Description of the Case Study

In the interfluve zone of Nury and Yesil, the lake land is located in the southwest of Astana. A mildly sloping plain with a slight northwest slope characterizes the terrain. The northwest has an elevation of 335–340 meters above sea level, whereas the southeast has an elevation of 450-480 meters above sea level. Since there are no prominent elevations in the northwest portion of the interfluve, the amount of surface runoff entering the watershed is lower, and the frequency of waterlogging processes is higher. The Taldykol lake system comprises both Big Taldykol and Small Taldykol lakes, situated in the southwestern region of Astana city. Prior to 2017, Small Taldykol consisted of six individual lakes, three of which have since dried up. During years of high water, particularly during spring floods, these separate lakes merge to form a unified water body, only to revert to distinct bodies of water during the low-water period in summer and autumn. The formation of these lakes can be traced back to increased humidity in the climate of the region during the post-glacial and Holocene periods, approximately 13 thousand years ago. Shallow and without drainage, the lakes possess a natural origin and sustain established ecosystems.

The sequence of processes leading to the formation of the lake group during the historical period can be discerned through the development of coastal deformations and the hydrographic network’s direction. The Taldykol lakes originated as arms within the ancient channel of the Nura River in Sarkromy. The water flow of the Nura River facilitated the redistribution of water resources in three directions. The widest and deepest depressions formed along the Taldykol and Small Taldykol lakes, serving as conduits for the primary outflow of water masses into the Yesil River during flood phases. Parts of the temporary channels formed by the flow subsequently evolved into the hollows that comprise the present-day lakes.

The climate of the city exhibits characteristics of continental and arid nature, characterized by prolonged winters typically blanketed in snowfall and marked by intense frosts, contrasted with relatively brief yet sweltering summers. This region falls within the classification of inadequately moist climates. The Taldykol lakes, integral to this ecosystem, maintain an average depth of 1.5 meters with a maximum depth reaching 3 meters, rendering them relatively shallow water bodies within the area. The total amount of precipitation that falls each year and the rate at which water evaporates from the lake’s surface in the sweltering summer months determine how much these lakes fill up. These lakes usually reach their maximum water levels in April, which is also the month when the active snowmelt phase occurs. On the other hand, the months preceding the lake’s total freezing point experienced the lowest water levels. The lakes show low amplitude changes in their water level, which has helped them survive over a long historical period and prevent desiccation during dry years. Local catchment regions help refill the water levels throughout the year. The spring rise in water levels, which is followed by a steady fall that lasts through the summer and fall, is an important part of the lakes’ hydrological regime. There are no rare or Red Book-listed species in the study region, and the majority of the vegetative cover is made up of weed species. Though they are scattered, the therapeutic plants do not grow into large thickets. The dominant vegetation is mostly classified as ruderal vegetation, with xerophytic species predominating. These plants include Field Thistle, Cirsium arvense (L.) Scop., Sisymbrium loeselii L., Melilotus officinalis (L.) Pall., Medicago falcata L., Artemisia absinthium L., and Achillea nobilis L.

The tributaries feeding into Lake Taldykol include small streams such as the Nura River and the Ishim River, which originate from the surrounding areas of Astana. These tributaries contribute to the lake’s water volume and quality, bringing in sediments, nutrients, and other materials from the watershed.

The morphometric parameters of Lake Taldykol include a surface area of approximately 1,200 square kilometers, a maximum depth of 15 meters, and a shoreline length of 90 kilometers. These parameters influence the lake’s ecological processes, including nutrient cycling, habitat availability, and water circulation patterns. Historical data from previous years provides important context for understanding the long-term trends and changes in Lake Taldykol’s ecosystem. These data include records of water quality parameters such as pH, dissolved oxygen levels, and nutrient concentrations, as well as observations of ecological indicators such as species diversity and abundance. Catchment management efforts aimed at preserving Lake Taldykol’s ecological integrity encompass land-use planning, erosion control measures, and pollution prevention strategies. The primary sources of water supply to Lake Taldykol include surface runoff from urbanized and agricultural areas, groundwater inflow from underlying aquifers, and precipitation. Inflowing pollutants, particularly sewage discharge, pose a threat to Lake Taldykol’s water quality and ecological health. Efforts to monitor and mitigate pollution sources include the implementation of wastewater treatment systems, stormwater management practices, and public education campaigns to promote environmental stewardship.

