Variability of primary and bacterial production in a coral reef lagoon (New Caledonia)

Marine Pollution Bulletin 61 (2010) 335–348

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Marine Pollution Bulletin journal homepage: www.elsevier.com/locate/marpolbul

Variability of primary and bacterial production in a coral reef lagoon (New Caledonia) Jean-Pascal Torréton a,*, Emma Rochelle-Newall a, Olivier Pringault a, Séverine Jacquet a,1, Vincent Faure b, Enora Briand a,2 a b

UR 103, CAMELIA, UMR 5119 ECOLAG, Université Montpellier II, Case 093, 34095 Montpellier, France Centre d’Océanologie de Marseille, Station Marine d’Endoume, 13007 Marseilles, France

a r t i c l e

i n f o

a b s t r a c t

Keywords: Nutrients Phytoplankton Bacterioplankton Temporal variability New Caledonia Pacific Ocean

We assessed the temporal variability of nutrients, phytoplankton and bacterioplankton at two sites of different trophic status in New Caledonia’s South-West lagoon, a tropical coastal ecosystem. During stable meteorological conditions, Chl.a, bacterial production and nutrient concentrations experience weak but consistent daily variation. Short-term (1–2 week interval) fluctuations of planktonic variables are in the same range as annual variations at both sites. A part of these short term variations is linked to local meteorological events (wind in the main channel, precipitation at the coastal station). Although annual variations are weak compared to short term variations, phytoplankton and bacterioplankton production show consistent temporal patterns, with maxima in December–January and April–May and minima in August. Annual bacterial production represents 21% and 34% of particulate primary production at the oligotrophic and mesotrophic sites, respectively. Mineral nutrient availability indicates that nitrogen is probably the primary limiting factor of phytoplankton throughout the year. Ó 2010 Elsevier Ltd. All rights reserved.

1. Introduction

itude coastal ecosystems, like in coral reef lagoons isolated from terrestrial influence, the respective importance of diel and seasonal variations may change considerably. Seasonal variations of phytoplankton and bacterioplankton biomass and production are usually low in coral reef lagoons (Burford et al., 1995; Furnas and Mitchell, 1986; Torréton and Dufour, 1996). Moreover, any seasonality found is often variable and is superimposed by short term variations induced by meteorological forcing such as sediment resuspension (Muslim and Jones, 2003; Walker and O’Donnell, 1981) or marine intrusion (Furnas and Mitchell, 1986; Gast et al., 1999). The relative importance of temporal variations at different scales in tropical ecosystems may differ from those observed in temperate systems (Longhurst and Pauly, 1987). Therefore, evaluating the range of temporal variations over a period of hourly, daily and annual time scales is of critical importance to assess the representativeness of observed planktonic processes (Tsai et al., 2005). Moreover, in the open ocean, temporal variations of respiration appear less important than those of primary production (Aristegui and Harrison, 2002; Williams et al., 2004). Williams et al. (2004) showed that missing intermittent bursts of primary production through undersampling (Karl et al., 2003), could explain a part of the paradoxically high respiration/production ratio in oligotrophic areas of the ocean and may thus lead to erroneous metabolic balance calculations.

Primary producers and heterotrophic microbial consumers are at the base of aquatic food webs and their abundance and growth are under the influence of several biotic and abiotic factors, including resources, temperature, light, and predation. Most of these factors, varying over different time frames, induce temporal variations of biomass and activity within the microbial foodweb. Diel to seasonal changes in abundance and growth of plankton have been studied extensively in various marine environments in temperate waters. While the pattern and range of diel variations may change with trophic status (Gasol et al., 1998), seasonal variations are usually high compared to short term (i.e. diel) fluctuations. Indeed, diel variations of nutrients, bacterioplankton and phytoplankton fall generally in the 1.5–5-fold range (Gasol et al., 1998; Tsai et al., 2005; Winter et al., 2004), whereas seasonal variations can typically attain 1–2 orders of magnitude (Calvo-Diaz and Moran, 2006; Pinhassi et al., 2006; Tsai et al., 2005). In contrast, in low lat-

* Corresponding author. Tel.: +33 4 67 14 45 19; fax: +33 4 67 14 37 19. E-mail address: [email protected] (J.-P. Torréton). 1 Present address: Centre Technique Littoral, Lyonnaise des Eaux, Technopôle Izarbel, 64210 Bidart, France. 2 Present address: MNHN, USM505/EA4105 Ecosystèmes et Interactions Toxiques, 57 rue Cuvier, Case 39, 75231 Paris Cedex 05, France. 0025-326X/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.marpolbul.2010.06.019

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Despite these problems, in coral reef lagoons few have attempted to determine the variability of nutrients (Gast et al., 1999; Muslim and Jones, 2003; Walker and O’Donnell, 1981), phytoplankton (Burford et al., 1995; Charpy, 1996; Walker, 1981b) and bacterial biomass and production (Gast et al., 1999; Torréton and Dufour, 1996) at different time frames. Furthermore, to our knowledge, none have attempted to simultaneously determine the concomitant fluctuations of all these variables and to compare them at time frames ranging from daily to seasonal cycles in a coral reef ecosystem. Planktonic functioning in the South-West lagoon of New Caledonia has received increasing attention in the recent years (Briand et al., 2004; Jacquet et al., 2006; Mari et al., 2007a, 2007b; Torréton et al., 2007; Conan et al., 2008; Rochelle-Newall et al., 2008; Faure et al., 2010; Pringault et al., 2009), however, most of these process studies were performed during short campaigns. Several recent studies have described temporal variations of either nutrient, phytoplankton or zooplankton standing stocks in this system (Dolan et al., 2006; Rodier and Le Borgne, 2008; Le Borgne et al., 2010; Fichez et al., 2010) and all suggested moderate seasonal fluctuations compared to variations at shorter time frames. For example, the longest time series, a 4.5-year study of chlorophyll a concentrations, revealed a seasonal 2-fold maximum at a coastal station in the SW lagoon of New Caledonia (Binet and Le Borgne, 1996; Le Borgne et al., 2010). These authors also showed that this amplitude of variation can be observed at short time scales in relation to local meteorological events or advection of water masses (Le Borgne et al., 2010). Finally, only one other study has focused on temporal variations of planktonic productivity in this system. However, this study was restricted to a 1-month survey in one site (Renaud et al., 2005). The objective of this study was to assess temporal variations of bacterioplankton and phytoplankton biomass and production and nutrients at time frames ranging from hours to seasons in a tropical coastal ecosystem, the South-West lagoon of New Caledonia. We compare the variability of these parameters at two sites: one considered isolated from anthropogenic influences and another located in a bay subject to urban impacts. We also assess the range of variations of nutrient and elemental ratios with the goal of determining the probable limiting factor and its variation throughout a 1-year study. Finally, we examine if there are temporal shifts in the ratio between bacterial and phytoplankton production.

