regional, vertical and seasonal distribution of phytoplankton and

Regional, vertical and seasonaldistribution of phytoplankton andphotosynthetic pigments in Lake Baikal

SUSANNE FIETZ1*, GALINA KOBANOVA2, LYUBOV IZMEST’EVA2 AND ANDREAS NICKLISCH3

1

LEIBNIZ INSTITUTE OF FRESHWATER ECOLOGY AND INLAND FISHERIES, MUEGGELSEEDAMM 301, 12587 BERLIN, GERMANY,2

SCIENTIFIC RESEARCH

INSTITUTE OF BIOLOGY, STATE UNIVERSITY IRKUTSK, LENINA 3, 664003 IRKUTSK, RUSSIA AND3

INSTITUTE OF BIOLOGY, HUMBOLDT UNIVERSITY

BERLIN, LUISENSTRASSE 53, 10099 BERLIN, GERMANY

*CORRESPONDING AUTHOR: [email protected] and [email protected]

Received May 2, 2005; accepted in principle July 26, 2005; accepted for publication August 3, 2005; published online August 17, 2005

A 3-year phytoplankton study was carried out in Lake Baikal (Siberia) as part of the CONTINENT

project and in conjunction with a 60-year long monitoring programme by the Irkutsk State University.

A combination of microscopy and high performance liquid chromatography (HPLC) pigment analysis

was used. All over the lake, the dominant functional group (by biovolume) was the vernal diatom

blooms, due to the dominance of endemic Cyclotella species. Chlorophyll a (Chl a) was significantly

highest at the Selenga and Barguzin inflows (2.39 � 0.34 and 2.49 � 0.18 nmol L–1, mean �95% CI, respectively) and higher in the South than in the North (1.43 � 0.26 and 0.96 � 0.13

nmol L�1). This variation of Chl a reflected changes in the phytoplankton composition. Diatoms and

Chrysophyceae were the major contributors to the total Chl a except in the South (Chlorophyceae) and

Selenga Delta (cyanobacterial picoplankton). There were also indications of species composition

changes due to enhanced P-loading from the Selenga River. However, canonical analyses indicated

that temperature and stratification were the major driving forces for regional distribution patterns and

seasonal succession. It seems likely that further global warming will cause a shift in the species and

group composition towards small cells at the expense of the large endemic diatom flora.

INTRODUCTION

Lake Baikal is one of the oldest, largest and deepest lake

in the world. It has over 569 formally identified algal

(planktonic and benthic) species of which 35% are esti-

mated to be endemic (Kozhova and Izmest’eva, 1998).

This unique ecosystem has changed very little since

regular research began in the early 20th century

(Kozhova and Izmest’eva, 1998) but a warming of the

air temperature and a decline of the ice cover duration

has been reported recently (Shimaraev et al., 2002).

Moreover, pollution in the Selenga River and South

Basin due to both industrial and domestic discharge

was shown (Kozhova and Silow, 1998; Mackay et al.,

1998; Beeton, 2002). Yet the effects of global warming or

local anthropogenic impacts are poorly known. One

group that responds rapidly to such environmental

changes is the phytoplankton. However, to quantify the

significance of any changes, it is important to determine

the variability of populations over space and time.

In Lake Baikal, gradients of temperature, insolation

and nutrients are caused by its great length over five

degrees of latitude, its rift-generated morphometry as

well as its large tributaries and bays (see Kozhov, 1963;

Galazyi, 1993; Kozhova and Izmest’eva, 1998). Also, an

unusual feature of the lake is the vertical mixing and

deep water ventilation driven by small density changes

close to the point of maximum density of water (Weiss

et al., 1991; Shimaraev et al., 1993; Wuest et al., 2005).

This is important for the phytoplankton because results

of growth experiments point to temperature as possible

cause of community change (Richardson et al., 2000).

However, the regional variation of nutrient supply, ther-

mal stratification and ice conditions are also critical

factors (Goldman et al., 1996; Genkai-Kato et al., 2002;

Mackay et al., 2003). Characteristic of Lake Baikal are

JOURNAL OF PLANKTON RESEARCH j VOLUME 27 j NUMBER 8 j PAGES 793–810 j 2005

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the so called Melosira years, which occur every 3 or 4

years (at least in the South Basin). During these years

blooms of endemic Bacillariophyceae, such as Aulacoseira

baicalensis (formerly Melosira baicalensis) begin to develop

in the convective layer under the ice (Kozhov, 1963;

Granin et al., 1991, 1999; Kelley, 1997; Kozhova and

Izmest’eva, 1998).

Most former studies on Lake Baikal focused on single

topics such as nano- and microphytoplankton or on

bacteria, primary production or chlorophyll, whereas

photosynthetic pigments other than chlorophyll have

not been studied. However, pigments have been success-

fully used to quantify the relative importance of different

chemotaxonomic groups in phytoplankton in other

freshwater and marine systems (Gieskes et al., 1988;

Everitt et al., 1990; Wright et al., 1996; others). Within

the multiproxy EU-project CONTINENT (http://con-

tinent.gfz-potsdam.de/), a preliminary study in 2001

revealed the potential of an high performance liquid

chromatography (HPLC)-aided pigment based approach

in Lake Baikal (Fietz and Nicklisch, 2004). In this study,

light microscopy was combined with epifluorescence

microscopy and HPLC to investigate the distribution of

phytoplankton groups and species, including autotrophic

picoplankton (APP). In particular three gradients: region,

depth and season were studied during three consecutive

years (2001–2003) in conjunction with the long-term

monitoring of the Scientific Research Institute of Biology

at the Irkutsk State University. An attempt was made to

evaluate the response of the phytoplankton to global

warming or local eutrophication.

METHOD

Sampling

Sampling for the study of regional distribution patterns

was conducted in July 2001, 2002 and 2003 during the

CONTINENT cruises CON 01–4, CON 01–5, CON

02–8 and CON 03–9 with the Research Vessel ‘Veresh-

chagin’ (Fig. 1A). In 2001 samples for pigment analyses

were taken from 0.5, 5, 10 and 30 m water depth.

Samples for phytoplankton counting were taken from

5, 10 and 30 m water depth. In 2002, samples for

pigment and phytoplankton analyses were taken from

5, 10 and 30 m and/or in the deep chlorophyll-maxima

determined with a submersible fluorometer (FluoroProbe,

bbe Moldaenke GmbH, Kiel, Germany). In 2003, only

samples for pigment analyses were taken (same depths as

in 2002). In 2001, temperature was directly measured in

the pigment samples. Temperature in 2002 and 2003 was

provided for all sampling stations and depths, where

phytoplankton and pigment samples were taken, by the

fluorometer and by CTD profiles from Limnological

Institute of Irkutsk, Russian Academy of Sciences.

