Basin-scale variability of phytoplankton bio-optical characteristics in relation to bloom state and community structure in the Northeast Atlantic

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Deep-Sea Research I 52 (2005) 401–419 www.elsevier.com/locate/dsr

Basin-scale variability of phytoplankton bio-optical characteristics in relation to bloom state and community structure in the Northeast Atlantic C. Mark Moore, Mike I. Lucas, Richard Sanders, Russell Davidson Southampton Oceanography Centre, European Way, Southampton SO14 3ZH, UK Received 2 June 2003; received in revised form 11 March 2004; accepted 24 September 2004 Available online 7 January 2005

Abstract Phytoplankton physiological data collected throughout the Iceland Basin and Rockall Trough during the North Atlantic spring bloom from May to June 2001 are presented. Physiological parameters including the maximum photochemical quantum efficiency (Fv/Fm) and the functional absorption cross section of photosystem II (sPSII) were measured using fast repetition rate fluorometry. Information on the taxonomic and pigment characteristics of the phytoplankton populations was also collected, with pigment data being used to reconstruct absorption spectra. Significant changes in the physiological properties of PSII were found to be associated with the progression of the spring bloom from diatom to flagellate domination. Changes in both community composition and physiology were in turn correlated with environmental parameters. Lower Fv/Fm, higher sPSII and corresponding decreases in cell size were associated with the observed decrease of nutrients that accompanied increasing stratification. Differences in sPSII were primarily associated with the changing pigment composition of the phytoplankton populations, with the largest changes appearing to be governed by the amount of absorption by photosynthetic carotenoids. The physiological state of PSII was thus found to be an indicator of bloom status and community structure in this productive temperate region principally as a result of taxon specific variability. r 2004 Elsevier Ltd. All rights reserved. Keywords: Phytoplankton; Fluorescence; Photosynthesis; Pigments; Spring bloom; Fast repetition rate fluorometry; Northeast Atlantic Ocean

1. Introduction

Corresponding author. Tel.: +44 23 8059 6446;

fax: +44 23 8059 3059. E-mail address: [email protected] (C.M. Moore).

The advent of satellite remote sensing of ocean colour has provided an unprecedented view of phytoplankton pigment distributions at scales ranging from a few kilometres up to basin and

0967-0637/$ - see front matter r 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.dsr.2004.09.003

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Table 1 Fluorescence notation Parameter

Definition

F0, Fm F00 , F0 , Fm0 Fv Fv0 Fq0 Fv/Fm F0 v/Fm0 F0 q/Fm0 sPSII sPSII0

Minimal and maximal fluorescence yields measured in the dark Minimal, steady-state and maximal fluorescence yields measured under ambient irradiance Variable fluorescence (=Fm–F0) Variable fluorescence measured under ambient irradiance (=Fm0 –F00 ) Change in fluorescence yield measured under ambient light (=F0 m–F0 ) Maximum photochemical quantum efficiency Maximum photochemical quantum efficiency measured under ambient light Photochemical quantum efficiency measured under ambient light Functional absorption cross section of PSII in the dark Functional absorption cross section of PSII under ambient light

global scales. However converting maps of phytoplankton pigment into estimates of primary productivity, which allow questions concerning the influence of phytoplankton in global carbon cycling to be addressed, requires an understanding of how the efficiency of light absorption and utilisation varies at these same scales (Platt and Sathyendranath, 1988). Active fluorescence techniques such as the fast repetition rate (FRR) fluorometer (Kolber et al., 1998) have the potential to greatly extend the scales at which phytoplankton physiological and bio-optical parameters can be measured in situ (Kolber and Falkowski, 1993). In particular, by circumventing the need for time-consuming incubations, observations at much higher spatial and temporal resolution and over greater scales can be made during ship-based studies (e.g. Falkowski et al., 1991; Olaizola et al., 1996; Moore et al., 2003). It is therefore important to improve our understanding of the relationships between fluorescence derived physiological parameters of natural communities and other bio-optical parameters, as well as the environmental controls on these. The FRR technique has the ability to measure a number of parameters describing the physiological state of photosystem II (PSII), including the maximum photochemical quantum efficiency (Fv/ Fm) and the functional absorption cross section (sPSII), see Table 1. The maximum photochemical quantum efficiency is closely related to the maximum quantum efficiency of photosynthesis

(e.g. Genty et al., 1989; Babin et al., 1996), an important parameter in bio-optical models (Bidigare et al., 1992). Previous work indicates that low Fv/Fm is an indicator of nutrient starvation (Cleveland and Perry, 1987; Kolber et al., 1988) although Fv/Fm may remain high under balanced nutrient limited growth conditions (Parkhill et al., 2001). The functional absorption cross section is a measure of the photochemical target size of PSII and is the product of absorption by the suite of PSII antenna pigments and the probability that an exciton within the antenna will cause a photochemical reaction (Mauzerall and Greenbaum, 1989; Kolber et al., 1998). Considerable taxonomic variability of sPSII is observed whilst a number of other factors including photoacclimation and nutrient status can also affect this parameter (Kolber et al., 1988, 1990; Greene et al., 1991; Geider et al., 1993a, b; Suggett et al., 2004). Previous work using active fluorescence has often focused on oligotrophic waters (Olaizola et al., 1996) or regions where iron limitation plays an important role (e.g. Behrenfeld et al., 1996; Sosik and Olson, 2002; Suzuki et al., 2002). In contrast, relatively little has been reported on the variability of Fv/Fm and sPSII in productive open ocean regions. The spring bloom in the North Atlantic represents the most marked seasonal signal in global maps of oceanic autotrophic biomass (Esaias et al., 1986; Longhurst, 1998) and is responsible for a considerable flux of organic