volume and the daily exchange flux) of 6.8 days in the SW lagoon (Jouon et al., 2006). In this study, temporal variations of nutrients and planktonic processes were studied at different time scales (hours to months) over the period February 2002 to April 2004 in two contrasting stations (Table 1). Station M33 (depth 24 m, Fig. 1), isolated from coastal influence, is more efficiently flushed by oceanic waters than the shallower (depth 14 m) station N12 (Jouon et al., 2006) located in a bay receiving urban wastewater. Hourly variations were studied by collecting water samples at 3 m depth every 2–4 h (Table 1), using acid-washed Niskin bottles and were processed within 1 h. An assessment of the day-to-day variation was conducted at station N12 in February 2004 (Table 1). Water samples were collected at 3 m depth every day at 0730 and 1630 and treated within 1 h at the laboratory on-shore. Samples for the annual variation study were collected at both stations every 1–2 weeks from 04/04/02 to 04/04/03. Water samples were collected at 0730 at 5 depths homogeneously distributed over the whole water column (3, 7.2, 11.5, 15.8, 20 m for M33; 3, 4.7, 6.5, 8.2, 10 m for N12). Samples were kept in Niskin bottles until being pooled at the laboratory within 1–2 h. Sampling continued with fewer variables (Table 1) between 04/04/03 and 04/04/04. 2.2. Water column physical description Temperature, in vivo fluorescence, salinity, turbidity and Photosynthetically Active Radiation (PAR) profiles were recorded throughout the whole water column using a SeaBird SBE 19 profiler with Seapoint Fluorometer and Turbidity Meter and a LiCor spherical sensor. The ratio between 3 m-deep and water column averaged in vivo fluorescence is not significantly different from 1 at both stations. This indicates that 3 m deep sampling, chosen to avoid reduced salinity water following high precipitation, is on average representative of the whole water column. 2.3. Meteorological variables Wind was continuously recorded at the Maître Island station and at the Meteo France station at Faubourg Blanchot (Fig. 1). Incident PAR was recorded continuously adjacent to the primary production incubations. Pluviometry was recorded at the Meteo France station at Faubourg Blanchot. 2.4. Nutrients

2. Material and methods 2.1. Study site and sampling New Caledonia is located in the Pacific Ocean between latitudes 19° and 23° South and longitudes 163° and 168° East. The main island is surrounded by barrier reefs delimiting large lagoon areas. Among those, the South-West lagoon of New Caledonia is separated from the ocean by an emerging barrier reef interrupted by 3 passes. It is connected to the Southern lagoon at its southeastern end, from which it receives the main input of oceanic waters. Mean water depth is 17.5 m, however, in the canyons located in front of the passes depths of up to 60 m are found. Climate in New Caledonia is mainly characterized by a dry-tropical regime with a dry and a wet season. Lagoon temperature varies by a maximum of 10 °C over the year (Le Borgne et al., 2010). The hydrodynamics of the South-West lagoon of New Caledonia have been extensively studied (e.g. Ouillon et al., 2010). The semidiurnal tide propagates from the South to the North. South-East trade winds drive the main North-West flushing which rapidly renews the lagoon water. Recent hydrodynamic modeling has calculated an average water exchange time (ratio between the total

Ammonium concentration was determined fluorometrically on triplicate 40 ml samples with a Turner TD-700, using the o-phtaldialdehyde method (Holmes et al., 1999). This procedure gave an average coefficient of variation (CV) of 7% between triplicates. Unfiltered replicate 40 ml samples were immediately frozen pending nitrate + nitrite (NO3 + NO2), and phosphate analyses. Nitrates were reduced to nitrites according to Wood et al. (1967) and NO3 + NO2 concentrations were determined according to Raimbault et al. (1990) on a Bran + Luebbe Autoanalyzer III with an average CV of 7% between replicates. Phosphate concentrations (Soluble Reactive Phosphorus, SRP) were determined using the same autoanalyzer according to Grasshoff et al. (1983) with an average CV of 9% between replicates. Total silicates (dissolved and colloidal) were measured on one 60 ml subsample immediately frozen after sampling following Grasshoff et al. (1983). 2.5. Bacterial biomass and production Heterotrophic bacteria were enumerated by flow cytometry after staining with SYBR I green (Molecular Probes, Eugene, OR) according to Marie et al. (1997). Water samples (1.5 ml) were

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Table 1 Sampling overview. BP: bacterial production; BA: bacterial abundance; PP: primary production; Chl.a: chlorophyll a concentration; nutrients: ammonium, nitrate + nitrite, phosphate; CTD casts: temperature, salinity, turbidity, in vivo fluorescence. Station

Measured variables

Sampling depth (m)

Sampling frequency

13/04/02 27/06/03 17/02/04 04/04/03

M33 N12 M33 N12 M33 N12

3 3 3 Integrated

Every Every Every Every

04/04/03 to 04/04/04

M33 N12

BP, Chl.a, nutrients, CTD casts BP, Chl.a, nutrients, CTD casts BP, Chl.a, CTD casts BA, BP, Chl.a and PP (total, >2 lm, >10 lm), nutrients, CTD casts, wind, irradiance Chl.a, nutrients, CTD casts

3

Weekly for CTD, bimonthly for nutrients and Chl.a

N é

mb

Du

20

22°S

No

166°E

Pir

um

og

éa

20

164°E

r

ve

i aR

168°E

22°20'

ive r

20°S

4 h from 6 am 2 h from 6 am day at 7:30 am and 4:30 pm 1–2 weeks

ue sR

to to to to

Coulée

11/04/02 26/06/03 11/02/04 04/04/02

River

Date

N12

Maître Is.

