Search Results (298)

The Yellow River Basin (YRB) serves as a vital ecological security barrier in northern China, and the stability of its ecosystems and the dynamics of its vegetation productivity have significant implications for national ecological strategies and regional sustainable development. This study utilized net primary productivity (NPP) and precipitation data, employing a linear regression method with a 7 × 7 pixel grid and a 4-year spatiotemporal window to quantify vegetation precipitation sensitivity (VPS) in the YRB from 2000 to 2020. Principal component regression was used to assess the relative contributions of environmental and anthropogenic factors to the interannual variability and long-term trends of VPS. The results indicate that during the 2000–2020 period, 19.27% of the YRB experienced significant changes in VPS, with the area showing a decrease (14.99%) far exceeding that showing an increase (4.28%). The downward trend was most pronounced in the midstream (24.2%). Spatially, VPS exhibited a distinct pattern of negative values in the south and positive values in the north, with 36° N serving as the boundary. Among vegetation types, desert vegetation exhibited the highest VPS, while forests and shrubs exhibited the lowest. GDP and temperature were identified as key factors influencing VPS changes. It should be noted that GDP, as a proxy for human activity, has certain limitations; future studies should incorporate more direct indicators of human activity for further validation. This study clarifies the spatiotemporal characteristics and key drivers of VPS in the YRB, providing a scientific basis for regional ecological conservation. Full article

Grassland lake basins are mostly located in arid and semi-arid regions and represent typical ecologically fragile zones. As a representative inland lake in the cold and arid region of northern China, Hulun Lake serves as a crucial node for maintaining the ecological balance of the Hulunbuir grassland. Studying its ecological carrying capacity is particularly key to implementing the philosophy of a holistic approach to the management of mountains, rivers, forests, farmlands, lakes, grasslands, and deserts. Based on data from 2018 to 2024 across four cities (banners, districts) in the Hulun Lake basin, this study constructs an evaluation system to measure ecological carrying capacity across three dimensions—ecosystem support, human activity pressure, and socio-economic response—using the Pressure–State–Response (PSR) model. Spatial analysis and geodetector methods are employed to explore its spatiotemporal differentiation and influencing factors. The findings are as follows: (1) The ecological carrying capacity in the Hulun Lake basin exhibits a significant spatial differentiation pattern, characterized by a gradient of “high in the east, low in the west; high in pastoral areas, low in urban areas.” (2) The overall trend in ecological carrying capacity shows a slow increase amid fluctuations, but the carrying capacity level remains relatively low. (3) The core driving forces of ecological carrying capacity primarily stem from the dimensions of population quality and infrastructure, while the direct influence of agricultural production is relatively limited. (4) Transportation infrastructure plays a strongly influential role as a driving mechanism of ecological carrying capacity in the Hulun Lake basin. Its synergy with factors such as education, information, and industry significantly affects both the ecosystem support capacity and the socio-economic responses of the basin. This study provides a reference for ensuring the ecological security of the Hulun Lake basin. Full article

The administrative boundaries of ecosystems do not necessarily align with natural watershed boundaries, which is a significant reason for the current inefficiency and pronounced conflicts in ecological governance. Using the watershed as the fundamental unit, this study assessed the forest ecosystem services (FES) of the Beihai Wetland watershed in Tengchong (As of 2025). Forest vegetation was classified to the formation level, and the functional value method was employed. The results showed the following order of service values: regulating services > provisioning services > supporting services > cultural services. Biodiversity was identified as the most valuable ecosystem function. The study further revealed that factors such as stand type, stand age, and altitude influence the total FES value within the watershed. Analysis of FES per unit stand (1 ha) indicated that Lithocarpus variolosus Franch. Chun (natural forest) exhibited the highest value. Through in-depth analysis of linear correlations and spatial associations of FES per unit stand, a synergy-trade-off visualization was constructed. This revealed that natural forests in the upper watershed may exert systemic effects on nutrient cycling in the lower watershed. The results obtained at the formation level provide support for the development of watershed-based forest tending plans. Moreover, studying FES using the watershed as a unit represents a practical exploration of the “life community of mountains, rivers, forests, farmlands, lakes, grasslands, and deserts” and offers a potential reference for maintaining the ecological security and supporting the ecological protection and restoration of the Beihai watershed. Full article

