Search Results (92)

Thermal stability is a key factor in determining the phenomena of deep chlorophyll maxima (DCM) in stratified lakes, as it mediates the vertical balance between light and nutrients required by phytoplankton. While it is well established that lake stratification is sensitive to latitude gradients, the ways in which thermal stability modulates DCM characteristics (i.e., depth, thickness, and concentration) and nutrient–chlorophyll relationships across different latitude classifications remain unclear. In this study, data on thermocline depth, DCM feature, and water quality parameters were collected from 88 globally distributed stratified lakes. Our findings indicate that (1) higher-latitude lakes exhibit strong thermoclines, with light and nitrogen serving as the primary drivers of thermal stratification; (2) in high-latitude lakes, surface chlorophyll a concentrations are more tightly linked to total phosphorus than that at DCM depth in low-latitude lakes; and (3) structural equation modeling (SEM) results demonstrate that higher-latitude lakes form shallower and thinner DCM structures, where low light levels contribute to reduced peaks in algal biomass. These findings provide valuable insights for the management of stratified lakes facing the dual pressures of climate change and eutrophication. Full article

Massive phytoplankton blooms threaten lake ecosystems, causing significant ecological and socio-economic damage. While remote sensing is vital for monitoring, the vertical stratification of algae influences light propagation and distorts remote sensing reflectance signals. This effect is particularly understudied in high-latitude lakes, leaving a gap in understanding phytoplankton biomass patterns. To address this, our study investigated three high-latitude water bodies: Lake Hulun, Fengman Reservoir, and Lake Khanka. We collected water samples from three depths based on total and euphotic zone depth and developed layer-specific inversion models for chlorophyll-a (Chal) and phycocyanin (PC) using a random forest algorithm. These models demonstrated strong performance and were applied to Sentinel-3 OLCI imagery from 2016–2024. Our results show that Chla generally decreases exponentially with depth, whereas PC exhibits a Gaussian-like vertical distribution with a pronounced subsurface maximum at approximately 1 m. In addition, a significant positive correlation between Chla and PC was observed in surface waters. In Lake Khanka, the northern basin exhibited a significant interannual increase in phytoplankton biomass. At 3 m, PC correlated negatively with turbidity and responded strongly to cyanobacterial blooms, while organic suspended matter correlated positively with Chla. This work establishes a robust framework for multilayer water quality monitoring in high-latitude lakes, providing critical insights for eutrophication management and cyanobacterial bloom early warning. Full article

The aquatic environments of main stems in large rivers and their connected lakes exhibit significant disparities under human activities. Fish are crucial for sustaining the structure and function of aquatic ecosystems as high-level predators. This study investigated fish communities in 192 samples from lakes and rivers across the Yangtze river (YR) basin utilizing environmental DNA (eDNA) technology. Additionally, the environmental variable impact on fish biodiversity in these two aquatic environments was uncovered. Herein, we identified approximately 230 fish taxa in this basin, with lakes and rivers comprising both prevalent and habitat-specific species. Water quality played different roles in affecting fish diversity in these two water systems. The geography traits, including Longitude, Latitude, and Altitude, as well as the water traits conductivity (CD), demonstrated the variance in fish diversity and community composition in both rivers and lakes. The human activity factors, including permanganate index (PMI), chlorophyll-a (CHLA), and SiO₂, elucidated much more variance in fish diversity and community composition in lakes. These findings suggested that human activity factors exert a more significant influence on fish diversity within lakes compared to rivers. Our outcomes document the complex impacts of water quality on fish diversity in different aquatic habitats of the YR basin and emphasize the distinctive considerations required to protect aquatic biodiversity in this basin. However, it should be noted that eDNA technology provides only a single snapshot of community composition. This method possesses limitations common to all approaches (e.g., detection gaps for certain taxa) as well as inherent biases (such as the difficulty in accurately reflecting the abundance and demographic structure of detected species). Full article

