Freshwater Biology 49 (2004): 332-345
An HPLC analysis of the summer phytoplankton assemblage in Lake Baikal
Susanne Fietz and Andreas Nicklisch
Lake Baikal is one of the largest freshwater bodies in the world and is a unique ecosystem with many endemic species (Martin 1994, Timoshkin 1997). It extends over five degrees of latitude, is more than 600 km long and more than 1.6 km deep. Although Lake Baikal is a freshwater lake, the nutrient status of the pelagial is ocean-like, and the only nutrient-rich regions of the lake are the deltas of the main river inflows (Genkai-Kato 2002).
Seasonal, horizontal and vertical changes in the phytoplankton biomass have been well investigated in Lake Baikal (Kozhova & Izmest’eva 1998, Popovskaya 2000). Most studies have used the traditional method of microscopic measurement and counting, which primarily records nano- and microphyto-plankton. Autotrophic picoplankton (APP), believed to contribute significantly to the summer assemblage (Kozhova & Izmest’eva 1998, Popovskaya 2000), is little known, in part due to technical difficulties (Boraas, Bolgrien & Holen 1991, Nagata et al. 1994).
Considering the enormous size of the lake, monitoring the phytoplankton response to anthropogenic and climatic influences requires a less time-consuming method that includes all phytoplankton size classes. One suitable approach might be the determination of chlorophylls and carotenoids as measures of the biomass of the dominant groups. This approach allows no differentiation at the species level, but most former studies of Lake Baikal have drawn their main conclusions based only on algal groups and not on single species (Popovskaya 2000). A rapid quantitative pigment analysis, supplemented by qualitative microscopic taxonomic analysis, would provide a sufficiently comprehensive record of phytoplankton in Lake Baikal.
High-Performance Liquid Chromatography (HPLC) allows semi-automated and rapid analysis of lipophilic photosynthetic pigments (Gieskes et al. 1988, Wilhelm, Rudolphi & Renner 1991, Millie, Paerl & Hurley 1993, Jeffrey, Mantoura & Wright 1997, Jeffrey, Wright & Zapata 1999). With HPLC all chlorophylls and carotenoids, plus their degradation products, can be separated and quantified at extremely low detection levels. Marker pigments allow the identification of most phytoplankton classes, including different groups of APP and fragile cells which can be overlooked during microscopic counting (Gieskes & Kraay 1983, Everitt et al. 1990).
Marker pigments permit the quantitative contribution from different groups to total chlorophyll a (Chla) to be calculated by multiple linear regression (MLR) (Gieskes & Kraay 1983, Gieskes et al. 1988, Woitke et al. 1996) or to total biovolume by simple linear regression. Such calculations have been successfully applied to marine systems (Gieskes et al. 1988, Everitt et al. 1990, Letelier et al. 1993, Andersen et al. 1996, Bidigare & Ondrusek 1996, Wright et al. 1996, Latasa et al. 1997, Jeffrey et al. 1997, Rodriguez, Varela & Zapata 2002) and to freshwater bodies (Wilhelm et al. 1991, Lami et al. 1992, Soma et al. 1993 & 1995, Quiblier et al. 1994, Descy & Métens 1996, Woitke et al. 1996).
However, although these calculations have been standardised and software such as the CHEMTAX matrix factorisation program have been developed for marine systems (Mackey et al. 1996 & 1998, Jeffrey et al. 1997), this is not yet the case for freshwater systems. Since the pigment content and the Chla to marker pigment ratio vary between species and are influenced by light and nutrient availability (Kohl & Nicklisch 1988, Gieskes et al. 1988, Wilhelm & Manns 1991, Wright et al. 1996, Millie et al. 1993, Nicklisch & Woitke 1999), marker pigments must be chosen carefully, taking into account the taxonomic composition of the phytoplankton.
The present study investigated the applicability of an approach utilising MLR and the CHEMTAX program for phytoplankton from Lake Baikal collected during a 3-week cruise by the research vessel “Vereshchagin” in summer 2001. Counts of phytoplankton (including APP) and pigment analysis were carried out. Additionally, a comparison was made between Chla to marker pigment ratios estimated by MLR and those found in cultures of algal and cyanobacterial strains isolated from European lakes and from Lake Baikal.
|Figure 1. Diagram of Lake Baikal locating the sample stations for pigment analyses.|
Lake Baikal can be divided into three basins (Fig. 1). The north basin is separated from the central basin by Academician Ridge, and the central basin is separated from the south basin by the more than 20 km long Selenga Delta. The so-called Posolski bank is located in the southern part of the delta (Fig. 1). In July 2001 samples were collected during the CONTINENT cruises CON 01-4 and CON 01-5 in a seven-station transect over the lake (Table 1). At all stations, samples were collected within the euphotic layer at 5 m, 10 m and 30 m depths. For the pigment analysis, additional samples were taken at 5 m depth (21 stations) and just below the water surface at 0.5 m depth (11 stations). Samples were processed on board for further analyses as follows.
Phytoplankton samples (1-2 l) were concentrated by filtering through Nuclepore© polycarbonate filters (2 µm pore size). The overlaying water (1/10 of the original sample) was fixed with some drops of Lugol´s solution (Utermöhl 1958) and stored at room temperature.
Samples for cyanobacterial and eucaryotic APP (50 ml) were fixed with formaldehyde (0.7% final concentration) and filtered through black Nuclepore© polycarbonate filters (0.2 µm pore size) according to well-established methods (Søndergaard 1991, Stockner & Shortreed 1991, Nagata et al. 1994). The filter was placed on a microscope slide, dried briefly and covered with a drop of fluorescence-free immersion oil and a cover slide. Slides were stored frozen. The preparations were stable for at least six months. Duplicate samples for HPLC-aided pigment determination (1–2.5 l) were filtered through 25 mm Whatman GF/F-filters, the filters put in 2 ml test-tubes, immediately freeze-dried and stored frozen in the dark. The further analyses were conducted at the laboratory in Berlin.
