Saline lakes of Transbaikalia (Russia): Limnology and diversity of plankton communities

doi:10.21203/rs.3.rs-4096940/v1

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Saline lakes of Transbaikalia (Russia): Limnology and diversity of plankton communities

https://doi.org/10.21203/rs.3.rs-4096940/v1

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The paper summarises the results of a three-year research study (Russian Science Foundation grant: 22-17-00035) aimed at investigating the variability of chemical composition and the species diversity and functional structure of planktonic communities in saline lakes of Transbaikalia (Russia). According to the ionic content, the lakes were classified either as soda (13 lakes), chloride (3 ones), and sulphate (2 ones) types. Water salinity ranges widely, from 0.5 to 334.5 g/L in soda lakes, from 8.2 to 257.8 g/L in chloride ones, and from 21.3 to 146.8 g/L in sulphate ones. In all lakes the cation Na⁺ dominated, with its concentration increasing as the salinity of the water rises. An increase in salinity, accompanied by a sequential change in the chemical types and subtypes of lakes, led to an excess of bioavailable forms of nitrogen and phosphorus. Diversity and density of phytoplankton and zooplankton depent both to an increase in the total salt content and to the anionic composition of water. Salinity constrains species composition and functional diversity and leads to changes in trophic structure and density of some aquatic organisms. We determined two assemblages of aquatic organisms: Anabaenopsis knipowitschii and Brachionus angularis prefering sulphate dominated habitats and Limnospira fusiformis, Ascomorpha ecaudis, and Hexarthra mira commonly associating with carbonate dominated habitats.

Saline lakes

Water chemistry

Aquatic organisms

Species diversity

Functional structure

A series of endorheic saline lakes located in a compact area and characterized by similar landscape and hydrographic conditions is interest in many aspects. These lakes have wide variations in morphometric parameters and chemical composition of waters, varying depending on changes of climatic or hydrogeological conditions (Zheng and Liu 2009; Sklyarov et al. 2011; Schagerl 2016; Boros et al. 2017a, b; Lin et al. 2017; Guerreiro et al. 2019; Borzenko 2021), which allows us to consider saline lake systems as natural model objects for studying various aspects of its habitat and aquatic biota (Evans and Prepas 1996; Zhao et al. 2005; Balushkina et al. 2007, 2009; Jiménez-Melero et al. 2013; Sui et al. 2016; Li et al. 2021; Gutierrez et al. 2018; Afonina and Tashlykova 2020, 2023; de Necker et al. 2021; Zadereev et al. 2022). According to Kurnakov-Valiashko hydrochemical classification of continental waters (Valiashko 1962) based on combination of main cations and anions three main types of natural mineral waters are singled out: 1) carbonate (soda) type, with main components Na⁺ (К⁺), С1^–, SO₄^2–, НСО₃^–, СО₃^2– ions; 2) sulphate type, the main components are Na⁺ (К⁺), Mg²⁺, Сl^–, SO₄^2– ions; 3) chloride type with main components Na⁺ (К⁺), Mg²⁺, Са²⁺, C1– ions. The НСО₃^– and СО₃^2– anions content in water of sulphate and chloride types are in the limits of solubility of their Са²⁺ and Mg²⁺ salts.

Saline lakes are found on all parts of the world with an arid or semiarid climate. Sulphate-rich saline waters are considered to have rare water chemistry globally; such lakes are distributed in the Great Plains (Canada, USA), the Qinghai-Tibet Plateau (China), La Pampa province (Argentina), the Crimea (Russia). In contrast, chloride lakes are the most common form of salt in saline lakes globally; they are most frequently encountered in Australia, the West and East Siberia (Russia), Transylvanian basin (Romania), the Tibetan Plateau (China), Northern Kazakhstan. Soda lakes occur in Africa (the East Rift Valley), Europe (the Carpathian Basin), Asia (Songnen Plain, Altai, Transbaikalia), America (British Columbia, California, the Pantanal). Based on their origin, sulphate and chloride lakes mау bе both halassogenic and athalassic. Soda lakes are typical alkaline environments of athalassic origin. They form under the same conditions as athalassic chloride lakes (Hammer 1986).

Numerous saline lakes with a significant variation in their area (from 0.1 to 500 km²) are widespread in the semiarid zone of the Trans-Baikal Territory (Russia), where evaporation rates exceed precipitation rates and where drainage basins frequently are closed (Sklyarov et al. 2011; Borzenko 2020). All three types of lake waters (soda, chloride and sulphate) occur in this region. The overwhelming majority of lakes are soda-type (87%). There are very few sulphate and chloride waters (3% and 10% respectively). According to the prevailing anion soda lakes are divided into 3 subtypes. The first subtype includes lakes with the predominance of HCO₃⁻+CO₃²⁻, the second subtype has a predominance of SO₄²⁻ and the third subtype has a predominance of Cl⁻. Lakes of the subtypes I and III are most widespread, 45% and 50%, respectively (Borzenko and Shvartsev 2019).

Salinity and aquatic biodiversity are inversely related in lake waters (Williams 1998). However, the role of salt ion composition relative to salt concentration in determining phytoplankton and zooplankton communities is pooly studied (Bos et al., 1996; Derry et al. 2003; Larson and Belovsky 2013). The differences in ionic composition and salinity between saline lakes are in turn reflected by differences in the composition and nature of the biota. Diatom algae Nitzschia frustulum prefers more SO₄^2– than Cl^– (Stenger-Kovács et al. 2014; Lengyel et al. 2015). Following Blinn (1993), certain diatom taxa (Synedra radians (currently Fragilaria radians (Kützing) D.M. Williams & Round 1988), Mastogloia spp.) associate with Cl^–-dominated habitats, while other taxa (Synedra pulchella (currently Ctenophora pulchella (Kützing) D.M. Williams & Round 1986), S. fasciculata, Fragilaria pinnata var. subsolitaris, Navicula subinflatoides) commonly associate with SO₄^2–-dominated habitats. Still other taxa (Anomoeoneis costata, A. sphaerophora, Campylodiscus clypeus) tend to be common in HCO₃^–-dominated habitats. Cocconeis placentula var. lineata showes significant correlations with K⁺, Cl^–, and HCO₃^– contents, while Navicula cincta with Cl^– and Ca²⁺; Amphora coffeiformis and Synedra fasciculata have high tolerance to MgSO₄. Green algae Dunaliella salina and D. parva are the most frequently reported in Cl-rich lakes (Oren 2014). Following Klymiuk and Barinova (2016) cell size of Entomoneis paludosa var. subsalina and Navicula cryptocephala var. veneta are impacted mainly by chlorides; Halamphora holsatica cell volumes are positively correlated with the chloride content. Derry et al. (2003) reported, that the harpactacoid copepod Cletocamptus sp. prevailes in lakes with Cl-dominated; the calanoid copepods Leptodiaptomus sicilis (Forbes S.A., 1882) and Diaptomus (Hesperodiaptomus) nevadensis Light, 1938 are dominant in the SO₄/CO₃-dominated waters with elevated potassium. Natronophilic Arctodiaptomus spinosus (Daday, 1891) prefers high concentrations of NaHCO₃ and Na₂CO₃ (Megyeri 1999) and stands out with the ability to survive under extremely high concentrations of carbonates (Tóth et al. 2014). Anostraca Artemia is in positive correlation with Na⁺ and Cl^– ions (Zhuga et al. 2021). Following Bos et al. (1996) among carbonate/bicarbonate and sulphate-dominated waters Artemia franciscana Kellog, 1906 prefers waters with high in Mg²⁺, Ca²⁺, and sulphate contents. Cladocera Moina hutchinsoni Brehm, 1937 inhabits in waters with low in Mg²⁺ and Ca²⁺; Daphnia pulex Leydig, 1860 is more abundant in waters with lower Mg²⁺, while Ceriodaphnia quadrangula (O.F. Müller, 1785) in waters of greater Mg²⁺ and Ca²⁺ concentrations. Rotifer Brachionus asplanchnoides Charin, 1947 dominates in sulphate lakes (Ermolaeva and Fetter 2021).

The purposes of this study were: i) to determine the main physical and chemical parameters and to identify the patterns of hydrochemical composition fluctuations in various lake types; ii) to assess and compare the variability of structural and functional indicators of phytoplankton and zooplankton communities in saline lakes with variable anion composition; iii) to identify those physicochemical factors that influence the community structure of planktonic assemblages in lakes with variable ionic composition; iv) to identify the key determinant ionic composition for the relative of aquatic organism diversity. This study complements existing knowledge and provides new information about the diversity and functioning of planktonic communities in waters with variable ionic composition.

Study area

We investigated 18 lakes belonging to the Onon-Borzinsky system of shallow lakes, which are located in an endorheic zone of the northeastern part of the Central Asian physiographic area (Southeastern Transbaikalia (Russia)) (Fig. 1).

The vast territory is characterized by aridity and an extremely continental climate (Sklyzrov et al 2011). Saline lakes are considerably distinguished by their area and depth. The relatively small depth, usually not exceeding the first meters from the water surface, is common to all of them. The main characteristics of the surveyed lakes are presented in previous papers (Borzenko 2018; Afonina and Tashlykova 2019, 2020, 2023).

Due to the ground and fissure underground waters and streams participated in the hydrological regime lakes Bain-Bulak, Bain-Tsagan, Balyktui, Ukshinda, and Nozhii are permanent. These lake basins are inclined towards tectonic faults, fixing the zone of articulation of depressions with the surrounding young uplifts. Apart from underground sources and atmospheric precipitation, Nozhii Lake is fed by fresh waters from the Suduntuy River. Springs are also found on the shores of the lakes Barun-Shivertuy and Shikhalin-Nuur, with their waters discharging due to subaqueous discharge. The Uksinda Lake depression is carved into the bedrock and are located in the zone of transition from an accumulative plain to a denudation surface; this lake is primarily fed by groundwater. Other surveyed lakes are the intermittenly drying up; they are primarily fed by atmospheric precipitation and surface runoff during the summer rains. Presumably, at this stage of their existence, deep underground waters do not participate in their water balance (Borzenko, 2020). The beginning of the refilling in ones lakes and the water level raising in others were recorded in recent years (2020–2023). Despite the divergence in the morphometric parameters of the lakes, evaporation is the main expenditure in their water balance. Morphological signs of higher water levels are observed in all lake basins in the form of distinct littorals, as well as shore accumulative and abrasive microforms of relief (Borzenko 2020).

The surveyed lakes were fishless. The exception was Lake Barun-Torey, in which fish (Cyprinidae) has been coming from the Uldz-Gol River since 2020. Fish occurs in small numbers, and as potential zooplankton predators, they do not play a significant role in this environment.

Water sampling and analysis

Water samples were collected in spring (March–April), summer (July), autumn (September–October), and winter (December) in 2021–2023. The seasonal drying and freezing of some lakes prevented sampling in its. At each sampling site, water temperature (T), pH, dissolved oxygen (O₂), reduction-oxidation reaction (Eh), and total dissolved solids (TDS) were measured with a multi-parameter probes AMTASTAMT 03 (USA) and pH Cond 340i, WTW (Germany). Water samples were collected and refrigerated until further analysis. In the laboratory, each water sample was carried out by standard methods (Manual on Chemical Analysis... 1977; Novikov et al. 1990). We determined the concentrations of Ca²⁺ and Mg²⁺ with the method of atomic absorption in a nitrous acetylene flame using a SOLAAR 6M spectrophotometer (England-Germany) while Na⁺ and K⁺ contents with the flame-emission method. Cl⁻ content were determined potentiometrically with ion selective electrodes. We used titration to determine the CO₃²⁻ and HCO₃^– contents. Turbidity and SO₄²⁻ were analysed by the turbidimetric method. We measured phosphorus content using the photometric method and nitrogen content with the potentiometric and colorimetric methods. The photometric method was used to determine the chemical oxygen demand. Permanganate oxidizability was determined by titration.

