Analysis of the seasonal dynamics of river phytoplankton based on succession rate indices for key...

ALGAE FOR MONITORING RIVERS

Analysis of the seasonal dynamics of river phytoplanktonbased on succession rate indices for key event identification

Roman E. Romanov • Vladimir V. Kirillov

Received: 30 December 2009 / Accepted: 14 June 2011

� Springer Science+Business Media B.V. 2012

Abstract The seasonal dynamics of river phyto-

plankton was analyzed using succession rate indices

based on data collected from year-round observations

of two small plain rivers in the Upper Ob Basin

(Western Siberia). The study revealed a generally

clear seasonal pattern of structural changes in the

phytoplankton of the lower reaches of the studied

rivers. The dynamics of succession rate indices reflects

the key events in the life of phytoplankton in the

Bolshaya Losikha and Barnaulka Rivers, showing

mainly changes in the dominant species during the

main phases of the hydrological cycle. The most

significant changes in phytoplankton structure tend to

occur in the period between the spring flood decline

and the beginning of summer–autumn low water.

These changes coincide with the most drastic changes

in both environmental conditions and phytoplankton

successional stages. Use of succession rate indices to

analyze the seasonal dynamics of phytoplankton

allowed us to distinguish between periods of abrupt

change and periods of comparatively low-intensity

changes in plankton composition in small lowland

temperate rivers.

Keywords Phytoplankton � Succession rate �Community change rate � River �Western Siberia

Introduction

According to Margalef (1968), succession is one of

the most important and fruitful concepts in classical

ecology, occupying a place similar to that of evolution

in general biology. Although there is currently no

concise definition of succession, two underlying

components are generally recognized (Lewis, 1978):

(1) succession determines changes in species abun-

dance within a community, and (2) succession is a

directed change. Furthermore, it is far more useful to

express rates of changes in a community quantitatively

rather than just point out the direction of such changes.

A succession index value characterizes the rate of

change in the relative abundance of all components in

a given community. In analysis of community dynam-

ics, it enables complete and concise descriptions of

bulky statistics and the phenomenology of community

succession (Lewis, 1978). It also allows changes in the

succession structure that correspond to significant

environmental changes to be identified (Reynolds,

Guest editors: L. Ector, D. Hlubikova & L. Hoffmann /

Proceedings of the 7th International Symposium ‘‘Use of Algae

for Monitoring Rivers’’, Luxembourg, November 23–25, 2009

R. E. Romanov (&)

Central Siberian Botanical Garden, Siberian Branch of

Russian Academy of Sciences, Zolotodolinskaya St.,

101, Novosibirsk, Russia 630090

e-mail: [email protected]

V. V. Kirillov

Institute for Water and Environmental Problems of SB

RAS, Molodeznaya St., 1, Barnaul, Russia 656038

e-mail: [email protected]

123

Hydrobiologia

DOI 10.1007/s10750-012-1198-6

1984). Moreover, this method allows us to outline the

general character of a community’s dynamics, i.e., to

define whether it is cyclic, directed change (succes-

sion) or stochastic (Collins et al., 2000). Changes in

community structure tend to be sharp or asymmetrical

when they are caused by abrupt shifts in allogenic

factors, and, conversely, gradual changes mean

autogenic species replacement, which corresponds to

ecological succession (Reynolds, 1988; Huszar &

Reynolds, 1997).

Succession rate indices can be used as a universal

approach to analyze succession in various types of

community (Lewis, 1978; Huhta, 1979; Stephenson,

1980; Collins et al., 2000; Foster & Tilman, 2000).

Establishing temporal heterogeneity in the structure of

aquatic communities is one element in the empirical

statistical description model used as a tool in quanti-

tative ecological forecasting and paleoecological

reconstruction.

Phytoplankton lends itself well to succession

research because of the short life cycles of its

components (Huszar & Reynolds, 1997), which leads

to relatively rapid structural responses to environ-

mental change. Use of succession rate indices in

analysis of phytoplankton dynamics has been

severely criticized due to the strong influence of

counting error on the results; thus, succession rate

indices can be applied only when ‘‘uncertainty

derived from counting error is considered’’ (Duarte

et al., 1990), i.e., only to data with the lowest possible

values of counting error. Moreover, these measures

may theoretically be insensitive to community com-

position changes when changes in the fractions

of different species are counterbalanced (Rojo &

Alvarez Cobelas, 1993). Obviously, a succession rate

index as a measure of change intensity ‘‘gives little

information about the nature of that change’’ (Kuhn

et al., 1981).

