Markus G Weinbauer

Marie-Emmanuelle Kerros

Chiaki Motegi

Inés C Wilhartitz

Fereidoun Rassoulzadegan

Jean-Pascal Torréton

Xavier Mari

Bacterial community composition and potential controlling mechanisms along a trophic gradient in a barrier reef system

INTRODUCTION

Genetic fingerprinting (sometimes including sequencing) and cloning have been used to assess changes in bacterial community composition and potential controlling mechanisms. Genetic fingerprints have been used to characterize gradients such as depth [START_REF] Lee | Spatial and temporal variation of natural bacterioplankton assemblages studied by total genomic DNA cross-hybridization[END_REF][START_REF] Giovannoni | 16S rRNA genes reveal stratified open ocean bacterioplankton populations related to the green non-sulfur bacteria[END_REF][START_REF] Acinas | Diversity of free-living and attached bacteria in offshore Western Mediterranean waters as depicted by analysis of genes encoding 16S rRNA[END_REF], salinity (Bouvier & del Giorgio 2002[START_REF] Crump | Microbial biogeography along an estuarine salinity gradient: combined influences of bacterial growth and residence time[END_REF]), or productivity [START_REF] Reinthaler | Relationship between bacterioplankton richness, respiration, and production in the Southern North Sea[END_REF], Winter et al. 2005). Also, the dynamics of bacterioplankton diversity during phytoplankton blooms have been studied [START_REF] Arrieta | Changes in bacterial β-glucosidase diversity during a coastal phytoplankton bloom[END_REF][START_REF] Arrieta | Response of bacterioplankton to iron addition in the Southern Ocean[END_REF]) and the results used to argue that there is seasonality in oceanic bacterio-ABSTRACT: Bacterial abundance and community composition were investigated along trophic gradients in the barrier reef lagoon of Noumea, New Caledonia. Bacterial abundance and the percentage of high nucleic acid (%HNA) bacteria (a potential indicator for bacterial production) increased from offshore waters towards the head of the bays. 16S rRNA gene PCR and denaturing gradient gel electrophoresis (DGGE) were used as genetic fingerprints for assessing differences in bacterial community composition. Sequences of DGGE bands were assigned to (1) the genera Rugeria and Roseobacter (Rhodobacteriaceae), (2) the SAR11 cluster, (3) other Alphaproteobacteria, and (4) the genus Alteromonas. Removal of the operationally defined attached bacteria by prefiltration did not affect community profiles in offshore waters but had a strong influence in the bays, probably due to the much higher particle load and thus, attached bacteria in the bays. For the free-living community, the number of bands decreased linearly with increasing water residence time, chlorophyll a concentration, and viral abundance. Specific bands were found for offshore waters and the 2 investigated semi-enclosed bays, whereas the lagoon showed no specific bands. A similarity analysis showed specific clusters for offshore water, the lagoon, and the bays. A principle component analysis together with cluster and correlation analysis indicated that water residence time, viruses, and a complex topdown cascading effect of ciliate grazers on flagellates influenced community composition. Also, data from fingerprints of the total and free-living communities suggest that the free-living and the attached community are controlled by different mechanisms.

KEY WORDS: Diversity

• Virus • Protist • Flagellate • Ciliate • Roseobacter • SAR11
Resale or republication not permitted without written consent of the publisher OPEN PEN ACCESS CCESS plankton composition [START_REF] Pinhassi | Seasonal successions in marine bacterioplankton[END_REF][START_REF] Fuhrman | Annually reoccurring bacterial communities are predictable from ocean conditions[END_REF]). Although the number of studies on bacterial diversity has increased in recent years, many environments remain poorly investigated, including the water column systems of tropical coral reefs [START_REF] Dinsdale | Microbial ecology of four coral atolls in the Northern Line Islands[END_REF].

A variety of mechanisms influence bacterial community composition, including UV radiation [START_REF] Winter | Impact of UV radiation on bacterioplankton community composition[END_REF], turbulence [START_REF] Malits | Effect of turbulence and viruses on aggregate formation and prokaryotic cell size, production and diversity[END_REF], nutrient and dissolved organic matter composition [START_REF] Arrieta | Changes in bacterial β-glucosidase diversity during a coastal phytoplankton bloom[END_REF], grazing [START_REF] Pernthaler | Predation on prokaryotes in the water column and its ecological implications[END_REF][START_REF] Pernthaler | Fate of heterotrophic microbes in pelagic habitats: focus on populations[END_REF], and viral infection [START_REF] Hewson | Bacterial diversity in shallow oligotrophic marine benthos and overlying waters: effects of virus infection, containment, and nutrient enrichment[END_REF][START_REF] Winter | Impact of virioplankton on archaeal and bacterial community richness in seawater batch cultures[END_REF]. Also, general ecological patterns such as the species-area relationship (Horner-Devine et al. 2004b), the increase of diversity with system ('island') size [START_REF] Bell | Larger islands house more bacterial taxa[END_REF][START_REF] Reche | Does ecosystem size determine aquatic bacterial richness?[END_REF], or the existence of latitudinal gradients [START_REF] Fuhrman | A latitudinal diversity gradient in planktonic marine bacteria[END_REF] appear to apply to bacteria. While one can expect that such influences and patterns are also operational in coral reef systems, no studies are available. In coral reef systems, the release of nutrients and mucus by corals stimulates the production of bacteria in nearby waters [START_REF] Herndl | Microheterotrophic utilization of mucus released by the Mediterranean coral Cladocora cespitosa[END_REF][START_REF] Schiller | Evidence of enhanced microbial activity in the interstitial space of branched corals: possible implications for coral reef metabolism[END_REF]) and fuels the food web of lagoon systems [START_REF] Wild | Coral mucus functions as an energy carrier and particle trap in the reef ecosystem[END_REF]). This likely explains observations that the microbial loop is predominant and the community is often heterotrophic in the water column part of reef systems [START_REF] Ferrier-Pagès | Biomass, production and grazing rates of pico-and nanoplankton in coral reef waters (Miyako Island, Japan)[END_REF]. Typically, lagoon bacteria are more active than bacteria in the open ocean, and usually only a moderate fraction of bacteria (ca. 10%) is attached to particles in the open ocean and reef lagoons [START_REF] Rath | Ectoenzymatic activity and bacterial dynamics along a trophic gradient in the Caribbean Sea[END_REF][START_REF] Torréton | Temporal and spatial stability of bacterioplankton biomass and productivity in an atoll lagoon[END_REF][START_REF] Torréton | Biomass, production and heterotrophic activity of bacterioplankton in the Great Astrolabe Reef lagoon (Fiji)[END_REF][START_REF] Torréton | Relationship between bacterioplankton and phytoplankton biomass, production and turnover rate in Tuamotu atoll lagoons[END_REF]. However, attached bacteria are often more active than their free-living counterparts [START_REF] Simon | Microbial ecology of organic aggregates in aquatic ecosystems[END_REF][START_REF] Grossart | Comparison of cell-specific activity between free-living and attached bacteria using isolates and natural assemblages[END_REF]. It is also well documented that the diversity of prokaryotes attached to organic aggregates can be very different from free-living prokaryotes [START_REF] Delong | Phylogenetic diversity of aggregate-attached vs. free-living marine bacterial assemblages[END_REF][START_REF] Acinas | Diversity of free-living and attached bacteria in offshore Western Mediterranean waters as depicted by analysis of genes encoding 16S rRNA[END_REF], although this has not been investigated yet in coral reef systems.