We determined the water transparency and the ice thickness with a Secchi disk.

Phytoplankton and zooplankton surveys

A sampling points were placed in the deepest zone and in the two–four coastal stations of lakes. All samples were fixed in situ with formaldehyde (4%). We studied the seasonal succession in soda lakes (Barun-Torey, Bain-Tsagan, Bain-Bulak, Nozhii, Ukshinda). We used a Patalas bathometer to collect phytoplankton samples. In lakes Bain-Tsagan, Nozhii, Bain-Bulak, and Ukshinda, samples were collected from two and/or three depths (the surface layer, the Secchi depth, and the benthic layer). We collected samples from the subsurface in shallower waters. Phytoplankton was concentrated by sedimentation method. We used the Hansen method (Sadchikov 2003) to count cell calculation. Algae biomass was determined with the geometric figures method (Sadchikov 2003). The mean cell size was based on measurements of at least 30 individuals. The current names of species were checked using the website (Guiry and Guiry 2024).

Zooplankton samples were taken at depths greater than 1.0 m in total (bottom–0 m) with a Judy net (0.064 mm mesh size). In shallower waters (at a depth of less than 1 m), we concentrated the water collected for analysis by filtering it through a net (0.094 mm mesh size). In the laboratory, zooplankton samples were counted in Bogorov and Kolkwitz chambers (Kiselev 1969) and identified as the lowest possible taxonomic units. Abundance and biomass were calculated for each species in each sample. Rotifera biomass was expressed as dry weight and estimate following Ruttner-Kolisko (1977) and Ejsmont-Karabin (1998), and both Copepoda and Cladocera biomass were estimated following Balushkina and Vinberg (1979), while biomass of Anostraca was measured directly. The species of zooplankton species followed modern nomenclature (WoRMS 2024). The taxonomic position of Anostraca in the studied lakes has not been clarified. For this reason, the denomination of Anostraca was used generally.

Data and statistical analyses

The Shannon (H) and the Pielou (e) indices were calculated as a measure of α-diversity (Maguran 1990). Whittaker's measure (βw) or global replacement of taxa between systems was used to express β-diversity within each lake group and beetwen ones (Whittaker 1972). Species comprising more than 20% of the total phytoplankton and zooplankton abundance and biomass were considered to be dominant (Fedorov and Gilmanov 1980; Korneva 2015).

Phytoplankton species were grouped into Functional Groups (FG_ph) (Reynolds et al. 2002; Padisák et al. 2009) and morphologically based functional classification (MBFC_ph) (Crossetti and de M. Bicudo 2008; Kruk et al. 2010; Kruk and Segura 2012). Zooplankton Functional Groups (FG_zoo) were based on a combination of locomotion type, feeding type and food sources (Chuikov 2000; Barnett et al. 2007; Benedetti et al. 2016; Gavrilko et al. 2020; Branco et al. 2023). The numbers FG_ph and FG_zoo were considered as a measure of functional diversity of phytoplankton and zooplankton (FD_ph and FD_zoo).

Zooplankton was divided into three trophic groups. The first group are nonpredators (herbivores and detrivores), including all cladoceran species, all taxa of rotifers (except Ascomorpha), all age stages of calanoid copepods, and nauplii of all species of Cyclopoida. The second group is represented by omnivores (or polyphages, the main food are small rotifers and cladocerans, ciliates, detritus, bacterio- and phytoplankton), including copepodites I–III of all Cyclopoida. The third group includes predators (carnivores, food sources are large unshelled rotifers, cladocerans, juvenile of copepods, fish eggs and larvae), adult specimens of Thermocyclops dybowskii and copepodites of stages IV–V of cyclopoid copepods. The trophic relations between the zooplankton groups were analyzed using published data (Sushchenya 1975; Kazantseva 2003; Monakov 2003).

Daily production (P) of zooplankton was calculated on the basis of biomass (B_zoo) of trophic groups and values of specific rate of production (P/B coefficient, day^− 1 (Ivanova 1985; Lokot' et al. 1991)): P = P/B × B_zoo. Daily ration (C) was calculated using the equation: C = P / k₁, where k₁ is consumed food for growth, were taken as 0.22 for nonpredatory animals and 0.16 for predatory and omnivorous copepods (Bul'on et al. 1999; Hart et al. 2000; Lazareva and Kopylov 2011). Considering the efficiency of exploitation of assimilated food for growth (k₂) and the production, the expenditures for metabolism (R) were determined as R = P × (1–k₂) / k₂, where k₂ is 0.4 for rotifers, 0.35 for cladocerans, 0.2 for copepods, and 0.6 for anostracans (Khmeleva 1968; Salazkin et al 1984; Bul'on et al. 1999; Lazareva 2010). In calculating the functional characteristics depending on temperature, the temperature correction was considered h(T) using Q₁₀ (2.25) is Van’t Hoff''s coefficient (Ivleva 1981; Vinberg 1983). Considering the values of the coefficients mentioned above, the following parameters were evaluated: daily production, expenditures for respiration, and daily ration of leading trophic groups of plankton in each lake (each sampling sites) according to summer sampling. The daily P, R, C for the entire zooplankton community was calculated as a sum of the daily P, R, C of all zooplankton groups. All calculations were made in cal units. Calorie content is accepted as 0.56 kcal/gO₂ of wet weight for invertebrates and as 0.52 kcal/gO₂ for Anostraca.

According to the method (Kazantseva 2003) we calculated the coefficient of energy transformation of phytoplankton by nonpredatory zooplankton (P_zoo/P_ph). Primary production values were taken from published data (Bazarova et al. 2023, 2024).

The sampling sites distribution map of the study area was completed in Google Earth Pro 7.3.6.9750. To characterize the abiotic and biotic variables, we calculated the mean values and standard deviation for each variable (mean ± SD). To determine the extent of variability in relation to the mean of the population we used coefficient of variation (CV, %). Environmental and biological variables were normalized prior to calculations and to achieve normal distribution. The data were analyzed using a post hoc comparison using t-test to examine the difference in biological parameters among the lakes with various salinity ranges. Statistical differences were considered to be significant if p < 0.05. All statistics mentioned above were performed with the statistical package XLSTAT, Statictica v. 10. Direct ordination analyses were used to assess significant relationships (p < 0.05, r ≥ 0.70) between biological (species number (n), total abundance (N) and biomass (B) of phytoplankton (ph) and the main taxonomic groups: Bacillariophyta (Bac), Chlorophyta (Chl), Cyanobacteria (Cya), Cryptophyta (Cry), Chrysophyta (Chr), Charophyta (Cha), Euglenophyta (Eug), Dinophyta (Din) and species number (n), secondary production (P), total abundance (N) and biomass (B) of zooplankton (zoo) and the main taxonomic groups: Rotifera (Rot), Cladocera (Clad), Copepoda (Cop), and Anostraca (Ano)) and environmental data (water temperature (T), pH, reduction-oxidation reaction (Eh), total dissolved solids (TDS), permanganate oxidizability (TOC), chemical oxygen demand (COD), turbidity (Turb), dissolved oxygen (O₂), anions (bicarbonate + carbonate (HCO₃⁻+CO₃²⁻), sulfate (SO₄²⁻), chloride (Cl⁻)), ratios between anions ((HCO₃⁻+CO₃²⁻)/Cl⁻, (HCO₃⁻+CO₃²⁻)/SO₄²⁻, Cl⁻/SO₄²⁻), cations (sodium (Na⁺), potassium (K⁺), calcium (Ca²⁺), magnesium (Mg²⁺), ratios between canions (Na⁺/K⁺, Mg²⁺/Ca²⁺), nutrients (nitrate (NO₃⁻), total nitrogen (ƩN), phosphate (PO₄^3–), total phosphorus (ƩP), and ratios NO₃⁻/ PO₄^3–, ƩN/ ƩP).

Physical and chemical features

Barun-Torey Lake being the largest among of other lakes (567 km² and at a water level of 599.0 m BS) had completely dried up by summer 2009. The relatively stable refilling began in September 2020 (Obyazov et al. 2021) and has been continued to present time. In summer 2020 lake area was about 180 km²(Google Earth Pro 7.3.6.9750). Lakes Bain-Tsagan (4–5.0 m), Nozhii (1.9–2.3 m), Ukshinda (1.3–1.6 m), and Bain-Bulak (1.1–1.5 m) were relatively deep. The depths in other lakes varied from 0.02 to 1.0 m. Water transparency was low, with a Secchi reading of less than 0.02–0.3 m. In lakes Nozhii and Bain-Tsagan transparensy varied within 0.7–0.9 and 0.7–1.5 m respectively. In spring water temperature ranged within –2.1–12.6 °C, 18.4–33.4 °C in summer, 2.8–18.7 °C in autumn, and 0.5–1.5 °C in winter (Table 1). In lakes Nozhii, Bain-Tsagan, Bain-Bulak, and Ukshinda ice thickness were 1.1–1.3 m. The rest of the surveyed lakes frozen to the bottom.

All studied lakes were grouped according to TDS following the classification of Venice System (1959): oligohaline (0.5–5.0 g/L), mesohaline (5.0–18.0 g/L), polyhaline (18.0–30.0 g/L), euhaline (30.0–40.0 g/L), and hyperhaline (> 40.0 g/L). According to chemical composition the studied waters fall into some categories (Table 1).

Oligohaline Barun-Torey Lake belonged to the soda-type – Na-HCO₃ with pH < 9. The salinity and pH values were minimal. The salinization of lake waters was accompanied by an increase in pH and the accumulation of HCO₃^–+CO₃^2–, whose relative content averaged 67 eq.%, at relatively low values of SO₄^2– and Cl^– (10 and 19 eq.%, respectively). Na⁺ dominated (79 eq.%), followed by Ca²⁺ and Mg²⁺ at 12 and 16 eq.%, respectively (Table 1).

There were 6 oligo-, meso- and hyperhaline lakes (Bain-Bulak, and Nozhii, Bain-Tsagan, Balyktuy, Nizhnii Mukey and Kudzhertay) in the soda-type I subtype – Na-HCO₃-CO₃, pH > 9. Nozhii Lake had low TDS (average 5.1 g/L) and an alkaline pH (9.2). Its water column was stratified based on salinity, Eh and pH. Hydrogen sulfide presented in the bottom layer, resulting in a sharp decrease in Eh value towards the bottom. HCO₃^–+CO₃^2– content (2.1 g/L) was higher, but their share in the sum of anions was lower (53 eq.%). Second in importance was SO₄^2–, which accounted for an average of 30 eq.%. The relative content of Na⁺ averaged 60 eq.%, and in the freshened lake waters, the share of Mg²⁺ could reached 47 eq.%. According to average estimates, other lakes differed in higher water salinity and pH (correspondingly, an average of 8.3 and 9.4 g/L, not accounting for the data of the hyperhaline lakes Kudzhertay and Nizhnii Mukey). Anions HCO₃^–+CO₃^2– dominated (on average 58 eq. %). The second most significant was Cl^–, averaged 38 eq. %. The relative content of Na⁺ in this group of lakes sharply increased to 92 eq. % (Table 1).

Oligo- and mesohaline lakes Kharaganash and Sheluta were classified as soda-type II subtype (Na-SO₄, pH > 9). The dominance of SO₄^2– (46 eq. %) at a relatively high pH (average 9.5) and content of HCO₃^–+CO₃^2– (25 eq. %) and Cl^– (29 eq. %), and consequently high TDS (9.5 g/L) was noted. With an increase in TDS, a large amount of HCO₃^–+CO₃^2– accumulated in these lakes and, naturally, the pH increased. On the contrary, freshening their water was accompanied by a decrease in pH (down to 8.8) and the accumulation of SO₄^2–(Table 1).