Phytoplankton counts and taxonomic identification were made under the microscope according to Utermöhl (1958). The algae were classified in accordance with Ettl et al. (1986). Cells were counted at 100-x magnification. 40-x magnification was used to count less abundant species. The whole chamber of 25 - 50 ml was then examined. APP (0.2 – 3 µm) were counted at 1000-x magnification using a Zeiss Axioskop epifluorescence microscope equipped with filters for green (546 nm excitation filter, 580 nm splitter and 590 nm barrier filter) and blue (450-490 nm excitation filter, 510 nm splitter and 520 nm barrier filter) excitation. Eucaryotic APP fluoresced deep red (>665 nm) when excited with blue or green light due to the dominance of chlorophyll. Phycobilin-containing procaryotic APP was identified by its light-red autofluorescence (<665 nm) when excited with green light (Fahnenstiel et al. 1991). Phycoerythrin (PE) and phycocyanin (PC) containing cyanobacteria could be distinguished by their yellow or extreme weak emission at blue light excitation, respectively, but the difference was not definite in all stored preparations. The different taxonomic groups of APP were further divided into size classes: 1 µm spherical, 1x2 µm oblong, 2x2 µm spherical and 2x3 µm oblong. Cell counts were converted to biovolume according to their size and geometric form.
Chlorophylls, carotenoids and their derivatives were extracted with 1 ml of a mixture of acetone, methanol and water (80:15:5 by volume; Leavitt, Carpenter & Kitchell 1989) under dim light at 4 °C. The extraction was carried out by vibration shaking for 1.5 hours at 2000 rpm with a supplement of glass beads (0.75-1 mm). An IPR solution (ion-pairing reagent, 15 g l-1 tetrabutyl ammonium acetate and 77 g l-1 ammonium acetate) was added 10:1. The extract was centrifuged for 20 min at 2500 g and at 4 °C in a cooled centrifuge (Biofuge Fresco, Heraeus Instruments). The separation, identification and quantification of pigments were performed according to Woitke et al. (1994).
The HPLC system (Waters, USA) comprised a Waters 717 autosampler, a Waters 616 pump and a Waters 600S controller. Pigments were separated at a flow rate of 1.0 ml min-1 at 30 °C through a non-endcapped Waters Resolve C18 column (30 cm), protected with an appropriate precolumn, with an optimised gradient from eluent A to eluent B. Eluent A consisted of methanol, acetonitril and IPR (45:45:10) and eluent B consisted of acetonitril and acetone (45:55). Peaks were detected by a Waters 996 photodiode array detector. The system was controlled by Millenium© software. Pigments were identified by their relative retention times and by their absorption spectra.
Unialgal cultures, standards and literature data were used for comparison. Peak area integration allowed quantification with factors determined by Woitke et al. (1994, 1996) and checked from time to time with standards supplied by Sigma, Hoffmann-La Roche AG (Grenzach, Germany) or Carbon 14 Centralen (Hørsholm, Denmark).
If not specifically mentioned, strains from the culture collection of our institute (Leibniz-Institute of Freshwater Ecology and Inland Fisheries) were grown under saturating nutrient and light conditions at 15 °C in semi-continous culture (Nicklisch 1992). Statistical tests were performed using the SPSS© statistical package (SPSS Inc., USA).
The micro- and nanophytoplankton biovolumes in the basins of Lake Baikal varied from 0.5 to 1.4 mm3 l-1 (Fig. 2a). The mean biovolume was 0.89 mm3 l-1 and the median 0.52 mm3 l-1. Although the biovolume appeared to be highest in the north basin (Fig. 2a), differences between the basins were not significant. Nor were differences in depth significant but, the biovolume decreased from 1.8 to 0.16 mm3 l-1 with depth (5 m to 30 m) at Posolski bank, which is influenced by the Selenga River. The share of the algal groups did not differ significantly either over the transect (Fig. 3a) or over the vertical profile. Bacillariophyceae dominated all over the lake. Dinophyceae and Chlorophyceae were present in all basins and at all depths. Chrysophyceae were absent at Posolski bank. Except at 10 m depth in the south basin, where some Planktothrix cf. suspensa were present, micro- and nanoplanktonic Cyanobacteria were absent.
|Figure 2. Boxplots of the biovolume of (a) total phytoplankton (>3µm) and (b) total APP. Boxes represent the median with interquartile ranges (25% to 75%), minima and maxima and extremes (asterisk). Variances aroused from combining different depths and and stations within each basin.|
In contrast to the algal groups, the species composition did show differences. In the south basin and at Posolski bank microplanktonic centric Bacillariophyceae (15-50 µm) dominated. The main contribution to biovolume in the central basin was from pennate Bacillariophyceae. In the north basin, the main contribution to Bacillariophyceae biovolume was from a relatively small number of very large centric cells (>80 µm). The main Bacillariophyceae species present were Cyclotella sp. (Centrales)and Fragilaria sp. (Pennales). Aulacoseira spp. occurred only in the north basin. Other important algal species were Chlorella sp., Monoraphidium spp. (Chlorophyceae), Dinobryon sp. (Chrysophyceae) and Gymnodinium sp. (Dinophyceae). Peridinium sp. (Dinophyceae), Rhodomonas sp. (Cryptophyceae) and Chrysochromulina sp. (Haptophyceae) occurred only sporadically. In order to reduce the number of groups in Figures 3 & 5, Chrysochromulina sp. (Haptophyceae, containing fucoxanthin) was included with the Chrysophyceae.