For the study of seasonal dynamics, weekly sampling

from May 2002 to June 2003 was carried out at the

long-term sampling site of the Scientific Research Insti-

tute of Biology, State University Irkutsk (SRIB), located

2.8 km offshore from Bolshye Koti (51�540 N 105�040 E,

Fig. 1A). Water depth at that site was 800 m. Samples

from this latter station were taken with the Research

Vessel ‘M.M. Kozhov’ in summer or from the ice in

winter and processed at the Biological Station Bolshye

Koti.

Phytoplankton qualitative and quantitativedetermination

Samples for APP (0.2–3 mm; 50 mL) were preserved with

formaldehyde (0.7% final concentration) and filtered

through black Nuclepore polycarbonate filters (0.2 mm

pore size). The filter was placed on a microscope slide,

quickly dried and covered with a drop of fluorescence-

free immersion oil and a coverslip. Once frozen, pre-

parations were stable for months. APP were counted at

1000� magnification using a Zeiss Axioskop epifluores-

cence 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. Eukaryotic

APP fluoresced deep red (>665 nm) when excited with

blue or green light, whereas cyanobacterial APP

fluoresced light red (<665 nm) when excited with green

light (Phycobilins). Phycoerythrin and phycocyanin con-

taining cyanobacteria were distinguished by their respec-

tive yellow or extreme weak emission at blue light

excitation, but this difference was not definite in all

stored preparations. Cell counts were converted to bio-

volume according to their size and geometric form (Fietz

and Nicklisch, 2004). During seasonal monitoring APP

was counted with a light microscope; in doing so

colonies were easily identified, but single cells could be

overlooked.

In both years of phytoplankton counts (2001 and 2002),

samples from cruises (1–2 L) were concentrated by

filtering through Nuclepore polycarbonate filters (2 mm

pore size), resuspended in 100 mL, fixed with some drops

of Lugol’s solution and stored at room temperature. Sam-

ples for seasonal monitoring were not concentrated.

Counting and identification was done according to the

settling technique (Utermohl, 1958). The taxonomic com-

position of algae was established in accordance with ‘The

Keys of Freshwater Algae of the USSR’ (see Kozhova and

Izmest’eva, 1998; p. 325 for references), with monographs

(references in Bourrelly, 1957; Kozhova and Izmest’eva,

1998) and additional keys (references in Topachevsky and


794


http://con-tinent.gfz-potsdam.de



Fig. 1. Regional variability of temperature, chlorophyll a (Chl a), carotenoids and biovolumes. (A) A map of Lake Baikal showing the samplingstations, (B) the temperature, (C) nano- and microphytoplankton biovolume, (D) Chlorophyll a, (E) APP biovolume, and (F) sum of carotenoids.The APP biovolume versus total phytoplankton biovolume ratios as well as the sum of carotenoids versus Chl a are given as percentages. Thenumber of samples (n) for temperature and pigments was 43–52 in each of the three open basins and at Selenga Delta (S Delta), 22 at Barguzin Bay(B Bay) and 6 at Academician Ridge (A Ridge) and Maloe More (MM). The number of samples (n) for biovolumes was 9–12 in each of the threeopen basins and S Delta. All samples were taken in July 2001, 2002 and 2003.

S. FIETZ ETAL. j PHYTOPLANKTON VARIABILITY IN LAKE BAIKAL

795


Masyuk, 1984; Wasser et al., 1989; Gleser et al., 1992;

Kozhova and Izmest’eva, 1998) and supplemented by

articles (references in Kozhova and Izmest’eva, 1998;

Edlund et al., 1996). Gymnodinium coeruleum (Pyrrophyta)

is often cited within Lake Baikal phytoplankton assem-

blages (Kozhova, 1987; Kozhova and Izmest’eva, 1998;

Genkai-Kato et al., 2003) but has been omitted from the

phytoplankton counts in this study because it did not

contain chloroplasts and, therefore, was counted as

protozoan. All species were tentatively grouped into

functional associations according to the scheme pro-

posed by Reynolds et al. (Reynolds et al., 2002). We

consulted with its authors over the classification of the

species we have encountered.

Pigment analysis

Duplicate samples for HPLC-aided pigment determina-

tion (1–2.5 L) were filtered through Whatman GF/F-

filters with 25 mm diameter, stored in 2 mL reaction

vessels, frozen at �25�C and immediately freeze-dried

and stored frozen in the dark. The sample temperature

during freeze-drying was controlled below �25�C. For

2001 samples, chlorophylls, carotenoids and their deriva-

tives were extracted with 1 mL of a mixture of acetone,

methanol and water (80:15:5 by volume, Leavitt et al.,

1989) and in 2002 and 2003 with 1 mL of dimethylfor-

mamide under dim light at 4�C. No significant difference

was found between both solvents. The extraction was

done by vibration shaking at a frequency of 2000 min�1

with a supplement of glass beads (0.75–1 mm) over 1.5 h.

An IPR solution (ionpairing reagent, 15 g L�1 tetrabutyl

ammonium acetate and 77 g L�1 ammonium acetate)

was added 1:10. The extract was centrifuged for 20 min

at 4�C at 2500 g in a cooled centrifuge (Biofuge Fresco

Heraeus Instruments, Hanau, Germany). The separation,

identification and quantification of pigments were per-

formed according to Woitke et al. (Woitke et al., 1994)

with a Waters HPLC system as described by Fietz and

Nicklisch (Fietz and Nicklisch, 2004).

In this study we used chemotaxonomic groups,

which may be classes or families, according to the

respective pigment compositions. In that way we used

‘Bacillariophyceae + Chrysophyceae’, because both

families contain the marker pigments fucoxanthin and

Chl c but other families of their class ‘Heterokonto-

phyta’ contain other marker pigments. Also, we used

‘Chlorophyta’, because all phytoplankton families of

this class contain the same pigment composition, but

we used ‘cyanobacterial picoplankton’ that clearly

dominate the Baikalian cyanobacteria because their

marker pigments are zeaxanthin and caloxanthin,

which are not prominent in filamentous cyanobacteria

(Fietz and Nicklisch, 2004).