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2. Methods 2.1. General Data were collected from 4 May to 20 June 2001 during a cruise of the R.R.S. Discovery (D253), the Faeroes, Iceland, Scotland Hydrographic and Environmental Survey (FISHES). The cruise was split into two legs, the first consisting of the occupation of 4100 stations throughout the Iceland Basin and Rockall Trough (Fig. 1), while the second leg concentrated on a process study of the Iceland Faeroes Front (IFF). Meteorological data including photosynthetically available radiation (PAR) was recorded throughout the cruise. Sea surface temperature (SST) was measured using a Falmouth Scientific Instruments Online Temperature Monitor. A Chelsea Scientific Instruments FastrackaTM FRR fluorometer was also placed in line with the underway non-toxic water supply in order to monitor the physiological state of the surface phytoplankton populations. During each of the stations occupied during legs 1 and 2, hydrographic data were obtained using either a Neil Brown MkIIIc or a Seabird 911 CTD. CTD profiles were used to calculate the mean buoyancy frequency (N) between the surface (taken as 10 m for practical purposes) and 100 m (N ¼ ðgDr=rDzÞ1=2 ; where g is the acceleration due to gravity and r is the density) as an index of the degree of upper water column stratification. The

68°N 14071

64°N Latitude

carbon to the deep ocean (Billet et al., 1986; Honjo and Manganini, 1993). The current study aimed to investigate the environmental controls on bulk community values of Fv/Fm and sPSII throughout the Iceland Basin during the spring bloom (May–June 2001). FRR fluorometer measurements were combined with taxonomic data and information on the pigment composition of the varying phytoplankton communities encountered. Relationships between the fluorescence and pigment derived biooptical properties could therefore be examined in relation to changes in community composition and environmental variability at large (450–1000 km) scales.

403

13989 Iceland

14066

IFF

RR

60°N 14005

56°N 14038

RT

52°N 30°W

Eire

24°W

18°W

12°W Longitude

6°W

UK

0°

Fig. 1. Map showing cruise track and stations surveyed during both legs of cruise D253, FISHES May–June 2001. Symbols mark station positions where FRR fluorometer profiles were obtained. Symbols with crosses indicate stations where HPLC data were also acquired. Labelled square symbols indicate stations specifically referred to in text. The 1000 m depth contour is also indicated. The Iceland Faeroes Front (IFF), Reykjanes Ridge (RR) and Rockall Trough (RT) are marked.

chosen depth range spanned the mixed layer at all stations. Water sampling was achieved using Niskin bottles attached to the CTD rosette system. A second FRR fluorometer was deployed in a profiling mode using a stand-alone frame during the majority of stations. Unfortunately, the ship could not always be re-aligned into the sun for FRR fluorometer profiles. Subsequent data analysis revealed intermittent shading of the instrument package by the ship (see below). Along track station spacing averaged around 50 km. 2.2. Chemical and biological sampling Nutrients (nitrate+nitrite, phosphate and silicate) were measured on board using the standard colorimetric techniques of Sanders and Jickells (2000) on a Skalar San Plus autoanalyser for the majority of stations. Chlorophyll a (Chl a) was routinely determined fluorometrically. Water (100 ml) was filtered through 25 mm Whatman GF/F filters and the pigments extracted into 90%

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acetone solution within a dark freezer. After 24 h Chl a was determined on a Turner Designs digital fluorometer, following the method of Welschmeyer (1994). Additionally, at 20 stations occupied around dawn (Fig. 1), samples were collected at 6–7 depths spanning the euphotic zone for the determination of pigments by HPLC. Samples (500 ml) were filtered through 25 mm Whatman GF/F filters which were then stored in a 80 1C freezer. On return to the laboratory pigments were extracted into 90% acetone and analysed according to the method of Barlow et al. (1997) on a Thermo Separation products HPLC. Pigments were identified by retention time and using on-line diode array spectroscopy. Fluorometric estimates of Chl a were higher than HPLC-derived estimates. All values of Chl reported here are HPLC derived or scaled to the HPLC value using the observed relationship between the two techniques (HPLC Chl a ¼ 0:53 fluorometric Chl a, r2 ¼ 0:96; n ¼ 109). Samples for the identification and enumeration of phytoplankton were collected at a number of stations (n ¼ 40), usually from the depth corresponding to 45% of surface irradiance. Samples (2  100 ml) were preserved in 1% Lugol’s iodine solution or 2% buffered Formalin. The latter samples were used for enumeration of coccolithophores from a smaller subset of stations (n ¼ 17). Counts were performed using inverted microscopy and were converted into estimates of cell biovolume and carbon content (Strathmann, 1967). Accurate enumeration of picoplankton was not possible and the biomass and cell volume estimates are therefore restricted to the larger (42 mm, nano- and microplankton) sizes. However, picophytoplankton (o2 mm) and particularly cyanobacteria were a minor constituent (generally o20%) of the total biomass throughout the sampling region as evidenced by microscope observations, size fractionated Chl measurements and low zeaxanthin concentrations. 2.3. Reconstruction of absorption spectra Phytoplankton absorption spectra were reconstructed from the measured pigment concentrations (Bidigare et al., 1990; Babin et al., 1996;

