domain: sdu sdv

text:
Emilie Houliez
email: emilie.houliez@outlook.fr

Sebastien Lefebvre

Fabrice Lizon

Francois G Schmitt

Houliez Emilie

Lizon Fabrice

François G Schmitt

Rapid light curves (RLC) or non-sequential steady-state light curves (N-SSLC): which fluorescence-based light response curve methodology robustly characterizes phytoplankton photosynthetic activity and acclimation status?

    Rapid light curves (RLC) or non-sequential steady-state light curves (N-SSLC): which fluorescence-based light response curve methodology robustly characterizes phytoplankton photosynthetic activity and acclimation status?

Introduction

Within their natural environment, phytoplankton species are exposed to highly variable conditions including strong fluctuations in the degree of water mixing, light intensity, nutrients availability and temperature [START_REF] Macintyre | The effect of water motion on short-term rates of photosynthesis by marine phytoplankton[END_REF]. These never-ending changes, operating at different scales in space and time, can be considerably stressful for phytoplankton and this influences their growth rate, photosynthetic activity and survival [START_REF] Geider | A dynamic regulatory model of phytoplanktonic acclimation to light, nutrients, and temperature[END_REF].

In order to maintain optimal growth and photosynthetic performances under such variable conditions, phytoplankton have developed different mechanisms including photoacclimation which allow them to avoid damaging energy imbalance within the photosynthetic apparatus [START_REF] Brunet | Pigments and photoacclimation processes[END_REF]. Understanding these processes of acclimation and their controlling factors is a critical issue in phytoplankton ecology and this requires accurate measurement methodology.

The so-called photosynthesis-light response (PE) curves, in which photosynthetic rates are plotted against a range of irradiance intensities, are one of the most widely used methods to characterize phytoplankton photosynthetic performances and acclimation status [START_REF] Henley | Measurement and interpretation of photosynthetic light-response curves in algae in the context of photoinhibition and diel changes Journal of Phycology 29[END_REF][START_REF] Macintyre | Photoacclimatation of photosynthesis irradiance response curves and photosynthetic pigments in microalgae and cyanobacteria[END_REF][START_REF] Sakshaug | Parameters of photosynthesis: Definitions, theory and interpretation of results[END_REF]. PE curves were presented in literature as early as 1930's (e.g. Baly 1935) but their measurement became popular with the development of the traditional photosynthesis measurement techniques based on C isotopeincorporation [START_REF] Hama | Measurement of photosynthetic production of a marine phytoplankton population using a stable 13 C isotope[END_REF][START_REF] Nielsen | The Use of Radio-active Carbon (C 14 ) for Measuring Organic Production in the Sea[END_REF] or oxygen evolution [START_REF] Gaarder | Production of plankton in the Oslo Fjord Rapports et Procès-Verbaux des Réunions Conseil Permanent International pour l[END_REF][START_REF] Montford | Measuring dissolved oxygen as an indicator of primary productivity[END_REF]. Using these techniques, a PE curve is obtained either by a sequential measurement of oxygen exchange rates on a single sample exposed to several steps of different irradiances or by simultaneous measurements of 14 C incorporation on several subsamples (drawn from a single phytoplankton sample) and each exposed to constant irradiances of different intensity [START_REF] Macintyre | Photoacclimatation of photosynthesis irradiance response curves and photosynthetic pigments in microalgae and cyanobacteria[END_REF]. Even though these traditional techniques are still widely used in phytoplankton ecology, they are associated with several methodological drawbacks reducing their practicality such as the requirement of incubation time that limits the resolution at which measurements can be made, the low sensitivity and concentration steps of oximetry based-methods, and the so-called bottle effect [START_REF] Lefebvre | Comparison between fluorimetry and oximetry techniques to measure photosynthesis in the diatom Skeletonema costatum cultivated under simulated seasonal conditions[END_REF]).

Consequently, these last few years, there was a great deal of interest in alternative optical techniques based on active chlorophyll fluorescence because they enable to measure photosynthesis at a higher spatiotemporal resolution and free of the constraints associated with the traditional techniques [START_REF] Kromkamp | The use of variable fluorescence measurements in aquatic ecosystems: differences between multiple and single turnover measuring protocols and suggested terminology[END_REF][START_REF] Suggett | Estimating Aquatic Productivity from Active Fluorescence Measurements[END_REF].

Fluorescence-based techniques, including the Pulse Amplitude Modulated (PAM) [START_REF] Schreiber | Pulse-Amplitude-Modulation (PAM) fluorometry and saturation pulse method : an overview[END_REF]) and Fast Repetition Rate Fluorometry (FRRF) [START_REF] Kolber | Measurements of variable chlorophyll fluorescence using fast repetition rate techniques: Defining methodology and experimental protocols[END_REF]), measure the rate at which electrons flow from water through photosystems II to NADPH and other electron acceptors [START_REF] Lawrenz | Predicting the Electron Requirement for Carbon Fixation in Seas and Oceans[END_REF]. A PE curve built using these techniques measures thus the electron transport rate (ETR) under a range of irradiance levels and is called ETR vs. E curve.

The growing interest for these techniques introduced at the same time new methodologies to construct PE curves and raised new questions about the best way to measure phytoplankton photosynthesis and acclimation status. Steady-state light curves (SSLC) were the first fluorescence-based methodology employed because they are comparable to the traditional PE curves based on C isotopeincorporation or oxygen evolution. SSLC measure the photosynthesis rate at steady-state i.e.

with light steps long enough to allow the stabilisation of photosynthetic processes under each irradiance level. As a consequence, the transient effects of recent light history, defining the short-term acclimation status before the start of SSLC, are attenuated (even eliminated) during their construction [START_REF] Cruz | Relationship of rapid light curves of variable fluorescence to photoacclimation and non-photochemical quenching in a benthic diatom[END_REF]. SSLC are thus used to study the long-term acclimation status (hours to days) and the potential photosynthetic performances of autotrophic organisms [START_REF] Cruz | Relationship of rapid light curves of variable fluorescence to photoacclimation and non-photochemical quenching in a benthic diatom[END_REF][START_REF] Perkins | The Application of Variable Chlorophyll Fluorescence to Microphytobenthic Biofilms[END_REF][START_REF] Serôdio | Rapid light-response curves of chlorophyll fluorescence in microalgae: Relationship to steady-state light curves and nonphotochemical quenching in benthic diatom-dominated assemblages[END_REF].

SSLC can be constructed following two methodologies. The non sequential steady-state light curves (N-SSLC) are built by applying each light step on different subsamples [START_REF] Henley | Measurement and interpretation of photosynthetic light-response curves in algae in the context of photoinhibition and diel changes Journal of Phycology 29[END_REF][START_REF] Perkins | Light response curve methodology and possible implications in the application of chlorophyll fluorescence to benthic diatoms[END_REF]. Measurements are independent from each other and the photosynthetic activity measured at each light step only depends on the irradiance to which the sample is exposed at the moment of measurement. By opposition, the sequential steadystate light curves (S-SSLC) are built by applying all the light steps on the same sample.