Water residence time is an important concept to understand the hydrodynamically restricted aquatic systems and its control of ecological processes in the plankton. Water residence time is thought to be the most important physical control factor of ecological processes in estuaries [START_REF] Jouon | Calculations of hydrodynamic time parameters in a semi-opened coastal zone using a 3D hydrodynamic model[END_REF]. In atoll and lagoon systems, it has been shown that chlorophyll a (chl a) concentrations, primary production, and bacterial production increase with water residence time [START_REF] Delesalle | Residence time of water and phytoplankton biomass in coral reef lagoons[END_REF][START_REF] Charpy | Particulate organic matter in sixteen Tuamotu atoll lagoons (French Polynesia)[END_REF], Torréton et al. 2007). Water residence time also influences the dynamics of dissolved organic carbon and transparent exopolymeric particles (TEP; Mari et al. 2007b). Water residence time also determines whether a specific bacterial community can develop; thus, for the develop-ment of a specific bacterial community, the water residence time must exceed that of bacterial growth. Indeed, a study in an estuary showed that specific communities developed with high bacterial production and long water residence time [START_REF] Crump | Microbial biogeography along an estuarine salinity gradient: combined influences of bacterial growth and residence time[END_REF].

A recent study of organic matter reactivity along eutrophic gradients in the lagoon of New Caledonia revealed that the transfer efficiency of organic matter from the dissolved to the particulate phase via aggregation processes was reduced when the residence time of the water increased (Mari et al. 2007b). Such a reduction in organic matter reactivity may, in addition to water residence time itself, influence the distribution and fate of attached and free-living prokaryotes. The lagoon of Noumea represents a steep, 20 km long gradient from the oligotrophic open ocean to mesotrophic semi-enclosed bays with a negligible freshwater input from terrestrial runoff. Here we present data on the community composition of bacterioplankton in the water column of various lagoon habitats by using genetic fingerprints and relate these diversity patterns to potential controlling factors such as water residence time and mortality factors.

MATERIALS AND METHODS

Study site and sampling. The SW lagoon of New Caledonia is an enclosed, relatively shallow site (average depth: 20 m), surrounded by oligotrophic oceanic water. In contrast to the oligotrophy observed near the coral barrier, the near-shore environment is subject to terrestrial and, especially in the bays around the city of Noumea, to both industrial and urban inputs that increase the general productivity in these areas. Eutrophication in Grande Rade Bay is mainly of industrial origin, due to the close proximity of a large nickel smelter, while in Sainte Marie Bay, eutrophication is mostly of urban origin, i.e. due to wastewater outfalls from the Sainte Marie area. For more details see Mari et al. (2007b).

Seawater samples were collected during November and December 2004 at 10 stations distributed along 2 transects in the SW lagoon of New Caledonia, going from 2 semi-enclosed bays in the city of Noumea (~130 000 inhabitants) to a station outside the reef barrier (Fig. 1). Both transects were sampled twice, on 22 and 24 November 2004 (from Grande Rade Bay to the outer edge of the coral reef) and 29 November and 1 December 2004 (from Sainte-Marie Bay to the outer edge of the coral reef). Samples were obtained from 5 m depth using a Teflon pump. CTD casts were used on each sampling occasion to determine the vertical distribution of physical parameters. All stations were sampled within 1 h; water samples were stored in acid-cleaned polycarbonate bottles and brought back to the laboratory within 1 to 2 h after sampling.

Residence time of the water masses. The parameter used to depict the 'residence time' of the water mass is the Local e-Flushing Time (LeFT; in days). The LeFT is defined as the time required for a tracer mass contained within the control volume (station) to be reduced by a factor 1/e by waters coming from outside the lagoon and, thus, it describes the replacement efficiency of water masses in the study area [START_REF] Jouon | Calculations of hydrodynamic time parameters in a semi-opened coastal zone using a 3D hydrodynamic model[END_REF]): the shorter the LeFT, the faster the water masses at the location will definitely be replaced and, thus, renewed. The annual average LeFT at the different stations was calculated from a hydrodynamic model taking into account topographic constraints, average wind condition, and tidal cycle [START_REF] Jouon | Calculations of hydrodynamic time parameters in a semi-opened coastal zone using a 3D hydrodynamic model[END_REF]. During the sampling period, wind conditions were similar to those used as input parameters in the hydrodynamic model (i.e. well established trade winds of about 8 to 10 m s -1 ). The LeFT was 0 at the offshore station (input parameter) and it was calculated for each station to range from 0.4 to 5.6 d in the lagoon stations, 12 to 17 d in Sainte Marie Bay, and 31 to 47 d in Grande Rade Bay (Mari et al. 2007b; Table 1).

Enumeration of microbes. Water samples were preserved with glutaraldehyde (0.5% final concentration) for 30 min at 4°C, then flash frozen in liquid nitrogen and stored at -80°C until analysis. Viruses and bacteria were stained with SYBRGreen I and counted by flow cytometry using the protocol of [START_REF] Gasol | Using flow cytometry for counting natural planktonic bacteria and understanding the structure of planktonic bacterial communities[END_REF] for bacteria and [START_REF] Brussaard | Optimization of procedures for counting viruses by flow cytometry[END_REF] for viruses. Synechococcus, Prochlorococcus, and autotrophic picoeukaryotes were counted as described by [START_REF] Jacquet | Impact des apports en nutriments sur le réseau trophique planctonique dans du lagon sud-ouest de Nouvelle-Calédonie[END_REF]. Samples for viruses were diluted 100-fold in TE (10 mM Tris, 1 mM EDTA, pH 8.0) buffer. Based on fluorescence intensity (and side scatter) 2 bacterial populations were distinguished: low (LNA) and high nucleic acid (HNA) bacteria.