Morphological traits, as core components of functional traits, are fundamental in determining environmental adaptability. However, under climate warming, the adaptive morphological changes and associated ecological risks of locust populations migrating to higher altitudes remain poorly understood. Here, we investigated Calliptamus italicus, the dominant locust species in the desert steppes of the Ili River Basin, to explore the response patterns of its morphological functional traits along an altitudinal gradient and their relationships with environmental factors. Morphological measurements revealed that forewing area, width, and length, as well as hindwing width, exhibited highly significant positive correlations with altitude (p < 0.01); in contrast, body length, head width, head height, pronotum length, pronotum width, hind femur length, and hind tibia length displayed significant negative correlations with altitude (p < 0.05). All morphological indicators presented highly significant sexual dimorphism (p < 0.001). Ratio analysis showed that the pronotum width-to-head width ratio (M/C), pronotum height-to-head width ratio (H/C), and forewing length-to-hind tibia length ratio (E/F) were significantly positively correlated with the altitudinal gradient (p < 0.05), with all ratios exhibiting significant sexual differences (p < 0.05). Random Forest analysis showed that PC1 (75.5% of variation) reflected traits for feeding, jumping, and reproduction, whereas PC2 (5.6%) represented flight-related traits, with significant sexual dimorphism. This study demonstrates that trait variation in C. italicus along an altitudinal gradient is closely linked to environmental factors. Our findings provide critical data for predicting habitat adaptation responses in locust populations, thereby enhancing the precision and efficacy of locust plague management and contributing to the conservation and restoration of desert steppe ecosystems. Full article

Desertsand concrete (DSC) is a sustainable alternative to natural river sand; however, its application in cold regions is restricted by inadequate crack resistance and freeze–thaw durability. This study investigates the freeze–thaw performance of steel–polypropylene hybrid fiber-reinforced desert sand concrete (SPHF-DSC), with emphasis on durability enhancement and service life prediction. A three-factor, three-level orthogonal experimental design was employed to evaluate the effects of desert sand replacement ratio (DSR), steel fiber (SF) content, and polypropylene fiber (PPF) content on mass loss, relative dynamic elastic modulus, and compressive strength under 25–100 freeze–thaw cycles. The results demonstrate that hybrid fiber reinforcement significantly improves freeze–thaw resistance due to the synergistic interaction between SF and PPF. After 100 cycles, the mass loss of all specimens remained within a narrow range of 0.65% to 0.73%, and the relative dynamic elastic modulus retention stayed above 90%. The optimal mixture (DSR = 30%, SF = 2%, PPF = 0.05%) exhibited superior frost resistance with the lowest deterioration indices among all groups. A freeze–thaw damage model based on damage mechanics was established and validated ($R^2$ > 0.96), enabling prediction of a service life exceeding 38 years under typical cold-region climatic conditions. These findings provide a durability-oriented design reference for the engineering application of DSC in cold-region infrastructure. Furthermore, the utilization of local desert sand reduces transportation energy consumption and promotes the sustainable development of energy infrastructure. Full article