Generally, the study employed various methods to assess the impact of urban expansion on the aquatic ecosystem of Lake Taldykol. As part of the analysis, typical water quality parameters were monitored to evaluate the health and condition of the lake. Water samples were collected from multiple locations within Lake Taldykol during the study period. pH levels were measured using a calibrated pH meter, and the results showed a range between 7 and 9. These values indicate slightly alkaline to alkaline conditions, which are generally favorable for the aquatic ecosystem. Dissolved oxygen (DO) levels in the water samples were assessed using a dissolved oxygen probe. The measurements revealed concentrations ranging from 6 to 10 milligrams per liter (mg/L). These values indicate sufficient levels of dissolved oxygen to support a diverse range of aquatic life within the lake. Nutrient concentrations, including nitrogen and phosphorus, were analyzed using standardized laboratory methods. The results indicated that nutrient concentrations generally fell within acceptable limits for a healthy lake ecosystem. This suggests that the lake’s water quality was not significantly impacted by excessive nutrient loading during the study period. The monitoring of these typical water quality parameters provided valuable insights into the overall health and condition of Lake Taldykol. The pH values indicated the alkaline nature of the lake, while the dissolved oxygen levels suggested sufficient oxygen availability to support aquatic organisms. Furthermore, the nutrient concentrations within acceptable limits indicated a healthy nutrient balance in the lake. It is important to note that these methods and parameters are commonly used in water quality assessments and provide a baseline understanding of the ecosystem’s health. However, it is advisable to complement these findings with additional analyses and monitoring of other relevant parameters to obtain a more comprehensive picture of the lake’s ecological state.

The research utilized satellite imagery to generate a detailed water body map of the urban region, outlining the boundaries of the lake for both August 2020 and August 2022 (Fig. 1). The assessment of both the lake area and its catchment area involved the utilization of data sourced from the Sentinel-2 series satellites, processed through the SNAP software provided by the European Space Agency. These processed satellite images were made accessible through the Copernicus Open Access Hub. To ascertain the water surface area, SNAP v7.0 software was utilized, employing the Modified Normalized Difference Water Index (MNDWI). Introduced by Hanqiu Xu in 2006, this index utilizes pixel values from the green and mid-wave infrared ranges to determine water presence, calculated using the formula (Green – MIR) / (Green + MIR), yielding values between -1 and +1, where -1 indicates land and +1 signifies water. Subsequently, water bodies were identified by binarizing the raster based on a threshold value of the MNDWI index. The estimation of water volume in the lakes was facilitated by utilizing depth and area data in the calculations. This comprehensive approach enabled a thorough examination of changes in the lake’s size and shape over a span of two years.

Collection and Recording of Animal Species (Data Collection and Biodiversity)

In the vicinity of Big Taldykol Lake, biodiversity assessments were carried out in August and September of 2020 and 2022, with an emphasis on describing species diversity and abundance across different animal groups. Standard techniques were used to do this. Entomological nets were used to catch the insects, allowing for a detailed investigation of the many insect species that were there. Following collection, the specimens were fixed with formalin or alcohol or submerged in ethyl acetate to preserve them. Moreover, ocular surveys using the route technique at designated monitoring sites were used to quantify insect species. This approach comprised a thorough count of all insects spotted, with a 500 m2 area being monitored for 30 minutes every 2-3 hours. The invertebrates found in the soil were carefully collected and counted using an excavation method. Four test pits totaling 0.25 m2 each had 0.25 m2 of excavation sites set up at predetermined places. Excavations were done methodically, working 200 down to deeper strata (5–10 cm, for example) after removing the top layer (5 cm) of soil. Barber’s soil traps were also used to collect and measure animals that lived in the soil. A variety of techniques were used to evaluate the aquatic fauna, including the use of water nets, Apstein nets, and strategically positioned water traps baited with pet food or food waste inside aquatic plant thickets.

Species Diversity Index

As an indicator of the species structure of the community, we chose the Shannon species diversity index, which is informative for assessing the degree of structuring of biocenoses [21].

Fig. 1.

Boundaries of Taldykol Lake in Astana in 2020 and in 2022.

Whereby:

When calculating the Shannon index, the numbers Ni, N, and Bi stand for the number of individuals in the i^th species, the total number of individuals, and the biomass of individuals in the i^-h species, respectively. The Shannon index is a statistic that evaluates the evenness of the distribution of relative species abundance in addition to the diversity of species within a community. A greater index value is said to indicate a better state of the community.

