_REF] Burns | Enzyme activity in soil: location and a possible role in microbial ecology[END_REF]. In spite of this, -glucosidase activity was not significantly higher in sediment from Rosário, where S. maritima root biomass was significantly higher (Figure 1; Table 3).

This might be caused by an inhibition of this enzyme in the presence of higher metal concentrations in Rosário (Table 1) (Geiger et al., 1998). Exudation of phosphatases from plant roots is one of the strategies used by plants to cope with P deficiency [START_REF] Ryan | Function and mechanism of organic anion exudation from plant roots[END_REF]. This might be a strategy of S. maritima as well, given the correlation found between acid phosphatase activity and root biomass of the plant (Table 3). [START_REF] Ravit | Macrophytes and microbes: Spartina alterniflora and Phragmites australis affect brackish sediment microbial community structure and function[END_REF] concluded that, in salt marsh environments of the USA, the sediment microbial community structure and function is determined by the interaction of hydrological conditions and the effect of plant roots. From the observed results we deduce that S. maritima roots could influence the extracellular enzymatic activity of the hydrolytic enzymes analysed and, accordingly, it may affect the microbial function in the rhizosphere of the plant in Tagus estuary salt marshes. Given the importance of microbially mediated reactions in metal cycling around plant roots in wetlands [START_REF] Jacob | Conflicting processes in the wetland plant rhizosphere: metal retention or mobilization? Water[END_REF], and the proposed use of halophytes like S. maritima for phytostabilization of metals in metal contaminated salt marshes [START_REF] Reboreda | Halophyte vegetation influences in salt marsh retention capacity for heavy metals[END_REF]Reboreda et al., In press), the halophyte-microorganism interactions arise as an additional concern for phytoremediation studies.

Variations in EEA with depth were only significant (p<0.05) for -glucosidase and acid phosphatase from Rosário. Still, enzymatic activities were in general lower in the horizon 40-45 cm, most likely as a consequence of low organic matter content and oxygen availability (Table 2). In Pancas, the lack of significant differences in EEA with depth (p>0.05) was surprising considering the 2-orders of magnitude change in root biomass and organic matter (Table 2). Other sediment parameters such as grain size (muddy-sand in Pancas; Reboreda et al., in press) may have a stronger effect on enzymes distribution [START_REF] Kandeler | Structure and function of the soil microbial community in microhabitats of a heavy metal polluted soil[END_REF].

In Rosário, EEA's of -glucosidase and chitobiase were positively correlated with EEA of phenol oxidase (Table 4). This might suggest a similar behaviour of these enzymes, in organic matter rich/oxygen limited salt marshes, as that found by [START_REF] Freeman | An enzymic 'latch' on a global carbon store[END_REF] and [START_REF] Freeman | A regulatory role for phenol oxidase during decomposition in peatlands[END_REF] in peatlands, which was described above. EEA of -glucosidase also showed correlation with peroxidase activity. There were no significant correlations between EEA's of the studied enzymes in Pancas.

Conclusions

Sediments colonised by S. maritima show differences in some extracellular enzymes activities between salt marshes in the Tagus estuary, which appears to be related to differences in sediment organic matter and root biomass. The results support the idea that S. maritima could influence to some extent the microbial function in the rhizosphere, which in turn may potentially influence microbially mediated metal cycling in the sediment. In addition, site characteristics seem to play a relevant role in enzymatic activity as well, given the differences observed between the two sites.

Consequently, we suggest that halophyte-microorganism interactions are worthy of further study for its usefulness in phytoremediation strategies.

Acknowledgements

  such as C cycling (β-glucosidase, catalyzes the final step of cellulose degradation), N and C cycling (β-N-acetylglucosaminidase, hydrolyzes the glucosamine), P cycling (acid phosphatase, hydrolyzes organic-P compounds) and decomposition of plant litter (phenol oxidase, catalyzes polyphenol oxidation; and peroxidase, catalyzes the oxidation of various compounds such as phenols and amines). We used the method described in[START_REF] Ravit | A comparison of sediment microbial communities associated with Phragmites australis and Spartina alterniflora in two brackish wetlands of New Jersey[END_REF] with a modification in the incubation temperature and without dilution of the supernatant. Sediment samples were prepared for analysis adding 75 ml of sodium acetate buffer (pH 5) to 5 g fresh sediment. The sample was mixed for 1 min to obtain the sediment slurry. The substrates used for -glucosidase, acid phosphatase and -N-acetylglucosaminidase (chitobiase) were p-Nitrophenyl--Dglucopyranoside, p-Nitrophenyl phosphate and p-Nitrophenyl-N-acetyl--Dglucosaminide, respectively. All of them released p-nitrophenol (pNP) when hydrolized.Two millilitres of substrate (5 mM) was added to 2 ml of the slurry in a test tube and incubated at 30ºC in gentle agitation for 60 min ( -glucosidase), 30 min (acid phosphatase) and 2 hours (chitobiase). After incubation the samples were centrifuged at 2000 rev min -1 for 15 min and 0.2 ml of 1 N NaOH was added immediately to stop the reaction and cause colour change. Determination of phenol oxidase and peroxidase activities was carried out using L-DOPA (L-3,4-dihydroxyphenylalanine) as substrate

Figure 1 .

 1 Figure caption

Table 1 .

 1 Concentrations (mean ± standard deviation) of Zn, Pb, Cu and Cd (µg g -1 dry weight) in surface sediments (0-5 cm) ; intermediate rooted sediment layers (10-15 cm) and deeper layers (40-45 cm) in areas colonised by Spartina maritima, from Pancas and Rosário salt marshes (after[START_REF] Caçador | Retention of Heavy Metals in Salt Marshes and Estuarine Water Quality Metals in the Environment: Analysis by Biodiversity[END_REF]

	Sites	Depth (cm)	Zn µg g -1 dw	Pb µg g -1 dw	Cu µg g -1 dw	Cd µg g -1 dw
	Pancas	(0-5)	95+17	42+4	22+3	1.1+0.2
		(10-15)	177+18	53+4	33+6	1.3+0.1
		(40-45)	93+5	43+9	14.7+3	0.4 + 0.1
	Rosário	(0-5)	402+ 27	395 +16	51+ 2	1.2 +0.2
		(10-15)	1169+ 74	577+ 21	78+ 15	1.7 +0.2
		(40-45)	98+ 10	55.3+ 11	12.7+ 3	0.4 +0.1

Table 3 .

 3 Correlation coefficients (Pearson's) between sediment characteristics and extracellular enzymatic activities of phenol oxidase, peroxidase, -glucosidase, acid phosphatase and chitobiase in salt marsh sediments colonised by Spartina maritima. * Correlation is significant at the 0.01 level.

		Eh (mV) pH	LOI (%) Moisture (%) Biomass (g m -2 )
	Phenol ox.	0.48	-0.01	-0.38	-0.17	-0.13
	Peroxidase	0.46	0.00	-0.54*	-0.31	-0.11
	β-glucosidase	0.32	0.46	0.26	0.31	0.86**
	Phosphatase	0.47	-0.05 0.70**	0.51*	0.58*
	Chitobiase	-0.17	0.57*	0.69*	0.59*	0.88**
	* Correlation is significant at the 0.05 level.

*

Table 4 .

 4 Correlation between the activities of phenol oxidase, peroxidase, βglucosidase, acid phosphatase and chitobiase in sediments of Rosário and Pancas colonised by S. maritima (Pearson's Correlation). * Correlation is significant at the 0.01 level.

		Enzyme	Phenol ox.	Peroxidase	β-gluc	Phosphatase Chitobiase
		Phenol ox.
	Rosário	Peroxidase β-glucosidase Phosphatase	0.454 0.591* 0.211	0.650* 0.198	0.398
		Chitobiase	0.707**	0.473	0.796**	0.530
		Phenol ox.
	Pancas	Peroxidase β-glucosidase Phosphatase	0.497 0.089 0.025	-0.230 0.192	-0.046
		Chitobiase	-0.079	0.328	0.204	0.033
	* Correlation is significant at the 0.05 level.