Precipitation is a fundamental element in terrestrial water circulation and ecosystem hydrological balance. The occurrence of concentrated precipitation is closely linked to vegetation growth and soil fertility rather than accumulated or averaged precipitation. Despite its importance, the characteristics of continuous precipitation and its specific effects on vegetation cover remain uncertain. In this study, we formulated a new continuous precipitation index system, including $C{P}_d$ (continuous precipitation days); $AC{P}_t$ (annual continuous precipitation times); $C{P}_a$ (continuous precipitation amount); and $FCP$ (frequency in different ranges of $AC{P}_a$). We utilized daily precipitation data from 467 meteorological stations across China, which were divided into eight vegetation type regions. We observed that the spatial distribution of continuous precipitation differed to varying degrees from accumulated precipitation. The national average of $MAC{P}_a$ for a single event was 16.7 mm, ranging from 3.8 mm in the temperate desert region to 37.1 mm in the tropical monsoon forest and rainforest region. Similarly, the national average of $MC{P}_d$ ($MMC{P}_d$) for a single event was approximately 2.3 or 9 days. At the regional level, the tropical monsoon forest and rainforest region experienced the longest $MMC{P}_d$. Furthermore, the national average of $MAC{P}_t$ occurrences for 1 year was 57.7 times, varying from 29.8 times in the temperate desert region to 77.9 times in the tropical monsoon forest and rainforest region. Vegetation responses to precipitation regimes exhibit significant regional heterogeneity across China. Our analysis reveals that $MAC{P}_t$ and $M{P}_a$ show markedly positive correlations with vegetation growth. In subtropical monsoon climate zones, particularly the Yunnan–Guizhou Plateau and Qinling Mountains, $MAC{P}_t$ demonstrates strong positive correlations (r = 0.6–1.0) with NDVI, where sustained rainfall provides stable moisture availability for vegetation. While a positive correlation between vegetation (NDVI) and mean annual consecutive precipitation is observed in some arid northern regions, in ecosystems such as the Loess Plateau (TG/TM), vegetation growth shows greater dependence on $M{P}_a$, highlighting the crucial role of total precipitation amount in water-limited ecosystems. Notably, extreme precipitation events display dual effects on vegetation dynamics. Prolonged heavy rainfall ($MMC{P}_d$/$MMC{P}_a$) exhibits significant negative impacts on NDVI (r = −1.0 to −0.6) in topographically complex regions, including the Hengduan Mountains and Yangtze River Basin (SE), likely due to induced soil erosion and waterlogging stress. Our findings underscore the importance of incorporating continuous precipitation indices to evaluate and forecast the influence of precipitation on ecosystem stability. This understanding is vital for developing informed conservation and management strategies to address current and future climate challenges. Full article

Lakes on the Inner Mongolia–Xinjiang Plateau (IMXP) are increasingly vulnerable to eutrophication under climate change and human pressure, yet long-term monitoring remains limited by sparse field sampling. Here, we reconstruct multi-decadal trophic dynamics across the IMXP using Landsat time series and temporally transferable machine-learning models and further quantify the underlying natural and anthropogenic drivers. We compiled monthly in situ water-quality observations (chlorophyll-a, Chl-a; total phosphorus, TP; total nitrogen, TN; Secchi depth, SD; and permanganate index, COD_Mn;) and calculated the trophic level index (TLI). After rigorous quality control and monthly aggregation, we compiled a dataset of 1345 matched lake–month samples spanning 2000–2024, and divided it into a training set (n = 1076; ≤2019) and an independent test set (n = 269; 2020–2024) to evaluate temporal transferability. We utilized Google Earth Engine to generate monthly surface reflectance composites from Landsat 7 ETM+, Landsat 8 OLI, and Landsat 9 OLI-2. Four supervised regression algorithms—ridge regression (RR), support vector regression (SVR), random forest (RF), and eXtreme Gradient Boosting (XGBoost)—were trained to estimate TLI. On the independent test period, XGBoost performed best (R² = 0.780, RMSE = 3.290, MAE = 1.779), followed by RF (R² = 0.770, RMSE = 3.364), SVR (R² = 0.700, RMSE = 3.842), and RR (R² = 0.630, RMSE = 4.267); we then used XGBoost to reconstruct monthly and yearly TLI for 610 perennial grassland lakes from 2000 to 2024. From 2000 to 2024, the annual mean TLI (48–49) across the IMXP exhibited a statistically significant upward trend (slope = 0.0158 TLI yr⁻¹; 95% confidence interval (CI) = 0.0050–0.0267; p = 0.006). Meanwhile, spatial heterogeneity was distinct (TLI: 41.51–59.70). High values concentrated in endorheic and desert–oasis basins (e.g., Eastern Inner Mongolia Plateau, >51), whereas lower values characterized high-altitude regions (e.g., Yarkant River, <45). Overall, trends ranged from −0.49 to 0.51 yr⁻¹, increasing in 54% of lakes (15.6% significantly) and decreasing in 46% (15.4% significantly). Attribution analyses identified NDVI (33.92%) and temperature (21.67%) as dominant drivers (55.59% combined), followed by precipitation (13.99%) and human proxies (30.42% combined: population 10.66%, grazing 10.31%, built-up 9.45%). Across 53 sub-basins, NDVI was the primary driver in 28, followed by temperature (11), population (7), precipitation (3), grazing (3), and built-up land (1); notably, the top two drivers explained 56.6–87.1% of variations. TWFE estimates revealed bidirectional NDVI effects (significant in 31/53): positive associations in 22 basins were linked to nutrient retention, contrasting with negative effects in nine basins associated with agricultural return flows. Temperature effects were significant in 15 basins and predominantly negative (14/15), except for the Qiangtang Plateau. Overall, eutrophication risk across the IMXP lake region reflects the combined influences of climatic conditions, vegetation conditions, and human activities, with their relative contributions varying among basins. Full article