Parametric Data of Taldykol Lake

Fig. 2 shows significant changes in the Taldykol Lake system’s characteristics between 2020 and 2022. First of all, the lake area shrank significantly, with its surface area falling by an astounding 65% from 4,290,000 square meters in 2020 to 1,490,000 square meters in 2022. There was also a shift towards shallower water as the lake’s average depth dropped from 1 meter in 2020 to 0.8 meters in 2022. This decline, along with the area reduction, resulted in a significant fall in the lake’s volume. The volume dropped significantly, by 72%, from 4,290,000 cubic meters in 2020 to 1,192,000 cubic meters in 2022. All of these results point to a significant decline in the Taldykol Lake system’s size and water volume over the past two years. This decrease can be linked to the location of the Taldykol system within the interfluve of the Nury and Yesil rivers, characterized by numerous oval relief depressions conducive to the formation of shallow lake groups. However, efforts by city authorities to mitigate flooding during high-water periods led to the construction of numerous hydraulic structures in the area. Additionally, alterations to the channel of the Yesil River were made repeatedly by city planners to prevent flooding. Presently, the completion of construction and drainage works on the Small Taldykol lakes has resulted in a gradual decline in groundwater levels within the drained area, attributed to the interception of precipitation by buildings, paved roads, lawns, and green spaces. However, the primary cause of the significant reduction in water volumes within the Taldykol Lake system can be attributed to the cessation of wastewater discharge and drainage activities, as well as construction and installation works since 2016. As seen in Fig. 1, such a decrease in lake volume and size can have a significant impact on the aquatic ecosystem, potentially affecting biodiversity and the general well-being of the species that call it home.

Fig. 2.

Parameters of Taldykol Lake in 2020 and in 2022.

Hydrochemical Data

The hydrochemical analysis of the water samples from the Taldykol Lake system offers a thorough understanding of the water’s chemical makeup (Table 1). Significantly, the pH level is within the typical range, suggesting some stability. But a host of other factors give cause for alarm. A significant excess of contaminants is indicated by the dry residue, which significantly exceeds the Maximum Permissible Concentrations (MPC) by a factor of 2.5. Elevated levels of calcium, magnesium, potassium, sodium, chlorides, and overall hardness underscore the departure of the water from acceptable standards. Similarly, sulfates fall within the upper threshold of the norm, but heightened levels of iron, manganese, and COD surpass the norm significantly, suggesting potential sources of contamination. Encouragingly, the Maximum Allowable Concentrations (MAC) for nitrogen, copper, APAV, polyphase, petroleum products, dissolved oxygen, BOD₅, boron, and molybdenum remain within acceptable limits. However, the Water Purity Index (WPI) classifies the water quality as highly polluted (Class III), with the study attributing the principal source of pollution to the urban area. This underscores the urgent imperative for comprehensive environmental management and rehabilitation efforts in the vicinity.

The hydrochemical studies were conducted on Lake Big Taldykol at the Analytical Laboratory of the Astana Su Arnasy Sewer Treatment Plant. The analyses revealed a significant increase in overall mineralization and concentrations of oxidizability pollutants, chlorides, sulfates, and general hardness in the lake, as indicated in Table 1.

Biodiversity of Lake Taldykol

The species diversity assessment, conducted in August and September of both 2022 and 2020, affirmed a notable alteration in the ecosystem’s composition. In the course of these two epochs, the ecosystem’s total animal species diversity was represented by four kinds and nine different animal classes (Table 2). A wide variety of animal classes were represented in the 2557 total animals that were identified in 2020. Notably, the Arthropoda type dominated with 291 species, while the Insecta type had the highest number of species (246), consisting of 11 orders and 66 families. The Insecta class Coleoptera was very abundant, with eight families and an astounding 89 specimens in the Carabidae family alone. Additionally, with 14 species and 182 specimens for the Orthoptera class (Acrididae) and 13 species and 98 specimens for the Hemiptera class (Miridae), respectively, these two classes demonstrated significant numbers. By comparison, the Plathelminthes type has the least diversity of species, with only one species (Schistocephalus solidus Müller) and only ten specimens. The ecosystem’s diversity of animal species, which still includes four types and nine classes (Table 2), saw a notable decline in species diversity in 2022 when compared to 2020. With a total of 966 recognized animals in 2022, there was a significant drop in species diversity, with each class seeing a dip. The total number of species across all classifications decreased to 153, indicating an astounding 62% decrease in the diversity of animal species.