*


PhD Daniela Cianelli
email: daniela.cianelli@uniparthenope.it

L Manfra

E Zambianchi

C Maggi

A Cappiello

G Famiglini

M Mannozzi

A M Cicero

Near-field dispersion of Produced Formation Water (PFW

Keywords: Produced Formation Waters, Dispersion, Modelling, Chemical tracer analysis, Adriatic Sea, Environmental Monitoring

published or not. The documents may come

Introduction

A number of offshore natural gas (CH 4 ) extraction platforms are currently active in the Adriatic Sea (Mediterranean Sea). During production, Produced Formation Water (PFW), a by-product of both oil and gas extraction originated from water naturally present in geological formations (Formation Water) and water injected in the oil field (Process Water) to maintain reservoir pressure [START_REF] Henderson | Potential impact of production chemical on the toxicity of produced water discharges from North Sea oil platforms[END_REF], is brought to the surface. PFW contains inorganic compounds (i.e. trace metals), volatile aromatic compounds (benzene, toluene, ethylbenzene, xylenes), semivolatile substances (i.e. naphthalene, phenanthrene, dibenzothiophene), phenols, organic acids and additives [START_REF] Manfra | Metal content and toxicity of produced formation water (PFW): study of the possible effects of the discharge on marine environment[END_REF]. PFW is separated from the hydrocarbons on the platforms and then discharged into the sea, where potential effects on biota may occur [START_REF] Neff | Bioaccumulation in Marine Organisms[END_REF][START_REF] Osenberg | Spatial scale of ecological effects associated with an open coast discharge of produced water[END_REF][START_REF] Grant | Toxicity of sediments from around a North Sea oil platform: are metals or hydrocarbons responsible for ecological impacts[END_REF][START_REF] Cicero | Monitoring of environmental impact resulting from offshore oil and gas installations in the Adriatic Sea: preliminary evaluations[END_REF][START_REF] Trabucco | Study of the soft bottom macrozoobenthic community around an offshore platform central Adriatic sea[END_REF]. This makes the investigation of the physical and chemical characteristics of PFWs extremely important from the environmental standpoint.

After discharge, PFWs may be affected by several different processes, such as dispersion into the sea, volatilization towards the atmosphere and settling at the bottom. In particular, the first main process occurring immediately after discharge is the mixing of the PFW plume with the ambient fluid which determines an immediate PFW dilution and the reduction of its concentration in the sea water (e.g. [START_REF] Baumgartner | Dilution models for effluent discharges (Third Edition)[END_REF].

In the last decade relevant works published on PFW dispersion (e.g., [START_REF] Berry | Integrated fate modeling for exposure assessment of produced water on the Sable Island Bank (Scotian Shelf, Canada)[END_REF][START_REF] Nedwed | Verification of the OOC mud and produced water discharge model using lab-scale plume behaviour experiments[END_REF] showed the importance of using numerical methods to investigate the fate of PFWs discharged in coastal areas. [START_REF] Washburn | Dispersion of produced water in a coastal environment and its biological implications[END_REF] demonstrated, by means of a field and modeling study around a diffuser located in California, that a factor controlling the exposure of organisms to PFWs around the discharge location is the depth of the plume in the water column which, in turn, is modulated by seasonal stratification. Realistic calculations of the fate of the PFW components after discharge and different tools for estimation of environmental exposures at various levels of contaminant have also been developed [START_REF] Sabeur | Validation and application of the PROTEUS model for the physical dispersion, geochemistry and biological impacts of produced waters[END_REF][START_REF] Neff | Oil well produced water discharges to the North Sea. Part II: Comparison of deployed mussels (Mytilus edulis) and the DREAM model to predict ecological risk[END_REF][START_REF] Durell | Oil well produced water discharges to the North Sea. Part I: Comparison of deployed mussels (Mytilus edulis), semipermeable membrane devices, and the DREAM model predictions to estimate the dispersion of polycyclic aromatic hydrocarbons[END_REF]. Moreover chemical tracer studies have been recognized as an efficient method to accurately describe PFW pathways into the sea as well as to predict concentrations of both drilling mud and produced water in detail (Smith et al., 2004). Applying a combination of oceanographic techniques and chemical assessment methods on the Australian Shallow Water Ecosystem, [START_REF] Burns | Dispersion and Fate of Produced Formation Water Constituents in an Australian Northwest Shelf Shallow Water Ecosystem[END_REF] suggested that fast rates of dispersion and degradation processes may prevent any long-term contamination in the sandy sediments.

The few studies carried out on this topic for the North Adriatic area pointed out that the short term influence of the natural gas platform structures on surrounding sediments is related more to the installation phase than to the subsequent extraction phase [START_REF] Fabi | Methods of assessing the ecological impact of gas platforms in the Adriatic Sea: two different scenarios[END_REF].

Metal (Zn and As) accumulation [START_REF] Cicero | Monitoring of environmental impact resulting from offshore oil and gas installations in the Adriatic Sea: preliminary evaluations[END_REF][START_REF] Manfra | Metal content and toxicity of produced formation water (PFW): study of the possible effects of the discharge on marine environment[END_REF] in sediments and mussels (Mytilus galloprovincialis), as well as influences on benthic communities [START_REF] Trabucco | Study of the soft bottom macrozoobenthic community around an offshore platform central Adriatic sea[END_REF], have been observed at locations very close to the platforms. On the other hand no literature is available, to our knowledge, on the identification of PFWs in the Mediterranean Sea by means of chemical tracers and the use of numerical models to investigate the near field dispersion of PWFs in the Adriatic area.

In this paper we present the results of an integrated numerical-chemical approach developed to investigate the initial mixing of the PFWs discharged from three offshore natural gas platforms located in the Northern Adriatic Sea. Our research is primarily conceived to relate field and laboratory observations with the near field dilution processes through a numerical process study. The present study introduces a multidisciplinary methodology for the estimation of the presently available monitoring protocol efficiency, as well as the potential effects induced on marine systems by PFW discharges in the Adriatic Sea.

A typical method to reconstruct the path of the PFW into the sea consists of adding tracer dyes to the effluent before the discharge [START_REF] Roldão | Evaluation of sewage outfalls by using tracer techniques combined with oceanographic measurements[END_REF][START_REF] Carvalho | Field Observations of Ipanema Beach Outfall[END_REF]. The restrictive regulations of offshore platforms often make this approach impractical. In the present work, in order to follow the PFW plume within the marine environment and investigate its dispersion, we analyzed the PFWs' chemical composition and identified some possible chemical tracers of these effluents. We assessed the concentrations of the main groups of compounds typical of produced waters originating from natural gas platforms.

Metal concentrations were often under detection limits, while the volatile and semivolatile aromatic hydrocarbons have not always been quantifiable. For polycyclic aromatic hydrocarbons, it was difficult to separate the platform and anthropic contributions. On the basis of these analyses, two chemical additives, diethylene glycol and toluene hydrossibutilate, proved to be the most suitable tracers of the PFWs [START_REF] Manfra | Dispersione in mare delle acque di produzione e valutazione ecotossicologica degli effetti indotti[END_REF].

We here report the data relative to the diethylene glycol (DEG), which provided the best affordable chemical tracer among the investigated substances. DEG is an additive used on offshore gas platforms to prevent the hydrate formation during the gas-water separation process and to inhibit corrosion events [START_REF] Ballantyne | Developmental toxicity study with diethylene glycol dosed by gavage to CD rats and CD-1 mice[END_REF][START_REF] Ferrari | Clinical parameters, postmortem analysis and estimation of lethal dose in victims of a massive intoxication with diethylene glycol[END_REF].

The estimate of DEG concentrations in both PFW and seawater samples collected at different distances from the platforms led us to select DEG as PFW tracer. This choice also takes into account that the DEG presence in seawater is exclusively attributable to the PFW discharge and that it is miscible in water, thus allowing tracing of the PFW plume [START_REF] Company | Water-Base Flexographic Ink, Material Safety Data Sheet MSDS[END_REF]. Moreover it is worth noting that the competent authorities permit the addition of high DEG concentrations (maximum values of 3500 ppm) to PFWs and these may be easily tracked in the seawater.

In this work we focus on the entrainment and initial dilution processes that have been reproduced in the regions of our three platforms by means of the UM3 (Three Dimensional Update Merge) numerical model widely and successfully applied [START_REF] Baumgartner | Dilution models for effluent discharges (Third Edition)[END_REF][START_REF] Frick | Dilution models for effluent discharges, 4th Edition, Visual Plumes[END_REF] by the US Environmental Protection Agency to simulate the near field mixing. The overall study area, the northern Adriatic Sea, is a shelf zone, characterized by depths less than 200 m, where the circulation system shows a relevant seasonal variability (e.g. Artegiani et al., 1997a-b). As previous theoretical and experimental studies demonstrated [START_REF] Wu | Buoyant plume dispersion in a coastal environment: Evolving plume structure and dynamics[END_REF][START_REF] Petrenko | Shape and near-Þeld dilution of the Sand Island sewage plume observations compared to model results[END_REF], stratification and current variability around the discharge location are critical for the effluent dispersion. Our simulations are realized in different seasonal conditions (summer and winter) using as model input historical current data and density profiles of the receiving water body as well as the actual outfall pipe characteristics. Measured concentrations of the DEG tracer represent another numerical input.

Model results are designed to describe the initial dilution phase of the plume and the extent to which water column stratification and ambient currents affect its dynamics. These results are compared with those of the chemical analyses relative to the tracer concentrations observed in the receiving waters.

Using oceanographic observations to reproduce the ambient conditions and initial concentrations of the chemical tracer in the PFW, the UM3 model has proven to be able to predict the initial dilution of the PFW from the three investigated platforms in the Adriatic Sea. The integrated approach has allowed us to evaluate the temporal and spatial distribution of the effluent and has provided suggestions to plan and optimize the PFW discharge protocols as well as the monitoring strategy.