Surface water–groundwater interactions within oasis–desert ecotones of arid regions play a pivotal role in sustaining regional water security and ecological stability. Taking the Niya River Basin in Xinjiang, Northwest China, as a representative inland watershed, this study systematically elucidates the mechanisms and seasonal dynamics of surface water–groundwater coupling under the combined influences of natural processes and anthropogenic activities. A total of 68 surface water and groundwater samples were collected during the dry, normal, and wet hydrological periods. Integrated hydrochemical characterization, mineral saturation index analysis, and stable isotope (δ²H and δ¹⁸O) mass balance modeling were employed to quantify recharge contributions and unravel hydrogeochemical evolution pathways. Results indicate that the waters in the study area are predominantly brackish to saline, with consistent dominant ionic assemblages (SO₄²⁻ and Na⁺) across all hydrological periods, highlighting evaporite dissolution as the primary control on solute composition. Hydrochemical evolution is jointly regulated by evaporation concentration, water–rock interactions, and cation exchange processes. Surface water chemistry reflects the combined effects of silicate weathering and evaporite dissolution, whereas groundwater chemistry is mainly governed by evaporite dissolution coupled with pronounced cation exchange. Stable isotope signatures reveal substantial secondary evaporation of regional precipitation prior to recharge. Frequent bidirectional recharge between surface water and groundwater was observed, exhibiting distinct seasonal transitions. During the dry period, groundwater provides significant baseflow support to surface water (48.6% in the oasis zone and 54.3% in the desert zone). In the normal period, recharge direction reverses, with surface water becoming the dominant source of groundwater recharge (99.0% in the oasis zone and 76.6% in the desert zone). In the wet period, spatial heterogeneity becomes evident: surface water continues to dominate groundwater recharge in the oasis zone (92.7%), whereas groundwater recharge to surface water prevails in the desert zone (50.5%). This study identifies a seasonally dynamic “discharge–infiltration–zonal regulation” bidirectional recharge pattern in arid inland river systems. The findings advance the mechanistic understanding of hydrological connectivity reconstruction within oasis–desert ecotones and provide a scientific basis for optimized regional water resource allocation and groundwater salinization risk mitigation. Full article

