Introduction
Antarctic waters constitute very productive areas of the world’s oceans on a short-term basis (Arrigo et al. Reference Arrigo, Worthen, Schnell and Lizotte1998) with photosynthetic eukaryotes being the major group responsible for primary production. Antarctic productivity is high during the summer, when ice melts and light levels are elevated, and declines to near zero during the long winter. Phytoplankton standing stocks in these waters are thought to be influenced mostly by water column stability, since most micro- and macronutrients have been shown to be abundant (Vernet et al. Reference Vernet, Martinson, Iannuzzi, Stammerjohn, Kozlowski, Sines, Smith and Garibotti2008). Freshwater input from sea ice and glaciers plays a critical role in water column stratification and light penetration, affecting phytoplankton photosynthesis, especially in coastal environments (Vernet et al. Reference Vernet, Martinson, Iannuzzi, Stammerjohn, Kozlowski, Sines, Smith and Garibotti2008, Gonçalves-Araujo et al. Reference Gonçalves-Araujo, de Souza, Tavano and García2015).
The western Antarctic Peninsula (WAP) has shown important decadal temperature changes not primarily associated with global temperature change drivers (Turner et al. Reference Turner, Lu, White, King, Phillips, Hosking, Bracegirdle, Marshall, Mulvaney and Deb2016). Environmental shifts within the WAP have resulted in changes in biomass and composition of primary producers (Montes-Hugo et al. Reference Montes-Hugo, Doney, Ducklow, Fraser, Martinson, Stammerjohn and Schofield2009, Gonçalves-Araujo et al. Reference Gonçalves-Araujo, de Souza, Tavano and García2015). However, the short timescale dynamics of phytoplankton size structure and the taxonomic identity of the main representatives are not well known. In the WAP, surface waters are mostly dominated by pico- and nanoplankton (0.2–3 µm and 3–20 µm, respectively) (Garibotti et al. Reference Garibotti, Vernet, Ferrairo, Smith, Ross and Quetin2003, Montes-Hugo et al. Reference Montes-Hugo, Vernet, Martinson, Smith and Iannuzzi2008, Lee et al. Reference Lee, Joo, Joo, Kim, Song, Jeon and Kang2015). However, occasional blooms of microphytoplankton (20–200 µm) contribute considerably to the high primary production and biomass observed in summer (Moline et al. Reference Moline, Prezelin and Schofield1997, Clarke et al. Reference Clarke, Meredith, Wallace, Brandon and Thomas2008, Schloss et al. Reference Schloss, Abele, Moreau, Demers, Bers, González and Ferreyra2012). In these waters, picophytoplankton is dominated by prasinophytes and haptophytes (Agawin et al. Reference Agawin, Agustí and Duarte2002, Gonçalves-Araujo et al. Reference Gonçalves-Araujo, de Souza, Tavano and García2015), while cryptophytes and small diatoms dominate the nanophytoplankton (Garibotti et al. Reference Garibotti, Vernet and Ferrario2005). Diatoms and dinoflagellates, from the Thalassiosira, Fragilariopsis and Heterocapsa genera, are mostly found in the microplankton (Piquet et al. Reference Piquet, Bolhuis, Davidson, Thomson and Buma2008, Gonçalves-Araujo et al. Reference Gonçalves-Araujo, de Souza, Tavano and García2015, Pearson et al. Reference Pearson, Lago-Leston, Cánovas, Cox, Verret, Lasternas, Duarte, Agustí and Serrão2015).
Fildes Bay (King George Island) is located at the north-western tip of the WAP. In this coastal region, Lee et al. (Reference Lee, Joo, Joo, Kim, Song, Jeon and Kang2015) estimated the average contribution of pico- and nanophytoplankton between 1996 and 2008 to be 63% of the total chl a and 86% of cell abundance. Molecular diversity and community composition analyses using high-throughput sequencing of the 18S rRNA gene for the <20 µm size fraction indicated that the dominant taxa belonged to dinoflagellates, cryptophytes, prymnesiophytes, diatoms and chlorophytes (Luo et al. Reference Luo, Li, Gao, Yu, Lin and Zeng2015). More recently, Moreno-Pino et al. (Reference Moreno-Pino, De la Iglesia, Valdivia, Henríquez-Castillo, Galán, Díez and Trefault2016), using high-throughput sequencing of the 16S rRNA plastidial gene, showed that these waters are dominated by diatoms, haptophytes and cryptophytes.