Measurements lost their independency and the photosynthetic activity measured at each light step depends not only on the irradiance to which the sample is exposed at the moment of measurement but also on the irradiance experienced (and accumulated) during the previous step(s) (recent light history) [START_REF] Frankenbach | One pulse, one light curve: Fast characterization of the light response of microphytobenthos biofilms using chlorophyll fluorescence[END_REF][START_REF] Henley | Measurement and interpretation of photosynthetic light-response curves in algae in the context of photoinhibition and diel changes Journal of Phycology 29[END_REF]. Both protocols are time-consuming as they require several minutes to a few hours to be completed. This is a constraint for field studies because: 1) the time required to complete the protocol makes replication impossible and 2) investigation of temporal and spatial variations in photosynthetic activity may be jeopardized by the time spent by users to obtain a single set of measurements [START_REF] Perkins | The Application of Variable Chlorophyll Fluorescence to Microphytobenthic Biofilms[END_REF]. This is particularly true in highly variable systems for which a high spatio-temporal resolution is required to completely capture changes in photosynthetic activity in response to rapidly fluctuating environmental conditions. Another limitation of these methods is that sample's acclimation status is strongly modified during the curve building while the goal of SSLC measurements is normally to characterize the acclimation status developed in situ.

To limit these acclimation processes occurring during the curve building, another methodology called Rapid Light Curves (RLC) was introduced [START_REF] Schreiber | Assessment of photosynthetic performance of Prochloron in Lissoclinum patella in hospite by chlorophyll fluorescence measurements[END_REF]White and Critchley 1999). RLC are built with short light steps (≤ 30 s) and preserve the acclimation state attained immediately prior to the start of the curve measurement. They allow thus to describe the effective photosynthetic capacities and short-term acclimation status [START_REF] Henley | Measurement and interpretation of photosynthetic light-response curves in algae in the context of photoinhibition and diel changes Journal of Phycology 29[END_REF][START_REF] Perkins | Light response curve methodology and possible implications in the application of chlorophyll fluorescence to benthic diatoms[END_REF]Serôdio et al. 2005b;[START_REF] Serôdio | Rapid light-response curves of chlorophyll fluorescence in microalgae: Relationship to steady-state light curves and nonphotochemical quenching in benthic diatom-dominated assemblages[END_REF]. Because of the short duration of their light steps, RLC can be completed within 80-240 s (depending on the number and duration of light steps) which shortens drastically the time required for their measurement and represents a considerable operational advantage during field works [START_REF] Cruz | Relationship of rapid light curves of variable fluorescence to photoacclimation and non-photochemical quenching in a benthic diatom[END_REF][START_REF] Perkins | The Application of Variable Chlorophyll Fluorescence to Microphytobenthic Biofilms[END_REF].

RLC were used to characterize the effective photosynthetic activity and short-term acclimation status of different autotrophic organisms including macroalgae, ice microalgae, corals and seagrasses (Serôdio et al. 2005b and references therein) and were widely applied on microphytobenthic assemblages (e.g. [START_REF] Cruz | Relationship of rapid light curves of variable fluorescence to photoacclimation and non-photochemical quenching in a benthic diatom[END_REF][START_REF] Henley | Measurement and interpretation of photosynthetic light-response curves in algae in the context of photoinhibition and diel changes Journal of Phycology 29[END_REF][START_REF] Lefebvre | Duration of rapid light curves for determining the photosynthetic activity of microphytobenthos biofilm in situ[END_REF][START_REF] Perkins | Light response curve methodology and possible implications in the application of chlorophyll fluorescence to benthic diatoms[END_REF][START_REF] Serôdio | Photosynthetic activity, photoprotection and photoinhibition in intertidal microphytobenthos as studied in situ using variable chlorophyll fluorescence[END_REF]Serôdio et al. 2005b;[START_REF] Serôdio | Rapid light-response curves of chlorophyll fluorescence in microalgae: Relationship to steady-state light curves and nonphotochemical quenching in benthic diatom-dominated assemblages[END_REF].

Several methodological studies were even conducted to examine the usefulness of RLC and improve the measurement protocol to assess microphytobenthos photosynthetic activity (Lefebvre et al. 2011 and references therein).

However, despite the potential advantages offered by this methodology, RLC remain seldom applied for studying phytoplankton photosynthetic activity. This is probably because RLC raise some questions about the physiological interpretation of the resulting photosynthetic parameters, particularly in comparison with the other methodologies [START_REF] Henley | Measurement and interpretation of photosynthetic light-response curves in algae in the context of photoinhibition and diel changes Journal of Phycology 29[END_REF]. Indeed even though RLC are less intruvise than SSLC, this does not mean they are completely free of any acclimation processes occuring during the curve building. It was shown that light steps duration and order (i.e. increasing or decreasing light steps) influence the photosynthetic parameters extracted from RLC and involve physiological processes that can be different from the ones operating during the SSLC building [START_REF] Henley | Measurement and interpretation of photosynthetic light-response curves in algae in the context of photoinhibition and diel changes Journal of Phycology 29[END_REF][START_REF] Lefebvre | Duration of rapid light curves for determining the photosynthetic activity of microphytobenthos biofilm in situ[END_REF][START_REF] Perkins | Light response curve methodology and possible implications in the application of chlorophyll fluorescence to benthic diatoms[END_REF]). To our knowledge, no previous study compared phytoplankton photosynthetic parameters extracted from RLC and S-SSLC or N-SSLC.

Consequently, for the users of fluorescence-based techniques who wish to study phytoplankton photosynthesis it is still difficult to know which methodology they should employ to accurately characterize phytoplankton photosynthetic performances and acclimation status. Ideally the protocol employed should not take too much time to be completed, should allow for replication and should estimate properly the short-and long-term acclimation status in one measurement.

This study aimed: 1) to compare RLC and N-SSLC in their efficiency to characterize in situ dynamics of phytoplankton photosynthetic activity at different time scales and 2) to study the relationships between the photosynthetic parameters extracted from RLC and N-SSLC measured under different environmental conditions in order to define the possibility to use RLC to predict N-SSLC parameters and thus characterize the long-term acclimation status. Because RLC use light steps too short to completely alter the acclimation status formed just before the curve measurement, in opposition to N-SSLC, we hypothesized that RLC can detect rapid changes in photosynthetic activity that would have been passed unnoticed if N-SSLC were measured. We also hypothesized that relationships between the photosynthetic parameters extracted from RLC and N-SSLC can be different according to the time scale considered.

Samplings were carried out in the coastal waters of Wimereux at two time scales (daily and annual). Photosynthetic activity was measured on natural phytoplankton communities using the PAM fluorometry. ETR vs. E curves were constructed using RLC and N-SSLC in order to compare the resulting photosynthetic parameters.