Materials and methods

Field data

In this work we consider three platforms located in the northwestern Adriatic Sea (Fig. 1) As mentioned above, this portion of the basin is characterized by a very wide and shallow continental shelf, and the overall main current in the area is represented by the Western Adriatic Current (WAC), a southeastward coastal current flowing along the Italian coast [START_REF] Falco | Transport properties in the Adriatic Sea as deduced from drifter data[END_REF] The water column depth at the platforms ranges between 18 and 120 m (Table I); the PFWs are discharged from a single port outfall pipe oriented downward at the depths from 3 m above the sea surface to 12 m depth (Table 1).

The data utilized in this study come from two monitoring surveys carried out in the summer of [START_REF] Company | Water-Base Flexographic Ink, Material Safety Data Sheet MSDS[END_REF]and 2006[START_REF] Manfra | Dispersione in mare delle acque di produzione e valutazione ecotossicologica degli effetti indotti[END_REF]: the PFWs were sampled on all three gas platforms Surface currents have been derived from historical surface Lagrangian drifter measurements in the Adriatic Sea from 1994 to 1996 (Falco et al., 2000) (Fig 1). They indicate current values in a range from a minimum of 3 cm s -1 to a maximum of 18 cm s -1 (Table I) with a southeastward prevailing direction in the area of the platforms, corresponding to the above mentioned WAC. These data were complemented with ADCP data collected between May 1995 and February 1996 (Ursella and Ga i , 2001). Current speeds were considered as uniform with depth down to two meters above the bottom (a typical order of magnitude for the logarithmic bottom boundary layer thickness in both shelf and deep ocean; see [START_REF] Nakata | Observation of the bottom boundary layer on the continental shelf[END_REF][START_REF] Gust | Velocities, turbulence, and skin friction in a deep-sea logarithmic layer[END_REF], where the profile assumed a logarithmic shape and a no slip condition was applied.

Chemical analyses

For DEG analysis, the samples were preconcentrated by an off-line solid phase extraction technique (SPE), which provides a concentration factor of about 500 and avoids problems connected to the different salinity of the samples [START_REF] Cappiello | Application of NANOFIA-MS to determine diethylene glicol in produced formation water and seawater samples (Adriatic Sea)[END_REF]. Each sample was introduced into a cartridge packed with 200 mg of ISOLUTE ENV+, an adsorbent material suitable for polar compounds (International Sorbent Technology, Glamorgan, UK). The cartridge was conditioned beforehand with 15 ml of acetone and then with 10 ml of deionized water. 100 ml of each sample was forced through the cartridges at a flow rate of 5 ml min -1 . DEG was eluted with 8 ml of acetone. The extract was evaporated to a volume of 200 µl under a gentle stream of nitrogen and 200 µl of deionized water were then added; finally, after a complete evaporation of the acetone, DEG remained dissolved in 200 µl of water.

The extract was introduced into the mass spectrometer (Hewlett-Packard 5989A) using a Direct-EI, LC-MS interface in Flow Injection Analysis (FIA) mode [START_REF] Cappiello | A simple approach for coupling liquid chromatography and electron ionization mass spectrometry[END_REF].

The Direct-EI interface shows several advantages in this specific application: high specificity, very low influence of the mobile phase and matrix composition [START_REF] Choi | LC-MS/MS signal suppression effects in the analysis of pesticides in complex environmental matrices[END_REF][START_REF] Reemtsma | The use of liquid chromatography-atmospheric pressure ionizationmass spectrometry in water analysis -Part II: Obstacles[END_REF]. In particular, residues of salts in the extracts do not affect mass spectral response.

Identification of DEG was obtained in Selected Ion Monitoring analysis (SIM) using three characteristic ions (m/z 45, 75 and 76). M/z 75 signal was used in quantitation experiments.

The limit of detection (LOD) of the method, expressed as the minimum concentration of the DEG that can be detected in the sample, was 31 µg l -1 . The percentage of recovery for this method was 65.0 ± 16.3 % [START_REF] Cappiello | Application of NANOFIA-MS to determine diethylene glicol in produced formation water and seawater samples (Adriatic Sea)[END_REF] but further studies are currently in progress in order to improve the sensitivity of method.

UM3 model

The near field dilution is the initial mixing process of an effluent discharged into the sea, due to the combined effects of momentum and buoyancy and acting close to the effluent diffuser [START_REF] Baumgartner | Dilution models for effluent discharges (Third Edition)[END_REF].

In the present work the dispersion of a PFW plume in the near field has been simulated by means of the UM3 (Three-dimensional Updated Merge) model specifically conceived for single and multi-port submerged discharges [START_REF] Baumgartner | Dilution models for effluent discharges (Third Edition)[END_REF][START_REF] Frick | Dilution models for effluent discharges, 4th Edition, Visual Plumes[END_REF] and included in the EPA interface PLUMES (http://www.epa.gov/ceampubl/swater/vplume).

Compared with other models for the near field mixing, UM3 provides a good prediction of the initial dilution processes for both waste-water [START_REF] Carvalho | Field Observations of Ipanema Beach Outfall[END_REF] and PFWs discharges [START_REF] Roberts | New Experimental Techniques for Validation of Marine Discharge Models[END_REF]; moreover, strictly dealing with produced water discharges, UM3 has proven to accurately reproduce the observed dilutions [START_REF] Roberts | New Experimental Techniques for Validation of Marine Discharge Models[END_REF].

UM3 is a three-dimensional Lagrangian model that quantifies entrainment, the process by which ambient fluid is incorporated into a plume, by applying both the Taylor entrainment (or shear) and the projected-area-entrainment (PAE) (or forced) hypotheses (e.g. [START_REF] Winiarski | Cooling tower plume model[END_REF]. The equations for conservation of mass, momentum and energy are computed at each time step along the plume trajectory.

The dilution process may be considered the outcome of entrainment; it may be enhanced or inhibited by outfall pipe, ambient fluid and effluent properties [START_REF] Baumgartner | Dilution models for effluent discharges (Third Edition)[END_REF] which the UM3 model takes into account as model inputs. In particular, the model considers the diameter and the orientation of the port as well as the depth of discharge as the outfall pipe features which may affect the effluent velocity and the plume trajectory.

The receiving ambient fluid properties are described by means of vertical profiles of density, which is the main variable affecting plume buoyancy. The effluent and the ambient density typically differ and the entrainment process tends to cancel this difference; when an equilibrium condition is reached (s.c. neutral buoyancy level, or trap level) the initial mixing process terminates. The current velocity and direction close to the point of discharge are also important features affecting plume dynamics. The former parameter may increase the shear between plume and ambient fluid thus contributing to the production of turbulence that directly influences the dilution; the second mainly acts on the plume trajectory [START_REF] Frick | Dilution models for effluent discharges, 4th Edition, Visual Plumes[END_REF]. The current profile used in our computations was obtained as described above, in the section on "Field data".

The UM3 model provides output parameters useful to evaluate the space and time evolution of the effluent. The PFW dilution is parameterized through the mass dilution factor (S a ), which is the ratio between the effluent concentration and the cross sectional average concentration in the plume. For a round shaped outfall, the densimetric Froude number [START_REF] Brandsma | Modeling offshore discharges of produced water[END_REF], which provides an estimate of the relative importance of momentum and buoyancy in driving the initial mixing, is defined as:

1) where D is the outfall pipe port diameter, a the ambient density at depth of the port, e the effluent density and g is gravity. U 0 represents the effluent outflow velocity and is given by:

2

)
with q is the volume flux at outfall pipe port.

In order to characterize the stability of the water column at discharge depth we

Results and discussion

The numerical and chemical results on PFWs discharged by three gas platforms are here

2 0 4 D q U ⋅ = π 2 1 ∂ ∂ - = z g N ref ρ ρ 2 1 ∆ ∆ - = z g N ref ρ ρ
discussed. In this work, the PFW characteristics from the offshore gas platforms have been used to run three numerical simulations in summer conditions (see Table II); in this case, as input data we considered the tracer concentration (DEG) measured in sea water (platform 1) and in the effluent (platform 2 and 3). The field current and water mass circulation of the Northern Adriatic Sea present a marked seasonal variability (e.g. Artegiani et al., 1997a-b) which may affect the PFW dispersion. To evaluate the role of stratification on the plume dynamics we also simulate a winter PFW discharge from the three platforms (see Table II) using the same effluent characteristics as in the summer case (average flow, temperature and salinity) and the total PFW concentration. We also compare the vertical DEG profile measured at 25 m from the source with the dilution and path of the plume predicted by the near field model.

The chemical results are presented in Figure 2 and Figure 4, while the output data of the UM3 model are summarized in Table II andFigures 3 -5 The average effluent flow is approximately 27400 l d -1 ; the PFW outfall pipe is located 3 m above the surface so that, immediately after the discharge, the PFW sinks into the water column. In the proximity of the platform, the surface DEG content was nearly one third of the initial value (Fig. 2); a surface concentration decrease is observed at 5 m from the discharge point, after which surface DEG values display an increasing trend until the farthest measurement station.