The contribution of the individual chemotaxonomic

groups to total Chl a was calculated according to Fietz

and Nicklisch (Fietz and Nicklisch, 2004) by multiple linear

regression using specific marker pigments (MP) for the

chemotaxonomic groups (Chl a = a�MP1 + b�MP2 +

c�MP3). In the first study for the Baikalian summer assem-

blage 2001 (Fietz and Nicklisch, 2004), it was mentioned

that caloxanthin, a zeaxanthin transformation product, pos-

sibly coeluted with alloxanthin in some samples. In this

study, the correlation between a-carotene and alloxanthin,

both contained in Cryptophyta, was significant. Therefore,

we assumed that alloxanthin in almost all samples did not

coelute with caloxanthin. Few outliers from the significant

alloxanthin/a-carotene relationships were omitted in the

multiple linear regression calculations of this study.

HPLC-based pigment analysis was provided for the three

summer cruises as well as for the intensive monitoring from

May 2002 to June 2003. Additional weekly Chl a data were

provided from January 2001 to December 2003 by the

long-term monitoring program conducted by the SRIB.

For these analyses water samples were taken at the above

mentioned Bolshye Koti station, filtered through 0.7 mm

pore size Nuclepore polycarbonate filters, dried in cold,

dark conditions and stored frozen. Extraction was done

with 96% acetone. Extracts were centrifuged and the absor-

bance of the supernatant was measured with a spectrophot-

ometer at 750, 665, 645 and 630 nm. Chl a was calculated

according to guidelines given by the SCOR-UNESCO

Workgroup (SCOR-UNESCO Workgroup, 1966).

Statistics

Variance analyses, Spearman-Rho and Pearson correla-

tions and linear regressions were calculated with SPSS

(SPSS Inc., Chicago, IL, USA) statistical package. Cano-

nical correlation analysis (CCA) was calculated with

Statistica (StatSoft Inc., Tulsa, OK, USA). The Simpson

index and Shannon-Wiener index were calculated with

BioDap (New Brunswick, Canada, cf. Magurran, 2003)

using cell abundances.

RESULTS

Regions

The phytoplankton in Lake Baikal included APP, nano-

and microphytoplankton. The phytoplankton biovo-

lume, the Chl a and other phytoplankton pigments

were distributed very heterogeneously in Lake Baikal,

indicating variations of both phytoplankton abundance

and composition. Differences were found between the

open basins (South, Centre, and North) as well as

between the near-shore (Maloe More) and river-inflow

(Selenga Delta, Barguzin Bay) sites (Fig. 1A–F).


796


Distribution of APP, nano- and microphytoplanktonThe whole lake average phytoplankton biovolume was

0.61 mm3 L�1 whereof APP comprised only 11% in the

North, but 61% in the Selenga Delta (Fig. 1E). Sign-

ificant differences for the APP biovolume were found in

the following order: Selenga Delta > South, Centre >

North (Fig. 1E). In contrast, no significant differences

were found for the nano- and microphytoplankton

between individual regions, either based on biovolumes

(Fig. 1C) or cell numbers. Between 9 and 14 nano- and

microphytoplankton species were identified at the differ-

ent sites and depths and the mean reciprocal Simpson

diversity index for the whole lake was 3.40 (Shannon-

Wiener 1.92) ranging at individual sites from 2.1 to 3.6

(Table I); we did not record significant differences

between the regions. On average 53% of the nano-

and microphytoplankton biovolume resulted from

endemic species.

The dominant functional group (by biovolume) was

that of vernal bacillariophycean blooms typical of oligo-

trophic lakes, due to the dominance of Cyclotella species

(Table I). Only at a few sites the dominances changed. In

the South (5 m), for example, the dominant functional

group was that usually found at the start of summer

stratification in oligotrophic conditions (Table I) and in

the Selenga Delta the dominant functional groups indi-

cated summer stratification (Table I). Besides Cyclotella

species, flagellata, most of them belonging to Chryso-

phyceae, were numerous across the lake (Table I). The

contribution to the total biovolume of these flagellates

was nonetheless higher in the South and Selenga Delta

than in the North (Table I). A high number of Koliella

longiseta (Chlorophyta) was found along with Cyclotella in

the South and Centre, as well as a high number of

Nitzschia acicularis (Bacillariophyceae) in the Centre

(Table I). In the North the contribution of Cyclotella

species to the total biovolume was higher than at all

other sites unless at Academician Ridge (Table I). At

Academician Ridge, Cyclotella cells were very numerous

and the biovolume per Cyclotella cell was much higher

than at the other sites (their diameter reached 150 mm).

Within the Selenga Delta the number of Aulosira sp.

(cyanobacteria) cells was the highest; the respective Aulo-

sira species differed morphologically from Aulosira implexa

and Aulosira laxa, which up until now were the only

Aulosira species described for Lake Baikal (Bondarenko,

1995).

Distribution of phytoplankton pigmentsThe Chl a concentration was significantly correlated to

temperature (r2 = 0.35, P < 0.001) and was significantly

lower in the three open basins (South, Centre and

North) than at the river inflows (Selenga and Barguzin)

(Fig. 1B and D). Within the open basins, the North had a

significantly lower Chl a concentration and temperature

than the South (Fig. 1B and D). However, significant

differences in the Chl a concentrations were found in

each basin when the 3 years were compared, particularly

in the North (Fig. 2). Similarly, significant interannual

differences were found for each of the carotenoids, for

Chl b, for Chl c, for the sum of carotenoids and for the

carotenoids versus Chl a ratios (data not shown).

Changes in the carotenoid versus Chl a ratios (which

varied from 53% in the Maloe More to 98% at Acade-

mician Ridge when expressed as weight ratios, Fig. 1F)

indicated either changes of the phytoplankton commu-

nity composition or changes of the physiological state of

the cells. The ratios of carotenoids that collected light

(such as fucoxanthin, Fig. 3A) versus carotenoids that

protected cells against high light (such as diadinoxanthin)

was not correlated to the total carotenoid versus Chl a

ratio. Changing phytoplankton community composition

was, therefore, more likely than light acclimation. Only

at Maloe More did the very low carotenoid versus Chl a

ratio clearly result from a lowering of protecting carote-

noids (data not shown), indicating the low light acclima-

tion of the phytoplankton at that site. That might be due

to high content of dissolved coloured organic com-

pounds (humic substances) at this particular site.