Nevertheless, this method can be used fruitfully in

analysis of phytoplankton and periphyton dynamics,

and has allowed identification of stages of seasonal

succession or differentiation of parts of reservoirs with

different intensities of phytoplankton succession

(Kuhn et al., 1981; Millie & Lowe, 1983; Reynolds,

1984, 2006; Trimbee & Harris, 1984; Giorgio et al.,

1991; Huszar et al., 1998; Hubble & Harper, 2002; de

Souza Cardoso & da Motta Marques, 2003; Pannard

et al., 2008). This succession rate indices approach

has been applied to potamophytoplankton succession

analysis in only a few cases to date (Giorgio et al.,

1991; Garcıa de Emiliani, 1997).

The aim of this work is to analyze the seasonal

dynamics of river phytoplankton using different

succession rate indices in order to recognize key

events and detect the periods of most significant

change in river phytoplankton composition.

Materials and methods

Study sites

Two lowland rivers of the Upper Ob Basin were

chosen as the study locations: the Barnaulka and

Bolshaya Losikha Rivers. The lower reaches of the

Barnaulka and Bolshaya Losikha Rivers were studied

in 2001–2003 (Fig. 1). Of all the innumerable small

rivers of Western Siberia, the complete seasonal

dynamics of phytoplankton is described only for these

two. Data from these surveys can be used to calculate

succession rate indices by sampling frequency and

duration, yielding comparatively low counting errors

due to accurate sample analysis (see below).

The Bolshaya Losikha River flows into a channel of

the Ob near the Town of Barnaul. According to the

Korytny classification of river systems (2001), the

Bolshaya Losikha is a medium-length river (150 km)

with small catchment area (1,500 km2). The flow

velocity of the Bolshaya Losikha near its mouth varied

from 0.5 to 0.7 m s-1 in the summer–autumn low

water period of 2002. The salinity during spring floods

is 0.1–0.2 mg l-1, rising to 0.5–0.6 g l-1 in summer

(Uryvaev, 1962).

The Barnaulka River flows into the Ob within the

city limits of Barnaul. According to Korytny (2001),

the Barnaulka is a medium-sized river (approximately

200 km in length with 5,700 km2 watershed), catego-

rized as minor by discharge. Measurements conducted

in 2000 showed discharge varying from 0.4 m3 s-1

(March 14) to 7.3 m3 s-1 (April 12), and flow velocity

between 0.3 m s-1 (October 5) and 0.9 m s-1 (April

12) (Temerev et al., 2001). In the summer–autumn

low water period, the water salinity of the Barnaulka

varies from 0.16 to 0.90 g l-1 at various measurement

locations. The concentration of biogens, i.e., inorganic

compounds of phosphorus and nitrogen, is very high,

and increases further downstream. In the middle and

lower reaches, both the water and bottom sediments

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123

are contaminated with heavy metals and harmful

organic compounds (Mikhailov et al. 2000; Tret’yak-

ova, 2000; Temerev et al., 2001), as supported by data

on zooplankton and zoobenthos (Bezmaternykh &

Eidukaitene, 2003).

The spring floods on the plain rivers of the Upper

Ob Basin are followed by steady low waters that

remain until the formation of ice before falling further

to the winter low water level. There are, however,

occasional insubstantial floods (one or two per

season). A system of lakes in the upper reaches of

the Barnaulka and the swamped floodplains in its

upper and middle reaches define the low values of

maximal flood discharge and explain the relatively

extended spring flood period (Uryvaev, 1962). The

low water season in the Barnaulka is rarely interrupted

by floods (Shenberg, 1991).