The mean APP biovolume was 0.21 mm3 l-1 (median 0.08 mm3 l-1). The total amount of APP decreased significantly from south to north (Fig. 2b). The highest amount was found at Posolski bank, where cyanobacterial APP dominated. In the south basin, eucaryotic APP was dominant. In the north and central basins, the contribution of cyanobacterial APP and eucaryotic APP was nearly equal (Fig. 3b). The ratio of PC-containing cells to PE-containing cells gradually diminished from the south to the north. Generally, cyanobacterial APP cells were smaller (1-2 µm) than those of eucaryotic APP (2-3.5 µm). All over the lake, but most prominently at Posolski bank, colonies or aggregates of cyanobacterial APP with up to 40 cells for the 1 µm spherical size class and 15 cells for the 1x2 µm oblong size class were found, but these were not frequent. The vertical profiles did not show a significant difference in total APP content. However, at Posolski bank the APP decreased dramatically with increasing depth, as did the phytoplankton. At all depths throughout the lake, the mean amount of cyanobacterial APP was higher than that of eucaryotic APP and the contributions of PC-containing and PE-containing cells were nearly equal.
|Figure 3. Relative algal class distribution determined by light- and epifluorescence microscopy: (a) phytoplankton (>3µm) and (b) APP. Abbreviations: Bacillarioph. = Bacillariophyceae, Chrysoph. = Chrysophyceae, Dinoph. = Dinophyceae, Cryptoph. = Cryptophyceae, Chloroph. = Chlorophyceae, Cyanob. = Cyanobacteria, Cy APP = cyanobacterial APP, Eu APP = eucaryotic APP|
The HPLC method effectively separated out distinct lipophilic photosynthetic pigments, except for the co-eluting pigments alloxanthin and caloxanthin. Eighteen pigments were resolved (Table 2). Pigment degradation products were negligible. Mean Chla concentration in Lake Baikal in July 2001 was 1.35 µg l-1. The Chla concentration was significantly lower in the central basin than in all other basins (Fig. 4). The Chla concentration in the north basin was significantly lower than at Posolski bank, but not significantly different from that found in the south basin (Fig. 4). Mean Chla concentrations did not, in general, vary significantly with depth. The only exception was at Posolski bank, where the Chla concentration decreased dramatically at 30 m depth. All over the lake, the sum of the carotenoids was about 60% of the Chla.
|Figure 4. Chla concentration in Lake Baikal in July 2001. Error bars represent a 95% C.I., n=92.|
In order to calculate the contribution of different taxonomic groups of phytoplankton to Chla, a multiple linear regression (MLR) of pigment data was performed using the following model:
Chla=a(fucoxanthin) + b(lutein) + c(zeaxanthin)
where a is the Chla/fucoxanthin ratio of Bacillariophyceae plus Chrysophyceae, b is the Chla/lutein ratio of Chlorophyceae and c is the Chla/zeaxanthin ratio of Cyanobacteria (cyanobacterial APP). An iterative process was used to check whether these or other marker pigments were suitable for a correct description using the coefficient of determination (r²) and the correct prediction of Chla in each basin as criteria. For a right interpretation of pigment data the knowledge of the occurring species and its carotenoids, as known from literature and cultures, was very important.
Fucoxanthin was more suitable than Chlc as a marker pigment for Bacillariophyceae and Chrysophyceae and lutein was more suitable than Chlb for Chlorophyceae (Table 3a). The only possible marker pigments for cyanobacterial APP were zeaxanthin and caloxanthin, but caloxanthin was not clearly separated from alloxanthin. Therefore, zeaxanthin was chosen as a marker, although Chlorophyceae also contain small amounts of zeaxanthin. The amount of zeaxanthin derived from Chlorophyceae was calculated from lutein using a zeaxanthin/lutein ratio of 5.3 (Nicklisch & Woitke 1999). Zeaxanthin/lutein ratios of isolated strains from Lake Baikal were similar to this suggested ratio.
The calculated proportion of zeaxanthin attributed to the Chlorophyceae was subtracted from the total zeaxanthin of each sample so that the zeaxanthin used in the final MLR (zea*) included only the cyanobacterial part of zeaxanthin, which was at least 94 % of the total zeaxanthin. The contribution to the total Chla was calculated for every dominant algal group from the significant factors listed in Table 3a, considering all samples which were also microscopically analysed. In all basins and at all depths the estimated Chla (Fig. 5a) was then very close to the measured Chla (Fig. 4).
The pigment data were also processed using the CHEMTAX software – a matrix factorisation program for estimating class abundances in marine systems (Mackey et al. 1996). The same phytoplankton groups as mentioned for the MLR were included. Fucoxanthin, Chlc, lutein, Chlb, zea* and ß-carotene were chosen as marker pigments. The factors calculated by MLR were used as estimates of the initial pigment-ratios that are crucial for good CHEMTAX results. Suggestions given in the accompanying paper of Mackey et al. (1996) were used as initial factors for ß-carotene. The final pigment ratios differed greatly from the initial factors and the coefficient of determination (r²) was lower (Table 3a).
Nevertheless, the estimated percentage contributions of the phytoplankton groups to Chla (Fig. 5b) fitted well to the figure assessed via MLR (Fig. 5a). Only at Posolski bank were Chlorophyceae overestimated at the expense of Bacillariophyceae and Cyanobacteria. A splitting of the Bacillariophyceae and Chrysophyceae was not successful with our data set, due to the lack of precise initial Chla vs. fucoxanthin or Chlc ratio of Lake Baikal Chrysophyceae. Unreliable results were also obtained when less abundant groups, such as Cryptophyceae, Dinophyceae and Haptophyceae, were included. Causes could be that α-carotene (Cryptophyceae), peridinin (Dinophyceae) and butanoyloxyfucoxanthin (Haptophyceae) were detected in too low concentrations.