Marra et al., 2000). The in vivo, weight-specific absorption coefficients ðai ðlÞÞ for Chl a, Chl b, Chl c, the photosynthetic carotenoids (PCs) and the non-photosynthetic carotenoids (NPCs) were taken from Bidigare et al. (1990) and combined with the measured pigment concentrations (ci) to generate the absorption spectrum for all the pigments ðaTpig ðlÞÞ according to X aTpig ðlÞ ¼ ai ðlÞci ; (1) where peridinin, 190 -butanoyloxyfucoxanthin, fucoxanthin and 190 -hexanoyloxyfucoxanthin were taken to be the PCs and prasinoxanthin, violaxanthin, diadinoxanthin, alloxanthin, zeaxanthin and b-carotene were taken to be the NPCs. Such a reconstruction is dependent on the assumption that the absorption spectra of all the PCs and NPCs are well represented by the spectra quoted in Bidigare et al. (1990) for fucoxanthin and bcarotene, respectively. Spectra were normalised to Chl a in order to generate the specific absorption spectra for all the cellular pigments (a*Tpig(l), m2 (mg Chl a)1). Specific absorption spectra for photosynthetic pigments only (a*pp(l)), PCs (a*pc(l)) and NPCs (a*npc(l)) were calculated in a similar manner. Examples of reconstructed absorption spectra are presented in Fig. 2. 2.4. Fast repetition rate fluorometer measurements FRR fluorometers were set up using protocols similar to those employed by Suggett et al. (2001) and Moore et al. (2003). Variable Chl fluorescence was induced using a saturating sequence of 100 1.1 ms flashes applied at 2.8 ms intervals using LEDs with peak emission at 478 and 30 nm half-bandwidth. The fluorescence signal was detected between 668 and 705 nm. Fluorescence transients from 16 sequences were averaged internally, then corrected for non-linearities in instrument response using transients recorded during the analysis of an extract of Chl a. Values of the initial (F0, F 0 or F00 ) and maximal (Fm or Fm0 ) fluorescence, and sPSII (sPSII0 ) were calculated by fitting the measured saturation curves to the biophysical model of Kolber et al. (1998). Curve

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Depth = 6m a*Tpig

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14038

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14066 Depth = 26m

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405

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14071

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Depth = 3m

0.04 0.03 0.02 0.01

500

(e)

600 λ (nm)

0 400

700

(f)

500

600

700

λ (nm)

Fig. 2. Examples of reconstructed absorption spectra for: all pigments (a*Tpig), photosynthetic pigments (a*pp), PCs (a*pc) and NPCs (a*npc). Spectra are reconstructed from individual HPLC samples at the specified stations and depths. The additional dashed vertical line at 478 nm in (b–f) corresponds to the peak of the FRR fluorometer excitation spectrum, the full spectrum is indicated by the dotted line in (b).

fitting was performed using software run in MATLABTM, based on original codes provided by Laney (2003). Analysis of filtrate samples passed through Whatman GF/F filters indicated that background (‘dissolved’) fluorescence was a minor (o10%) source of error within the current study (Cullen and Davis, 2003). A pressure sensor and Chelsea Instruments 2p (400–700 nm) PAR sensor were interfaced with the instrument deployed in profiling mode. For the purposes of the current study we were principally concerned with the investigation of broad-scale variability in the maximum photochemical quantum efficiency (Fv/Fm, Table 1) and

the dark-acclimated functional absorption cross section (sPSII). These parameters have to be calculated from measurements made without the influence of irradiance dependent photochemical or non-photochemical quenching (e.g. Butler, 1978; Kolber and Falkowski, 1993; Suggett et al., 2001). The nomenclature of Oxborough and Baker (1997) is adopted in order to distinguish Fv/Fm and sPSII from measurements made with the FRR fluorometer under conditions of ambient irradiance. Thus, parameters measured in the shaded sample area of the profiling instrument when background irradiance is present (i.e. during daytime) correspond to F 0 0, Fm0 , Fv0 , Fv0 /Fm0 and

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sPSII0 . Measurements made using the sample area of the profiling instrument exposed to ambient light correspond to F 0 , Fq0 , Fq0 /Fm0 and sPSII0 (Table 1).

excepting stations south and southwest of Iceland (Figs. 4b, c, 5b and c). Vertical profiles of Chl a displayed uniform values within the upper mixed layer and a decrease below the thermocline for the majority of stations (Fig. 4d and 5d). Relatively few stations (o20%) had pronounced subsurface chlorophyll maxima (SCMs). Where present (e.g. 14005), SCMs were associated with low surface Chl levels (Fig. 4d). The maximum and minimum fluorescence yields F0 and Fm were both correlated with the Chl a concentration for the complete HPLC data set (R2 ¼ 0:58 and 0.72, respectively, n ¼ 130; po0:001); however, the relationship did not remain constant. Both F0/Chl a (Figs. 4e and 5e) and Fm/Chl a (not shown) were higher north of the IFF and for stations in the south of the study region. The major accessory pigments were fucoxanthin and 19-hexanoyloxyfucoxanthin (hereafter fuco and hex, respectively). Over 92% of the variance in Chl a for the complete data set (n ¼ 130) was explained by multi-linear regression against fuco and hex. Consistent with microscope counts, higher ratios of hex/Chl a were observed at the more southerly stations where prymnesiophytes (e.g. E. huxleyi) were found (Table 2). As expected fuco/Chl a ratios were higher at diatom dominated stations. High fuco/Chl a ratios were also found in the regions to the north of the IFF and were likely to have reflected the presence of some diatoms and fuco containing flagellates including Phaeocystis. Station 14005 was anomalous as a significant proportion of alloxanthin was found. Microscope