Phytoplankton sampling and analysis

Phytoplankton in the Barnaulka was sampled 1 km from

the river mouth from November 2001 to February 2003,

and samples in the Bolshaya Losikha were collected

6.5 km from the mouth from December 2001 to

December 2002 at 10–15-day intervals. The samples

were fixed with 40% formaldehyde solution to final

concentration of 2–4%, and filtered through Vladipor

no. 6 membrane filters with pore diameter of

0.55–0.65 lm. A total of 59 samples were analyzed

by light microscopy using standard techniques (Wasser,

Fig. 1 Map of the Upper

Ob drainage basin showing

the location of two sampling

sites at two rivers

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123

1989): 32 from the Barnaulka and 27 from the Bolshaya

Losikha. At least 500 individuals, and all cells in all 500

individuals, were counted in each sample to achieve the

lowest possible count error (*10%). To calculate the

biomass (biovolume), cell volumes were approximated

as simple or combined geometric figures. Diatoms were

identified in permanent preparations.

The numbers of cells and individuals (solitary cells,

colonies, coenobia, filaments, temporary cell aggregates)

were counted independently, resulting in two indepen-

dent sets of values for the Barnaulka and Bolshaya

Losikha Rivers. The cell and individual counts are not

interchangeable, and their integration into a single set of

values is impossible. Using both of these independent

measurements simultaneously instead of the more com-

monly used cell count method allowed more precise

evaluation of the role of species and of the size groups of

phytoplankton (Shtin, 1945; Mikheyeva & Lukyanova,

1999, 2000). Noncolonial centric diatoms (mostly Step-

hanodiscus spp. and Cyclotella spp.) were counted in

bulk without regard to the particular species since it is

impossible to distinguish them adequately under light

microscopy and in uncleaned material. Species of

Gymnodinium, Chlamydomonas, and Cryptomonas were

counted and used for index calculation (see below) as

aggregate components (Gymnodinium spp., etc.) since

the exact identification of individual cell types is

impossible in formaldehyde-fixed material.

Data analysis

Succession rate indices (SD, ED, WG) were calculated

using the following three formulae:

SDt1;t2 ¼Xn

k¼1

pk2� pk1

j j !,

t2 � t1ð Þ;

EDt1;t2 ¼Xn

k¼1

ðpk2� pk1

Þ2" #1=2,

ðt2 � t1Þ;

WGt1;t2

¼Xn

k¼1

pk2log2 pk2

�Pn

k¼1

pk2log2 pk2

� pk1log2 pk1

�Pn

k¼1

pk1log2 pk1

2

664

3

775

20

BB@

1

CCA

1=2

,

ðt2 � t1Þ;

pkiis the share of species k in the total abundance of a

community at time point ti; n is the number of species

in the community at time points t1 and t2 (Williams &

Goldman, 1975; Lewis, 1978; Stephenson, 1980),

however only for periods of comparable sampling

intensity.

The numerator in SD corresponds to an n-dimen-

sional vector rate. Its start–end coordinates describe

two points in an n-dimensional space. In our case,

these points describe the set of species of phytoplank-

ton at t1 and t2; the numerator in ED corresponds to the

n-dimensional vector length mentioned above

(Euclidean distance). Both expressions conform to

the distance function definition and are a particular

case of the lp-norm (Duran & Odell 1974) and a

particular case of the Minkovsky distance metric

function. The WG index, where the numerator also

obeys the definition of a distance function, is the rate

of community movement through the diversity space

and assigns a value to the relative contribution of a

single species to the diversity of the whole commu-

nity. If the species composition has changed but the

community diversity has stayed the same, WG will be

greater than zero (Williams & Goldman, 1975). SD is

less sensitive to counting error than the index proposed

by Jassby & Goldman (1974); the latter was not used

in our research. Due to the large influence of counting

errors on succession rate index values (Duarte et al.,

1990), only prominent differences in rate index values

(at least threefold) were taken into account.

Results

Taxonomic richness

A total of 383 species belonging to 138 genera and 63

families were found in the phytoplankton of the

Barnaulka River (Romanov & Kirillov, 2009). The

phytoplankton richness in the Bolshaya Losikha was

somewhat lower: 362 species in 128 genera and 55

families. The highest richness was seen among the

green algae, diatoms, euglenoids, and cyanobacteria.