The contributions to the total biovolume of the main groups were also calculated based on the marker pigments (Fig. 5c). For this purpose marker pigment vs. biovolume ratios calculated by simple linear regression were used (Table 3b). Contributions of the Bacillariophyceae and Chrysophyceae could be divided by calculating their respective fucoxanthin/biovolume ratios via MLR. However, the result was not significant (Table 3b).
Altogether, the correspondence between the models (Fig. 5a,b&c) and the microscopic counts of micro-, nano- and picoplankton (Fig. 5d) was good. Dominances were clearly distinguishable by all models (Fig. 5a,b,c&d). In contrast, they differed strongly from dominances deduced from the simple micro- and nanoplankton data (Fig. 3a).
In order to evaluate the accuracy of the determined Chla vs. marker pigment ratios in the Baikal water they were compared to mean ratios of strains from European lakes and isolated strains from Lake Baikal. The relationship of fucoxanthin and Chlc fitted very well to these reference values, whereas we found some discrepancies for Chlorophyceae and Cyanobacteria. The Chla/zea* ratio in the Baikal samples was one quarter of that of European Cyanobacteria (Fig. 6a). While the Chla/zea* ratio of PC containing cells of Lake Baikal was similar than that of European strains, the Chla/zea* ratio of PE containing cells was only half (Fig. 6a). Grown under nutrient limitation the Chla/zea* ratio of this latter group was nearly the same than that of the Baikal samples (Fig. 6a).
The Chla/Chlb ratio of the Baikal samples was slightly lower than that of European strains, but this difference was minimal when the Baikal samples were compared to Baikal strains (Fig. 6b). The Chla/lutein ratio was higher in Baikal samples compared to the mean of 15 European and one Chlorophyceae APP strain from Lake Baikal, but was nearly the same as the ratio of an isolate of Monoraphidium sp. from Lake Baikal (Fig. 6b). Nevertheless, whereas in the south and central basin and at Posolski bank the lutein/Chlb ratio was about 0.44 mol mol-1 it was only 0.26 mol mol-1 in the north basin which is an unusually low ratio for Chlorophyceae.
The extreme Chla/violaxanthin ratio of lake samples indicates an abundant presence of Eustigmatophyceae since their Chla/ violaxanthin ratio was even lower (Fig. 6b). The presence of Eustigmatophyceae is also suggested by the record of vaucheriaxanthin traces, their marker pigment (Table 2). Finally, the presence of this easily overlooked group could be demonstrated by their isolation from Lake Baikal water samples. The isolated strains belong to the group of eucaryotic APP and resemble Nannochloropsis limnetica described first by Krienitz et al. (2000). Since in the south the violaxanthin content was highest, vaucheria-xanthin was detected and the eucaryotic APP was most abundant, a higher contribution of Eustigmatophyceae in this part of the lake could be assumed.
The Eustigmatophyceae were therefore included in the contribution to the Chla-model considering the eustigmatophycean part of violaxanthin as difference between the total violaxanthin and the chlorophycean part (Table 3c). The chlorophycean part of violaxanthin was estimated as being 15% of Chlb (Nicklisch and Woitke 1999). For this model Chlb should be used as marker for Chlorophyceae instead of lutein since Eustigmatophyceae do not contain Chlb, but stressed cells can contain lutein. Additionally we cannot exclude that a derivative of vaucheriaxanthin co-eluted in HPLC with lutein. Although the coefficient of determination (r²) of this model was high, the prediction of the total Chla was slightly less accurate. Again, the factors calculated with the CHEMTAX program differed from those calculated by MLR (Table 3c), but the estimated contributions to Chla were similar in both calculations.
The average phytoplankton biovolume of nearly 0.9 mm3 l-1, exceeded values of biovolume or fresh weight (equal to biovolume) reported in former studies (Bondarenko et al. 1996, Popovskaya 2000, Goldman & Jassby 2001). The most prominent difference was the much higher biomass in the north basin observed in July 2001, although biovolume in the different regions is known to vary greatly from year to year (Popovskaya 2000).
The latitudinal differences of the species composition and of cell sizes found in July 2001 reflected seasonal patterns: the southern part of the lake showed a summer community, whereas the northern part showed components of the usual spring community. Popovskaya (2000) stated in her review that after Chrysophyceae and cysts, the Baikal summer phytoplankton was usually dominated by small centric Bacillariophyceae, similar to our findings in the south basin. In contrast, the north basin was dominated by very large centric Bacillariophyceae, notably Aulacoseira baicalensis. This species and the other relatively common Aulacoseira species, A. skvortzowii, generally formed large blooms in spring but gradually disappeared in summer (Kobanova 2000, Richardson, Gibson & Heaney 2000).
|Figure 5. Contribution of the different phytoplankton groups - considering all samples, which were also microscopi-cally analysed – (a) to the total Chla, based on fac-tors calculated by MLR (shown in Table 3a), (b) to the total Chla, based on factors calculated by CHEMTAX (shown in Table 3a), (c) to the total biovolume based on fac-tors calculated by simple linear regres-sion (shown in Table 3b), (d) to the total biovolume based on cell counts ta-king into account the phytoplankton (>3µm) and the APP (see also Fig. 2 & 3). Abbreviations: Bacill. = Ba-cillariophyceae, Chrys. = Chrysophy-ceae, Chloroph. = Chlorophyceae, Cyanob. = Cyanobacteria.|
The APP reached nearly 20% of the total biovolume. The high contribution of APP in the south and at Posolski bank confirmed findings of Boraas et al. (1991) that about half of the Chla in the south basin, including the Selenga delta, originated from cells smaller than 5 µm. The contribution of APP to the primary production was probably even more important (Votintsev, Meshcheryakov & Popovskaya 1972). Neglecting the contribution of APP would clearly lead to a false interpretation of the summer community in Lake Baikal.