The UM3 model simulates the plume trajectory only from outfalls located below the sea surface; here we consider that the plume starts to spread at 2 m depth below the surface, after the initial sinking of the discharged PFW and the effect of air entrainment owing to the impact with the water surface. The initial DEG value used here as input concentration to the UM3 refers to the surface concentration detected at 5 m from the source.

The measured hydrological structure of the water column in the summer shows a pycnocline (Fig. 3a) at ~12 m, whereas the surface layer, influenced by the PFW discharge, appears homogeneously mixed. A first sinking phase of the effluent induces the low DEG concentrations detected at the surface, close to the PFW source. On the other hand, effluent and ambient water show different densities (23.95 and 25.75 σ t respectively) which explain the resurfacing of the plume at ~14 m from the PFW source (Fig. 3b) and the consequent increase in the surface measured concentration at 15, 20 and 25 m.

In spite of the high effluent flow (Table I), the mixing condition of the surface layer, along with the swift currents associated with the platform location (17 cm s -1 ), determine a rapid initial dilution (S a = 175 after 1.5 mins) of the DEG tracer.

At the simulated discharge depth (2 m) the summer and winter Brunt-Vaisala frequency values are comparable (Table II), even though winter intense mixing leads to a fully homogeneous density profile (Fig. 3a). In the winter season the increased density difference between effluent and ambient water (Table 2) affects plume dynamics both decreasing the extent of initial mixing zone (Fig. 3b) and quickening the initial dilution process (S a = 170 in 60 s). The PFW showed high initial DEG concentration (9600 µg l -1 ) whereas values about fourfive times lower than the initial concentration were recorded in ambient water samples. The outfall is located at 9 m depth and the discharged volume is relatively small (about 11000 l d - 1 ); at 25 m from the source, the DEG surface value is lower than that recorded at 8 m depth (2460 µg l -1 ; Fig. 4).

Under summer stratification (Fig. 5a) and low ambient current conditions (the measured surface value is 3 cm s -1 ), a negative buoyancy is far more relevant (Fr = 0.66). As reported in Table II, the PFW is characterized by a density greater than the receiving water at the port depth, which causes an initial sinking in the water column down to ~ 10 m depth (Fig. 5b). At the end of the initial mixing phase the plume, not much diluted (S a = 55), remains close to the source point and approximately at the depth where the highest concentrations of DEG have been observed (Fig. 4 and5b). The comparison between field and model data suggests that the plume is trapped into a narrow layer centered at the discharge depth; the initial dilution terminates very rapidly, developing within only 2.5 m from the source in slightly more than one minute. After the near field dilution, vertical diffusivity processes may affect the plume path determining the maximum DEG concentration observed at 8 m depth; however it is worth to underline that discretised sampling strategy does not allow to reconstruct the vertical DEG profile in detail.

A completely different situation is found in simulating the water column winter mixing, when a low stability condition (N = 0.15) occurs at the discharge depth. The PFW plume is lighter than the receiving water, shows a Froude number (0.06) with positive buoyancy and rises to ~ 8 m depth (Fig. 5b). Current conditions being equal, the intense winter mixing determines a significant increase of the initial dilution extent and time (Table II). High DEG concentration (13000 µg l -1 ) was measured in the discharged fluid, while in seawater surface samples values about one order of magnitude lower than the initial concentration were detected (Fig. 2). The DEG vertical profile (Fig. 4), similarly to platform 2, displays the maximum value (2810 µg l -1 ) at 8 m sampling depth along the water column even though the PFW source is located at 12 m depth and the volume of discharged effluent is low (about 8200 l d -1 ).

During summer, the ambient conditions of platform 3 discharge are similar to those of platform 2 in terms of low current (4 cm s -1 ) and water column stability (N = 0.33) (see also Fig. 6a.). A positive buoyancy (Fr = 0.15) leads the plume to slightly rise to ~11.5 m, where the trap level is reached (Fig. 6b). At the end of the initial mixing phase the dilution has reached the value of 74 at ~15 m horizontal distance from the source. In this case the initial dilution process ends in approximately 7 minutes. The model results indicate an initial plume rising in the near field region, after which additional dilution may occur reducing the PFW density and sustaining its further rising in the water column, in agreement with the 8 m maximum DEG concentration measured at 25 m distance.

Modifying the water column stratification (Fig. 6a) yields an increase in the density difference between effluent and receiving water (σ t are 24.8 and 26.5 respectively). The plume shows positive buoyancy and immediately after the discharge starts to rise in the water column reaching the trap level at ~ 11 m depth (Fig. 5b). The low stability of the water column acts to drastically decrease the time dilution and to enhance S a . It is worth noting that the initial mixing zone extension around the discharge point is less than 7 m. Even with the limitations due to the unavailable vertical discretization when it comes from water sampling, the comparison between chemical analyses and numerical simulations showed a good agreement, pointing out the presence of a limited layer within which the plume spreads and evolves. In particular, both outcomes indicate that the plume mainly develops within a layer 2 to 4 meters thick, centered at the discharge depth. Moreover, as in previous experimental studies carried out in similar conditions (e.g. Robert and Tian, 2004), the platforms discharging in the water column in low current conditions are characterized by a near field dilution occurring within 15 m or less from the outfall. It is worth underlining that the UM3 model only simulates the initial dilution phase of the plume, whereas the PFW can also be found in the sea at distances further from the source, where far field processes play a significant role; this is the case here, as shown by the chemical analyses.

Since DEG is exclusively attributable to PFW discharge, it is miscible in seawater, is easily measured and can be added to PFW in concentrations as high as 3500 mg l -1 , it provides a very convenient chemical tracer of PFWs originating from gas platforms. However, the results have shown that the DEG traceability varies according to the discharge position and the PFW density.

All effluent features being the same, the plume dynamics within the water column appears strongly modulated by the seasonal stratification for all modelled current speeds. During summer, the N frequency values are typically greater than in winter, thus indicating a high level of stability at discharge depth. The periods of high stratification also influence the trap level depth of the plume (see Platforms 2 and 3) which is deeper in the summer. In winter conditions, when intense mixing fosters the rise of the plume in the water column, an opposite situation occurs for all the investigated platforms.

As suggested by previous studies (e.g [START_REF] Frick | Dilution models for effluent discharges, 4th Edition, Visual Plumes[END_REF], for horizontal outfalls densimetric Froude numbers less than 1.0 tipically indicate a fluid so buoyant to rise to the top of the discharge port; in this case ambient fluid may flow into the outfall under the plume. Recent technologies (involving the adoption of special valves) have been developed to prevent this problem by increasing the Froude number via a reduction of the port cross-sectional area in low flow situations (e.g [START_REF] Frick | Dilution models for effluent discharges, 4th Edition, Visual Plumes[END_REF]. In this work we only treat platforms with vertical outfall pipes operating in weak current conditions, for which Froude number values less than 1.0 indicate that the plumes are dominated by the buoyancy effect [START_REF] Frick | Visual Plumes mixing zone modeling software[END_REF]. In our numerical experiments, Fr values less than 1 in both unstratified and stratified scenarios also point out that stratification conditions have a more relevant effect in controlling the plume dilution compared to the current field.

Another consequence of the variability in stratification is that the near-field dilution parameter S a may be highly variable. When the water column is highly stable in summer, the plume is mixed over a smaller region of the water column (Table II), resulting in lower values of S a . For periods of weaker stratification in winter, the plume mixes over a larger zone of the water column and S a increases. A particular situation occurs when the discharge mainly develops in the surface mixed layer (Platform 1). In this case the effect of the high currents (17 cm s -1 ) is clearly predominant with respect to the water column stability, the winter mixing only affecting the time required for the initial dilution and the plume horizontal extent.

The initial dilution times resulting from our integrated study are also consistent with observed toxicological data [START_REF] Icram | Monitoraggio sperimentale integrativo per lo studio degli effetti potenziali a seguito dello sversamento in mare delle acque di strato da piattaforme off-shore[END_REF][START_REF] Manfra | Dispersione in mare delle acque di produzione e valutazione ecotossicologica degli effetti indotti[END_REF] revealing low or null toxic effects in the water column close to the Adriatic platforms (stations sampled close to the source and at 25 m, 50 m and 500 m distances). The time required to complete the initial dilution (between 60 and 400 s) allows even the organisms entrained in the plume to be exposed to rapidly decreasing concentrations of pollutants.

Conclusions

An integrated numerical-chemical approach has been used to investigate the near-field dispersion of the produced formation waters discharged from three offshore natural gas platforms operating in the northern Adriatic Sea.

The chemical approach is an analytical procedure which gives accurate concentrations of the single compounds present in PFWs. The observed quantities of a selected contaminant (DEG) have been integrated in the UM3 model allowing a comprehensive description of the initial dilution path and time scales of the PFWs. In addition, measurements of currents and ambient density stratification have been used, representing another model input necessary to assess the role of the physical constraints on the effluent dynamics.