Dust and sand storms occurring in northern China are strongly controlled by near-surface aerodynamics, yet the spatial heterogeneity of these processes remains poorly understood. We obtained field measurements of the wind above gobis, sandy surfaces, and dry lakebeds in the Hexi Corridor Desert and Heihe River Basin, and sandy surfaces in northern China. First, the slope of wind profile (a₁) reveals distinct drag reversal with increasing wind speed: under low winds, a₁ increases from sandy to dry lakebed to gobi surfaces, whereas under high winds, actively saltating sandy surfaces exhibit the highest a₁, surpassing gobi and dry lakebed. Second, the dynamic feedback between sediment transport and aerodynamics is clear: at below-threshold winds, friction velocity ($u_{*}$) and aerodynamic roughness length (z₀) are lowest for sand; however, as wind speed increases to initiate significant saltation, the sandy surface develops the highest $u_{*}$ and z₀, highlighting the dominant role of grain-borne roughness. Third, the focal height (z_f) shows regional disparity, varying by up to two orders of magnitude for both sandy and gobi surfaces, with a strong correlation to local gravel coverage. This work provides spatially explicit parameterizations of surface type, offering a physical basis for modeling dust emission and transport in northern China and similar arid regions globally. Such parameterizations are essential for developing reliable early warning systems and evidence-based land management strategies. These advances contribute directly to ecosystem sustainability and community resilience in vulnerable arid and semi-arid regions under climate change. Full article

Populus euphratica is a critical constructive species in arid desert regions, serving as a “natural barrier” for oasis protection. The sustainable management of Populus euphratica forests is directly related to regional ecological security, and the fine identification of sparse Populus euphratica forests is essential for the conservation of natural Populus euphratica forests. Currently, most mapping studies on Populus euphratica distribution focus on the extraction of dense, contiguous Populus euphratica forests, with insufficient attention paid to the identification of sparse Populus euphratica forests. This study utilizes Gaofen-2 (GF-2) satellite imagery as the data source and takes a typical sparse Populus euphratica forests distribution area in the Tarim River Basin as the study site. It systematically evaluates the performance of nine mainstream deep learning models, including U-Net, DeepLabV3+, and SegFormer, in the task of sparse Populus euphratica forests identification. The results indicate that: (1) The false-color sample set, synthesized from near-infrared, red, and green bands, contributes to improved model accuracy. Compared to the true-color (red, green, blue bands) dataset, the average Intersection over Union (IoU) of the nine models shows a relative improvement of approximately 20%. (2) For the sparse Populus euphratica forests identification task based on the false-color dataset, four models—U-Net, U-Net++, MA-Net, and DeepLabV3+—exhibited excellent performance, with IoU exceeding 75%. (3) Using U-Net as the baseline model, this study integrated the max-pooling indices mechanism, atrous spatial pyramid pooling, and residual connection modules to construct a semantic segmentation network tailored for sparse Populus euphratica forests, named Sparse Populus euphratica Segmentation Network (SPS-Net). This model achieved an IoU of 80%, a relative improvement of approximately 6.3% over the baseline model, and demonstrated good stability in large-scale classification tests. The identification scheme for sparse Populus euphratica forests constructed using GF-2 imagery and deep learning models proposed in this study can provide effective technical support for the refined monitoring and protection of natural Populus euphratica forests. Full article