Similar to reviews for marine and freshwater systems (Søndergaard 1991) the relative importance of APP in Lake Baikal is highest in summer (Votintsev et al. 1972, Popovskaya 2000). Therefore, the assumption that latitudinal variations reflected seasonal patterns was emphasized by the decrease of APP from south to north in July 2001. Nevertheless, this decrease of APP from south to north contradicted findings of Popovskaya (2000) that the maximum APP growth is typical for the north basin. The cell number of cyanobacterial APP in July 2001 (1.9*105 cells ml-1) was higher than mean values reviewed by Popovskaya (2000) as lake average (2-80*103 cells ml-1) but similar to the maximum abundance of 1.2*105 cells ml-1 reported by an early study of Votintsev et al. (1972).
Only rough indications such as “abundant” could be found in the recent literature about APP of the north and central basin (Bondarenko et al. 1996), but few studies were available for the south. Considering only the southern part of the lake, including Posolski bank, the cell numbers of cyanobacterial and eucaryotic APP (3.8*105 and 0.08*105 cells ml-1, respectively) in July 2001 were similar to those found by Goman (1971), Boraas et al. (1991), Nagata et al. (1994) and Bondarenko et al. (1996). Direct comparisons with these data were difficult because of different cell sizes, and because some of the former studies made no reference to group or size specification at all.
Traditional measurements like Chla determination can be made with improved precision using HPLC (Jeffrey et al. 1999). The mean Chla concentration (1.35 µg l-1) was high in July 2001. Usually mean summer Chla concentration in the 0-50 m layer of Lake Baikal was below 1 µg l-1 (Kozhova et al. 1985, Kozhova 1987, Kozhova & Izmest’eva 1998), although higher concentrations have been reported, particularlyin those areas influenced by river inputs, such as the Selenga shallow waters, where Chla concentrations up to 5 µg l-1 were found (Kozhova et al. 1985, Boraas et al. 1991, Kozhova & Izmest’eva 1998). In our study this region also showed highest Chla concentrations. Probably, nutrients carried by the Selenga River as well as the longer growth period mentioned by Popovskaya (2000) influenced the Chla concentration at these stations. Summer Chla concentrations are therefore strongly dependent on sample location in Lake Baikal.
According to Rodriguez et al. (2002) HPLC is especially useful when APP contribute a large proportion of the phytoplankton community. The phytoplankton assemblage was described very accurately based on marker pigments. In general, the estimated contribution to Chla and biovolume by multiple or simple linear regression showed good correspondence to the results of microscopic counts. The contribution to Chla-model was processed with a correlation value (r²) of 0.98 and the calculated Chla in each basin deviated from the measured Chla by less than 7%. Therefore, it can be assumed that environmental changes had only little effect on the marker pigment vs. Chla relationships and that the species within a taxonomic group had very similar marker pigment vs. Chla relationships.
Estimates of the contribution of different phytoplankton groups were also accurate, although slightly less exact than the MLR model, when processed by the CHEMTAX factor analysis (r²=0.95). Since it was launched in 1997 this program has been applied successfully to different oceanic regions (Mackey et al. 1996 & 1998, Wright et al. 1996, Rodriguez et al. 2002) and also to Wisconsin lakes (Descy et al. 2000) and is now confirmed to be applicable to Lake Baikal.
|Figure 6. Comparison of Chla vs. marker pigment ratios from European strains, Baikal strains and Baikal water samples: (a) Chla vs. zeaxanthin: Comparison of 5 cyanobacterial APP strains from European lakes, new isolated cyanobacterial APP strains from Lake Baikal and Baikal water. The cyanobacterial APP of Lake Baikal were differentiated into Phycocyanin (PC) and Phycoerythrin (PE) containing cells. Baikal cultures that experienced nutrient deficiency or high light stress during growth were reported too. (b) Chla vs. marker pigments for Chlorophyceae: Comparison of 15 Chlorophyceae strains from European lakes, new isolated Chlorophyceae strains of Lake Baikal (chlorophycean APP and Monoraphidium sp.), new isolated Eustigmatophyceae and Baikal water samples.|
However, there were some discrepancies. The MLR and the CHEMTAX models assume that all algal groups identified in the samples were included into the calculations. However, only the CHEMTAX model was improved including Eustigmatophyceae as a fourth group, whereas the MLR model , was then less exact. Groups or pigments that occurred only in very low concentrations were not usefully included in both analyses. Hence the contribution of the less abundant groups could only be estimated directly from marker pigments or by cell identification and quantification. An advantage of the CHEMTAX program in previous studies was that it could separate algal groups with the same marker pigments, such as Bacillariophyceae and Chrysophyceae, based on differences of the initial ratios between both groups (Mackey et al. 1996 & 1998, Wright et al. 1996, Rodriguez et al. 2002). However, an exact knowledge of initial ratios of the local species is a prerequisite for reliable results. Initial ratios reported for oceanic species (Mackey et al. 1996) were obviously not suitable here. Pigment analyses of isolated Chrysophyceae and other species will be necessary in future to improve the CHEMTAX calibration.
The contribution to the biovolume-model was less exact than the contribution to Chla-model, and correlation values (r²) of only 0.67 were reached. But from the present data set it cannot be deduced if changes within the species or within the species composition were the cause. The shape of the contribution to the Chla plot and that of the contribution to biovolume will only be the same when the Chla content per unit biovolume is constant.