Different methodological approaches have been used to characterize phytoplankton dynamics in Antarctic coastal waters. Most studies have relied on chl a and microscopic observations (Wright et al. Reference Wright, Ishikawa, Marchant, Davidson, van den Enden and Nash2009, Lee et al. Reference Lee, Joo, Joo, Kim, Song, Jeon and Kang2015). Flow cytometry has also been used to determine the abundance of different photosynthetic populations in Antarctic waters (Boyd et al. Reference Boyd, Watson, Law, Abraham, Trull, Murdoch, Bakker, Bowie, Buesseler, Chang, Charette, Croot, Downing, Frew, Gall, Hadfield, Hall, Harvey, Jameson, LaRoche, Liddicoat, Ling, Maldonado, Mckay, Nodder, Pickmere, Pridmore, Rintoul, Safi, Sutton, Strzepek, Tanneberger, Turner, Waite and Zeldis2000, Díez et al. Reference Díez, Massana, Estrada and Pedrós-Alió2004). Molecular fingerprinting techniques, such as denaturing gradient gel electrophoresis (DGGE) and terminal-restriction fragment length polymorphism (T-FRLP), have allowed the rapid characterization of phytoplankton composition (Baldwin et al. Reference Baldwin, Moss, Pakulski, Catala, Joux and Jeffrey2005, Piquet et al. Reference Piquet, Bolhuis, Davidson, Thomson and Buma2008). Traditionally, these fingerprinting techniques have used the 18S rRNA gene, which targets all eukaryotes. The use of the plastidial 16S rRNA gene greatly enhances the specificity of these approaches, since it selectively targets photosynthetic groups (Henríquez-Castillo et al. Reference Henríquez‐Castillo, Rodríguez‐Marconi, Rubio, Trefault, Andrade and De la Iglesia2015, Moreno-Pino et al. Reference Moreno-Pino, De la Iglesia, Valdivia, Henríquez-Castillo, Galán, Díez and Trefault2016).
Here, the hypothesis that Antarctic phytoplankton experiences rapid changes in response to water column conditions over short timescales was tested. The phytoplankton dynamics in Fildes Bay were examined over 12 days in February 2012 using size fractionation of chl a, microscopy, flow cytometry and T-RFLP of the plastidial 16S rRNA gene. Our data reveal a dramatic change in phytoplankton biomass and composition following a water column mixing event.
Methods
Study site and sampling
Seawater samples were collected in Fildes Bay, King George Island, at Station 6 (62°12'11''S, 58°55'15''W) using 5 l Niskin bottles on eight different days between 4–15 February 2012 (Fig. 1 and Table I). Samples were taken near the surface (5 m) and at a depth corresponding to 10% of the surface photosynthetic active radiation (PAR) (9–26 m, Table I). Samples were prefiltered on board through a 100 µm mesh, stored in sterile plastic carboys and kept in darkness until further processing. Once at the laboratory (<2 h later), subsamples for chl a, flow cytometry, microscopy and molecular analyses were taken.
Location of the sampling area in Fildes Bay, King George Island, Antarctica.
Sampling date, depth, and environmental and cell abundance data.
CRY=cryptophytes, n.a.=not available, PAR=photosynthetic active radiation, PNE=photosynthetic nanoeukaryotes, PPE=photosynthetic picoeukaryotes, T-RFLP=terminal-restriction fragment length polymorphism.
Physicochemical parameters
Temperature (SST), salinity and PAR measurements were obtained using a CTD SBE 911 plus (SeaBird Electronics) equipped with an auxiliary biospherical PAR sensor (LiCor LI-193). The CTD casts were processed and validated with the SBE data processing software version 7.23.2.
Chlorophyll determination
Total and fractionated chl a were determined from triplicate 100 ml subsamples. For total chl a, biomass (<100 µm) was collected on 25 mm diameter GF/F filters (Whatman). For fractionated chl a, seawater samples were filtered through 20 µm (Nylon, Millipore) and 3 µm (Polycarbonate, Millipore) pore size filters. The biomass recovered from each fraction was collected on 25 mm diameter GF/F filters (Whatman) to obtain chl a<20 µm and chl a<3 µm, respectively. Filtration was completed in the dark immediately after the samples arrived to the laboratory. Chlorophyll a and pheopigments were determined by fluorometry. Pigments were extracted in 90% acetone for 24 h at -20°C and analysed on a Turner Designs Trilogy fluorometer, according to the method of Holm-Hansen et al. (Reference Holm-Hansen, Lorenzen, Holmes and Strickland1965). Calibration was made with a chl a standard (Sigma-Aldrich).
