M Falcão
email: mfalcao@cripsul.ipimar.pt

M N Santos

M Vicente

C C Monteiro

Biogeochemical processes and nutrient cycling within an artificial reef off southern portugal

Keywords: artificial reefs, benthic remineralization, biogeochemical process, nutrients, temporal changes

Biogeochemical processes and nutrient cycling within an artificial reef off southern portugal

INTRODUCTION

In recent years, great strides have been made in the understanding of artificial habitat ecology, although many questions regarding their performance and environmental impacts remain unanswered [START_REF] Carr | Artificial reefs: The importance of comparisons with natural reefs[END_REF]. One of the reasons for the poor understanding of AR ecology is the lack of knowledge of their effect on the surrounding natural environment [START_REF] Sheng | Physical characteristics and engineering at reef sites[END_REF]Svane & Petersen, 2001), which is a fairly new area of AR research. Scientific literature in this field is scarce and commercial technological applications have not been developed [START_REF] Antsulevich | Artificial reefs project for improvement of water quality and environmental enhancement of Neva Bay (St. Petersburg County Region)[END_REF]. In Portugal, research regarding these systems has been mainly focused on ichthyological fauna, especially on commercial species [START_REF] Santos | The Olhão artificial reef system (south Portugal): fish assemblages and fishing yield[END_REF], 1998;[START_REF] Santos | Diurnal variations in the fish assemblage at an artificial reef[END_REF][START_REF] Santos | Observations and trends on the intraannual variation of the fish assemblages on two artificial reefs in Algarve coastal waters (southern Portugal)[END_REF] and benthic communities [START_REF] Boaventura | Macrobenthic colonisation of artificial reefs on the southern coast of Portugal (Ancão, Algarve)[END_REF][START_REF] Moura | Sucessão bentónica num recife artificial no sul de Portugal -resultados preliminares[END_REF][START_REF] Moura | Effect of depth on the macrobenthic communities' biomass of the Algarve AR (southern Portugal)[END_REF].

Reef structures, by providing protection for marine species, can result in marine system biomass enhancement [START_REF] Santos | The Olhão artificial reef system (south Portugal): fish assemblages and fishing yield[END_REF], 1998;[START_REF] Godoy | Fish assemblages and environmental variables on na artificial reef north of Rio de Janeiro, Brazil[END_REF] with associated changes in local productivity [START_REF] Grossman | Do artificial reefs increase regional fish production? a review of existing data[END_REF][START_REF] Pickering | Artificial reefs and fisheries exploitation: a review of the "attraction versus production" debate, the influence of design and its significance for policy[END_REF]. As a result of biomass enhancement sediment becomes more active in the process of nutrient regeneration providing a nutritional source for other forms within the ecosystem [START_REF] Rizzo | Nutrient exchanges between the water column and a subtidal benthic microalgal community[END_REF], or being exported by water movements increasing the general productivity of neighbouring areas. Furthermore, planktivorous fish species can induce nutrient production in the water column, excreting substantial amounts of ammonium, urea and depositing organic material, which is then incorporated into the reef food web.

This process implies the increase of productivity and diversity on a local scale by increasing biotic and abiotic habitat complexity [START_REF] Ambrose | Influence of an artificial reef on the surrounding infaunal community[END_REF], promoting biological colonization and species richness in many ecological niches and food webs [START_REF] Relini | Patterns of sessile macrobenthos community development on an artificial reef in the Gulf of Genoa (northwestern Mediterranean)[END_REF].

In productive ecosystems the biogeochemical processes are extremely complex due to the interactions with the sediments and the benthic-pelagic competition of primary producers [START_REF] Fourqurean | Processes influencing water column nutrient characteristics and phosphorus limitation of phytoplankton biomass in Florida Bay, FL, USA: inferences from spatial distributions[END_REF]. In the case of nitrogen, sediments are a source as well as a major sink in the cycling of this element regulating its concentration and thus, the productivity of coastal marine systems (Lohse et al., 1993). Phosphorus is an essential nutrient for the growth of marine phytoplankton and has been suggested as the limiting factor for ocean primary production (Howarth et al., 1995). Most of P-removal from the water column takes place through sedimentation of organic matter [START_REF] Berner | The nature of phosphorus burial in modern marine sediments[END_REF]. Consequently, it is of prime importance to know the fate of the phosphorous in organic matter upon reaching the sediment [START_REF] Slomp | Early diagenesis of phosphorus in continental margin sediments[END_REF].

In the present study a survey was carried out during a two-year period in order to better understand AR's biogeochemical processes, the chemical composition of settled particles and nutrient cycling. The main goal of this study was to evaluate the trophic chain pull-out promoted by the deployment of concrete blocks on a sandy coastal area through organic matter deposition, benthic remineralization and local productivity.

METODOLOGY

Study site

The location of the study area was approximately 2.5-4.0 km off Faro (Algarve, Southern Portugal) on a flat sandy bottom (Figure 1). These sediments range from coarse sand (500 µm) to fine sand (125 µm). Drift currents tend to run along the shore, to depths of 30 m or more [START_REF] Moita | Plataforma continental. Carta dos sedimentos superficiais[END_REF][START_REF] Melo | Caracterização hidro-oceanográfica da Ria Formosa[END_REF]. The current speed may in extreme conditions reach 0.5 m s -1 . Tides are semi-diurnal with a mean tidal range of 2 m, with a maximum of 3.5 m and a minimum of 0.5 m. The Faro/Ancão AR consists of 5.460 concrete cubic units (2.7 m 3 each), distributed in 52 reef groups, occupying a narrow strip (6.727 ha), at depths ranging from 17 to 25 m (shallow waters). A sediment-trap with 6 PVC tubes (5 cm diameter and 50 cm length) was placed on a random reef block group (A 10 ) immediately after its deployment (August 2002).

Field sampling

Water sampling was carried out at AR group A 10 (37º 01 N; 7º 55 W) and at a control site-C (37º 01 N; 7º 57' W) located about 1.5 km from the AR (Figure 1) to eliminate or minimize the possibility that it might be affected by the presence of the man-made blocks. A multi-parameter deep-sea probe (Yellow Spring-mod.YSI 6820) was deployed in situ to determine temperature, dissolved oxygen and pH. Water samples were collected down the water column (surface-0.5 m; mean depth-10 m; and bottom-20 m: three replicates at each depth), using a Niskin bottle, during the years [START_REF] Nuccio | Phytoplankton abundance, community structure and diversity in the eutrophicated Orbetello Laggon (Tuscany) from 1995 to 2001[END_REF]2004 (February, May, August andNovember). Samples were stored in leakproof polycarbonate vials, completely filled and kept in a refrigerated chamber prior to determining ammonium, nitrate, phosphate, silicate, organic nitrogen and phosphorus, September). Organic and inorganic carbon, nitrogen and phosphorus were determined in settled particles. Divers simultaneously collected ten random sediment cores within the reef group (monthly from August 2002 to September 2004). Samples were kept in a refrigerator chamber prior to determining organic and inorganic carbon, nitrogen and phosphorus, chlorophyll a and phaeopigments.

Laboratory analysis

Solid fraction. Settled particles and sediment cores from upper layers (0-1 cm and 1-2 cm) were dried to 80ºC until a constant weight and ground to a fine powder. Total organic carbon (TOC), nitrogen (TON) and phosphorus (TOP) were determined in the powder samples. Total organic (TOC) and inorganic carbon (TIC) and total inorganic nitrogen (TIN), were determined by a CNH analyser "NC 2500 CE instruments" using acetanilide as reference material [START_REF] Byers | A comparison of methods of determining organic carbon in marine sediments with suggestions for a standard method[END_REF]. Total organic phosphorus was determined by digestion with HCl during 20 minutes at 200ºC according to [START_REF] Andersen | An ignition method for determination of total phosphorus in lake sediments[END_REF]. Phosphorus sorbed to litogenic particles was sequentially extracted: phosphorus weakly bound (weakly bound-P), 1 hour stirring with NH 4 Cl; phosphorus bound to calcium (Ca-bound P), 1 hour stirring with HCl and phosphorus bound to iron (Fe-bound P), 17 hours stirring with NaOH according to [START_REF] Chang | Fractionation of soil phosphorous[END_REF][START_REF] Chang | Fractionation of soil phosphorous[END_REF]Hosomi &Sudo (1982). Chlorophyll a (Chl a) was extracted with acetone (90 %) from the upper sediment layers and determined by spectrophotometry according to [START_REF] Lorenzen | Determination of chlorophyll and phaeopigments: spectrometric equations[END_REF] and dissolved organic phosphorus (DOP) were analysed by potassium peroxodisulphate (K 2 S 2 O 8 ) oxidation in autoclave (1.5 bar; 120º C) as described in [START_REF] Grasshoff | Methods of seawater analysis[END_REF] and oxidized forms determined in the autoanalyser. Chlorophyll a (Chl a) and phaeopigments (Phaeop) retained in filters were determined using a spectrophotometer "Hitachi 150-12" according to [START_REF] Lorenzen | Determination of chlorophyll and phaeopigments: spectrometric equations[END_REF].

