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The objective of this study was to explore the environmental factors having the greatest influence on the distribution and abundance of epipelic diatom species in different wetlands in southern Spain. We previously defined four groups of conductivity categories: fresh (< 0.8 mS cm−1), oligosaline (< 8 mS cm−1), mesosaline (8–30 mS cm−1) and eusaline (> 30 mS cm−1). A dbRDA analysis performed on a subset of 36 of the 53 wetlands, using a total of 25 environmental variables, showed that five environmental variables (conductivity, pH, wetland area, silicates, and total suspended solids) were the best explanatory variables for the diatom assemblage, with conductivity being the main explanatory variable. Nonmetric multidimensional scaling (nMDS) analysis performed on the set of 53 wetlands revealed significant differences in diatom composition among the four conductivity groups. The key species in the eusaline group were Tryblionella pararostrata, Halamphora sp.1 and Cocconeis euglypta, whereas in the mesosaline and oligosaline group, these were Navicula veneta, Tryblionella hungarica and Nitzschia inconspicua. Finally, in the fresh group dominated Achnanthidium minutissimum, Navicula veneta and Gomphonema exilissimum. This study on epipelic diatoms can therefore contribute to the knowledge of these organisms in a European region with a high diversity of wetland typologies. [ABSTRACT FROM AUTHOR]

Currently, more and more lakes around the world are experiencing outbreaks of cyanobacterial blooms, and high-precision and rapid monitoring of the spatial distribution of algae in water bodies is an important task. Remote sensing technology is one of the effective means for monitoring algae in water bodies. Studies have shown that the Floating Algae Index (FAI) is superior to methods such as the Standardized Differential Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) in monitoring cyanobacterial blooms. However, compared to the NDVI method, the FAI method has difficulty in determining the threshold, and how to choose the threshold with the highest classification accuracy is challenging. In this study, FAI linear fitting model (FAI-L) is selected to solve the problem that FAI threshold is difficult to determine. Innovatively combine FAI index and NDVI index, and use NDVI index to find the threshold of FAI index. In order to analyze the applicability of FAI-L to extract cyanobacterial blooms, this paper selected multi-temporal Landsat8, HJ-1B, and Sentinel-2 remote sensing images as data sources, and took Chaohu Lake and Taihu Lake in China as research areas to extract cyanobacterial blooms. The results show that (1) the accuracy of extracting cyanobacterial bloom by FAI-L method is generally higher than that by NDVI and FAI. Under different data sources and different research areas, the average accuracy of extracting cyanobacterial blooms by FAI-L method is 95.13%, which is 6.98% and 18.43% higher than that by NDVI and FAI respectively. (2) The average accuracy of FAI-L method for extracting cyanobacterial blooms varies from 84.09 to 99.03%, with a standard deviation of 4.04, which is highly stable and applicable. (3) For simultaneous multi-source image data, the FAI-L method has the highest average accuracy in extracting cyanobacterial blooms, at 95.93%, which is 6.77% and 13.26% higher than NDVI and FAI methods, respectively. In this paper, it is found that FAI-L method shows high accuracy and stability in extracting cyanobacterial blooms, and it can extract the spatial distribution of cyanobacterial blooms well, which can provide a new method for monitoring cyanobacterial blooms. [ABSTRACT FROM AUTHOR]

This study examines the dynamics of limnological parameters of a South American lake located in southern Chile with the objective of predicting chlorophyll-a levels, which are a key indicator of algal biomass and water quality, by integrating combined remote sensing and machine learning techniques. Employing four advanced machine learning models (recurrent neural network (RNNs), long short-term memory (LSTM), recurrent gate unit (GRU), and temporal convolutional network (TCNs)), the research focuses on the estimation of chlorophyll-a concentrations at three sampling stations within Lake Ranco. The data span from 1987 to 2020 and are used in three different cases: using only in situ data (Case 1), using in situ and meteorological data (Case 2), using in situ, and meteorological and satellite data from Landsat and Sentinel missions (Case 3). In all cases, each machine learning model shows robust performance, with promising results in predicting chlorophyll-a concentrations. Among these models, LSTM stands out as the most effective, with the best metrics in the estimation, the best performance was Case 1, with R2 = 0.89, an RSME of 0.32 µg/L, an MAE 1.25 µg/L and an MSE 0.25 (µg/L)2, consistently outperforming the others according to the static metrics used for validation. This finding underscores the effectiveness of LSTM in capturing the complex temporal relationships inherent in the dataset. However, increasing the dataset in Case 3 shows a better performance of TCNs (R2 = 0.96; MSE = 0.33 (µg/L)2; RMSE = 0.13 µg/L; and MAE = 0.06 µg/L). The successful application of machine learning algorithms emphasizes their potential to elucidate the dynamics of algal biomass in Lake Ranco, located in the southern region of Chile. These results not only contribute to a deeper understanding of the lake ecosystem but also highlight the utility of advanced computational techniques in environmental research and management. [ABSTRACT FROM AUTHOR]