Abundance of photosynthetic eukaryotes by flow cytometry
Subsamples of 1.35 ml were taken in triplicates, fixed with 150 µl of fixative (1% paraformaldehyde, 0.5% glutaraldehyde, 100 mM sodium borate, pH 8.4), incubated for 20 min at room temperature and fast frozen in liquid nitrogen. Photosynthetic eukaryote abundances were enumerated with a ‘jet-in-air’ influx flow cytometer (Becton Dickinson) using blue 488 nm and red 640 nm lasers. Particles were differentiated by forward angle light scatter and trigger pulse width from the 488 nm laser, and red fluorescence (692/40 nm) detection from the 488 and 640 nm lasers. Fluorescent Ultra Rainbow Beads (3 µm, Spherotech) were used for calibration. Each sample was run at an average flow rate of 47 µl min-1 for 5 min. Analyses were performed with the FlowJo software (Tree Star).
Abundance of microplankton by light microscopy
Duplicate 50 ml seawater subsamples were taken every day and fixed with 1% formaldehyde and counted using the Utermöhl’s method (Hasle Reference Hasle1978). The microplankton was counted at 400x in 15 random fields or by counting cells throughout the whole settling chamber, depending on the density of cells, under phase contrast microscopy using a Nikon Eclipse T100 microscope. All organisms with a length >20 µm were counted.
DNA extraction
Samples of 4.5 l of seawater were size fractionated using a peristaltic pump (Cole-Palmer) by sequential filtration using 47 mm diameter Swinnex filter holder (Millipore), and 60 µm, 20 µm (Nylon, Millipore), 12 µm, 3 µm and 0.2 µm (Polycarbonate, Millipore) pore size filters. Filters were stored in 2 ml cryovials at -196°C or -80°C until analysis. All steps were performed under sterile conditions. Filters were thawed and half of the filters were cut into small pieces, while the other half was kept at -20°C as backup. Each half-filter was incubated in lysis buffer (TE 1x/NaCl 0.15 M), with 10% SDS and 20 mg ml-1 proteinase K at 37°C for 1 h. DNA was extracted using 5 M NaCl and hexadecyl-trimethyl-ammonium bromide (CTAB) extraction buffer (10% CTAB, 0.7% NaCl) and incubated at 65°C for 10 min before protein removal using a conventional phenol-chloroform method. DNA was precipitated using ethanol at -20°C for 1 h and resuspended in 50 µl Milli-Q water (Millipore). DNA integrity was evaluated by agarose gel electrophoresis and quantified using a fluorometric assay (Qubit 2.0 fluorometer).
Terminal-restriction fragment length polymorphism
Phytoplankton composition was determined by T-RFLP analysis for three sampling days: 4, 7 and 11 February (see Table I). The plastid 16S rRNA gene was amplified by polymerase chain reaction (PCR) with plastidial biased primers PLA491F (Fuller et al. Reference Fuller, Campbell, Allen, Pitt, Zwirglmaier, Le Gall, Vaulot and Scanlan2006), labelled at the 5' end with the fluorochrome NED, and OXY1313R (West et al. Reference West, Schönhuber, Fuller, Amann, Rippka, Post and Scanlan2001). The PCR mixture (25 µl final volume) contained 1.2 mM MgCl2, 1X buffer, 0.2 mM dNTPs, 0.75 mM of each primer, 2.5 U KAPA Taq polymerase and 15–40 ng µl-1 of DNA. The amplification conditions included one step at 94°C for 5 min, 30 cycles of 95°C for 30 sec, 60°C for 45 sec and 72°C for 1 min, and a final elongation at 72°C for 6 min.
Four restriction enzymes (HaeIII, RsaI, HhaI and AluI) were tested to determine the one that best discriminates between the different phylotypes present in the samples. The labelled PCR products were digested independently with the four restriction enzymes. Restriction reactions comprised 2.5U of restriction enzyme and 1X buffer (Promega) in a final volume of 20 µl at 37°C overnight. The restriction fragments were precipitated using 3 M sodium acetate and 100% v/v ice-cold ethanol (2.5 v) at -80°C for 1 h, centrifuged at 20 000 g at 4°C for 30 min, washed with 70% v/v ice-cold ethanol, again centrifuged at 20 000 g at 4°C for 30 min, air-dried and resuspended in a final volume of 20 µl of Milli-Q water (Millipore). The T-RFLP analyses were conducted at Macrogen, Seoul, using the internal size standard LIZ1200. Raw T-RFLP data were handled as previously described (Henríquez-Castillo et al. Reference Henríquez‐Castillo, Rodríguez‐Marconi, Rubio, Trefault, Andrade and De la Iglesia2015). The average number of terminal-restriction fragments (T-RFs) obtained for HaeIII, RsaI, HhaI and AluI were nine, ten, six and five, respectively. Since restriction enzymes HaeIII and RsaI appeared the most resolutive, all subsequent analyses were performed using only these two enzymes.