Flagellate and ciliates were stained with DAPI, collected onto 0.8 µm pore-size Nuclepore filters, and counted using an epifluorescence microscope. It should be noted that ciliate counts obtained by this method can be underestimates. Heterotrophic (HNF) and autotrophic nanoflagellates (ANF) were distinguished based on autofluorescence. Total flagellate (TNF) abundance is the sum of HNF and ANF. Chl a was determined fluorometrically from duplicate 200 ml subsamples filtered onto 25 mm Whatman GF/F filters, and data were obtained from Mari et al. (2007b). DNA extraction. Cells from 0.5 to 1 l samples (total community) were recovered on a 0.2 µm pore-size polycarbonate filter (diameter 47 mm; Whatman). A replicate sample (except for the Sainte-Marie Bay transects) was prefiltered through 1 µm polycarbonate filter (diameter 47 mm; Whatman) to remove mainly attached bacteria, and the filtrate containing mainly the free-living community was collected. Nucleic acids were extracted from the filters and purified as described elsewhere [START_REF] Winter | Impact of virioplankton on archaeal and bacterial community richness in seawater batch cultures[END_REF]. Briefly, after 4 freeze-thaw cycles (-196°C to + 37°C), an enzyme treatment was performed with lysozyme (1.25 mg ml -1 final concentration; Fluka Bio-Chemika) for 30 min at 37°C followed by a digestion with Proteinase K (100 µg ml -1 final concentration; Fluka Bio-Chemika) and 1% sodium dodecyl sulfate for 2 h at 55°C. In contrast to the phenol-chloroform extraction step from the original protocol, nucleic acids were extracted with 4.5 M NaCl 2 , followed by 100% isopropanol precipitation. This modified procedure avoids the use of a toxic chemical and yields genetic fingerprints identical to those obtained by the original method [START_REF] Malits | Effect of turbulence and viruses on aggregate formation and prokaryotic cell size, production and diversity[END_REF]. The pellets were re-suspended in 60 µl of 0.5× TE buffer (10 mM Tris, 1 mM EDTA [HCl, pH 8.0]).

PCR. Conditions of the touchdown PCR and chemicals were as described by [START_REF] Schäfer | Denaturing gradient gel electrophoresis in marine microbial ecology[END_REF]. One to 4 µl of cleaned nucleic acid extract were used as template in a 50 µl PCR reaction (1.5 mM MgCl 2 , 0.25 µM of each primer, and 2.5U Taq polymerase; Sigma) together with a positive and a negative control. A fragment of the 16S rRNA gene was amplified using the primer pairs 341F-GC/ 907R and 344F-GC/ 915R for Bacteria and Archaea, respectively [START_REF] Schäfer | Denaturing gradient gel electrophoresis in marine microbial ecology[END_REF]. The bacterial primers had the modifications suggested to also detect Gammaproteobacteria [START_REF] Sanchez | Comparison of different denaturing gradient gel electrophoresis primer sets for the study of marine bacterioplankton communities[END_REF]. Archaeal PCR products could either not be obtained or were often too weak to perform denaturing gradient gel electrophoresis (DGGE). Therefore, we conclude that Archaea were not abundant at the study site and we use the term 'bacteria' in the following. DGGE. DGGE procedures followed those described by [START_REF] Schäfer | Denaturing gradient gel electrophoresis in marine microbial ecology[END_REF]. PCR products (500 ng) were separated into bands by electrophoresis for 18 h at 100 V on acrylamide/bis-acrylamide (6%) gels prepared using a gradient of 30 to 70% (urea and formamide) using an INGENYphorU DNA Mutation Detection System (Ingeny International). A standard made from a 200 l bacterioplankton extraction was loaded to allow for comparison of bands within and between gels. DGGE gels were photographed with a gel documentation system (GelDoc EQ; Bio-Rad) after 15 min of staining with a 10× SYBR Gold solution (Molecular Probes). Analysis of band patterns between lanes was performed with the Quantity One Software (Bio-Rad) using a variety of exposure times.

Selected samples covering all detected bands were rerun on a DGGE gel, and bands were excised. The DNA was eluted overnight in autoclaved Milli Q water at 4°C, checked for purity by re-running it on a gel, and sequenced (MWG-Biotech). Sequences were edited using the freeware program 4Peaks 1.6 (www. mekentosj.com). Up to approximately 500 bp of the 16S rRNA gene were used in a BLAST search.

Statistical analyses. Correlation and regression analyses were performed using a probability (p) < 0.05 as significant. Data were log or arcsine transformed (for percentages) to meet statistical requirements. Bacterial fingerprints were analyzed using a Simple Match similarity index. The difference in the number of bands was compared between offshore, lagoon, and bay waters using an analysis of variance (ANOVA). Data comparison between the 2 bays was done by Student's t-test.

Potential relationships among variables were tested by linear pairwise correlations (Spearman correlation analysis). Key parameters were used to perform principal component analysis (PCA). Data were log(+1) transformed to satisfy the requirements of normality and homogeneity of variance necessary for parametric statistics. Only factors with an eigenvalue >1 were retained. All statistical analyses were performed with the JMP program.

RESULTS

Characterization of sampling sites

A physical and chemical characterization of the sampling stations at the sampling dates can be found in Mari et al. (2007b). Briefly, salinity and temperature varied only slightly between sampling sites and dates, and no stratification of the water column was observed within the barrier reef. Nutrient concentrations were highest at the head of the bays and gradually decreased towards the mouth of the bays, the distant parts of the lagoon, and the open ocean. All sampling stations during the sampling period were characterized by inorganic nitrogen limitation as indicated by N:P ratios < 5 (Mari et al. 2007b).

Microbial abundance

Bacterial abundance ranged from 0.6 × 10 6 to 2.0 × 10 6 ml -1 , and in all 4 transects, bacterial abundance was lowest at the open ocean station and highest at the head of the bays (Table 1). Bacterial abundance was generally higher in Sainte Marie Bay than in Grande Rade Bay. HNA ranged from 51 to 82% and increased from 54% in the open ocean to 80% at the head of Grande Rade Bay.

The abundance of Synechococcus ranged from 0.8 to 19.8 × 10 4 ml -1 . The abundance was highest in Grande Rade Bay, similar in the lagoon and Sainte Marie Bay, and much lower offshore (Table 2). Prochlorococcus was not detectable in most bay stations and showed low abundances in the lagoon and very high abundances offshore (on average 1.5 × 10 5 ml -1 ). Thus, Prochlorococcus dominated the cyanobacterial community offshore, whereas Synechococcus dominated in the lagoon and bays. Abundances of Cyanobacteria (i.e. Synechococcus plus Prochlorococcus) did not change much between study sites. Picoeukaryotes ranged from 1.6 to 12.4 × 10 3 ml -1 and generally showed higher abundances in the bays than at other stations.

HNF abundance ranged from 0.6 to 13.4 × 10 3 ml -1 . HNF abundance was higher at the head of the bays than in the open ocean, although the lowest values were found at a station in the middle of the lagoon and in the middle and mouth of Sainte Marie Bay (Table 3).