Taking a lake average (July 2001, 2002 and 2003), the

dominant carotenoids were zeaxanthin, fucoxanthin and

lutein. Fucoxanthin (Fig. 3A), Chl c, diadinoxanthin and

diatoxanthin concentrations showed no significant differ-

ences between the basins although significantly higher

values were found at Barguzin Bay and at Academician

Ridge. The Chl b (Fig. 3B) and lutein showed significantly

higher concentrations in the South than at most of the

other sites. Alloxanthin (Fig. 3C) and peridinin did not

show significant variations between the open basins and

the remaining regions. Violaxanthin concentrations

showed significant decreases in the order South > Centre

> North (Fig. 3D). Zeaxanthin (Fig. 3E) and b-carotene

were significantly highest in the Selenga Delta and the

South showed significantly higher concentrations than the

North. The 190butanoyloxyfucoxanthin was not detected

in any sample.

Fucoxanthin, Chl b, Alloxanthin, Violaxanthin and

Zeaxanthin were used to estimate the composition of

the phytoplankton assemblage (Fig. 3F; Table II). The

coefficient of determination (r2) was high (0.97; Table II)

and the calculated Chl a matched the measured Chl a

with a mean error of 6% and a maximum error of 24%

in all regions and years. The highest contribution of

Bacillariophyceae + Chrysophyceae to the total Chl a

was found in the North, Barguzin Bay and at Academi-

cian Ridge, whereas the contribution of Chlorophyta


797


Regions

Depth (m) 5 10 30 5 10 20 85 5 10 16 5 10 30 5 10 30 5 10 45 5 10 16 5 10 30

Diversity Indexa 3.11 3.48 2.17 3.91 3.54 1.68 4.98 3.68 4.26 3.56 3.35 1.39 2.51 2.32 3.74 4.06 4.68 3.89 2.28 3.82 1.02 1.74 3.40 1.17 1.57

Dominant Functional Groups (FG)b A A A E A A B A A C A A A A A A A A A A S1 Z A A B

Species FG b Percentage contribution to total biovolume

Bacillariophyceae

Stephanodiscus meyerii c B

Cyclostephanus dubius B/C

Aulacoseira baicalensis cB

Synedra acus D

Cyclotella baicalensis cA

Cyclotella ornata and minuta cA

Nitzschia acicularis C

Chlorophyta

Koliella longiseta X 3

Koliella sp. X 3

Monoraphidium pseudomirabile X 1

Elakatothrix genevensis F

Pyrrophyta

Glenodinium ssp. X 2

Cryptophyta

Cryptomonas sp. Y

Rhodomonas pusilla X 2

Rhodomonas sp. X 2

Chrysophyta

Flagellata, small E

Chrysidalis sp. -

Chrysococcus sp. X 3

Dinobryon cylindricum E

Cyanobacteria

Aulosira sp. H

APP

Eukaryotic APP X 3

Cyanobacterial APP Z

A Ridge S Delta (N) S Delta (S)South (C) South (E) North (E) North (C)Centre (N)

<1%; 10%; 10-3 %; 30-50%; 50-80%; >80%.1-

C, Central; E, Eastern; N, Northern; S, Southern. a Reciprocal Simpson diversity index. b Rough interpretation of the functional groups (FG; details in Reynolds et al. (2002); the classification of endemic species base on their description in literature and classification of related species: A,B,C + D: vernal diatom blooms in mixed oligotrophic (A) to eutrophic (D) lakes; E, F, H: start of summer stratification; E, able to mixotrophy; F, oligotrophic Chlorococcales; H, dinitrogen-fixing Nostocaleans; LM: summer epilimnia in eutrophic lakes, sensitives to mixing; S1, X1, X2 + X3: tolerant to stratification, sensitive to mixis, filamentous cyanobacteria (S1) or eukaryotic pico- and smaller nanoplankton (X) in shallow mixed turbid (S1) or clear (X) layers from eu- (X1) to oligotrophic (X3). Y is represented by larger cryptomonad species in enriched conditions; Z is represented by cyanobacterial APP). C Marks endemic species

Table I: Spatial phytoplankton species, diversity and functional groups distribution (only those species are listed thatcontributed at least 1% of biovolume at any of the sites)

JOU

RN

AL

OF

PL

AN

KT

ON

RE

SE

AR

CHj

VO

LU

ME

27j

NU

MB

ER

8jP

AG

ES

79

3–8

10j

20

05

79

8


was highest in the South (40%) and that of the cyano-

bacterial APP in the Selenga Delta (30%) (Fig. 3F). The

contribution of Eustigmatophyceae was highest at Maloe

More (45%). Possibly several Chrysophyceae contribu-

ted to the total violaxanthin at Maloe More so that the

eustigmatophycean violaxanthin was overestimated at

that site. The contribution of Cryptophyta was small

(<15%) all over the lake.

Depth

Temperature and chlorophyll depth profiles from January

2001 to December 2003 near Bolshye Koti indicated that

an inverse stratification, with mixing restricted to a shal-

low layer under the ice occurred regularly in February.

Furthermore, every year wind-induced mixing occurred

over the upper 250 m from May to June, after ice break

up, and again in November (Fig. 4). During spring over-

turn concentrations over 2 nmol L�1 were found down to

100 m and up to 0.5 nmol L�1 down to 250 m (Fig. 4),

while during the autumn overturn the Chl a did not reach

depths greater than 200 m.

Mixing conditions varied among the different basins

and regions, as high-resolution temperature and conduc-

tivity depth profiles showed that in the North mixed

conditions prevailed, whereas a weak stratification

developed in the South and Selenga Delta (Fig. 5).

Stable stratification with a broad epilimnion developed

in Barguzin Bay, where the conductivity showed a sec-

ond maximum at 20–25 m, probably indicating the

influence of subsurface water currents induced by the

river (Fig. 5).

The Chl a concentration in July was highest in the

epilimnion and decreased with depth at the stratified

sites, but showed a second maximum at 16 m in the

South, and was rather homogeneously distributed in the

North and Centre (Fig. 5). The total APP also decreased

in the 20–30 m samples compared to the 5 m samples

considering the whole lake average, whereas no significant

changes could be found for the nano- and microphyto-

plankton (data not shown). Nonetheless, several groups

and species showed distinct relationships with depth. The

cyanobacterial APP, for example, was higher at 16 m

than above in the Selenga Delta, and, furthermore, Aula-

coseira baicalensis formed a deep maximum in 85 m water

depth in the South (Table I).

A CCA (Table III) indicated that cyanobacterial APP

made the highest contributions when the water column

was stratified, with temperature as secondary factor.