Soda-type III subtype (Na-Cl, pH > 9) was observed for the lakes Ukshinda, Shvartsivskoe, Borzinskoe and Khadatuy. These waters fell into 4 salinity, from meso- to hyperhaline. Salinity and alkaline values averaged 25.9 g/L and 9.5, respectively. The dominant anion was Cl^–, accounting for 51 eq. %, while the share of HCO₃^–+CO₃^2– was slightly lower (on average 43 eq. %). Concurrently, the proportion of Na⁺ increased with Cl^– (95 eq. %). In Shvartsivskoe Lake, with the prevalence of Cl^– in the anionic composition (56 eq. %), the relative content of HCO₃^–+CO₃^2–was only 13 eq. %. Its waters had more salinity (26.7 g/L) due to the relatively high concentration of Cl^– and SO₄^2– (32 eq. %), making them less alkaline (pH = 9.2). A slight decrease in the cationic composition of Na⁺ (81 eq. %) was accompanied by an increase in the share of Mg²⁺ (up to 18 eq. %). Borzinskoe Lake was the most saline (138.5–334.5 g/L); it standed out for its relatively high concentration of Cl^– (78 eq. %) and lower concentration of HCO₃^–+CO₃^2– (10 eq. %). With increasing water salinity, there was a significant accumulation of SO₄^2–reached to 21 eq. %. The dominant cation was Na⁺ (94 eq. %) (Table 1).

Lakes Dabasa-Nor, Khilganta, Gorbunka were classified as chloride-type (Na-Сl, pH < 9) and mesohaline to polyhaline. They had relatively high salinity (69.2 g/L) and low pH of 8.5. The relative content of Cl^– was on average 82 eq. %, and Na⁺ was 84 eq. %. The proportion of SO₄^2- and HCO₃^–+CO₃^2–was 19 and 14 eq. % respectively (Table 1).

Poly- and hyperhaline lakes Barun-Shivertuy and Shikhalin-Nuur formed sulphate-type (Na-SO₄, pH < 9 ). The average salinity was 44.7 g/L, and the pH was 8.6. The dominant cation was Na⁺ (87 eq. %), followed by Mg²⁺ (12 eq. %). SO₄^2– accounted for 51 eq. % and Cl^– for 45 eq. %, while the combined HCO₃^–+CO₃^2–was on average 3 eq. %. We observed that at a salinity of 147 g/L, the sulfate type (Lake Barun-Shivertuy) shifts to the chloride type (Cl^– 55 eq. % and SO₄^2– 44 eq. %) (Table 1).

The accumulation of total nitrogen and total phosphorus increased with salinity. There was an opposite relationship concerning the ratios ƩN/N(NO₃^–) and ƩР/Р(РО₄^3–) (Table 1).

Phytoplankton community characteristics

In total, 73 taxa of phytoplankton were found (26 taxa of Cyanobacteria, 10 taxa of Bacillariophyta, 5 taxa of Cryptophyta, 1 taxa of Dinophyta, 2 taxa of Charophyta, 25 taxa of Chlorophyta, and 4 taxa of Euglenophyta) (Table 2). The species number ranged from 9 (Barun-Torey Lake, from 0 to 10 per site at various years) to 51 (soda lakes, I subtype, 1–19 taxa) (Fig. 2). Depauperate phytoplankton community composition dominated by Cyanobacteria and Chlorophyta (65–83% of taxa) was characteristic of all lakes while Bacillariophyta dominated (44%) in Barun-Torey Lake. Only one taxa Phormidium sp. was identified in all lake types and subtypes and seven taxa (Leptolyngbya foveolarum, Spirulina major, Lindavia comta, Navicula sp., Cryptomonas sp., Chlamydomonas sp., Oocystis sp.) were almost in all.

FD_ph was determined by 19 FG_ph, varying within 5–17, and 6 MBFG_ph, varying within 5–6 (Fig. 2). Codons MP (15–37% of species composition) and S1 (12–23%) prevailed. Groups III, represented by large filaments of Cyanobacteria (30–46% of species composition), V, represented by unicellular flagellates (medium and large size) of Cryptophyta and Chlorophyta (16–33%) and VI, represented by diatoms (16–44%), predominated. The basis of species composition consisted of unicellular non-flagellated forms (30–44% of species composition) with a high proportion of filaments (30–42%) (Table 2). Filamentous forms of algae predominated in soda (II subtype) and sulphate lakes, unicellular non-flagellated forms in soda lakes (Barun-Torey Lake and I subtype).

Total phytoplankton abundance and biomass were highly variable (CV > 100%), ranging from 177.76±255.61×10³ cell/L (sulphate lakes) to 34838.22±77111.22×10³ cell/L (Barun-Torey Lake) and from 201.67±348.62 mg/m³ (sulphate lakes) to 14546.93±32023.64 mg/m³ (soda lakes, III subtype) respectively (Fig. 2). At TDS of 31.4 g/L, 194.5 g/L and 291.6 g/L, cyanobacteria and cryptophyte blooms were observed. The Cyanobacteria (8 species), Chlorophyta (6 species), Cryptophyta (3 species), and Euglenophyta (one species) were numerically abundant. Four species Leptolyngbya foveolarum, Stenomitos frigidus, Ankyra ancora and Oocystis submarina were recorded almost in all lake types and subtypes (Table 3).

The values of α- and ß-diversity varied widely (CV = 44–190%). The Shannon’s index changed from 0.76±0.62 (soda lakes, III subtype) to 1.37±0.06 (soda lakes, II subtype), the Pielou’s index from 0.14±0.05 (soda lakes, I subtype) to 0.55±0.02 (chloride lakes), and the Whittaker’s index from 0.57±0.15 (sulphate lakes) to 0.76±0.00 (soda lakes, I subtype) (Fig. 2).

Seasonal variation of species richness, abundance and biomass in the phytoplankton was characterized by the highest values in spring and summer and lowest in autumn. Cyanobacteria and green algae were the major contributor to the total density of phytoplankton in all sampling data, while cryptomonads in summer and diatoms in autumn. In spring, no phytoplankton were found in samples from the Ukshinda Lake (TDS = 48.8 g/L) (Table 4).

Zooplankton community characteristics

The species composition included 43 taxa (19 taxa of Rotifera, 13 taxa of Cladocera, and 10 taxa of Copepoda, and 1(2?) taxa of Anostraca). Not determined juvenile Cyclopoida were also encountered (Table 5). Sulphate lakes had the fewest species richness (4 species, varying within 0–3) and soda-I lakes had the greatest species number (37 taxa, 0–13) (Fig. 2). No invertebrates were found in samples from the lakes Nizhnii Mukey (TDS = 128.3 g/L), Borzinskoe (TDS = 334.5 g/L), and Barun-Shivertuy (TDS = 146.8 g/L). In sumples we found only empty body coverings (Moina, Daphnia, chydorids, Keratella), ephippiums, and restings eggs. Two species Brachionus plicatilis and Moina brachiata were recorded at all lake types and subtypes.

FD_zoo were determened by 14 FG_zoo, which changed within 3–15 (Fig. 2). Rotifers and crustaceans with swimming locomotion type and verification/filtration feeding type were the most divers and abundant. There were three trophic groups (nonpredatory – 37 taxa, omnivorous – 5 taxa, and predatory – one species) (Table 5).

Total abundance and biomass varied within wide limits (CV > 100%). The density averaged from 147.18±77.22 ×10³ ind./m³(Barun-Torey Lake) to 42526.94±93273.73 ×10³ ind./m³ (soda lakes, III subtype) and biomass from 16.07±17.28 g/m³ (chloride lakes) to 89.59±64.80 g/m³ (sulphate lakes) (Fig. 2). The dominant complex under different conditions was formed by 8 taxa (1–2 taxa per lake type) (Table 6).

Low zooplankton diversity was characteristic of lakes under study. Diversity indices varied widely (CV = 20–120%): H = 0.45±0.62 – 1.57±0.28, e = 0.29±0.39 – 0.93±0.04, βw = 0.42±0.27 – 0.69±0.07. Zooplankton of Barun-Torey Lake and chloride lakes were characterized the highest and the lowest species diversity respectively (Fig. 2).

The daily production, expenditures for metabolism, and ration averaged within 0.65±1.02 – 16.74±24.24 kcal/m³, 5.88±2.43 – 44.34±60.54 kcal/m³, and 7.62±4.61 – 76.09±110.20 kcal/m³respectively(CV > 100%). The greatest values of productivity were noted for soda lakes (III subtype) and the least for Barun-Torey Lake. Herbi- and detrivores both of large-bodied crustaceans (Mixodiaptomus incrassatus, Metadiaptomus asiaticus, Moina brachiata, Daphnia sinensis, D. magna, Anostraca) and small-sized rotifers (Brachionus plicatilis) formed up to 100% of daily production. Omnivorous and predatory cyclopoids formed 2–57% of daily production in oligo- and mesohaline soda lakes (Barun-Torey Lake and I and II subtypes) (Table 7).

In seasonal aspect, a summer maximum and a spring minimum were observed in the zooplankton population. Rotifers and copepod and anostracan nauplii were the main zooplankton component in spring while crustaceans in summer and autumn (Table 8).

Relationships of phytoplankton and zooplankton to physical and chemical parameters

The effect of some physical and chemical parameters on the diversity and structure of aquatic organisms were analyzed, and Principal component analysis (PCA) was conducted. For chloride lakes, the forward selection procedure identified TDS and turbidity as significant explanatory variables with 52.44% variation captured in PCA. No high relations (p ≤ 0.50) were noted between environmental and biological variables (Fig. 3). In sulphate lakes, TDS, turbidity, and COD were the most important predictors in phytoplankton community on the PCA first axis (33.74% variation). It was positively and strongly correlated with the Shannon’s index and density of Bacillariophyta, Cryptophyta, Dinophyta, Charophyta, Chlorophyta (Fig. 3). In soda lakes, the variance along the PCA first axis (57.71% variation) was mostly explained by the pH and Eh. Phytoplankton and zooplankton communities included the species diversity and density of cyanobacteria, diatoms, cryptophyts, dinophyts, charophyts, chlorophyts, euglenophyts, copepods, secondary production, and total biomass of phytoplankton and zooplankton (Fig. 3A).

Analyses showed that the highest positive correlation was observed between ƩN and ƩР and cryptophyte abundance and biomass in soda lakes while total nitrogen and nitrate showed a positive correlation with cyanobacteria in chloride ones. In sulphate waters all forms of nitrogen and phosphorus recorded a positive correlation with α-diversity of phytoplankton while ƩN/ƩР recorded correlations with rotifer density (Fig. 3B).

To assess significant relationships between the major ions and the ratios between them and phytoplankton and zooplankton species, expressed in terms of abundance was conducted ordination analysis. We selected 11 chemical variables (Na⁺, K⁺, Ca²⁺, Mg²⁺, SO₄^2–, Cl^–, HCO₃^–+CO₃^2–, SO₄^2–/(HCO₃^–+CO₃^2–), Cl^–/(HCO₃^–+CO₃^2–), Na⁺/K⁺, Ca²⁺/Mg²⁺) and 12 phytoplankton and 11 zooplankton species from the data set (Fig. 4).

PCA indicated that in all lake types, K⁺andNa⁺recorded high positive correlation with Anabaenopsis knipowitschii, Gloeocapsa minutula, and Colurella adriatica (0.87–0.95) and Gloeocapsa minima, Lyngbya sp., and Cephalodella sp. (0.74–0.94) respectively while Ca²⁺ and Mg²⁺ showed a positive correlation with Coleofasciculus chthonoplastes, Merismopedia minima, Brachionus plicatilis, Lecane luna (0.78–0.98) and Microcystis aeruginosa, Dolichospermum flos-aquae, Brachionus variabilis (0.72–0.99) respectively. Ratios K⁺/Na⁺and Ca²⁺Mg²⁺ showed a positive correlation (0.72–0.97 and 0.80–0.98) with Coleofasciculus chthonoplastes, Brachionus angularis, B. plicatilis, L. luna and Aphanothece salina, Brachionus quadridentatus respectively. PCA declared that the high positive correlation was observed between sulphate and ratio SO₄^2–/HCO₃^–+CO₃^2– and A. knipowitschii, B. angularis while hydrocarbonate/carbonate and ratio Cl^–/(HCO₃^–+CO₃^2–) showed a positive correlation with Limnospira fusiformis, Ascomorpha ecaudis, Hexarthra mira. Chloride recorded a positive correlation with A. salina, G. minima, Brachionus quadridentatus, Cephalodella sp., Keratella quadrata. Other species were not considered because their share in the total variance is insignificant and/or low.