3. Results 3.1. General distribution of pigments, taxa and physiological variability The broad-scale distributions of Chl a and the estimated contribution of diatoms to the community biomass are presented in Fig. 3. High concentrations of Chl (42 mg m3) were observed south of Iceland and down the Reykjanes Ridge. High concentrations were also observed in the vicinity of the IFF and associated with eddies to the south of this feature. Elsewhere surface Chl concentrations were typically around 1 mg m3 dropping to o0.3 mg m3 (Fig. 3a). Microscope counts indicated that regions with surface Chl concentrations 41 mg m3 tended to be diatom dominated, while outside of the diatom blooms the community was typically dominated by assorted nanoflagellates (Fig. 3b). Vertical profiles of parameters measured at five stations representing the range of different conditions encountered are presented in Figs. 4 and 5. Taxonomic data from these stations are presented in Table 2. Nutrient profiles collected throughout the cruise displayed a reduction in silicate, nitrate and phosphate within the upper mixed layer, 5 13

63°N

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57°N

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10°W 5°W

0°

% C by Diatoms

406

54°N 0

25°W 20°W 15°W

10°W 5°W

0°

0

(b)

Fig. 3. Distribution of Chl a and diatoms. (a) Surface Chl a concentration from combined fluorescence and HPLC data set. (b) Percentage of community carbon biomass contributed by diatoms as estimated from microscopy. Arrows and numbers indicate order of occupation for some of the survey lines. Circled station (63170 N, 91590 W) was associated with an eddy to the south of the IFF.

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(g)

0.4

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0.6

200

400

600

800

1000

(h) σPSII (1020 m2quanta–1)

Fig. 4. Example vertical profiles of: (a) temperature, (b) silicate concentration, (c) nitrate concentration, (d) Chl a concentration, (e) F0/Chl a ratio, (f) a*pp (478) reconstructed from HPLC data, (g) Fv/Fm and (h) sPSII. FRR fluorometer data in (g, h) are from nighttime profiles. All stations are south of IFF, locations and profile numbers are indicated in (a), CIB indicates central Iceland Basin.

analysis of samples taken from a number of depths revealed the presence of the mixotrophic ciliate M. rubrum at this station. Reconstructed absorption spectra from this station must therefore be treated with caution, as M. rubrum contains endosymbiotic cryptomonads (consistent with the high alloxanthin/Chl a) which are rich in phycobilins (Kyewalyanga et al., 2002). Reconstructed specific absorption spectra were flatter for diatom dominated stations as a result of a lower ratio of accessory pigments to Chl for these communities (Fig. 2). Hereafter specific absorption coefficients at 478 nm (a*(478)) are primarily considered, this wavelength being appropriate for comparison with the FRR fluorometer.

We also concentrate on changes in a*pp as the absorption by photosynthetic pigments (i.e. those pigments which transfer excitation energy to PSII), should be directly related to sPSII. Higher values of both a*Tpig(478) and a*pp(478) resulted from increases in carotenoid/Chl a (Fig. 2). An increase in a*pp(478) was associated with the SCM at station 14005 (Fig. 4f), with an increase with depth at station 14066 also associated with the increase in carotenoid/Chl a concentration (Fig. 5f). For the majority of stations a*pp(478) was relatively constant within the mixed layer (Figs. 4f and 5f). For stations occupied at night, both photochemical and non-photochemical quenching could be assumed negligible and vertical profiles of Fv/Fm

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Fig. 5. Example vertical profiles from two stations, within and to the north of the IFF; locations and profile numbers are indicated in (a). Plots and symbols as in Fig. 4.

could thus be obtained from the profiling instrument (Figs. 4g and 5g). Values of Fv/Fm were typically uniform in the surface layer. A decrease in Fv/Fm below the mixed layer, where Chl concentrations started to decrease, was often observed. A subset (o20%) of the night-time stations also displayed a small decrease in the near surface. Variability of Fv/Fm displayed patterns similar to the inverse of both F0/Chl a and Fm/ Chl a. The functional absorption cross section was relatively uniform within the surface layer and decreased below the mixed layer for the majority of stations; however, a clear increase in sPSII was associated with the SCM at station 14005 (Figs. 4h

and 5h). Differences in Fv/Fm and sPSII between stations were marked, with diatom dominated communities tending to have higher Fv/Fm and lower sPSII than flagellate dominated communities. 3.2. Variability of Fq0 /Fm0 , Fv0 /Fm0 and estimation of station specific or ‘mean’ Fv/Fm As a consequence of non-photochemical quenching processes, the observed value of Fv0 / Fm0 (Table 1) will be a function of both the ambient irradiance and the maximum photochemical quantum efficiency (Fv/Fm), while Fq0 /Fm0 will be further influenced by photochemical quenching (e.g. Kolber and Falkowski, 1993).

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409

Table 2 Phytoplankton taxonomic data from representative stations Station

13989

14005

14038

14066

14071

Area

Southeast of Iceland Fucoxanthin

Central Iceland Basin Fucoxanthin and alloxanthin Flagellates and ciliates Mesodinium rubrum in SCM

Rockall Trough

North of IFF

IFF

19-Hex

Fucoxanthin

Fucoxanthin

Flagellates

Flagellates

Diatoms

Unidentified flagellates 2–4 mm 14,000 cells ml1

Unidentified flagellates 2–4 mm 10,000 cells ml1

Asterionelliopsis glacialis 120 cells ml1, Chaetoceros sp. 670 cells ml1 Thalassiosira gravida 40 cells ml1

Emiliania huxleyi 350 cells ml1 Nitzschia sp.