Comparing the contribution to Chla and to biovolume models results in an apparent overestimation of the Chlorophyceae and an underestimation of the Bacillariophyceae since the mean Chla content of the former group is higher due to the chlorophyll a/b antennae (Reynolds 1984, Wilhelm et al. 1991). According to the CHEMTAX results, the ratio of the total Chla vs. chlorophycean Chla was lowest compared to the ratios of Bacillariophyceae and Cyanobacteria. These findings confirmed the results of Soma et al. (1993) where measured Chla could be explained by the Chla calculated from carotenoids except for those samples in which green algae were dominant. In these cases total Chla was overestimated.
Bacillariophyceae and Chrysophyceae showed an inverse relationship: they were apparently underestimated by the pigment-based MLR model compared to the counts and to the pigment-based simple linear regression model. Woitke et al. (1996) found the same discrepancies for similar models and concluded that they were caused by different Chla contents of the Chlorophyceae and Bacillariophyceae. Compared to the Chlorophyceae, the ratio of the total Chla vs. bacillariophycean Chla was higher when calculated by the CHEMTAX software. Nevertheless, an overestimation of the bacillariophycean biovolume is also possible when calculating the biovolume from the cell number because of the variable thickness vs. diameter ratio of the silica valves. Rodriguez et al. (2002) also found discrepancies for the Bacillariophyceae contribution derived from CHEMTAX calculations compared to cell counts, suggesting changes of in situ pigment ratios in Bacillariophyceae with different cell sizes. Cyanobacteria were assumed to be overestimated as their Chla content is low and the ratio of the total Chla vs. cyanobacterial Chla was high. But this overestimation could not be confirmed by comparing the contribution to Chla and contribution to biovolume models.
Calculated Chla vs. marker pigment and biovolume vs. marker pigment ratios for fucoxanthin, Chlc, lutein and Chlb fitted well to those found in Bacillariophyceae, Chrysophyceae and Chlorophyceae cultures reported in this paper and by Wood (1979), Wilhelm et al. (1991), Woitke et al.(1996) and Nicklisch & Woitke (1999). For calculations of the contribution of Cyanobacteria to Chla the choice of the right marker pigment is species-specific. It could be oscillaxanthin or myxoxanthophyll in lakes with a dominance of Planktothrix sp. (Quiblier et al. 1994), echinenone for a community with different nano- and microplanktonic species (Woitke et al. 1996) or zeaxanthin at a dominance of cyanobacterial APP, as in this paper.
Discrepancies between cultures and lake samples were found for the Chla/zeaxanthin ratio. The high zeaxanthin content of Lake Baikal´s water could be explained by the presence of PE-containing APP, especially as the zeaxanthin concentration increased in cells suffering from nutrient or light stress (Fig. 6a). As Lake Baikal is oligotrophic and therefore certainly sometimes nutrient limited, and had a secchi depth of up to 30 m, both conditions could be important in the upper 30 m of the water column.
The unusual violaxanthin concentration could be explained by the presence of other violaxanthin containing groups besides Chlorophyceae. Chrysophyceae can also reach Chla/violaxanthin ratios of 5.8 (Mackey et al. 1996), but none of the Chrysophyceae isolated from Lake Baikal had violaxanthin, so no comparison was possible. Xanthophyceae have also Chla/violaxanthin ratios of up to 4.8 (Krasnovská, Masarovicová & Hindák 1994). According to Kozhova & Izmest’eva (1998) five Xanthophycae species have been described from Lake Baikal (living in river mouths) but they were not found microscopically in our samples. A very high violaxanthin content could be found in thegreen (eucaryotic) picoplanktonic Eustigmatophyceaeisolated from Lake Baikal in March 2002 in the south basin and in July 2002 in the north basin. The taxonomic identification of this group that had not been described in Lake Baikal until now was done by comparison of the pigment composition with that of Nannochloropsis limnetica published by Krienitz (2000).
The models presented offer a useful approach to quantitative determinations of the summer assemblage of Lake Baikal, but the importance of microscopic checks for a right interpretation of a broad pigment sample set was also demonstrated. Pigment analysis can also contribute to the knowledge of groups such as Eustigmatophyceae, which cannot be reliably identified microscopically. The disadvantage of pigment analysis that they cannot distinguish between genera or even species should be less important since most former studies of phytoplankton have drawn its main conclusions based only on algal groups (cf. Popovskaya 2000). In comparison with the microscopic determination of the biovolume, the HPLC based pigment determination has the strength that Chla is closer related to primary production than biovolume (Kiefer & Mitchel 1983), and that the total Chla was successfully used as a measure of biomass in many limnological studies.
We are grateful to the captain and crew of the R.V. Vereshchagin for their support. We wish to thank H. Täuscher for phytoplankton counts. We thank Drs David Livingstone, Anson Mackay and Jan Köhler as well as two anonymous reviewers and Prof. Roger Jones for their helpful comments on the manuscript. This study was part of the research project CONTINENT supported by the European Commission (EVK2-2000-00057).
Andersen R.A., Bidigare R.R., Keller M.D. and Latasa M. (1996) A comparison of HPLC pigment signatures and electron microscopic observations for oligotrophic waters of the North Atlantic and Pacific Oceans. Deep-Sea Research II, 43, 517-537.
Bidigare R.R. and Ondrusek M.E. (1996) Spatial and temporal variability of phytoplankton pigment distributions in the central equatorial Pacific Ocean. Deep-Sea Research II, 43, 809-834.
Bondarenko N.A., Guselnikova N.E., Logacheva N.F. and Pomazkina G.V. (1996) Spatial distribution of phytoplankton in Lake Baikal, spring 1991. Freshwater Biology, 35, 517-523.
Boraas M.E., Bolgrien, D.W. and Holen D.A. (1991) Determination of Eubacterial and Cyanobacterial Size and number in Lake Baikal using epifluorescence. Internationale Revue der gesamten Hydrobiologie, 76, 537-544.