Materials and methods

Study area and sampling

The study was completed in the coastal waters of Wimereux (50°45'57.42''N, 1°35'55.17"E, depth range: 1-4 m) situated in the English Channel; a well-mixed macrotidal ecosystem (Fig. 1). Further information on this study area are available in Houliez et al. (2013b). Samples were collected in surface waters using a bucket from the foreshore next to our institute using two different protocols according to the time scale considered. At daily scale, samples were taken every 1.45 h. from sunrise to sunset in winter (January 28 th 2010), with an Alliance Integral Futura Autoanalyser II according to the method of [START_REF] Aminot | Dosage automatique des nutriments dans les eaux marines vol 1. Editions de l'Ifremer. pp. 188[END_REF]. Incident photosynthetically active radiation (PAR in µmol quanta m -2 s -1 ) was measured continuously (1 measurement per minute) with a 4 π spherical quantum sensor (ultra-miniature MDS-MkV/L, JFE Alec Electronics co. LTD., Kobe, Japan).

The composition of phytoplankton community was investigated using a submersible spectral fluorometer (the FluoroProbe, bbe-Moldaenke, Kiel, Germany) after the recalibration of its reference fingerprints (further details are provided in [START_REF] Houliez | Spectral fluorometric characterization of Haptophyte dynamics using the FluoroProbe: an application in the eastern English Channel for monitoring Phaeocystis globosa[END_REF]. This recalibration allows the discrimination of four spectral algal groups in mixed populations: brown algae (diatoms + dinoflagellates), cyanobacteria (cyanobacteria with phycocyanin), the Haptophyte Phaeocystis globosa and "Cryptophyta" (Cryptophyta, Rhodophyta, cyanobacteria with phycoerythrin). Measurements on phytoplankton samples were made using the 25 mL cuvette of the FluoroProbe.

Photosynthetic activity

Photosynthetic activity was measured by Pulse Amplitude Modulated (PAM) fluorometry using a Phyto-PAM fluorometer (Heinz Walz GmbH, Effeltrich, Germany). For a detailed description of the Phyto-PAM, see [START_REF] Kolbowski | Computer-controlled phytoplankton analyser based on a 4wavelengths PAM chlorophyll fluorometer[END_REF] andSchreiber (1998). Measurements were made on suspension using the quartz cuvette of the Phyto-PAM with samples of 2.5 mL. Before the measurements of ETR vs. E curves, samples were darkacclimated during 15 minutes at sampling temperature.

RLC were constructed by exposing samples for 10 s to 21 sequential increasing light steps (14,41,53,80,94,145,175,206,236,295,323,352,409,464,521,573,626,676,726,775 and 867 µmol photons m -2 s -1 ). RLC measurements were made in triplicate. N-SSLC were constructed using 14 subsamples extracted from a dark-acclimated sample maintained in the dark at sampling temperature until the end of the N-SSLC measurement. These 14 subsamples were one after another exposed to a light step of different intensity (14,53,80,94,145,175,236,295,352,464,521,626,726 or 867 µmol photons m -2 s -1 ) for 5 min.

Because of their long duration, N-SSLC were measured without any replication. Intensity of each light step (E) was obtained using the Spherical Micro Quantum Sensor US-SQS (Heinz Walz GmbH, Effeltrich, Germany). The fluorescence terminology follows van Kooten and Snel (1990).

At each light step, the fluorescence levels before and after applying a saturating pulse (200 ms up to 4,000 µmol photons m -2 s -1 at 655 nm) were measured with 4 pulse-modulated measuring lights peaking at 470, 520, 645 and 665 nm. It was preliminary checked that this saturating pulse intensity and duration were appropriate to reach the maximal fluorescence levels (F m or F m ') using the "View Pulse" function of the Phytowin software associated with the Phyto-PAM to examine the fluorescence kinetics during the saturating pulse. The effective quantum yield of photosystem II (ΦPSII also noted ΔF/F m ') was calculated for each measuring wavelength according to [START_REF] Genty | The relationship between the quantum yield of photosynthetic electron transport and quenching of chlorophyll fluorescence[END_REF] :

ΦPSII = ΔF F m ' = (F m ' -F) F m '
where F is the fluorescence level of the light-acclimated sample measured just prior to the saturating pulse and F m ' is the maximum fluorescence emitted by the light-acclimated sample after a saturating pulse.

ΦPSII measured with the measuring light peaking at 470 nm was then selected to calculate the absolute electron transport rate (ETR): ETR = ΦPSII ×E ×0.5 × ā * phy where E (µmol photons m -2 s -1 ) is the actinic irradiance, 0.5 is a multiplication factor because the transport of one electron requires two photons (one per photosystem) [START_REF] Gilbert | Estimation of primary productivity by chlorophyll a in vivo fluorescence in freshwater phytoplankton[END_REF][START_REF] Kromkamp | The use of variable fluorescence measurements in aquatic ecosystems: differences between multiple and single turnover measuring protocols and suggested terminology[END_REF], ā * phy (m² (mg chl a) -1 ) is the spectrally averaged (400-700 nm) chlorophyll a specific absorption coefficient (see below for its measurement). The measuring light peaking at 470 nm was chosen because it was the most appropriate to the English Channel's phytoplankton communities but also because almost all commercially available PAM and FRRF fluorometers are equipped with blue excitation lights. ETR vs. E curves were fitted using the model of Webb et al. (1974) to estimate the maximal light utilization efficiency (α) which corresponds to the initial slope of the curve, the maximum electron transport rate (ETR m ) which is the asymptote of the curve and the light saturation coefficient (E k ) calculated as ETR m /α. As described in [START_REF] Lefebvre | Duration of rapid light curves for determining the photosynthetic activity of microphytobenthos biofilm in situ[END_REF], curve fitting was achieved using the downhill simplex method of the Nelder-Mead model (1965), and standard deviation of parameters was estimated by an asymptotic method. All fittings were tested by analyses of variance (P<0.001), residues being tested for normality and homogeneity of variance, and parameters significance by Student's t-test (P < 0.05). All the curve fitting processes and associated statistics were coded under MATLAB R2010b.

At each light step, the non-photochemical quenching of fluorescence (NPQ) was calculated from the fluorescence levels measured with the measuring light peaking at 470 nm using the equation proposed by Serôdio et al. (2005a):

NPQ= (F m ' m -F m ') F m '
where F m ' m is the maximum F m ' value, higher than F m , that is measured under low actinic irradiance. NPQ vs. E curves were fitted using the model of [START_REF] Serôdio | A model for describing the light response of the nonphotochemical quenching of chlorophyll fluorescence[END_REF] modified to directly extract the physiological parameter "S" corresponding to the slope of the first part of NPQ vs. E curves i.e. the part of the curve where NPQ increases monotonically with irradiance:

NPQ=NPQsat E n ( NPQsat S ) n +E n
where E (µmol photons m -2 s -1 ) is the actinic irradiance, NPQsat is the maximum NPQ value reached at saturation, S is the slope of the first part of the curve and n is the Hill coefficient characterizing the sigmoidicity of the curve. When n < 1, the curve has a saturation-like shape and increases asymptotically toward NPQsat while when n > 1, the curve has a sigmoidal shape. Because, most of our NPQ vs E curves did not reach saturation within the range of irradiances tested, NPQ max , which corresponds to the highest NPQ value measured during the ETR vs. E curve, was also extracted.