All the simulations have been performed neglecting the loss of material contained in the PFWs through removal or degradation processes and assuming a current field uniform with depth, therefore our results may be considered a worst case of PFWs discharge. A good agreement between field chemical data and modelling prediction is obtained even though the comparison is only restricted to the near-field process. Future efforts will investigate times and spatial scales of the far field region.

Results show that the plume behaviour is highly influenced by the thermal stratification observed during the summer season, while no effect of the detected DEG concentrations on the effluent density is clearly visible. In the case of submerged discharges, under stratified conditions, the plume appears mainly trapped around the outfall pipe depth and the dilution parameter S a is relatively low (less than 80), while the presence of weak currents exerts little influence on it. In unstratified conditions the effluent rises in the water column and the dilution significantly increases to more than 130. In agreement with several dispersion/fate models of produced water [START_REF] Neff | Bioaccumulation in Marine Organisms[END_REF][START_REF] Nedwed | Verification of the OOC mud and produced water discharge model using lab-scale plume behaviour experiments[END_REF][START_REF] Berry | Integrated fate modeling for exposure assessment of produced water on the Sable Island Bank (Scotian Shelf, Canada)[END_REF]Smith et al., 2004;[START_REF] Durell | Oil well produced water discharges to the North Sea. Part I: Comparison of deployed mussels (Mytilus edulis), semipermeable membrane devices, and the DREAM model predictions to estimate the dispersion of polycyclic aromatic hydrocarbons[END_REF]) also in our cases the initial dilution processes are very rapid, the fast PFWs dispersion times (< 7 min) causing negligible or no-toxic effects on the marine organisms [START_REF] Icram | Monitoraggio sperimentale integrativo per lo studio degli effetti potenziali a seguito dello sversamento in mare delle acque di strato da piattaforme off-shore[END_REF][START_REF] Manfra | Metal content and toxicity of produced formation water (PFW): study of the possible effects of the discharge on marine environment[END_REF].

In recent years the importance of assessing the influence of the PFWs discharge on the marine environment has been recognized, and monitoring programmes have been successfully developed [START_REF] Maggi | A methodological approach to study the environmental impact of oil and gas offshore platforms[END_REF]. Our integrated numerical-chemical approach may represent a suitable tool providing advice to optimize both the monitoring activities and the industry discharge practices.

For example, the present work clearly shows that under strong stratification conditions the effluent mainly develops its path around the discharge depth. Our results suggest that an improvement of monitoring programmes is needed, for example to plan more samplings along the water column starting close to the platform and up to 1 km from the source. Since the water column stability has a relevant role on plume dynamics, it could also be useful to schedule field measurements during the winter season.

Another relevant result achieved in the present work is that the highest effluent concentrations, within the near-field zone, are found with strong stratification and low current speed. Discharging higher volumes of effluent during the winter period could be a good practice, as it would promote the dilution in the near-field.

Such indications may be essential to support decision makers in their efforts to mitigate the impacts of the offshore platform operations on the marine ecosystems. Integrated chemicalnumerical approaches could also be employed by the regulatory authorities [START_REF] Frick | Modeling consistency, model quality, and fostering continued improvement[END_REF] -as usually done, e.g. by the US Environmental Protection Agency -to establish the extent of the initial dilution zone (ZID). Even though many definitions exist [START_REF] Roberts | Sea Outfalls[END_REF][START_REF] Jirka | Environmental Quality Standards in the EC-Water Framework Directive: Consequences for Water Pollution Control for Point Sources[END_REF], the ZID may be typically considered as a mixing zone around the discharge point where ambient concentrations may exceed surface water quality standards but acutely toxic conditions must be prevented. The initial dilution zone may be established by the authorities, for example to protect local marine resources [START_REF] Larsen | Necessity of Initial Dilution for Sea Outfall Diffusers in Respect to the European Directive on Municipal Discharges[END_REF]; an integrated approach can be used to assess the seasonal extent of the mixing zone, by taking into account the effluent flow, the local current field and the concentration acceptable for the key organisms. The path of the plume is described by means of its centerline (cln) and boundaries (bnd).

Figure captions

  (1, 2 and 3 hereinafter) and marine surface water samples were collected during PFW discharge in six stations at increasing distance from the discharge source (0 m -close to the platform -5 m, 10 m, 15 m, 20 m and 25 m) after a qualitative estimate of the ambient current direction. In the case of platforms 2 and 3, at the farthest station (25 m) subsurface samples were also collected at discrete depths (0 m, 4 m, 8 m, 12 m; at platform 3 also 16 m) in the water column. The samples were stored in dark glass bottles to inhibit photochemical activity and saturated with mercury cloride to inhibit bacterial activity, then were refrigerated at 4°C. A characterization of the dynamic environment in which the PFWs are discharged was also carried out; hydrological data were collected on a number of oceanographic cruises carried out during spring and summer seasons starting in April 2001 through August 2003 (ICRAM, 2002, 2003 and 2004). Temperature and conductivity were measured by an Idronaut Ocean Seven 316 CTD sonde at a distance of 50 m from the platform. Hydrographic data for the winter season have been drawn from the Dartmouth Adriatic Data Base (http://thayer.dartmouth.edu/other/adriatic/databanks/hydrography/hydrography.html) in the form of seasonal average stratification at the platform locations.

Figure

  Figure 1 approximate location

  approximate, for each platform, the classic formulation of the Brunt-Väisälä frequency N 3) as in Washburn et al. (1998): 4) where ρ ref represents the ambient fluid density at the depth of the discharge and z ∆ ∆ρ is the vertical density gradient in correspondence of the outfall depth. N is computed by finite differencing the measured density profile in a vertical range of 4 m centred around the depth of discharge.

  .

Figure 2

 2 Figure 2 approximate location, Table II approximate location

Figure

  Figure 3 a-b approximate location Figure 4 approximate location

Figure

  Figure 5 a-b approximate location

Figure

  Figure 6a-b approximate location

Figure 1 -

 1 Figure 1 -Adriatic Sea: surface velocity fields as deduced by Lagrangian Drifters (adapted

Figure 2 -

 2 Figure 2 -DEG concentrations observed at the sea surface at increasing distances from the

Figure 3

 3 Figure 3 -a. Summer and winter density profiles close to Platform 1. b. Plume vertical

Figure 4 -

 4 Figure 4 -Profiles of DEG concentrations detected along the water column at 25 m from

Figure 5

 5 Figure 5 -a. Summer and winter density profiles close to Platform 2. b. Plume vertical

Figure 6

 6 Figure 6 -a. Summer and winter density profiles close to Platform 3. b. Plume vertical

  Fig.1

  Fig.3a

  Fig.3b

  Fig.4

  Fig.6a

  Fig.6b

Table I approximate location

 I

Table I

 I Field data and input model values

	Platform	Distance from the coast	Average effluent flow	Port diameter	Water column depth	Diffuser Depth	Sampling distances from diffuser	Sampling depths	Surface current speed	Effluent salinity	Effluent temperature	Initial DEG conc.
		(Km)	(l d -1 )	(m)	(m)	(m)	(m)	(m)	(cm s -1 )	(g kg -1 )	(°C)	(µ µ µ µg l -1 )
	1	36	27400	0.45	116	3*	0,5,10,15,20,25	-	17	35	23	2040
	2	15	11000	0.45	18	9	0,5,10,15,20,25	0,4,8,12	3	37.6	20	9600
	3	21	8200	0.45	23	12	0,5,10,15,20,25	0,4,8,12,16	4	35.2	20.5	13000
	* Outfall located above sea surface

Acknowledgements

The authors acknowledge comments by the three anonymous Reviewers and F.Bignami. This research has been carried out as the result of a reciprocal agreement between the University of Naples Parthenope and the Central Institute for Applied Marine Research (ICRAM). This work was partly funded by the QUAMACO Project (Plan of activity of knowledge of coastal marine environment) and by the EU Interreg III B Archimed CORI (Prevention and Management of Sea Originated Risk to the Coastal Zone) project.


Alberto Ugolini
email: ugolini_alb@dbag.unifi.it

Giuseppe Ungherese

Silvia Somigli

Giuditta Galanti

Davide Baroni

Francesca Borghini

Nicola Cipriani

Massimo Nebbiai

Maurizio Passaponti

Silvano Focardi

The amphipod Talitrus saltator as a bioindicator of human trampling on sandy beaches

Keywords: Human trampling, Heavy metals, Mediterranean Sandy shores, Beaches, Bioindicator, Amphipod, Talitrus saltator

The present paper assesses the use of the supralittoral amphipod Talitrus saltator as a bioindicator of the effects of human trampling on the supralittoral sandy band.

Samplings in delimited areas were carried out at sites subjected to different human impact. The results showed a strong negative correlation between the number of swimmers and the sandhopper population density, while there was no clear relationship between sandhopper abundance and the other factors considered: granulometry, compactness and organic carbon content of the sand, and trace metal contents in the sand and sandhoppers. A field test of trampling conducted in a confined space showed its direct negative effect on sandhopper survival. However, trace metal analysis confirmed the ability of T. saltator to bioaccumulate some elements (Hg, Zn, Cu, Cd).