The green algae were always superior in richness

compared with diatoms, and euglenoids were enriched

compared with cyanobacteria. The taxonomic richness

of the other algal groups was very low.

The seasonal dynamics of the numbers of simulta-

neously vegetating species (including their varieties

and forms) was similar in the studied rivers

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123

(hereinafter referred to as simultaneous species

richness, SSR). Minimum SSR was registered during

winter low water and during floods (11–54 species,

varieties, and forms); maximum SSR was registered

during summer and autumn low water when the water

temperatures are highest (90–129 species, varieties,

and forms). The SSR peaked dramatically with the

decline of floods (Romanov, 2006).

Seasonal dynamics of abundance and composition

Planktonic forms, diatoms, green algae, and, in a few

cases, cyanobacteria form the core of phytoplankton in

the studied rivers.

The abundance of the fluctuation range of phyto-

plankton in the Bolshaya Losikha was significantly

broader compared with that of the Barnaulka (Table 1).

Cell count, individual count, and gross biomass of

phytoplankton in the Barnaulka River were approxi-

mately the same during the winter low water season

and spring floods (less than 0.23 9 106 cells l-1,

0.15 9 106 individuals l-1, 0.2 g m-3; Fig. 2). The

counts rose dramatically during the flood decline along

with the fall in water level. The maximum values for cell

count, individual count, and gross biomass were

recorded during periods that were relatively stable

hydrologically, with water temperatures above 10.0�C,

primarily during the summer–autumn low water season

(early May through early September).

Similarly to the Barnaulka, noncolonial centric

diatoms were the dominant group throughout the larger

part of the year. Their abundance reached 31.6 9 106

cells or individuals l-1, 16.1 g m-3, and their share

of total phytoplankton abundance was 58.4, 63.8,

and 89.0%, respectively. Monoraphidium contortum

(Thuret) Komarkova-Legnerova and Chrysococcus

rufescens f. tripora J.W.G. Lund had the top cell and

individual counts (up to 11.7 9 106 cells or individu-

als l-1, 21.9% of total phytoplankton cell count, 22.7%

of total individual count, and up to 4.2 9 106 cells or

individuals l-1, 46.9% of total phytoplankton cell

count, 37.0% of total individual count, respectively),

while Chlamydomonas spp. dominated the gross bio-

mass (up to 1.2 g m-3, 84.3% of total biomass).

The studies revealed two seasonal peaks of abun-

dance in Barnaulka River phytoplankton (Fig. 3). The

first peak corresponded to the spring flood decline (up to

6.0 9 106 cells l-1, 4.6 9 106 individuals l-1, 3.7 g

m-3), and the second, stronger peak to the season

preceding ice cover formation (up to 35.1 9 106

cells l-1, 9.6 9 106 individuals l-1, 4.6 g m-3). The

cell count, individual count, and gross biomass of

phytoplankton were low (up to 1.0 9 106 cells l-1,

0.6 9 106 individuals l-1, 0.6 g m-3) in the winter low

water of 2001–2002. On the contrary, phytoplankton

abundance was higher in the first half of the winter low

water of 2002–2003 due to significant development of

noncolonial centric diatoms and Limnothrix redekei

(Van Goor) Meffert (up to 27 9 106 cells l-1, 2.3 9

106 trichomes l-1, 0.4 g m-3; 77.3, 24.1, and 7.8% of

total phytoplankton abundance, respectively). The cell

count, individual count, and gross biomass of phyto-

plankton were in the same order during the winter low

water of 2001–2002 and the following spring flood. The

abundance of phytoplankton increased significantly

with the flood decline, due mainly to an outburst of

noncolonial diatoms and Chlamydomonas spp., reach-

ing 0.5–3.2 9 106 cells l-1, 0.2–2.4 9 106 individu-

als l-1, and 0.3–3.6 g m-3. Noncolonial centric

diatoms often dominated all three values—cell count,

individual count, and gross biomass (up to 68.6, 71.2,

and 73.4% of total abundance of phytoplankton,

respectively)—and M. contortum by cell count and

individual count (up to 40.0 and 43.8% of total

abundance of phytoplankton, respectively). The maxi-

mal abundance of noncolonial centric diatoms

was 6.4 9 106 cells l-1, 5.9 9 106 individuals l-1,

and 2.75 g m-3; that of M. contortum was up to

758.0 9 103 cells or individuals l-1.

