Taxonomical Composition and Functional Structure of Phytoplankton in Two Water Supply Reservoirs in Serbia

Dragana Predojević1, Vesna Karadžić2, Gordana Subakov-Simić3



1 University of Belgrade, Faculty of Biology, Studentski trg 16, 11000 Belgrade, Serbia; Phone:+381 11 3244847; Fax: +381 11 3243603; E-mail: This e-mail address is being protected from spambots. You need JavaScript enabled to view it

2 Institute of Public Health of Serbia „Dr Milan Jovanović Batut", Dr Subotica 5, 11000 Belgrade, Serbia

3 University of Belgrade, Faculty of Biology, Takovska 45, 11000 Belgrade, Serbia




Species composition, seasonal succession and functional structure of phytoplankton were analyzed in water supply reservoirs Garaši and Bukulja. Samples were taken in September 2005, November 2005, July 2006 and October 2006 from different depths (Bukulja: 4m, 8m; Garaši: 0m, 4m, 8m and 13m). Six phytoplankton divisions with 194 taxa were present. The most dominant division was Bacillariophyta, followed by Chlorophyta division. Functional groups were determined for all taxa whose relative biomasses represented ≥ 5 % of the total biomass in the samples. A total number of 11 functional group was present. H1, C, J, S1, LM were the most dominant functional groups in these two reservoirs. Successional sequence of functional groups B(C) /Y →G → H1→ M → LM, as general pattern, was confirmed, but with some exceptions. Ceratium hirundinella and Microcystis aeruginosa, which are the members of codon LM, are found together, but in almost every season which is rarely a situation.

Keywords: cyanobacteria, Ceratium, Microcystis, codon.



The phytoplankton community forms a key component of primary production in reservoirs. Phytoplankton constitutes a diverse congregation of short-living organisms, which derive their nutrients from the water column of reservoirs. These features make this community the most direct and initial earliest indicator of the impacts of changing nutrient conditions in reservoir ecosystems. It also makes them particularly suitable for measuring the success of restoration measures following reductions in nutrient loads (Carvalho et al., 2012).

Functioning of aquatic ecosystems largely depends on phytoplankton morpho-functional diversity, as produced by the range of environmental pressures to which this group of organisms is adapted, which in turn allow them to cope with the environmental constraints (Hu et al., 2013). In particular, resource availability, water motion and temperature, largely contribute to set the specific composition of the phytoplankton assemblages, the shape and size of the organisms involved and their seasonal succession (Naselli-Flores et al., 2007; Naselli-Flores andBarone, 2011). For this reason, investigations on phytoplankton dynamics and structure are considered basic tools to understand the ecology of aquatic ecosystems (Hu et al., 2013).

The identification of organisms at the species level is a time consuming activity which involves high costs in terms of time and expertise (Hu et al., 2013), and because of that taxonomic classifications are very impractical.

There was a need to create a system of classification which has practical application, which replaces long taxonomic lists (Padisák et al., 2009) and makes easier both the interpretation of ecological patterns and the comparison among different freshwater ecosystems (Hu et al., 2013).

The use of ecological classification systems is becoming more and more widely used in analysis of phytoplankton. One of the first formal attempts to define a system of classification based on the functional properties of the phytoplankton was proposed by Reynolds (1980, 1984). Utilizing long series of phytoplankton observations from a group of lakes in Northwest England, he distinguished 14 associations, with each comprising species that coexist and increase or decrease in numbers simultaneously. The species of a particular association share common ecological attributes so that they may potentially dominate or co-dominate (SalmasoandPadisák, 2007). Successively, this functional system of classification was refined and expanded (Reynolds, 1997; Padisák and Reynolds, 1998; Reynolds et al., 2002; Padisák et al., 2003, 2006, 2009). Such classification is of practical use for generalizations across species and represent necessary tool for scientific communication and water-body analysis (Körner, 1993).

The changes in abundance and composition experienced by phytoplankton communities in lakes and reservoirs occur in response to variations in the physical (light, climate or energy) and the chemical (nutrient availability or resources) constraints for algal growth (Hoyer et al., 2009).

The aim of this study is to see can classification based on functional groups replace the traditional taxonomical classification of phytoplankton community? So, we observed traditional taxonomical classification as well as classification based on functional groups.