Data analysis

Multivariate analysis of all information concerning water samples and its variability

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RESULTS

Temporal changes in sediment composition: C, N, P and Chl a

Results of sediment characteristics from August 2002 (AR deployment date) to

September 2004 are shown in Table 1. Two years after the reefs' deployment TOC, Febound P and Chl a were respectively 100, 3 and 2 fold higher than those obtained immediately before the AR deployment. Over the studied period, TOC and Chl a concentrations were significantly higher in sub-layer (ANOVA; n= 26; p<0.01), pointing to a hydrodynamic disturbance on the topmost sediment layer. During the studied period, organic nitrogen concentration in the seabed remained below the detection limit (<0.005 µmol g -1 dw ), while TOP concentrations (1.2 -2.6 µmol g -1 dw ) and sediment porosity (0.28 -0.31) presented slight differences. A well-defined seasonal variation was exhibited by TOC, TIC, Fe-bound P and Chl a, reaching the highest concentrations in the sub-layer, during 2004 Spring/Summer period.

Temporal changes in composition of sediment-trap settled particles: C, N, P

The time course of changes in particulate organic carbon (POC), nitrogen (PON) and phosphorus (POP) content of settled particles within the AR is presented in Table 2.

Results show a well-defined POC increased during the period of study. Mean concentrations of 590 µmol g -1 dw were observed before AR deployment, reaching 2.330 µmol g -1 dw and 3.292 µmol g -1 dw during 2003 and 2004 Spring/Summer periods, respectively. PON concentrations followed the same temporal pattern. A mean PON value of 2.5 µmol g -1 dw was found immediately before AR deployment, reaching 241 µmol g -1 dw and 178 µmol g -1 dw during the 2003 and 2004 Spring/Summer periods, respectively. Results also emphasize that POP mean concentration obtained before AR deployment (6 µmol g -1 dw ) reached values 1.5 to 2-fold higher during 2003 and 2004

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Spring/Summer periods. Alongside the time series, biogenic compounds also exhibited a clear seasonal pattern, reaching maximum concentrations during the warmer periods.

C/N and N/P ratios -Before AR deployment the C/N ratio of settled particles was in negative axis 1 and 2 (Figure 4a). An opposite cluster was defined by the control site euphotic and bottom water samples, corresponding to the lowest nutrient concentrations.

Down the water column profile, the high similarity observed among control site samples mean that stratification was not observed away from the AR. One year after AR deployment (Figure 4b) near bottom and euphotic water samples showed high affinity for organic nitrogen and phosphorus, which are well represented in positive axis 1 and 2.

In contrast, euphotic control site samples show maximum affinity to photosynthesis related parameters (DO and pH) which had the highest contribution in negative axis 2.

May: spatial variability -A well-defined stratification down the water column between near bottom and euphotic water samples both for AR and control site results from the high variance among samples during this month (Figure 5a). AR near bottom water reaches maximum affinity to nutrients and organic compounds, which are well represented in negative axis 1 and 2. Photosynthesis related parameters (Chl a, Phaeop, DO, pH) highly represented in positive axis 1 show the maximum affinity with AR and control site euphotic water samples. A similar pattern was observed one year later (Figure 5b) reflecting intense photosynthetic activity in superficial waters. Silicate availability and chlorophyll a high concentrations (6 µM and 3 µg L -1 , respectively), probably due to diatoms development during the Spring period reinforced the previous mentioned results. Nutrients and organic dissolved compounds that reach maximum representation in negative axis 1 led to a high affinity with near bottom water samples.

August: spatial variability -An evident contrast was observed between AR near bottom water and control samples in August (Figure 6a).

DISCUSSION

Artificial reef structures enhance settlement of organic matter in the seabed with the biological and chemical degradation of dead plants and animals leading to benthic remineralization [START_REF] Ambrose | Influence of an artificial reef on the surrounding infaunal community[END_REF]Lomstein et al., 1989;[START_REF] Rizzo | Nutrient exchanges between the water column and a subtidal benthic microalgal community[END_REF].

These findings may explain the rate of organic carbon accumulation in AR seabed (14 µg g -1 month -1 ). In fact, a linear relationship (TOC= 14.3m th -20.5; r 2 = 0.4; n= 19; p< 0.05) was obtained for TOC upper sediment layer over the period of study. Although an accumulation of TOC in the upper sediment layer was observed, the highest concentrations were recorded in the sub-layer (ANOVA; n= 19; p< 0.01). This may be due to hydrodynamic disturbance (winds, waves, and tidal currents) on topmost sediment that easily lose incorporated organic material. A significant exponential fit between TOC and Chl a (r 2 = 0.91; n= 19; p< 0.01) indicates a relationship between the sub-layer high TOC concentrations and benthic productivity. Such results were also reported in a study on a benthic-pelagic coupling system, indicating that fresh organic input result in benthic activity enhancement (Gutiérrez et al., 2000). As animal metabolic activities and decomposition processes may be transforming larges quantities of particulate nitrogen into dissolved-reduced forms [START_REF] Dame | The outwelling hypothesis and North Inlet, South Carolina[END_REF], the extremely low levels of organic nitrogen found in the seabed beneath the reef may be due to rapid turned over of nitrogen.. It is known that HPO 4 2-released from organic material is almost completely retained in sediment due to an early diagenetic "sink-switching" to authigenic carbonate fluorapatite (Ca-bound P) and to Fe-bound P [START_REF] Slomp | Early diagenesis of phosphorus in continental margin sediments[END_REF]. This could explain the relatively constant level of organic phosphorus in AR seabed over the two-year period, since phosphorus may be transferred to litogenic particles (Ca and Fe),

being Fe-bound P an intermediate chemical structure between organic phosphorus and carbonate fluorapatite [Ca 5 (PO 4 ,CO 3 ) 3 F], the most important source/sink for reactive dissolved phosphorus [START_REF] Slomp | Early diagenesis of phosphorus in continental margin sediments[END_REF].

It is known that artificial reefs enhance planktonic communities due to changes in water flow and turbulence patterns, bringing more plankton to bottom waters and promoting recycling of benthic nutrients (Haroun et al., 1994;[START_REF] Ambrose | Influence of an artificial reef on the surrounding infaunal community[END_REF].

Planktonic communities development in the AR surrounding environment are in accordance with POC, PON and POP time evolution. This fact highlights a clear pattern with lowest concentrations before AR submersion, followed by pulse increases during settled particles became clear due to biogenic material pull-out within a short time scale.

At the deployment stage high C/N and low N/P ratios were both abnormal (236 and 0.4, respectively). The reasons for such a phenomenon may be related to scarcity of biogenic material and fast nitrogen degradation, in relation to carbon and phosphorous. Nitrogen concentrations tended to decrease to zero, leaving a small phosphorous concentration.

Other authors have shown that nitrogen is the most important nutrient in limiting

phytoplankton growth in open sea [START_REF] Ryther | Nitrogen, phosphorus and eutrophication in the coastal marine environment[END_REF][START_REF] Codispoti | Phosphorus vs. Nitrogen limitation in new and export production[END_REF].

Artificial reefs have the capacity to promote biological production due to high availability of nutrients in the water column [START_REF] Relini | Patterns of sessile macrobenthos community development on an artificial reef in the Gulf of Genoa (northwestern Mediterranean)[END_REF][START_REF] Perkol-Finkel | Recruitment of benthic organisms onto a planned artificial reef: shifts in community structure one decade post-deployment[END_REF]. The highest concentrations of ammonium, nitrates, phosphates, silicates and organic nitrogen were observed in the reefs' near bottom water, in contrast to euphotic waters due to phytoplankton uptake in surface waters. In fact, higher values of chlorophyll a (2.7µg g -1 ) and pH (8.8) were observed in the AR and control site euphotic water mainly during Spring period. This may reflect photosynthesis effect, since micro and nanophytoplankton densities seasonal cycle are higher during Spring/Summer [START_REF] Nuccio | Phytoplankton abundance, community structure and diversity in the eutrophicated Orbetello Laggon (Tuscany) from 1995 to 2001[END_REF], due to nutrient availability and primary production pattern in coastal waters [START_REF] Fiala | Phytoplankton distribution in the Indian sector of the Southern Ocean during spring[END_REF]. Water temperature seems to play an important role in chemical and biological changes down the water column during the summer, since biological activity within euphotic zone may induce organic material production by exudation and excretion. This could explain the highest concentrations of dissolved organic compounds in euphotic water observed in August (2004). In this period, dissolved organic nitrogen was 20 % higher in the euphotic zone than near the bottom. Within the AR, water enrichment became more evident in November ( 2004),

showing higher percentages of ammonium (30 %), nitrates (21 %), silicates (70 %), DON (33 %), Chl a (30 %) and Phaeop (77 %), than at the control site, suggesting that two years after reef deployment chemical changes may be reflected in the water column.