With the exception of a single sampling, ANF abundance was lower than HNF abundance. ANF abundance and its relative contribution to total abundance were lowest in the open ocean and highest in the bays. Ciliate abundance ranged from 0.1 to 19 cells ml -1 , and abundance was on average lowest in the open ocean. The distribution of viral abundance in the lagoon of Noumea has been described elsewhere (Mari et al. 2007a). Briefly, viral abundance ranged from 0.8 to 3.2 × 10 7 ml -1 and was highest at the head of the bays and lowest in the open ocean.

Bacterial community composition

Fourteen different bands were successfully sequenced (Table 4). The identity of bands could be confirmed by identical sequences. Five major groups of phylotypes were detected: (1) sequences related to Rhodobacteri-

Trophic group

Stn HNF ANF TNF Ciliates Viruses (10 3 ml -1 ) (10 2 ml -1 ) (10 3 ml -1 ) (ml -1 ) (10 7 ml -1 ) Duplicate filters yielded identical community profiles (data not shown). Bacterial community composition changed strongly along trophic gradients. Twenty different bands were detected, and 13 bands were present at all stations. The number of detected bands ranged from 14 to 16 in offshore waters, from 11 to 13 in the lagoon and the mouth of the bays, and from 13 to 15 in Grande Rade Bay, and it was 16 in Sainte Marie Bay (middle and head of bays). Thus, the highest number of bands of total bacterial communities was found in the upper part of the bays and at the open ocean station (Fig. 2). An ANOVA and post hoc tests showed that the number of bands of the total community in the lagoon was significantly different from bay and offshore stations. The number of bands of the free-living community showed a different trend and decreased from the open ocean towards the head of the bays. An ANOVA showed that offshore, lagoon, and bay waters were significantly different with respect to the number of bands of the free-living community.

Using band identity to describe environments, 3 specific bands were found for offshore waters, 1 band was specific for the middle and head station of Sainte Marie Bay, and 1 band was specific for Grande Rade Bay. An additional band occurred only in the 2 bays, whereas no specific band was detected for the lagoon stations.

A similarity tree of the DGGE profiles (presence versus absence of bands) showed that the free-living community in Grande Rade was different from all others (Fig. 3). The offshore community was different from all other remaining lagoon and bay communities. Within the lagoon and bay communities, 3 clusters were found: 1 consisting of the head and center of Sainte Marie Bay, 1 of the mouth of Sainte Marie Bay and some lagoon stations (total community), and 1 of the

Relationship between parameters

Regression and correlation analyses were performed with average values per station, since LeFT values were only available as average values per station, and not all stations were sampled at the same frequency (Table 1). Bacterial abundance increased strongly with chl a concentration and ciliate and viral abundance, but not with LeFT, whereas %HNA increased significantly with LeFT, chl a concentration, and viral abundance but not with ciliate abundance parameters (Table 5). Other significant relationships were those between LeFT and chl a, between viruses and chl a (although r was lower than for the relationship between viral and bacterial abundance), and between HNF or TNF abundance and ciliate abundance. The abundance of Synechococcus was strongly related to viruses, whereas the abundance of picoeukaryotes was strongly related to %HNA, HNF, and TNF.

Using correlation analysis, the number of bands of total communities was only related significantly to HNF, TNF, and eukaryote abundance (Table 5). However, we also found more complex relationships using regression analysis. For example, the number of bands was related to chl a concentration in a U-shape (Fig. 4). No relationship was detected between the number of bands of total communities and LeFT. The number of bands of the free-living community decreased linearly with LeFT, chl a concentration (Fig. 4), Synechococcus, %HNA, and bacterial, viral, and ciliate abundance. The distance matrix was calculated using a simple match similarity index

Integrated view of data: PCA

Key parameters, namely richness, LeFT, bacteria, viral, HNF and ciliate abundance, and chl a concentrations were selected for PCA. Three significant components with an eigenvalue >1 were extracted, explaining 86.2% of the total variation (Table 6). The component matrix revealed 2 fundamental factors influencing the environment. Most of the variations in the barrier reef system were characterized by the first component (PCA-C1), where LeFT was strongly correlated with bacterial and viral abundance and chl a and was responsible for almost 50% of the variation in the system. The other 2 components, together explaining about 36% of the variation, revealed a relation between grazers and richness. The second component (PCA-C2) showed a positive correlation between the number of bands for the total community and HNF abundance, and the third component (PCA-C3) showed a negative correlation between the number of bands for the total community and ciliate abundance. [START_REF] Torréton | Biomass, production and heterotrophic activity of bacterioplankton in the Great Astrolabe Reef lagoon (Fiji)[END_REF]. This difference was only moderate [START_REF] Torréton | Biomass, production and heterotrophic activity of bacterioplankton in the Great Astrolabe Reef lagoon (Fiji)[END_REF] and is supported by our study. The relationship between bacterial abundance and chl a concentrations (Table 5) suggests that bacterial production was linked to primary production as has been shown before for the barrier reef system of New Caledonia [START_REF] Torréton | Phytoplankton-bacterioplankton coupling in the coastal sub-tropical South Pacific[END_REF]) and many other pelagic environments (e.g. [START_REF] Cole | Bacterial production in fresh and saltwater ecosystems: a cross-system overview[END_REF]. Such a tight link is thought to be mainly the consequence of dissolved organic matter release from healthy phytoplankton cells [START_REF] Baines | The production of dissolved organic matter by phytoplankton and its importance to bacteria: patterns across marine and freshwater systems[END_REF], which fuels bacterial production. Other links could be detritus formation and subsequent use by bacteria. Indeed, the concentration of transparent organic particles (TEP) was also well correlated with chl a (Mari et al. 2007b) and bacterial abundance (data not shown). It is known that %HNA often increases with bacterial production and that the HNA populations are often more active (e.g. [START_REF] Servais | Coupling bacterial activity measurements with cell sorting by flow cytometry[END_REF]). We did not measure bacterial production in the present study, although previous work has shown that bacterial production increases along the trophic gradient in the lagoon in all seasons [START_REF] Torréton | Correspondence between the distribution of hydrodynamic time parameters and the distribution of biological and chemical variables in a semienclosed coral reef lagoon[END_REF][START_REF] Conan | Effect of solar ultraviolet radiation on bacterio-and phytoplankton activity in a large coral reef lagoon (southwest New Caledonia)[END_REF], Rochelle-Newall et al. 2008). Thus, the strong correlation between %HNA (and total abundance) and chl a detected in the lagoon of Noumea and the fact that these parameters strongly increase along trophic gradients is a good indication of a link between bacterial and primary production as shown previously along the trophic gradients investigated [START_REF] Torréton | Phytoplankton-bacterioplankton coupling in the coastal sub-tropical South Pacific[END_REF]). In the bays, the long water residence time and the positive buoyancy of TEP result in an efficient cycling loop of organic matter (Mari et al. 2007b), and this could be an additional mechanism explaining the high %HNA.