In silico analysis of terminal-restriction fragments
For taxonomic assignment of OTUs detected in the T-RFLP profiles, an in silico restriction analysis was performed, with the restriction enzymes HaeIII and RsaI, using Mothur software (Schloss et al. Reference Schloss, Westcott, Ryabin, Hall, Hartmann, Hollister, Lesniewski, Oakley, Parks, Robinson, Sahl, Stres, Thallinger, van Horn and Weber2009). For this, sequences from major marine phytoplankton taxonomic groups (Dinophyceae, Cryptophyceae, Prasinophyceae, Prymnesiophyceae, Bacillariophyceae, Chlorophyceae, Mamiellophyceae) were retrieved from the PhytoREF database (Decelle et al. Reference Decelle, Romac, Stern, Bendif, Zingone, Audic, Guiry, Guillou, Tessier, Le Gall, Gourvil, Dos Santos, Probert, Vaulot, de Vargas and Christen2015), to which the 16S plastidial sequences previously obtained from Fildes Bay were added (GenBank KT964300-KT964307). After PLA491 primer alignment, restriction sites for the two enzymes were detected. Finally, the size of the in silico T-RF were compared with the observed T-RF. Taxonomic assignation was achieved i) with a ±2 nucleotides threshold and ii) checking for the presence of the peak of the taxon in both HaeIII and AluI restriction profiles.
Statistical analysis
Linear regression analyses were performed to test relationships between total and fractionated chl a using Prism 6.0 (GraphPad). The T-RFLP fingerprinting profiles were analysed using Primer 6 (Primer-E). Profiles were standardized and square root transformed. Starting with 92 T-RFLP HaeIII profiles obtained, an initial filter of those replicates not matching a 60% Bray–Curtis coefficient of similarity threshold, based on the relative abundances of each T-RFs, was applied. This filter reduced the total number of T-RFLP profiles to 55, which were used in further analyses (Table S1 found at http://dx.doi.org/10.1017/S0954102016000699). The resulting similarity matrix was used to obtain hierarchical cluster and non-metric multidimensional scaling (NMDS), for visual interpretation of the grouping and sorting of the data in a two-dimensional space. To evaluate statistically significant differences between size fractions, according to the relative abundances of taxonomic groups, analyses of similarity (ANOSIM) were performed based on the Bray–Curtis distance matrix. To explore the most important T-RFs for each group, SIMPER analysis were conducted. Spearman rank correlation analysis was performed to test the correlation between T-RFLP HaeIII and T-RFLP RsaI profiles using the Relate function in Primer 6 (Primer-E).
Results
Characterization of sampling site
Fildes Bay is a typical fjord-like Antarctic embayment located on King George Island (Fig. 1). In this bay, vertical profiles (down to 50 m) of temperature and salinity (Fig. 2) were measured over 12 days in February 2012. Temperature and salinity ranged from 1–2.25°C and 33.8–34.2, respectively. On 7 February, PAR surface maximum was 650 µmol photons m-2 sec-1. A reduction in light penetration through the water column was observed during the sampling as evidenced by the decrease of 10% PAR depth, which was 26 m at the beginning of the sampling period vs 9 m at the end (Table I).
Temporal variation of physicochemical parameters (temperature, salinity, photosynthetic active radiation (PAR) and density) in Fildes Bay, King George Island. Filled circles below the x-axis represent the days when DNA samples were collected.
During the first two sampling days, 4 and 6 February, the water column was stratified with warmer waters at the surface. This was followed by a vertical mixing episode from 7–11 February (as shown in Fig. 2) that probably injected nutrients into the euphotic layer. Unfortunately, weather conditions between 7–11 February did not allow sampling. Afterwards, the water column tended to re-stratify with warmer surface waters until the last day of sampling when it mixed again.
Size fractionated chlorophyll a
Chlorophyll a levels were low at the beginning of the sampling period, with a steady increase after 6 February reaching >10 mg m-3 chl a at the surface on the last day of sampling. Values for surface samples were higher than those from samples at 10% PAR (Fig. 3a). During the sampling period until 13 February, phytoplankton biomass in Fildes Bay was dominated by nanoplankton (Fig. 3b), with chl a<20 µm accounting for 98% of total chl a. Nano- and picoplankton chl a were highly correlated with total chl a (r 2 =0.96, P=0.0001, n=7 and r 2 =0.99, P<0.0001, n=7, respectively). A sharp increase in total chl a was observed at the surface on 13 and 14 February, indicating a shift towards the microplankton size class (Fig. 3a).
Chlorophyll a and b. phytoplankton abundance during the sampling period. Filled symbols correspond to surface samples and open symbols to 10% photosynthetic active radiation (PAR) samples. Filled circles below the x-axis represent the days when DNA samples were collected. CRY=cryptophytes, PNE=nanoeukaryotes, PPE=picoeukaryotes.