Control site oligotrophic waters contrast with reef water emphasizing the role of substratum composition in water column nutrient enrichment. Similar findings were described in other oceanographic studies over the continental shelf in central Adriatic coast [START_REF] Fabi | Comparison between an artificial reef and a control site in the Adriatic Sea: analysis of four years of monitoring[END_REF], Scotland [START_REF] Wilding | The physical and chemical performance of artificial reef blocks made using quarry by-products[END_REF] and Canary Islands (Haroun et al., 1994).

According to other worldwide studies, artificial reef deployment has resulted in original community enrichment and diversification, increasing biotic and abiotic habitat complexity, ecological niches and food webs on a local scale [START_REF] Relini | Patterns of sessile macrobenthos community development on an artificial reef in the Gulf of Genoa (northwestern Mediterranean)[END_REF][START_REF] Fabi | Comparison between an artificial reef and a control site in the Adriatic Sea: analysis of four years of monitoring[END_REF][START_REF] Ambrose | Influence of an artificial reef on the surrounding infaunal community[END_REF]. The present study shows a trophic chain pull out due to nutrients, biogenic particles and microphytobenthos enrichment two years after the deployment of the Faro/Ancão artificial reef. The organic sediment enhancement and water nutrient enrichment within the reef system reinforces the importance of these man-made structures as a potential tool in the modification of coastal ecosystems as described by [START_REF] Pickering | Artificial reefs as a tool to aid rehabilitation of coastal ecosystems: Investigating the potential[END_REF].

TABLES CAPTIONS

Table 1 -Concentrations (mean ± sd) of total organic carbon (TOC), total inorganic carbon (TIC), weakly bound-P, Fe-bound P, Ca-bound P and total organic phosphorus (TOP), within the sediments of the artificial reef (A 10 ), from Summer 2002 to Summer

2004.

Table 2 -Concentrations (mean ± sd) of particulate organic carbon (POC), particulate organic nitrogen (PON) and particulate organic phosphorus (POP), in the settled particles of sediment traps within the artificial reef from Summer 2002 to Summer 2004.

FIGURES CAPTIONS

A 10 P O R T U G A L Figure 1-

  chlorophyll a and phaeopigments. Sediment-trap tubes were collected and replaced each month by divers during Summer 2002 (August and September); Autumn 2002/Winter 2003 (October, November, December, January and February); Spring/Summer 2003 (April, May, July and August); Autumn 2003/Winter 2004 (September, October, December, January, February) and Spring/Summer 2004 (March, July, August and

  abnormally high, due to low PON concentrations (Figure 2). Six months after AR deployment, C/N ratio became close to Redfield value, remaining approximately constant over 2003 and 2004. An abnormally low N/P ratio (<2) was obtained before AR submersion resulting from the extremely low PON values. During 2003 and 2004 Spring/Summer periods, N/P ratio (Figure 3) reached standard values of 10 to 20. Water column: spatio-temporal variability Data on physical (Temp, DO and pH), chemical (NH 4 biological (Chl a and Phaeop) parameters occurring in the water column, within the AR (A 10 : R 0 , R 10 , R 20 ) and at the control site (C: C 0 , C 10 , C 20 ), were obtained during this study. Principal component analysis (PCA), applied to the overall data showed a spatial variability through a two-dimensional space, defined by two principal coordinate axes (A1 and A2). More than 50 % of the analysis is explained by the axis inertia. The descriptors (parameters) and location -A 10 (0.5 m; 10m; 20m) and C (0.5 m; 10 m; 20m) -at February, May, August and November of 2003 and 2004, are represented in the PCA (Figures 4 (a,b) , 5 (a,b) , 6 (a,b) , 7 (a,b) ).February: spatial variability -AR near bottom water samples were closely associated with , Chl a and Phaeop which have the highest contribution

  AR near bottom water samples are well represented in the negative axis 1 showing affinity with Si(OH) 4 contrast to AR euphotic water samples, possibly due to biological nutrient consumption in surface waters. A similarity among all control site water samples, closely associated with pH, Chl a and NO 3 -was observed showing no stratification at AR control areas. One year later (Figure6b), a high variance between near bottom and euphotic water samples was observed both for AR and control site water samples, pointing to a well-defined stratification along the water column. Organic dissolved compounds and photosynthesis related parameters (DO, pH, Chl a) affinity with euphotic water samples was the most important result observed in August. The near bottom water samples were closely associated with nutrients (variability -The highest variance between AR and control site water samples was observed in November (Figure7a). The DON, ) 4 , DO, Chl a and pH, highly represented in positive axis 1, were closely associated with AR near bottom water samples pointing to a clear environmental difference between the AR and control site. The same spatial pattern was found one year later (Figure7b), emphasising the association between environmental parameters and all AR samples.

  reef site in Gran Canaria (Canary Islands, Spain) prior to reef placement. Bulletin of MarineScience, 55 (2-3), 932-938. Hosomi, M. & Sudo, R. (1982). Release of phosphorous from lake sediments.EnvironmentInternational, 7, 93-98. Howarth, R.W., Jensen, H.S., Marino, R. & Postma, H. (1995).Transport to and processing of P in near-shore and oceanic waters. In H. Tiessen (Ed.), Phosphorus in the Global Environment: Transfers, Cycles and Management. SCOPE (pp. 323-345). UK: Wiley Sons. Legendre, L. & Legendre, P. (1984). Écologie numérique 2. Le traitement multiple des données écologiques. Mason-Paris et Presses de L'Université du Québec-Canada, 335 p.Lohse, L., Malschaert, J. F. P.,Slomp, C. P., Helder, W. & VanRaaphorst, W. (1993).Nitrogen cycling inNorth Sea sediments: Interaction of denitrification and nitrification in offshore and coastal areas. Marine Ecology Progress Series, 101, 283-296. Lomstein, B. A., Blackburn, T. H. & Henriksen, K. (1989). Aspects of nitrogen and carbon cycling in the northen Bering Shelf sediments. I. The significance of urea turnover in the mineralization of NH 4 + . Marine Ecology Progress Series, 57, 237-247.

Figure 1 -

 1 Figure 1 -Location of the Faro/Ancão artificial reef off Faro (Algarve, southern

Figure 2 -

 2 Figure 2 -Values of C/N ratio in settled particles from Summer 2002 to Summer 2004.

Figure 3 -

 3 Figure 3 -Values of N/P ratio in settled particles from Summer 2002 to Summer 2004.

Figure

  Figure 4 (a,b) -Principal Component Analysis ordination plots of physical (DO, pH),

  Figure 2 -

  .

	Water column. Water samples were filtered through 0.45 µm Millipore filters and stored
	at -4º C until nutrient analysis. Ammonium (NH 4 + ), nitrate (NO 3	-), phosphate (HPO 4	2-)
	and silicate Si(OH) 4 were determined using a "Skalar" autoanalyser (Skalar
	methodology). Detection limit used in the present method was 0.2 µM for ammonium
	and silicate and 0.05 µM for nitrate and phosphate. Dissolved organic nitrogen (DON)

Table 1 -

 1

	Layer	TOC	TIC	Wb-P	Fe-bound P	Ca-bound P	TOP	Chl a
	cm	µmol g -1	µmol g -1	µmol g -1	µmol g -1	µmol g -1	µmol g -1	µg g -1

ACKNOWLEDGEMENTS

The authors would like to thank the IPIMAR/CRIPSul scientific diving team (P. Lino, F. Leitão, J. Cúrdia and M. Ferreira) and the crew of RV "PUNTAZZO" for helping during ACCEPTED MANUSCRIPT the fieldwork. The authors are in debt to Dr. J. Santos for his support in this paper revision and also thanks to M.L. Santos for her help in the field and laboratory work.

This study was carried out within the project "Implantação e Estudo Integrado de Sistemas Recifais", supported by the MARE programme.

parameters (concentration range) in water column within the AR ( -0.5 m; -10m; -20m) and C-control site (Ο-0.5 m; -10 m; -20m), in February (2003 and[START_REF] Moura | Sucessão bentónica num recife artificial no sul de Portugal -resultados preliminares[END_REF].