The majority of research on food webs has focused on temperate lakes, and little is known about the food web of lakes in polar regions. Subarctic lakes are particularly sensitive to climate change, which affects their stability. Therefore, the trophic structure of the food web in such lakes was considered as the object of this study. We studied a clear-water oligotrophic lake located in the subarctic region of Eurasia, specifically in northern Karelia and the White Sea coast of Russia. The study examined both open water periods (summer–autumn) and ice-covered periods (winter–spring) in this lake. Stable isotope analysis of carbon (¹³C/¹²C ratio or δ¹³C value) and nitrogen (¹⁵N/¹⁴N, δ¹⁵N) in producers and consumers was applied and revealed significant seasonal variations in the structure of the food web. The results indicate the presence of both pelagic and littoral/benthic food web compartments, with a notable contribution of autochthonous carbon derived from benthic sources. Omnivorous fish (perch, Perca fluviatilis; vendace, Coregonus albula; nine-spined sticklebacks, Pungitius pungitius) and some benthic invertebrates (mayfly, Ephemera vulgata; bivalves, Sphaerium corneum) had intermediate δ¹³C values, integrating these compartments by obtaining resources from both. Planktonic invertebrates had significantly depleted ¹³C, with the lowest δ¹³C value reaching −41.7‰, indicating an important contribution of methane-derived carbon. The study also revealed close trophic relationships between lake invertebrates and cyanobacteria, namely with planktonic Dolichospermum lemmermannii and benthic Phormidium sp. Seasonal changes in δ¹⁵N values and in trophic position have been observed among predacious omnivorous fish and crustaceans (amphipods, Gammaracanthus loricatus, and copepods, Cyclops scutifer), which are capable of a generalist feeding strategy depending on food availability. Using the example of this lake, it can be concluded that polar lake ecosystems are characterized by different seasonal intakes of allochthonous organic carbon from wetland catchment (humic compounds) and nitrogen because of nitrogen fixation in the air by cyanoprocaryotes. Alternative energy sources, such as carbon derived from methane, can also contribute to the energy balance of lake ecosystems. This study contributes to our understanding of energy flow and connectivity between producers and consumers in high-latitude lakes. Full article

Leaf area index (LAI) is a crucial parameter reflecting the crown structure of the grassland. Accurately obtaining LAI is of great significance for estimating carbon sinks in grassland ecosystems. However, spectral noise interference and pronounced spatial heterogeneity within vegetation canopies constitute significant impediments to achieving high-precision LAI retrieval. This study used hyperspectral sensor mounted on an unmanned aerial vehicle (UAV) to estimate LAI in a typical grassland, Hulun Lake Basin. Multiple machine learning (ML) models were constructed to reveal a relationship between hyperspectral data and grassland LAI using two input datasets, namely spectral transformations and vegetation indices (VIs), while SHAP (SHapley Additive ExPlanation) interpretability analysis was further employed to identify high-contribution features in the ML models. The analysis revealed that grassland LAI has good correlations with the original spectrum at 550 nm and 750 nm–1000 nm, first and second derivatives at 506 nm–574 nm, 649 nm–784 nm, and vegetation indices including the triangular vegetation index (TVI), enhanced vegetation index 2 (EVI2), and soil-adjusted vegetation index (SAVI). In the models using spectral transformations and VIs, the random forest (RF) models outperformed other models (testing R² = 0.89/0.88, RMSE = 0.20/0.21, and RRMSE = 27.34%/28.98%). The prediction error of the random forest model exhibited a positive correlation with measured LAI magnitude but demonstrated an inverse relationship with quadrat-level species richness, quantified by Margalef’s richness index (MRI). We also found that at the quadrat level, the spectral response curve pattern is influenced by attributes within the quadrat, like dominant species and vegetation cover, and that LAI has positive relationship with quadrat vegetation cover. The LAI inversion results in this study were also compared to main LAI products, showing a good correlation (r = 0.71). This study successfully established a high-fidelity inversion framework for hyperspectral-derived LAI estimation in mid-to-high latitude grasslands of the Hulun Lake Basin, supporting the spatial refinement of continental-scale carbon sink models at a regional scale. Full article