Chlorophyll a and mean chl a-specific absorption coefficients

Chlorophyll a (chl a) concentrations were determined by filtering known volumes of water samples through Whatman 47 mm GF/F glass-fibre filters. The filters were stored at -80°C and subsequently extracted in 90% acetone. Chl a concentration was evaluated by fluorometry using a Turner Designs fluorometer (Model 10-AU) calibrated using known concentrations of commercially purified chl a (Sigma). The fluorescence was measured before and after acidification with HCl [START_REF] Aminot | Dosage automatique des nutriments dans les eaux marines vol 1. Editions de l'Ifremer. pp. 188[END_REF][START_REF] Lorenzen | A method for continuous measurement of in vivo chlorophyll concentration Deep-Sea Research (Part I[END_REF].

The mean chl a-specific absorption coefficients (ā * phy ) were obtained by measuring the optical density (OD) spectrum of samples filtered on Whatman GF/F filters according to the method of [START_REF] Mitchell | Determination of spectral absorption coefficients of particles, dissolved material and phytoplankton for discrete water samples[END_REF]. The OD spectrum was measured on wet glass-fibre filter attached on a quartz glass plate between 300 and 800 nm with 0.5 nm increments using a dual beam spectrophotometer (UV-2450, Shimadzu). A clean filter wetted with ultra-filtered (0.2 µm) sea water was used as a reference. The OD of the filtered sample was corrected for the optical path length across the filter and the algal deposit on top of it, yielding the OD corresponding to the same sample in suspension, using mean β-correction factors according to [START_REF] Mitchell | Algorithms for determining the absorption coefficient of aquatic particulates using the quantitative filter technique[END_REF]. The average OD between 750 and 800 nm was used to correct for scattering.

The depigmented particle absorption spectrum was obtained after extraction of the pigments in a solution of 98% methanol. The spectral absorption coefficient for phytoplankton pigments, a phy (λ), was calculated by subtracting the depigmented particle absorption spectrum to the absorption coefficient of total filtered particles and was normalized to the chlorophyll a concentration to obtain the chl a-specific absorption: a * phy (λ). Finally, the mean absorption coefficient between 400 and 700 nm, ā * phy in m² (mg chl a) -1 , was calculated.

Statistical analyses

An analysis of similarities (one-way ANOSIM, Clarke and Warwick 1994) was used

to test the significance of differences in phytoplankton communities. The analysis was based on Euclidean similarity matrix and was performed using PRIMER 6 (PRIMER-E Ltd., Plymouth, UK).

Differences in environmental and photosynthetic parameters measured at high and low tide were evaluated using Student t-tests or their non parametric equivalent (the Mann Whitney U test) [START_REF] Scherrer | Chlorophyll fluorescence: New instruments for special applications[END_REF]. Comparisons of RLC and N-SSLC and their derived photosynthetic parameters were performed using the method of [START_REF] Ratkowski | Non linear regression modeling. A unified practical approach[END_REF] for non-linear models.

This method was coded under MATLAB R2010b. Differences between NPQ photosynthetic parameters resulting from RLC and N-SSLC were evaluated using paired Student t-tests.

Pearson's correlation analysis and simple linear regressions were performed to evaluate relationships between the photosynthetic parameters derived from RLC and N-SSLC. Simple linear regression lines were compared to the 1:1 relationship using an analysis of covariance (ANCOVA) [START_REF] Scherrer | Chlorophyll fluorescence: New instruments for special applications[END_REF]. To understand deviations between photosynthetic parameters extracted from RLC and N-SSLC, the ratios ETR m_RLC / ETR m_N-SSLC , α _RLC / α _N-SSLC and E k_RLC / E k_N-SSLC were calculated. Relationships between these ratios and environmental variables (that were scales i.e. centered and reduced) were then quantified using stepwise multiple linear regression analyses. The environmental variables tested were: incident PAR, ), salinity and assemblage composition (in term of chl a concentration by groups and relative proportions of total biomass). Analyses were performed using R (R Core Team 2016). Linear models were built using the lm function and the most parsimonious model was identified using the stepAIC function from the MASS package (Venables and Ripley 2002). Environmental variables were included in the model using a stepwise selection and the model with the lowest Akaike score was selected. Significance of the selected model was then tested by F tests.

Results

Environmental parameters

During the study period, environmental factors to which phytoplankton were exposed allowed the comparison of RLC and N-SSLC under different conditions at daily scale as well as at annual scale.

At daily scale, maximum sea water temperature showed seasonal variations. It was low in January (6°C), medium in March (9°C) and high in July (22°C) (Table 1). During the day, sea water temperature increased by 0.6°C in January, 2-3°C in March and 4°C in July. Salinity ranged from 28.2 to 34.8 and showed no seasonal variation.

Different

Phytoplankton composition

At daily scale, phytoplankton composition did not vary significantly during the day (ANOSIM, P>0.05) but different phytoplankton community structures were observed between the different sampling days according to the sampling season (ANOSIM, P<0.05) (Fig. 3A). On January 28 th 2010, the community was composed of "diatoms + dinoflagellates" and "Cryptophyta + cyanobacteria" in almost equal proportions. March 2010 was the period when the Haptophyte Phaeocystis globosa bloomed. This species dominated phytoplankton community on March 18 th and 26 th 2010 with a small contribution of "diatoms + dinoflagellates" and "Cryptophyta + cyanobacteria". On July 23 th and 29 th 2010, P. globosa and "Cryptophyta + cyanobacteria" were present in almost equal proportions with a lower contribution of "diatoms + dinoflagellates". Total chl a biomass was equal to 5 µg.L -1 in January 2010, 19-20 µg.L -1 in March 2010 and 3 µg.L -1 in July 2010.