Robinia pseudoacacia is a major tree species for soil and water conservation afforestation in the “Three-North” Region, with crucial ecological improvement and carbon sequestration functions. This study aimed to investigate the dynamics of suitable areas and carbon storage of R. pseudoacacia plantations under different future climate scenarios, further reveal the changing trend of their carbon sequestration potential, and provide a scientific basis for the rational layout and sustainable management of R. pseudoacacia plantations in the “Ω”-shaped bend of the Yellow River. Based on the MaxEnt model, we predicted the potential suitable distribution of R. pseudoacacia under future climate change scenarios, identified the potentially threatened geographical distribution regions and area changes in R. pseudoacacia, and clarified the limiting factors affecting the potential geographical distribution of R. pseudoacacia plantations by analyzing the contribution rates and permutation importance of comprehensive environmental variables. Combined with the InVEST model, we estimated and analyzed the spatial distribution of carbon storage in R. pseudoacacia plantations in the 2090s. The results showed that the minimum temperature of the coldest month was the main environmental factor affecting the distribution of potential suitable areas of R. pseudoacacia plantations, with a contribution rate of 46.98%, followed by annual precipitation. Under current climatic conditions, the potential suitable areas of R. pseudoacacia plantations were mainly distributed in the Loess Plateau, Hetao Plain, Ordos Plateau, Kubuqi Desert, and northern Mu Us Sandy Land. The highly suitable areas were mainly concentrated in the south-central part of the Loess Plateau, accounting for approximately 22.81% of the total area of the “Ω”-shaped bend of the Yellow River. Under future climate change, the moderately and highly suitable areas tended to shift northwestward. Under the four future climate scenarios, the carbon storage and carbon density of R. pseudoacacia plantations showed a trend of first increasing and then decreasing; by 2100, the carbon storage reached the maximum under the SSP370 scenario, and the areas with medium-to-high carbon storage first expanded and then contracted, mainly concentrated in the Ordos Plateau and Loess Plateau. Full article

Populus euphratica (P. euphratica) is a dominant tree species in the arid and semi-arid regions along the main stem of the Tarim River. This study aims to explore the response of microbial communities in the rhizosphere soil of P. euphratica to varying groundwater depths (GWD) and to elucidate the ecological functions of key microbial groups in drought resistance. We established three groundwater depth levels (3.8 m, 5.4 m, and 7.35 m) and employed metagenomic sequencing technology to systematically analyze the topological characteristics of functional microbial community networks, as well as the types and quantities of key microbial groups in the rhizosphere soil of P. euphratica under different GWD conditions. The results indicate that compared to GWDs of 3.8 m and 7.35 m, the average degree and graph density of microbial communities in the rhizosphere soil of P. euphratica at a depth of 5.4 m are the highest. This suggests that at a GWD of 5.4 m, the connectivity and stability of the microbial network structure in the rhizosphere soil of P. euphratica are significantly enhanced. Analysis of the Zi-Pi values within the microbial network structure reveals that, compared to GWDs of 3.8 m and 7.35 m, a depth of 5.4 m supports the greatest variety and quantity of key microbial species in the rhizosphere soil of P. euphratica. The four connecting nodes identified are Actinophytocola, Haladaptatus, Devosia and Pseudonocardia. Spearman correlation analysis demonstrates that the relative abundance of the key bacterial genus Mesorhizobium in the rhizosphere soil of P. euphratica at different GWD is significantly positively correlated with soil catalase (CAT) and urease (UE) activity. Furthermore, the relative abundance of the key bacterial genus Pseudonocardia shows a significant positive correlation with soil total nitrogen (TN) and ammonium nitrogen (NH₄⁺-N) (p < 0.05). The relative abundance of the key bacterial genus Devosia exhibits a highly significant positive correlation with soil water content (SWC) (p < 0.01) and a significant negative correlation with soil NH₄⁺-N (p < 0.05). Additionally, the relative abundance of Devosia is significantly positively correlated with soil CAT (p < 0.05). This study provides a theoretical foundation for the conservation of desert poplar forests in arid regions and for the identification and cultivation of specific key microbial communities in the rhizosphere soil of P. euphratica. Full article