DISCUSSION

Potential control mechanisms of bacterial abundance

Our data support a previous report [START_REF] Torréton | Correspondence between the distribution of hydrodynamic time parameters and the distribution of biological and chemical variables in a semienclosed coral reef lagoon[END_REF] suggesting that water residence time has an influence on bacterioplankton biomass. Recalculating 2 data sets from a total of 6 cruises from the same stations as in the present study [START_REF] Jacquet | Impact des apports en nutriments sur le réseau trophique planctonique dans du lagon sud-ouest de Nouvelle-Calédonie[END_REF], Torréton et al. 2007), a negative relationship was found between LeFT and bacterial turnover time (data were used as logtransformed averages per station from 3 cruises; Torréton data set: r = -0.70, p < 0.01, n = 9; Jacquet data set: r = -0.74, p < 0.005, n = 10). In the bays, water residence time was much higher than bacterial turnover time (Fig. 5). At Stn M05 (lagoon station closest to coast), LeFT and turnover times were similar, whereas for the other lagoon stations, bacterial turnover times were much lower than LeFT. Water residence time is a crucial ecological parameter in semi-confined environments, but it has not often been related to bacterial abundance and production or bacterial subpopulations [START_REF] Crump | Microbial biogeography along an estuarine salinity gradient: combined influences of bacterial growth and residence time[END_REF]. For example, it has been argued that specific communities can develop when the water residence time is higher than the bacterial turnover time [START_REF] Crump | Microbial biogeography along an estuarine salinity gradient: combined influences of bacterial growth and residence time[END_REF]). PCA-C1 also suggests a positive link between water residence time and bacterial and viral abundance and chl a concentrations (Table 6), thus supporting the argument outlined here.

The abundances of bacteria and HNF often show a lack of coupling across trophic gradients, especially in more eutrophic environments [START_REF] Gasol | Lack of coupling between heterotrophic nanoflagellates and bacteria: a general phenomenon across aquatic systems?[END_REF][START_REF] Gasol | A framework for the assessment of top-down vs bottom-up control of heterotrophic nanoflagellate abundance[END_REF]. This is probably due to top-down control of HNF by larger protists such as ciliates. These findings have been used by Gasol and co-workers to develop a model predicting that grazing by flagellates controls bacterial production in oligotrophic but not in eutrophic environments (see also [START_REF] Pernthaler | Predation on prokaryotes in the water column and its ecological implications[END_REF]. In support of these ideas, we did not find a significant relationship between bacterial and HNF or TNF abundance, whereas HNF and TNF abundance were highly correlated with ciliate abundance. This analysis could be influenced by mixotrophic flagellates, which are able to feed on bacteria and thus represent an additional mortality factor for bacteria. However, total or autotrophic flagellate abundance was also not coupled to bacterial abundance. The lack of correlation between HNF (or TNF) and bacterial abundance could also be due to flagellates grazing mainly on Cyanobacteria as shown for an atoll lagoon [START_REF] Sakka | Structure of the oligotrophic planktonic food web under low grazing of heterotrophic bacteria: Takapoto Atoll, French Polynesia[END_REF]. HNF (or TNF) abundance was not related significantly (Mari et al. 2007a). Bacterial turnover times were calculated from 2 data sets available from the study stations [START_REF] Jacquet | Impact des apports en nutriments sur le réseau trophique planctonique dans du lagon sud-ouest de Nouvelle-Calédonie[END_REF], Torréton et al. 2007). The Torréton data set was obtained from cruises in September 2000, June 2003, and October 2004, and the Jacquet data set was from April-May 2002, August 2002, and January 2003. Bacterial production was calculated from 3 H-thymidine incorporation rates (TdR) using a conversion factor of 2.85 × 10 8 cells mol -1 TdR obtained for the environment [START_REF] Jacquet | Impact des apports en nutriments sur le réseau trophique planctonique dans du lagon sud-ouest de Nouvelle-Calédonie[END_REF] to Synechococcus, Prochlorococcus, or Cyanobacteria but to autotrophic picoeukaryotes, suggesting that flagellates could have grazed on autotrophic picoeukaryotes. [START_REF] Sakka | Structure of the oligotrophic planktonic food web under low grazing of heterotrophic bacteria: Takapoto Atoll, French Polynesia[END_REF] also provided evidence that protistan grazing on bacteria is low in oligotrophic coral reef lagoons. Thus, the weak correlation between bacterial abundance and HNF abundance could not only be due to top-down control of HNF by ciliates but also due to selective feeding of HNF.

Using the approach of [START_REF] Gasol | Lack of coupling between heterotrophic nanoflagellates and bacteria: a general phenomenon across aquatic systems?[END_REF], [START_REF] Weinbauer | Significance of viruses versus heterotrophic nanoflagellates for controlling bacterial abundance in the Northern Adriatic Sea[END_REF] found the same lack of coupling between bacterial and HNF abundance in the Adriatic Sea. In addition, they reported a strong correlation between bacterial and viral abundance. Since viral infection also increased with bacterial abundance and trophic conditions, they speculated that viral control was stronger in eutrophic than in oligotrophic environments. Compilations of literature data also suggest that on average, the viral impact can be greater in eutrophic than in oligotrophic environments [START_REF] Weinbauer | Ecology of prokaryotic viruses[END_REF][START_REF] Parada | Viral burst size of heterotrophic prokaryotes in aquatic systems[END_REF]. The reason for this could be the increased encounter rates with hosts and the lack of top-down control of viral abundance. HNF can ingest and digest viruses; however, since the removal rates are low [START_REF] González | Grazing by marine nanoflagellates on viruses and viral-sized particles: ingestion and digestion[END_REF], grazing is likely not an important mechanism controlling viral abundance. Viruses could also originate from sources other than heterotrophic bacteria, such as Cyanobacteria, which can be abundant at the study site; in addition, Synechococcus abundance was significantly related to viral abundance. However, the abundance of Synechococcus (and Prochlorococcus or Cyanobacteria) was typically ca. 1 order of magnitude lower than the abundance of heterotrophic bacteria. Moreover, viral lysis rates seem to be lower for Synechococcus and Prochlorococcus than for heterotrophic bacteria (e.g. [START_REF] Garza | The effect of cyanophages on the mortality of Synechococcus spp. and selection for UV resistant viral communities[END_REF][START_REF] Baudoux | Viruses as mortality agents of picophytoplankton in the deep chlorophyll maximum layer during IRONAGES III[END_REF]). Thus, it is likely that the majority of viruses originated from the lysis of heterotrophic bacteria. In the bays, up to 30% of total viral abundance was attached to organic particles at the study site (Mari et al. 2007a). If this attachment is detrimental to viral infectivity [START_REF] Simon | Microbial ecology of organic aggregates in aquatic ecosystems[END_REF], Weinbauer et al. 2009), attachment could be an important mechanism for viral decay [START_REF] Suttle | Mechanisms and rates of decay of marine viruses in seawater[END_REF]). However, this potential loss was at maximum 30% of the total abundance and did not result in a disruption of the correlation between viral and bacterial abundance. Thus, this suggests either that attachment of viruses was not a major cause of loss of viruses or that losses were not substantial.