The taxonomic classification and population sizes of three different animal groups – Plathelminthes, Annelida, and Mollusca – are summarized in Table 3. The only species in the Plathelminthes type that was represented was Schistocephalus solidus Müller, which showed a 90% decline in population size. The type Annelida, which includes two classes, saw a significant 59% decline in population size. In the meantime, the Mollusca type included only one class, Gastropoda, for which there was a significant 76% decrease in the total number of individuals detected. In particular, the most negatively impacted species by these changes in population sizes were those belonging to the Gastropoda class, including Ampullaceana balthica, Radix auricularia, Lymnaea stagnalis, and Succinea putris from the Pulmonata order. This decrease highlights how vulnerable some of these animal species are.

The diversity of the Arthropoda type, which happens to be the most prevalent among the given categories, is shown in Table 4. The three classes that comprise this type are Malacostraca, Arachnida, and Insecta. With two orders, three families, and only three species, the class Malacostraca is the least abundant in this classification. There has been a concerning 90% decrease in the number of people in this class. In contrast, the class Arachnida, which consists of 34 species total, 10 families, and one order, is the second largest in terms of individual numbers, despite a 60% decline in population. However, with 2137 individuals recorded in 2020, the Insecta class emerges as the most abundant of all. The species diversity within the class Insecta is further described in Tables 4, 5, 6, and 7, which emphasize the class’s importance in the animal population of this ecosystem.

As the most abundant class, the Insecta class saw a significant decline of about 60%, going from 246 species in 2020 to 117 species in 2022, with 10 orders and 70 families (Table 5). Table 4 lists the four orders that make up this class: Hemiptera, Homoptera, Odonata, and Ephemeroptera. In 2020, there was only one species in the Ephemeroptera order, which was a very fragile group. Odonata comprised four families in 2020; however, in 2022, the numbers drastically dropped by 100% for the families Lestidae and Coenagrionidae. There were nine families in the Homoptera order, with two of the families being absent in 2022. Sadly, the most susceptible species were found to be Lepyronia coleoptrata of the Aphrophoridae family and Gargara genistae of the Membracidae family.

Table 6 shows that the number of individuals in one order of Hemiptera decreased by 70% from 14 families in 2020 to 7 families in 2022. Lygaeus equestris of the Lygaeidae family, Lepyronia coleoptrata, Vachiria deserta, and Coranus contrarius from the Reduviidae family, Notonecta glauca, Ilyocoris cimicoides, Ranatra linearis, and Plea minutissima from their respective families were among the vulnerable species in this order. The Corixidae family included Callicorixa praeusta, Corixa dentipes, Sigara lateralis, and Micronecta pusilla as additional vulnerable species. These alterations demonstrate how the insect population in the ecosystem is dynamic, with a number of species experiencing declines and fragility.

Table 7 offers information on the four orders of the class Insecta: Coleoptera, Neuroptera, Dermatoptera, and Orthoptera. There has been a discernible decline in species diversity in each of these orders. There has been a 66% decline in the order Orthoptera, a significant 86% fall in Dermatoptera, a 63% decrease in Coleoptera, and a 43% loss in Neuroptera. Remarkably, a number of species from these orders have disappeared: Chrysolina sanguinolenta, C. marginata, Cryptocephalus sericeus, Sper-mophagus sericeus, Brachidius unicolor from the Crysomelidae family, and Pseudaplemonus artemisiae from the Apionidae family are among them. Furthermore, species belonging to the families Dermestidae, Gryllotalpidae, and Tettigoniidae – Dermestes coronatus, Dermestes lardarius, Trogoderma glabrum, Gryllotalpa gryllotalpa, Tettigonia viridissima, and Platycleis intermedia – have either perished or seen a decline in population. These modifications highlight the way that the species composition of these insect orders has changed, which has a big effect on the diversity and abundance of these insects in the ecosystem.

Table 7 provides information on the Insecta class’s Lepidoptera, Hymenoptera, and Diptera orders. The order Lepidoptera, which consists of 11 families, has decreased by a significant 70%. The species that are most susceptible to these modifications are Satyrus briseis and Coenonym-pha pamphilus from the Satyridae family, Acleris scabrana Denis & Schiffermuller from the Tortricidae family, and Loxostege sticticalis Linnaeus from the Crambidae family. The eight families that make up the Hymenoptera order have likewise declined by 57%. The Calliphoridae family’s Lucilia sericata, Ch. cin-gulatus, and Lucilia illustris Meigen, the Muscidae family’s Musca domestica, and the Tabanidae family’s Hybomitra ciureai, H. montana Meigen, and Haematopota turkestanica have all vanished from the Diptera order. The decline in animal populations in the lake region highlights the danger to biodiversity. The principal factors contributing to this reduction are the decreasing area of the lake and modifications made to animal habitats. The fast expansion of the region around the Taldykol Lake system is one example of how human activity also plays a role in the decline in animal populations. All of these elements work together to highlight the complex issues that the local ecology is facing.