Short timescale dynamics of phytoplankton abundance
Flow cytometry analysis indicated the presence of three major photosynthetic groups: picoeukaryotes (PPE), nanoeukaryotes (PNE) and a small group of phycoerythrin-containing nanoeukaryotes corresponding to cryptophytes (CRY). While the abundance of PPE and CRY was stable during the sampling period, with an average abundance of 1.2±0.4x103 and 0.8±0.4x103 ml-1, respectively, PNE increased sharply after the first sampling day and remained three times more abundant than PPE and CRY thereafter (Fig. 3b).
Microscopic observations indicated the presence of different cell sizes of Thalassiosira sp., as well as Pseudo-nitzschia sp. and others species of pennate diatoms (Fig. 4 and Table II). These analyses showed a large increase of Thalassiosira sp. (>20 µm) on 13 February in surface (sample M17) in concordance with the increase in total chl a (Fig. 3a and Table II). This event followed the mixing episode that took place between 7–11 February.
Phase contrast light microscopy of microphytoplankton. Scale bars represent 50 µm. a. Centric planktonic diatom Thalassiosira sp. valve view. b. Pennate epiphytic diatom Licmophora sp. cell in girdle view, separated from a colony. c. Colonies of the centric planktonic diatom Thalassiosira sp. in girdle view. d. Pennate planktonic diatom Nitzschia sp. e. Pennate diatom. f. Pennate planktonic diatom Cocconeis sp.
Abundance of microphytoplankton estimated by light microscopy.
Photosynthetic eukaryotes: diversity and structure
Plastidial 16S rRNA gene fingerprints obtained from three sampling days: 4, 7 and 11 of February with the restriction enzymes HaeIII and RsaI (Tables S2 & S3 found at http://dx.doi.org/10.1017/S0954102016000699) showed a high correlation between the abundance matrices; therefore, only the results for HaeIII are presented (Spearman rank correlation ρ: 0.8, P<0.0001). From T-RFLP HaeIII, six T-RFs accounted for >90% of relative abundances (Table III and Table S2): 427, 245, 252, 434, 440 and 836. In silico restriction analysis using the PhytoREF plastidial 16S rRNA gene database enabled the identification of four of these six T-RFs (Table III). Taxonomic identification was achieved at the class level for three of the identified T-RFs (T-RFs 252, 434 and 440) and order level for T-RF 836 (Table III). As T-RF 252 matched several plastidial 16S rRNA sequences from different cryptophytes species, Teleaulax acuta (Butcher) Hill and Geminigera cryophila (Taylor & Lee) Hill (family Geminigeraceae, order Pyrenomonadales), Pyrenomonas salina (Wislouch) Santore (family Pyrenomonadaceae, order Pyrenomonadales), and Cryptomonas curvata Ehrenberg and C. paramecium (Ehrenberg) Hoef-Emden & Melkonian (family Cryptomonadaceae, order Cryptomonadales), it could only be assigned at the class level (Cryptophyceae). Since T-RF 434 corresponded to Phaeocystis antarctica Karsten (family Phaeocystaceae, order Phaeocystales) and Emiliania huxleyi (Lohmann) Hay & Mohler (family Noelaerhabaceae, order Isochrysidales) it was also assigned at the class level (Prymnesiophyceae). As T-RF 440 corresponded to Thalassiosira antarctica Comber, T. punctigera (Castracane) Hasle and Minidiscus trioculatus (Taylor) Hasle (family Thalassiosiraceae, order Thalassiosirales), but also to Skeletonema costatum (Greville) Cleve (family Skeletonemataceae, order Thalassiosirales) and Phaeodactylum tricornutum Bohlin (family Phaeodactylaceae) it was assigned as Bacillariophyceae. Since T-RF 836 matched Ostreococcus lucimarinus Palenik et al. and Bathycoccus prasinos Eikrem & Throndsen (family Bathycoccaceae) but also Mantoniella squamata (Manton & Parke) Desikachary (family Mamiellaceae) it could be assigned to the order Mamiellales (class Mamiellophyceae). Neither T-RF 245 nor T-RF 427 corresponded to any sequence available for photosynthetic eukaryotes, or even cyanobacteria. These two RFs may correspond to species for which no plastid 16S rRNA sequence is available in public databases. Taxonomic assignment was corroborated using the T-RFs obtained with RsaI (see Table III).
Taxonomic assignment of the HaeIII terminal-restriction fragments (T-RFs).
a Other representatives from the same taxonomic classification that match the T-RF size.
b Corresponds to the T-RF in the RsaI profile.
N.A.=non-assigned, SD=standard deviation.
Taxonomic classification according to the PhytoREF database (July 2015).