Ronald A Kastelein

Sander Van Der Heul

Jan Van Der Veen

Willem C Verboom

Nancy Jennings

Dick De Haan

Peter Reijnders

Effects of commercially-available acoustic alarms, designed to reduce small cetacean bycatch in gillnet fisheries, on the behaviour of North Sea fish species in a large tank

Keywords: Acoustics, Cetaceans, Cod, Ecology, Herring, Noise pollution, Odontocetes, Pingers, Pout, Sea bass, thicklip mullet, Underwater sound

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

World-wide, every year, over 300,000 cetaceans are estimated to drown incidentally in fishing nets [START_REF] Read | Bycatch of marine mammals in U.S. and global fisheries[END_REF]. Many small odontocetes drown after accidental capture in gillnets [START_REF] Lewison | Understanding impacts of fisheries bycatch on marine megafauna[END_REF]. One potential alternative to reducing the incidental bycatch of small odontocetes in gillnets by time and area closures of fisheries, change in fisheries practices, or by fish gear modifications, is to deter the animals from the nets acoustically. The presently commercially-available pingers used to do this produce sounds between 10 and 160 kHz. Field studies with pingers on set gillnets have produced promising results with harbour porpoises (Phocoena phocoena; [START_REF] Lien | Field tests of acoustic devices on groundfish gillnets: assessment of effectiveness in reducing harbour porpoise by-catch[END_REF][START_REF] Kraus | Acoustic alarms reduce porpoise mortality[END_REF][START_REF] Laake | Observations of Harbor Porpoise in the Vicinity of Acoustic Alarms on a Set Gill Net[END_REF]Trippel et al., 1999;[START_REF] Gearin | Experimental testing of acoustic alarms (pingers) to reduce bycatch of harbour porpoise, Phocoena phocoena, in the state of Washington[END_REF][START_REF] Anonymous | Annex I, Report of the Sub-Committee on Small Cetaceans[END_REF][START_REF] Barlow | Field experiments show that acoustic pingers reduce marine mammal bycatch in the California drift gill net fishery[END_REF], and studies in captivity have shown that pingers elicit avoidance behaviour in porpoises [START_REF] Kastelein | The effects of acoustic alarms on Harbour porpoise (Phocoena phocoena) behaviour[END_REF]1997;[START_REF] Anonymous | Annex I, Report of the Sub-Committee on Small Cetaceans[END_REF]2001). Behavioural studies in the field also show that porpoises avoid pingers [START_REF] Laake | Observations of Harbor Porpoise in the Vicinity of Acoustic Alarms on a Set Gill Net[END_REF][START_REF] Culik | Reactions of harbor porpoises Phocoena phocoena and herring Clupea harengus to acoustic alarms[END_REF]. Although pinger use in gillnet fisheries is increasing, the long-term effects of pingers on porpoise bycatch and on non-target marine animals have not yet been studied.

One undesirable side-effect of pingers is local noise pollution, which may disturb marine fauna other than the species targeted. Knowledge of the ability of many marine animals to detect sound, and of the effects of sound on them, is limited. Marine animals are likely to be disturbed by anthropogenic noise in their environment, and intense sounds may cause negative physiological, auditory, and behavioural effects [START_REF] Richardson | Marine Mammals and Noise[END_REF]. Sounds produced by pingers should reduce bycatch of odontocetes and perhaps other species, but should cause minimal noise pollution for other marine fauna.

The use of pingers will become widespread, as they become compulsory in some areas in 2005 and in others in 2007 for EU fishing vessels larger than 15 m. Therefore, before pingers are widely used, their effects on marine animals, and especially fish, should be studied. Pingers developed to reduce odontocete bycatch should not deter the fisheries' target species from the gillnets, and should not deter target or non-target fish from ecologically important areas such as feeding and breeding grounds, or mask their communication sounds.

In some field studies on the effects of pingers on odontocetes, the size of the fish catch in nets with and without pingers has been compared. The effects of pingers on fish [Clupeids, cod (Gadus morhua) and Chinook salmon (Oncorhynchus tshawytscha)] in pens and tanks have also been investigated. Only one study suggests a reduction in catch rate of the target fish species. All other studies showed no effect on catch rate or on the behaviour of the fish in a pen or tank (Table 1).

Fish use sound for a variety of functions including hunting, territorial behaviour, bonding, spatial orientation, predator detection, and escape. Most audiograms of marine fish species indicate that their best sensitivity to sounds is within the 100 Hz -2 kHz range. This narrow bandwidth of hearing sensitivity could be due to mechanical limitations of the sense organs (Astrup andMøhl, 1993, 1998;[START_REF] Motomatsu | Auditory masking by ambient noise in black rockfish Sebastes schlegeli[END_REF]Mann et al., 1997[START_REF] Mann | Detection of ultrasonic tones and simulated dolphin echolocation clicks by a teleost fish, the American shad (Alosa sapidissima)[END_REF][START_REF] Mann | Ultrasound detection by clupeiform fishes[END_REF]2005;[START_REF] Akamatsu | Startle response level of the Japanese anchovy Engraulis japonicus to underwater pure tone signals[END_REF][START_REF] Akamatsu | Spotlined sardine Sardinops melanostictus listens to 1-kHz sound by using its gas bladder[END_REF][START_REF] Anraku | Flounder show conditioned response to 200-800 Hz tone bursts despite their conditioning to 300 Hz tone-bursts[END_REF]. Some researchers have investigated the effects of sounds on the behaviour of marine fish [START_REF] Moulton | Annotated references concerning the effects of manmade sounds on the movements of fishes[END_REF]Blaxter et al., 1981;[START_REF] Blaxter | Startle response in herring: the effect of sound stimulus frequency, size of fish, and selective interference with the acoustico-lateralis system[END_REF][START_REF] Fuiman | Ontogeny of routine swimming speed and startle responses in red drum, with a comparison of responses to acoustic and visual stimuli[END_REF][START_REF] Enger | Detection and reaction of fish to infrasound[END_REF][START_REF] Knudsen | Avoidance responses to low frequency sound in downstream migrating Atlantic salmon smolt, Salmo salar[END_REF][START_REF] Luczkovich | Sounds of sex and death in the sea: bottlenose dolphin whistles suppress mating choruses of silver perch[END_REF][START_REF] Finneran | Source levels and estimated yellowfin tuna (Thunnus albacares) detection ranges for dolphin pops, breaches and tail slaps[END_REF][START_REF] Lagardère | Influence of windproduced noise on orientation in the sole (Solea solea)[END_REF]Løkkeborg and Soldal, 1993;[START_REF] Engås | Effects of seismic shooting on local abundance and catch rates of cod (Gadus morhua) and haddock (Melanogrammus aeglefinus)[END_REF][START_REF] Pearson | Effects of sound from a geophysical survey device on behaviour of captive rockfish (Sebastes spp.)[END_REF][START_REF] Skalski | Effects of sound from a geophysical survey device on catch-per-unit-effort in the hook-and-line fisheries for rockfish (Sebastes spp.)[END_REF][START_REF] Hawkins | Underwater sound and fish behavior[END_REF][START_REF] Popper | Application of the use of sound to control fish behavior[END_REF]Wahlberg and Westerberg, 2005).

The sounds made by commercially-available pingers differ from the sounds used in previous studies on the effects of sound on fish. Therefore the aim of the present study was to determine whether commercially-available pingers, designed to deter small cetaceans from gillnets, have any effect on the behaviour of certain North Sea fish species under controlled conditions in a tank.

Materials and methods

Study animals

Five fish species regularly occurring in the North Sea were selected for testing based on their availability, their ease of maintenance in captivity, the temperatures at which they can be kept (the water temperature in the tank was influenced by the air temperature of the environment), and their economic importance in fisheries. In addition, the animal welfare commission of the Netherlands government stipulated that the individual fish used had to feed readily in captivity, so they had to come from aquaria.

A school of 9-13 individuals of each species was placed in a tank. The sea bass (Dicentrarchus labrax), pout (also called bib, or pout whiting in the US; Trisopterus luscus), thicklip mullet (Chelon labrosus), and cod (Gadus morhua) were supplied by "Het Arsenaal Aquarium", Vlissingen, and the herring (Clupea harengus) by the Oceanium department of "Blijdorp Zoo", Rotterdam. Characteristics of the fish are shown in Table 2. The fish had been wild-caught by hook and line or in a trap, so that damage to their swim bladder, which may be involved in hearing in some fish species, was unlikely. The fish used in this study were all adapted to captivity and were feeding voluntarily. Except for herring, the fish were fed ad lib. on pieces of raw fish (food was given until the animals stopped eating) twice a week, after the daily study sessions. Herring were fed ad lib. on pellets (Troutvit, size 00; Nutreco Aquaculture) once a day, after the study sessions.