Solar radiation can destroy viral particles and cause losses of infectivity without losses of particles [START_REF] Suttle | Mechanisms and rates of decay of marine viruses in seawater[END_REF]. Data from the study area suggest that DNA effective radiation attenuates more rapidly with depth in more coastal than in more offshore waters [START_REF] Conan | Effect of solar ultraviolet radiation on bacterio-and phytoplankton activity in a large coral reef lagoon (southwest New Caledonia)[END_REF]. Thus, a gradient in the losses of viral infectivity due to solar radiation can be expected, with the lowest effect in the bays. In addition, cell-specific bacterial production increased towards the bays [START_REF] Torréton | Correspondence between the distribution of hydrodynamic time parameters and the distribution of biological and chemical variables in a semienclosed coral reef lagoon[END_REF], Rochelle-Newall et al. 2008), and this could also result in an increase of viral infection [START_REF] Wommack | Virioplankton: viruses in aquatic ecosystems[END_REF]. However, these mechanisms did not disrupt the relationship between viral and bacterial abundance (Table 5). In the bays, it is possible that increased losses by attachment are balanced by reduced losses due to UV light and higher infection frequencies. Thus, assuming that the models of [START_REF] Gasol | Lack of coupling between heterotrophic nanoflagellates and bacteria: a general phenomenon across aquatic systems?[END_REF] and [START_REF] Gasol | A framework for the assessment of top-down vs bottom-up control of heterotrophic nanoflagellate abundance[END_REF] are applicable, the data indicate that the relative impact on bacterioplankton mortality changed from viral lysis dominating in the bays to HNF dominating in the open ocean.

Bacterial community composition

Genetic fingerprints such as 16S rRNA gene-based DGGE have methodological constraints, which could influence our analysis. For example, multiple operons could be problematic, either resulting in an overestimation of a phylotype (in the case of sequence identity of multiple operons) or in suggesting higher diversity (in the case of sequence diversity of multiple operons). However, this is unlikely for the investigated types of water-column environments [START_REF] Brown | Coupling 16S-ITS rDNA clone libraries and automated ribosomal intergenic spacer analysis to show marine microbial diversity: development and application to a time series[END_REF]). Moreover, it is known that some primers select against Gammaproteobacteria. However, we used an improved primer set that also detects the SAR11 cluster and some Gammaproteobacteria [START_REF] Sanchez | Comparison of different denaturing gradient gel electrophoresis primer sets for the study of marine bacterioplankton communities[END_REF]. Indeed, the ubiquitous SAR11 cluster [START_REF] Morris | SAR11 clade dominates ocean surface bacterioplankton communities[END_REF] was detected in our samples. In addition, plastids might be amplified. However, we did not obtain plastid sequences from the SW lagoon of New Caledonia. A high number of phylotypes belonging to Rhodobacteriaceae as in the present study was also found in the Mediterranean Sea using DGGE [START_REF] Alonso-Saez | Seasonality in bacterial diversity in north-west Mediterranean coastal waters: assessment through clone libraries, fingerprinting and FISH[END_REF][START_REF] Malits | Effect of turbulence and viruses on aggregate formation and prokaryotic cell size, production and diversity[END_REF], where it was also demonstrated by using fluorescence in situ hybridization (FISH) that Roseobacter can be numerically dominant [START_REF] Alonso-Saez | Seasonality in bacterial diversity in north-west Mediterranean coastal waters: assessment through clone libraries, fingerprinting and FISH[END_REF]. Our detection of Alteromonadaceae sequences is more surprising, since the abundance of this group is thought to be low. However, bloom-like outbreaks have been documented recently for Alteromonas [START_REF] Alonso-Saez | Seasonality in bacterial diversity in north-west Mediterranean coastal waters: assessment through clone libraries, fingerprinting and FISH[END_REF], probably because they can react quickly to disturbances [START_REF] Allers | Response of Alteromonadaceae and Rhodobacteriaceae to glucose and phosphorus manipulation in marine mesocosms[END_REF]. At the study site, the Alteromonas bands were most typical for the bays. Assuming that Alteromonas-specific responses to disturbance exist, such disturbances could be mixing of oligotrophic offshore-water with mesotrophic particle-rich bay water.

It is well known from marine systems that bacterial community composition changes along open gradients such as estuaries (e.g. Bouvier & del Giorgio 2002, del Giorgio & Bouvier 2002[START_REF] Crump | Microbial biogeography along an estuarine salinity gradient: combined influences of bacterial growth and residence time[END_REF]. Using cluster analysis, we found that the gradients separated specific bacterial communities in the open ocean and the 2 bays. The system is characterized by gradients from oligotrophic open ocean waters to mesotrophic bays within a distance of ca. 20 km [START_REF] Jacquet | Impact des apports en nutriments sur le réseau trophique planctonique dans du lagon sud-ouest de Nouvelle-Calédonie[END_REF], Mari et al. 2007b, Rochelle-Newall et al. 2008). The gradients include water residence time, metal concentrations (Ni, Cr, and Zn), nutrient and chl a concentrations, particulate organic concentration and TEP contribution, and bacterial production (Mari et al. 2007b, Migon et al. 2007, Torréton et al. 2007). In addition, coral mucus harbors a large bacterial diversity [START_REF] Rohwer | Diversity and distribution of coral-associated bacteria[END_REF], and mucus (and thus, probably also attached bacteria) is transported into the lagoon system [START_REF] Wild | Coral mucus functions as an energy carrier and particle trap in the reef ecosystem[END_REF]). All of these parameters could have influenced bacterial community composition.

The community composition of attached and freeliving bacteria can be different [START_REF] Delong | Phylogenetic diversity of aggregate-attached vs. free-living marine bacterial assemblages[END_REF][START_REF] Acinas | Diversity of free-living and attached bacteria in offshore Western Mediterranean waters as depicted by analysis of genes encoding 16S rRNA[END_REF][START_REF] Crump | Phylogenetic analysis of particle-attached and free-living bacterial communities in the Columbia River, its estuary, and the adjacent coastal ocean[END_REF]. Particle load increases from open ocean to bay stations (Mari et al. 2007b). Thus, the relative proportion of attached bacteria is likely much higher in the bays than in the open ocean. Fingerprints of total bacteria did not differ from free-living bacteria in the open ocean, whereas the strongest difference was found for Grande Rade Bay. Thus, our data suggest an abundant and phylogenetically specific attached bacterial community in the bays. The long water residence time as a consequence of constrained hydrodynamic circulation (Mari et al. 2007b) could provide enough time for the development of a specific or more pronounced community as has been previously suggested for another system [START_REF] Crump | Microbial biogeography along an estuarine salinity gradient: combined influences of bacterial growth and residence time[END_REF]). Bacterial turnover times were indeed much lower than the water residence times in the investigated bays (Fig. 5). In addition, the positively buoyant particles in the bays (Mari et al. 2007b), which keep the attached bacterial communities suspended, could have contributed to that. Moreover, this feedback system, where organic matter is not exported efficiently but is continuously degraded in the water column, results in refractory dissolved organic matter (Mari et al. 2007b), which could also have influenced the development of specific communities in the bays. Also, a longer water residence time could provide more opportunities for bacteria from other water masses or the atmosphere to become established and common. A similar mechanism could operate for organic matter compounds and metals, which could then also influence bacterial community composition.

