Response of phytoplankton to heavy pollution of water bodies

The research was carried out in the Oleksandriya Nature Park (the town of Bila Tserkva, Ukraine) in July 2016 and covered three cascades of decorative ponds of anthropogenic origin (Fig. 1). Samples were collected from five water bodies, including Rusalka – 49º48’9”N; 30º3’25”E, Laznevy – 49º48’38”N; 30º4’19”E, Dzerkalny – 49º48’46”N; 30º4’17”E, Lebedyny – 49º48’36”N; 30º3’58”E, and Sribny Serpanok – 49º48’30”N; 30º4’11”E.

Figure 1

In the 1990s, the western part of the park, including its soil and surface waters, was heavily polluted. The maximum content of ammonium (NH₄⁺-N) in the Rusalka pond was 660.0 mg l⁻¹, of nitrite (NO₂⁻-N) – 9.13 mg l⁻¹, and nitrate (NO₃⁻-N) – 123.41 mg l⁻¹ (Pleskach 2004). The content of pollutants in water continued to increase over time. For example, the maximum content of ammonium (NH₄⁺-N) in the Rusalka pond in 2003–2004 was 862.2 mg l⁻¹, nitrite (NO₂⁻-N) – 6.06 mg l⁻¹, nitrate (NO₃⁻-N) – 115.40 mg l⁻¹, and chloride (Cl⁻) – 684 mg l⁻¹ (Krot et al. 2005; Kyryziy 2014). The geodesic research carried out in the park has shown that fertilizers stored in the “Agrokhimobyednannya” storehouse and the selection station located outside the park can be a possible source of pollution (Kulyk 2003). Despite the fact that a considerable amount of time elapsed, soil water that flows currently into the ponds of the western ravine still contains high levels of pollutants.

In July 2016, water samples for hydrochemical analysis along with phytoplankton samples were collected from the littoral zone of the studied ponds in the sections free of vegetation. In all the studied ponds, samples were collected from the surface layer of water using a Ruttner water sampler (Arsan et al. 2006).

Algal samples of 0.5 l volume were fixed with 40% solution of formaldehyde (final concentration of 4%) and concentrated by the method of sedimentation. Some samples were analyzed in the live state. The algal cell numbers (the number of algae cells) were determined by the direct count method in a Nageotte counting chamber of 0.02 ml volume. Biomass was calculated by the count cell-volume method (Arsan et al. 2006). The algal numbers were expressed in thousand cells l⁻¹, whereas biomass – in mg l⁻¹. Species whose contribution to the total numbers and/or biomass of phytoplankton in a sample was fi 10% were assigned to dominants. Algal samples were analyzed at a magnification of 200×, 400×, and 1000× using a Zeiss Axio Imager-A1 microscope. Bacillariophyta were identified using permanent preparations. Diatoms were treated with hydrogen peroxide and mounted in Naphrax high-refractive index medium. The following manuals were used to identify algal taxa (Ettl 1978; 1983; 1988; Komarek & Anagnostidis 1999; 2005; Rieth 1980; Starmach 1985; Vetrova 2004; Popovský & Pfiester 2008; Kulikovskiy et al. 2016). The Latin names and the volume of algal taxa are given in accordance with the classification systems (Tsarenko et al. 2006; 2009; 2011). Ecological characteristics of algae indicators are given according to Van Dam et al. 1994; Barinova et al. 2006.

The species composition of algae found in various water bodies was compared using the Sorensen coefficient of community similarity (Arsan et al. 2006). Cluster analysis of plankton communities was carried out using the Paleontological Statistics Software (PAST). The Pantle-Buck saprobic index (S) as modified by Sládeček (Pantle & Buck 1955, Sládeček 1973, Wasser et al. 1989) and the Shannon index of species diversity (H’) (Odum 1969) were also calculated.