At annual scale, phytoplankton composition was not significantly different between high and low tides (ANOSIM, P>0.05). Phytoplankton community structure showed clear seasonal variations with different phytoplankton communities during the different seasons of the year (Fig. 3B). In spring 2009, there were three successive phytoplankton blooms. P.

globosa bloomed from mid-April to mid-May and disappeared at the end of spring. This bloom was preceded and followed by two blooms of "diatoms + dinoflagellates" (a first globosa bloom started earlier (from mid-March) and reached a maximum of biomass 2.8 times higher than in 2009. This bloom was preceded by a "diatoms + dinoflagellates" bloom (between February and March) but contrary to 2009, was not followed by a second bloom of "diatoms + dinoflagellates". The "diatoms + dinoflagellates" bloom preceding the P. globosa bloom in 2010 had a maximum of biomass 2.5 times higher than in 2009. "Cryptophyta + cyanobacteria" were present throughout the year. In 2009, their concentration always stayed low while in 2010, a bloom of "Cryptophyta + cyanobacteria" was observed at the same time of the "diatoms + dinoflagellates" bloom (in February-March). At daily scale, the shape of ETR vs E curves differed between RLC and N-SSLC and changed during the day (Fig. 4A,B,C). The photosynthetic parameters resulting from RLC and N-SSLC varied during the day without any diel pattern common to the different sampling days. The maximal light utilization efficiency derived from RLC (α _RLC ) and N-SSLC (α _N- SSLC ) (Fig. 5A) showed very similar patterns of variation during the day and their values were not significantly different regardless of the sampling date considered (Ratkowski test for nonlinear models, P>0.05). By contrast, the degree of resemblance between the maximum electron transport rate (ETR m ) (Fig. 5B) or light saturation coefficient (E k ) (Fig. 5C) derived from N-SSLC and RLC differed from one day to another. On January 28 th , March 18 th , July 23 th and July 29 th , ETR m derived from N-SSLC (ETR m_N-SSLC ) and from RLC (ETR m_RLC )

ETR vs. E curves and derived photosynthetic parameters (α, ETR m and E k )

showed similar patterns of variation. ETR m_N-SSLC was significantly higher than ETR m_RLC (Ratkowski test for non-linear models, P<0.05) only at the first and last sampling hours on January 28 th and throughout the day on July 23 th . On March 26 th , ETR m_RLC increased more rapidly to follow light variations than ETR m_N-SSLC which increased latter . At 12h00, ETR m_RLC was thus significantly higher than ETR m_N-SSLC while at 13h45, it was the opposite (Ratkowski test for non-linear models, P<0.05). E k derived from RLC (E k_RLC ) followed more closely light variations than E k derived from N-SSLC (E k_N-SSLC ) on January 28 th and on March 18 th and 26 th . By contrast, on July 23 th and 29 th , no significant difference was found between E k_RLC and E k_N-SSLC. Ratios ETR m_RLC / ETR m_N-SSLC and E k_RLC / E k_N-SSLC were related to temperature, phytoplankton composition and light conditions experienced before the measurement (Table 2).

At annual scale, the shape of ETR vs E curves was very similar between RLC and N-SSLC (Fig. 4D). Photosynthetic parameters were not significantly different between high and low tides (Student t-test, P>0.05). Patterns of variation of α (Fig. 6A) and ETR m (Fig. 6B) derived from N-SSLC and RLC were very similar at high tide as well as at low tide.

ETR m_RLC, ETR m_N-SSLC , α _RLC and α _N-SSLC showed a similar high variability without any clear seasonal cycle with high values in summer, late autumn-early winter and punctually during spring. However in term of absolute values, significant differences were found between RLC and N-SSLC photosynthetic parameters (Ratkowski test for non-linear models, P<0.05).

ETR m and α were generally significantly higher when measured with N-SSLC than after RLC measurements. ETR m_N-SSLC ranged from 0.02 to 3.78 µmol e -mg chl a -1 s -1 while ETR m_RLC ranged from 0.01 to 2.72 µmol e -mg chl a -1 s -1 . α _N-SSLC ranged from 0.0001 to 0.0172 µmol e -mg chl a -1 s -1 (µmol photons m -2 s -1 ) -1 while α _RLC ranged from 0.0001 to 0.0132 µmol e -mg chl a -1 s -1 (µmol photons m -2 s -1 ) -1 . However, gaps between ETR m_RLC and ETR m_N-SSLC and between α _RLC and α _N-SSLC varied during the year. E k_N-SSLC and E k_RLC did not show exactly the same pattern of variation (Fig. 6C). At some dates, E k_N-SSLC was higher than E k_RLC while at other dates it was lower but in term of absolute values, E k_N-SSLC and E k_RLC were very close. E k_N-SSLC ranged from 72 to 407 µmol photons m -2 s -1 while E k_RLC ranged from 83 to 402 µmol photons m -2 s -1 . Ratio α _RLC / α _N-SSLC was related to temperature and phytoplankton composition (Table 2) while no relationships could be found between the environmental factors investigated and ratios ETR m_RLC / ETR m_N-SSLC and E k_RLC / E k_N-SSLC . At daily scale, with the exception of March 26 th and July 29 th , significant linear relationships very close to the 1:1 relationship were found between α _N-SSLC and α _RLC (Fig. 7A,B,C). On July 23 th , this relationship was indeed not significantly different from a 1:1 relationship (ANCOVA, P=0.19). On January 28 th and March 18 th , the slope was not significantly different from 1 (ANCOVA, January 28 th P=0.89, March 18 th P=0.71) but the intercept was significantly different from zero (ANCOVA, P<0.05). The quality of the relationship between ETR m_RLC and ETR m_N-SSLC differed between sampling days (Fig. 8A,B,C,D). On March 26 th , no significant linear relationship was found between ETR m_RLC and ETR m_N-SSLC. On January 28 th and July 29 th , this relationship was not significantly different from the 1:1 relationship (ANCOVA, P=0.50). On March 18 th , the relationship was significant but different from a 1:1 relationship because the slope was less than 1 (ANCOVA, P<0.05).

On July 23 th , the relationship was very close to a 1:1 relationship. The slope was not significantly different from 1 (ANCOVA, P=0.20). Only the intercept was significantly different from zero (ANCOVA, P<0.001).

At annual scale, significant linear relationships were found between α _N-SSLC and α _RLC (Fig. 7D andE) and between ETR m_N-SSLC and ETR m_RLC (Fig. 8E andF) and at high tide and low tide. The relationship between α _N-SSLC and α _RLC was very close to a 1:1 relationship with a slope not significantly different from 1 (ANCOVA, low tide P=0.45, high tide P=0.13).

Only the intercept was significantly different from zero (ANCOVA, low tide P<0.05, high tide P<0.001). The relationship between ETR m_N-SSLC and ETR m_RLC was significantly different from a 1:1 relationship (ANCOVA, low tide and high tide P<0.001) with a slope significantly higher than 1 at high tide and low tide (ANCOVA, low tide P<0.05, high tide P<0.001).

At daily scale as well as at annual scale, no significant linear relationship was found between E k_N-SSLC and E k_RLC .

Non-photochemical quenching (NPQ)

At daily scale, the shape of NPQ vs. E curves was very similar when measured with RLC or N-SSLC. At the beginning of the curve, NPQ was close to zero and then increased monotonically with increasing light steps. 48% of NPQ vs. E curves did not reach saturation within the range of irradiances applied. Their shape was close to linear with a sigmoidicity equal to 1 (Fig. 9A). The 52% remaining reached saturation but sigmoidicity was also close to 1 (Fig. 9B). The maximum level of NPQ reached during the curve (NPQ max ) and the slope of the first part of the NPQ vs. E curve (S) (Fig. 5D,E) were not significantly different between RLC and N-SSLC (Paired t-test, P>0.05) even though they did not always follow the same trends of variation during the day.