Descy J.-P. and Métens A. (1996) Biomass-pigment relationships in potamoplankton. Journal of Plankton Research, 18, 1557-1566.
Descy J.-P., Higgins H.W., Mackey D.J., Hurley J.P. and Frost T.M. (2000) Pigment ratios and phytoplankton assessment in Northern Wisconsin lakes. Journal of Phycology, 36, 274-286.
Ettl H., Gerloff J., Heynig H. Mollenhauer D.(1986) Suesswasserflora von Mitteleuropa. Gustav Fischer Verlag, Stuttgart, Germany.
Everitt D.A., Wright S.W., Volkman J.K., Thomas D.P. and Lindstrom E.J. (1990) Phytoplankton community compositions in the western equatorial Pacific determined from chlorophyll and carotenoid pigment distributions. Deep-Sea Research, 37, 975-997.
Fahnenstiel G.L., Carrick H.J., Rogers C.E. and Sicko-Goad L. (1991) Red Fluorescing Phototrophic picoplankton in the Laurentian Great Lakes: What are they and what are they doing ? Internationale Revue der gesamten Hydrobiologie, 76, 603-616.
Genkai-Kato M., Sekino T., Yoshida T., Miyasaka H, Khodzher T., Belykh O., Melnik N., Kawabata Z., Higashi M. and Nakanishi M. (2002) Nutritional diagnosis of phytoplankton in Lake Baikal. Ecological Research, 17, 135-142.
Gieskes W.W.C. and Kraay G.W. (1983) Dominance of Cryptophyceae during the phytoplankton spring bloom in the Central North Sea detected by HPLC analysis of pigments. Marine Biology, 75, 179-185.
Gieskes W.W.C., Kraay G.W., Nontji A., Setiapermana D. and Sutomo (1988) Monsoonal alternation of a mixed and a layered structure in the phytoplankton of the euphotic zone of the Banda Sea (Indonesia): A mathematical analysis of algal pigment fingerprints. Netherlands Journal of Sea Research, 22, 123-137.
Goldman C.R. and Jassby A.D. (2001) The Great Lakes of the World (GLOW): FOOD-web, health and integrity: Primary productivity, phytoplankton and nutrient status in Lake Baikal. M. Munawar and R.E. Hecky , Ecovision World Monographs Series, Leiden (The Netherlands), pp.111-125.
Goman G.A. (1973) Characteristics of Bacteria in Southern Lake Baikal. Hydrobiological Journal, 9, 45-47.
Jeffrey S.W., Mantoura R.F.C., Wright S.W. (1997) Phytoplankton pigments in oceanography: guidelines to modern methods, UNESCO Publishing, Paris (France), 661 pp.
Jeffrey S.W., Wright S.W. and Zapata M. (1999) Recent advances in HPLC pigment analysis of phytoplankton. Marine Freshwater Research, 50, 879-896.
Kiefer, D.A. and Mitchell, B.G. (1983) A simple steady state description of phytoplankton growth based on absorption cross section and quantum efficiency. Limnology and Oceanography, 28, 770-776.
Kobanova G.I. (2000) Some pecularities of the life cycle of Aulacoseira skvortzowii in Lake Baikal. 16th International Diatom Symposium, 25, 205-212.
Kohl J.G., Nicklisch A. (1988) Ökophysiologie der Algen, Akademie-Verlag, Berlin (Germany), 253 pp.
Kozhova O.M. and Izmest’eva L.R. (1998) Lake Baikal: Evolution and Biodiversity, Backhuys Publishers, Leiden (The Netherlands), 447 pp.
Kozhova O.M., Pautova V.N., Ismest´eva L.R. and Davydova I.K. (1985) Chlorophyll a in the Water of Lake Baikal. Hydrobiological Journal, 21, 12-19.
Kozhova O.M. (1987) Phytoplankton of Lake Baikal: structural and functional characteristics. Archiv für Hydrobiologie Beiheft Ergebnisse der Limnologie, 25, 19-37.
Krasnovská E., Masarovicová E. and Hindák F. (1994) Pigment composition of six xanthophycean algae and Scenedesmus quadricauda. Biologia, Bratislava, 49, 501-509.
Krienitz L., Hepperle D., Stich H.-B. and Weiler W. (2000) Nannochloropsis limnetica (Eustigmatophyceae), a new species of picoplankton from freshwater. Phycologia, 39, 219-227.
Lami A., Guillizoni P., Ruggio D., Polli B., Simona M. and Barbieri A. (1992) Role of pigments on algal communities and photosynthesis. Aquatic Sciences, 54, 321-330.
Latasa M., Landry M.R., Schlüter L. and Bidigare R.R. (1997) Pigment-specific growth and grazing rates of phytoplankton in central equatorial Pacific. Limnology and Oceanography, 42, 289-298.
Leavitt P.R., Carpenter S.R. and Kitchell J.F. (1989) Whole-lake experiments: The annual record of fossil pigments and zooplankton. Limnology and Oceanography, 34, 700-717.
Letelier R.M., Bidigare R.R., Hebel D.V., Ondrusek M., Winn C.D. and Karl D.M. (1993) Temporal variability of phytoplankton community structure based on pigment analysis. Limnology and Oceanography, 38, 1420-1437.
Mackey M.D., Mackey D.J., Higgins H.W. and Wright S.W. (1996) CHEMTAX - a program for estimating class abundances from chemical markers: application to HPLC measurments of phytoplankton. Marine Ecology Progress Series, 144, 265-283.