Study area

The experiments were conducted in an outdoor tank at the field station of the Netherlands National Institute for Coastal and Marine Management (RIKZ) at Jacobahaven, Zeeland, the Netherlands. The freestanding rectangular tank (7.0 m long, 4.0 m wide; water depth: 2.0 m) was made of plywood covered on both sides with fibreglass (Fig. 1). A layer of 3 cm thick hard-pressed Styrofoam was placed between the bottom of the tank and the concrete floor, to reduce contact noise from the environment in the pool. The pool walls were blue (Ral colour 50/15). Red gridlines (1.5 cm wide) were taped on the walls and bottom of the tank at 0.5 m intervals in the vertical direction and at 1 m intervals in the horizontal direction.

To reduce predation by birds, algal growth, impact of noise from rain, glistening of the water surface, and to create a more even light pattern in the pool, a blue tarpaulin canopy was suspended at an angle above the water surface (1.5 m on one side and 0.75 m on the other side).

Scaffolding surrounded the pool for easy access, but made no contact with the pool. Two research cabins were placed on one side of the scaffolding: one to house the video recording equipment and sound generation equipment, and one to house the sound calibration equipment.

The water was pumped directly from the nearby Oosterschelde (a North Sea estuary in the SW coast of the Netherlands). The salinity was 30-33 ‰, the pH 7.9-8.1, nitrogen concentration < 5 mg/l N, and nitrate concentration < 0.1 mg/l. To ensure the good water clarity needed to film the fish, the water was circulated via sand and carbon filters and UV light. During the experiments the water system was a closed circuit for the period in which each fish species was tested (about 5 weeks). Water parameters (temperature, salinity, oxygen, and nitrate) were measured daily and remained well within the boundaries suitable for the fish. The water temperature varied during the study period due to fluctuations in the air temperature. During the test period with the sea bass, the water was heated to keep it above 4 °C, so that the fish showed normal swimming behaviour (Table 3).

The week before each species was tested, the fish were kept in a white polyester 2.2 m diameter holding tank with a water depth of 1 m. The tank stood next to the test tank and contained the same water composition at the same temperature as the test tank.

To make the environment inside the tank as quiet as possible, the filter unit had a lownoise pump. To reduce contact noise entering the pool, the pump and filter unit were placed on rubber tiles. To reduce contact noise, flexible tubes were used to connect the filtration pump to the pool.

As the pump in the pool was extremely quiet, it was left on during the experiments, so as not to change the ambient noise before and during the test periods. The background noise level in the pool is shown in Figure 2. To maintain sufficient light for the underwater cameras, two lamps (2000 Watts each) were lit 30 cm above the water surface. The lamps were switched on at least half an hour before a session began and were only used when required to obtain good video images (during an entire session they were either on or off).

Stimuli

In order to identify the behavioural parameters which indicated a response for each fish species, the individuals of each species were first submitted to sounds that were known to have an effect on them (the 'known effect' sounds). A 600 Hz tone pulse produced clearly visible responses in all species except herring and cod. For herring, a 3 kHz tone pulse was used (for specifics of the signals see Table 4). For cod, no response could be elicited to any sound that could be produced with the available equipment, though loud 300 ms duration sounds in a wide frequency range (50 Hz-60 kHz) were offered. The sounds were produced by a generator (Hewlett Packard, model 33120A), a power amplifier (Quad 150), an impedance matching transformer, and an underwater transducer (Ocean Engineering Enterprise, model DRS-8; 20 cm diameter).

Once the behavioural parameters that indicated a response had been identified for each fish species, the effect of seven commercially-available pingers on the behaviour of the five fish species was quantified by comparing the parameters during baseline periods (pinger off) with those during test periods (pinger on). Although the reaction of fish to sounds may be spectrum-dependant [START_REF] Nestler | Responses of Blueback Herring to High-Frequency Sound and Implications for Reducing Entrainment at Hydropower Dams[END_REF], the fish responded to the pingers in the same way as they had to the 'known effect' sounds.

The pingers were suspended from ropes 20 cm from the pool wall, and were positioned horizontally at 1 m below the water surface, half way up the water column (Fig. 1). A weight of 150 g underneath each pinger kept it at the right depth. To avoid influencing the behaviour of the fish by human action, each pinger was modified so that it could be activated remotely from inside the research cabin.

During test sessions sounds were monitored by use of a hydrophone (Labforce 1 BV, model 90.02.01), a custom made pre-amplifier, and an amplified loudspeaker. For sounds above 16 kHz, the hydrophone was connected to a heterodyne bat detector (Stag Electronics, UK, model Batbox III) to make the signal audible to the researchers.

Sound parameters and Sound Pressure Level distribution in the tank

In order to measure the Sound Pressure Levels (SPLs) fish had been exposed to, the SPLs of all sound sources were measured at distances of 1 and 6 m from the sound source at the depth of the pinger/transducer. Sounds were measured with a hydrophone (Brüel & Kjaer (B&K), model 8101) connected to a battery-powered conditioning amplifier (B&K, model Nexus 2690). The output was connected, via a coaxial module (National Instruments, model BNC-2090), to a computer (Joheco, PIV-1.6 GHz) with a data acquisition card (National Instruments, model PCI-MIO-16E-1), on which signals were digitised with a sample frequency of 512 kHz and 12-bits resolution. A pistonphone (B&K, model 4223) was used as a reference to calibrate the system. Monitoring, recording and analysis of sounds were accomplished by the use of software modules developed by IMARES (in National Instruments, Labview 6.0).

The sound sources and their measured acoustic properties are shown in Table 4. The Source Levels (SLs) of the pingers are shown as SL pulse which is the signal level fast Fourier transformed (FFT) over the duration of the signal according the formulae:

= T rms dt p t p T spl 0 2 0 2 ) ( 1 log 10
In which spl is Sound Pressure Level, rms is root-mean-square, T is time, p is pressure, p 0 is the reference pressure, and dt is the time window. To compare the levels of pinger signals with constant time intervals to those with randomized repetition rates, the levels of all signals measured at 1 m distance are also integrated in FFT over the time of a complete cycle (time between two rise times), this level is called SL cycle (also known as L eq ). For randomized signals the SL cycle is calculated over the shortest, average and longest repetition rate. The results of the randomised signals are based on file lengths of 195 s and therefore may not be representative for the timing over longer time periods, such as during the test sessions.

A Dukane NetMark 1000 pinger was used as a reference to validate the SPL measurements of sound sources at 1 m distance. The measured SL in the tank with the hydrophone at 1 m from the pinger deviated by approximately 2 dB from the calculated SL of the same pinger based on a measurement in open sea with the hydrophone 2 m from the pinger. Recordings of the SaveWave black high impact and white high impact pingers were also compared with those of the same pingers measured at sea. These levels matched within 3 dB.

The SPLs measured at 6 m from the source demonstrate the contribution of the reverberant effects of the sound in the tank and showed that the sound propagation loss did not follow the formula SPL = SL -[20 log R], in which R is the distance in m between the sound emitter and the recording hydrophone. In fact, the SPL and pulse duration of the sound sources hardly decreased with distance from the transducer. The 'sweep pingers' (SaveWave and AQUAmark) all produced low frequency components in the range of 0.5-5 kHz, with peaks 30-40 dB above the system noise level. The 10 kHz tonal pingers (Fumunda and Airmar) did not produce these low frequency components.

Observation equipment

The behaviour of the fish was recorded by three black-and-white underwater video cameras (Mariscope, model Micro). The cameras were mounted in a row along one side of the pool (Fig. 1), at a depth of 1 m, so that about 60 % of the water volume was in view.

Methodology

In each test a school of fish of only one fish species was used, in order to avoid the behaviour of one species influencing the behaviour of another. The 9 -13 fish of each species were placed in the tank at least three days before the first session was conducted, to allow the fish to habituate to the tank. The pinger (or transducer for 'known effect' sounds) was placed in the pool at least one hour before a session. Each session consisted of a 10-minute baseline period during which no sound was produced, followed immediately by a 10-minute test period during which the pingers were active or the 'known-effect' sound was produced.

Each day, four sessions of 20 minutes each were conducted (at 08.30, 10.00, 11.30, and 13.00 h). Each session a different pinger was used in random order. Per fish species, each pinger was tested up to 11 times over a period of around five weeks. The study was conducted between November 2003 and July 2004.