M33

22°30'

N 5

Land Reefs 166°10'

166°20'

166°30'

166°40'

Fig. 1. New Caledonia and study sites in the SW lagoon. MF: Meteo France meteorological station at Faubourg Blanchot.

preserved with an addition of 7.5 ll glutaraldehyde per sample (Sigma Grade II) at room temperature in the dark for 15 min before storage in liquid nitrogen pending analysis. Enumeration was conducted on a FACSCan™ flow cytometer (BD-Biosciences, San-Jose, CA) equipped with an air-cooled laser providing 15 mW at 488 nm and with a standard filter setup. Yellow fluoresbrite beads (0.1002 lm, Polysciences Inc., Warrington, PA) were used as internal standard. Duplicate determinations varied by 10% on average. Bacterial production (BP) was estimated in the dark using [methyl-3H]thymidine (TdR) (Fuhrman and Azam, 1982) and the protocol is detailed elsewhere (Briand et al., 2004). Duplicate incubations varied by 4% on average. TdR incorporation was converted into bacterial production using a conversion factor empirically determined in the SW lagoon (avg. ± SE 2.9 ± 0.4  1018 cell mol 1, n = 7) and 12.4 fgC cell 1 (Fukuda et al., 1998). 2.6. Phytoplankton abundance and production Chlorophyll a (Chl.a) concentration was determined fluorometrically on replicate 300 ml samples collected on Whatman GF/F fil-

ters according to Holm-Hansen et al. (1965). When determined (i.e. during the 1 year survey), size fractionated Chl.a concentrations were estimated on replicate 300 or 500 ml samples, using 2 lm and 10 lm porosity Nuclepore membranes. Primary production was estimated using the 14C-method in ‘‘simulated in situ” conditions. Water was distributed into seven 76 ml Nalgene polycarbonate bottles. Five sub-samples, used to measure total phytoplanktonic incorporation, were incubated with 0.15 MBq of 14 C-bicarbonate (Amersham, 60–68 MBq ml 1) under shading nets re-creating different percentages of irradiance (0%, 18%, 34%, 68% and 100% incident irradiation) in a thermoregulated (in situ temperature ±2 °C) incubator exposed to the daylight. Two sub-samples used to measure 14C-incorporation in size fractions were incubated with 0.30 MBq of 14C-bicarbonate at 68% incident irradiance. The irradiance received during the incubations was measured using a LiCOR detector attached to the side of the incubator. Incubations lasted about 4 h, generally between 9 a.m. and 1 p.m. Then, samples were immediately filtered onto either Whatman GF/F, 2-lm or 10-lm porosity Nuclepore polycarbonate membranes under low vacuum pressure (<7000 Pa). Membranes were then

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placed in scintillation vials with 250 ll of 0.5 N HCl and were placed under the hood overnight to remove any inorganic carbon. Samples were counted in a Tri-Carb scintillation counter after the addition of 4 ml of scintillation cocktail (Packard, Ultima GoldÒ). Counting efficiency was determined using external standards. The amount of carbon fixed per day (PP in mgC m 3 d 1) was computed as (dpm1/dpm2)  (Vp/Vt)  A  1.05  (Ed/Ei), where dpm1 is the radioactivity incorporated in each sample, dpm2 is the total introduced radioactivity, Vp is the volume of sample taken for determination of total radioactivity, Vt the volume of sample, A is the concentration of inorganic carbon in the SW lagoon (average 28.215 mg C L 1), 1.05 is the isotopic fractionation between 12C and 14C, and Ed and Ei are irradiances (E m 2 d 1) received daily and during the incubation, respectively. A previous study showed that duplicate determinations vary on average by 5% using this procedure (Jacquet, 2005). Production at each irradiance level was attributed to a depth at which the same irradiance occurred, as determined from the PAR attenuation profiles. Depth-integrated production was computed using the trapezoid method and production per unit of volume was computed using average depth.

age by 16% and 7%, respectively, in the nepheloid layer (18–24 m). Station N12 displayed similar but more pronounced vertical trends. Average differences between sub-surface (0.5 m) and bottom temperature and salinities were 0.25 °C and 0.5, whereas, turbidity and Chl.a increased more sharply (77% and 9%, respectively) within the nepheloid layer (10–14 m). The larger nepheloid at station N12 could be due to the shallower depth combined with sediment type differences. At station N12 the muddy sediment is likely to be more easily resuspended by vertical mixing due to wind influence than at the deeper station M33 where sediment is composed of coarse sand (Chevillon, 1996). Ouillon et al. (2010) reported a thermo-haline stratification during the wet and warm season from January to April. The average vertical profiles at N12 and M33 varied along the water column when the two seasons were compared. Sub-surface salinity was on average 1.23 and 0.18 percent lower than bottom salinity during the wet season (January–April) for N12 and M33, respectively, whereas it was 0.24% and 0.15% lower than bottom salinity during the dry season (May–December) for N12 and M33, respectively. However, the vertical trends for chlorophyll a in vivo fluorescence and turbidity did not change significantly between these two seasons (not shown).

3. Results 3.2. Nutrients and chlorophyll a 3.1. Meteorological and hydrological conditions During the study periods, winds were characterized by two main directions. South-Eastern trade winds (90–160°) represented 66% of wind occurrence. Westerly winds (220–300°) represented 11% of wind occurrence. Between May and October 2002, winds were characterized by an alternation between these two directions, whereas between October 2002 and February 2003 SouthEast Trade Winds prevailed. Wind speed ranged between 0.13 and 13 m s 1 (average 6.2 ± 0.2 m s 1) with an exceptional daily averaged intensity of 41 m s 1 on 14 March 2003 corresponding to cyclone Erica. Wind speed varied on average (±Standard Error, SE) by 2.0 ± 0.1-fold between successive days, with a maximum ratio of 15. This short term variability of wind direction and speed was also detectable during the 24 h cycle of 11 April 2002. Wind velocity increased from 6.9 m s 1 at 0600 to 13.8 m s 1 at 1300 and these variations (wind speed 9.4 ± 0.5 m s 1, wind direction 110 ± 4°, average ± SE computed from wind values averaged every hour) may in part explain the high variability of BP during these diurnal cycles (see below). This peak in wind speed was followed by a return to more quiet conditions the following day (wind speed 8.7 ± 0.3 m s 1, wind direction 108 ± 2°), characterized by lower BP variations (Table 2). Irradiance showed important day-to-day variations (average 1.42-fold), and varied seasonally with minimal values in June–July (5–25 E m 2 d 1) and maximal values in December–January (10– 62 E m 2 d 1), as would be expected in the austral summer (Fig. 2). The yearly averaged PAR received daily was 38.6 ± 0.7 E m 2 d 1. Precipitation was abundant from April 2002 to September 2002 and December 2002 to April 2003, and minimum between October 2002 and December 2002. Corresponding to the austral winter, minimum water column temperature (21.2 and 20.4 °C at M33 and N12, respectively) occurred in August and maximal values were attained in February (27.8 and 28.3 °C at M33 and N12, respectively; data not shown). Similar to temperature, the seasonal variability of salinity was more pronounced at N12 (range 34.5–36.0) located in a bay, than at M33 in the Western Shelf (range 35.1–35.8). Based on CTD casts, the water column at station M33 was generally well mixed (Fig. 3). Indeed, differences between sub-surface (0.5 m) and bottom samples were weak, with average differences of 0.2 °C and 0.06 (salinity). Turbidity and Chl.a increased on aver-