This article presents the genome sequence of a strain of Methylomonas sp. AM2-LC, a methanotrophic bacterial species found in a Finnish lake. Methanotrophic bacteria are important for reducing methane emissions and have potential for biotechnological applications. The genome sequence can be used for comparative analysis and understanding the metabolic capabilities of methanotrophs. The article also discusses the isolation and DNA extraction process, as well as bioinformatic services provided by a sequencing facility. The document is a list of references related to methanotrophic bacteria, providing a comprehensive overview of current research in the field. It includes references to three scientific articles that cover microbial variant detection, methane-dependent mineral reduction, and the discovery of a new type of methanotroph. These articles are valuable resources for library patrons conducting research in microbiology. [Extracted from the article]

The cartographic landscape analysis of Lake Doshne employs geographic landscape methods, GIS cartographic modeling, and geo-ecological analysis. This study includes hydrochemical analysis of the lake's water mass, focusing on saline blocks, tropho-saprobiological indicators, and specific toxic action indicators. Three geological sections of anthropogenic and pre-Quaternary complexes, along with a geological–lithological transverse profile of the lake basin, were developed. Additionally, a geographical landscape model of the lake's natural aquatic complex was presented, distinguishing littoral–sublittoral and profundal aquatic sub-tracts and five types of aquafacies with landscape metric assessments. This approach enables a comprehensive analysis and the creation of cartographic models that can serve as a basis for lake cadastre and optimization of the ecological and landscape conditions in local territories. [ABSTRACT FROM AUTHOR]

The investigation of lakes' vulnerability to external impacts is essential for understanding and potentially mitigating the threats they face. By studying how lakes are affected by external factors, such as pollution, climate change and human activities, we can assess the health of the ecosystem and predict how it may respond to future changes. The purpose of this research is the analysis of climate change's influence on the vulnerability of Belarusian lakes to external impact. The vulnerability indices were calculated using the randomized aggregate method. The dependences between parameters were defined on the basis of correlation and regression analysis. We investigated the vulnerability of 149 Belarusian lakes. Classifying the lakes allowed us to divide them into three types, with high, medium and low vulnerability to external impact. All the types include 2–3 subtypes. On the basis of classification, we created a zoning scheme for Belarus on the vulnerability of lakes to external impact. A forecast of lake vulnerability for three SSP scenarios to 2100 was conducted. In the SSP1 scenario, the vulnerability of stratified lakes will increase insignificantly. The vulnerability of homothermous lakes will not change. In the SSP2 scenario, the vulnerability of lakes will first increase then decrease. Lakes with high and medium vulnerability will be classed as medium- and low-vulnerable. In the SSP5 scenario, the vulnerability of lakes will decrease more significantly than in the other scenarios. [ABSTRACT FROM AUTHOR]

This study is structured to address the problem of mapping the bottom of shallow and ultra-shallow inland water bodies using high-resolution satellite imagery. These environments, with their diverse distribution of optically relevant components, pose a challenge to traditional mapping methods. The study was conducted on several research issues, each focusing on a specific aspect of the SDB, related to the selection of spectral bands and regression models, regression models creation, evaluation of the influence of the number and spatial distribution of reference soundings, and assessment of the quality of the bathymetric surface, with a focus on microtopography. The study utilized basic empirical techniques, incorporating high-precision reference data acquired via an unmanned surface vessel (USV) integrated with a single-beam echosounder (SBES), and Global Navigation Satellite System (GNSS) receiver measurements. The performed investigation allowed the optimization of a methodology for bathymetry acquisition of such areas by identifying the impact of individual processing components. The first results indicated the usefulness of the proposed approach, which can be confirmed by the values of the obtained RMS errors of elaborated bathymetric surfaces in the range of up to several centimeters in some study cases. The work also points to the problematic nature of this type of study, which can contribute to further research into the application of remote sensing techniques for bathymetry, especially during acquisition in optically complex waters. [ABSTRACT FROM AUTHOR]