All samples collected from five ponds in July 2016 were analyzed for ammonium (NH₄⁺-N), nitrite (NO₂⁻-N), nitrate (NO₃⁻-N), inorganic phosphorus (P_inorg), chloride (Cl⁻), and organic matter. The content of inorganic compounds of nitrogen and phosphorus was determined by the colorimetric method using the KFK-2 photoelectric colorimeter. The chloride ion concentration was determined by titration with silver nitrate (Mohr’s method). The indicator used was a diluted potassium chromate solution. The concentration of dissolved organic matter was determined in terms of permanganate (PO) and dichromate (DO) oxidizability (Arsan et al. 2006). Water transparency was measured using the Secchi disk. The content of chlorophyll a and the total content of carotenoids were determined by the method of spectrophotometry in acetone extracts and calculated using relevant formulas (Jeffrey & Humphrey 1975; Parsons & Strickland 1963). The obtained data were processed using the MS Excel 2010.

As Table 1 shows, the studied ponds are very similar in their morphometric characteristics. Their depth ranges from 1.0 to 2.5 m, whereas their transparency – from 0.4 to 0.7 m. All ponds are artificial water bodies, which are supplied by water from springs. The cascades of the ponds are arranged 350–400 m apart. Thus, the light intensity at their water surface is very similar.

The surface area of water occupied by macrophyte beds was insignificant in the surveyed ponds. Higher aquatic plants were represented by nine species.

No macrophytes were found in the Lebedyny pond, while in the other water bodies they were represented by one to three species.

The content of nutrients, including nitrogen and phosphorus, is one of the main characteristics of the hydrochemical regime of water bodies. Their high content results in the deterioration of the aquatic environment.

The hydrochemical analysis has shown that the studied water bodies significantly differed in the content of nutrients, primarily in the content of inorganic compounds of nitrogen, which was due to the difference in the anthropogenic load. As shown in Table 2, the Rusalka pond located in the western ravine was characterized by the highest concentration of ammonium, nitrite, nitrate, and chloride. In addition, the highest (compared to other studied water bodies) concentration of dissolved organic matter was also recorded in the Rusalka pond.

In total, 93 algal species represented by 96 infraspecific taxa were found in the water column of the studied ponds during the study period, including those containing the nomenclatural types of species from seven divisions. Chlorophyta, Bacillariophyta, and Euglenophyta (91.4% of the total number of species) were highly diverse in their species composition (Table 3).

The classes comprising the largest number of species were Chlorophyceae (36), Bacillariophyceae (22), and Euglenophyceae (13), whereas the orders represented by the largest number of species were Sphaeropleales (28), Euglenales (13), Cymbellales (6), Fragilariales (4), Bacillariales (3), and Naviculales (3). The major families (57.0% of the total number of species) included: Scenedesmaceae (17), Euglenaceae (13), Hydrodictyaceae (5), Selenastraceae (5), Fragilariaceae (4), Cymbellaceae (3), Gomphonemataceae (3), and Bacillariaceae (3), whereas the main genera (41.9%) were: Desmodesmus (Chodat) An, Friedl et E. Hegew. (9), Euglena Ehrenb. (6), Phacus Dujard. (5), Monoraphidium Komárk.-Legn. (4), Acutodesmus (E. Hegew.) P. Tsarenko (3), Coelastrum Nägeli (3), Cyclotella Kütz. (3), Ulnaria (Kütz.) Compère (3), Cymbella C. Agardh (3), and Gomphonema (C. Agardh) Ehrenb. (3).

The distribution of plankton algae in the ponds differing in the level of anthropogenic load was not uniform. Their lowest number (21) was found in the most contaminated Rusalka pond. The number of algal species in the other ponds varied from 33 to 44 (Table 3).

Taxonomic spectra of phytoplankton varied in the studied ponds. In almost all ponds, Chlorophyta (42.9–66.7%) and Bacillariophyta (16.7–31.8%) were represented by the largest number of species. Euglenophyta (33.3%) and Bacillariophyta (23.8%) ranked second and third in the Rusalka pond characterized by the highest level of contamination. Euglenophyta (16.7–31.8%) ranged third in the Laznevy, Dzerkalny, and Lebedyny ponds, whereas Cyanoprokaryota (4.9%) and Dinophyta (4.9%) – in the Sribny Serpanok pond (Table 3).

