Phytocenosis biodiversity at various water levels in mesotrophic Lake Arakhley, Lake Baikal basin, Russia

Study Area

Lake Arakhley is located south of the Vitim Plateau within the Beklemishev tectonic basin. The area is characterized by a continental subarctic climate with considerate diurnal temperatures, long, cold, dry winters and short, hot summers with more precipitation occurring during the latter half of the season. The lake is used for recreation and fishery purposes and is approximately 100 km from Chita, the capital of the Zabaikalsky region (Fig. 1, Table 1).

Lake Arakhley’s water regime is determined by changes in the ratio of water balance elements. Precipitation on the reservoir surface is slightly higher than the inflow (precipitation equals 17.8 million m³/year; inflow equals 16.1 million m³/year) and accounts for the incoming water balance of Lake Arakhley. Water typically dissipates through evaporation (27.1 million m³/year) and runoff from the lake only accounts for 20% of the outflow (Obyazov, 2011). Consequently, changes in the moisture content are reflected in the cyclical variations in the water level. The cyclical variations of the water level coincide with the cyclicality of the atmospheric precipitation. The integral difference curve reveals the phases of low (precipitation below normal) and high (precipitation above normal) moisture content of the territory (Obyazov, 2011). Long-term changes in Lake Arakhley’s water levels are shown in Fig. 2.

The water level was highest in 1962 and decreased over the following year. The decline in the water level slowed between 1967–1968 then increased until 1972. The next low-water phase continued until 1980, at which point the water level increased over the next 4–6 years. Water level fluctuations continued until 1990–1991. In 2008 the water level was close to the absolute minimum (Obyazov, 2011; Obyazov, 2014). We observed the minimum water level in 2017–2018, when the level decreased by approximately 2 m. This decrease caused a 50 m displacement of the water’s edge, causing the littoral zone, composed of sand and gravel deposits, to disappear.

Physical and chemical data

We used data from 2011, 2013, 2014, and 2016–2018 to analyze the long-term dynamics of hydrochemical parameters (Tsybekmitova & Subbotina, 2013; Tsybekmitova et al., 2020). Hydrochemical data taken during the low-water period in Lake Arakhley show the state of its ecosystem (Fig. 2). Samples were collected from the surface and bottom layers using a Schindler-Patalas trap (PB-6, Borok, Russia). Surface horizon samples were taken 0.10 m below the water surface level, and bottom water samples were taken 0.10 m above the bottom. We conducted a chemical analysis of the water to identify nitrites using Griss reagent, nitrates (reduction to nitrites with the Griss reagent), ammonium ions (using the Nessler reagent), phosphates (with a reagent mixed with ascorbic acid), and total phosphorus (by combustion with potassium persulfate). The organic carbon concentration was determined by adding wet potassium dichromate oxidation (COD) and permanganate oxidation (PO) to lake water samples. These methods are described in detail by Adamovich et al. (2019). Concentrations were determined using a Spekol-1300 spectrophotometer. We used the ion chromatography system ICS-1600 and a Profile Plus inductively coupled plasma atomic emission spectrometer to determine the macro- and micro-components of water with 2% accuracy. The physical and chemical parameters of water (pH, total dissolved solids, water temperature, electrical conductivity, oxidation–reduction potential, salinity, dissolved oxygen content, and turbidity) during sampling were measured using AQWA-READER (Germany). These methods have been used since 2000 to monitor Lake Arakhley long term.

Phytoplankton data

Phytoplankton samples were taken in May–June, July–August, October, and December of 2017–2018. We used data from the following periods to analyze the long-term dynamics of phytoplankton: 1966–1969 (Morozova, 1975; Morozova, 1981), 1970–1971 (Morozova & Shishkin, 1973; Morozova, 1981), 1988 and 1994–1995 (Ogly, 1993; Ogly, 1995), and 2008–2009 (Tashlykova & Koryakina, 2013).

Phytoplankton was collected from 0.5–1.0 L water samples taken from two or three horizons (surface, transparency, bottom) using the Schindler-Patalas sampler (PB-6, Borok, Russia) in the deep-water sites of the lake. Quantitative samples were fixed with a 4% formalin solution and quality samples were fixed with Lugol’s solution. The samples were prepared using the sedimentary method and each sample was processed separately. Algae were counted according to the Hansen method (Sadchikov, 2003) on a counting plate. The biomass was determined based on the volume of individual algae cells or colonies and their geometric figures. The specific weight was taken equal to one unit. Abundance and biomass were calculated as a weighted arithmetic mean (Sadchikov, 2003). Taxon classification and algae group synonymy were taken from the algological site AlgaeBase (Guiry and Guiry ©1996–2020). Species diversity was calculated using Shannon’s index (Shanon & Weaver, 1963). The evenness or equitability index was calculated using Pielou’s formula (Pielou, 1967).