Thus, we have identified two types of planktonic communities inhabiting in sulfate and carbonate lakes, respectively (Fig. 5).

The ratio of incoming and outgoing components in the studied lakes is different (Borzenko and Shartsev, 2019). In soda lakes, the ratio of incoming water to outgoing water fluctuates between 0.60–0.99, while in chloride ones 0.46–0.52. Probably this pattern is related to another factor: the studied soda lakes are often geographically located lower than the chloride lakes, so they drain deeper water horizons, and therefore, the pressure of fresh groundwater takes part in their water balance (Borzenko et al. 2020). Therefore, their hydrological regime is more stable, and their waters are less saline.

The obtained data showed that in all identified types and subtypes of lakes the cation Na⁺ sharply dominated among cations, with its concentration increasing as the salinity of the water rises (Fig. 6a).

In soda lakes, at salinity ≥ 10 g/L, Ca²⁺ and Mg²⁺ do not accumulate. However, in chloride and sulphate lakes, Mg²⁺ becames concentrated as the salinity of the water increases. These lakes have a higher presence of Ca²⁺. The Mg/Ca ratio in chloride and sulphate types is on average 2 times higher than in soda lakes. As salinity increases, the value of this coefficient increases in chloride and sulphate lakes, whereas this dependency is not observed in soda lakes (Fig. 6b). In chloride and sulphate lakes, HCO₃^–+CO₃^2– does not accumulate as salinity increases, leading to a decrease in water pH (Fig. 6c, d). In soda lakes, their concentration increases, resulting in an increase in water pH. The accumulation of SO₄^2– and Cl^– may be more intensive than that of HCO₃^–+CO₃^2–.

Within the soda type, at an average salinity of 7 g/L, SO₄^2– becomes the second most significant anion, and at 10 g/L, it becomes the primary one. Further increases in the salinity of soda lake water lead to the accumulation of Cl^–, which becomes the dominating anion at TDS = 27 g/L. In this case, HCO₃^–+CO₃^2– become the second most significant anion, causing the pH not to drop below 9.2. The first two subtypes have lower water salinity (6.4 and 6.8 g/L), but a higher average pH (9.5). Lakes Kudzhertay and Nizhnii Mukey are except, in which soda precipitation has been observed. This implies that the processes responsible for the accumulation of HCO₃^– and CO₃^2– in the waters precede the process of Cl^– accumulation, which even at maximum established salinity has a subordinate value in this subtype of lakes. Subtype III averages higher salinity (27 g/L) and a lower average pH (9.3). Totaly, an increase in the salinity of the water is accompanied by a decrease in the values of the (HCO₃^–+CO₃^2–)/Cl^– and (HCO₃^–+CO₃^2–)/SO₄^2– coefficients, clearly indicating different sources and processes responsible for the accumulation or dissipation of these elements in waters (Borzenko 2021).

The established relationship between the turbidity of lake waters and their salinity (Table 1) can be explained by the fact that in smaller saline and salt lakes, as a result of wind turbulence of bottom sediments, a finely dispersed suspension composed of pelitic fractions of authigenic and chemogenic minerals, organic pellets, etc, enters the water column, thereby increasing the turbidity value. Simultaneously, as turbidity increases, the values of TOC and COD in water also increase due to the greater amount of oxygen required for the oxidation of the suspended matter.

An increase in water salinity, accompanied by a sequential change in the chemical types and subtypes of lakes, leads to an excess of bioavailable forms of nitrogen and phosphorus, indicating an excess of energy subsidies over their utilization (the ratio ƩN/NO₃^– and ƩР/РО₄^3– decreased against the backdrop of increased total nitrogen and total phosphorus and phytoplankton biomass) (Fig. 6e).

The species richness of aquatic biota is low in all types of saline lakes (Williams 1998; Hammer 1986) and is similar, suggesting the existence of “sister genera” in phytoplankton (Sili et al. 2011) and vicarious taxa in zooplankton (Alonso 2010). During this investigation, phytoplankton and zooplankton were taxonomically simple in regard to number of species present. The sum of 73 phytoplankton (total varying 0–19 per lake) and 43 zooplankton taxa (0–18) were recorded. The FD of planktonic community consisted of 19 FG_ph and 6 MBFG_ph and 14 FG_zoo. Large filaments of cyanobacteria and medium- and large-sized unicellular flagellated and non-flagellated forms of algae and filter-feedings and zooplankters with swimming locomotion were the most divers and abundant (Tables 2, 5). Many species (50% of the total species list) reported once and/or only in one lake. Some species were weakly represented in saline environments although their presence in the less concentrated waters is not a rarity since they are very eurioic and cosmopolitan, as in the case of Cymatopleura solea, Fragilaria crotonensis, Nitzschia sigmoidea, Pseudopediastrum boryanum, Raphidocelis danubiana, Monoraphidium minutum among phytoplankton, Lecane luna, Euchlanis dilatata, Keratella quadrata, Notholca acuminata, Chydorus sphaericus, Coronatella rectangula, Macrothrix laticornis, Eucyclops serrulatus, Microcyclops varicans and others among zooplankton. Phytoplankton of soda (III subtype) and sulphate lakes showed the highest floristic affinity (βw = 0.33), between soda lakes Barun-Torey Lake and I–II subtype (βw = 0.75–0.76) species similarity was the lowest. In zooplankton, the highest faunistic affinity was between soda (III subtype) and chloride lakes (βw = 0.30) and the lowest was between soda (I subtype) and sulphate lakes (βw = 0.80).

Taxonomic diversity (the Shannon’s index and richness) showed various trends in lakes with various ionic composition and salinity. Phytoplankton of habitats dominated by chloride salts (TDS = 65.8 ± 68.3 g/L) had an average H diversity of 1.34 ± 0.71 and a mean of 9.0 ± 4.6 taxa and zooplankton of 0.45 ± 0.62 and 2.3 ± 2.0 taxa, while phytoplankton of carbonate habitats (TDS = 47.1 ± 85.81 g/L) had an average H diversity of 0.71 ± 0.87 and a mean of 3.7 ± 4.0 taxa and zooplankton of 1.13 ± 0.81 and 4.3 ± 3.05 taxa. In sulphate lakes (TDS = 60.4 ± 52.0 g/L), H = 0.95 ± 0.68 and n = 4.3 ± 1.5 taxa (phytoplankton) and H = 0.57 ± 0.74 and n = 2.0 ± 1.2 taxa (zooplankton). The data obtained are considerably lower than for other studied lakes of Africa, Australia, Asia, Europe (Blinn 1993; Redden and Rukminasari 2008; Scharerl and Oduor 2008; Toth et al. 2014; Gutierrez et al. 2018; Zhuga et al. 2021). When ranking lakes by salinity, we noted, that increasing salinity lead to the species and functional diversity decrease and structural changes in plankton communities in all lake types. Regardless of the ionic composition, mainly representatives of green algae and copepod and cladoceran crustaceans were numerically abundant under oligo- and mesohaline conditions while cyanobacteria, rotifer Brachionus plicatilis and Anostraca in poly- and hyperhaline waters. Planktonic community being by one-three highly tolerant species developed in the Cl^–- and SO₄^2–-rich waters while aquatic communities were characterized as divers and eveness in soda lakes Barun-Torey and I subtype. Salinity constrains species composition and results in communities of low complexity, where few tolerant species ensure high biomass production in the absence of antagonistic interactions. This agrees with the findings in other studies (Andersen 1955; Bos et al. 1996; Zhao et al. 2005; Balushkina et al. 2007; Schagerl and Oduor 2008; Horváth et al. 2014; Sui et al. 2016; Lin et al. 2017; Gutierrez et al. 2018; Li et al. 2021; Zhuga et al. 2021; Zadereev et al. 2022).

The dominant composition of phytoplankton differed in the studied lakes (17 taxa, varying within 1–4) while zooplankton dominant species were almost the same (8 taxa, varying within 1–2). Five phytoplankton species (Leptolyngbya foveolarum, Phormidium sp., Lindavia comta, Ankyra ancora, Spirulina major and four zooplankton taxa (Brachionus plicatilis, Moina brachiata, Metadiaptomus asiaticus, and Anostraca) being specialized well-adapted species were found in many lakes and accounted for a large proportion in their respective communities of the lakes. A few species of Cyanobacteria and algae (Chlamydomonas, Cryptomonas erosa) and two zooplankters Brachionus plicatilis and Anostraca were recorded at wide salinity spectra (from 1 to 194.5–334.5 g/L). Regardless of the ionic composition of waters at salinity above 100 g/L algae either bloomed (chloride Lake Dabasa-Nor, 257.8 g/L; soda-I Lake Kudzhertay, 194.3–291.6 g/L, sulphate Lake Barun-Shivertuy, 146.8 g/L) or did not develop at all (soda-I Lake Nizhnii Mukey, 128.3 g/L). Invertebrates were recorded in lakes Dabasa-Nor, Kudzhertay and did not in lakes Nizhnii Mukey and Barun-Shivertuy. The reasons for such phenomena remain unclear.

In the spring, during the period of intense vegetation of cyanobacteria and green algae, mass development of rotifers and crustacean nauplii was observed. Cyanobacteria made up summer bloom while copepods comprised the summer (mainly juvenile stages) and autumn (copepotites and adults) peaks. Cryptomonads had a high abundance in summer, diatoms in fall. Results on seasonal succession of planktonic communities are in good agreement with those of other studies on soda lakes (Walker 1973; Vesnina et al. 2005; Golubkov et al. 2007; Alcocer et al. 2022).

Changes in phytoplankton quality and availability may reflect on zooplankton functional diversity (Chapin et al. 2000; Barton et al. 2013) since zooplankton species diversity can be closely related to resources usage and supply (Ptacnik et al. 2008). The major food sources for zooplankton grazers are the cyanoprokaryots, algae, and detritus/organic aggregates. The large-size phytoplankton (above 20 µm) was the most abundant and contributed most of the biomass in this study. Polyphagous rotifers (Brachionus) and the herbivores (Moina, Daphnia, calanoids, cyclopoids, anostracans) filter feed on those items (Monakov 2003; Schagerl 2016; Gilbert 2022). Intense grazing is a consequence of the high salinity and/or lack of fish, which reduces zooplankton diversity, resulting in dominance by large-bodied herbivores (Evans et al. 1996; Boros et al. 2006; Balushkina et al. 2007; Horváth et al. 2014; Lin et al. 2017) and a relatively strong top-down control of phytoplankton (Szabó et al 2020). The zooplankton to phytoplankton biomass ratio (B_zoo/B_ph) ranged from 0.01 to 882 in soda lakes, from 0.01 to 503 in chloride ones, from 31 to 503 in sulphate ones. The data obtained are considerably higher than values in other saline lake ecosystems (Evans et al. 1996; Alimov et al. 2013; Lin et al. 2017; Golubkov et al. 2018). This is primarily due to the excessively high zooplankton biomass in some lakes. High zooplankton density and very low phytoplankton density suggest the existence of a period with a detritus-based food web (García and Niell 1993).