Analysis of the main T-RFs indicates a transition in taxonomic composition of size fractionated phytoplankton through time (Fig. 5a & b). On 4 February, phytoplankton was dominated by Prymnesiophyceae and Bacillariophyceae, while on the following days (7 and 11 February) Bacillariophyceae were practically absent. During these days, T-RF 427 (not assigned) and Mamiellales showed an increase in relative abundance. Cryptophyceae were detected at the beginning of the sampling period, with predominance in the 0.2–3 µm and 3–12 µm size fractions. At the surface, Cryptophyceae were detected only on 11 February, despite been present in all surface samples analysed by flow cytometry (Fig. 3b).
Taxonomic distribution of the main phytoplankton groups (a. and b.) and hierarchical cluster (c. and d.) as determined from T-RFLP HaeIII profiles of the plastid 16S rRNA gene. Bars represent the relative abundance of terminal-restriction fragments (T-RFs) belonging to a given class. ‘Others’ corresponds to T-RFs <5% of relative abundance. Size fraction was used as factor for Bray–Curtis similarity analyses. a. and c. =surface samples, b. and d. =10% photosynthetic active radiation (PAR) samples.
Hierarchical cluster analyses based on Bray–Curtis dissimilarities of the T-RFLP HaeIII profiles clearly differentiated samples (<20% similarity) into two main groups based on sampling date (Fig. 5c & d). This differentiation was supported by ANOSIM analysis (R=0.639, P=0.1%). In addition, SIMPER analysis indicates that four T-RFs were responsible for similarities: 252 (Cryptophyceae), 434 (Prymnesiophyceae), 440 (Bacillariophyceae) and 832 (Mamiellophyceae). Moreover, inside each cluster, samples differentiated between size fractions.
Relative contributions of the T-RFs responsible for the differences observed between size fractions were visualized by NMDS (Fig. 6). Based on this analysis, Prymnesiophyceae and Cryptophyceae were dominant in the 0.2–3 µm and 3–12 µm size fractions (Fig. 6a & b), Bacillariophyceae in the 12–20µm and 20–60µm size fractions (Fig. 6d) and Mamiellophyceae were mainly present in the microphytoplankton size fractions (20–60 µm and 60–100 µm) (Fig. 6e). Similar results were obtained after in silico assignment of the RsaI T-RFLP profiles (Table III and Tables S2 & S3).
Non-metric multidimensional scaling analysis of T-RFLP HaeIII profiles of the plastid 16S rRNA gene during summer 2012. a. Sample grouping was performed according to size fraction and dotted circles represent >60% similarity between samples, based on hierarchical cluster analysis of the terminal-restriction fragment length polymorphism (T-RFLP) data. R value corresponds to ANOSIM test between size fractions groups. b.–e. Relative abundance of the main terminal-restriction fragments (T-RFs) that contribute to the difference between photosynthetic eukaryote size fractions. The relative abundance of a given T-RF is indicated by the size of the circle. b. =T-RF 252, Cryptophyceae, c. =T-RF 434, Prymnesiophyceae, d. =T-RF 440, Bacillariophyceae and e. =T-RF 836, Mamiellophyceae.
Discussion
Size fractionation of chl a, microscopy, flow cytometry and T-RFLP of plastidial 16S rRNA gene analyses were combined to follow the short timescale dynamics of phytoplankton abundance and composition in Fildes Bay, WAP, for 12 days in February 2012. In this study, the hypothesis that Antarctic phytoplankton experiences prompt changes in response to water column conditions during short timescales was tested.
While nutrients are drivers of the phytoplankton composition in many oceanic waters, shallow coastal Antarctic waters are rarely nutrient limited (Agawin et al. Reference Agawin, Agustí and Duarte2002). In the case of Fildes Bay, reported concentrations are of the order of 2 µM for PO4 –3, 0.2 µM for NO2 –, 30 µM for NO3, 80 µM for SiO3 and 1.5 µM for NH4 (Lee et al. Reference Lee, Joo, Joo, Kim, Song, Jeon and Kang2015, Luo et al. Reference Luo, Li, Gao, Yu, Lin and Zeng2015), far from being considered as limiting. In contrast, phytoplankton in Antarctic waters is strongly influenced by the stability of the water column (Garibotti et al. Reference Garibotti, Vernet and Ferrario2005, Piquet et al. Reference Piquet, Bolhuis, Meredith and Buma2011, Marañon et al. Reference Marañon, Cermeño, Latasa and Tadonléké2012, Smith et al. Reference Smith, Ainley, Arrigo and Dinniman2014). Indeed, our results show that Antarctic coastal phytoplankton responds rapidly to changes in the water column stability. Phytoplankton responses to water column stability have been clearly observed over the long term along the WAP (Montes-Hugo et al. Reference Montes-Hugo, Doney, Ducklow, Fraser, Martinson, Stammerjohn and Schofield2009, Gonçalves-Araujo et al. Reference Gonçalves-Araujo, de Souza, Tavano and García2015), but few data exist for short timescales (Garibotti et al. Reference Garibotti, Vernet, Ferrairo, Smith, Ross and Quetin2003, Moreno-Pino et al. Reference Moreno-Pino, De la Iglesia, Valdivia, Henríquez-Castillo, Galán, Díez and Trefault2016).