Cryptomonads 1000 ml1 Fragilariopsis oceanica

Dominant accessory pigment Dominant group Dominant species

Other significant constituents Principal diatoms

Diatoms Nitzschia sp. 850 cells ml1

As above

Nitzschia sp.

Such relationships were evident in both underway (not shown) and profiling FRR fluorometer data (Fig. 6). Vertical profiles of Fv/Fm could therefore not be recovered for the day-time stations. In order to compare broad-scale changes in maximum photochemical quantum efficiency at the highest resolution possible, a station-specific Fv/ Fm was calculated as follows. Day-time vertical profiles of Fq0 /Fm0 against irradiance within the upper mixed layer were fitted to the following form (Fig. 6a inset): F 0q =F 0m ¼ F v =F m tan hðE=E k ÞE k =E;

(2)

where E k is the PSII light saturation parameter (Bidigare et al., 1992; Suggett et al., 2001). The derived water column Fv/Fm was thus the maximum value observed within the water column (Fig. 6b). The estimated values of E k were considered inaccurate in many cases, as shading from the ship was often apparent in the vertical profiles of irradiance (Fig. 6a). Values of Fv/Fm calculated using Eq. (2) were insensitive to this problem. A similar procedure was used to calculate sPSII from day-time profiles of sPSII0 .

As above

The method used for calculating water column values of Fv/Fm and sPSII neglects the possible influence of vertical variability. For example, the calculated value would underestimate (overestimate) the surface value under conditions where Fv/Fm or sPSII increased (decreased) towards the surface. However, such effects were considered to be minor for the current study, as Fv/Fm and sPSII were relatively uniform within the surface layer for the majority of night-time profiles (Figs. 4 and 5). Vertical variability of phytoplankton physiology was of secondary importance to horizontal gradients during the sampled stages of the spring bloom. Additionally, no diel variability could be detected in the calculated station-specific values of Fv/Fm or sPSII. 3.3. Broad-scale variations in stratification, nutrients, Fv/Fm and sPSII Maps of Fv/Fm and sPSII calculated using the method described above, along with SST, stratification and surface nutrient concentrations during leg 1 are presented in Fig. 7. SST increased towards the south of the study area (Fig. 7a). As

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Fig. 6. Example calculation of Fv/Fm value from vertical profiles with in situ instrument. (a) Vertical profiles of PAR from three stations. Station 13989 was occupied just prior to dawn when surface irradiance was minimal. Station 13991 was occupied during the early afternoon with relatively high surface irradiance and a clear exponential decrease with depth. Station 14022 was occupied around midday and was one of the most extreme examples of ship shading affecting the irradiance profile obtained. (b) Vertical profiles of ratios of variable fluorescence to maximal fluorescence from in situ FRR fluorometer instrument. Near surface quenching was not apparent during station 13989. During station 13991, vertical profiles of Fv0 /Fm0 displayed near surface reduction indicating nonphotochemical quenching. Values of Fq0 /Fm0 were further reduced due to the additional influence of photochemical quenching. The value of Fv/Fm calculated from each station using Eq. (2) is indicated. Inset in (a) example fit of data from station 13991 to Eq. (2).

expected, a marked decrease in SST was observed north of the IFF. Stratification (N) was high north of the IFF and showed an increasing trend towards the south and east of the region south of the IFF (Fig. 7b). Surface nitrate concentrations were 43 mM throughout the basin with the exception of two stations on the UK continental shelf which are not considered further (Fig. 7c). Highest nitrate levels approached 12 mM for surface samples collected southwest of Iceland. Surface silicate concentrations were low (o1 mM) throughout much of the basin. Higher concentra-

tions of around 2–3 mM were observed in the vicinity of the IFF, while concentrations approaching 6 mM were measured on surface samples to the southwest of Iceland along the Reykjanes Ridge (Fig. 7d). Maximum photochemical quantum efficiencies approached 0.65 within the diatom bloom southwest of Iceland (Fig. 7e). Relatively high values 40.55 were observed within and immediately to the south of the IFF. Throughout the rest of the basin Fv/Fm was lower, with no values 40.55 observed south of 601N. Variability in sPSII showed patterns opposite to that for Fv/Fm with

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Fig. 7. Maps of (a) SST, (b) buoyancy frequency (N), (c) surface nitrate concentration, (d) surface silicate concentration, (e) Fv/Fm and (f) sPSII throughout the study region during leg 1. Plotted values of Fv/Fm and sPSII were calculated from vertical profiles using the in situ FRR fluorometer instrument (see text and Fig. 6).

low values (400–500  1020 m2 quanta1) observed in the diatom blooms south of Iceland and within the IFF. Values observed throughout much of the rest of the basin were higher with no values o550  1020 m2 quanta1 observed south of 601N excluding one on-shelf station (Fig. 7e). 3.4. Relationships between environmental and physiological parameters Surface nitrate concentrations were non-linearly related to silicate concentrations (Fig. 8a). Dissolved phosphate concentrations were highly

correlated with nitrate concentrations (not shown) with a mean nitrate:phosphate ratio of 14.7. Near surface phosphate concentrations were therefore 40.2 mM throughout the study area. Surface nutrient concentrations were decreasing functions of stratification (Fig. 8b and c), suggesting that the phytoplankton bloom associated with increasing spring stratification was responsible for the drawdown of nitrate and silicate from winter levels. Values of Fv/Fm were significantly positively correlated with both the surface nitrate (R2 ¼ 0:32; Fig. 8d) and silicate (R2 ¼ 0:32; Fig. 8e) concentrations (po0:001; n ¼ 109). A low