Objective To assess contribution and seasonal variation in groundwater discharge (LGD) to lake water and nutrient budgets, Methods this study investigated Changhu Lake in the middle reaches of the Yangtze River. Field sampling was conducted during both the wet and dry seasons using multiple tracing techniques, including electrical conductivity (EC), stable isotope (2H and 18O), hydrochemical element (Ca2+ and Mg2+), and 222Rn isotope data. The 222Rn mass balance model was employed to quantify the LGD and associated nutrient fluxes in different seasons. Results Results show that LGD rates during the wet and dry seasons were 64.52 mm/d and 14.95 mm/d, respectively, with significant differences between these seasons. Furthermore, during the wet and dry seasons, groundwater carried TN inputs of approximately 25.68×106 g/d and 5.58×106 g/d, respectively. The TP inputs were approximately 8.14×106 g/d and 0.17×106 g/d in the wet and dry seasons, respectively. The differences in the LGD rates between the wet and dry seasons lead to differences in groundwater carrying TN and TP inputs, and inputs of TP during the wet season is also influenced by agricultural activities during that period. Sronger precipitation and evaporation during the wet season drive greater LGD intensity and their carrying TN and TP fluxes. Conclusion The research can provide scientific reference for water resource management and aquatic ecosystem preservation efforts in the Changhu area.

The cartographic landscape analysis of Lake Doshne employs geographic landscape methods, GIS cartographic modeling, and geo-ecological analysis. This study includes hydrochemical analysis of the lake’s water mass, focusing on saline blocks, tropho-saprobiological indicators, and specific toxic action indicators. Three geological sections of anthropogenic and pre-Quaternary complexes, along with a geological–lithological transverse profile of the lake basin, were developed. Additionally, a geographical landscape model of the lake’s natural aquatic complex was presented, distinguishing littoral–sublittoral and profundal aquatic sub-tracts and five types of aquafacies with landscape metric assessments. This approach enables a comprehensive analysis and the creation of cartographic models that can serve as a basis for lake cadastre and optimization of the ecological and landscape conditions in local territories.

Lakes in the hilly regions of the Sikkim Himalayas in India are crucial for water supply and tourism. However, this area experiences frequent earthquakes and microtremors, increasing the risk of seismic hazards and contributing to a higher density of subsurface fractures and discontinuities. This has led to water seepage in lakes across Sikkim, turning some from perennial to seasonal. To investigate these issues, geoelectrical mapping techniques, specifically Vertical Electrical Sounding (VES) and profiling, were used to study Dhap Pokhari Lake in Sikkim’s Pakyong district. The findings revealed a subsurface fracture zone beginning at a depth of 20 m and extending down to 50 m. The VES data showed significant variations in sediment thickness and subsurface lithology between two measurement points only 10 m apart, with a noticeable ground settlement of about 2 m at one location. The profiling results indicated a major fracture and two minor ones, which are likely causing water seepage and ground saturation, particularly during rainy seasons, leading to compaction and ground settlement. This poses a risk to the structural stability of the surrounding areas, highlighting the need for effective lake restoration strategies. Geoelectrical mapping is a valuable tool for identifying such subsurface fractures and making evidence-based strategies to revive lakes in this seismically active region.