Macrophytes data

Water plants were studied using their ecological profiles (Yunnatov, 1964; Katanskaya, 1981), which reflected the distribution of aquatic phytocenoses at specific depths. Ten meter-wide profiles were observed from the water edge to the maximum depth at which the plant grew. Our observations included registering the species diversity, selecting the phytomass of plants, and recording the depth of the water and the nature of the soil. Plants were collected from the reservoir using a cat anchor with a metal mesh, which could also collect small plants. The cat anchor was cast along the depth change gradient five to 15 times, depending on the density of the communities. We studied eight profiles around the lake, covering the entire coastal area. Plant phytomass was selected using a device for the quantitative accounting of gammarids (KUG) with a capture area of 0.25 m² (Bazarova & Itigilova, 2006). The phytomass data are given in their absolute dry value. We listed the dominant species sequentially to create a graphical description of the composition and structure of vegetation in the ecological series with increasing depths. In the ecological row of macrophytes unidirectional changes in communities are indicated by single-pointed arrows. Double-pointed arrows indicate moving species; plus signs indicate species forming communities at the same depth.

Data analysis

We used Microsoft Excel and XLSTAT (Addinsoft, USA) to conduct the statistical and mathematical analyses of the findings. Redundancy analysis was performed to illustrate the correlation between the composition of the plankton and abiotic factors (Table 2). The absolute value of the load above 0.90 was considered to be significant.

The data were normalized by dividing the initial data by the standard deviation of the corresponding variables (Shipunov et al., 2014).

Physical and chemical parameters of the lake ecosystem

The physical and chemical parameters of environmental waters depend on the dissolution and chemical weathering of rocks and biogeochemical processes in the soils of the catchment area and bottom sediments of water bodies. We show the specific physical and chemical parameters of the lowest water level (Fig. 2) in Table 3.

The temperature exchange between the water, atmosphere, and bottom sediments resulted in stratified thermal conditions in 2017 and 2018 with a gradient slightly above 3 °C between the surface and bottom layers (Table 3). The lake water was slightly alkaline. The oxidation–reduction potential (ORP) of the ecosystem in Lake Arakhley ranged from 200 to 218 mV, creating oxidative conditions and a number of elements in their highest valence. The ORP values of the surface and bottom horizons of the water column differed slightly due to more favorable oxygen conditions in the surface water layer. The oxygen concentration in the surface horizon was higher (11.4 mg O₂ L⁻¹) compared to the bottom layers (8.8 mg O₂ L⁻¹). There was a slight difference between the parameters of the surface and bottom water layers in terms of TDS and EC. Lake Arakhley is a low-mineralized freshwater lake with regard to total dissolved solids. We determined the main chemical composition and concentration values of specific elements (Table 3) and found that the water was of the hydrocarbonate class with a calcium-sodium group. The contrast analysis of macro- and microelement compositions indicated that the values did not exceed MPC. However, manganese concentration was 86 times higher than the MPC in the bottom water layers (Table 3).

Biogenic elements in the lake during the most productive summer period are shown in Table 4.

The nitrate form of nitrogen was dominant during the summer period. The nitrites and ammonium ions were minimal. The concentration of phosphorus was greater in the bottom layers compared to the surface layers. The organic matter was of autochthonous origin in the PO/COD ratio.

The analysis of year-to-year variations of biogenic elements showed that the ammonium and nitrite-nitrogen concentrations declined from 2011 to the present day, while the concentration of nitrates increased (Fig. 3).

According to the results from 2011–2018, the PO/COD ratio was below 50%, which indicates the autochthonous origin of the organic matter. The concentration of organic matter resistant to oxidation (COD) increased since 2013, but has not reached the level of 2011. The content of easily-oxidized organic substances (PO) is consistent according to the data of 2011–2018 (Fig. 4).

The analysis of year-to-year variations of the concentration of phosphates and total phosphorus showed that their concentrations decreased in 2013–2018 compared to 2011 (Fig. 4).

Phytoplankton composition

A total of 39 taxa ranking below the genus level were detected in the lake’s phytoplankton sampled from the central zone between 2017–2018 (Table 5).