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proportion of the variance in the total data set for sPSII could be explained by nutrients, although the variability in sPSII increased markedly at lower silicate and to a lesser extent nitrate levels (Fig. 8g and h). In contrast, stratification was a

better predictor of sPSII than of Fv/Fm, particularly south of the IFF where 29% of the variance in sPSII was explained by N (Fig. 8f and i). Removal of the two stations with low sPSII and N4.6 s1 (Fig. 8i), which were both associated

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with mesoscale activity in the vicinity of the IFF (Fig. 3), increased this positive correlation (R2 ¼ 0:42; po0:001; n ¼ 95).

with reference to SST. Stations were separated into those north of the IFF and within and south of the IFF using an SST value of 7 1C. Stratification south of the IFF increased with higher SST (Fig. 9a). A gradient of silicate with SST was also apparent south of the IFF, with a significant negative correlation (R2 ¼ 0:21; n ¼ 101; po0:001) for SSTo7 1C (Fig. 9b). Surface nitrate concentration was also significantly negatively correlated with SSTo7 1C (R2 ¼ 0:38; n ¼ 101; po0:001; not shown).

3.5. Relationship of parameters to sea surface temperature The pronounced broad-scale variability observed in the taxonomic composition of the natural phytoplankton communities, as well as FRR derived parameters, was further investigated IFF

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Fig. 9. Plots of SST vs. the following environmental and physiological parameters: (a) N, (b) surface silicate concentration, (c) Fv/Fm, (d) sPSII, (e) surface Chl a concentration, (  ) fluorescence derived, (K) HPLC derived, (f) ratio of PCs to Chl a, (g) a*pp, (h) estimated proportion of autotrophic carbon accounted for by diatoms (K) and coccolithophores (J), (i) ratio of fuco (K) and hex (J) to Chl a. Open symbols (J) in (b–d) indicate stations with corresponding HPLC measurements. Two stations associated with mesoscale activity in the vicinity of the IFF and one mixed station on the Faroes shelf are labelled in (a). Examples of significant linear relationships are indicated by model II regression lines for regions south of IFF in (a, R2 ¼ 0:29 or 0.40 without stations on Faroes shelf and in vicinity of IFF), (c, R2 ¼ 0:40), (d, R2 ¼ 0:46), (f, R2 ¼ 0:71) and (g, R2 ¼ 0:67), po0:001 for all.

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Values of Fv/Fm and sPSII were both functions of SST south of the IFF with 40% and 46% of the variance in these parameters explained, respectively (Fig. 9c and d). North of the IFF a reduction in Fv/Fm and increase in sPSII with decreasing SST was observed. Patterns of variability in the surface Chl concentration were less clear although the majority of stations with Chl a42 mg m3 were found at SSTs between 7 and 9 1C (Fig. 9e). Parameters calculated from the HPLC data displayed patterns related to SST south of the IFF, with the ratio of PCs to Chl a and hence a*pp(478) increasing towards the south of the basin (Fig. 9f and g). Microscope and pigment-based assessment of the contribution of the dominant phytoplankton groups displayed the previously mentioned trends, with a shift from diatom dominance in the north of the study region to coccolithophores and other nanoflagellates in the south (Fig. 9h and i).

4. Discussion 4.1. Potential causes of variability in Fv/Fm A number of non-physiological factors have the potential to affect measured values of Fv/Fm, including dissolved fluorescence and particulate fluorescence from Chl degradation products (Geider et al., 1993a; Olaizola et al., 1996; Fuchs et al., 2002). Particulate fluorescence from Chl degradation products could not be fully discounted from the current data set and may have resulted in our measured values of Fv/Fm being underestimates of the maximum photochemical quantum efficiency (Fuchs et al., 2002). However, HPLC data indicated low ratios of phaeophytin to Chl (o0.1). Together with relatively low dissolved fluorescence this provided confidence in the measured values. Observed values of Fv/Fm were around the maximum (0.65) previously measured on nutrient rich cultures within the diatom blooms to the southwest of Iceland (Kolber et al., 1988; Kolber and Falkowski, 1993) (Figs. 7e and 9c). These high values of Fv/Fm are consistent with a high maximum photochemical efficiency under condi-