Values for seawater physicochemical parameters were consistent with previous reports for the same time of the year in Fildes Bay (Chang et al. Reference Chang, Jun, Park and Eo1990, Schloss et al. Reference Schloss, Abele, Moreau, Demers, Bers, González and Ferreyra2012, Lee et al. Reference Lee, Joo, Joo, Kim, Song, Jeon and Kang2015). At the beginning of the sampling period, the water column was stratified (Fig. 2) with low chl a concentration (Fig. 3a) and low phytoplankton abundance (<1x103 cell ml-1; Fig. 3b). As the stability of the water column decreased (7–11 February; Fig. 2), both chl a levels and phytoplankton abundance started to increase, with a clear dominance of the nano-sized fraction until the end of the sampling period (Fig. 3). After 11 February, the water column tended to stratify again with a marked increase in both chl a and cellular abundances, particularly from the PNE group. Warmer surface waters lasted until the last day of sampling when the water column mixed again, showing the highest biomass, as measured by chl a and cell numbers. However, the lack of data from 8–10 February prevents further interpretation of the development of the vertical structure disturbance of the water column.
Phytoplankton composition changed through time in response to water column stability (Fig. 5a & b). At the beginning of the sampling period, the phytoplankton, which was in low abundance, was dominated by Prymnesiophyceae (<12 µm size fraction) and Bacillariophyceae (>12 µm size fraction). After the mixing event, taxonomic composition clearly changed (Fig. 5c & d) with a dominance of diatoms (Thalassiosira) and haptophytes (Phaeocystis), followed by cryptophytes and chlorophytes. Phaeocystis (class Prymnesiophyceae) was probably represented by both single-celled and colonial forms, as evidenced by T-RFLP results. The T-RFs assigned to Phaeocystis were detected as abundant in the 3–12 µm and 60–100 µm size fractions (Fig. 6c).
Diatoms identified by both microscopy and molecular techniques were similar to those previously identified in coastal Antarctic waters (Mendes et al. Reference Mendes, Tavano, Leal, de Souza, Brotas and García2013, Schloss et al. Reference Schloss, Wasilowska, Dumont, Almandoz, Hernando, Michaud-Tremblay, Saravia, Rzepecki, Monien, Monien, Kopczyńska, Bers and Ferreyra2014, Pearson et al. Reference Pearson, Lago-Leston, Cánovas, Cox, Verret, Lasternas, Duarte, Agustí and Serrão2015). They were dominant in the >12 µm size fraction (Fig. 6d & Table II), with both molecular and microscopy data being highly concordant. However, the low taxonomic resolution obtained with T-RFLP assignment did not allow precise determination of diatom taxonomic identity at the species level. Diatom abundance was very low at the beginning (Table II), in concordance with chl a data (Fig. 3a). While diatoms other than Thalassiosira and dinoflagellates dominated the microplanktonic compartment at the beginning of the sampling (Table II), i.e. when water column was stratified, a strong change in composition was evident after the mixing event occurred (Fig. 5a & b). By 13 February, a strong increase in Thalassiosira sp. abundance was observed (Table II), suggesting that this taxon was responsible for the increase in total chl a that day (Fig. 3a). An increase in Thalassiosira after mixing events has been observed previously in other Antarctic regions (Mendes et al. Reference Mendes, Tavano, Leal, de Souza, Brotas and García2013).