Chlorophyta dominated in the low latitude regions,

probably related to the insolation, as temperature was

not of great importance. Bacillariophyceae + Chryso-

phyceae dominated at the deep water sites, which means

in the colder, nutrient-poor open basins rather than in

the near-shore or river inflow areas.

Seasonal monitoring

Intense monitoring was conducted from May 2002 to

June 2003. The year 2002 was warmer than 2001 and

2003 with a mean summer (July – September) tempera-

ture at 5 m water depth of 12�C, compared to 8.5�C in

2001 and 8�C in 2003 (cf. Fig. 6A). Moreover, the ice

cover was shortest in 2002 (1 month) relative to 2001

(2.5 months) and 2003 (2 months).

Dynamics of APP, nano- and microphytoplanktonThe amount of APP was high in July (about 0.7 mm3 L�1)

and decreased towards autumn (less than 0.2 mm3 L�1;

Fig. 6B). Nevertheless, the presence of APP in February

and March (about 0.1 mm3 L�1), when the lake was

covered with ice, indicated an important APP formation

under the ice. The nano- and microphytoplankton biovo-

lume was highest from mid to end of May (median 2.0

mm3 L�1), decreasing at the end of May and was then low

during summer and autumn (median 0.08 mm3 L�1; Fig.

6B). In contrast, the cell numbers then grew again in July

and were as high as during spring (Fig. 6B). The diversity

index (reciprocal Simpson index) increased from a mini-

mum in mid-May (1.2) to a maximum in mid-June (10.6;

Fig. 6B) and was, therefore, highest at the time of the

minimum biovolume and cell abundance.

The spring bloom (2002) was dominated by Stephano-

discus meyerii and Aulacoseira baicalensis (Bacillariophyceae),

endemic species that fill a niche similar to indicators of

vernal blooms usually found in mixed, mesotrophic con-

ditions (Table IV). Towards the beginning of July (2002),

the contribution of Bacillariophyceae decreased and

Chlorophyta (Koliella sp. and Monoraphidium sp.) became

important (Fig. 6B; Table IV). The dominant functional

groups changed to mixed, oligotrophic or mesotrophic

conditions (Table IV). In July, the large number of

chrysophycean flagellates indicated the start of summer

Fig. 2. Interannual variability of chlorophyll a (Chl a). Error barsrepresent a 95% CI. S Delta, Selenga Delta.


799


stratification, and Bacillariophyceae were rather rare

(Fig. 6B; Table IV). Small algae such as Rhodomonas

pusilla and Chrysophyceae predominated also during

the whole August and September (Table IV). Asterionella

formosa reached a mass development (10-fold increase

within one week) that was unusual for the Bolshye

Koti site (Table IV). Under the ice of the next year

(2003) the assemblage was dominated by species

Fig. 3. Regional variability of the marker pigment concentrations for (A) Bacillariophyceae + Chrysophyceae (fucoxanthin), (B) Chlorophyta[chlorophyll b (Chl b)], (C) Cryptophyta (alloxanthin), (D) Eustigmatophyceae (violaxanthin) and (E) cyanobacterial APP (zeaxanthin) (F)contribution to total Chl a of the chemotaxonomic phytoplankton groups (see text for calculations). Combined data set 2001–2003 (July) wasused for the calculations. Error bars represent a 95% CI. S Delta, Selenga Delta; B Bay, Barguzin Bay; A Ridge, Academician Ridge; MM, MaloeMore. Lines do not indicate trends between two neighboured points, but serve to visualize regional differences.


800


preferring cold, mixed and enriched conditions, such

as A. formosa (Bacillariophyceae) (Table IV), but

shortly before ice break up Synedra acus (Bacillariophy-

ceae) and Gymnodinium baicalensis (Pyrrophyta) became

dominant (Table IV). Both indicated conditions of

nutrient availability.

Dynamics of phytoplankton pigmentsThe biovolume maximum did not correspond to the

chlorophyll and carotenoid one (Fig. 6B). Shifts towards

Chl a rich phytoplankton groups prevailed in summer,

while large and Chl a poor cells dominated in winter and

spring. Thus, the Chl a versus nano- and microphyto-

plankton biovolume ratios were <6 nmol mm�3 in

spring (May–June) but 22 nmol mm�3 on average in

summer (July–September) and 8.5 nmol mm�3 on aver-

age under the ice (February–April).

After the ice break up at the end of April 2002, Chl a

showed a first maximum in mid-May (2 nmol L�1),

decreasing strongly from the end of May to the begin-

ning of June (Fig. 6B). The clear-water phase gave way

to another Chl a maximum in mid-July (Fig. 6B) and the

sum of carotenoids increased up to 160% of Chl a.

Then, the Chl a concentration was high during summer,

when temperatures rose to a maximum of 16�C and

Secchi depth was less than 10 m (Fig. 6B). From the

end of summer to autumn the temperature, Chl a con-

centration and percentage carotenoids decreased while

the Secchi depth increased (Fig. 6B). From February to

March 2003 the Chl a concentration increased under

the ice and Secchi depth was decreased (Fig. 6B).

Fig. 4. Depth profiles of temperature and chlorophyll a (Chl a) (0–250 m) from January 2001 to December 2003 pointing out mixing andstratification over the season. Origin, site and timing of temperature and pigment data were the same. Values at the time of ice break up (April)have been interpolated. From mid-April to end of August 2003 data below 50 m were not available (hatched rectangle). Ice cover is only indicativeof this site and does not necessarily reflect conditions in the main basin.

Table II: Molar ratios of chlorophyll a (Chla) versus marker pigments and their respectivestatistics for the whole lake

Molar ratio P Partial c. 95% CI r2

Chl a/fucoxanthin 1.26 <0.001 0.81 0.12 0.977

Chl a/Chl b 3.00 <0.001 0.69 0.42

Chl a/alloxanthin 1.62 <0.001 0.37 0.54

Chl a/zeaxanthina 0.61 <0.001 0.82 0.06

Chl a/violaxanthinb 6.49 <0.001 0.84 0.57

Ratios and statistics were calculated by multiple linear regression for the

complete data set of July 2001, 2002 and 2003.aCyanobacterial zeaxanthin only (the chlorophycean part has been sub-

tracted using a zeaxanthin/lutein ratio of 5.3%).bEustigmatophycean violaxanthin only (the chlorophycean part has been

subtracted using a violaxanthin/Chl b ratio of 15%).