Our study demonstrates that T. saltator is a good bioindicator of human impact in the supralittoral zone of sandy shores.

Introduction

In the coastal zone, the input of materials and substances from terrestrial, fluvial and marine sources is particularly important. In addition to elevated concentrations of nutrients, there can be increased quantities of natural and anthropogenic contaminants.

Since the 1960s, European shores (particularly Italian ones) have seen a very strong increase in the number of swimmers at beach resorts. Many studies on the submerged and intertidal littoral environment of rocky and sandy shores have dealt with the use of organisms as biomonitors of trace metal contamination. Similarly, many investigations have attempted to evaluate the effects of human trampling and recreational uses on natural populations and communities of the littoral zone of sandy shores (see [START_REF] Milazzo | The impact of human recreational activities in marine protected areas: What lessons should be learnt in the Mediterranean Sea[END_REF] for a review). In contrast, the supralittoral band, an ecotonal environment of great ecological importance in the economy of sandy shore ecosystems, has received relatively little attention (see [START_REF] Brown | Ecology of sandy shores[END_REF][START_REF] Schlacher | Sandy beaches at the brink[END_REF]).

Most research on the effects of trampling on natural communities concerns the vegetation or macrofaunal components (especially birds) [START_REF] Liddle | A selective review of the ecological effects of human trampling on natural ecosystems[END_REF][START_REF] Brown | Ecology of sandy shores[END_REF]. Several studies have examined the effects of trampling on the invertebrate fauna of rocky shores or of loose substrata of the intertidal zone (for instance see [START_REF] Povey | Effects of trampling on plant and animal populations on rocky shores[END_REF][START_REF] Brosnan | Effects of human trampling on marine rocky shore communities[END_REF][START_REF] Chandrasekara | Effects of human trampling on tidalflat infauna[END_REF][START_REF] Casu | Human exclusion from rock shores in a Mediterranean marine protected area (MPA): An opportunity to investigate the effects of trampling[END_REF][START_REF] Dye | Persistent effects of physical disturbance in mangrove sediments[END_REF][START_REF] Johnson | Recovery of meiofauna communities following mudflat disturbance by trampling associated with crab-tiling[END_REF]. Instead, there have been very few investigations of the supralittoral fauna of sandy shores and the results of these studies have been contradictory [START_REF] Jaramillo | Macroinfauna and human disturbance in a sandy beach of south-central Chile[END_REF][START_REF] Moffet | Impact of trampling on sandy beach macrofauna[END_REF]Weslawski et al., 2000b, c;[START_REF] Veloso | Comparison between the macrofauna of urbanized and protected beaches in Rio de Janeiro State, Brazil[END_REF]. Recent studies have attempted to establish the utility of supralittoral amphipods as indicators of the impact of tourist activities on sandy shores [START_REF] Fanini | Relationships between the dynamics of two Talitrus saltator populations and the impacts of activities linked to tourism[END_REF]. However, because of their methods and sampling sites, the investigations have not provided clear results.

In summer, the supralittoral zone is intensely frequented by swimmers but it is also where the major consumers of stranded organic material, i.e. talitrid amphipods and isopod, find shelter during the day, buried in the wet sand. In fact, most of the energy flow deriving from the use of stranded material passes through supralittoral crustaceans [START_REF] Branch | The living shores of Southern Africa[END_REF][START_REF] Griffiths | Kelp wrack and the flow of energy through a sandy beach ecosystem[END_REF][START_REF] Brown | Ecology of sandy shores[END_REF].

Sandhoppers occupy a trophic niche as detritivores and collector-gatherers. Hence they feed on plant and animal material from both marine and terrestrial sources [START_REF] Palluault | Notes ecologiques sur le Talitrus saltator[END_REF][START_REF] Wildish | Ecology and natural history of aquatic Talitroidea[END_REF][START_REF] Bergerard | Ecologie des laisses de marée[END_REF], integrating the two routes of contamination of the supralittoral.

The aims of the present study were to examine the possibility of using the amphipod T. saltator as a bioindicator of the effects of human trampling on the supralittoral of sandy shores and to provide a simple low-cost monitoring tool. For this reason the relationship between sandhoppers abundance and swimmers has been considered, as well as the possible influence of some other factors such as granulometric composition and sand compactness, organic carbon content in the sand and trace metal contamination.

Materials and methods

Sandhopper sampling

Samplings to determine the density of sandhoppers were carried out at eight sites on the coast of Tuscany subjected to different tourist impact and either with or without beach cleaning procedures. In the five sites inside the Regional Park of Migliarino, San delimited by plastic containers inserted a few cm into the sand. Each container was inserted along the sea-land axis of the beach at a progressively increasing distance starting from the water line until the beginning of dry sand. At each site, the sampling was carried out twice, a few meters apart, since the distribution of sandhoppers in the band of wet sand does not seem to be uniform (Weslawski et al., 2000a).

At each sampling site, the people to the right and left of the shoreline, along a 150 m transect in the central hours of the day on the days with the highest tourist presence, were also counted (Saturday and Sunday).

At some locations, the following factors were also analyzed to exclude differences between the sampling sites: 1) contents of trace metals in the sand and in the sandhoppers (Hg, Cr, Cd, Cu, Zn, Fe, Al, Pb); 2) compactness of the sand; 3) granulometric composition of the sand; 4) organic carbon content of the sand.

Trace metals

The trace metal analysis was conducted on sand samples collected from the zone frequented by the sandhoppers during the day and on adult individuals of T. saltator collected at all the sites. The animals were transported to the laboratory in plastic containers with sand and detritus from the sampling site and then sacrificed by freezing.

At each site, a sample of sand was collected in the zone frequented by the sandhoppers during the day. We dehydrated the samples at 40°C until they reached a constant weight and then were finely ground. Around 150 mg of each sample were mineralized in Teflon vessels containing 3 ml of HNO 3 at 120°C for 8 h. After digestion, the solution was brought to a volume of 10 ml by addition of deionized water. During each mineralization, we performed several "blank trials", by putting only the reagents in the Teflon containers, to verify the absence of contamination. were within the certified concentration range; if not, we repeated the analyses. The element concentrations (expressed as µg/g) were calculated by the method of "internal additions". The coefficients of variation for the various elements were between 5 and 10%.

Granulometric composition and sand compactness

For the granulometric analysis, the sand samples were split to obtain samples of approximately 10 grams (the choice of the representative volume was based on the median of the sediment, as estimated by visual examination).

A statistically representative portion of the sample was placed in an oven at 80°C to eliminate the humidity, after which we sifted the material through a series of progressively finer sieves (2500 µm, 1600 µm, 1000 µm, 630 µm, 400 µm, 250 µm, 160 µm, 100 µm, 63 µm) for around 5 minutes with a Ro-Tap shaker. Since the samples were prevalently sandy, it was not necessary to analyze the mud-clay fraction (< 63 µm) of the sediment.

To assess the compactness of the sand in the zone frequented by sandhoppers during the day, an aluminum pole was dropped from a height of 1 m and the distance the pole penetrated into the sand was measured. The distance was transformed into arbitrary units by assigning a value of 100% compactness to 0 cm and 50% compactness to 10 cm.

Organic carbon

The sand samples were collected at each site in July 2006. The organic carbon in the sand samples was determined as the difference between the total carbon and the inorganic carbon. The sand was crushed to a fine powder so as to homogenize the sample. Total carbon was determined with a CHNS/O ANALYZER (mod. 2400 ser. II, Perkin Elmer), while inorganic carbon was measured with a De Astis calcimeter.

Trampling test

The

Statistical analysis

The granulometric data were analyzed with specific software (Dept. of Earth Sciences, Univ. of Florence) that provided parametric statistics indicative of the sorting of the samples, as well as the percentages of the granulometric classes for the purposes of textural classification [START_REF] Shepard | Nomenclature based on sand -silt -clay ratios[END_REF].

The statistical analysis of sandhopper density was performed independently of an analysis of natural population fluctuations (see [START_REF] Anastácio | A model for amphipod (Talitrus saltator) population dynamics[END_REF][START_REF] Marques | Compararision of Talitrus saltator (Amphipoda, Talitridae) biology, dinamics, and secondary production in Atlantic (Portugal) and Mediterranean (Italy and Tunisia) populations[END_REF] The values for the other sites were expressed as a percentage of FM.

Results

Sandhopper density

The frequency of T. saltator individuals collected at the MSRM Park sites was negatively correlated with the frequency of swimmers (Fig. 1). Despite the small sample sizes, statistical significance was reached for each of the four months (June-September) (June and July, r s =-1, p = 0.01; August and September, r s = -0.925, n = 5, p<0.05, n = 5, Spearman rank-order correlation coefficient test, Fig. 1). This is also confirmed considering the mean number of sandhoppers and swimmers (Table 1). In fact, the Fiume Morto Vecchio site (FM) consistently had the lowest tourist impact and the highest sandhopper abundance (Table 1). In contrast, no sandhoppers were found at the site with the highest tourist impact, Oasi 1 (Table 1).