Extreme environments, such as hypersaline habitats, hot springs, deep-sea hydrothermal vents, glaciers, and permafrost, provide diverse ecological niches for studying microbial evolution. However, knowledge of microbial communities in extreme environments at high southern latitudes remains limited, aside from Antarctica. Laguna Timone is a hypersaline crater lake located in a Pleistocene maar of the Pali Aike Volcanic Field, southern Patagonia; the lake was formed during basaltic eruptions in a periglacial setting. Here, we report the first integrative characterization of microbial communities from biofilms and microbial mats in this lake using high-throughput 16S rRNA and ITS gene sequencing, along with mineralogical and hydrochemical analyses of water, sediments, and carbonates. Bacterial communities were dominated by the genera Enterobacterales ASV1, Pseudomonas, Oscillatoria, Nodularia, and Belliella, with site-specific assemblages. Fungal communities included Laetinaevia, Ilyonectria, Thelebolus, Plectosphaerella, and Acrostalagmus, each showing distinct distribution patterns. These baseline data contribute to understanding microbial dynamics in hypersaline maar environments and support future investigations. This integrative approach highlights key microbe–mineral relationships and underscores the potential of Laguna Timone as a natural laboratory for exploring biosignature formation and microbial adaptation in chemically extreme environments, both on early Earth and potentially beyond. Full article

Various data such as power grid sensors and manual observed icing, CMA (China Meteorological Administration) Land Surface Data Assimilation System (CLDAS) products, and the Fifth Generation Atmospheric Reanalysis of the Global Climate from Europe Center of Middle Range Weather Forecast (ERA5) are adopted to diagnose an icing process under a cold surge during 16–23 December 2023 in northeastern Yunnan Province. The results show that: (1) in the early stage of the process, mainly the freezing types, such as GG (temperature > 0 °C, relative humidity ≥ 75%) and DG (temperature < 0 °C, relative humidity ≥ 75%), occur. At the end of the process, an increase in icing type as GD (temperature > 0 °C, relative humidity < 75%) appears. (2) Significant differences exist in the elements during different stages of icing, and the atmospheric thermal, dynamic, and water vapor conditions are conducive to the occurrence of freezing rain during ice accretion. The main impact weather systems of this process include a strong high ridge in the mid to high latitudes of East Asia, transverse troughs in front of the high ridge south to Lake Baikal, low altitude troughs, and ground fronts. The transverse trough in front of the high ridge can cause cold air to accumulate and then move eastward and southward. The southerly flows, surface fronts, and other low-pressure systems can provide powerful thermodynamic and moisture conditions for ice accumulation. Full article

Recreational fisheries increasingly intersect with the habitats of flagship species, i.e., species that attract public attention and drive conservation efforts, raising potential ecological conflicts. This study investigated the spatial coupling between recreational fisheries and three flagship species in the Yangtze River Basin: the Chinese alligator (Alligator sinensis), the Yangtze finless porpoise (Neophocaena phocaenoides), and the scaly-sided merganser (Mergus squamatus). Drawing on over 10,000 fishing Points of Interest recorded between 2015 and 2024 and over 300 verified species occurrences, this study applied a Random Forest model with spatial integration and a Maximum Entropy model to examine estimated current distributions and forecast interactions from 2025 to 2035. Flagship species habitat suitability was modeled and projected at a spatial resolution of 1 km, while recreational fishing density was resolved on a coarser grid of 1.875° × 1.25° in latitude–longitude dimensions. Results reveal a substantial increase in high-risk overlap zones. For example, high-density fishing areas within high-suitability habitats for the scaly-sided merganser expanded from 0 km² in 2015 to 85,359 km² in 2024. Projections indicate continued intensification of such overlaps, particularly in regions including Ma’anshan–Wuhu, the Taihu–Chaohu–Poyang lake system, and Yibin. These findings offer robust, model-driven evidence of growing spatial conflicts and offer actionable insights for ecosystem-based governance. The methodological framework is transferable and supports broader applications in other regions and species under ecological sustainability goals. Full article