Analyses of video recordings

Behavioural parameters were measured from the video recordings. The images from the three cameras were synchronized by means of a marker signal which was produced every minute from a tape recorder in the research cabin and recorded on the audio tracks of the video recorders. A scan sampling technique was used: at the end of each minute during the 10 minute recording period, the tape was stopped and the image was analysed. From each camera image, only the behaviour of fish in a specific section of the tank (the boundary of which was determined by the grid on the pool wall) was analysed. Because the three images overlapped somewhat, this method ensured that each individual fish was recorded only once per scan moment. Fish behaviour was only measured where it could be quantified accurately, in approximately a quarter of the volume of the tank. That meant that the behaviour of the fish was only scan-sampled when they were in the 1 m section of the wall opposite the cameras (Fig. 1), and swimming parallel to the wall (so that location and swimming speed could be measured accurately). All distance parameters were determined with 10 cm accuracy. A fourth aerial camera with a wide angle lens, placed in front of the window on one end of the pool, provided a general view of how the fish swam in the tank. Images from this camera showed that none of the fish species tended to swim near the underwater cameras.

The following response parameters were derived from the video footage:

1. School length. The distance between the fish closest to the pinger or transducer and the one furthest away. Reasoning: fish may school tighter when feeling threatened. 2. Distance to bottom. Distance between the centre of each fish and the bottom of the tank (range: 0.1-2.0 m). Reasoning: fish may drop to the bottom when feeling threatened. 3. School height. The distance between the fish closest to the bottom and the one furthest away from it. Reasoning: fish may school tighter when feeling threatened. 4. Swimming speed. The speed of each fish was determined by measuring the time (by stopwatch) it took to swim 1 m (from one vertical line on the wall to the next) after the scan signal. If fish were swimming in a school, all fish were given the same speed. If the distance between a fish and the school was more than 0.5 m, its speed was measured separately. Reasoning: fish may speed up when feeling threatened. 5. Polarisation in the school. The proportion of a group of fish in the view of a camera swimming in the same direction. Fish with swimming directions differing less than 90 degrees were defined as swimming in the same direction. Reasoning: fish may increase polarisation when feeling threatened.

Statistical analysis

Per scan moment, the mean of all parameters of all visible fish (total of all recordings of the three cameras) was taken, and then the mean for each baseline or test period (n = 10 for each period; one scan moment per minute during the 10-minute period) was used for the analysis.

The difference in the mean variables between baseline and test (calculated as test minus baseline) was compared to zero in paired statistical tests. The response to the 'known effect' sound was first considered for each species. Paired t-tests, or if the differences were not normally distributed, Wilcoxon matched pair tests (Zar 1984), were used to evaluate the effect of the sounds on the behavioural parameters. From the results of these tests, for each species, response parameters were identified, which were defined as those which showed a significant ( = 0.05) response to the 'known effect' sounds. Only these response parameters, which differed for each fish species, were compared in baseline and test periods with the pingers. Paired t-tests or Wilcoxon matched pair tests, as appropriate, were used as described above. Statistical tests were carried out using Minitab release 13 [START_REF] Ryan | Minitab handbook[END_REF] and were all two-tailed.

Results

General swimming behaviour and effects of "known effect" sounds on each fish species

The general behaviour of the five fish species used in the present study differed (Table 5). Results of the statistical tests on all measured parameters showed that responses to the 'known effect' sounds also varied between species. Sea bass and thicklip mullet responded by increasing their speed and swimming closer to the bottom, herring by increasing their speed, and pout by swimming closer to the bottom (Table 6). No response at all could be elicited in cod, although several sounds that were certainly audible to them [START_REF] Buerkle | An audiogram, of the Atlantic cod, Gadus morhua L[END_REF][START_REF] Chapman | A field study of the hearing in cod, Gadus morhua L[END_REF][START_REF] Offutt | Structures for the detection of acoustic stimuli in the Atlantic codfish, Gadus morhua[END_REF], and some at higher frequencies, were tried. No species responded to 'known effect' sounds by increasing the school length or height, or by increasing the polarisation in the school. The behavioural parameters that did change during sound emissions were thus identified for each species, and were measured and compared in the tests with the pingers.

Effects of pingers on each fish species

Sea bass responded to the AQUAmark 100 and Fumunda pingers, but opposite to their response to the 'known effect' sound. They swam more slowly when the AQUAmark 100 pinger was active and swam closer to the water surface when exposed to the sound of the Fumunda pinger (Fig. 3(a) and(b)). Thicklip mullet reacted to the Airmar pinger by increasing speed, and to the AQUAmark 100 and SaveWave white high impact pingers by swimming closer to the bottom (Fig. 3 (c), (d) and(e)). Herring reacted to the Airmar pinger by increasing speed. Cod and pout did not respond in any way to any pinger, and although for cod, in the absence of 'known effect' parameters, all six recorded behavioural parameters were tested, no significant differences between baseline and test were found. No reactions were observed in any of the five fish species to the AQUAmark 200, the SaveWave endurance and SaveWave black high impact pingers (Table 6).

Discussion and conclusions

Evaluation of the observations

Of the five behavioural parameters recorded, only swimming speed and distance to bottom formed part of the response to pingers and 'known effect' sounds. The fish species did not respond to the pingers or 'known effect' sounds by swimming closer together (horizontally or vertically) or by increasing the polarisation of the school. As this is a pilot study, it was important to test all available pingers, and also, given the potential variability in response, to quantify many different behavioural parameters. In follow-up studies in similar contexts, emphasis can be placed on the behavioural parameters shown to be affected in the present study.

In fisheries, pingers are attached to gillnets. Fish that are about to be caught in the nets are close to the pingers, and are therefore exposed to sound levels similar to those experienced by the fish in the present study. So, the responses observed in the fish species in the present study may be observed in the wild in fish near nets (at < 6 m distance). Whether the use of pingers will cause a drop in catch rate cannot be predicted from the present study. Responses may be influenced by environmental parameters such as location, water depth (pressure), time of day, and water temperature, and may depend on the animal's behaviour, physiological condition, and motivational condition. Responses are also influenced by the surrounding fauna (conspecifics, prey or predators).

In the rectangular tank, resonance enhanced specific components of the projected sound. Because gillnet fishery in the North Sea is usually carried out in shallow water or near wrecks, resonant effects between the bottom and the water surface may also occur at sea (although less than in a tank).

The size of a tank has an influence on the general swimming behaviour of many fish species. The fish swam very slowly or not at all in the small holding tank (2.2 m diameter, 1 m deep). In the large test tank, they were much more active. So, although the test tank was far from a natural environment, it may be a much better study area than the smaller tanks that have been used in several previous studies on the effects of sound on fish.

This experiment was not designed to test whether fish move away from the sound. In the confines of the tank, the sound did not attenuate as it would have done at sea, so a larger tank (or better a floating pen) would have been needed to test for movement away from the sound. In fact, the SPL measurements showed that due to the reverberant field, the sound in the tank did not attenuate over distance. The SPL differed per location because of resonance, but did not vary in relation to the sound source. Therefore, a response consisting of a move away from the sound source was not expected in the present study based on an SPL gradient. In addition, moving away from a sound source requires directional hearing, which these fish may or may not possess. Furthermore, the loss in exposure level by moving away from a sound source in the sea is very small if the fish is not very close to the sound source. For example, moving from 10 to 11 m away from a sound source will only reduce exposure level by less than 1 dB and the fish must move to 20 m to reduce the received level with 6 dB. Moving up or down the water column may provide a much larger reduction in exposure level as the fish could move into an acoustic shadow zone.

Potential causes of differences in behavioural responses to pingers

The effect of a pinger may depend on properties of the sound, such as frequency spectrum, duration, repetition rate, background noise (acoustic interference, masking), SPL (exposure level) and spectrum received by the animal, and exposure duration, as well as properties of the animal, such as hearing properties (sensitivity, critical ratio and receiving beam pattern), and species-specific or individual behavioural reactions to sound. The reactions of the fish in the present study to the 'known effect' signals could be described as startle responses, whereas the animals' responses to some of the pingers were slow and more subtle. The exposure level to a sound may also influence the direction of a reaction. Low exposure level sounds can be attractive, whereas the same sounds can be deterrent at higher exposure levels. Signal duration also plays a role in the effect of a sound on fish; a 500 ms pulse length provides adequate time for fish to detect and react to a sound [START_REF] Hawkins | The hearing abilities of fish[END_REF][START_REF] Nestler | Responses of Blueback Herring to High-Frequency Sound and Implications for Reducing Entrainment at Hydropower Dams[END_REF][START_REF] Dunning | Alewives avoid high-frequency sound[END_REF].