At annual scale, the shape of NPQ vs. E curves was also very similar between RLC and N-SSLC and was the same as at daily scale. 74% of NPQ vs. E curves were close to linear and did not reach saturation. The 26% remaining reached saturation but their sigmoidicity was also close to 1.NPQ max and S (Fig. 6D,E) were not significantly different between high and low tide whatever the methodology employed (Student t-test, P>0.05). NPQ max_N-SSLC and S _N- SSLC were significantly higher than NPQ max_RLC and S _RLC (Paired t-test, P<0.05) and they showed several peaks that did not appear in NPQ max_RLC and S _RLC variations.

Discussion

Variations at different time scales of α _RLC , , ETR m_RLC, E k_RLC versus α _N-SSLC , ETR m_N-SSLC and E k_N-SSLC

The level of similarity between the photosynthetic parameters extracted from RLC and N-SSLC differed according to the time scale and parameter considered. The highest level of dissimilarity was observed at daily scale due to the recent light history which had more influence on the photosynthetic parameters resulting from RLC than N-SSLC. As a consequence, at daily scale, ETR m_RLC and E k_RLC followed more closely rapid light variations than ETR m_N-SSLC and E k_N-SSLC did and some rapid changes in phytoplankton photosynthetic activity were not detected when the measurements were made with N-SSLC. These observations are in accordance with studies made on microphytobenthos showing that patterns of variation and absolute values of photosynthetic parameters are influenced by the duration of light steps [START_REF] Frankenbach | One pulse, one light curve: Fast characterization of the light response of microphytobenthos biofilms using chlorophyll fluorescence[END_REF][START_REF] Henley | Measurement and interpretation of photosynthetic light-response curves in algae in the context of photoinhibition and diel changes Journal of Phycology 29[END_REF][START_REF] Lefebvre | Duration of rapid light curves for determining the photosynthetic activity of microphytobenthos biofilm in situ[END_REF][START_REF] Perkins | Light response curve methodology and possible implications in the application of chlorophyll fluorescence to benthic diatoms[END_REF]. Differences between photosynthetic parameters measured on microphytobenthic algae grown under experimental high light or low light conditions have thus been shown to decrease as a function of increasing duration of light steps. As a result, SSLC can reduce or negate the real level of the previous 1 hour photoacclimation while RLC with short light steps keep this difference [START_REF] Frankenbach | One pulse, one light curve: Fast characterization of the light response of microphytobenthos biofilms using chlorophyll fluorescence[END_REF][START_REF] Perkins | Light response curve methodology and possible implications in the application of chlorophyll fluorescence to benthic diatoms[END_REF]). These results have important implications for the design of future phytoplankton photosynthesis studies at daily scale because they show that N-SSLC may not be appropriate to accurately measure phytoplankton responses to short-term environmental variations.

Indeed, some of the phytoplankton acclimation abilities may go undetected with N-SSLC measurements. It should however be noted that duration of RLC light steps has to be as short as possible like in the present study (10 s) to modify the less as possible the acclimation status reached by phytoplankton communities immediately prior to the start of the curve measurement. The use of longer RLC light steps would reduce differences between the photosynthetic parameters extracted from RLC and N-SSLC because RLC ability to capture acclimation to recent light history is inversely proportional to light steps duration. Indeed, the longer the light steps, the more phytoplankton acclimate during the curve building and the more it is difficult to characterize differences in short-term acclimation status of algae exposed to contrasted environmental conditions just before the RLC measurement [START_REF] Frankenbach | One pulse, one light curve: Fast characterization of the light response of microphytobenthos biofilms using chlorophyll fluorescence[END_REF][START_REF] Lefebvre | Duration of rapid light curves for determining the photosynthetic activity of microphytobenthos biofilm in situ[END_REF][START_REF] Perkins | Light response curve methodology and possible implications in the application of chlorophyll fluorescence to benthic diatoms[END_REF].

By conducting laboratory experiments on natural communities and cultures of benthic microalgae, [START_REF] Serôdio | Rapid light-response curves of chlorophyll fluorescence in microalgae: Relationship to steady-state light curves and nonphotochemical quenching in benthic diatom-dominated assemblages[END_REF] and [START_REF] Cruz | Relationship of rapid light curves of variable fluorescence to photoacclimation and non-photochemical quenching in a benthic diatom[END_REF] found that besides providing information on the algal photosynthetic response to recent changes in ambient irradiance, RLC also inform on the long-term photoacclimation status, namely the status which was supposed to be exclusively measured with SSLC. Our results seem to be in accordance with these observations because at annual scale, the general trends of α _RLC and ETR m_RLC variations were very similar to α _N-SSLC and ETR m_N-SSLC , while at this time scale the recent light history has a lower effect on photosynthetic parameters than at daily scale. However, the methodology employed still influenced the absolute values of photosynthetic parameters and higher values were obtained with N-SSLC.

Several explanations have been proposed to explain discrepancies between the photosynthetic parameters extracted from RLC and SSLC. [START_REF] Serôdio | Rapid light-response curves of chlorophyll fluorescence in microalgae: Relationship to steady-state light curves and nonphotochemical quenching in benthic diatom-dominated assemblages[END_REF] and [START_REF] Cruz | Relationship of rapid light curves of variable fluorescence to photoacclimation and non-photochemical quenching in a benthic diatom[END_REF] explained differences between ETR m_RLC and ETR m measured with SSLC (ETR m_SSLC ) by the activation of the carbon metabolism during the final steps of SSLC or by its rapid de-activation during RLC measurement. According to [START_REF] Perkins | Light response curve methodology and possible implications in the application of chlorophyll fluorescence to benthic diatoms[END_REF], the inequality between ETR m_RLC and ETR m_SSLC results from the light dose effect experienced during the curve itself which primarily involves the rate of primary quinone acceptor Q A reoxydation and the induction of the non-photochemical quenching (NPQ). Q A reoxydation has the strongest impact particularly during RLC. The short light steps of RLC applied sequentially do not allow the complete reoxydation of Q A between each irradiance step which lead to the accumulation of reduced electron acceptors down to PSII. This has a higher impact on the last light steps and consequently results in lower values of ETR m_RLC in comparison to ETR m_SSLC [START_REF] Lefebvre | Duration of rapid light curves for determining the photosynthetic activity of microphytobenthos biofilm in situ[END_REF][START_REF] Perkins | Light response curve methodology and possible implications in the application of chlorophyll fluorescence to benthic diatoms[END_REF]. NPQ induced by light dose accumulation during the curve may also be involved but in a more complex way. It impacts the acquisition of F' and F m ' used in the calculation of ETR and it was found that the level of NPQ induced by light dose accumulation increases proportionally to the duration of light steps [START_REF] Perkins | Light response curve methodology and possible implications in the application of chlorophyll fluorescence to benthic diatoms[END_REF]. Differences between α _RLC and α _SSLC have also been explained by the influence of NPQ [START_REF] Cruz | Relationship of rapid light curves of variable fluorescence to photoacclimation and non-photochemical quenching in a benthic diatom[END_REF][START_REF] Lefebvre | Duration of rapid light curves for determining the photosynthetic activity of microphytobenthos biofilm in situ[END_REF][START_REF] Perkins | Light response curve methodology and possible implications in the application of chlorophyll fluorescence to benthic diatoms[END_REF][START_REF] Serôdio | Rapid light-response curves of chlorophyll fluorescence in microalgae: Relationship to steady-state light curves and nonphotochemical quenching in benthic diatom-dominated assemblages[END_REF]. It has been shown that NPQ formed in response to an excess in environmental light conditions just before the RLC measurement, dissipates incompletely during the first light steps on which the estimation of α _RLC is based. As a consequence, lower values of α _RLC are obtained in comparison to α _SSLC because SSLC allow NPQ to completely relax during the first light steps [START_REF] Cruz | Relationship of rapid light curves of variable fluorescence to photoacclimation and non-photochemical quenching in a benthic diatom[END_REF][START_REF] Lefebvre | Duration of rapid light curves for determining the photosynthetic activity of microphytobenthos biofilm in situ[END_REF][START_REF] Serôdio | Rapid light-response curves of chlorophyll fluorescence in microalgae: Relationship to steady-state light curves and nonphotochemical quenching in benthic diatom-dominated assemblages[END_REF]). In our study, discrepancies between α _RLC and α _N-SSLC cannot be explained by the incomplete dissipation of NPQ during the first light steps because at the beginning of RLC and N-SSLC, the level of NPQ was always close to zero and NPQ processes only start to be activated during the curves building (by light dose accumulation). Nevertheless, at annual