801


The distinct pigment changes mostly reflected varia-

tions in the phytoplankton groups. For example, pigments

found in Bacillariophyceae, such as fucoxanthin, Chl c

and diadinoxanthin, had maxima at the same time as the

biovolume, i.e. after ice break up in May (Fig. 6B), but in

summer, the Bacillariophyceae biovolume decreased

while the related pigments decreased to a lesser extent,

marking shifts towards smaller, pigment-rich Bacillario-

phyceae or towards Chrysophyceae (which also contain

those pigments). Thereby microscopic counts confirmed

the shift towards Chrysophyceae (flagellates, Table IV).

Furthermore, the Chlorophyta biovolume was low in

spring 2002 and 2003, while lutein and Chl b were

high, and in summer, lutein and Chl b increased faster

than the biovolume, suggesting the influence of chloro-

phycean APP with high pigment versus biovolume ratios

(Fig. 6B). Thus, the contribution of Chlorophyta to total

Chl a was highest in early summer (Fig. 6B). The summer

maxima and the winter decrease of zeaxanthin and b-

carotene corresponded to the changes in cyanobacterial

APP (Fig. 6B) and the contribution of cyanobacterial

picoplankton to the total Chl a was highest during sum-

mer (Fig. 6B). The CCA indicated that stratification and

temperature favoured the seasonal occurrence of chloro-

phyta and cyanobacterial APP (Table III).

DISCU SSION

Phytoplankton react quickly to environmental changes

and thus can be very useful for assessing changes in

aquatic ecosystems. This is especially so for Lake Baikal

where monitoring has been carried out for more than 60

years (Kozhov, 1963; Galazyi, 1993; Kozhova and

Izmest’eva, 1998; Popovskaya, 2000; Goldman and

Jassby, 2001; references therein). However, up until

now, few multiparameter studies have been conducted

of regional, vertical and seasonal variability. Also, com-

parison of studies set up to investigate the importance of

APP has been difficult because of the different meth-

odologies used in different decades. In this study, the aim

was to provide an overview of phytoplankton variability

over 3 years by comparing phytoplankton determined by

microscopy (to give taxonomic details) and HPLC-aided

pigment analysis, which gives rapid quantitative results

for large numbers of samples.

Regions

Variability of APP, nano- and microphytoplanktonMedian total biovolumes found in this investigation were

within the ranges of those reported in earlier studies

(Kozhova and Izmest’eva, 1998; Popovskaya, 2000).

Former studies also already indicated the importance

of APP in the South (Votintsev et al., 1972; Nagata

et al., 1994) and Centre (Nakano et al., 2003) as well as

at near-shore or river delta stations (Boraas et al., 1991),

Fig. 5. Depth profiles of (A) temperature, (B) conductivity (correctedto 20�C) and (C) chlorophyll a (Chl a) in July 2002 in the individualregions across the lake.


802


but only few studies compared the APP distribution in

the different regions. The broadest study on APP was

recently performed by Belykh and Sorokovikova (Belykh

and Sorokovikova, 2003) using epifluorescence scanning

electron microscopy. They reported an APP abundance

that varied by 2–10 times in different parts of the lake. In

2001 and 2002, the APP contribution to total biovolume

and to total Chl a varied considerably being lowest in the

North and highest in the Selenga Delta. The CCA

showed that latitude is negatively correlated to the cya-

nobacterial APP contribution, and contrasted, therefore,

suggestions of Popovskaya (Popovskaya, 2000) that APP

is generally most prominent in the North.

In most marine and freshwater systems the contribu-

tion of APP to the total biovolume and production was

inversely correlated to increasing trophy (Stockner, 1991;

Callieri and Stockner, 2002). This general concept may

not apply to Lake Baikal, assuming higher trophy in the

deltas and oligotrophic conditions in the pelagic regions of

the lake (Callender and Granina, 1997; Genkai-Kato

et al., 2002). The CCA indicated that water depth (and

thus the distance to the shore, which may be indicative for

the trophic state of the regions) was of minor influence for

the cyanobacterial APP contribution. In growth experi-

ments with Synechocystis limnetica, it was concluded that

temperature is the major driving force (Richardson et al.,

2000). In contrast, in situ, temperatures only showed sec-

ondary influence but stratification was the dominant fac-

tor for increasing cyanobacterial APP contribution.

Belykh and Sorokovikova (Belykh and Sorokovikova,

2003) also found the highest APP abundances in the

epilimnion during the periods of thermal stratification.

The nano- and microphytoplankton biovolume varied

between the basins and also between years, but not sign-

ificantly. A general increase of the biovolume from North

to South, as reviewed by Goldman and Jassby (Goldman

and Jassby, 2001), could not be confirmed in 2001 and

2002. It could also not be confirmed that the regions with

shallow waters and with river water input, such as the

Selenga Delta, showed highest biovolumes (even includ-

ing the APP), as mentioned in former comparative studies

(Bondarenko et al., 1996; Popovskaya, 2000). Therefore, if

eutrophication occurs in the Selenga Delta due to anthro-

pogenic or natural impacts (Popovskaya, 2000) it might

affect the phytoplankton composition rather than the total

biovolume.

Table III: Canonical correlation analysis (CCA)

Regional distribution (canonical loadings) Seasonal distribution (canonical loadings)

Root 1 Root 2 Root 3 Root 4 Root 1 Root 2

Set 1, environmental variables

Latitude –0.52 –0.67a 0.10 0.52 — —

Water depth –0.51 0.44 –0.71a 0.20 — —

Stratification 0.99a –0.05 –0.15 –0.05 –0.73a –0.68

Temperature 0.53 –0.47 –0.20 –0.68a –0.74a 0.67

Set 2, phytoplankton group contributionb

Total Chl a 0.87a –0.40 –0.01 0.08 –0.51 –0.57a

Bacillariophyceae + Chrysophyceae –0.28 –0.44 0.74a 0.16 0.39 –0.57a

Chlorophyta –0.06 0.92a 0.09 0.14 0.44a –0.22

Cyanobacterial APP 0.46a –0.02 –0.29 –0.07 –0.91a 0.07

Eustimatophyceae 0.16 –0.12 –0.30 –0.84a –0.33 0.38a

Cryptophyta –0.62a –0.10 –0.50 –0.02 0.16a –0.04

Eigenvalue 0.51 0.27 0.10 0.03 0.75 0.20

Canonical correlation (r) 0.72 0.52 0.31 0.18 0.86 0.45

Significance (P) 0.00 0.00 0.00 0.06 0.00 0.30

Percentage variance, set 1 0.45 0.22 0.14 0.19 0.54 0.46

Percentage variance, set 2 0.24 0.20 0.16 0.13 0.26 0.14

Redundancy, set 1 0.23 0.06 0.01 0.01 0.40 0.09

Redundancy, set 2 0.13 0.05 0.02 0.00 0.19 0.03

The stratification was determined as 0, mixed and 1, stratified according to the temperature profiles gathered with the CTD and/or submersible

fluorometer.aMarks the highest values within a set for each canonical variate.bRespective percentage contribution of each phytoplankton group to the total calculated chlorophyll a (Chl a). See text for calculation of the contributions.