Three fish species in the present study reacted to one or more of four of the seven pingers tested. There are many acoustic differences between the pingers, so it is difficult to determine which acoustical parameter caused the behavioural effect in a particular fish species. However, thicklip mullet and sea bass reacted to the AQUAmark 100 and not to the AQUAmark 200. Most parameters of both pingers were similar, but the source level of the AQUAmark 100 was around 14 dB higher than that of the AQUAmark 200. Although the Fumunda and Airmar both produce a low frequency (LF) fundamental frequency around 10 kHz, the Fumunda had more energy in harmonics (Table 4). Herring and thicklip mullet reacted only to the Airmar pinger, while sea bass reacted only to the Fumunda pinger. It is possible that differences in the orientation of sound beams between the two pingers, or in the hearing sensitivity of the species, caused them to react differently to the two similar pingers. The Airmar pinger contains air, which causes some directional effects. The directionality was not checked for this study, but the pingers were in a horizontal position, as they would be if used in fisheries. In a previous study, herring did not react to a Dukane NetMark 1000 pinger (Wilson and Dill, 2002), which is designed to be equivalent to the Airmar and Fumunda pingers used in the present study. These pingers are compulsory in some US gillnet fisheries for part of the year. In the present study, the herring increased their swimming speed when subjected to the sounds of the Airmar pinger, which produced less harmonic energy than the Fumunda and Dukane NetMark 1000 pingers. The sweep pingers (AQUAmark 100 and 200 and SaveWave) produced energy in the 0.5-5 kHz frequency range, and it is possible that the fish reacted to these low frequency components of the spectrum.

Thicklip mullet reacted to the SaveWave white high impact pinger but not to the other two SaveWave pingers. This could be because the level of the SaveWave white high impact pinger was around 15 dB higher than that of the SaveWave endurance pinger or because its spectrum was lower in frequency than that of the other two SaveWave pingers. Because the duration of the pulse and the repetition rate of the SaveWave endurance pinger were proportional, the SL cycle levels of the minimum cycle were equal to the levels measured over the maximum cycle and also much lower than those of the other two SaveWave pingers (-10 dB) (Table 4).

In some cases the sound characteristics measured for this study differed from the manufacturer's specification. The SL of the SaveWave pingers were 10 dB lower than the SL specified by the manufacturer, while the SL of the Fumunda pinger was 10 dB above the specified SL. The pulse duration of the Fumunda pinger was 300 ms instead of the specified 400 ms. The SL of the AQUAmark 100 pinger was 10 dB above the specified SL, while the AQUAmark 200 pinger was 10 dB below the specified SL.

Information on hearing sensitivity is available for sea bass (J. Lovell in [START_REF] Nedwell | Fish and Marine Audiograms: a summary of available information[END_REF], herring [START_REF] Enger | Hearing in herring[END_REF][START_REF] Blaxter | Startle response in herring: the effect of sound stimulus frequency, size of fish, and selective interference with the acoustico-lateralis system[END_REF]Blaxter et al., 1981;[START_REF] Schwarz | Responses of Pacific herring[END_REF][START_REF] Mann | Herring do not detect ultrasound[END_REF] and cod [START_REF] Enger | An electrophysiological field study of hearing in fish[END_REF][START_REF] Chapman | A field study of the hearing in cod, Gadus morhua L[END_REF][START_REF] Offutt | Structures for the detection of acoustic stimuli in the Atlantic codfish, Gadus morhua[END_REF][START_REF] Buerkle | An audiogram, of the Atlantic cod, Gadus morhua L[END_REF][START_REF] Astrup | Detection of intense ultrasound by the cod Gadus morhua[END_REF][START_REF] Astrup | Discrimination between high and low repetition rates of ultrasonic pulses by the cod[END_REF], but not for pout and thicklip mullet. Based on the audiograms, the frequency spectrum (> 9.8 kHz), and the exposure levels in the tank (up to around 135 dB re 1 re 1 µPa), the pingers should not have been audible to sea bass and cod, and to Atlantic herring if its hearing resembles that of Pacific herring [START_REF] Mann | Herring do not detect ultrasound[END_REF]. However, only the cod did not respond to the pingers.

Suitability of the pingers for use in gillnet fisheries

The results of the present study cannot be extrapolated to the remaining approximately 155 North Sea fish species. The reactions of fish to pinger sounds were observed in quiet conditions in a tank. In the wild, the sound characteristics that caused the fish to react in the tank may be masked by background noise. Whether responses similar to those observed in the present study would be elicited in the fish species in the wild, and if so, whether such responses would influence the catch rate in fisheries, cannot be predicted based on the results of the present study. However, even if pingers do not affect the catch of the target fish species in the fisheries, pinger sounds should be selected that do not affect other fish (and other marine fauna) in the environment.

Both the frequency spectrum and SL played a role in the effect of the pingers on the fish species tested. A combination of a SL < 130 dB re 1 µPa @ 1 m and a high frequency spectrum (> 10 kHz, although more knowledge on the hearing sensitivity of fish species is needed to verify this figure) seems to reduce the chance of a pinger affecting the behaviour of fish. However, reducing the SL may make the pinger less effective at reducing porpoise bycatch, especially under high background noise levels. A compromise may be needed. There are other considerations for a choice of sound characteristics apart from the effect of pingers on porpoises and fish. For instance, signals above 70 kHz cannot be heard by pinnipeds, and thus cannot act as a "dinner bell" for these animals which can damage the catch and the gillnets.

Suggestions for further research

The main limitations of the present study are that only about 3 % of the fish species that occur in the North Sea were tested, and that if a pinger with new acoustic characteristics is developed, a completely new study would be needed to test its effect on fish. Therefore, it would be useful to conduct a fundamental study on the reaction of various fish species to a wide range of sounds. For instance, effects of pure tones, narrow and wide-band sweeps, noise bands in the 100 Hz -180 kHz frequency range, and sounds of biological relevance could be tested. To determine the effects of the low frequencies which were present in sweep signals, a trained (feeding) experiment with high frequency (HF) sounds with and without LF contribution could be useful. With this information, the impact of any sound could be predicted, and for fish species of high commercial, scientific or public interest, audiograms could be obtained in follow-up studies. Despite important steps being made towards understanding effects of sounds on fish, comparisons of actual catches in nets with and without pingers are still needed to measure the effect of pingers on fisheries.

pallasi, to some underwater sounds. Canadian Journal of Fisheries and Aquatic Sciences, 41, 1183-1192. Trippel, E.A., Strong, M.B., Terhune, J. M., & Conway, J.D. (1999). Mitigation of harbour porpoise (Phocoena phocoena) by-catch in the gillnet fishery in the lower Bay of Fundy. Canadian Journal of Fisheries and Aquatic Sciences, 56, 113-123. Wahlberg, M., & Westerberg, H. (2005). Hearing in fish and their reactions to sounds from offshore wind farms. Marine Ecology Progress Series, 288, 295-309. Wilson, B., & Dill, L.M. (2002). Pacific herring respond to simulated odontocete echolocation sounds. Canadian Journal of Fisheries and Aquatic Sciences, 59, 542-553. Zar, J.H. (1984). Biostatistical analysis. (2 nd edition). Prentice Hall, Englewood Cliffs, NY.

Table 2. Mean standard body length and weight of the five fish species which were subjected to sounds. The length and weight of the herring were estimated as this species could not be handled without causing injury to the fish. N = number of individuals, SD = standard deviation. * For a detailed description of the signals of the AQUAmark 200, see [START_REF] Rossi | Frequency modulation of the sounds produced by AQUAmark 200® deterrent devices[END_REF]. Legends to the figures: Fig. 1. Schematic view of the study area showing the grid on the bottom and walls, the orientation of the three cameras, and the location of the transducer or pinger.

Species

Fig. 2. Background noise limits in the pool between 20 Hz and 50 kHz. Each measurement was done during a 32-60 s period. Results are given as equivalent spectrum levels at 1/3octave centre frequencies (dB re 1 µPa/√Hz), and as 1/3-octave band levels (dB re 1 µPa). SPL signifies Sound Pressure Level.

Fig. 3 .

 3 Fig. 3. Differences in behavioural parameters, calculated as mean test value minus mean baseline value, for each session. Only behavioural parameters which differed significantly from zero are shown (see Table6). A. Sea bass decreased their speed in response to the AQUAmark100; B. Sea bass swam closer to the surface in response to the Fumunda; C. Thicklip mullet swam closer to the bottom in response to the AQUAmark 100; D. Thicklip mullet increased their swimming speed in response to the Airmar; E. Thicklip mullet swam closer to the bottom in response to the SaveWave white high impact; F. Herring increased their swimming speed in response to the Airmar.

Table 3 .