At both stations nutrients varied widely (1.1–2.8) between successive weekly samples (Fig. 4). However, mineral nutrient concentrations were lower throughout the year at station M33 than at N12. At station M33, DIN (Dissolved Inorganic Nitrogen) was composed of on average 67 ± 3% NH4 and had a 5-fold maximum (0.79 lM, for a yearly average of 0.15 ± 0.02 lM) between June and August 2002 with only minor fluctuations during the remainder of the year (not shown). At station N12, DIN was composed of on average 56 ± 3% of NH4, and showed 3–5-fold relative maxima in April–May 2002 (2 lM), between June and August 2002 (1.6 lM) and again in April–May 2003 (2.61 lM) compared to the yearly average (0.56 ± 0.10 lM). SRP varied generally little around the yearly averages of 0.02 ± 0.00 lM at station M33 and 0.11 ± 0.01 lM at station N12 with few exceptions. Maximum values were 0.06 lM (May 02) at M33 and 0.32 lM (April 02) at N12. Silicate concentrations averaged 1.7 ± 0.1 lM at M33 and 3.0 ± 0.3 lM at N12. At N12, concentrations decreased from April to May, were then relatively stable and increased again from January to April. Variations were more erratic at M33. Nutrient concentrations showed a temporal pattern in 2003–2004 roughly similar to that observed in 2002–2003 (data not shown). We also observed significant trends during the 24 h cycles (M33, Fig. 5D–F). Typically, NH4, NO3 + NO2 and SRP concentrations decreased during the day and increased during the night, although significant differences maybe observed between the beginning and the end of diurnal cycle at M33. In contrast, no consistent trend was observed for silicate (mean CV% of 14 ± 1%). The DIN:SRP ratio was on average (±SE) higher at M33 (9.44 ± 1.24) than at N12 (4.4 ± 0.5; Fig. 6A and B). At both stations these ratios are lower than Redfield ratio (16:1, Redfield et al., 1963) most of the year. The Si:DIN ratio was also quite constant throughout the 2002–2003 year. This ratio was always higher than the Redfield value of 1:1 at both M33 and N12. An index of the potentially limiting factor for phytoplankton can be determined from nutrient ratios and threshold values (Dortch and Whitledge, 1992; Justic et al., 1995). Using these criteria, nitrogen was found to be the main factor limiting phytoplankton growth at both stations with few exceptions. There was some evidence of potential P limitation at station M33, however, this was infrequent and occurred only during short periods (Fig. 6A and B).

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Table 2 Summary of diel studies in the SW lagoon. BA: bacterial abundance (106 cell ml 1); BP: bacterial production (lgC l 1 h 1); Chl.a: chlorophyll a (lg l 1); NH4: ammonium (lM); NO2+3: nitrite + nitrate (lM); SRP: phosphate (lM); DIN:SRP = (NH4 + NO3 + NO2)/SRP; and Si: silicate (lM). CV%: coefficient of variation; max/min: maximum to minimum ratio and day/night: ratio between daily and nightly averages. Date

Stations

BA

BP

Chl.a

NH4

NO2+3

SRP

DIN/SRP

Si

11/04/02

M33

Mean CV% Max/min Day/night

0.55 14 1.7 0.9

0.033 59 5.9 0.4

0.23 43 4.6 0.7

0.02 30 2.6 0.8

0.01 50 6.2 1.1

0.05 12 1.4 1.2

0.48 22 2.0 0.8

3.1 6 1.3 0.9

11/04/02

N12

Mean CV% Max/min Day/night

0.62 14 1.6 1.1

0.15 63 7.6 0.6

0.77 31 3.3 0.7

0.05 52 3.8 0.5

0.08 72 10.5 0.2

0.13 26 2.3 0.6

0.94 50 4.1 0.4

4.3 10 1.5 0.9

12/04/02

M33

Mean CV% Max/min Day/night

0.63 14 1.3 1.0

0.059 16 1.5 0.8

0.42 25 2.3 1.1

0.02 24 1.8 1.3

0.01 61 5.7 0.3

0.04 10 1.3 1.0

0.70 25 1.9 1.0

2.8 8 1.3 1.0

12/04/02

N12

Mean CV% Max/min Day/night

0.61 6 1.2 1.0

0.31 7 1.2 1.0

0.81 16 1.6 0.8

0.03 38 3.1 0.6

0.04 79 10.1 0.2

0.15 7 1.2 1.0

0.46 64 5.8 0.3

4.0 10 1.3 1.1

26/06/03

M33

Mean CV% Max/min Day/night

0.74 8 1.3 0.9

0.21 21 2.6 0.9

0.26 16 1.7 1.1

0.04 85 13.4 0.3

0.02 34 2.64 0.7

0.03 22 2.13 0.8

2.46 22 2.0 0.8

1.7 23 2.2 1.0

360 40

Wind speed (m.s-1)

Wind direction (360°)

300 240 180 120

1/6/02

1/8/02

1/10/02

1/12/02

1/2/03

1/6/02

1/8/02

1/10/02

1/12/02

1/2/03

1/4/03

1/6/02

1/8/02

1/10/02

1/12/02

1/2/03

1/4/03

60

Precipitations (mm.d-1)

PAR (E.m-2 d-1)

10

0 1/4/02

1/4/03

60

40

20

0 1/4/02

15

5

60 0 1/4/02

35

1/6/02

1/8/02

1/10/02

1/12/02

1/2/03

1/4/03

40

20

0 1/4/02

Fig. 2. Meteorological variables between April 2002 and April 2003. Wind data recorded at Maître I. station and precipitation recorded at Meteo France station.