Among Prymnesiophyceae (Haptophyta), although it also matches Emiliania, the T-RF obtained probably corresponds to Phaeocystis since other studies have shown that this genus is abundant in this region (Luo et al. Reference Luo, Li, Gao, Yu, Lin and Zeng2015, Moreno-Pino et al. Reference Moreno-Pino, De la Iglesia, Valdivia, Henríquez-Castillo, Galán, Díez and Trefault2016). Prymnesiophyceae sequences were dominant both in the 0.2–3 µm and 3–12 µm size fractions at the beginning of the sampling period (Fig. 5c & d, Tables II & III and Tables S1–S3). Later, it was detected in both the 3–12 µm and 60–100 µm size fractions (Fig. 6c). The change between the unicellular and colonial life stages of Phaeocystis (Whipple et al. Reference Whipple, Patten and Verity2005) could easily explain the dominance of this organism in the nano- and microplankton fraction at different times and the observed increase in PNE abundance during the study (Fig. 3b). As water column mixing developed, Prymnesiophyceae was one of the dominant phytoplankton groups for the rest of the sampling period. Taken together, it is likely that Phaeocystis and Thalassiosira were responsible for the observed increase in chl a (Fig. 3). Arrigo et al. (Reference Arrigo, DiTullio, Dunbar, Robinson, VanWoert, Worthen and Lizotte2000) showed that P. antarctica dominates during spring in the Ross Sea when the water column is mixed and that their dominance is explained by their ability to photosynthesize under the reduced spring irradiances (Kropuenske et al. Reference Kropuenske, Mills, van Dijken, Bailey, Robinson, Welschmeyer and Arrigo2009) allowing them to out compete diatoms. This general pattern was also evidenced at a short timescale in Fildes Bay. However, comparisons, even when attractive, need to be interpreted with caution as these systems present different characteristics. More importantly, in this case timescales are indeed difficult to compare, as long-term data series aiming to understand the ecology and oceanography in Fildes Bay have not been established, in contrast to the Ross Sea (Smith et al. Reference Smith, Ainley, Arrigo and Dinniman2014).
Cryptophyceae have been previously observed in the study area (Luo et al. Reference Luo, Li, Gao, Yu, Lin and Zeng2015), as well as in other coastal Antarctic regions (Mendes et al. Reference Mendes, Tavano, Leal, de Souza, Brotas and García2013). The T-RF signature did not allow more precise assignment to either Pyrenomonadales (Geminigera) or Cryptomonadales (Cryptomonas). However, other molecular surveys have detected Geminigera as the dominant cryptophyte in Fildes Bay (Luo et al. Reference Luo, Li, Gao, Yu, Lin and Zeng2015). Cryptophytes showed low abundance during the sampling period, both in terms of cellular numbers and T-RF abundance, suggesting that they had little influence on chl a through the study period (see Figs 3b, 5a, 5b & 6); these findings are in agreement with pigment and microscopy studies that have shown that this group is rarely abundant (Marchant Reference Marchant1993, Garibotti et al. Reference Garibotti, Vernet, Ferrairo, Smith, Ross and Quetin2003).
Mamiellophyceae also contributed to the phytoplankton and were present in low abundances at the beginning of the sampling period, showing an increase after 7 February, as indicated by T-RFLP analysis (Fig. 5a & b). Surprisingly, the T-RF corresponding to Mamiellophyceae was most abundant in the >12 µm size fraction. However, Mamiellophyceae are normally very small, e.g. Bathycoccus and Micromonas are <2 µm (Vaulot et al. Reference Vaulot, Eikrem, Viprey and Moreau2008). There are a number of possible explanations for their presence in a larger size fraction. The filters may have been clogged during the filtration process, decreasing the effective pore size so that small cells were retained; however, this appears unlikely since similar procedures have been applied in many studies and Mamiellophyceae are always found in the smaller fraction (e.g. Collado-Fabri et al. Reference Collado-Fabbri, Vaulot and Ulloa2011). Alternatively, small Mamiellophyceae may have been either preyed upon or occurring in symbiosis with larger organisms, as has been observed for other prasinophytes (Cachon & Caram Reference Cachon and Caram1979) that are retained by 12 µm filters.
Conclusions
Our approach, although limited in its taxonomic resolution, has established the importance of water column stability for phytoplankton composition, which responded at very short timescales (in the order of a day) to changes in mixed layer depth. In the future, combining microscopy, flow cytometry and high-throughput sequencing using specific markers for phytoplankton should improve the taxonomic resolution of the studies.
Acknowledgements
This work was funded by INACH grants T_16-10 and RG_31-15, and Fondecyt grant #11121554 to NT. Collaboration with France was funded through CNRS International Research Network ‘Diversity, Evolution and Biotechnology of Marine Algae’ (GDRI No. 0803) and ECOS No. C16B02. The authors thank the logistic support at the scientific station, Professor Julio Escudero, Juan Francisco Santíbañez for his invaluable help during the sample collection, Catharina Alves do Souza and Cristián Vargas for their advice and assistance in the microplankton microscopic identification, and Osvaldo Ulloa for his support with the flow cytometry measurements. The authors also thank the reviewers for their comments on the manuscript.
Author contribution
RDI and NT collected the samples. CE performed the T-RFLP analysis. CHC performed the FCM analysis. ND performed the microscopy. EM performed the hydrology analysis. PL, ALS, RDI, DV and NT performed the data analysis and interpretation. ALS, RDI, DV and NT designed the study and wrote the paper.
Supplementary Material
Three supplemental tables will be found at http://dx.doi.org/10.1017/S0954102016000699.