Use of RLC to assess the photoacclimation status at steady-state

One of the objectives of this study was to characterize at different time scales, the relationship between RLC and N-SSLC under a wide range of environmental conditions and phytoplankton community structures. The underlying goal was to evaluate the possibility to use RLC to predict the photosynthetic parameters at steady-state and thus to define the longterm phytoplankton photoacclimation status in the context of field studies. According to Serodio et al. (2006), the relationship between the photosynthetic parameters extracted from RLC and SSLC is strongly dependent on the level of ambient irradiance to which algae have been acclimated before the measurement of light response curves. As a result, the use of α _RLC to predict α _SSLC is only possible when algae have been exposed to low ambient irradiance while ETR m_RLC can provide a reasonable prediction of ETR m_SSLC only after acclimation to high irradiance. Due to this inverse possibility to predict α _SSLC and ETR m_SSLC from α _RLC and ETR m_RLC , E k_SSLC cannot be predicted using E k_RLC [START_REF] Serôdio | Rapid light-response curves of chlorophyll fluorescence in microalgae: Relationship to steady-state light curves and nonphotochemical quenching in benthic diatom-dominated assemblages[END_REF]. About E k , our results confirm the observations of [START_REF] Serôdio | Rapid light-response curves of chlorophyll fluorescence in microalgae: Relationship to steady-state light curves and nonphotochemical quenching in benthic diatom-dominated assemblages[END_REF] because no significant linear relationship was found between E k_N-SSLC and E k_RLC at daily scale as well as at annual scale.

Nevertheless, it should be noted that at annual scale even though the relationship between E k_N-SSLC and E k_RLC is not significant, conclusions about the phytoplankton acclimation status remain the same. In the case of phytoplankton, it seems to be mainly the RLC susceptibility to measure rapid changes in α and ETR m which would have been passed unnoticed with N-SSLC measurements (and thus the time scale at which measurements are made) that influences the possibility to use RLC parameters to predict SSLC parameters rather than the level of ambient irradiance to which algae have been acclimated before the curve measurement. Indeed, at annual scale, even though ambient irradiance followed a seasonal cycle, there was not a seasonal signal in the difference between α _RLC and α _N-SSLC and between ETR m_RLC and ETR m_N-SSLC and the highest differences between ETR m_RLC and ETR m_N-SSLC were observed in spring and summer i.e. during periods where algae were exposed to the highest ambient irradiances. Additionally, at daily scale, it was not systematically during the periods with the highest irradiance that the relationship between ETR m_RLC and ETR m_N-SSLC was the best and inversely for α _RLC and α _N-SSLC . By contrast, relationships between the photosynthetic parameters extracted from RLC and N-SSLC were better at annual scale than at daily scale.

As a consequence, because RLC measurements better capture the short-term changes in photosynthetic activity than N-SSLC do, at daily scale, relationships between photosynthetic parameters resulting from RLC and N-SSLC may not be linear. The use of RLC to predict N-SSLC photosynthetic parameters is thus compromised. However, this seems possible at annual scale because at this time scale, recent changes in environmental conditions have a lower influence on photosynthesis and stronger relationships have been observed between ETR m_RLC and ETR m_N-SSLC and between α _RLC and α _N-SSLC regardless of the seasonal variations in physico-chemical parameters and phytoplankton structure.

Conclusions

The results of this study highlight the usefulness of RLC to accurately characterize short-term and long-term in situ variations in phytoplankton photosynthetic performances and acclimation status. At daily scale, RLC measurements are strongly sensitive to recent phytoplankton light history and short-term acclimation status which allows for detecting rapid changes in photosynthetic activity that would have been overlooked with N-SSLC measurements. This ability is advantageous to study phytoplankton photosynthesis in environments with rapidly fluctuating conditions such as coastal systems with high water mixing rates or estuaries. Besides these short-term changes, RLC can also be used to follow seasonal fluctuations in phytoplankton photosynthesis as they inform on the long-term photoacclimation status in a very similar way to N-SSLC. Absolute values of photosynthetic parameters and ETR extracted from RLC are impacted by the short duration of light steps which leads to lower values in comparison to N-SSLC. However, at annual scale, information about the steady-state photoacclimation status can be obtained from RLC measurements using the strong linear relationships between RLC and N-SSLC measurements to make a correction.

In their application at this time scale, RLC have the advantage over N-SSLC of drastically

  spring (March 18 th and 26 th 2010) and summer (July 23 th and 29 th 2010). At annual scale, samples were collected once per week from February 2009 to August 2010 at high and low tide.