803


Fig. 6. Seasonal monitoring during May 2002 to June 2003 (at the long-term monitoring station of SRIB 2.8 km offshore from Bolshye Koti,South Basin) of temperature, Secchi depth, biovolumes and selected pigments: (A) temperature at 5 m water depth and chlorophyll a (Chl a)integrated over 40 m water depth (the suggested euphotic zone) from January 2001 to December 2003. The highlighted area designate the periodof the intensive monitoring, detailed in section (B): Intensive monitoring from May 2002 to June 2003. On the left side: Secchi depth, temperature,total autotrophic picoplankton (APP) biovolume (epifluorescence microscopic spot counts + light microscopic estimation), total nano- andmicrophytoplankton (NMP biovolume and cell abundance), reciprocal Shannon–Wiener diversity index and composition of the phytoplanktoncommunity based on their share to total Chl a (see text for calculations). On the right side: total Chl a as well as marker pigments and biovolumesof the respective phytoplankton groups.


804


(Con

tinu

ed)

Tab

leIV

:A

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rse

ason

alva

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805


Tab

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:C

ontinu

ed


806


Kozhova (Kozhova, 1987) noted for river-estuary

regions enrichment by the flora of the tributaries. Possi-

bly, these species do not survive, as a diversity increase

could not be found in the delta. However, one sign of

changing phytoplankton community was the develop-

ment of the N2-fixing Aulosira sp., which indicated a

possible N limitation in the Selenga Delta. Low N/P

ratios (14) were found in the Selenga Delta in prelimin-

ary nutrient measurements in July 2003, whereas the

ratios in the open basins varied between 25 and 36 (V.

Straskrabova and J. Borovec, Ceske Budejovice, Czech

Republic, personal communication). Increasing P-load

from the tributaries (Callender and Granina, 1997) was

supposed to create the N limitation (Goldman and

Jassby, 2001).

Variability of phytoplankton pigmentsAs has been pointed out by Kozhova et al. (Kozhova

et al., 1985), it is impossible to delineate a region within

the pelagic basins characterized from year to year by

constant higher or lower Chl a. In fact, in the North for

example, each year showed significantly different Chl a

concentrations. While lowest Chl a concentrations in

2001 were found in the Centre, they were found in the

North in 2002 and 2003. Nevertheless, the combined

data set (July 2001 + 2002 + 2003) showed significant

changes for Chl a and the sum of carotenoids, as well as

for several marker pigments. For example, significantly

higher Chl a concentrations in the South compared to

the Centre and North were found. SeaWiFs satellite data

analyses at the time of the CONTINENT expeditions

(July 2001, 2002 and 2003) confirmed these trends

(Heim et al., 2005). Moreover, besides variations among

the open basins, significantly higher Chl a concentrations

were found at the river inflows. Nutrient enrichment

could be assumed to trigger Chl a increase but the

CCA suggested a higher correlation with stratification.

Stratification was enhanced in the delta because of the

warm river water inflow and because the shallow water

zone warmed up faster than the deep water basins. The

role of eutrophication might, therefore, be secondary up

to now for total phytoplankton abundance (which does,

however, not exclude the aforementioned expected shift

in the species composition if nutrient loading further

increase).

Marker pigment analysis of the open basins revealed

statistically significant changes in the phytoplankton

community that could not be distinguished statistically

using phytoplankton counts, illustrating the benefit of

fast techniques for large sample sets. For example, mar-

ker pigments of the chlorophyta, cyanobacteria and

Eustigmatophyceae decreased significantly from South

to North. Marker pigments are also potential indicators

of varying environmental conditions in regions where

total biovolume, Chl a and sum of carotenoids did not

show significant differences. For example, Chl a and

total carotenoids were both high in the Selenga Delta

and Barguzin Bay suggesting similar environmental con-

ditions. Nevertheless, the marker pigments of Bacillario-

phyceae + Chrysophyceae (e.g. fucoxanthin) were

significantly higher in the Barguzin Bay than in the

Selenga Delta, whereas the marker pigments of cyano-

bacterial APP (e.g. zeaxanthin) were significantly lower.

Therefore, different environmental conditions are likely

at the two sites. For instance, much higher concentra-

tions of humic substances (dissolved coloured organic

compounds) were observed in the Barguzin Bay (unpub-

lished data; Heim et al., 2005), which decreased the light

availability.

Depth

Regional and daily varying wind, insolation and stra-

tification have been shown to strongly influence the

phytoplankton vertical distribution (Bondarenko et al.,

1996; Kartushinsky, 1997). Below the ice, the homoge-

neous layer was due to convective flow-fields (Granin

et al., 1991, 1999; Kelley, 1997). The euphotic zone

under the clear, snow-free ice in Lake Baikal in 2003

was 1.7 * Secchi depth (Straskrabova et al., 2005) and,

therefore, a 15–35 m thick euphotic zone can be

assumed. In spring 2001, 2002 and 2003 Chl a concen-

trations up to 0.5 nmol L�1 reached 250 m and con-

centrations over 2 nmol L�1 reached 100 m. Thus, cells

were obviously transported out of the zone of maximal

productivity. In summer, the phytoplankton is concen-

trated in the upper 25 m but even during stratification

Chl a was found down to 100 m in 2001 and 2002.

Genkai-Kato et al. (Genkai-Kato et al., 2003) found that

cells collected during mixing as well as during stratifica-

tion in the deep water of Lake Baikal (500 m) were able

to photosynthesize when exposed to surface levels of

irradiance. They suggested that live Bacillariophyceae,

remnants from the spring community, sank out to

greater depths during stratification, which was supported

by unpublished taxon depth profiles of our long-term

monitoring.

However, even during homothermy the Baikalian

pelagial is not homogenous. The South is ice-free

many weeks before the North and thus is stratified ear-

lier. Warm water inflows from rivers, such as the Selenga

and Barguzin, also enhanced the stratification locally.