The species composition of plankton algae varied considerably in the ponds that differed in the level of contamination. The dendrogram of phytoplankton species composition similarity built based on the Sorensen coefficient produced four clusters: the first cluster included the heavily polluted Rusalka pond, the second cluster – the Lebedyny pond, the third cluster – the moderately contaminated Dzerkalny and Laznevy ponds, whereas the fourth cluster – the Sribny Serpanok pond characterized by the lowest concentration of pollutants (Fig. 2). The lowest similarity (less than 30%) was observed between the cluster representing the Rusalka pond and other clusters, which indicates significant transformations of phytoplankton species composition in this water body under the influence of heavy pollution.

Figure 2

The distribution of quantitative phytoplankton development indices was highly heterogeneous. The algal numbers varied from 17 828 thousand cells l⁻¹ to 88 569 thousand cells l⁻¹, whereas their biomass ranged from 8.235 to 34.225 mg l⁻¹. The highest numbers (88 569 thousand cells l⁻¹) and the lowest biomass of phytoplankton (8.235 mg l⁻¹) were observed in the heavily polluted Rusalka pond. The structure of the algal numbers and biomass also differed significantly (Tables 4 and 5).

In the Rusalka pond with a high concentration of pollutants, the distribution of phytoplankton numbers and biomass among individual species was not uniform, which is supported by very low values of the Shannon index (0.38 in terms of the numbers and 1.96 in terms of the biomass), which is accounted for by a high contribution of Chlorella vulgaris Beijer. to the total numbers (92.1%) and biomass (32.7%) of phytoplankton. Its higher values (2.54 in terms of the numbers and 2.27 in terms of the biomass) were recorded in the Sribny Serpanok pond with the lowest concentration of pollutants. In the other ponds, the Shannon index was 1.88–2.51 in terms of the numbers and 1.42–2.39 in terms of the biomass (Table 6). The obtained results correlate well with the literature data presented below. For example, phytoplankton in water bodies with the minimum level of anthropogenic load was characterized by high species diversity (Shannon index was 2.26–4.38), while water bodies with a high level of anthropogenic load were generally characterized by lower values of the Shannon index (1.81–1.84; Shchur et al. 2011).

In the studied ponds, phytoplankton dimensional structure was varied. In the heavily polluted pond, cells of plankton algae were smaller compared to those occurring in other ponds. Thus, the relationship between the average biomass and the average numbers of phytoplankton in the Rusalka pond was only 0.09. In the other studied water bodies, the value of this index varied from 0.30 to 0.78. In the Sribny Serpanok pond with the lowest concentration of pollutants, the size of algal cells was one order of magnitude larger (0.78) than that in the heavily polluted Rusalka pond (Table 6).

In the studied water bodies, values of the saprobic index varied over a wide range – from 1.91 to 3.11. The highest values were determined for the Rusalka pond – 3.11 (α-mesosaprobic zone), which indicates intensive contamination of this water body by organic matter and correlates with the data from hydrochemical analysis (Table 2). In the other ponds, the saprobic index values were lower – 1.91–2.31 (β-mesosaprobic zone; Table 6).

In the pond with the maximum concentration of pollutants, the relationship between the sum of carotenoids and chlorophyll a content – indicating the physiological state of phytoplankton and its functioning (Yelizarova 1973; Mineyeva 2004; Sidelev & Babanazarova 2008) – was almost twice as high (0.70) as in the pond with the minimum level of contamination (0.32), which was conditioned by chlorophyll a decomposition and by the increase in the total content of carotenoids. Thus, the chlorophyll a content in the heavily polluted Rusalka pond was 1.4 times lower compared to the Sribny Serpanok pond with the minimum concentration of pollutants, whereas the content of carotenoids was higher by a factor of 1.5. The C_car/C_chl ratio decreased with the decreasing level of contamination (Table 6). The obtained data correlate well with the results of previous research (Klochenko et al. 2019). The literature data (Belaya 2011) suggest that the accumulation of carotenoids and chlorophyll decomposition (high values of the C_car/C_chl ratio) are due to the impact of adverse factors.