There were 97 algae taxa recorded from the lake’s center and coastal areas during the spring-to-summer period of 2017 (Tashlykova, 2019). The most diverse groups were the diatoms (Bacillariophyta), green algae (Chlorophyta), and golden algae (Chrysophyta) comprising 79.9% of the total identified taxa. Among the most frequently identified species were the following: Lindavia comta (Kützing) Nakov, Gullory, Julius, Theriot & Alverson, Fragilaria crotonensis Kitton, F. radians (Kützing) D.M.Williams & Round, Ulnaria ulna (Nitzsch) Compère in Jahn et al., Nitzschia graciliformis Lange-Bertalot & Simonsen, Chrysococcus rufescens Klebs, Dinobryon cylindricum O.E. Imhof, D. divergens O.E. Imhof, D. sertularia O.E.Imhof, Kephyrion spirale (Lackey) Conrad, and Oocystis marssonii Lemmermann.

The value of the weighted average abundance and biomass is shown in Fig. 5.

Algae’s quantitative development in the spring was insignificant when compared with the predominance of small-sized Chrysophyta. Algocenoses composition was comprised of Chrysophyta (10–75% of total taxa and 30–92% of the overall biomass) and Bacillariophyta (20–85% of total taxa and 10–60% of the overall biomass). The total number of algae and overall biomass increased in the summer by an order of magnitude due to a measurable growth of large diatoms. Bacillariophyta prevailed in the phytoplankton with 60–80% of total taxa and 50–95% of the overall biomass. The winter season was similarly marked by the predominance of Bacillariophyta in the algocenosis. We assessed the biodiversity in phytoplanktonocenoses using the Shannon and Pielu indices. The phytoplankton of the lake was characterized by high values of these indices, which demonstrates the complexity and high diversity of the community. The Shannon index varied from 2.97 to 3.11 in the spring and the Pielou index ranged from 0.52−0.76. In the summer, the value of the Shannon index was 1.27−1.38 and the Pielou index varied from 0.15 to 0.28. These values correspond to algae’s seasonal distribution. The maximum values of the Shannon index are recorded in the spring and autumn, and the minimum values are recorded in the winter and summer.

From 1966 to 1969, the lake’s algocenosis featured abundant Cyclotella comta Kützing, (currently Lindavia comta) (Guiry & Guiry, 2020) (Yunnatov, 1964; Morozova & Shishkin, 1973). The lake was dominated by Asterionella formosa Hassall from 1970 to 1971 (Morozova, 1981; Morozova & Shishkin, 1973), A. formosa (Ogly, 1993; Ogly, 1995) from 1990 to 1995, Puncticulata comta (Kützing) H. Hakansson (currently L. comta) from 2008 to 2009 (Tashlykova, 2018), and L. comta from 2017 to 2018 (Table 6). The aforementioned distribution of the dominant species corresponds to the alternate phases of the hydrological cycle. L. comta was dominant during the dry years, while A. formosa was prevalent in high-water years.

There is inconsistent data on the quantitative development of algae in different periods of the hydrological cycle. The average annual biomass is shown in Table 6. According to these data, the highest biomass values were recorded for 1966, 1994–1995, 2008–2009, and 2017–2018.

Macrophyte communities

There are two species of Charophyta, one species of Bryophytes, and 58 species of vascular plants recorded in Lake Arakhley. The maximum growth depth of lacustrine vegetation decreased from 11.0 m to 4.5 m from 1967 to 2018 and the wide strip of Nitella opaca (Bruz.) Ag and Fontinalis hypnoides Hartm disappeared. From 1967 to 1974, these species occupied isobaths 7.0–11.0 m. The communities of N. opaca were still observable at four to six-meter depths along the western and eastern shores of the lake from 1998 to 2000. Moss F. hypnoides was found at a depth of 4 m on the lake’s northern coast (Bazarova & Itigilova, 2006). N. opaca and F. hypnoides populations have not been registered since 2006.