This research focuses on developing a multipurpose riparian zone designed to effectively reduce erosion and control nutrient flow into Lake Tondano. The goal is to enhance both conservation and pollution control strategies for sustainable ecosystem management. Conducted at Lake Tondano in Minahasa, Indonesia, the research followed three main stages: data collection, analysis, and design. The data collection included a vegetation survey of riparian species, land use mapping, and measuring nitrogen and phosphorus levels in lake sediments. A total of 91 plant species from 60 genera and 42 families were documented. Based on their Importance Value Index (IVI), non-invasive status, and nutrient absorption capabilities, 15 species were selected for restoration in areas with high nutrient concentrations, with sediment levels recorded at 0.09% nitrogen and 0.06% phosphorus in impacted zones. These plant species were carefully identified and rigorously tested, originating from intact riparian zones. They will be strategically employed in areas facing significant challenges from nutrient overloading. Using QGIS analysis, a riparian zone measuring 100 m x 30 m was designed at coordinates 1.1745604 latitude and 124.8972748 longitude, targeting areas most impacted by nutrient pollution, which poses a risk of eutrophication and negatively affects aquatic ecosystems. The multipurpose riparian zone incorporates distinct wet, transition, and dry zones, employing a zigzag planting pattern to optimize pollutant filtration and nutrient uptake. This design effectively addresses critical issues of erosion and nutrient excessive enrichment, promoting ecological health and biodiversity in the region. The novel contributions of this study include identifying specific plant species capable of thriving in nutrient-rich sediments and quantifying their nutrient absorption capacities, thereby providing a scientifically grounded model for similar conservation efforts in vulnerable ecosystems and enhancing overall resilience. However, long-term impacts on water quality require further research to assess nutrient mitigation efficacy.

The investigation of lakes’ vulnerability to external impacts is essential for understanding and potentially mitigating the threats they face. By studying how lakes are affected by external factors, such as pollution, climate change and human activities, we can assess the health of the ecosystem and predict how it may respond to future changes. The purpose of this research is the analysis of climate change’s influence on the vulnerability of Belarusian lakes to external impact. The vulnerability indices were calculated using the randomized aggregate method. The dependences between parameters were defined on the basis of correlation and regression analysis. We investigated the vulnerability of 149 Belarusian lakes. Classifying the lakes allowed us to divide them into three types, with high, medium and low vulnerability to external impact. All the types include 2–3 subtypes. On the basis of classification, we created a zoning scheme for Belarus on the vulnerability of lakes to external impact. A forecast of lake vulnerability for three SSP scenarios to 2100 was conducted. In the SSP1 scenario, the vulnerability of stratified lakes will increase insignificantly. The vulnerability of homothermous lakes will not change. In the SSP2 scenario, the vulnerability of lakes will first increase then decrease. Lakes with high and medium vulnerability will be classed as medium- and low-vulnerable. In the SSP5 scenario, the vulnerability of lakes will decrease more significantly than in the other scenarios.

In Indonesia, a country in which 70% of its area is water, people relate easily to both the sea and inland water, such as rivers and lakes. Authors consequently also find inspiration in these bodies of water, expressing their admiration towards the beauty of nature. For example, while they originate from different literary eras, “Danau Toba” (Lake Toba) by Sitor Situmorang, “Sepantun Laut” (Like the Sea) by J.E. Tatengkeng, “Akulah Si Telaga” (I am the Lake) by Sapardi Djoko Damono, “Apa Kata Bintang di Laut” (What the Star Tells the Sea) by Iwan Simatupang, “Kali Martapura” (Martapura River) by Hidjaz Yamani, and “Perempuan Pesisiran” (Women on the Coasts) by Iman Sembada all reflect the dynamic portrayals of water in Indonesian literature, as a charm of nature from each poet’s perspective or a framework for criticizing the realities of the lives of the people who live alongside water. This research analyzed these authors’ interconnectedness with nature, employing the qualitative descriptive method and using ecocriticism theory, which explores how nature is depicted in the respective poems and connects human relationships to nature. The results showed that the poets easily relate to the river, lake, or sea, and aside from describing the beauty of nature based on fond memories, their poems are used as critiques of the changing relationship between humans and nature, as well as between humans and humans. Their portrayals of nature further reveal the feelings of belonging engendered by water, which they use as criticism for the destruction of nature and societal changes stemming from the need for progress.

The determination of a lake or natural watercourse shoreline is the subject of various administrative proceedings relating to, among others, the engineering of riverbeds, construction of hydro-technical facilities, remediation work, land division, or delimitation of parcels. The provisions of law, while laying out the rules for determining shorelines, do not explicitly specify the measurement method to follow. All the more so, as many shores of lakes and watercourses are among terrain details that are difficult to measure due to their varied accessibility, which depends on the terrain, vegetation, and water conditions. The purpose of this paper is to compare selected methods for determining the shoreline of watercourses and lakes in terms of their applicability under different environmental conditions under current legislation. This study comprises an assessment of the suitability of the applied methods of shoreline measurement under varying field conditions and their applicability in surveying work on shoreline determination. Surveys were conducted on 3 reservoirs and one watercourse using geodetic, photogrammetric, and remote sensing techniques, and the suitability of the various methods was evaluated with respect to the field conditions of the measurements.