The conducted research showed that different algal species dominated in the studied ponds, which is evidenced by very low Sorensen coefficient values (0–25%). Only Chlorella vulgaris dominated in four heavily and moderately polluted ponds, whereas Ulnaria acus (Kütz.) Aboal and Aulacoseira granulata (Ehrenb.) Simonsen dominated in two water bodies – the Lebedyny and Sribny Serpanok ponds. Chlorella vulgaris was not found in the pond with the minimum concentration of pollutants. Other algal species dominated only in one of the studied water bodies (Table 7).

It is significant that algal species that are indicators of organic contamination dominated in the Rusalka pond with a high content of organic matter. Those were Chlorella vulgaris and Euglena viridis Ehrenb. that are poly-α-mesosaprobic organisms. The algal species that are indicators of water salinity were also found in the Rusalka pond with a high content of chloride, i.e. Chlorella vulgaris – a halophile, and Euglena viridis – a mesohalobe occurring at relatively high concentrations of chloride, which correlates with data obtained from hydrochemical analysis (Table 2). The pond with the minimum concentration of pollutants was dominated by algal species that are indicators of moderate organic contamination – Desmodesmus armatus (Chodat) E. Hegew. (o-α–mesosaprobiont), Desmodesmus brasiliensis (Bohlin) E. Hegew. (β–mesosaprobiont), and Aulacoseira granulata (β–mesosaprobiont) indifferent to water salinity.

It should be noted that the studied water bodies differed not only in the ecological structure of the dominant complex, but also in the ecological spectra of phytoplankton in general.

In the Rusalka pond with a high content of chloride (560.5 mg l^-1), the contribution of halophiles and mesohalobes (indicators of water salinity) to the total numbers of species was higher (99.0%) compared to the other water bodies (3.2–87.2%; Fig. 3). The lowest contribution of these organisms (3.2%) was observed in the Sribny Serpanok pond characterized by the lowest content of chloride (Table 2).

Figure 3

In the Rusalka pond with the highest content of organic matter (permanganate oxidizability = 10.4 mg O l⁻¹, dichromate oxidizability = 81.0 mg O l⁻¹), the contribution of polysaprobic organisms (S = 3.5–4.0) – indicators of organic contamination – to the total numbers of algae accounted for 99.3%. In the other ponds studied, the contribution of polysaprobic organisms gradually decreased from 78.5 to 23.4% with decreasing concentration of organic matter (Table 2). No polysaprobic organisms were found in the Sribny Serpanok pond (Fig. 4). On the other hand, the contribution of β–mesosaprobionts increased with decreasing organic matter content from 0.6 to 99.6%. Its highest values were recorded in the Sribny Serpanok pond (Fig. 5).

Figure 4

Figure 5

It can be concluded that, in terms of contamination, the studied ponds can be arranged in the following order: Rusalka > Laznevy > Dzerkalny > Lebedyny > Sribny Serpanok.

The correlation analysis showed that in most cases significant negative correlations were found between the content of inorganic compounds of nitrogen, phosphorus, chloride, and organic matter and the total number of plankton algae species, the number of Cyanoprokaryota, Bacillariophyta, and Chlorophyta species and the numbers of Bacillariophyta. At the same time, significant positive correlations were found between the content of inorganic compounds of nitrogen, phosphorus, chloride, and organic matter and the number of Euglenophyta species, as well as between the content of inorganic compounds of nitrogen, chloride, and organic matter and the total numbers of phytoplankton, the numbers and biomass of Euglenophyta, the numbers and biomass of Chlorella vulgaris, and the numbers of Chlorophyta. In addition, significant positive correlations were found between pH values and the number of Cyanoprokaryota species, between the numbers and biomass of Bacillariophyta, and between water temperature and the total numbers of phytoplankton, the numbers of Chlorophyta, the biomass of Euglenophyta, and the numbers and biomass of Chlorella vulgaris. At the same time, significant negative correlations were found between water temperature and the total number of phytoplankton species and the number of Bacillariophyta and Chlorophyta species (Tables 8, 9, 10).