In less-saline soda lakes (< 10 g/L), zooplankton formed three trophic levels (herbivores/detrivores, omnivores with different body sizes, and relatively small predators consuming a limited set of prey) while in more-saline waters (TDS > 30 g/L, regardless of ionic composition of waters) trophic chain was the simplest – only one to three species and one trophic level. Microfilter-feeder (Brachionus plicatilis) and macrofiltrators (Moina, Dahnia, Metadiaptomus) were the main the first-order consumers and rotifer Ascomorpha and Cyclopoida were the second- and third-order consumers. The predatory zooplankton was absent at salinity above 8–10 g/L. Lin et al. (2017) and Zadereev et al. (2022) verified similar results in subsaline to hypersaline lakes. The anostracans and small rotifers play a critical role in the hypersaline food web, which provides for highly efficient utilization of plankton primary production by first-order consumers the predominance of which provide > 98% of the zooplankton ration (Balushkina et al. 2007; Golubkov 2013; Golubkov et al. 2018). Cladoceran and copepod filter-feeders poorly utilize organic matter produced in the course of inedible filamentous algal bloom which was also noted in hyperhaline lakes (Vesnina et al. 2005; Litvinenko et al. 2013; Golubkov et al. 2018; Anufriieva and Shadrin 2023).

Following Bazarova et al. (2023, 2024), the rates primary production were 0.1–5.06 mgO₂/m²day in soda lakes, 0.15–1.65 mgO₂/m²day in sulphate ones, and 0.08–0.29 mgO₂/m²day in chloride ones. Saline lakes are characterized by both extraordinarily high or low primary production levels (Walker 1973; Melack and Kilham 1974; Hammer 1981; Robarts et al. 1992; Oduor and Schagerl 2007; Kompantseva et al. 2009; Oren 2009; Salm et al. 2009; Golubkov 2012; Asencio 2013; Shadrin and Anufriieva 2020) that considerably differs the rates observed in the surveyed region. Secondary production changed within 0.18–32.75 kcal/m³day in soda lakes, 4.75–4.93 kcal/m³day in sulphate ones, and 6.38–29.55 kcal/m³ day in chloride ones. The high values of summer daily production reflects the lack of competition by other zooplankton and surplus food sources in saline lakes, which result in enormous numbers of crustaceans or rotifers. Calanoid Metadiaptomus asiaticus had a prodigious abundance and very high production (reached 0.66 kcal/m³) in Ukshinda Lake (soda-III) when compared with other calanoids Paradiaptomus africanus in soda Lake Nakuru (Mengistou 2016). Wherein secondary production by rotifers (Brachionus plicatilis) in lakes Shvartsivskoe (soda-III) and Shikhalin-Nuur (sulphate) was almost the same (12.91–81.37 kcal/m³) when compared with Lake Nakuru (Mengistou 2016).

The efficiency of energy transmission from the first to second trophic levels (P_zoo/P_ph) averaged 29% (soda lakes), 49% (sulphate ones), and 92% (chloride ones) (CV ≥ 100%), which is considerably higher than the values for Crimean saline lake ecosystems (Golubkov et al. 2018). Zooplankton grazing may depress phytoplankton accumulation rates and ultimately total primary production, that was observed in Tibetan lakes (Lin et al. 2017). The maximum efficiency of energy transmission was observed in the chloride lakes, approaching the average values in marine ecosystems (Golubkov et al. 2018). No statistically significant correlation was found in the Crimean lakes between the efficiency of energy transmission from producers to the second trophic level and salinity within the range 28–312 g/L. Thus, hyperhaline sulphate lakes Marfovskoe and Koyashskoe had the efficiency of energy transmission values of 0.1% and 27% at a salinity level of 186 g/L and 311 g/L respecively; in polyhaline chloride Lake Bakalskoe, 23.6% at salinity of 28 g/L (Golubkov et al. 2018). It was shown that growth rate and production of animals decreases with a salinity increase in hypersaline waters (Anufriieva and Shadrin 2022). Environmental stress results in highly constrained systems which exhibit high rates of functioning due to these key species, in spite of the very limited species (Horváth et al. 2014). Thus, in lakes with high salt content (regardless of ionic composition) phytoplankton is large relative to those in waters with the low TDS values, and this allows for the establishment of a shorter food web and a more direct transfer of organic matter to higher trophic levels. And consequently, aquatic community with two-three levels shifts to a community with one trophic level, as well as from low productivity to higher productivity. Moreover, the zooplankton community is relatively simple and energy may be transferred efficiently from one trophic level to another.

Some recent studies showed that environment is crucial in the formation of planktonic communities (Balushkina et al. 2009; Barnett et al. 2007; Golubkov et al. 2018; Larson and Belovsky 2013; Horváth et al. 2014; Hébert et al. 2016; Shagerl 2016; Sui et al. 2016; Lin et al. 2017; Gutierrez et al. 2018; Shadrin and Anufriieva 2018; Afonina and Tashlykova 2019; Somogyi et al. 2022; Zadereev et al. 2022). The most important factors affecting on phytoplankton and zooplankton structure were resources (nitrogen and phosphorus) and acid-alkali properties (pH and Eh) in soda lakes, while the main measured factors in sulphate waters were water temperature, turbidity, the chemical oxygen demand, nitrate, total nitrogen, phosphate, and total phosphorus. TDS, NO₃^–, ƩN, and Turb were the main variables in chloride waters.

Three phytoplankton phyla (Cyanobacteria, Bacillariophyta, and Chlorophyta) are the main functional groups, divers and abundant in the saline lakes under a wide range of salinity values. Along salinity gradients cyanobacteria and chlorophytes prefer different salinity ranges and could even be able to grow at salinity > 100 g/L producing a bloom and scum (Vesnina et al. 2005; López-González et al. 2006; Golubkov et al. 2007; Kirillov et al. 2008; Samylina et al. 2010, 2016; Almeida et al. 2011; Komova et al. 2018; Alcocer et al. 2022) while diatoms favor mid-to-high salinities (Hammer et al. 1983; Robarts et al. 1992; Evans and Prepas 1996; Blinn et al. 2004; Salm et al. 2009). In studied lakes as well as in saline lakes of Western Siberia and Altai (Vesnina et al. 2005; Kirillov et al. 2008; Samylina et al. 2010, 2014; 2016; Litvinenko et al. 2013; Bryanskaya et al. 2016; Komova et al. 2018; Gorlenko et al. 2020), Transylvanian Basin (Alexe et al. 2018; Korponai et al. 2019), Crimea (Golubkov et al. 2007), the Uldza and Kerulen river valleys (Afonina and Tashlykova 2018), the Pantanal of Nhecolândia (Almeida et al. 2011), and lakes Alchichica (Alcocer et al. 2022), Big Soda (Cloern et al. 1983), Balkhash and Kamyslybas (Kawabara et al. 1997) singular (e.g. Ankyra ancora, Chlamydomonas sp.) and colonial (e.g. Tetrastrum komarekii, Oocystis submarina) chlorophytes and filamentous (e.g. Anabaenopsis knipowitschii, Nodularia spumigena, Phormidium breve, Nostoc commune, Leptolyngbya foveolarum) and colonial (e.g. Microcystis aeruginosa, Aphanothece salina) cyanobacteria dominance are characteristic of summer phytoplankton. In this study, a bloom of cyanobacteria Aphanothece salina, Limnospira fusiformis, and Leptolyngbya foveolarum occurred, reaching a cell density of 2963.52 ×10³ cell/L, 1189.0 ×10³ cell/L and 1114.74 ×10³ cell/L at salinity of 17.6 g/L (soda lake, II subtype), 31.4 g/L (soda lake, III subtype), and 39.8 g/L (chloride lake), while green algae Ankyra ancora abundance was 3322.4 ×10³ cell/L (sulphate lake, TDS = 45.4 g/L).

The halotolerant members of the genera Amphora, Nitzschia and Navicula of the motile diatom ecological guild are the most frequent in the saline lakes, especially if nitrogen and phosphorus are high (Koçer and Şen 2012; Stenger-Kovács et al. 2014; Lengyel et al. 2015; Ćiric et al. 2021). But in the surveyed lakes diatom algae were rare while cryptophyte algae (Cryptomonas sp., C. erosa) played important roles in the mesohaline (5.3–8.7 g/L) to hyperhaline soda lakes (194.5–291.6 g/L). Wherein following (Khromechek et al. 2010; Naceur et al. 2013) the phytoflagellate Cryptomonas was one of the dominant species in sulfate-chloride waters.

Regarding the mass zooplankton species, rotifer Brachionus plicatilis tolerates a remarkable range of environmental conditions and may attain very high population densities (Walker 1981). Following Derry et al. (2003), B. plicatilis prefers chloride-rich lakes whereas Walker (1973) noted that the rotifer attaines a maximal abundance in soda lakes. In current study, B. plicatilis formed monodominant communities in the various lake types and subtypes with wide TDS variations (soda-II subtype, TDS = 17.6 g/L; soda-III subtype, TDS = 22.1–31.4 g/L; sulphate, TDS = 45.4–67.5 g/L; and chloride, TDS = 39.8–73.3 g/L) where density had abruptly grown (21780.0 ×10³ ind./m³, 47500.0–303187.5 ×10³ ind./m³, 3649.17–130400 ×10³ ind./m³, and 874.67–31681.43 ×10³ ind./m³ respectively). At a salinity of 194.5–291.6 g/L (Kudzhertay Lake) rotifer occured rarely (6.67–10.52 ×10³ ind./m³). PCA declared that the strong negative correlation (r = -0.91) was observed between B. plicatilis abundance and Cl^– and HCO₃^–+CO₃^2– in sulphate lakes.

Cladoceran Moina brachiata being common in small ephemeral localities or highly eutrophic ponds and can withstand elevated salinities (Horváth et al. 2014; Tóth et al. 2014). In our researches, M. brachiata dominated in meso- and polyhaline lakes regardless of the ionic composition. The highest abundance and biomass (217.33–370.08 ×10³ ind./m³ and 18.15–53.51 g/m³) were observed at a salinity of 6.2–21.3 g/L. Accoding previous researches (Tashlykova and Afonina 2019), M. brachiata can be very abundant; thus, in Lake Aru-Torum (TDS = 30 g/L), its abundance and biomass reached 3045 ×10³ ind./m³ and 201.32 g/m³. Moina eggs and ephippia can observed in lakes with salinity ≥ 100 g/L (Balushkina et al. 2007; Gorlacheva et al. 2014).

Among Copepoda Metadiaptomus asiaticus is the most typical halobiont that avoids fresh waters (Borutsky et al. 1991) and is widespread in chloride lakes of Kazakhstan (Zhuga et al. 2021), Mongolia (Alonso 2010), and China (Wang et al. 2014). Wang et al. (2014) summarized that M. asiaticus prefers to waters with high Cl^– concentration and alkalinity. In our study, M. asiaticus was recorded in all lake types except the Barun-Torey Lake and inhabited mainly in mesohaline to polyhaline waters (regardless of the ionic composition). The highest abundance (734.4–1782.86 ×10³ ind./m³) and biomass (44.97–137.51 g/m³) were in Lake Ukshinda at TDS = 14.9–16.4 g/L. At the same time, single adults and juveniles can be found at a salinity of 138.5–231.3 g/L.

Anostracan crustaceans dominated in Cl-rich waters at a salinity of 70.23–138.5 g/L (10.26–54.72 ×10³ ind./m³) in this study. Due to the most developed osmoregulatory system, the some species of Anostraca can stay in a medium with a high amount of salts. One of the halopfilic representatives Artemia can tolerate and adapt to extreme environment (Salazkin et al 1984; Vesnina et al. 2005; Balushkina et al. 2007; Boyko 2013; Vignatti et al. 2020). In the hypersaline waters a very simple tropical structure are found and Artemia plays monopolistic ecological function in the zooplankton community. Some researches (Boyko 2013; Litvinenko et al. 2013; Zhuga et al. 2021) obtained that pH, TDS and ions (Cl^–, SO₄^2–, (Na⁺+K⁺), ratios Cl^–/(HCO₃^–+CO₃^2–), SO₄^2–/(HCO₃^–+CO₃^2–), and Cl^–/SO₄^2– have the greatest effect on the development and growth of Artemia.