FIG. 1 TABLE 1

The July vs. September comparison for the various sampling sites was statistically significant for the localities in the MSRM Park (G = 114.5, df = 4, p<0.001, fig. 1) but not for the sites on the Feniglia sandbar (G = 1.9, df = 2, p>0.1, G test, Fig 3).

There was a significant monthly difference in sandhopper abundance even at a single locality with very low tourist impact (Fiume Morto Vecchio, Table 1, Fig. 2, G = 664, df = 1, p<0.001, G test) due to the natural population fluctuation. However, these differences did not affect the swimmers-sandhoppers relationship.

FIG. 2

It was not possible to make statistical comparisons for the Feniglia sandbar (Fig.

3

) because of the small number of sampling sites. Nevertheless, the number of sandhoppers captured at the Feniglia sites clearly followed the same trend in relation to tourist impact as the one recorded at the MSRM Park sites, i.e. localities with higher tourist impact had lower T. saltator densities.

FIG. 3

Regarding

Trace metals

At the sites with sandhoppers, the Cu, Cd, Hg and Zn concentrations (Fig. 4) were constantly higher in the sandhoppers than in the sand. In contrast, the Fe, Pb and Al contents (Fig. 4) were higher in the sand than in the sandhoppers. For Cr, there was a higher concentration in the sandhoppers at two sites and in the sand at the other two sites.

There was no significant correlation between sandhopper abundance (in Fig. 4 abscissa, the sites are in decreasing order of abundance) and trace metal contents in the individuals or in the sand (P = NS in each case, n = 6, Spearman rank-order correlation test).

FIG. 4

Granulometric composition and sand compactness

The granulometric composition of the sand was fairly uniform among sites: all samples were well classified and in the medium-to coarse-grained range (Table 2).

TABLE 2

For the MSRM Park sites, there was no correlation between mean sand grain diameter and sandhopper density (Spearman rank-order correlation coefficient test, r s = -0.1, n = 5, p = NS, Fig. 5A). A qualitative evaluation also suggested a lack of correlation between sandhopper abundance and mean sand grain diameter at the Feniglia localities (Fig. 5B).

Sand compactness at the MSRM Park sites (Fig. 5C) was not significantly correlated with the number of sandhoppers (r s = -0.175; n = 5, p=NS, Spearman rankorder correlation coefficient test). Indeed the highest values occurred at site SF where sandhoppers were present (Fig. 5C). For the Feniglia sites, a qualitative evaluation indicated a negative correlation between sand compactness and sandhopper abundance (Fig. 5D).

Organic carbon

For the MSRM Park sites, the organic carbon content of the sand was not significantly correlated with sandhopper density (r s = 0.7, n = 5, p = NS; Spearman rank-order correlation coefficient test, Fig. 5E). However, the localities along the Feniglia sandbar showed a negative correlation between the two parameters (fig. 5F).

FIG. 5

Trampling test

The effect of trampling on T. saltator survival (Fig. 6) was evident immediately after the treatment: the difference between the number of live individuals before and after treatment was highly significant (G = 86, df = 1, p<0.001, G test). After 24 hours, the percentage of surviving sandhoppers dropped almost to zero (G = 428, df = 1, p<0.001, G test) while the survival of the control sandhoppers remained the same.

FIG. 6

Discussion

Of all the factors that might have negatively influenced the population density of T. saltator, only the number of swimmers showed a significant correlation with the number of captured sandhoppers. Although the effect of trampling in a confined test space is probably not the same as in natural conditions (in which case the animals could escape), our test results are the first direct proof that human trampling affects sandhopper survival. This is likely an important factor at Mediterranean latitudes and for species that burrow only slightly into the sand (ca. 3-5 cm depth).

This does not mean that other factors are never influential, only that they are not particularly important in the conditions encountered in this study. Sand compactness probably has a negative effect on sandhopper abundance beyond a certain threshold: a particularly compact substrate could hinder burrowing, thus reducing the probability of survival. However, sites like BV and SF, where sandhoppers were present, had more compact sand than O1, where sandhoppers were never found. The negative correlation at the Feniglia sites probably depended on the fact that the increasing order of sand compactness at the sites corresponded to an increasing order of tourist impact.

Furthermore, the sand compactness at O1, where sandhoppers were absent, was lower than at FB2 and FB1 where sandhoppers were present. Therefore, sand compactness does not seem to be a primary determinant of T. saltator population density.

There did not appear to be any relationship between sandhopper abundance and sand grain size at the various sites. In fact, T. saltator lives on beaches with sand that ranges from medium-to coarse-grained (i.e. from around 0.5 to 2 mm, [START_REF] Ugolini | Distribution of Talorchestia ugolinii and other sandhoppers in Corsica[END_REF]. All the locations considered in this study fell within this range.

The results for organic carbon suggested a negative correlation with sandhopper abundance at the Feniglia sandbar sites. However, as for sand compactness, the increasing order of organic carbon content at the sites corresponded to an increasing order of tourist impact. In addition, the FM site (MSRM Park) had a high sandhopper abundance but a higher organic carbon content than at FA where there were very few sandhoppers (but many swimmers).

The trace metal analysis confirmed T. saltator's good ability to bioaccumulate Hg, Cu, Cd and Zn [START_REF] Rainbow | Comparative metals analyses in amphipod crustaceans[END_REF][START_REF] Moore | Copper and zinc in an ecological series of talitroidean Amphipoda (Crustacea)[END_REF][START_REF] Rainbow | Phylogeny of trace metal accumulation in crustaceans[END_REF]Rainbow et al., 1998a, b;[START_REF] Marsden | Does the accumulation of trace metals in Crustaceans affect their ecology -the Amphipods example[END_REF][START_REF] Ugolini | Mediterranean Talitrus saltator (Crustacea, Amphipoda) as a biomonitor of heavy metals contamination[END_REF][START_REF] Ugolini | Heavy metals accumulation in two syntopic sandhoppers species: Talitrus saltator Montagu and Talorchestia ugolinii Bellan Santini and Ruffo[END_REF]. Although there were some differences in trace metal contamination among sites, there was no clear relationship with the abundance of sandhoppers. Hg accumulation seemed to be negatively correlated with sandhopper abundance at the various sites (Fig. 4). Nevertheless, the Hg concentration in the sand was lowest at O1 where there were no sandhoppers. Thus, the absence of sandhoppers at O1 and the low density at FA cannot be attributed to Hg contamination. Furthermore, the trace metal concentrations in both the sandhoppers and sand samples were much lower than those recorded previously at heavily polluted localities where sandhoppers or beachflies were present (Rainbow et al., 1998a, b;[START_REF] Fialkowski | Biomonitoring of trace metals along the Baltic Coast of Poland using the sandhopper Talitrus saltator (Montagu) (Crustacea: Amphipoda)[END_REF][START_REF] Ugolini | Mediterranean Talitrus saltator (Crustacea, Amphipoda) as a biomonitor of heavy metals contamination[END_REF]).

Since we did not evaluate the effects of beach cleaning separately from the effects of trampling, we cannot exclude a possible influence of beach cleaning on sandhopper density. Nevertheless, at the sampling sites not subjected to mechanical beach cleaning, sandhopper abundance still varied in relation to the different tourist impact. In fact, the sandhopper distributions along the Feniglia sandbar (where the beach is regularly cleaned) and at Fiume Morto Vecchio and Batteria Vecchia (where beach cleaning is not carried out) all presented the same pattern in relation to the numbers of swimmers. Therefore, contrary to the hypothesis of [START_REF] Fanini | Relationships between the dynamics of two Talitrus saltator populations and the impacts of activities linked to tourism[END_REF], trampling rather than beach cleaning has a negative effect on the survival of sandhoppers. We can also add a qualitative datum: at site O1, the one with the highest tourist impact in the MSRM Park, we never captured any sandhoppers during the present research, whereas hundreds of sandhoppers were regularly collected around 25 years ago when the zone had no beach resorts and swimming was forbidden.

We studied populations living within 200 Km of each other and thus subject to very similar general climatic and environmental conditions. Therefore, the natural fluctuations of population density are probably synchronous. In any case, since the proposed method is based on the comparison of densities recorded at the various sites in the same time period, it is independent of natural population fluctuations and does not require biodiversity estimates for the considered environment. Hence, the method is simple and low-cost. Other recently proposed methods using sandhoppers to assess human disturbance are based on quantification of the variability of spatial-temporal habitat use [START_REF] Elgtari | Behavioural adaptation of Talitrus saltator populations to beaches with different dynamics and degree of human disturbance along Tunisian coasts[END_REF][START_REF] Nardi | Seasonal variation in the free-running period in two Talitrus saltator populations from Italian beaches differing in morphodynamics and human disturbance[END_REF][START_REF] Fanini | Relationships between the dynamics of two Talitrus saltator populations and the impacts of activities linked to tourism[END_REF][START_REF] Scapini | Orientation of sandhoppers at different points along a dynamic shoreline in southern Tuscany[END_REF] or on determination of the degree of genetic variability [START_REF] Ketmaier | Exploratory analysis of talitrid population genetics as an indicator of the quality of sandy beaches[END_REF].