Against global ecological and environmental challenges, water ecological security in arid desert regions is of great significance to regional ecological balance and socio-economic development. This study focuses on the Kashgar Prefecture, specifically the Yarkant River Basin and Kashigaer River Basin, in Xinjiang, China. Employing the perspective of the “Ecology-production-life Space” and the Drive-Pressure-Status-Influence-Respond (DPSIR) model, this study utilizes the objective entropy value method to construct a comprehensive evaluation index system to assess the status of water ecological security and its spatial security in the three regions from 2012 to 2019. The results show that the two major river basins and Kashgar Prefecture present an underbalanced state of production-led ecology, and life space lagging in the Ecology-production-life Space, with different trends and substantial fluctuations in the comprehensive indices of ecology, production, and life of the three. From the DPSIR model, the changes in the indices of the dimensions of the three are complicated, and the response indices are generally low. The composite indices of the two basins and the Kashgar Prefecture are in fair condition, which is affected by the synergistic influence of human activities and natural factors. The production pressure threatens the safety of water ecology, while the ecological protection has a certain degree of effectiveness, but still needs to be improved overall. The rate of improvement is slow due to the limitations of production-led and ecological lag in the future, although there is an upward trend. This study establishes a coupled, complementary assessment framework integrating spatial patterns and causal chains. It validates an evaluation model applicable to discontinuous multi-basin networks in an arid desert region, revealing the evolution patterns and core contradictions of water ecological security in arid multi-basin areas. The results of this study can provide a scientific basis and data support for the study of water ecological security in arid desert multi-basin watersheds. Full article

Desert oases and river systems are complex and dynamic ecosystems featuring unique hydrological patterns. The system significantly influences the production, degradation, and transformation of dissolved organic matter (DOM), thereby further regulating DOM in the desert oasis. However, the molecular composition and significance of DOM in rivers within desert oases are rarely studied. In this paper, the optical properties and spatial variation in molecular characteristics of surface water DOM in the Aksu River were investigated using three-dimensional fluorescence spectroscopy (3D-EEM) and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). The results indicated that the rivers possess distinct molecular compositional characteristics of DOM, with high spatial heterogeneity (variations in optical parameters and molecular compounds). Diversity in DOM is revealed at the molecular level primarily through S- and N-containing functional groups. Unlike large rivers (e.g., the Yangtze) dominated by terrestrial inputs or algal blooms, our study reveals that the DOM in the Aksu River (a desert-oasis river) is characterized by highly unsaturated and phenolic compounds and is primarily driven by intense photodegradation and evaporation rather than by microbial or terrestrial allochthonous inputs. This highlights a distinct photochemical signature unique to arid river systems. The findings will deepen the understanding of the DOM in desert-oasis river systems. Based on this research, seasonal variation in DOM in the Aksu River under different hydrological conditions can be further studied, thereby enriching the understanding of the carbon cycle in desert-oasis river systems. Full article

Freshwater ecosystems in arid and semi-arid zones of the East European Plain are characterized by severe habitat degradation, which negatively impacts their biodiversity. This study attempts to comprehensively examine the species richness of molluscs and determine the influence of abiotic factors on their spatial distribution using the example of one of the river basins in southern Eastern Europe—the Yeruslan River basin (a tributary of the Volga River). Fifteen watercourses in the Yeruslan basin were surveyed, with 72 samples collected from the littoral and deepwater zones. A total of 28 mollusc species were identified in the samples, predominantly those with broad ranges (Holarctic, Palearctic, and Euro-Siberian). Estimating true species richness using nonparametric methods revealed that the collected samples contained at least 90% of the expected number of species. In the small tributaries of the Yeruslan River, the dominant species were the lymnaeids Lymnaea stagnalis (Linnaeus, 1758) and Radix auricularia (Linnaeus, 1758). The Yeruslan River is dominated by the non-native species Dreissena polymorpha (Pallas, 1771). The low values of the Shannon diversity index recorded in the rivers of the Yeruslan basin are typical of desert and semi-desert riverine ecosystems with low stability and productivity, caused by the constant reduction in habitats due to periodic and/or permanent drying. It was established that the most significant abiotic factors determining the distribution of molluscs are the bottom substrate and the concentrations of nitrites and phosphates. Moreover, non-critical concentrations of the latter in the water likely had a beneficial effect on the productivity of streams in an arid climate. Full article