Seasonal dynamics of succession rate indices

Use of SD and ED indices (linear correlation coeffi-

cient for Bolshaya Losikha and Barnaulka, k =

0.85–0.98; Table 2), cell count and individual count

Table 1 Abundance of phytoplankton in the Bolshaya Losi-

kha and Barnaulka Rivers

Abundance index, season, unit Bolshaya

Losikha

River

Barnaulka

River

Cell count, all seasons,

106 cells l-10.02–95.68 0.19–35.10

Individual count, all seasons,

106 individuals l-10.01–57.83 0.13–9.65

Biomass, all seasons, g m-3 0.01–18.80 0.08–4.57

Arithmetical mean biomass,

open water period, g m-34.94 ± 1.47 1.53 ± 0.28

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123

(k = 0.72–0.87) yielded very similar results. The

seasonal dynamics of the SD and WG indices were

similar only in their general features (Figs. 4, 5).

The seasonal dynamics of values of succession rate

indices by cell count, individual count, and gross

biomass of the Bolshaya Losikha phytoplankton share

two features. Firstly, they peaked in the second third of

the low water season of 2001–2002 and during the

flood decline. Secondly, they showed reduced vari-

ability from the summer–autumn low water through

the first half of the winter low water season of

2002–2003 (Fig. 4). The latter was less obvious by

the cell-count-based SD. There were no peaks in the

second half of the winter low water in the seasonal

dynamics of the biomass-based ED.

The maximum values of the succession rate indices

at the flood decline reflect the sharp change of

dominants from Chlamydomonas spp. to noncolonial

centric diatoms, just as in the Barnaulka River.

Presumably this was due to the significant decrease

in velocity, level decline, and increase in the residence

time of the river waters.

Only two peaks in the individual-count-based SD

values for the Barnaulka exceeded 0.1 day-1.

Reynolds (1984) used this threshold to analyze

phytoplankton succession in a number of lakes and

Fig. 2 Seasonal dynamics

of phytoplankton abundance

in the lower reach of the

Bolshaya Losikha in 2002


of phytoplankton abundance

in the lower reach of the

Barnaulka in 2002

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experimental mesocosms. The first maximum at the

flood decline (Fig. 5) reflects the change of dominants

from Chlamydomonas spp. to noncolonial centric

diatoms; the second maximum at the beginning of the

summer–autumn low water season corresponds to the

change from the apparent dominance of the latter

group to M. contortum and Nitzschia acicularis (Kut-

zing) W. Smith subdominance. The SD values vary

greatly in the summer–autumn and winter low water

seasons. The peak at the boundary between the

summer–autumn and winter low water seasons is

more prominent, especially in terms of the cell count,

and reflects the onset of L. redekei dominance. The

cell-count- and individual-count-based WG are less

informative; their dynamics shows a clearer peak at

the flood decline.

The values of biomass-based ED varied greatly

throughout the year and were relatively higher in the

period from the second half of the spring floods to the

beginning of the summer–autumn low water season,

when a sharp decline in the water level takes place.

Above all, these peaks reflect the changes in the

relative abundance of noncolonial centric diatoms.

A peak of the biomass-based ED in the first half of the

winter low water after ice cover formation also reflects

the increase of the L. redekei share.

The biomass-based WG values for the Barnaulka

did not vary much throughout the year; there was,

however, a noticeable peak at flood decline. Observa-

tions of the first half of the winter low water season of

2002–2003 yielded stable, low values.

The most significant and relatively rapid changes in

the composition and the increase in SSR and abundance

of phytoplankton in the Bolshaya Losikha and Barnaulka

tend to occur in the period between the spring flood

decline to the beginning of the summer–autumn low

water season. In the Barnaulka River, the sharpest

changes were registered a month earlier. This can

probably be explained by its specific hydrological regime

due to a system of flood lakes in its upper reaches.