Nutrient enrichment and climate warming threaten freshwater systems. Metabolic theory and the paradox of enrichment predict that both stressors independently can lead to simpler food‐webs having fewer nodes, shorter food‐chains and lower connectance, but cancel each other's effects when simultaneously present. Yet, these theoretical predictions remain untested in complex natural systems. We inferred the food‐web structure of 256 lakes and 373 streams from standardized fish community samplings in France. Contrary to theoretical predictions, we found that warming shortens fish food‐chain length and that this effect was magnified in enriched streams and lakes. Additionally, lakes experiencing enrichment exhibit lower connectance in their fish food‐webs. Our study suggests that warming and enrichment interact to magnify food‐web simplification in nature, raising further concerns about the fate of freshwater systems as climate change effects will dramatically increase in the coming decades. [ABSTRACT FROM AUTHOR]

Hypophthalmichthys nobilis are widely distributed in the Yangtze River basin and its related lakes. They are an important economic fish species and are a famous cultured species known as the "Four Famous Domestic Fishes" in China. Currently, with the fishing ban in the Yangtze River basin, fishing for H. nobilis in the natural water bodies of the Yangtze River basin has been completely prohibited. In order to identify the sources of H. nobilis appearing in the market, further control and accountability is necessary to trace the sources of H. nobilis in the Yangtze River basin and its related water bodies. Therefore, this study identified and traced different sources of H. nobilis through muscle element fingerprint analysis (EFA). The results show that H. nobilis from different stations have characteristic element compositions. The characteristic element of H. nobilis from Wuhan (WH) is Pb, which is significantly higher than that in other stations; the characteristic element from Anqing (AQ) is Hg, which is significantly higher than that in other stations; and the characteristic element from Taihu (TH) is Al, which is significantly higher than that in other water areas. Multivariate analysis selected different spatial distribution patterns in four discriminative element ratios (Pb/Ca, Cr/Ca, Na/Ca, and Al/Ca) in the muscle of H. nobilis in the Yangtze River basin and its related lakes. This study suggests that the screened discriminative elements can be used to visually distinguish different sources of H. nobilis and to quickly trace and verify the origin of newly emerging samples. Therefore, the use of selected discriminative element fingerprint features to trace the origin of new samples has been proven to be feasible. By further discriminating and verifying the muscle element fingerprints of new samples, the discrimination rate is high. Therefore, a multivariate analysis of muscle element fingerprints can be used for tracing the origins of samples of unknown origin in market supervision. [ABSTRACT FROM AUTHOR]

Most information on rotifers living in lake sands comes from the 1930s, when the first reports on this subject by Jerzy Wiszniewski appeared. After some decline in the interest in lake psammon in the following years, research on lake psammon returned in the last decade of the twentieth century. The last comprehensive review of ecology of psammon Rotifera was included in the excellent 1998 publication by Schmid-Araya on Rotifera in interstitial sediments. More than 20 papers have been published since that time. So far, research conducted almost exclusively in the northern hemisphere have dealt with issues related to distribution of rotifers, their species structure and diversity as well as to their relation to abiotic and biotic factors. The aim of the present study was to collect all available information on psammon rotifers, assess the shortcomings in our knowledge and fill these gaps with the results of some of my recent research. The results of the study show that the species richness of this group in geographical terms is still unknown. It means we also do not know the level of endemism among the psammon rotifers. The role of psammon rotifers in benthic food webs is another issue requiring research. [ABSTRACT FROM AUTHOR]