Diversity hypotheses

It is noteworthy that we sampled a trophic gradient along which chl a concentration and bacterial production varied by more than an order of magnitude (Mari et al. 2007b, Torréton et al. 2007, Rochelle-Newall et al. 2008). Thus, the trophic gradient in the lagoon of Noumea allows for testing predictions from hypotheses describing the relationship between diversity and productivity. The number of bands detected using genetic fingerprinting is certainly an underestimation of species richness. Thus, as the number of DGGE bands is interpreted as an indicator of evenness, i.e. a low number of bands likely means a lower evenness and a higher dominance of detectable phylotypes [START_REF] Bonilla-Findji | Viral and flagellate control of prokaryotic production and community structure in offshore Mediterranean waters[END_REF]). As such, DGGE bands can be used to assess hypotheses on mechanisms controlling diversity.

A general hypothesis assumes a unimodal distribution of diversity along a productivity gradient, with the highest diversity at intermediate productivity (e.g. [START_REF] Worm | Consumer versus resource control of species diversity and ecosystem functioning[END_REF]. Using chl a to represent productivity and the number of bands as a diversity parameter, the number of phylotypes of free-living communities decreased linearly with chl a concentration. Others have found a decrease in the number of phylotypes of free-living communities with increasing bacterial production and respiration [START_REF] Reinthaler | Relationship between bacterioplankton richness, respiration, and production in the Southern North Sea[END_REF], Winter et al. 2005). This potentially suggests a common feature such as a change in evenness when trophic gradients are investigated [START_REF] Worm | Consumer versus resource control of species diversity and ecosystem functioning[END_REF]. We found a unimodal distribution for total communities; however, this distribution showed a U-shape and not a hump form. It has been shown before that the relationship between chl a and the number of detected bands for bacterioplankton can be complex. Hump-shaped, Ushaped, and a lack of relationships between the richness of different large taxonomic groups of bacteria and chl a concentration have been demonstrated for freshwater systems (Horner-Devine et al. 2004a). Our findings (PCA, regression and cluster analysis) suggests that complex patterns can also originate from differences in community composition between freeliving and attached bacteria and from varying contributions of the attached to total communities. The low dominance in offshore waters supports widely held but not thoroughly tested ideas that dominance is lower and species diversity is higher in oligotrophic than in eutrophic environments. The low dominance in the bays could then be due to a mixture of very different free-living and attached communities.

Mortality factors such as viral lysis and protistan grazing can also influence productivity-diversity relationships [START_REF] Worm | Consumer versus resource control of species diversity and ecosystem functioning[END_REF]. For example, the number of detected phylotypes of the free-living community decreased with viral abundance in the North Sea [START_REF] Winter | Linking bacterial richness with viral abundance and prokaryotic activity[END_REF]. A decrease in the number of bands of the free-living community with increasing viral abundance was also detected in the present study. PCA-C2 suggested a positive effect of HNF on the number of bands of the total community, and PCA-C3 indicated a negative effect of ciliates. HNF can sustain the number of detected phylotypes, especially when acting synergistically with viral lysis [START_REF] Zhang | Viruses and flagellates sustain apparent richness and reduce biomass accumulation of bacterioplankton in coastal marine waters[END_REF][START_REF] Bonilla-Findji | Viral and flagellate control of prokaryotic production and community structure in offshore Mediterranean waters[END_REF]. HNF and viruses can also modify the relationship between diversity (as the number of DGGE bands) and productivity [START_REF] Bonilla-Findji | Viral and flagellate control of prokaryotic production and community structure in offshore Mediterranean waters[END_REF]. The PCA component matrix could thus suggest that, at high grazing pressure by HNF, bacterial evenness is sustained; at low grazing pressure, i.e. when HNF are top-down controlled by ciliates, only a few bacterial phylotypes may dominate.

CONCLUSIONS

This study is one of the few investigating bacterial community composition in tropical coral reef ecosystems. Bacterial community composition was clearly different between offshore waters and the semi-enclosed bays. Water residence time and mortality factors seemed to be a crucial parameter structuring bacterial communities. An unexpected potentially cascading effect of ciliate control on HNF, and thus on bacterial community composition, was detected. Our data also confirm the idea that it may be necessary to distinguish between attached and free-living bacterial community diversity and associated methods to assess productivity.

Fig. 1 .

 1 Fig. 1. Study area showing sampling stations. Stns D and N are in Grande Rade Bay and Sainte Marie Bay, respectively, whereas Stns M are in the lagoon proper and offshore

Fig. 3 .

 3 Fig. 3. Cluster analysis of denaturing gradient gel electrophoresis (DGGE) band patterns by the unweighted pair-group method.The distance matrix was calculated using a simple match similarity index

Fig. 5 .

 5 Fig.5. Local e-flushing time (LeFT) and bacterial turnover times at the sampling stations. Water residence times were calculated for the most common trade wind conditions of 8 m s -1(Mari et al. 2007a). Bacterial turnover times were calculated from 2 data sets available from the study stations[START_REF] Jacquet | Impact des apports en nutriments sur le réseau trophique planctonique dans du lagon sud-ouest de Nouvelle-Calédonie[END_REF], Torréton et al. 2007). The Torréton data set was obtained from cruises in September 2000, June 2003, and October 2004, and the Jacquet data set was from April-May 2002, August 2002, and January 2003. Bacterial production was calculated from 3 H-thymidine incorporation rates (TdR) using a conversion factor of 2.85 × 10 8 cells mol -1 TdR obtained for the environment[START_REF] Jacquet | Impact des apports en nutriments sur le réseau trophique planctonique dans du lagon sud-ouest de Nouvelle-Calédonie[END_REF]

Table 3 .