Discussion

On the whole, the observed structural and quantitative

dynamics of phytoplankton in the lower reaches of the

Barnaulka and Bolshaya Losikha was seasonal. The

wider annual abundance fluctuation range in the

Bolshaya Losikha compared with that of the Barna-

ulka most likely reflects the hydrology specifics of the

latter due to the presence of a system of lakes in its

upper reaches. Taking into account the high content of

ammonium, nitrogen, nitrite, and phosphates in the

water of the Barnaulka (Tret’yakova, 2000), it can be

assumed that growth of algae and cyanobacteria is not

limited by biogens, or at least that it has not been since

the 1960s (Maslov, 1969) until the present day, when

the river has become essentially a sewer. In terms of

the seasonal dynamics of phytoplankton biomass, the

Bolshaya Losikha is similar to the lowland river

Berounka (139.1 km in length), a small tributary of the

River Vltava (Desortova & Puncochar, 2010).

Table 2 Linear correlation indices of phytoplankton succes-

sion rate of the lower reaches of the Barnaulka (n = 28; above

the diagonal from the upper left to the lower right corner) and

the Bolshaya Losikha (n = 25; below the diagonal); with

assurance by Student criterion at * P \ 0.05; ** P \ 0.01;

*** P \ 0.001

ED by

cell count

ED by

individual

count

ED by

biomass

SD by

cell count

SD by

individual

count

SD by

biomass

WG by

cell count

WG by

individual

count

WG by

biomass

1 2 3 4 5 6 7 8 9

1 – 0.82 0.54 0.95 0.84 0.43 0.56*** 0.47 0.59

2 0.72 – 0.47 0.80 0.98 0.52 0.49 0.56*** 0.46

3 0.65 0.72 – 0.58*** 0.53*** 0.88 0.45 0.34 0.71

4 0.85 0.64 0.46** – 0.82 0.49 0.57*** 0.51 0.69

5 0.64 0.91 0.53 0.76 – 0.57 0.59 0.63 0.58

6 0.53*** 0.69 0.88 0.57 0.65 – 0.51 0.50 0.57***

7 0.60*** 0.29* 0.16* 0.59*** 0.41** 0.20* – 0.83 0.68

8 0.49** 0.48** 0.17* 0.62 0.67 0.33* 0.87 – 0.61

9 0.53** 0.38*** 0.30* 0.52*** 0.46** 0.42** 0.85 0.82 –

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123


of succession rate indices in

the lower reach of the

Bolshaya Losikha in 2002:

a by cell count, b by

individual count, and c by

biomass

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123

As a rule, the maximal abundance and SSR were

recorded during the summer–autumn low water season

at the lowest current velocity, discharge, and water level

(Weber & Moore, 1967; Okhapkin, 2000; Zalokar de

Domitrovic, 2002). Judging by the arithmetic mean

biomass values of phytoplankton from the open water

period (Table 1), the Bolshaya Losikha is meso-eutro-

phic, and the Barnaulka mesotrophic (Okhapkin, 2002).

Application of formal methods to data analysis of

phytoplankton richness and abundance in different


of succession rate indices in

the lower reach of the

Barnaulka in 2002: a by cell

count, b by individual count,

and c by biomass

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123

seasons of the year performed on two plain rivers of

the Upper Ob Basin has thus revealed more precisely

the patterns of seasonal heterogeneity in phytoplank-

ton distribution.

The seasonal succession of river phytoplankton

based on succession rate indices has been analyzed

only occasionally (Giorgio et al., 1991; Garcıa de

Emiliani, 1997), and only once (this work) to identify

the key events in the seasonal dynamics of potamo-

plankton. Consequently, a wider comparison of

different types of rivers on the basis of the approach

realized here is virtually impossible at the moment.

It is possible that, in some cases, the phytoplankton of a

lotic ecosystem shows less structure and diversity

compared with that of a floodplain lake, as in the case

of the Parana River canal and a small floodplain lake

connected with this canal during floods (Garcıa de

Emiliani, 1997). In the Parana River canal, biomass-

based SD values varied from 0.03 to 0.11 day-1

(sampling was done twice a week) and exceeded the

threshold of 0.1 day-1 in only two cases: at the beginning

of the flood decline along with the decrease in water level,

and during the summer–autumn low water season (Garcıa

de Emiliani, 1997). In a tributary of the Parana River, the

cell-count-based SD values varied between 0.03 and

0.16 day-1 (Giorgio et al., 1991).