The analysis of the long-term macrophyte vegetation dynamics showed that communities of nine species were dominant in 1967 (Fig. 6) and occupied approximately 44% of the littoral area. These communities were characterized by low-density thickets. In terms of the overgrowth area and phytomass value, the dominant species were Charophyta, including the deep-water species of N. opaca, and the shallow-water species of Chara arcuatofolia (Fig. 6). Decreased Ch. arcuatofolia in 1974 led to an increase in N. opaca thickets density, and the start of the active development of vascular plants. In 1998, a sharp reduction in N. opaca thickets was recorded and an increase in the phytomass of Lemna trisulca L. and Ceratophyllum demersum L. was noted. Five species of macrophytes dominated the vegetation from 2000–2008. Species diversity was preserved from 2017–2018 with C. demersum as the dominant vegetation. Plant communities grew from the water’s edge and were represented by Potamogeton perfoliatus L., Potamogeton pectinatus (L.), and Myriophyllum sibiricum Kom. Chara arcuatofolia Vilh populations were found at depths of of 1.5–2.0 m and C. demersum grew at greater depths. L. trisulca populations were found in depressions on the lake bottom at depths of 3.0 m, whereas Potamogeton praelongus Wulf was observed at the maximum depths of plant growth (4.5 m). The abundance of M. sibiricum communities indicated an increased eutrophicity of the littoral zone. During this period, splash water bodies were formed on the coastal areas of the lake with Ch. arcuatofolia (Kuklin & Bazarova, 2019). A slight rise in the water level in 2018 did not cause significant changes in the vegetation. However, the flooding of the coastal strip initiated the development of helophyte communities represented by the thinned strip of Scrispus sp.

Maximum plant germination occurred at a depth of approximately 4.5 m, which corresponded to the sixth belt of growth in 1998–2000. In the high-water period of 1967–1974, the ecological row of macrophytes in Lake Arakhley was characterized by the following sequence: Persicaria amphibia (L) Gray (depths ≈ 0.2−0.8 m) → P. perfoliatuis (≈ 1.0−1.5 m) →Ch. arcuatofolia (≈ 2.0 m) →L. trisulca ↔C. demersum ↔P. praelongus (≈ 3.0−7.0) →N. opaca ↔F. hypnoides. (≈ 7.0–11.0). In the period of 1998–2000, this row decreased but maintained its general structure: P. amphybia (≈ 0.5 m) →P. perfoliatuis (≈ 1.0 m) →Ch. arcuatofolia (≈ 2.0 m) →L. trisulca (≈ 3.0 m) ↔C. demersum (≈ 4.0 m) ↔P. praelongus (≈ 5.0 m) →N. opaca (≈ 6.0 m). Observations made in 2017–2018 revealed a decrease in the depth of plant growth and a violation of the clearly-expressed belt structure of vegetation. The row was featured the following species: P. perfoliatuis + P. pectinatus + M. sibiricum (≈ 0.1−0.8 m) → Ch. arcuatofolia (≈ 1.8 m) → C. demersum + P. praelongus (≈ 2.5–4.5 m). During the low-water period of 2017-2018, there was no clear correlation to the depths and the ecological series was as follows: P. perfoliatuis + P. pectinatus + M. sibiricum (0.1−0.8 m), Ch. arcuatofolia (1.8 m) → C. demersum + P. praelongus (2.5−4.5 m). Consequently, the lake featured a complex mosaic vegetation structure that varied along a depth gradient. Helophytes communities only grow along the southwestern coast, whereas neystophytes are represented by a narrow strip of P. amphibia along the southern and western coast with a well-developed hydatophyte community.

Phytoplankton composition in correlation with abiotic environmental factors

We sought to identify the key factors that determined the change in the structural parameters of phytoplankton in the central zone of Lake Arakhley from 2018–2019 (Tsybekmitova et al., 2020). We performed redundancy analysis and the first two components were selected, explaining 94.92% of the total variance (Fig. 7).

The number of Chlorophyta and the biomass of Dinophyta showed a clear negative correlation. The number and biomass of Euglenophyta, the number of Dinophyta, the biomass of Cyanobacteria and Bacillariophyta, and the number of taxa of Cyanobacteria, Bacillariophyta, Chrysophyta, and Chlorophyta were positively correlated with the first major factor (RDA axis 1). These results explained a 74.12% variability of the community. The second major factor (RDA axis 2) explained a 20.80% variability of the pelagial communities. The number of microalgae and groups of Chlorophyta, Charophyta, Cyanobacteria, and Bacillariophyta demonstrated positive correlation with RDA axis 2. Abiotic factors had the most meaningful effect on biocenosis and the physical and chemical parameters of water (TDS, pH, EC, ORP, Turb and Sal) positively correlated with RDA axis 1. The biogenic elements (nitrites, ammonium, phosphates) negatively correlated with RDA axis 1. Depth and transparency were positively correlated with RDA axis 2.