For eighteen lakes there is evidence that species sorting in response to anionic composition is a key determinant of the taxon composition of aquatic communities. We found a positive relationship with sulphate ions for cyanobacteria Anabaenopsis knipowitschii and rotifer Brachionus angularis and with carbonate ions for cyanobacteria Limnospira fusiformis and rotifers Ascomorpha ecaudis and Hexarthra mira. Our study confirms that Limnospira fusiformis is a character species of soda lakes in Africa and Asia (Krienitz and Schagerl 2016). We did not find any references about the preference of other mantioned above species to specific ions.

In conclusion, the surveyed lakes fall into five categories (sulphate (Na-SO₄, pH < 9) – 2 lakes; chloride (Na-Сl, pH < 9) – 3 ones; soda (Na-HCO₃, pH < 9) – one lake; soda, I subtype (Na-HCO₃-CO₃, pH > 9) – 6 ones; soda, II subtype (Na-SO₄, pH > 9 ) – 2 ones; soda, III subtype (Na-Cl, pH > 9) – 4 ones). The composition and structure of planktonic communities is regulated both by the total salt content (TDS) and the anionic composition of waters. Total salinity determines species and functional diversity, changes in trophic structure and results in communities of low complexity, where few population of aquatic organisms ensure high abundance, biomass and secondary production. When ranking lakes by salinity, in phytoplankton, a shift occurred from the small-medium cell size unicellular and colonial non-flagellated forms to the large-extra large filamentous cyanobacteria and colonial algae. A shift from selective raptorial and microphagous carnivores to herbivorous copepods and cladocerans and further to more generalist filter-feeder of rotifers and anostracans was observed in zooplankton. We determined two population of aquatic organisms: species Anabaenopsis knipowitschii and Brachionus angularis prefer sulphate dominated habitats while other species Limnospira fusiformis, Ascomorpha ecaudis, and Hexarthra mira commonly associate with carbonate dominated habitats.

Acknowledgments The reported study was carried out at the expense of the grant of the Russian Science Foundation No. 22-17-00035, https://rscf.ru/project/22-17-00035/. We would also like to thank the anonymous reviewers and editors of this manuscript.

Author contributions Conceptualization and developing methods: EA, SB, and NT. Conducting the research: EA, SB, and NT. Data analysis and interpretation: EA and SB. Preparation of figures and tables: SB and NT. Writing: EA and SB.

Data Availability Data, associated metadata, and calculation tools are available from the corresponding author ([email protected]).

Conflict of interest All of the authors claim that none of the material in this paper “Saline lakes of Transbaikalia (Russia): Limnology and diversity of plankton communities” has been published or is under consideration for publication elsewhere. All authors declare that we have no confict of interest. This paper does not contain any studies with human participants or animals performed by any of the authors. The funding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

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Таble 1 The main physical and chemical parameters of lakes under study

Lake	Sampling data	T	pH	TDS	HCO₃^–+ CO₃^2–	SO₄^2–	Cl^–	Са²⁺	Mg²⁺	Na⁺	K⁺	O₂	NO₃^–	ƩN	РО₄^3–	ƩP	TOC	Eh	Turb	СOD
Lake	Sampling data	°C	pH	g/L	g/L							mg/L					mgO/L	mV	FTU	mgO/L
Na-HCO₃, pH < 9
Barun-Torey	29.12.2021	0.5	7.8	0.1	0.08	0.01	0.01	0.007	0.004	0.01	0.00	-	0.2	0.2	0.00	0.09	4.3	-	-	-
	10.04.2022	2.3	8.4	0.5	-	-	-	-	-	-	-	-	-	-	-	-	-	314.0	-	-
	26.07.2022	20.4	8.3	1.0	0.52	0.09	0.11	0.014	0.017	0.26	0.01	7.9	6.1	1.5	0.36	0.46	16.2	106.0	1429.0	43.2
	06.10.2022	2.8	8.4	1.2	0.61	0.06	0.10	0.029	0.045	0.28	0.08	12.2	5.0	1.3	0.39	0.55	14.1	129.0	18.8	26.4
	17.07.2023	24.5	8.7	1.2	0.63	0.07	0.13	0.027	0.015	0.34	0.01	6.4	24.1	7.1	0.46	0.53	11.7	242.0	177.9	46.2
Soda-type, I subtype (Na-HCO₃-CO₃, pH > 9)
Nozhii	21.07.2021	22.8	9.4	4.1	1.67	0.82	0.34	0.011	0.124	1.01	0.07	-	7.0	2.3	0.26	0.29	25.7	151.0	6.5	136.8
	21.07.2021	23.1	9.5	4.2	1.68	0.88	0.33	0.012	0.145	1.02	0.09	10.4	7.1	1.8	0.27	0.27	23.4	127.0	6.7	131.5
	28.12.2021	0.8	9.1	4.3	1.97	0.69	0.43	0.012	0.359	0.58	0.30	-	12.2	3.7	0.22	0.25	28.8	164.0	6.1	135.8
	28.12.2021	1.5	9.1	4.9	2.00	1.04	0.43	0.012	0.362	0.74	0.31	-	16.8	4.9	0.23	0.27	30.0	181.0	6.1	134.9
	16.03.2022	–0.2	9.1	7.2	2.87	1.60	0.64	0.013	0.546	1.10	0.44	-	17.1	4.1	0.34	0.38	41.0	158.0	6.1	190.5
	16.03.2022	–0.3	9.1	7.2	2.84	1.56	0.65	0.022	0.507	1.16	0.41	-	17.9	4.4	0.28	0.33	43.3	171.0	6.2	301.7
	30.07.2022	22.4	9.3	3.5	1.35	0.82	0.27	0.015	0.117	0.85	0.06	8.8	8.1	1.9	0.05	0.08	23.9	82.0	2.3	98.4
	07.10.2022	4.1	9.6	4.1	-	-	-	-	-	-	-	11.9	-	-	-	-	-	115.1	19.2	-
Bain-Tsagan	30.03.2021	–0.1	9.4	9.9	4.17	0.33	2.04	0.012	0.107	3.11	0.10	-	25.1	5.9	0.66	1.51	44.6	83.0	2.8	276.0
	23.07.2021	20.0	9.5	8.2	3.44	0.21	1.74	0.008	0.074	2.59	0.10	-	24.7	5.8	2.50	2.66	34.0	60.0	1.4	266.0
	23.07.2021	20.1	9.5	8.0	3.42	3.42	0.17	1.70	0.007	0.07	2.54	-	0.10	23.6	5.50	2.43	2.8	30.0	92.0	3.0
	24.09.2021	17.7	9.4	7.8	3.33	0.15	1.68	0.010	0.090	2.45	0.09	-	29.0	6.9	1.76	1.83	38.5	124.0	-	208.0
	17.03.2022	–0.1	9.4	11.0	4.51	0.32	2.35	0.012	0.222	3.09	0.40	-	53.7	12.5	2.18	3.01	42.2	145.0	1.5	281.6
	17.03.2022	–0.6	9.3	10. 9	4.46	0.32	2.35	0.011	0.213	3.09	0.38	-	53.7	12.6	2.10	2.74	41.8	158.0	1.5	273.4
	24.07.2022	27.2	9.4	8.8	3.55	0.23	1.83	0.007	0.077	2.95	0.09	6.6	18.1	4.5	1.97	2.24	37.3	117.0	7.6	162.7
	24.07.2022	26.9	9.4	8.8	3.50	0.34	1.84	0.007	0.081	2.92	0.09	5.5	17.3	4.3	1.95	2.23	38.1	134.0	10.6	159.2
	05.10.2022	7.5	9.6	11.6	-	-	-	-	-	-	-	10.3	-	-	-	-	-	139.4	7.5	-
	18.07.2023	21.5	9.2	9.7	3.91	0.33	2.05	0.008	0.080	3.10	0.10	7.8	89.5	20.9	2.40	2.60	37.7	121.0	8.8	273.9
Balyktuy	23.07.2021	27.1	9.6	8.0	3.97	0.28	1.07	0.008	0.071	2.49	0.07	13.2	20.1	4.8	3.12	3.64	61.9	66.0	139.6	332.0
Bain-Bulak	30.03.2021	–0.3	9.3	8.7	3.98	0.27	1.65	0.010	0.214	2.54	0.04	-	19.0	4.4	0.18	0.44	78.9	29.0	9.7	436.0
	23.07.2021	26.4	9.5	4.7	2.29	0.04	0.81	0.007	0.095	1.37	0.04	11.2	12.4	2.9	0.13	0.19	30.2	137.0	6.7	172.0
	24.09.2021	15.4	9.8	3.6	1.55	0.09	0.69	0.009	0.098	1.11	0.03	-	12.8	3.5	0.04	0.08	34.6	9.5	-	146.0
	04.10.2022	3.4	9.9	5.3	-	-	-	-	-	-	-	9.8	-	-	-	-	-	132.0	316.0	-
Kudzhertay	30.03.2021	8.9	9.9	105.8	36.49	1.40	26.27	0.009	0.013	40.86	0.45	-	250.8	60.8	2.30	26.50	543.7	–501	530.6	2164.0
	22.07.2021	21.0	9.9	194.5	69.56	2.35	45.94	0.001	0.004	75.44	0.27	1.2	778.5	181.1	152.83	180.48	724.5	–479	635.4	4720.0
	24.09.2021	18.7	10.0	49.8	15.84	0.62	13.61	0.007	0.006	19.17	0.17	-	274.0	63.8	31.39	39.81	169.2	–248	-	930.0
	24.07.2022	33.4	9.8	291.6	99.32	4.65	72.83	0.002	0.013	112.40	1.49	2.3	617.4	146.7	279.50	359.63	1333.3	95.6	125.6	7936.5
Nizhnii Mukey	31.03.2021	7.6	9.9	67.4	22.07	6.72	12.95	0.010	0.064	25.29	0.14	-	134.6	31.0	2.99	19.10	266.5	–15.0	548.6	676.0
Nizhnii Mukey	26.07.2021	24.4	9.9	128.3	39.65	13.50	25.86	0.002	0.033	48.72	0.14	8.4	339.1	80.0	37.82	55.55	483.0	–443	927.1	1560.0
Soda-type, II subtype (Na-SO₄, pH > 9 )
Haraganash	29.07.2022	18.4	8.8	3.7	0.47	1.56	0.50	0.010	0.149	0.85	0.11	9.4	6.9	1.7	0.33	0.49	14.0	102.8	63.1	52.9
Haraganash	19.07.2023	25.0	10.2	10.4	0.65	4.29	1.92	0.009	0.405	2.67	0.38	8.3	77.4	17.9	0.04	0.17	47.4	61.1	4.9	318.4
Sheluta	29.07.2022	23.5	9.4	6.2	1.62	1.69	0.84	0.003	0.133	1.73	0.19	9.9	14.3	3.5	0.78	1.09	43.1	82.3	18.6	162.1
Sheluta	19.07.2023	25.8	9.4	17.6	4.66	3.84	2.91	0.003	0.217	5.21	0.57	13.4	153.2	39.4	0.82	2.47	157.6	50.9	25.8	595.4
Soda-type, III subtype (Na-Cl, pH > 9)
Ukshinda	30.03.2021	–1.4	9.3	37.4	12.41	1.89	9.90	0.009	0.249	12.65	0.18	-	79.7	18.4	1.31	3.20	109.9	113.0	19.2	680.0
	23.07.2021	24.0	9.5	16.1	5.34	0.68	4.34	0.002	0.086	5.50	0.12	8.2	55.1	12.8	0.08	1.19	43.4	17.0	32.7	258.0
	24.09.2021	16.2	9.4	13.2	4.22	0.59	3.66	0.010	0.088	4.46	0.09	-	53.4	12.4	1.42	1.75	46.2	–200	-	238.0
	17.03.2022	–2.1	9.2	48.8	15.90	2.42	12.98	0.010	0.603	15.49	1.06	-	283.4	65.3	5.23	5.60	149.8	116.0	6.4	938.8
	25.07.2022	22.4	9.6	15.0	4.73	0.84	4.04	0.003	0.074	5.11	0.10	7.4	32.2	7.5	1.60	1.83	45.0	97.0	12.2	310.4
	04.10.2022	4.2	9.6	22.7	-	-	-	-	-	-	-	11.3	-	-	-	-	-	144.4	41.5	-
Khadatuy	30.03.2021	12.6	9.7	35.2	8.95	1.70	11.29	0.009	0.081	12.76	0.25	-	126.6	29.4	2.30	15.20	299.2	–50.0	579.9	1600.0
Khadatuy	24.09.2021	18.5	9.7	15.9	4.14	0.57	5.32	0.016	0.053	5.64	0.15	-	9.3	2.3	12.19	12.86	107.7	–167	-	565.0
Shvartsivskoe	22.07.2022	31.1	9.3	22.1	2.16	5.17	7.24	0.031	0.761	6.54	0.10	11.9	64.3	24.2	1.75	3.42	96.3	129.0	72.0	492.8
Shvartsivskoe	15.07.2023	26.0	9.0	31.4	3.17	8.00	9.61	0.040	1.070	9.15	0.13	2.3	149.4	83.1	3.42	6.12	135.3	124.0	65.2	989.0
Borzinskoe	02.04.2021	3.0	9.3	235.3	16.29	11.93	116.18	0.006	0.010	89.68	0.13	-	1029.0	237.0	2.99	23.00	282.9	–397	1344.0	640.0
	27.07.2021	30.1	9.4	231.3	14.34	37.66	92.31	0.002	0.004	85.53	0.10	3.6	1353.0	311.3	59.89	72.96	269.2	–59.0	204.9	320.0
	23.07.2022	29.1	9.5	138.5	9.51	3.76	71.73	0.002	0.007	53.12	0.11	2.0	286.5	66.0	54.70	57.62	181.0	125.0	16.7	1770.8
	15.07.2023	31.4	9.2	334.5	18.90	31.46	156.53	0.002	0.005	126.17	0.14	1.2	1271.4	292.5	103.00	136.33	337.3	48.0	57.0	4747.1
Chloride-type (Na-Сl, pH < 9)
Khilganta	01.04.2021	2.3	8.9	8.2	0.37	1.10	3.89	0.023	0.353	2.43	0.03	-	43.8	10.2	0.01	0.06	23.3	29.0	29.7	160.0
	22.07.2021	20.9	8.5	33.9	0.28	5.79	15.82	0.099	1.408	10.16	0.09	-	214.0	51.7	0.03	0.06	43.0	-3.0	8.1	170.3
	28.07.2022	25.1	8.8	17.1	0.15	2.87	8.05	0.070	0.702	5.14	0.05	10.8	98.3	22.7	0.02	0.03	28.3	105.0	0.9	72.2
	20.07.2023	22.4	8.6	65.6	0.14	7.93	34.17	0.203	2.823	19.94	0.14	8.1	276.6	78.7	0.03	0.10	104.4	–25.8	3.4	1068.1
Gorbunka	01.04.2021	2.2	8.2	33.1	0.64	3.82	16.65	0.027	0.986	10.73	0.08	-	154.6	35.6	0.01	0.10	59.3	15.0	70.5	160.0
	21.07.2021	28.5	8.1	69.9	0.34	6.07	37.09	0.027	0.916	24.86	0.12	-	427.9	98.7	0.10	0.18	101.9	–116	34.4	1020.0
	28.07.2022	22.0	8.1	14.5	0.38	1.32	7.48	0.030	0.416	4.70	0.05	8.8	74.4	17.5	0.03	0.05	31.4	123.0	6.3	77.9
	20.07.2023	24.0	8.0	70.3	0.56	4.88	38.80	0.037	1.891	23.58	0.19	8.0	309.7	87.2	0.04	0.11	116.3	–28.4	42.6	1097.8
Dabasa-Nor	24.07.2021	22.4	8.9	39.8	0.72	6.53	18.21	0.043	1.007	13.04	0.09	-	196.0	45.4	0.05	0.20	55.8	–13.0	1.5	952.0
	25.07.2022	24.6	8.6	73.1	0.30	14.06	32.19	0.061	1.325	24.69	0.10	8.9	323.3	77.9	0.13	0.36	134.0	132.5	9.7	2259.3
	18.07.2023	31.7	8.1	257.8	1.08	43.16	120.81	0.082	6.906	84.40	0.41	2.0	997.8	231.1	0.22	0.27	454.9	–63.9	51.9	4628.4
Sulphate-type (Na-SO₄, pH <9 )
Shikhalin-Nuur	23.07.2022	24.9	9.0	21.3	1.15	7.88	5.13	0.028	0.532	6.45	0.04	4.7	39.5	9.3	0.19	0.34	33.4	115.0	2.1	117.2
Shikhalin-Nuur	15.07.2023	19.4	9.0	67.5	2.29	27.04	15.52	0.015	1.358	21.02	0.11	3.3	124.7	42.1	0.35	0.84	98.0	108.1	7.1	607.2
Barun-Shivertuy	22.07.2022	25.8	7.8	45.4	0.63	19.25	10.18	0.069	0.813	14.18	0.07	4.3	82.4	28.0	0.22	0.62	76.9	167.0	11.7	228.9
Barun-Shivertuy	14.07.2023	27.7	8.6	146.8	1.24	49.40	45.64	0.073	4.026	45.27	0.28	0.4	367.2	96.4	1.10	3.42	370.7	20.9	124.9	3837.2