At station M33, total Chl.a concentration showed two periods of slight relative maxima, one between April and June 2002 (0.27 ± 0.01 lg l 1) and the other one in January 2003 (0.25 ± 0.02 lg l 1) compared to the remaining of the year (0.21 ± 0.01 lg l 1, Fig. 6C and D). Maximum values of April–June 2003 (0.39 ± 0.03 lg l 1) and January 2004 (0.30 ± 0.07 lg l 1, not shown) were higher than in 2002–2003. This seasonal pattern was similar but more pronounced in N12 (1.7-fold variations) over the 2 years. Yearly average (±SE) Chl.a concentration was significantly (P < 0.001) higher in N12 than in M33. Average

variation between successive samples was roughly similar at N12 and M33 (Fig. 4). The distribution of Chl.a in size classes was different between the two stations and did not show any clear seasonal trend. M33 was characterized by a < 2 lm fraction dominant throughout the year (average ± SE = 72 ± 1%) and 2–10 lm and >10 lm fractions contributing by 12 ± 1% and 17 ± 1% on average to total Chl.a. At station N12, <2 lm and >10 lm fractions contributed in similar proportions to total Chl.a (40 ± 2, and 42 ± 2%, respectively), whereas 2–10 lm fraction was on average 18 ± 2%.

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Temperature (°C difference from water column avg.) -0.2

-0.1

0.0

0.1

0.2

Chlorophyll a (% water column avg.)

Salinity (% water column avg.) 99.5

100.0

70

100

Turbidity (% water column avg.) 130

0

0

0

5

5

5

5

10

10

10

10

15

15

15

15

20

20

20

20

70

100 130 160 190 220

70

100 130 160 190 220

Depth (m)

0

Depth (m)

-0.2

-0.1

0.0

0.1

0.2

99.5

100.0

70

100

130

0

0

0

0

2

2

2

2

4

4

4

4

6

6

6

6

8

8

8

8

10

10

10

10

12

12

12

12

14

14

14

14

Fig. 3. Average vertical distribution of normalized temperature, salinity, chlorophyll a in vivo fluorescence, and turbidity CTD variables during 2 years at stations M33 (upper panel, n, number of profiles = 107) and N12 (lower panel, n = 102). Temperature (°C) is expressed as the difference from water column average. Salinity, in vivo fluorescence of chlorophyll a, and turbidity are expressed as a percentage of water column average. Error bars are SE.

Similar to that observed for inorganic nutrients, some short term variations in Chl.a were also evident. Trends of Chl.a concentration were consistently observed over the 24 h cycle (Fig. 5A) during stable meteorological conditions (wind speed 8.4 ± 0.4 m s 1, wind direction 109 ± 2°, mean ± SE), Chl.a increased during daylight hours and decreased during night time. This daily pattern of Chl.a is in agreement with the one-week survey at station N12 which was also characterized by stable meteorological conditions (wind speed 4.2 ± 0.4 m s 1, wind direction 121 ± 15°, mean ± SE) with afternoon (1630) values being slightly

higher (afternoon/morning ratio = 1.61 ± 0.06) than those of the morning (0700). Daily mean Chl.a varied by 1.11 ± 0.03-fold between successive days (Fig. 7). 3.3. Bacterial abundance Bacterioplankton abundance at M33 and N12 fluctuated little over the year around the mean values with no significant seasonal trend. On average, abundance in M33 (0.51 ± 0.02  106 cell ml 1) was significantly lower than in N12 (0.74 ± 0.02  106 cell ml 1,

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Maximum / minimum between successive samplings

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4

P < 0.001, Fig. 6C and D). The percentage of the most active bacteria (High Nucleic Acid content) did not exhibit a clear trend over the year with respective means of 55 ± 2% and 63 ± 2% at stations M33 and N12, respectively (not shown). In contrast to that observed for Chl.a, we observed little daily variation of bacterioplankton abundance at N12, with an average afternoon/morning ratio ± SE of 1.12 ± 0.09 and a ratio of 1.34 ± 0.08 between successive days (Fig. 4). Similarly, bacterial production varied little over the day (average afternoon/morning ratio ± SE = 1.12 ± 0.09, Fig. 7) and daily mean bacterial production varied by 1.34 ± 0.08 between successive days (Fig. 4).

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Fig. 5. (A) Chl.a, (B) bacterial abundance, (C) bacterial production, (D) NH4, (E) NO3 + NO2 and (F) SRP concentrations during a diel cycle at station M33, June 2003. Black lines represent polynomial fits. Bars are SE for duplicates analyses except for ammonium which was determined in triplicates. Closed symbols represent points excluded from the fits.

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Fig. 6. Nutrient concentrations and biological variables at stations M33 (Left) and N12 (Right). (A, B) DIN/SRP ratios. Symbols indicate probable factor limiting phytoplankton growth according to Justic et al. (1995), (s) P limitation (Si:SRP > 22, DIN:SRP > 22 and SRP < 0.1 lM), (d) N limitation (DIN:SRP < 10, Si:DIN > 1 and DIN < 1 lM), (d) neither N, P or Si, dotted lines indicate N/P = 16; (C, D) chlorophyll a (open symbols), bacterial abundance (closed symbols); (E, F) primary (closed symbols) and bacterial (open symbols) production; (G, H) ratios of bacterial to primary production.

compared to the remainder of the year (5.6 ± 0.6 mgC m 3 d 1). Similar to Chl.a, maximum values of March–April 2003 (16.7 ± 2.0 mgC m 3 d 1) were higher than those measured in April

2002. BP displayed the highest values between January and February (4.4 ± 1.2 mgC m 3 d 1) compared to the remainder of the year (1.1 ± 0.1 mgC m 3 d 1).

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Fig. 7. Bacterial production (closed symbols) and Chl.a (open symbols) at station N12 between 11/02/04 and 17/02/04. Bars represent SE.