 3 Protistan and viral characteristics at the sampling stations. Virus data are fromMari et al. (2007a). Each value corresponds to the average (range in parentheses) of 2 or 4 measurements taken for each station. HNF: heterotrophic nanoflagellates; ANF: autotrophic nanoflagellates; TNF: total nanoflagellates

	Trophic group	Stn	Synechococcus	Prochlorococcus	Cyanobacteria	Picoeukaryotes
			(10 4 ml -1 )	(10 3 ml -1 )	(10 4 ml -1 )	(10 3 ml -1 )
	Head of bays	D01	16.8 (16.0-17.7)	3.7 (ND-7.3)	17.1 (16.7-17.8)	6.3 (5.6-7.1)
		N04	12.4 (11.2-12.8)	ND	12.0 (11.2-12.8)	10.7 (10.1-11.4)
	Middle of bays	D08	19.1 (18.5-19.8)	ND	19.1 (18.5-19.8)	5.3 (5.1_5.5)
		N12	12.9 (12.2-13.6)	ND	12.9 (12.2-13.6)	11.6 (10.7-12.4)
	Mouth of bays	D22	18.3 (17.4-19.5)	0.7 (ND-1.3)	18.6 (17.5-19.5)	3.9 (3.7-4.0)
		N33	10.5 (10.2-10.8)	ND	10.5 (10.2-10.8)	5.4 (5.0-5.9)
	Middle of lagoon	M05	12.5 (11.1-13.9)	10.1 (5.5-14.6)	13.5 (11.2-15.4)	3.2 (2.3-4.4)
		M33	13.2 (12.5-14.0)	6.1 (5.0-7.2)	13.9 (13.3-14.5)	3.3 (2.4-4.2)
	Near barrier	M10	12.2 (8.2-15.2)	20.7 (9.2-41.4)	13.6 (9.5-17.1)	4.8 (2.0-8.1)
	Open ocean	M41	2.2 (0.8-2.8)	145.7 (130.7-167.7)	16.8 (15.0-19.4)	3.4 (1.6-4.3)

Table 2 .

 2 Characteristics of Cyanobacteria and autotrophic picoeukaryotes at the sampling stations. Each value corresponds to the average (range in parentheses) of 2 or 4 measurements taken for each station.

ND: not detectable. Cyanobacteria is the sum of Synechococcus and Prochlorococcus aceae (e.g. genera Rugeria and Roseobacter), (2) sequences related to the SAR11 cluster, (3) sequences related to other Alphaproteobacteria, (4) sequences related to Alteromonadaceae (genus Alteromonas), and (5) a sequence related to cyanobacterial sequences. The band corresponding to cyanobacterial sequences was not included in the analysis of the community composition. It is noteworthy that no plastid sequences were detected.

Table 4 .

 4 Phylogenetic affiliation of sequences from denaturing gradient gel electrophoresis (DGGE) bands with closest uncultured and cultured matches. The number of bases used to calculate sequence similarity is given in parentheses in the third column. Note that the last 2 sequences were from bands not included in the analysis of the community composition because they were below the threshold set for the detection of a band

	20
	Band	Closest match	% Sequence similarity	Taxonomic group
		(environmental or culture)		(no. bases)
	Noumea04-3	Roseobacter sp. MED001		98 (413)	Alphaproteobacteria/Rhodobacteriaceae
	Noumea04-4	Roseobacter sp. MED001		96 (369)	Alphaproteobacteria/Rhodobacteriaceae
	Noumea04-7	Clone VH-PA7-59		97 (457)	Gammaproteobacteria/Alteromonadaceae
	Noumea04-9	Clone 2_B6 or 2_C6		99 (433)	Alphaproteobacteria/Rhodobacteriaceae
	Noumea04-10	Clone SIMO-846		99 (420)	Alphaproteobacteria/Rhodobacteriaceae
	Noumea04-11	Clone 2_C6		98 (434)	Alphaproteobacteria/Rhodobacteriaceae
	Noumea04-12	Clone SIMO-846		98 (470)	Alphaproteobacteria/Rhodobacteriaceae
	Noumea04-13	Alphaproteobacterium IMCC10404		99 (279)	Alphaproteobacteria
	Noumea04-14	Alphaproteobacterium IMCC10417		97 (281)	Alphaproteobacteria
	Noumea04-16	Proteobacterium MS-B-38 or MS-F-42	96 (250)	Proteobacteria
	Noumea04-18	Clone VH-PA7-59		98 (445)	Gammaproteobacteria/Alteromonadaceae
	Noumea04-21	Marine eubacterial sp. (FL1)		93 (242)	Alphaproteobacteria/SAR11
	Noumea04-22	SAR11 cluster Alphaproteobacterium	86 (268)	Alphaproteobacteria/SAR11
	Noumea04-27	Prochlorococcus marinus Str. MIT 9215	98 (364)	Cyanobacteria/Prochlorococcus

Fig. 2. Number of detected bands denaturing gradient gel electrophoresis (DGGE) of total and free-living communities in the southwest lagoon of New Caledonia as a function of environment. For the free-living community, only data from Grande Rade Bay transects are available

Table 5 .

 5 Spearman correlation coefficients among all parameters. Data are from Table1-3 and were log or arcsine transformed. Temperature is not shown, as no significant correlation was found. R-TC: number of bands, total community; R-FLC: number of bands, free-living community; LeFT: local e-flushing time; chl a: chlorophyll a; Synecho: Synechococcus; PicoE: picoeukaryotes; HNA: high nucleic acid bacteria; HNF: heterotrophic nanoflagellates; TNF: total nanoflagellates. Values in bold are p < 0.05;

	A lower bacterial abundance in the open ocean than in
	lagoon stations of coral reefs as shown in the present

Table 6 .

 6 Component matrix for the lagoon of Noumea. Extraction method: principal component analysis (PCA). Data set for PCA was reduced to 7 key parameters (no. of samples = 24).

		17
				Free-living community
		16		Total community
	No. of DGGE bands	13 14 15
		12
		11
		-1	-0.8	-0.6	-0.4	-0.2	0	0.2	0.4
				log Chl a concentration (µM)
	Fig. 4. Number of detected denaturing gradient gel elec-
	trophoresis (DGGE) bands of total and free-living communi-
	ties in the southwest lagoon of New Caledonia as function of
	chl a concentration. For the free-living community, only data
	from Grande Rade Bay transects are available. Total commu-
	nity: y = 10.95x 2 + 8.17x + 14.6, R 2 = 0.71, p < 0.001; free-living
		community: y = -2.35x + 13.47, R 2 = 0.81, p < 0.005

Three components were extracted. Correlations > 0.4 are in bold. No. of bands: number of denaturing gradient gel electrophoresis (DGGE) bands for total community; LeFT: local e-flushing time; BA: bacterial abundance; VA: viral abundance; HNFA: heterotrophic nanoflagellate abundance; CA: ciliate abundance; chl a: chlorophyll a

Acknowledgements. We thank the crew of the RV 'Coris' for their assistance during sampling. This research was supported by the French National Research Agency (ANR-ECCO program and ANR-Blanc-MAORY project) and by the French Research Institute for Development (IRD). We thank C. Winter for help with the similarity tree and J. Dolan for improving the English. Two anonymous reviewers made valuable comments, which helped to improve the manuscript.