-, not measured

Table 2 List of phytoplankton taxa with their functional characteristics (cell size: S – small, M – medium, L – large, EL – extra-large; cell shape: S – singular, Col – colonial, Fil – filamentous; life form: UF – unicellular flagellates, CF – colonial flagellates, UNF – unicellular non-flagellates, CNF – colonial non-flagellated (including coenobia), FI – filaments; size: 1 – ˂10 µm, 2 – 11-20 µm, 3 – 21-50 µm, 4 – ˃ 50 µm; FG according Padisak et al. (2009); MBFG – according Kruk et al. (2010)) at various saline lakes

Taxa

Cell size

Cell shape

Life form

Size

MBFG

Soda

Chloride

Sulfate

B-T

III

Cyanobacteria

Anabaena sp.

Fil

III

Anabaenopsis knipowitschii (Usachev) Komárek 2005

Fil

III

Aphanothece salina Elenkin & A. N.Danilov 1915

Col

CNF

VII

Coleofasciculus chthonoplastes (Gomont) M. Siegesmund, J.R. Johansen & T. Friedl 2008

Fil

III

Dolichospermum flos-aquae (Bornet & Flahault) P. Wacklin, L. Hoffmann & Komárek 2009

Fil

III

Gloeocapsa minima (Keissler) Hollerbach 1938

Col

CNF

1-2

G. minutula N.L. Gardner 1927

Col

CNF

1-2

G. montana Kützing 1843

Col

CNF

1-2

Leptolyngbya foveolarum (Gomont) Anagnostidis & Komárek 1988

Fil

III

L. valderiana (Gomont) Anagnostidis & Komárek 1988

Fil

III

Limnospira fusiformis (Voronichin) Nowicka-Krawczyk, Mühlsteinová & Hauer 2019

Fil

III

Lyngbya sp.

Fil

III

Merismopedia minima G. Beck 1897

Col

CNF

1-2

VII

Microcystis aeruginosa (Kützing) Kützing 1846

Col

CNF

3-4

VII

Nodularia spumigena Mertens ex Bornet & Flahault 1888

Fil

III

Nostoc commune Vaucher ex Bornet & Flahault 1888

Fil

III

Oscillatoria limosa C. Agardh ex Gomont 1892

Fil

O. tenuis C. Agardh ex Gomont 1892

Fil

Phormidium breve (Kützing ex Gomont) Anagnostidis & Komárek 1988

Fil

III

P. sp.

Fil

III

Phormidesmis mollis (Gomont) Turicchia, Ventura, Komárková & Komárek 2009

Fil

III

Spirulina major Kützing ex Gomont 1892

Fil

III

S. sp.

Fil

III

Stenomitos frigidus (F.E. Fritsch) Miscoe & J.R. Johansen 2016

Fil

III

Synechococcus elongatus (Nägeli) Nägeli 1849

Col

CNF

1-2

Trichormus variabilis (Kützing ex Bornet & Flahault) Komárek & Anagnostidis 1989

Fil

III

Bacillariophyta

UNF

Amphora ovalis (Kützing) Kützing 1844

UNF

Cymatopleura solea (Brébisson) W. Smith 1851

UNF

Cymbella sp.

Col

CNF

Fragilaria crotonensis Kitton 1869

UNF

Lindavia comta (Kützing) T. Nakov & al. 2015

UNF

Navicula sp.

UNF

Nitzschia sp.

UNF

N. sp. sp.

UNF

N. sigmoidea (Nitzsch) W. Smith 1853

UNF

Pinnularia sp.

UNF

Dinophyta

Peridinium sp.

Cryptophyta

Cryptomonas erosa Ehrenberg 1832

C. marssonii Skuja 1948

C. salina Wisłouch 1924

C. sp.

Komma caudate (L. Geitler) D.R.A. Hill 1991

Chlorophyta

Ankyra ancora (G.M. Smith), 1957

CNF

Chlamydomonas platystigma Pascher 1927

C. sphagnophila Pascher 1930

C. sp.

C. sp. sp.

Coenococcus planctonicus Korshikov 1953

Col

CNF

Lagerheimia genevensis (Chodat) Chodat 1895

Col

CNF

Monoraphidium contortum (Thuret) Komárková-Legnerová 1969

UNF

M. komarkovae Nygaard 1979

UNF

M. minutum (Nägeli) Komárková-Legnerová 1969

UNF

M. sp.

UNF

Oocystis parva West & G.S. West 1898

Col

CNF

VII

O. rhomboidea Fott 1933

Col

CNF

VII

O. submarina Lagerheim 1886

Col

CNF

VII

O. sp.

Col

UNF

Pseudopediastrum boryanum (Turpin) E. Hegewald 2005

Col

CNF

Raphidocelis danubiana (Hindák) Marvan, Komárek & Comas 1984

UNF

Scenedesmus acutus Meyen 1829

Col

CNF

VII

S. quadricauda (Turpin) Brébisson 1835

Col

CNF

Schroederia robusta Korshikov 1953

UNF

Tetrastrum komarekii Hindák 1977

Col

UNF

T. triangulare (Chodat) Komárek 1974

UNF

Tetraëdron incus (Teiling) G.M. Smith 1926

UNF

Pandorina morum (O.F. Müller) Bory 1826

Col

Wislouchia salina (Wisłouch) Molinari & Guiry 2021

Col

Charophyta

Cosmarium sp.

UNF

Staurastrum sp.

UNF

Euglenophyta

Colacium simplex Huber-Pestalozzi 1955

Col

Euglena pisciformis Klebs 1883

E. sp.

Phacus sp.