 3 Water temperature during the test periods for the five fish species. N = number of measurements, SD = standard deviation.

		N Standard body length (cm) Body weight (g)
			Mean	SD	Range Mean SD Range
	Sea bass 10	25	4	20-30	209 69 86-332
	Pout 12	21	1	18-23	117 27 84-172
	Thicklip	10	17	3	14-21	57 29 24-91
	mullet
	Herring 13	20	4	15-25	75	4 70-80
	Cod	9	31	2	27-33	315 54 217-377
	Fish species	Mean water	SD N Range
			Temperature (°C)
	Sea bass	7.8		2.2 17 4.1 -10.9
	Pout		6.5		2.5 83 4.0-12.0
	Thicklip	9.2		1.7 88 4.0-11.0
	mullet
	Herring	13.7	1.0 88 11.0-16.0
	Cod		15.8	1.1 88 14.0-18.0

Table 4 .

 4 Description of the two 'known effect' reference sounds and the signals of seven commercially available pingers that were tested on North Sea fish species. The Source Levels (SLs) of the 'known effect' reference sounds and pinger signals were measured with the hydrophone 1 m from the transducer or pinger, the Sound Pressure Levels (SPLs) with the hydrophone 6 m from the transducer or pinger. The calculations of SL pulse and SL cycle are described in section 2.4. For randomized signals the SL cycle is calculated over the shortest (Min), average (Avg), and longest (Max) signal interval.

	Sound source and manufacturer	Signal type	Signal duration (ms)	Signal interval (s)	SL pulse (dB re 1 1 m) µPa @	SL cycle (dB re 1 m) 1 µPa@	SPL @ 6 m 1 µPa) (dB re	Frequency spectrum and peak levels at 1 m (dB re 1 µPa)
	DRS-8 transmitter	600 Hz tonal
	by Ocean Engineering	'known effect' reference	300	4	172	161	177
	Enterprise	sound
	DRS-8 transmitter	3 kHz tonal
	by Ocean Engineering	'known effect' reference	300	4	202	-	-
	Enterprise	sound
	Fumunda							Harmonic energy up to 73
	FMDP 2000							kHz, 3 rd and 5 th harmonic
	by Fumunda Marine	Tonal signal 9.6 kHz	297	3.2	141	131	138	-10 dB. 0.02-0.1 kHz -60 dB.
	Products, USA
	Airmar gillnet pinger by AIRMAR Technology Corporation, USA	Tonal signal 9.8 kHz	309	3.5	134	124	125	Harmonic energy up to 50 kHz -30 dB. 0.02-0.1 kHz -30 to -60 dB.
								Tonal levels +7 dB with
								peaks at 64.4 kHz (136
	AQUAmark 100 by Aquatec Subsea Ltd, UK	Tonal and sweep signals	Random Avg 304 Min 213 Max 358	Random Avg. 12.2 Min. 4.2 Max 22.6	148 (SD 3.7) (n=16)	Avg 133 Min 142 Max 130	143 (SD 1.6) (n=16)	dB) and 128 kHz (100 dB). Sweep signals peaked between 44-54 kHz & 60-80 kHz, LF
								peaks at 0.75 (-34 dB) &
								1.6 kHz (-50 dB).
								Tonal peaks at 21 & 42
	AQUA mark 200* by Aquatec Subsea Ltd, UK	Tonal and sweep signals	Random Avg 282 Min 272 Max 293	Random Avg 12.1 Min 3.7 Max 21.1	134 (SD 1.26) (n=16)	Avg 118 Min 123 Max 120	130 (SD 1.5) (n=16)	kHz (126-130 dB) and 63-104 kHz (-5 to-15 dB). Sweep signals peaked between 10-14 kHz & 48-53 kHz. LF peaks at 0.7
								kHz (-15 dB).
								Sweep 5.3 -110 kHz.
	SaveWave endurance by SaveWave BV, The Netherlands	Sweep signal	Random Avg. 295 Min. 196 Max. 393	Random Avg 14.5 Min 8.2 Max 21.1	134 (SD 0.41) (n=14)	Avg 117 Min 117 Max 117	132 (SD0.7) (n=12)	Peaks between 7-95 kHz 112-116 dB. LF contribution 0.5-3 kHz -40 dB. Pulse duration proportional to time
								intervals.
	SaveWave white high impact by SaveWave BV, The Netherlands	Sweep signal	Random Avg. 529 Min. 197 Max. 852	Random Avg. 11.39 Min. 2.65 Max. 18.24	140 (SD 0.58) (n=17)	Avg 126 Min 131 Max 125	141 (SD0.43) (n=17)	Sweep 5-95 kHz 115 dB. Peaks between 7.5-54 kHz +12 dB. LF contribution 0.75-2.4 kHz -20/-35 dB.
	SaveWave black high impact by SaveWave BV, The Netherlands	Sweep signal	Random Avg. 318 Min. 229 Max. 427	Random Avg 14.6 Min 8.8 Max 23.0	143 (SD 0.67) (n=13)	Avg 127 Min 127 Max 126	143 (SD1.0) (n=12)	Sweep 33 -97 kHz 108 dB, Peaks between 50-95 kHz (+10 dB). LF contribution 6 to 9 kHz -40 dB.

Table 5 .

 5 The general behaviour of the five fish species used in the present study.

	Fish	Swimming	Swimming speed	Description of school and	Distance to
	species	speed during	range during	swimming behaviour	bottom (m)
		baseline	baseline (m/s)
		qualified
	Sea bass Relatively fast 0.11 -0.34	Compact school. In large	0.1 -1.3
				ovals
	Pout	Very slow,	0.00 -0.23	Loose group. From one corner	0.0 -0.4
		sometimes		to another in no particular
		stationary		order, but usually following
				the pool walls
	Thicklip	Relatively fast 0.03 -0.29	In a school. In ovals	0.1 -1.9
	mullet
	Herring Fast	0.38 -0.74	In a school. In large ovals	0.1 -0.3
	Cod	Slow	0.16 -0.27	In a school. Through the tank	0.1 -0.9
				in seemingly random
				directions

Table 6 .

 6 Results of statistical analysis of responses of fish species to pingers. Results are from paired t-tests or Wilcoxon matched pairs tests (indicated by W ), depending on the distribution of the differences of the variable values in baseline and test periods (calculated as test minus baseline, and expressed by the D in front of the behavioural parameter). Sample size was 11 sessions in all cases except * n=6 and † n=10. 'ns' = no significant difference between baseline and test ( =0.05), 'increase' = value is significantly higher in test than in baseline, 'decrease' = value is significantly lower in test than in baseline; exact p-values are shown in parentheses. The table shows the response of each species of fish to 'known effect' sounds which elicited a clear response. Cod did not respond at all to any sound produced. Variables which did not change in response to the 'known effect' audible sounds are not shown in this table. Endu = endurance, w.h.i. = white high impact, b.h.i. = black high impact.

	Pinger

Acknowledgements

We thank Rob Triesscheijn for all his help, Petra van der Marel, Sonja de Wilde, Natascha Lor and Marius van Vliet for their help in data acquisition and animal husbandry. We thank Gerard Visser, Michaël Laterveer, and Peter van Putten (all of the Oceanium department of Blijdorp Zoo, Rotterdam), for lending us the herring and for transporting the herring to the study site. We thank Gijs Rutjes (Coppens International) for providing some of the sea bass. We thank Amy Scholik (GMI, USA) for all her help and advice, and Jacob Tougaard (National Environmental Research Institute, Denmark), David Mann (University of South Florida, USA), Ben Wilson (Marine Mammal Research Unit, Fisheries Centre, Canada), and Frank Reier Knudsen (Simrad AS, Norway) for their constructive comments on the manuscript. The following representatives of the companies that provided the pingers for this project also gave valuable constructive comments on the manuscript: Andy Smerdon and Richard Love (Aquatec Sub Sea Ltd, UK), Rick van Lent (SaveWave B.V., The Netherlands), Steve Christensen (Airmar Technology Corporation), and Stan Pleskunas (Fumunda Marine Products). Facilities at the research station were made available thanks to Dick Vethaak (RIKZ), Roeland Allewijn (RIKZ), and Wanda Zevenboom (Netherlands North Sea Directorate). This project complied with the Dutch standards for animal experiments. The project was funded by the Netherlands Ministry for Agriculture, Nature, and Food Quality (DWK-program 418: North Sea and Coast), and supervised by IMARES-Texel, The Netherlands (Han Lindeboom).

Tables:

Table 1. Review of studies on the effects of pingers on fish catches and behaviour of captive marine fish.

Pinger make and model

Pinger spectrum

Pinger SL (dB re 1 µPa @ 1 m)