Mackey D.J., Higgins H.W., Mackey M.D. and Holdsworth D. (1998) Algal class abundances in the western equatorial Pacific: Estimation from HPLC measurements of chloroplast pigments using CHEMTAX. Deep-Sea Research I, 45, 1441-1468.
Martin P. (1994) Lake Baikal. Archiv für Hydrobiologie Beiheft Ergebnisse der Limnologie, 44, 3-11.
Millie D.F., Paerl H.W. and Hurley J.P. (1993) Microalgal Pigment Assessments Using High-Performance Liquid Chromatography: A Synopsis of Organismal and Ecological Applications. Canadian Journal of Fisheries and Aquatic Sciences, 50, 2513-2527.
Nagata T., Takai K., Kawanobe K., Kim D.-S., Nakazato R., Guselnikova N., Bondarenko N., Mologawaya O., Kostrnova T., Drucker V., Satoh Y. and Watanabe Y. (1994): Autotrophic picophytoplankton in southern Lake Baikal: abundance, growth and grazing mortality during summer. Journal of Plankton Research 16: 945-959.
Nicklisch A. (1992) The interaction of irradiance and temperature on the growth rate of Limnothrix redekei and its mathematical description. Archiv für Hydrobiologie Supplement, 91, (Algological Studies 63), 1-18.
Nicklisch A. and Woitke P. (1999) Pigment Content of Selected Planktonic Algae in Response to Simulated Natural Light Fluctuations and a Short Photoperiod. Internationale Revue der gesamten Hydrobiologie, 84, 479-495.
Popovskaya G.I. (2000) Ecological monitoring of phytoplankton in Lake Baikal. Aquatic Ecosystem Health and Management, 3, 215-225.
Quiblier M., Feuillade M., Bourdier G., Amblard C. and Pepin D. (1994) Studies in Lake Nantua. Phytoplankton distribution as determined by HPLC pigment analysis. Archiv für Hydrobiologie Beiheft Ergebnisse der Limnologie, 41, 113-124.
Reynolds C.S. (1984) The Ecology of Freshwater Phytoplankton. Cambridge University Press, 384 pp.
Richardson T.L., Gibson C.E., Heaney S.I. (2000) Temperature, growth and seasonal succession of phytoplankton in Lake Baikal, Siberia. Freshwater Biology, 44, 431-440.
Rodriguez F., Varela M. and Zapata M. (2002) Phytoplankton assemblages in the Gerlache and Bransfield Straits (Antarctic Peninsula) determined by light microscopy and CHEMTAX analysis of HPLC pigment data. Deep-Sea Research II, 49, 723-747.
Soma Y., Imaizumi T., Yagi K. and Kasuga S. (1993) Estimation of Algal Succession in Lake Water Using HPLC Analysis of Pigments. Canadian Journal of Fisheries and Aquatic Sciences, 50, 1142-1146.
Soma Y., Tanaka A. and Soma M. (1995) Composition and vertical profiles of photosynthetic pigments in the sediment of Lake Kasumigaura. Geochemical Journal, 29, 107-113.
Søndergaard M. (1991) Phototrophic Picoplankton in Temperate Lakes: Seasonal Abundance and Importance along a Trophic Gradient. Internationale Revue der gesamten Hydrobiologie, 76, 505-522.
Stockner J.G., Shortreed K.S. (1991) Autotrophic picoplankton: community composition, abundance and distribution across a gradient of oligotrophic British Columbia and Yukon Territory lakes. Internationale Revue der gesamten Hydrobiologie, 76, 581-601.
Timoshkin O. A. (1997) Biodiversity of Baikal fauna: state-of-the-art (preliminary analysis), p. 35-76. In E. Wada, O. A. Timoshkin, N. Fujita, and K. Tanida [eds.], New scope on boreal ecosystems in east Siberia. DIWPA Series, Vol. 2.
Utermöhl H. (1958) Zur Vervollkommnung der quantitativen Phytoplankton-Methodik. Mitteilungen. Internationale Vereinigung Für Theoretische und Angewandte Limnologie, 5, 567-596.
Votintsev K.K, Meshcheryakova A.I. and Popovskaya G.I. (1972) The importance of ultrananoplanktonic algae in the primary production of Lake Baikal in the summer. Hydrobiological Journal, 8, 13-18.
Wilhelm C. and Manns L. (1991): Changes in pigmentation of phytoplankton species during growth and stationary phase - consequences for reliability of pigment-based methods of biomass determinations. Journal of Applied Phycology, 3, 305-310.
Wilhelm C., Rudolphi I. and Renner W. (1991) A quantitative method based on HPLC-aided pigment analysis to monitor structure and dynamics of the phytoplankton assemblage - a study from Lake Meerfelder (Eifel, Germany). Archiv für Hydrobiologie, 123, 21-35.
Woitke P., Martin C.-D., Nicklisch S. and Kohl J.-G. (1994) HPLC determination of lipophilic photosynthetic pigments in algal cultures and lake water samples using a non-endcapped C18-RP-column. Fresenius Journal of Analytical Chemistry, 348, 762-768.
Woitke P., Schiwietz T., Teubner R. and Kohl J.-G. (1996) Annual profiles of photosynthetic lipophilic pigments in four freshwater lakes in relation to phytoplankton counts as well as to nutrient data. Archiv für Hydrobiologie, 137, 363-384.
Wood A.M. (1979) Chlorophyll a:b ratios in marine planktonic algae. Journal of Phycology, 15, 330-332.
Wright S.W., Thomas D.P., Marchant H.J., Higgins H.W., Mackey M.D. and Mackey D.J. (1996) Analysis of phytoplankton of the Australian sector of the Southern Ocean: comparisons of microscopy and size frequency data with interpretation of pigment HPLC data using the "Chemtax" matrix factorisation program. Marine Ecology Progress Series, 144, 285-298.
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