Table 3 The dominant species composition of phytoplankton at various lake types in summer 2021–2023

Lake type	Salinity group	Phytoplankton (in descending order)
Na-HCO₃	oligohaline	C. simplex, L. foveolarum
Soda-type, I subtype (Na-HCO₃-CO₃)	oligohaline	A. ancora, T. komarekii, M. elegans, L. foveolarum
	mesohaline	Chlamydomonas sp., C. erosa, A. ancora
	hyperhaline	O. breve
Soda-type, II subtype (Na-SO₄)	oligohaline	O. submarina, A. ancora
Soda-type, II subtype (Na-SO₄)	mesohaline	N. commune, O. submarina
Soda-type, III subtype (Na-Cl)	mesohaline	L. foveolarum, O. submarina, A. ancora
	polyhaline	C. erosa, L. fusiformis
	euhaline	L. fusiformis
	hyperhaline	C. salina, L. foveolarum, S. frigidum, K. caudata
Chloride-type (Na-Сl)	mesohaline	A. ancora, L. foveolarum
	euhaline	O. breve, C. sphagnicola, Chlamydomonas sp. sp.
	hyperhaline	O. breve, C. chthonoplastes, L. foveolarum, S. frigidum
Sulphate-type (Na-SO₄)	polyhaline	O. submarina, S. frigidum
Sulphate-type (Na-SO₄)	hyperhaline	O. breve, L. foveolarum, S. frigidum

Table 4 Seasonal changes of phytoplankton diversity and structure (min–max/mean±SD) in 2021–2023

	Spring	Summer	Autumn
Na-HCO₃
Species number	10	1–4	3
N, ×10³ cell/m³	257.64	53.17–172776.8/57970.99±99426.08	20.47
B, mg/m³	54.04	15.58–7392.62/2484.56±99426.08	2.11
Dominant taxa	Monoraphidium sp.	L. foveolarum, C. simplex	N. sigmoidea
Soda-type I subtype
Species number	3–19	0–14	2–3
N, ×10³ cell/m³	4.5–1296.9/160.38±428.68	0–55605/2718.83±12119.45	0.75–16.96/8.04±6.86
B, mg/m³	0.76–4673.7/543.78±1550.19	0–24410.6/1230.61±5318.66	0.85–6.63/3.07±2.68
Dominant species	O. tenuis, Lyngbya sp.	Chlamydomonas sp., C. erosa, Anabaena sp., A. ancora, T. komarekii, L. foveolarum, P. breve	N. sigmoidea, G. minina, N. spumigena
Soda-type III subtype
Species number	0	1–7	2–3
N, ×10³ cell/m³	0	1.36–1188.44/223.85±363.61	0.75–76.46/38.61±53.54
B, mg/m³	0	0.13–86478.03/9434.04±25805.24	0.85–29.77/15.31±20.45
Dominant species	0	L. foveolarum, C. erosa, L. fusiformis, K. caudate	Anabaena sp.

Table 5 List of zooplankton taxa with their functional characteristics (Gavrilko et al. 2020) (FG – number of functional group; FD – feeding type: c – capture, v – verification, pf – primary filtration, sf – secondary filtration, s – suction, g – gathering; LT – locomotion type: s – swimming, c – crawling, a – attachment) at various saline type lakes

Taxa	FG	FD	LT	Soda				Chloride	Sulfate
Taxa	FG	FD	LT	B-T	I	II	III
Rotifera
Ascomorpha ecaudis Perty, 1850	7	c+s	s	-	+	-	-	-	-
Brachionus angularis Gosse, 1851	10	v	s+c	-	+	-	-	-	-
B. quadridentatus Hermann, 1783	10	v	s+c	-	+	-	-	-	-
B. quadridentatus quadridentatus Hermann, 1783	10	v	s+c	-	+	-	-	-	-
B. plicatilis Müller, 1786	10	v	s+c	+	+	+	+	+	+
B. variabilis Hempel, 1896	10	v	s+c	+	-	-	-	-	-
Cephalodella sp.	12	s	s+c	-	-	-	+	+	-
Colurella adriatica Ehrenberg, 1831	10	v	s+c	-	+			+	-
Eosphora najas Ehrenberg, 1830	12	s	s+c	-	+	-	-	-	-
Euchlanis dilatata Ehrenberg, 1832	10	v	s+c	-	+	-	-	-	-
Filinia longiseta (Ehrenberg, 1834)	14	v	s	+	-	-	-	-	-
Hexarthra mira (Hudson, 1871)	14	v	s	-	+	+	+	+	-
Kellicottia longispina (Kellicott, 1879)	14	v	s	-	+	-	-	-	-
Keratella quadrata (Müller, 1786)	14	v	s	+	+	-	-	+	-
Lecane luna (Müller, 1776)	11	c+s	s+c	-	+	+	-	-	-
Mytilina ventralis (Ehrenberg, 1830)	10	v	s+c	-	+	-	-	-	-
Notholca acuminata (Ehrenberg, 1832)	14	v	s	-	+	-	-	-	-
Synchaeta sp.	13	c+s	s	-	+	-	-	-	-
Proales similis de Beauchamp, 1907	10	v	s+c	+	-	-	-	+	-
Cladocera
Bosmina sp.	16	pf	s	-	-	-	+	-	-
Chydorus sphaericus (O.F. Müller, 1785)	9	sf	s+c	+	+	-	-	-	-
Coronatella rectangula Sars, 1862	9	sf	s+c	+	+	-	-	-	-
Daphnia galeata Sars, 1864	16	pf	s	-	+	-	-	-	-
D. sinensis Gu, Xu, Li, Dumont et Han, 2013	16	pf	s	+	-	-	-	-	-
D. sp.	16	pf	s	-	+	-	+	-	-
D. (Ctenodaphnia) magna Straus, 1820	15	pf	s	+	+	-	-	-	-
Macrothrix hirsuticornis Norman et Brady, 1867	8	g	s+c	-	+	-	-	-	-
M. laticornis (Jurine, 1820)	8	g	s+c	-	+	-	-	-	-
Moina brachiata (Jurine, 1820)	16	pf	s	+	+	+	+	+	+
Pleuroxus aduncus (Jurine, 1820)	9	sf	s+c	-	+	-	-	-	-
Simocephalus sp.	17	pf	s+a	-	+	-	-	-	-
Scapholeberis mucronata (O.F. Müller, 1776)	17	pf	s+a	-	+	-	-	-	-
Anostraca	15	pf	s	+	+	-	+	+	+
Copepoda
Arctodiaptomus bacillifer (Koelbel, 1885)	16	pf	s	-	+	+	-	-	-
A. niehammeri (Mann, 1940)	16	pf	s	-	+	+	-	-	-
Hemidiaptomus rylovi Charin, 1928	15	pf	s	-	+	-	-	-	-
Metadiaptomus asiaticus (Uljanin, 1875)	16	pf	s	-	+	+	+	+	+
Mixodiaptomus incrassatus (Sars, 1903)	16	pf	s	+	+	-	-	-	-
Eucyclops serrulatus (Fischer, 1851)	5	g	s+c	+	+	-	-	-	-
E. (Speratocyclops) arcanus Alekseev, 1990	5	g	s+c	-	+	-	-	-	-
Microcyclops varicans (Sars, 1863)	5	g	s+c	-	+	-	-	-	-
Thermocyclops dybowskii (Lande, 1890)	3	c	s	+	+	+	-	-	-
Cyclopoida (juvenile)	6	c+pf	s	+	+	-	+	+	-

Table 6 The dominant species composition of zooplankton at various lake types in summer 2021–2023

Lake type	Salinity group	Zooplankton (in descending order)
Na-HCO₃	oligohaline	M. incrassatus, Cyclopoida
Soda-type I subtype (Na-HCO₃-CO₃)	oligohaline	T. dybowskii, H. mira
	mesohaline	M. asiaticus, M. brachiata
	hyperhaline	B. plicatilis
Soda-type II subtype (Na-SO₄)	oligohaline	T. dybowskii, M. brachiata
Soda-type II subtype (Na-SO₄)	mesohaline	B. plicatilis, T. dybowskii
Soda-type III subtype (Na-Cl)	mesohaline	M. asiaticus, M. brachiata
	polyhaline	B. plicatilis
	euhaline	B. plicatilis
	hyperhaline	Anostraca
Chloride-type (Na-Сl)	mesohaline	M. brachiata, M. asiaticus
	euhaline	B. plicatilis
	hyperhaline	B. plicatilis, Anostraca
Sulphate-type (Na-SO₄)	polyhaline	M. asiaticus, M. brachiata
Sulphate-type (Na-SO₄)	hyperhaline	B. plicatilis

Table 7 Average values (mean±SD) of biomass (B, kcal/m³), production (P, kcal/m³day), expenditures for metabolism (R, kcal/m³day), and ration (C, kcal/m³day) of zooplankton trophic groups at various lake types in summer 2021–2023

Chemical type	Trophic group	B	P	R	C
Na-HCO₃	nonpredatory	14.03±4.93	1.65±1.03	5.80±2.44	7.54±4.65
	omnivorous	0.16±0.23	0.01±0.02	0.01±0.01	0.06±0.09
	predatory	0.04±0.06	0.003±0.006	0.06±0.10	0.02±0.03
Soda-type, I subtype (Na-HCO₃-CO₃)	nonpredatory	17.24±34.63	1.78±2.85	8.25±17.43	8.10±12.96
	omnivorous	0.03±0.44	0.01±0.02	0.02±0.02	0.01±0.02
	predatory	0.65±1.73	0.05±0.12	0.17±0.48	0.30±0.77
Soda-type, II subtype (Na-SO₄)	nonpredatory	10.91±11.67	2.27±2.46	5.56±6.18	10.34±11.21
	omnivorous	0.57±0.55	0.05±0.05	0.272±0.28	0.23±0.23
	predatory	0.94±1.05	0.08±0.09	0.23±0.27	0.50±0.56
Soda-type, III subtype (Na-Cl)	nonpredatory	105.04±142.69	16.74±24.25	44.34±60.54	76.09±110.20
	omnivorous	0	0	0	0
	predatory	0	0	0	0
Chloride-type (Na-Сl)	nonpredatory	8.96±9.69	1.81±1.82	4.14±4.13	8.24±8.26
	omnivorous	0.01±0.04	0.001±0.003	0.005±0.02	0.005±0.02
	predatory	0	0	0	0
Sulphate-type (Na-SO₄)	nonpredatory	50.20±34.36	9.35±10.80	22.43±25.18	42.51±49.10
	omnivorous	0	0	0	0
	predatory	0	0	0	0

Table 8 Seasonal changes of zooplankton diversity and structure (min–max/mean±SD) in 2021–2023

	Spring	Summer	Autumn
Na-HCO₃
Species number	4	5–6	4–6
Abundance, ×10³ ind./m³	43.28	91.94–235.42/163.68±101.46	43.75–111.06/77.40±47.60
Biomass, g/m³	0.30	16.17–26.40/21.28±7.23	5.45–17.44/11.45±8.49
Dominant taxa	Anostraca (metanauplii), Calanoida (nauplii)	M. incrassatus, Cyclopoida (copepodita)	M. incrassatus
Soda-type I subtype
Species number	1–6	1–13	3–13
Abundance, ×10³ ind./m³	0.25–44.96/11.13±19.22	5.02–1459.60/392.78±573.79	17.88–983.14/220.05±376.1
Biomass, g/m³	0.03–3.12/13.17±17.17	0.01–91.55/16.61±25.15	2.55–181.75/37.46±71.12
Dominant species	Synchaeta sp., H. mira, E. najas, A. ecaudis, A. bacillifer, E. arcanus	H. mira, A. bacillifer, M. incrassatus, T. dybowskii, M. asiaticus	N. acuminata, A. bacillifer, M. incrassatus, M. asiaticus
Soda-type III subtype
Species number	1–2	2–3	2–4
Abundance, ×10³ ind./m³	0.04–0.20/0.12±0.11	445.71–2000.14/1045.5±704.83	154.51–820.1/394.8±369.34
Biomass, g/m³	0.00–0.01/0.05±0.07	31.58–181.725/80.73±70.45	1.95–170.23/68.40±89.54
Dominant taxa	Cephalodella. sp., Daphnia sp.	M. brachiata, M. asiaticus	H. mira, B. plicatilis, M. asiaticus

No competing interests reported.

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Saline lakes of Transbaikalia (Russia): Limnology and diversity of plankton communities

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Abstract

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Introduction

Materials and methods

Study area

Water sampling and analysis

Phytoplankton and zooplankton surveys

Data and statistical analyses

Results

Discussion

Declarations

References

Tables

Additional Declarations

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