Utah, USA, relies heavily on snowpack for water to sustain its growing population. Scientists and policy makers are exploring and proposing several potential sustainable solutions to improving flow to the Great Salk Lake as it recently has significantly declined in size, including removing tree canopy. This study examines the influence of tree canopy coverage, climate, and topography on snow water equivalent (SWE) within the Great Salt Lake Watershed. Using SNOTEL data, NLCD land use/land cover rasters, t-tests, and multiple linear regression (MLR), the study analyzed SWE variability in relation to canopy density, winter precipitation, elevation, temperature, and latitude. Initial t-tests showed significant differences in SWE between sites with canopy coverage below and above 70%, yet tree canopy was excluded as a significant predictor in the MLR model. Instead, SWE was primarily explained by mean winter precipitation, elevation, average winter high temperatures, and latitude. Additionally, canopy change analysis of the 2018 Pole Creek Fire in the Jordan River watershed showed no significant changes in SWE following canopy loss. This study highlights the dominant role of climatic factors in influencing snowpack dynamics on a watershed scale. It also provides important data for sustainable watershed and forestry management and a framework for understanding snowpack responses to climate and land cover changes in saline lake ecosystems. Full article

High-quality precipitation data are vital for hydrological research. In regions with sparse observation stations, reliable gridded data cannot be obtained through interpolation, while the coarse resolution of satellite products fails to meet the demands of small watershed studies. Downscaling satellite-based precipitation products offers an effective solution for generating high-resolution data in such areas. Among these techniques, machine learning plays a pivotal role, with performance varying according to surface conditions and algorithmic mechanisms. Using the Qinghai Lake Basin as a case study and rain gauge observations as reference data, this research conducted a systematic comparative evaluation of nine machine learning algorithms (ANN, CLSTM, GAN, KNN, MSRLapN, RF, SVM, Transformer, and XGBoost) for downscaling IMERG precipitation products from 0.1° to 0.01° resolution. The primary objective was to identify the optimal downscaling method for the Qinghai Lake Basin by assessing spatial accuracy, seasonal performance, and residual sensitivity. Seven metrics were employed for assessment: correlation coefficient (CC), root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R²), standard deviation ratio (Sigma Ratio), Kling-Gupta Efficiency (KGE), and bias. On the annual scale, KNN delivered the best overall results (KGE = 0.70, RMSE = 17.09 mm, Bias = −3.31 mm), followed by Transformer (KGE = 0.69, RMSE = 17.20 mm, Bias = −3.24 mm). During the cold season, KNN and ANN both performed well (KGE = 0.63; RMSE = 5.97 mm and 6.09 mm; Bias = −1.76 mm and −1.75 mm), with SVM ranking next (KGE = 0.63, RMSE = 6.11 mm, Bias = −1.63 mm). In the warm season, Transformer yielded the best results (KGE = 0.74, RMSE = 23.35 mm, Bias = −1.03 mm), followed closely by ANN and KNN (KGE = 0.74; RMSE = 23.38 mm and 23.57 mm; Bias = −1.08 mm and −1.03 mm, respectively). GAN consistently underperformed across all temporal scales, with annual, cold-season, and warm-season KGE values of 0.61, 0.43, and 0.68, respectively—worse than the original 0.1° IMERG product. Considering the ability to represent spatial precipitation gradients, KNN emerged as the most suitable method for IMERG downscaling in the Qinghai Lake Basin. Residual analysis revealed error concentrations along the lakeshore, and model performance declined when residuals exceeded specific thresholds—highlighting the need to account for model-specific sensitivity during correction. SHAP analysis based on ANN, KNN, SVM, and Transformer identified NDVI (0.218), longitude (0.214), and latitude (0.208) as the three most influential predictors. While longitude and latitude affect vapor transport by representing land–sea positioning, NDVI is heavily influenced by anthropogenic activities and sandy surfaces in lakeshore regions, thus limiting prediction accuracy in these areas. This work delivers a high-resolution (0.01°) precipitation dataset for the Qinghai Lake Basin and provides a practical basis for selecting suitable downscaling methods in similar environments. Full article