Primary productivity and biomass increased strongly at

stratified stations in summer 1990 (Goldman et al., 1996).

According to the present data, the higher production

was due to chlorophyta and APP, both highly correlated

to stratification.


807


Seasonal monitoring

The spring bloom 2002 was founded on Aulacoseira bai-

calensis and Stephanodiscus meyerii. Thus, although the

spring peak 2002 did not reach the biovolume of real

Melosira-years, it was based on two formerly called Melo-

sira species (Kozhova and Kobanova, 2000). However,

the dominance of large Bacillariophyceae in spring is not

conform with the generally agreed Plankton Ecology

Group-model (PEG) for freshwater lakes, which would

predict a spring crop of small, fast growing algae such

as Cryptophyta and small centric Bacillariophyceae

(Sommer et al., 1986). Comparable dominance of large

Bacillariophyceae was found in only 5 out of 18 com-

pared lakes, and four of these five were stratifying, tem-

perate, eutrophic lakes or reservoirs not deeper than 34

m (references in Sommer et al., 1986).

Subsequently, a decline of biovolume and Chl a (the

‘clear-water’ phase) was found in June that might be due to

intense grazing. Consistent with the PEG-model, edible

Cryptophyta became dominant, as well as small Chryso-

phyceae. Then, in summer the ratios of pigments versus

biovolume of the Bacillariophyceae and chlorophyta

decreased indicating a shift towards smaller, pigment-rich

cells with increasing temperatures. Contrary to the PEG-

model, which predicts growth of nonedible algae, an explo-

sive growth of edible algae, such as eukaryotic and cyano-

bacterial APP took place in Lake Baikal, confirming,

however, APP trends reported previously (Moskalenko,

1971; Goman, 1973; Belykh and Sorokovikova, 2003;

Popovskaya and Belykh, 2004). According to the CCA

the seasonal cyanobacterial APP development might be

triggered by temperature and stratification. Furthermore

light limitation due to mixing (>100 m) much below the

euphotic zone (<40 m) might depress the APP formation at

the time of maximal homothermy after ice break up and in

autumn. However, during inverse stratification under the

ice APP contributed surprisingly large amounts to the total

Chl a (c. 9%) as well as to the total primary production (up

to 40%, Straskrabova et al., 2005).

High fucoxanthin/biovolume and Chl c/biovolume

ratios indicated a summer development of small pig-

ment-rich Bacillariophyceae or Chrysophyceae cells

along with the development of picoplanktonic cells.

This summer development of small cosmopolitans at

Bolshye Koti enhanced the suggestion of the shift within

the phytoplankton community attributed to global

warming (Popovskaya, 1991, 2000; Mackay et al., 1998;

Bondarenko, 1999). However, the summer communities

in the open basins were still dominated by endemics

(Cyclotella baicalensis, ornata, and minuta) and therefore,

we may claim that, until now, the warming or eutrophi-

cation possibly affects the nearshore regions but that the

open basins still remain unaffected, due to the huge

water masses.

The maximum of the nano- and microphytoplankton

biovolume found in February/March 2003, when ice

cover was 0.8 m thick and almost free from snow,

could be due to convection under the ice when solar

radiation warmed the near-surface water. Then volumi-

nous, nonmotile Bacillariophyceae can be maintained

days or even months near the surface providing cells

with enough light for growth (Kelley, 1997; Granin

et al., 1999). However, because horizontal currents

under the ice can confuse where the cells actually

grew, caution must be expressed on the role of clear

ice for diatom growth. Asterionella formosa dominated this

site for the first time since the beginning of the long-term

monitoring at Bolshye Koti. According to the regional

distribution A. formosa was localized at Bolshye Koti, as it

was not found in abundance elsewhere. It may be that

this species is an opportunistic taxa filling a niche where

available but never dominating the whole lake. Its mass

development was probably a result of multiple asexual

reproductions (Kobanova and Izmest’eva, 2003). An

alternative may be shifts of surface currents that fre-

quently occur under the ice in Lake Baikal and move

phytoplankton horizontally. Moreover, Likhoshway et al.

(Likhoshway et al., 1996) showed that A. formosa fre-

quently occur in higher concentrations in thermal bars.

Then, its mass appearance at Bolshye Koti indicate that

caution must be applied when interpreting the long-term

phytoplankton record from one site within Lake Baikal.

CONCLUSION

This investigation of regional, vertical and seasonal distri-

bution patterns has provided a broad overview of the

present state of Lake Baikal. The use of a combined meth-

ods approach, including microscopy and HPLC-based

pigment-analysis, provided further details on natural

changes, such as shifts of algal species or group domi-

nances. On the one hand, changes of total biovolume

and Chl a revealed impacts of the river inflow and shallow

strait regions and, on the other hand, marker pigment

changes revealed differences between regions, where bio-

volumes and Chl a were not significantly different, e.g.

between Selenga Delta and Barguzin Bay. Factorization

and ordination provided further insights into the driving

forces. Temperature and stratification were shown to have

major impact on the composition of the phytoplankton

community. Therefore, we can expect that a possible

long-term warming in the lake would lead to significant

changes in the phytoplankton group and species composi-

tion towards smaller, pigment-rich cells such as small


808


diatoms or picocyanobacteria. Recently, palaeoecological

analysis of preserved markers, such as diatom valves or

photosynthetic pigments, is increasingly used to monitor

environmental change in response to climate and human

activities. Insights into the driving forces will aid interpre-

tation of sediment formation in this ancient lake.

ACKNOWLEDGEMENTS

We thank the captains, crews and expedition members

of the research vessels ‘Vereshchagin’ and ‘Kozhov’.

Thanks are also due to the staff members of the Scien-

tific Research Institute of Biology (State University

Irkutsk), especially Ludmila Kraschuk and Elena Pislegina,

and of the Limnological Institute Irkutsk (Russian Acad-

emy of Science), especially Ruslan Gnatovski and Oleg

M. Khlustov, for help in field and to staff members of the

Leibniz Institute of Freshwater Ecology and Inland

Fisheries (Berlin), especially Helgard Tauscher, Hannah

Winkler and Marianne Graupe, for help in laboratory.

Special thanks are due to Dr. H. Oberhansli, for her

permanent engagement to the CONTINENT project

(EVK2-CT-2000-0057) and support of this study. We

thank David Morley, Anson Mackay, Vera Straskrabova,

Jan Kohler and especially David Jewson, Tammi Richard-

son and anonymous reviewers for their critical remarks

and helpful comments on this manuscript.

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