At station N12, PP showed maximal values in April–May 2002 (71.4 ± 2.1 mgC m 3 d 1), December–January (67.5 ± 8.0 mgC m 3 d 1) and again in March–April 2003 (81.9 ± 15.9 mgC m 3 d 1). BP was highest in December–January (34.0 ± 2.2 mgC m 3 d 1) and March 2003 (33.9 ± 6.3 mgC m 3 d 1) compared to the remaining of the year (11.2 ± 0.8 mgC m 3 d 1). Both BP and PP were significantly higher (Student’s t-test, P < 0.001) throughout the year at N12 than at M33. Interestingly, the variation between successive samples was generally higher at M33 than N12 (Fig. 4). The <2 lm size class of Chl.a contributed to 81 ± 2% of total PP throughout the year at M33 with only minor contributions for the 2–10 lm (11 ± 1%) and >10 lm (8 ± 1%) fractions. This is in contrast to the mesotrophic site, N12 where the mean contributions of each fraction to total PP were relatively similar for the three size fractions: <2 lm (39 ± 3%), 2–10 lm (28 ± 3%) and >10 lm (32 ± 2%).

4. Discussion Seasonal variations of phytoplankton and bacterioplankton biomass and production are generally low in coral reef lagoons (Burford et al., 1995; Furnas and Mitchell, 1986; Torréton and Dufour, 1996) and detecting seasonal trends may be prevented by short term variations due to meteorological forcing like sediment resuspension (Muslim and Jones, 2003; Walker, 1981a) or marine intrusions (Furnas and Mitchell, 1986; Gast et al., 1999). Moreover, neglecting short term variations may lead to erroneous mass balances. For example, ignoring diurnal variations in grazing activity would severely underestimate the contribution of cyanobacteria to microbial carbon flux based on daytime measurements (Tsai et al., 2005), and undersampling bursts of primary production may overestimate the respiration/production ratio in the open ocean (Williams et al., 2004). Finally, short term consequences of paroxystic events, like an increase in phytoplankton growth rate, can represent a significant contribution on an annual basis in coastal systems (Crosbie and Furnas, 2001; Delesalle et al., 1993). The southwest (SW) lagoon of New Caledonia is a semi-enclosed system, surrounded by oligotrophic oceanic water, that is connected to the ocean by narrow passes through the reef. Since the circulation is controlled by tides and winds (Douillet et al., 2001), local flushing rates of the lagoon by surrounding oceanic waters are highly spatially variable (Jouon et al., 2006), and the spatial distributions of some nutrients and planktonic variables have been shown to be linked to local residence times of water masses (Bujan et al., 2000; Pinazo et al., 2004; Torréton et al., 2007). Nevertheless, little is known about how these variables change at different temporal scales in this pelagic ecosystem. Here we simultaneously compare the range of variations of nutrient, biomass and production of phytoplankton and bacteria at short

(hourly) and long (weekly) time frames. This approach allows us to determine whether the variability in autotrophic and heterotrophic biomass and production can be explained by the variability of environmental factors such as wind which exerts a strong influence on water circulation (Douillet et al., 2001). In this study, we sampled at two sites of different trophic status: one representative of the main oligotrophic part of the lagoon, and one in a bay subject to lower rates of oceanic flushing under prevailing wind conditions (Jouon et al., 2006) and significant anthropogenic influence. The two stations showed similar patterns of temporal variation at the different scales examined. Pooling the ranges of variation of nutrients, biomass and production at both sites produced a synoptic view of the relative range of variability for each parameter (Fig. 8). Biomass of both phytoplankton (Chl.a) and bacteria (cell counts) fluctuated little week to week (1.3-fold) with Chl.a showing the most significant diurnal variations. In contrast, nutrients varied over a larger range and were 3.1 times higher in April– May than in November. In parallel with the variability in nutrients and Chl.a, production rates also varied by up to a factor of 2.5 over the year studied. This amplitude of variation for Chl.a and the periods of maxima are similar to those observed in this ecosystem by Le Borgne et al. (2010) and Fichez et al. (2010) who examined a time step of 1 week and 1 month, respectively. The relative similarity in the range of weekly and of hourly scales contrasts with that observed in temperate systems where seasonal trends are large compared to variations on the daily or hourly timescale (CalvoDiaz and Moran, 2006; Pinhassi et al., 2006). 4.1. Hydrodynamics It is well known that the average temperature and sun hours vary to a smaller degree in tropical latitudes than in higher, more temperate latitudes. However, in tropical ecosystems, rapid changes in meteorological variables can occur, thus inducing short term fluctuations in biological processes. In the SW New Caledonian lagoon, Douillet et al. (2001) showed that the semi-diurnal tide and, more importantly, wind-induced advection were the two main factors driving water currents. In particular, the southeasterly trade winds (average direction 110°) that prevail throughout most of the year induce a rapid renewal of lagoon water by oceanic water. In order to analyse the relationship with water column variables, an index of wind stress was computed using the square of wind speed projected on the 110° axis, and different time lags were tested. We did not observe any significant correlation between wind stress (data from the Faubourg Blanchot meteorological station) and the examined variables at station N12. Conversely,

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Fig. 8. Median variation at the hourly, weekly and annual scales. Nutrients: DIN, SRP, Si; biomass: chlorophyll a and bacterial abundance; production: primary and bacterial production. Bars are SE. Hourly: maximum daily variations (maximum/ minimum); weekly: variations between samples (1–2 weeks, see Table 2); annual: annual variations.