The values of biomass- and cell-count-based SD in

the Bolshaya Losikha were within the same limits as

those reported for the lotic ecosystems of the Parana

River system; the values registered in the Barnaulka

during the first half of the winter low water season

were lower. Further sampling with comparable inten-

sity is required before more meaningful comparison

with data for other rivers can be made.

Quite in accordance with the results of Williams &

Goldman (1975) on phytoplankton succession in five

lakes of different types, we conclude that, in phyto-

plankton of small lowland rivers of the Upper Ob

Basin, the ‘‘maximum succession rates (also) occur

after community independent environmental pertur-

bations which are usually but not necessarily corre-

lated with periods of high primary productivity’’ and

‘‘in the absence of disturbance succession rates decline

and remain low, partly because of community depen-

dent processes’’ (Williams & Goldman, 1975).

The key events in the seasonal dynamics of phyto-

plankton correspond to the main hydrological seasons of

the small lowland rivers of the Upper Ob Basin. This is

concordant with data from numerous publications on

the key role of hydrological factors in potamophyto-

plankton succession (Reynolds, 1984; Ibelings et al.,

1998; Zalokar de Domitrovic, 2002; Desortova &

Puncochar, 2010). The intensity and frequency of

disturbances caused by precipitation and water discharge

fluctuation are the most important factors determining

potamophytoplankton dynamics (Reynolds, 1988;

Ha et al., 1998). We consequently assume that river

phytoplankton succession is mainly allogenic; however,

the potamophytoplankton could be a subclimactic

community, i.e., the aquatic analog of the plagioclimax

(Reynolds, 1993; Garcıa de Emiliani, 1997).

The spatiotemporal heterogeneity of the structure

and abundance of potamoplankton is determined by

the formation of water runoff, and reflects the age

heterogeneity of the water masses in a river from the

source to the mouth. We can assume that the sequence

of changes in phytoplankton structure and abundance

observed at a stable sampling point on a river during

the year is not in fact ‘‘true succession’’. More likely, it

results from the superposition of two processes: (1) the

succession of phytoplankton along the course of

the river downstream (Margalef, 1968), and (2) the

seasonal succession of phytoplankton (Trifonova,

1986). The different water residence time probably

determined the observed ‘‘result’’ of this superposition

at a stable, year-round sampling point on the river.

This chronosequence is usually described as the

seasonal dynamics of potamophytoplankton.

Since there is no consensus on what causes species

changes in phytoplankton communities (Mikheyeva,

1983), the effectiveness of succession rate indices for

indicating and reconstructing specifics of annual

dynamics of phytoplankton communities in reservoirs

depending on their geographical location and the

degree and character of external impact makes use

of these indices for typological assessment of aquatic

ecosystems reasonable. Comparing the succession

rates for the same water body in different years can

be used as the basis for assessment of succession

character, including the rate of eutrophication pro-

cesses. The latter is of great importance for environ-

mental quality management.

Conclusions

The results of this study reveal a generally clear

seasonal pattern of changes in phytoplankton species

Hydrobiologia

123

structure in the lower reaches of small rivers, which is

probably due to sufficient water residence time and the

smaller influence of rainfall floods on their hydrology.

The dynamics of succession rate index values clearly

reflects key events in the life of river phytoplankton

that are connected with changes in dominant species

complexes according to the main hydrological sea-

sons. The most significant and rapid changes in

structure, as well as increases in species richness and

abundance of phytoplankton in the Bolshaya Losikha

and Barnaulka Rivers, tend to occur in the period

between the flood decline to the beginning of the

summer–autumn low water season. The dynamics

reflect both the most important and abrupt changes in

the environment and changes in the recorded stages of

phytoplankton succession.

Acknowledgments The authors are greatly indebted to

anonymous reviewers and Dr. Eduardo A. Morales for

valuable comments and to Dr. Helen Rothnie and Tatyana M.

Bulyonkova for improvement of the English manuscript.

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