The aim of this study was to expand the monitoring network and evaluate the accuracy of inexpensive WoMaster ES-104 sensors for monitoring particulate matter (PM) in temperate latitudes, using the example of the Southern Baikal region. The research methods included continuous measurements of PM_2.5 and PM₁₀ concentrations, temperature, and humidity at three stations (Listvyanka, Patrony, and Tankhoy) from October 2023 to October 2024, using the LCS WoMaster ES-104. ERA5-Land reanalysis data and the HYSPLIT model were used to analyze meteorological conditions and air mass trajectories. The results of this study showed a high correlation between the WoMaster ES-104 and the DustTrak 8533; the correlation coefficient was 0.94 (R² = 0.85) for both fractions. The seasonal dynamics of PM_2.5 and PM₁₀ were characterized by a dual-mode distribution with maxima in summer (secondary aerosols, high humidity) and winter (anthropogenic emissions, inversions). The diurnal cycles showed morning/evening peaks associated with transport activity and atmospheric stratification. Extreme concentrations were recorded in anticyclonal weather (weak north-westerly winds, stable atmosphere). This study confirms the suitability of the LCS WoMaster ES-104 for real-time monitoring of PM_2.5 and PM₁₀, which contributes to sustainable development by increasing the availability of air quality data for ecologically significant regions such as Lake Baikal. Full article

Cold-water lakes in high-latitude regions are experiencing rapid changes in community structure and functioning associated with local and global stressors (e.g., climate change, hydropower and invasive species). However, the long-term ecological responses of cold-adapted top predators are relatively poorly monitored despite their high importance for structuring ecological communities and for the provisioning of ecosystem services. We studied long-term changes (2010–2021) in the population structure and trophic niche of two cold-adapted coregonid fishes in oligotrophic Lake Osensjøen, southeastern Norway. Our gillnet surveys indicated that the whitefish (Coregonus lavaretus) population declines simultaneously with the increasing population density of roach (Rutilus rutilus), whereas vendace (Coregonus albula) showed more stable densities. Both whitefish and vendace became increasingly dominated by small-sized individuals following the increase in coexisting roach and perch (Perca fluviatilis) populations. Our stomach content and stable isotope data indicated a marked overlap in the trophic niches of whitefish and roach, with both species showing high among-individual variation in δ¹³C and δ¹⁵N values as compared to the more specialized zooplanktivorous vendace. Our study provides further evidence that the ongoing environmental changes in high-latitude lakes may induce rapid changes in community structures and lead to the population declines of cold-adapted fishes, likely associated with strong resource competition with warm-adapted cyprinid and percid fishes. Such shifts in fish community structure may, in turn, affect the benthic and pelagic food-web compartments and reduce valuable ecosystem services such as local fisheries targeting salmonids. Full article