Fig. 1

 1 Fig. 1 Map of the Strait of Dover with enlarged area representing the location of sampling station (S). Coordinates are in decimal degrees

  light conditions, representative of the natural hourly and daily variability, were encountered during the different sampling days. Light was the most variable parameter because it changed from hour to hour within each day and the intraday pattern of variation varied among the different sampling days. Day length and maximum daily irradiance varied according to seasons and increased from January to July. Because of the low depth of the sampling station, incident irradiance showed the same trends of variation as the mean light available within the water column and the water column was always within the photic zone(Houliez et al. 2013a; Houliez et al. 2013b). Salinity stayed relatively stable within the day and between the sampling days. During the day, nutrient concentrations increased with the flood of the tide and decreased with the ebb and changed between the sampling days according to seasons.At annual scale, environmental parameters (i.e. irradiance, sea water temperature, salinity and nutrients) were not significantly different between high and low tides (Mann Whitney U test, P>0.05). Sea water temperature, irradiance, NO 2 -+ NO 3 -and Si(OH) 4 showed clear seasonal variations (Fig.2). Sea water temperature and maximum incident irradiance followed the classical seasonal evolution of temperate northern regions with low values in

Fig. 2

 2 Fig. 2 Seasonal variability of physicochemical parameters. A) Maximum incident daily PAR (µmol photons m -2 s -1 ), B) Temperature (°C), C) Salinity, D) Nitrite + nitrate concentration (NO 2 -+ NO 3 -, µM), E) Silicate concentration (Si(OH) 4 , µM) and F) Phosphate concentration (PO 4 3-, µM). HT: high tide. LT: low tide

Fig. 3

 3 Fig. 3 A) Hourly and B) seasonal variability of taxonomic composition of phytoplankton assemblages identified by the FluoroProbe. The relative amount of each phytoplankton group is expressed in terms of the equivalent amount of chlorophyll a per litre. Values for the seasonal variability are the mean of measurements made at high and low tide

Fig. 4

 4 Fig. 4 Examples of ETR vs. E curves obtained after RLC and N-SSLC measurements at daily scale on A) July 29 th 6h45 am, B) July 29 th 8h30 am, C) July 29 th 8h45 pm and D) at seasonal scale on May 20 th at low tide. Black circles and solid line correspond to RLC. RLC values are mean ± standard deviation of 3 replicates. White triangles and dashed line are N-SSLC

Fig. 5 Fig. 6 Fig. 7

 567 Fig. 5 Photosynthetic parameters measured with RLC and N-SSLC at daily scale. A) Maximal light utilization efficiency (α in µmol emg chl a -1 s -1 (µmol photons m -2 s -1 ) -1 ), B) Maximum electron transport rate (ETR m in µmol e-mg chl a -1 s -1 ), C) Light saturation coefficient (E k in µmol photons m -2 s -1 ), D) Maximum level of nonphotochemical quenching reached during the curve (NPQmax) and E) Slope of the first part of the NPQ vs. E curve (S) (in black and white) and incident PAR (µmol photons m -2 s -1 ) in gray

Fig. 8

 8 Fig. 8 Linear relationship between ETR m_RLC and ETR m_N-SSLC measured at daily (A, B, C, D) and annual (E, F) scales. The solid line is the regression line. The dashed line represents the 1:1 ratio

Fig. 9

 9 Fig. 9 The two main shapes of NPQ vs. E curves observed at daily and seasonal scales. A) Shape close to linear with a sigmoidicity equal to 1 and saturation not reached within the range of irradiances applied. B) Saturation reached and sigmoidicity close to 1. Black circles and solid line correspond to RLC. RLC values are mean ± standard deviation of 3 replicates. White triangles and dashed line are N-SSLC

  photoacclimation processes during RLC and N-SSLC measurements.

  shortening the time required for measurement and they allow replication.vanKooten O, Snel JFH (1990) The use of chlorophyll fluorescence nomenclature in plant stress physiology Photosynthesis Research 25:147-150 Venables WN, Ripley BD (2002) Modern applied statistics with S. Fourth Edition. Springer, New York. 498 p. Webb WL, Newton M, Starr D (1974) Carbon dioxide exchange of Alnus rubra : a mathematical model Ecologia 17:281-291 White AJ, Critchley C (1999) Rapid light curves : a new fluorescence method to assess the state of the photosynthetic apparatus Photosynthesis Research 59:63-72

Table 1

 1 Physicochemical parameters at daily scale: range (minimum-maximum), mean (SE) and coefficient of variation (CV, %)

		Day length	PAR			Temperature		Salinity			NO2 -+ NO3 -			Si(OH)4
			Range	m (SE)	CV	Range	m (SE)	CV	Range	m (SE)	CV	Range	m (SE)	CV	Range	m (SE)	CV
	28 January 2010 9h12	0-534	126 (110) 87	5.3-5.9	5.7 (0.2)	4	29.80-33.30	32.01 (1.68)	5	15.4-48.3 29.1 (12.1) 42	2.2-6.7	4.8 (1.9)
	18 March 2010	12h04	0-613	259 (174) 67	6.0-9.0	7.2 (0.8)	12	30.00-34.10	33.24 (1.32)	4	0.1-5.4	1.7 (2.5)	149	1.2-3.9	2.5 (1.3)
	26 March 2010	12h31	0-808	352 (263) 75	7.0-9.1	8.2 (0.76) 9	32.00-33.80	33.40 (0.56)	2	0.4-1.8	0.8 (0.5)	61	1.3-4.2	2.3 (1.0)
	23 July 2010	15h25	0-960	428 (322) 75	17.0-21.0 19.6 (1.2) 6	34.62-34.70	34.69 (0.03)	0.1	0.1-1.3	0.4 (0.3)	88	0.1-3.1	1.1 (0.9)
	29 July 2010	15h10	0-1,202	351 (289) 82	18.1-22.2 19.6 (1.3) 7	34.72-34.80	34.78 (0.03)	0.1	0.3-2.5	1.2 (0.9)	72	0.5-2.8	1.6 (0.8)
		Day length	PO4 3-
			Range	m (SE)	CV
	28 January 2010 9h12	0.3-1.9	0.9 (0.5)	57
	18 March 2010	12h04	0.6-1.0	0.8 (0.2)	18
	26 March 2010	12h31	0.1-1.0	0.7 (0.2)	32
	23 July 2010	15h25	1.1-1.6	1.2 (0.1)	10
	29 July 2010	15h10	1.2-1.5	1.3 (0.1)	9
	PAR: incident irradiance (µmol photons m -2 s -1 ), temperature: water temperature (°C), NO 2 -+ NO 3 -(µM), Si(OH) 4 (µM), PO 4 3-(µM), SE: standard error

Table 2

 2 Stepwise multiple linear regression equations and their associated statistics relating ratios of photosynthetic parameters derived from RLC and N-SSLC to environmental factors and phytoplankton composition. r² = adjusted coefficient of determination (in %), PAR 4D : mean incident PAR over the three previous days and day of sampling, Phaeo: Phaeocystis globosa biomass (FluoroProbe estimation)

	Regression equation

Acknowledgments

We thank Xavier Mériaux for technical assistance in chl a-specific absorption coefficients analyses. We thank anonymous reviewers for their critical comments that improved the manuscript.

Compliance with ethical standards

Funding

This study was part of E.H.'s PhD thesis defended on September 25 th 2012 and financially supported by a grant from the French "Ministère de l'Enseignement Supérieur et de la Recherche" and the DYMAPHY INTERREG IVA "2 Mers Seas Zeeën" project cofunded by the European Union (ERDF funds).

Conflict of interest

The authors declare that they have no conflict of interest.

Human and animal right statement This article does not contain any studies with animals performed by any of the authors.