tions of adequate nutrients, a situation that might be expected during the early stages of the spring bloom. Throughout the majority of the remaining study area, measured values of Fv/Fm were lower than the assumed maximum. Such variability is frequently ascribed to a reduction in the proportion of functional PSII reaction centres due to nutrient starvation (Kolber et al., 1990; Kolber and Falkowski, 1993; Geider et al., 1993a; Olaizola et al., 1996; Suzuki et al., 2002). Station averaged values of Fv/Fm were correlated with variability in F0/Chl a and Fm/Chl a with 82% and 70% of the variance, respectively, (n ¼ 20) explained (Fig. 10a). Higher F0/Chl a and Fm/Chl a in combination with lower Fv/Fm was also found by Olaizola et al. (1996) and was inferred to be indicative of nutrient stress in keeping with laboratory data (Cleveland and Perry, 1987). Although Fv/Fm was positively correlated with both the surface silicate and nitrate concentrations (Fig. 8d and e), surface nitrate concentrations throughout the study region were typically much higher than those likely to be limiting for phytoplankton growth (Fig. 8e). Also values of Fv/Fm did not approach the low values (0.3–0.4) that have been observed in natural populations under conditions of very low ambient nitrate (Kolber et al., 1990; Geider et al., 1993a; Babin et al., 1996; Olaizola et al., 1996; Moore et al., 2003). Thus, the positive correlation between the ambient nitrate concentration and Fv/Fm was unlikely to have been causative (Fig. 8e). Surface silicate concentrations were often lower than those likely to be limiting for diatom growth (Azam and Chisholm, 1976; Egge and Aksnes, 1992; Brown et al., 2003). Lippemeier et al. (1999) presented evidence of a reduction in Fv/Fm for a diatom culture under conditions of silicate starvation. We could thus hypothesise that the decreased Fv/Fm values in low silicate regions resulted from the contribution of a declining population of silicate limited diatoms from earlier stages of the bloom. However, Lippemeier et al. (1999) also report that F0/Chl a and Fm/Chl a decrease with silicate starvation, which contrasts with the data presented here (Fig. 10a). Given the lack of a clear

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Fig. 10. Relationships between FRR fluorometer derived and independent bio-optical parameters. (a) Station mean fluorescence to Chl a ratio vs. Fv/Fm. Values of F0/Chl and Fm/Chl are plotted against Fv/Fm as estimated from in situ FRR fluorometer profiles (see text and Fig. 6) for the stations (n ¼ 20) where HPLC data were obtained. (b) sPSII vs. mean cell volume (R2 ¼ 0:27 or 0.37 for log transformed data, po0:001; n ¼ 40). (c) a*pp vs. sPSII (R2 ¼ 0:47; po0:001; n ¼ 20). Dotted line indicates the expected relationship between a*pp and sPSII for constant RCII:Chl a (=0.002), with cmax ¼ 0:65 and negligible packaging (see text). p

physiological mechanism relating loss of PSII efficiency to silicate limitation in diatoms, the possibility of lower Fv/Fm directly resulting from silicate limitation remains equivocal. If the values of Fv/Fm lower than 0.65 were not caused by a reduction in the proportion of functional reaction centres, then variability in the maximal value of Fv/Fm between different phytoplankton groups may have been responsible. A lower transfer efficiency between the carotenoids and Chl a within the antenna or higher reaction centre quenching could both result in lower Fv/Fm. Further study is needed to assess the causes and degrees of interspecific variability in maximal Fv/Fm before changes in this parameter between natural communities can be unambiguously interpreted.

4.2. Reconstructed absorption spectra, cell size and sPSII The calculation of absorption coefficients from HPLC data is subject to a number of assumptions (see above and e.g. Marra et al., 2000). Further, calculated values of a*Tpig and a*pp correspond to the Chl specific absorption of the phytoplankton pigments in the absence of any package effect (Duysens, 1956; Morel and Bricaud, 1981; Berner et al., 1989). The in vivo Chl a specific absorption coefficient, which we designate a*ph, will be a function of both the pigment composition and packaging, thus we expect that aph ¼ aTpig Q ;

(3)

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where Q is some factor (p1) which accounts for the reduction of absorption by the pigments as self-shading increases within the cell. The package effect is greater for larger cells (Morel and Bricaud, 1981) and recent work has shown that the majority of the variability in absorption within natural phytoplankton communities can be explained by cell size (Ciotti et al., 2002). The decrease in both a*Tpig(478) and a*pp(478), within diatom dominated communities (Fig. 9g–i), would therefore have resulted in lower a*ph. However, a further relative decrease in a*ph is also expected due to an increased cell size and hence larger package effect. Theoretical estimates of Q* calculated following Morel and Bricaud (1981) ranged from 0.6 to 0.9 (Appendix A). However, the accuracy of these estimates was difficult to assess given the wide range of cell sizes within any given community. As with a*ph, a reduction in sPSII might be expected under conditions of increased packaging and has been observed in the laboratory (Greene et al., 1991; Geider et al., 1993b). Communities dominated by larger cells may therefore be expected to have a lower sPSII. Such a relationship was consistent with the current data set, where a significant negative correlation (R2 ¼ 0:27 or 0.37 for log transformed data, po0:001; n ¼ 40) was observed between sPSII and the mean community cell volume as estimated by microscopy (Fig. 10c). The functional absorption cross section is related to absorption by pigments that transfer excitation energy to the PSII reaction centre. In agreement with these expectations, station mean values of sPSII were positively correlated with a*pp (R2 ¼ 0:47; po0:001; n ¼ 20) (Fig. 10e). For the reduced data set (n ¼ 17) where both a*pp and mean cell volume were available, 47% and 55% of the variance in sPSII were explained by pigments and size, respectively, while the product of a*pp and estimated Q* combined to explain 58% of the variance in sPSII. The natural variability of PSII:Chl a, an important component of biophysical models for the estimation of electron transport, is currently poorly constrained (Kolber and Falkowski, 1993; Suggett et al., 2001, 2004). The functional absorption cross section is expected to be related to a*pp

and PSII:Chl a by sPSII PSII : Chl a ¼ app Q cT 0:5;