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at station M33, BP, and BP/PP were negatively correlated with this index of wind stress (data from Maître Is. meteorological station), and the best correlation was observed with wind stress averaged over the 5 days preceding sampling (Spearman Rank correlations (Rs) 0.44 and 0.49, respectively, both significant at P < 0.01), with differences in significance being moderate between 4 (Rs 0.40 and 0.45) and 8 days ( 0.38, and 0.46). Although these correlations do not demonstrate a causal relationship, the statistical relationship is in agreement with the negative correlation between BP and along-shore wind observed during realistic simulations (Faure et al., 2010). Moreover, model studies (Pinazo et al., 2004; Faure et al., 2010) suggest that hydrodynamically driven dispersion is sufficient to maintain lagoon oligotrophic conditions under Trade Wind forcing. The difference between BP vs wind relationships at the two stations is in agreement with the much shorter turnover time of water at M33 compared to N12 under prevailing Trade Wind conditions. An index of this turnover time is given by the ‘e-flushing time’, a synthetic parameter indicating the time required for a tracer mass at a station (control volume) to be reduced e-fold by waters coming from outside the lagoon (Jouon et al., 2006). E-flushing times were computed under a constant moderate wind, uniform over the study area, corresponding to normal SE trade wind (110°, 8 m s 1 the most frequent and long-lasting one in this area, Jouon et al., 2006). Keeping in mind that a uniform wind forcing is an approximation in the SW lagoon (Lefèvre et al., 2010), e-flushing time computed under this wind regime is much shorter for M33 (0.5 day) than for N12 (12.5 days). Furthermore, in a recent study from this area, the distribution of Chl.a and bacterial biomass was shown to be correlated with the local e-flushing time at a series of stations in the South-West Lagoon, further demonstrating the importance of meteorological processes in controlling biological responses in this ecosystem (Torréton et al., 2007). Generally, we did not observe significant correlations between nutrients and precipitation immediately prior to sampling, except for silicates and nitrates at station N12. Positive significant correlations were observed between nutrients and the 2 day cumulative precipitation prior to sampling. Maximum correlations were observed between nutrients and the cumulative precipitation from the 4 days immediately prior to morning sampling (Fig. 9). Although all rain events are not associated with higher nitrate concentrations, this correlation underlines the importance of local meteorological events on nutrient availability at the most coastal station. Le Borgne et al. (2010) also showed that small nutrient pulses could be associated within rain events at the mouth of Sainte-Marie Bay. However, it is also probable that the higher stimulation that we observed at station N12 is also likely due to its vicinity to urban sewage at the end of the bay and the increase of flow associated with precipitation events. It is worth noticing that we were unable to show any significant effect of the cyclone that hit the sampling area on 14 March 2003. However, our first sample after the cyclone was collected on 25 March 2003. Interestingly, a 5–6-fold increase of Chl.a was observable 3 days after the cyclone in a range of stations in the SW lagoon (Neveux et al. 2009) similar to the changes in structure recently reported for a lake subject to tropical typhoons (Jones et al., 2008). This shows that, whatever the changes in nutrients, biomass and production that might have occurred in the water column the days following the cyclone, return to average conditions was achieved within 11 days at both stations. This is in agreement with scenarios simulating floods in the SW lagoon showing that enrichments are short enough so that return to average conditions may be observed within 10 days, under trade wind conditions (Faure, 2006). Of the five 24 h cycles studied, three were characterized by stable meteorological conditions with constant wind and no rain. During these three cycles, Chl.a and nutrient concentrations showed a

consistent diel pattern (example in Fig. 5), similar to what has been observed in the Mediterranean sea (Bettarel et al., 2002). These variations are due to a combination of (1) the balance between phytoplankton growth and mortality, (2) cellular physiological adaptations to environmental modifications (e.g. photoacclimatation), and (3) the effects of external physical factors such as vertical mixing, advection and sinking (Denman and Gargett, 1983; Serra et al., 2003). The slight increase during daylight hours and the subsequent decrease of Chl.a (Fig. 5) can probably be partially explained by a night time maximum grazing by vertically migrating mesozooplankton or even diel variations of grazing by protists (Christaki et al., 2002; Neveux et al., 2003; Tsai et al., 2005). BP increase during day time is consistent with other diel studies in this system (Pringault et al., 2009) and in other temperate systems (Gasol et al., 1998; Winter et al., 2004) and may result from a close coupling between phytoplankton exudation and bacterial growth as has been proposed for this system (Rochelle-Newall et al., 2008). In this study, BP was determined from 3H-TdR incorporation in dark conditions. Since several studies have reported that both UV and PAR illumination may influence bacterial production rates (e.g. Conan et al., 2008), the validity of the diel trends observed may be questioned. Maximum daily BP values were observed around 1800 when light, and hence UV is considerably reduced (Conan et al., 2008). Therefore, it is probable that any possible overestimation of daylight BP due to dark incubations would further re-enforce the trends observed. In contrast to BP, the decrease in nutrient concentration during daylight hours can be explained by phytoplankton uptake. While we still lack explanation for NO3+2 night time increase, night time increases of PO4 and NH4 can be the result of night time grazing and excretion by zooplankton and protists (Andersson et al., 1985; Smith and Whitledge, 1977; Dolan 1997; Titelman et al., 2008). Significant and consistent nutrient variations over 24 h cycles suggest possible changes of nutrient limitation at the same scale as already reported (Kuipers et al., 2000; Shiah, 1999). However, using nutrient ratios and threshold concentrations as an index of the potentially limiting factor (Dortch and Whitledge, 1992; Justic et al., 1995) we found that nitrogen was the potentially limiting factor and that this did not vary during the diurnal cycles followed during this study (not shown). The atypical diel cycles of 11 April 2002 are likely related to the effects of external physical factors. Wind forcing increased strongly during the first 12 h and then decreased during the second 12 h before remaining nearly constant the next 24 h. The increased bacterial activity and phytoplankton biomass could have been due to wind induced vertical mixing of the water column that led to sediment resuspension, or advection. These results suggest that, at the two stations studied, when meteorological conditions remain stable, biological processes show moderate and consistent daily variations and that phytoplankton biomass and bacterioplankton biomass and activity determined from a single sampling can be considered representative of the daily value within 20%. This amplitude of variation was assessed between April and June, and could change according to seasonal characteristics like irradiance. Similar to that observed for hourly variability, the day-to-day variability of phytoplankton biomass is small under stable meteorological conditions. During our survey at station N12, the average afternoon:morning ratio is 1.6 which is in agreement with diurnal trends of Chl.a. Bacterial production was slightly more variable (1.3-fold between consecutive days) but these variations were moderate compared to sampling variations along the annual survey (Figs. 4 and 6) where meteorological factors varied more widely. The variation between consecutive samples during the annual survey was similar at the two stations. In general, nutrients