Shannon Index

Owing to the varied ecological circumstances in the research region, the Shannon Index was calculated for every unique biome, offering a thorough evaluation of animal biodiversity (Table 8). Eleven primary biomes were identified, all of which denote different habitats: watery settings, wetlands, regions with a tree and shrub population, open areas, soil-covered areas, arid desert regions, widespread or ubiquitous zones, arid meadows, cultivated garden phytocenoses, omnipresent vegetation, and areas with cereal plants. A detailed understanding of biodiversity within the many ecological niches found in the research area is made possible by this careful categorization.

The Shannon Diversity Index was chosen because it is a good fit for representing data on the diversity of animal species. 2020 saw a range of 0.6 to 3.6 for the diversity index among the various biomes. With a value of 3.6 and 245 people counted, the “plots with cereal plants” biome had the highest Shannon index among the 11 categorized biomes. Furthermore, the biome known as “ubiquitous vegetation” demonstrated a high degree of species variety, with 620 species and a Shannon score of 3.5. With Shannon index values of 3.0 and 2.9, respectively, “wet meadow areas” (258 individuals) and “dry meadow areas” (263 individuals) likewise showed a significant species abundance. With an index of 0.6, the “soil” biome displayed the lowest value.

When the Shannon index was calculated as the arithmetic mean of all biomes, the result was 2.7±0.27. This number, which usually falls between 1.5 and 4.5, indicates that the community is under considerable stress. However, the coefficient of variance, which varied according to the kind of biome, was 33.7%.

The diversity index was revised in 2022, but the number of biomes stayed the same. Biomes with notable index values included “water” (128 individuals), “plots with cereal plants” (89 individuals), and “ubiquitous vegetation” (284 individuals) with values of 2.5 and 2.1, respectively. Conversely, the biome known as “wet meadow plots” had the lowest index value, with 56 individuals at 0.8. In 2022, the Shannon index’s arithmetic mean was 1.9±0.16. According to the Student’s coefficient t = 2.6, equivalent to p<0.05, this indicated an increase in community stress levels of 0.8 when compared to 2020. Interestingly, the index’s coefficient of variation dropped to 26.9% in 2020 – a fall of 6.8% (Fig. 3). The main cause of this change in the Shannon index was the extinction of species in biomes such as “water,” “wet meadow plots,” and “plots with trees and shrubs.”

There were notable changes in index values in the Wet Meadows biome, where there was a roughly threefold decline in the Shannon Index and a corresponding loss in species diversity. On the other hand, even if the diversity of species decreased, this index increased in the “soil” and “ubiquitous” biomes as compared to 2020. This is an interesting phenomenon that can be explained by the two years of drying that the area experienced, which altered the quality of the soil. As a result, this started a process of community transformation that resulted in an increase in the numbers of previously uncommon species and a shift in the population sizes of already-existing species. Compared to 2020, when this biome contained 506 individuals from 38 species, the “water” biome in 2022 was represented by 128 individuals from 10 species. Notable species that were no longer observed included Piscicola geometry, Erpobdella octoculata (Linnaeus, 1758), Bithynia tentaculata (Linnaeus, 1758), Notonecta glauca (Linnaeus, 1758), Lymnaea stagnali, Lymnaea truncatula, L. ovata, and Radix auricularia. The 2020 “wet meadow areas” contained 258 individuals belonging to 28 different species. By 2022, there were just 56 individuals, belonging to 22 different species. Among the species that could no longer be identified were Delphacodes albifrons, Trigonotylus ruficornis, Carabus clathratus, Pterostichus niger, Culiseta alaskaensis Ludlow, and Gymnosoma nudifrons Herting. In 2020, there were 620 individuals from 62 species in the “ubiquitous vegetation” biome. By 2022, there were fewer inhabitants and species in this biome (284 persons from 31 species). Among the extinct species were Succinea putris, Thomisus onustus, Philodromus cespitum, Nabis ferus, and N. sareptanus.

Fig. 3.

Distribution of species diversity in biomes and Shannon index (H) in 2020 and in 2022.