In the context of escalating climate change-induced impacts on water resources, robust monitoring tools are imperative. Satellite altimetry, benefiting from technical improvement such as the use of SAR and InSAR techniques and tracking modes considering topography, is emerging as a crucial means of estimating lake levels, data that are fundamental to understanding climate dynamics. This study delves into the use of satellite-altimetry-determined water levels to analyze changes in water storage and superficial area in Lake Ranco, in south-central Chile, from 1995 to 2023. The main objective is to provide valuable information for water-resource management and policy formulation. Leveraging AlTiS software (v2.2.9-0-gf5938ab), radar-altimetry data from the missions ERS-2, ENVISAT, SARAL, and Sentinel-3A were processed, generating a complete time series of water levels. The lake-level data were complemented by the bathymetric data for the lake to obtain the variation in the area and volume in the period 1995–2023. These results were analyzed with respect to hydrometeorological data from the study area, such as precipitation, temperature, relative humidity, and potential evapotranspiration. Additionally, the effects of ENSO (ENSO 3.4 index) and the Pacific Decadal Oscillation index (PDO) were considered. Results reveal a strong correlation between altimetry-derived lake levels and observed in situ data, with a mean square error of 0.04 m, a coefficient of determination of 0.99, an index of agreement of 0.99, and a Kling−Gupta efficiency of 0.90. The analysis of climatic variables showed that variations in lake level coincide with changes in precipitation within the study area and also showed the influence of variations in temperature and potential evapotranspiration. Additionally, the effects of the ENSO phenomenon can be seen within the study area for its cold phase (i.e., La Niña) in the 2010–2012 period and for its warm phase (i.e., El Niño) in the 2015–2016 period, with a decrease and increase in precipitation, respectively. These effects were enhanced when the cold and warm phases of the ENSO and PDO phenomena occured. The successful application of satellite altimetry demonstrated in this study underscores its critical role in advancing our understanding and management of water resources amidst changing climate scenarios. [ABSTRACT FROM AUTHOR]

Phosphorus (P) is a crucial nutrient in lake ecosystems and organic phosphorus (Po) is a significant component. However, the distribution characteristics and migration behaviour of Po in ice–water–sediment systems under freezing and thawing conditions in cold and arid regions remain unclear. This study aims to investigate the forms of Po and its contribution to endogenous P pollution. We selected three lakes (Dai, Hu, and Wu Lake) and employed phosphorus nuclear magnetic resonance (31P-NMR) techniques to analyse the following: (1) The total phosphorus (TP) content, which was the highest in the water from Dai Lake (0.16 mg/L), with substantial seasonal variation observed in Wu Lake, where P content was four times higher in summer than in winter because of farmland drainage. (2) Eutrophication analysis, which indicated that Dai Lake had significantly higher eutrophication levels than Wu Lake, with P being the controlling factor in Dai Lake and both N and P in Wu Lake. The proportion of Po in the TP content was 90%, 70%, and 55% for Wu, Dai, and Hu Lake, respectively, indicating that Po was the main component of eutrophic lakes. (3) 31P-NMR, which revealed that orthophosphate (Ortho-P) and monoester phosphate (Mon-P) were the main P components in the winter, with a higher P content in Dai Lake. Ortho-P has a higher content in ice, indicating that inorganic phosphorus (Pi) migration is the main factor in ice–water media. Mon-P showed multiple peaks in Dai Lake, indicating a complex composition of adenosine monophosphate and glucose-1-phosphate. (4) The ice–water phase change simulation experiments, which showed that phosphate was the least repelled in ice, while pyrophosphate (Pyro-P) and macromolecular P were more repelled. Adding sediment enhanced the migration of P but did not change the repulsion of macromolecular P, suggesting the molecular structure as the main influencing factor. These results provide important scientific evidence for the quantitative analysis of Po pollution in lake water environments, aiding in P load reduction and risk prevention and control. [ABSTRACT FROM AUTHOR]

Cyanobacterial blooms in freshwater sources are a global concern, and gaining insight into their causes is crucial for effective resource management and control. In this study, we present a novel computational framework for the causal analysis of cyanobacterial harmful algal blooms (cyanoHABs) in Lake Kinneret. Our framework integrates Convergent Cross Mapping (CCM) and Extended CCM (ECCM) causal networks with Bayesian Network (BN) models. The constructed CCM–ECCM causal networks and BN models unveil significant interactions among factors influencing cyanoHAB formation. These interactions have been validated by domain experts and supported by evidence from peer‐reviewed publications. Our findings suggest that Microcystis flos‐aquae levels are influenced not only by community structure but also by ammonium, phosphate, oxygen, and temperature levels in the weeks preceding bloom occurrences. We demonstrated a non‐parametric computational framework for causal analysis of a multivariate ecosystem. Our framework offers a more comprehensive understanding of the underlying mechanisms driving M. flos‐aquae blooms in Lake Kinneret. It captures complex interactions and provides an explainable prediction model. By considering causal relationships, temporal dynamics, and joint probabilities of environmental factors, the proposed framework enhances our understanding of cyanoHABs in Lake Kinneret. [ABSTRACT FROM AUTHOR]