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varied 1.3–5.1-fold (median 2.7), biomass varied 1.2–1.4-fold (median 1.3), and production varied 1.5–2.5-fold (median 1.7). Such variations at the weekly scale have also been observed for Chl.a during a 4.5-year long survey in the SW lagoon (Le Borgne et al., 2010). Similar large variations of phytoplankton and bacterioplankton biomass and production were recorded within 1 month in a bay under anthropogenic influence of the SW lagoon of New Caledonia (Renaud et al., 2005), and Tenório et al. (2005) have shown important day-to-day variations of phytoplankton biomass and community composition in relation to terrigeneous inputs in a deep cove on the south-eastern coast of New Caledonia. Finally, outputs from 53 days 3D realistic simulations using a model coupling biogeochemical fluxes with hydrodynamic processes also show variations of the same range for similar time frames in the SW lagoon (Faure et al. 2010). Although the two stations showed similar patterns of annual variation, the variations were more pronounced at the mesotrophic station N12 than at the oligotrophic station situated in the lagoon channel. Station M33 has much lower nutrient, abundance and production values than N12 (Fig. 10) and nutrient concentrations were often low compared to analytical precision at this site. Moreover, the two sampling stations are subject to different hydrodynamics. As mentioned above, during the most common wind regime (SE Trade Winds) flushing by oceanic waters was more important at station M33 and accordingly, some of the biological variables appeared to be negatively correlated with wind stress. Thus it is likely that station M33 is more subject to more energetic hydrodynamics than is N12. 4.2. Trophic balance The amplitude of variation of BP and PP over this 1-year study (Fig. 8) is similar to the 3-fold range for benthic respiration and production in the same system (Clavier and Garrigue, 1999). A 1-year survey is of course insufficient to precisely assess the seasonality of BP and PP in such an ecosystem characterized by significant inter-annual variations. However, Le Borgne et al. (2010) report that inter-annual variability was less marked than seasonal variability for Chl.a. In this study, Chl.a followed roughly the same temporal pattern the following year with maximal values being slightly higher for M33 (1.4-fold) and lower for N12 (0.9-fold).

Similar to the temporal trends observed during this study, Fichez et al. (2010) observed a Chl.a maximum between April and June during a 1-year monthly survey in a range of stations. They also reported another maximum in January in bay stations like in the present study. Finally, an analysis of 4.5 years Chl.a data also showed a maximum between mid-May and June in a coastal station of the South-West lagoon (Le Borgne et al., 2010). Hence, our data set is in agreement with the few studies so far investigating water column seasonality in the SW lagoon. As expected, the weak amplitude of intra-annual variation over the year is in contrast with observations in more temperate ecosystems where nutrients, and biomass and production of the first trophic levels of the planktonic foodwebs, vary typically 10–20-fold over the year (Paoli et al., 2006; Pinhassi et al., 2006; Umani and Beran, 2003). Moreover, the range is in agreement with low or insignificant seasonal variations observed in other low latitude coral reef ecosystems (Charpy, 1996; Furnas and Mitchell, 1986; Torréton and Dufour, 1996). We did not observe any clear temporal separation between PP and BP, however, we did observe significant short term fluctuations of the BP/PP ratio (Fig. 6G and H). Although the BP/PP ratio is only a proxy of the metabolic balance (primary production/respiration or PP/R), it is interesting to examine the consequences of short term fluctuations on carbon budgeting on an annual basis in the water column of this study site. In the sediments, Clavier and Garrigue (1999) computed a gross primary production/respiration ratio (GPP/R) of 0.88 and concluded that the SW lagoon of New Caledonia was net heterotrophic. An estimate of the sampling effort necessary in the water column at a single station to resolve such a weak difference, for example 15%, in the BP/PP ratio can be roughly obtained by taking into account the variability of this ratio. Over the 38 samples collected at each station during this 1year survey, BP/PP averaged 0.21 and 0.34 at stations M33 and N12, respectively, and their respective 95% confidence limits represent 24% and 19% of these ratios. Based on these data, determining 95% confidence limits for BP/PP ratio that were equal to 15% of the mean would require 56 samples at station N12 and 100 samples at station M33. If we postulate that temporal variations in R/PP ratios are comparable to those from BP/PP ratios in the water column, the sampling frequency necessary to obtain a 15% difference between PP and respiration would represent an unrealistic effort.

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An index of trophic balance can be obtained by comparing the respective variability of heterotrophic and autotrophic activities. Indeed, in the open ocean, respiration appears more constant in time and space than primary production (Aristegui and Harrison, 2002; Williams et al., 2004). Williams et al. (2004) reasoned that, since the primary metabolic event in the open sea is autotrophic production, and as there is evidence of intermittent bursts of PP (Karl et al., 2003), one can then expect a more constant heterotrophic production than autotrophic production due to the various pathways through which organic matter circulates from autotrophic to heterotrophic components of the foodweb. Under sampling, hence missing pulsed primary production events, would give an explanation for the paradoxically higher respiration than production in oligotrophic areas of the ocean. Discussing the PP/R ratio of the ocean is, of course, beyond the scope of this study, however, it is interesting to note that, contrary to Williams et al. (2004) at station Aloha and Aristegui and Harrison (2002) in the North Atlantic, we observed that variation of BP (an index of heterotrophic activity) exhibited higher temporal variations than those of particulate primary production. For instance, coefficients of variations are 68% and 99% at station M33 and 52% and 67% at station N12 for PP and BP, respectively. Correspondingly, variations between successive samples are more important for BP than for PP (Fig. 4). The reproducibility of BP measurements is such (4% variation between duplicates on average) that it is unlikely that this difference is due solely to a methodological artefact. It is probable that the variations in PP/BP are driven primarily by short term variations in BP rather than by variation in PP. Indeed, we observed significant log–log correlations between PP/BP and BP (log(PP/

BP) = 0.92  log(BP) + 0.82, R2 = 0.57, P < 0.001; log(PP/ BP) = 0.86  log(BP) + 1.45, R2 = 0.45, P < 0.001; and log(PP/ BP) = 0.53  log(BP) + 0.95, R2 = 0.51, P < 0.001 for M33, N12 and the whole data set, respectively) and not between PP/BP and PP (NS for the 3 data sets). Aristegui and Harrison (2002) stated that the close correlation between PP/R and PP, and the lack of correlation between PP/R and R, suggests that changes in PP but not in R control the trophic status of the system. Similarly, and keeping in mind the risk of autocorrelation, our data indicate that heterotrophic activity (i.e. bacterial production) and not primary production is the major determinant of trophic status in the SW lagoon of New Caledonia. The close relationship between BP and PP (P < 0.001, see above) observed in the lagoon, interpreted as a reliance of bacterioplankton on DOM production by phytoplankton in closed system, can also be interpreted as a dependency of primary producers on remineralization by bacterioplankton of allochtonous organic nutrients. Therefore, the lower temporal variability of PP compared to BP could be due to a smoothing of the short term variations of remineralization activities via the variety of regeneration pathways of allochtonous organic nutrients. This would suggest that the water column of the SW lagoon is net heterotrophic as was concluded by Clavier and Garrigue (1999) for the sediments. Acknowledgements This work was supported by the Institut Français de Recherche pour le Développement (IRD), and grants from the Programme National Environnement Côtier (PNEC) and the ZoNéCo programme. We express our gratitude to J. Bargibant, S. Tereua and A. Lapetite

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