However, T. saltator's high behavioral plasticity and remarkable ability to learn new directions of the sea-land axis of the beach (see [START_REF] Ugolini | Learned component in the solar orientation of Talitrus saltator Montagu (Amphipoda : Talitridae)[END_REF]Ugolini and Scapini, 1988;Ugolini et al., 1988) prevent a reliable and rapid determination of the reasons for variability in orientation behavior. The determination of genetic variability is interesting but not easily performed. Therefore, since these methods require specific expertise in various fields, sophisticated analytical techniques and complex statistical analyses, their practical application appears to be problematic.

The effect of human trampling and heavy tourist use of beaches on sandhopper populations raises the question of their conservation. T. saltator is a good osmoregulator [START_REF] Morritt | Osmoregulation in littoral terrestrial talitroidean amphipods (Crustacea) from Britain[END_REF][START_REF] Calosi | Physiological capacity and environmental tolerance in two sandhoppers species with contrasting geographical ranges: Talitrus saltator and Talorchestia ugolinii[END_REF] and metapopulations of this species are also found on the shores of retrodunal pools and on riverbanks near the mouth [START_REF] Ugolini | Learned component in the solar orientation of Talitrus saltator Montagu (Amphipoda : Talitridae)[END_REF]Ugolini and Scapini, 1988;Ugolini et al., 1988). These places are usually shunned by swimmers and if protected could be valid reserves for natural (spontaneous migrations) or artificial sandhopper repopulation of the adjacent beaches.

In conclusion, 1) our method is reliable and low-cost, 2) T. saltator is a good biomonitor of trace metal pollution (Cu, Hg, Zn, Cd), and 3) this species is a valid bioindicator of the effects of human trampling and could be used for ecocompatible management of the tourist impact on the supralittoral zone.

Figure captions

  Rossore, Massaciuccoli (MSRM Park, Pisa), the sampling was performed once a month from June to September 2004, 2005 and 2006: O1) Oasi 1 (cleaned beach) SM) Serchio Mare (seashore, not cleaned) SF) Serchio Fiume (right bank of river mouth, not cleaned) BV) Batteria Vecchia (not cleaned) FM) Fiume Morto Vecchio (not cleaned) At the three sites along the Feniglia sandbar (southern Tuscany, Grosseto), the sampling was performed in July and September 2005: FA) bathhouse (Ansedonia side, cleaned beach) FB1) beach ca. 1 km from FA (cleaned) FB2) beach ca. 2 km from FA (cleaned)At each sampling, all the sandhoppers were captured (also disturbing the surface layer to sample those in the sediment) and counted inside four areas (75 cm 2 each)

  The analyses were performed by atomic absorption spectrometry. Cd, Cr, Cu and Pb were determined by atomization with a graphite furnace and Zeeman background corrector. The FIMS (Flow Injection Mercury System) was used for Hg, while we determined Al, Fe and Zn by Inductively Coupled Plasma Atomic Emission Spectrometry (ICP/EAS). Each analysis was carried out 3 times and the accuracy of the analytical procedures was assessed by comparing the results of contemporary digestions and analyses of Standard Reference Materials, SRMs): SRM 1566a "oyster tissue" from the National Institute of Standards and Technology (NIST, Gaithersburg, USA). The results of the determination were only accepted if the values measured for the SRMs

  trampling test was carried out at Fiume Morto Vecchio (MSRM Park). Two plastic cylinders (110 cm diameter) were fixed in the sand in the wet band frequented by sandhoppers during the day. All the individuals inside each of the delimited areas were captured, counted and then freed within the same area. After around 15 minutes (sufficient time for the sandhoppers to return to their refuges in the wet sand), two people performed 400 footsteps in 15 minutes inside one of the two cylinders. The number of footsteps was chosen on the basis of the footsteps recorded during a survey carried out from 11:00 to 12:00 on a Saturday in July 2006 on the Marina di Pietrasanta beach (a popular beach on the Tuscan coast). During this survey, a mean transit of 866 swimmers per hour at a selected point on the shoreline was recorded. The sandhoppers within the other cylinder were left undisturbed. At the end of the trial, the sandhoppers still alive in both cylinders were captured, counted and transported to the laboratory in basins with wet sand. The numbers of individuals still alive 24 hours after the treatment was also recorded.

  and/or a comparison of the population densities at different sites. Such analyses were beyond the scope of our study and would not have provided information useful for our aims. It is possible that sandhopper populations living in the same environment and practically at the same latitude (ca. 200 km apart) present small differences in the natural fluctuation of population density. However, since we performed relative comparisons of the number of captured individuals among several localities of the same zone, any differences in population density between different zones in the same period of the year would not affect the interpretation of the results. The tests used are among the most common ones in non-parametric statistics[START_REF] Zar | Biostatistical Analysis[END_REF][START_REF] Siegel | Non parametric statistics for the behavioral sciences[END_REF].The possible influence of trace metal pollution on sandhopper density was assessed with the Spearman rank-order correlation coefficient test[START_REF] Siegel | Non parametric statistics for the behavioral sciences[END_REF]). In the figure illustrating trace metal pollution, we arranged the sampling sites in decreasing order of sandhopper density: the site with the highest sandhopper abundance in July 2006 (FM, captured sandhoppers = 1013) was given the arbitrary value of 100.

  the possible influence of beach cleaning on sandhopper survival, there was a significant difference between the only cleaned site (O1, n = 0) and the total of the other MSRM sites (SM + SF + BV + FM, n = 7 551; G = 10 434, df = 1, P<0.0001, G test). However, there were also significant differences among the not cleaned sites (SM, n = 28; SF, n = 164; BV, n = 2160; FM n = 5 199;G = 10 077, df = 3, P<0.0001, G test). A similar result was obtained for the cleaned beaches of the Feniglia sandbar (FA, n = 131; FB1, n = 41; FB2, n = 3; G = 164, df = 2, P<0.01, G test).

Fig. 1 .

 1 Fig. 1. Frequency (% of total numbers) of captured sandhoppers (black bars) and swimmers (white bars) for each month of sampling. The order of the sampling sites is based on the number of swimmers observed at each locality: FM = Fiume Morto; BV = Batteria Vecchia; SF = Serchio Fiume; SM = Serchio Mare; O1 = Oasi 1. The total numbers of sandhoppers and swimmers at all five sites are also given.

Fig. 2 .

 2 Fig. 2. Monthly variation of sandhopper numbers (% of total sampled) at Fiume Morto (FM). Total number of sandhoppers collected = 5199.

Fig. 4 .

 4 Fig. 4. Trace metal concentrations (µg g -1 dry wt) in the sand (white bars) and in the sandhoppers (black bars). For each element, the sampling sites are ordered according to decreasing frequency of sandhoppers recorded in July 2006. For further explanations, see Figs. 1, 3 and text.

Fig. 5 .

 5 Fig. 5. A-B: mean sand grain diameter (white bars) and frequency of captured sandhoppers (black bars; % of total numbers). The order of the sampling sites is based on mean diameter. C-D: sand compactness (white bars) expressed in arbitrary units (a. u.) and frequency of captured sandhoppers (black bars). The order of the sampling sites is based on sand compactness. E-F: percentage of organic carbon in the sand (white bars) and frequency of captured sandhoppers (black bars). The order of the sampling sites is based on percentage of organic carbon. For further explanations, see Figs. 1 and 3.

  Figure 1

Table captions Table 1 .

 captions1 Captured sandhoppers and number of swimmers (mean ± SD; n = 3) for each

	month of sampling

Table 2 .

 2 Results of the granulometric analysis for each sampling site. For further explanations, see Figs. 1, 3 and text.

Table

		ACCEPTED MANUSCRIPT
	Sampling	Mean sand	Standard	Skewness	Kurtosis
	sites	grain diameter	deviation
		(mm)
	FM	1.605	0.471	-0.012	0.503
	BV	1.324	0.507	0.247	0.494
	SF	1.751	0.506	0.180	0.598
	SM	1.669	0.469	0.051	0.582
	O1	1.484	0.486	0.170	0.543
	FB2	1.738	0.436	0.234	0.631
	FB1	2.166	0.435	-0.043	0.511
	FA	2.032	0.489	0.065	0.552
			Table

Acknowledgments

The research was funded by the Fondazione Monte dei Paschi (Siena), (grant 31017), Ente Parco Regionale di Migliarino, San Rossore, Massaciuccoli (Pisa), Centro Interuniversitario di Biologia Marina (CIBM, Livorno) and the University of Florence (local funds ex-60%) assigned to A.Ugolini.