(4)

where cT is the transfer efficiency and 0.5 is a factor to account for the proportion of absorbed energy which is transferred to PSII as opposed to PSI (Dubinsky et al., 1986; Mauzerall and Greenbaum, 1989; Suggett et al., 2004). Using Eq. (4) and assuming Q ¼ 1 and cT ¼ 0:65 (Kolber et al., 1988), the data were found to be bounded by values of PSII:Chl a from 0.0012 to 0.0025 mol PSII (mol Chl a)1 (Fig. 10e). Pigment packaging was likely to have resulted in these values being overestimated by around 10–40% (Appendix A). Derived values of PSII:Chl a were within the reported range for eukaryotic laboratory cultures (Falkowski et al., 1981; Dubinsky et al., 1986; Greene et al., 1991; Suggett et al., 2004) and close to the average value of 0.002 suggested by Kolber and Falkowski (1993). The taxonomically driven variability in pigment composition and packaging therefore controlled a large proportion of the variability in sPSII. Assessment of the relative contribution of these factors was, however, complicated by the covariance of cell size and pigment composition, which frequently occurs in marine ecosystems (Yentsch and Phinney, 1989; Bricaud et al., 1995; Ciotti et al., 2002). 4.3. Bloom succession in different biogeographic provinces Due to the nature of the survey and the time taken to cover the extensive study region, the maps of SST, surface nutrient concentrations and physiological variability (Fig. 7) could only be considered quasi-synoptic at best. The data in the present study were collected across two major biomes (sensu Longhurst, 1998), those regions to the north and south of the IFF. North of the IFF, the polar biome is classically characterised by an early spring bloom initiated around March. South of the IFF, within the Westerlies biome, the classical picture is one of a progression of the spring bloom northwards from around 30–401N again starting around March (Longhurst, 1998).

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Consistent with these general expectations and preceding arguments, the following working hypotheses are formulated. Stations north of the IFF were sampled after the initial stage of the spring bloom in these waters, when surface silicate concentrations were already depleted. The community was therefore principally composed of small flagellates exhibiting relatively low Fv/Fm and high sPSII. Conversely, south of the IFF, the main phase of the diatom spring bloom was sampled in towards the Reykjanes Ridge and was associated with high Fv/Fm and low sPSII. The decreasing Fv/Fm and increasing sPSII (as well as the related changes in bio-optical parameters derived from HPLC data, Figs. 9 and 10) with increasing stratification to the south of the region resulted from the spring bloom succession from diatoms to flagellates. The physiological state of PSII both in terms of absorption and efficiency therefore appeared to be an indicator of the state of the spring bloom, resulting from environmental forcing at broad (4meso-basin) scales, although the physiological meaning of the variations in Fv/ Fm remains unclear. Individual relationships were, however, relatively weak (Figs. 8 and 9). The observed patterns (Figs. 8 and 9) were likely to have reflected the large-scale ecological processes, upon which local environmental fluctuations were superimposed (Li, 2002). For example, considerable mesoscale variability was observed. Time lags between physical forcing, ecosystem response and nutrient drawdown was also likely to have contributed to the considerable unexplained variances between environmental variables and the largely taxonomically related physiological parameters.

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peared to be primarily related to taxonomic factors. The progression of the spring bloom from diatom to flagellate domination following increasing stratification and the depletion of silicate was thus the principal cause of the observed bio-optical variability. An increasingly accepted paradigm is that marine phytoplankton communities are composed from a background of smaller cells to which larger cells are added under conditions favourable for growth (Yentsch and Phinney, 1989; Chisholm, 1992; Li, 2002). In keeping with other recent work (Ciotti et al., 2002), the current study illustrates that these changes in community size structure, in response to environmental variability, result in broadly predictable variability in a number of biooptical parameters.

Acknowledgements The authors thank the officers and crew of the R.R.S. Discovery cruise D253 (FISHES) for their assistance. The FISHES scientific team provided support in the collection of data at sea, particular thanks go to Tim O’Higgins, David Hydes and Alex Mustard. Cathy Lucas aided with the HPLC analysis. Sam Laney kindly made his software for analysis of raw FRR Fluorometer data available and provided many helpful discussions on its use. We thank Patrick Holligan, David Suggett and two anonymous referees for comments that considerably improved earlier versions of the manuscript.

Appendix A 5. Summary and conclusions Marked changes in Fv/Fm and sPSII were observed over basin scales during the North Atlantic spring bloom. The extent to which both these physiological parameters were directly influenced by resource limitation, or indirectly reflected environmental forcing through shifts in community structure, could not be fully quantified. However, variability in sPSII in particular ap-

The dimensionless factor relating absorption in solution to that of cells (Q ) was estimated from (Morel and Bricaud, 1981) Q ¼ ð3=2ÞQðrÞ=r;

(A.1)

where QðrÞ ¼ 1 þ 2er =r þ 2er =r2

(A.2)

and r is the product of the absorption coefficient of cellular material acm and the cell size d. Cell size

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was taken as the mean equivalent spherical diameter for each of the samples. We assume that the absorption coefficient of cellular material can be estimated from the product of the Chl specific absorption of all the pigments in solution (a*Tpig(l)) and the cellular Chl concentration (ci). The latter term was estimated by regression of cellular biovolume estimated by microscopy against the measured Chl concentration (R2 ¼ 0:699; n ¼ 17) giving ci ¼ 2:7  106 (mg Chl a m3) comparable to other estimates (Morel and Bricaud, 1981). Concentrating on the wavelength required for comparison with FRRf estimates of sPSII we obtain acm(478) ranging from 0.6 to 1.2  105 m1 and hence Q ranging from 0.6 to 0.9. As noted in the text, considerable errors in many of these parameters are possible due to the variability of cell sizes and likely species specific differences in ci and acm within the mixed populations sampled.

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