Climate change has significantly altered plant habitats within the Earth’s surface system, reshaping the global distribution and succession of vegetation. The spatiotemporal simulation of vegetation dynamics is essential for effective ecosystem management and conservation at regional scales. In this study, an improved method is developed to analyze the vegetation patterns and scenarios in the Poyang Lake basin, based on the High-Accuracy Surface Modeling (HASM) method and the improved Holdridge Life Zone (HLZ) ecosystem model. HASM is applied to generate high-resolution (250 m × 250 m) spatial grid data for key climate parameters, including mean annual biotemperature (MAB), total annual precipitation (TAP), and potential evapotranspiration ratio (PER), for each decade from 1961 to 2050. The distribution thresholds of vegetation types are calculated based on current vegetation data, MAB, TAP, PER, longitude, latitude, and elevation datasets. In the improved HLZ ecosystem model, the classification parameters of vegetation types have been expanded from three to six. The simulation results indicate that cultivated vegetation, subtropical coniferous forest, and subtropical grassland are the dominant vegetation types, accounting for 75.88% of the total area. Between 2020 and 2050, subtropical coniferous forest is projected to experience the greatest decrease in area, shrinking by an average of 2.65 × 10³ km² per decade. In contrast, subtropical evergreen–deciduous broadleaf mixed forest is expected to undergo the largest increase, expanding by an average of 1.96 × 10³ km² per decade. Vegetation types in high-altitude regions exhibit the most rapid changes, with an average decadal variation of 15.26%, whereas low-altitude regions show relatively slower changes, averaging 0.52% per decade. Overall, subtropical grassland, subtropical coniferous forest, and subtropical evergreen–deciduous broadleaf mixed forest in the Poyang Lake basin demonstrate high sensitivity to projected climate change scenarios. Full article

Responding to a growing concern about impacts from anthropogenic activity on several dozen lakes, a group of citizens initiated and led a water quality sampling program that included characterizing groundwater dependence. The small lakes are located on hummocky glacial terrain near Edmonton, Alberta, Canada. A team of volunteers collected lake samples for a variety of limnological and ecological analyses to document lake health and trophic state, and collaborated with a university research group to identify groundwater dependence using specific environmental tracers (δ²H, δ¹⁸O, and ²²²Rn). Water chemistry and isotopic measurements are largely explained by the position of a lake within the local groundwater flow system. A simple metric to express the likelihood of groundwater dependence was calculated using the total dissolved solids (TDS), δ¹⁸O, and ²²²Rn values. Across the relatively small study area, a greater likelihood of groundwater dependence was determined for lakes located downgradient from an elevated recharge area. In contrast, where the water table was relatively flat, a lower likelihood of groundwater dependence was found. These results were similar to the spatial pattern of a trophic state, indicating that groundwater dependence may be one of the factors responsible for lake ecological status. The data generated by citizens and the knowledge gained about the hydrology of this area will help discussions between landowners and decision makers on how to best manage land use in this diverse landscape. Full article

The Qilian Mountains, located on the northeastern edge of the Qinghai–Tibet Plateau, are characterized by unique high-altitude and cold-climate terrain, where permafrost and seasonally frozen ground are extensively distributed. In recent years, with global warming and increasing precipitation on the Qinghai–Tibet Plateau, permafrost degradation has become severe, further exacerbating the fragility of the ecological environment. Therefore, timely research on surface deformation and the freeze–thaw patterns of alpine permafrost in the Qilian Mountains is imperative. This study employs Sentinel-1A SAR data and the SBAS-InSAR technique to monitor surface deformation in the alpine permafrost regions of the Qilian Mountains from 2017 to 2023. A method for spatiotemporal interpolation of ascending and descending orbit results is proposed to calculate two-dimensional surface deformation fields further. Moreover, by constructing a dynamic periodic deformation model, the study more accurately summarizes the regular changes in permafrost freeze–thaw and the trends in seasonal deformation amplitudes. The results indicate that the surface deformation time series in both vertical and east–west directions obtained using this method show significant improvements in accuracy over the initial data, allowing for a more precise reflection of the dynamic processes of surface deformation in the study area. Subsidence is predominant in permafrost areas, while uplift mainly occurs in seasonally frozen ground areas near lakes and streams. The average vertical deformation rate is 1.56 mm/a, with seasonal amplitudes reaching 35 mm. Topographical (elevation; slope gradient; aspect) and climatic factors (temperature; soil moisture; precipitation) play key roles in deformation patterns. The deformation of permafrost follows five distinct phases: summer thawing; warm-season stability; frost heave; winter cooling; and spring thawing. This study enhances our understanding of permafrost deformation characteristics in high-latitude and high-altitude regions, providing a reference for preventing geological disasters in the Qinghai–Tibet Plateau area and offering theoretical guidance for regional ecological environmental protection and infrastructure safety. Full article