Recently, as global climate change and local disturbances such as wildfires continue, long- and short-term changes in the high-latitude vegetation systems have been observed in various studies. Although remote sensing technology using optical satellites has been widely used in understanding vegetation dynamics in high-latitude areas, there has been limited understanding of various landscape changes at different spatiotemporal scales, their mutual relationships, and overall long-term landscape changes. The objective of this study is to devise a change monitoring strategy that can effectively observe landscape changes at different spatiotemporal scales in the boreal ecosystems from temporally sparse time series remote sensing data. We presented a new post-classification-based change analysis scheme and applied it to time series Landsat data for the central Yakutian study area. Spectral variability between time series data has been a major problem in the analysis of changes that make it difficult to distinguish long- and short-term land cover changes from seasonal growth activities. To address this issue effectively, two ideas in the time series classification, such as the stepwise classification and the lateral stacking strategies were implemented in the classification process. The proposed classification results showed consistently higher overall accuracies of more than 90% obtained in all classes throughout the study period. The temporal classification results revealed the distinct spatial and temporal patterns of the land cover changes in central Yakutia. The spatiotemporal distribution of the short-term class illustrated that the ecosystem disturbance caused by fire could be affected by local thermal and hydrological conditions of the active layer as well as climatic conditions. On the other hand, the long-term class changes revealed land cover trajectories that could not be explained by monotonic increase or decrease. To characterize the long-term land cover change patterns, we applied a piecewise linear model with two line segments to areal class changes. During the former half of the study period, which corresponds to the 2000s, the areal expansion of lakes on the eastern Lena River terrace was the dominant feature of the land cover change. On the other hand, the land cover changes in the latter half of the study period, which corresponds to the 2010s, exhibited that lake area decreased, particularly in the thermokarst lowlands close to the Lena and Aldan rivers. In this area, significant forest decline can also be identified during the 2010s. [ABSTRACT FROM AUTHOR]

Artificial neural networks offer a viable route in assessing and understanding the presence and concentration of heavy metals that can cause dangerous complications in the wider context of water quality prediction for the sustainability of the ecosystem. In order to estimate the heavy metal concentrations in Iznik Lake, which is an important water source for the surrounding communities, characterization data were taken from five different water sources flowing into the lake between 2015 and 2021. These characterization results were evaluated with IBM SPSS Statistics 23 software, with the addition of the lake water quality system. For this purpose, seven distinct physicochemical parameters were measured and monitored in Karasu, Kırandere, Olukdere and Sölöz water sources flowing into the lake, to serve as input data. Concentration levels of 15 distinct heavy metals in Karsak Stream originating from the lake were as the output. Specifically, Sn for Karasu (0.999), Sb for Kırandere (1.000), Cr for Olukdere (1.000) and Pb and Se for Sölöz (0.995) indicate parameter estimation R2 coefficients close to 1.000. Sn stands out as the common heavy metal parameter with best estimation prospects. Given the importance of the independent variable in estimating heavy metal pollution, conductivity, COD, COD and temperature stood out as the most effective parameters for Karasu, Olukdere, Kırandere and Sölöz, respectively. The ANN model emerges as a good prediction tool that can be used effectively in determining the heavy metal pollution in the lake as part of the efforts to protect the water budget of Lake Iznik and to eliminate the existing pollution. [ABSTRACT FROM AUTHOR]

In Indonesia, a country in which 70% of its area is water, people relate easily to both the sea and inland water, such as rivers and lakes. Authors consequently also find inspiration in these bodies of water, expressing their admiration towards the beauty of nature. For example, while they originate from different literary eras, "Danau Toba" (Lake Toba) by Sitor Situmorang, "Sepantun Laut" (Like the Sea) by J.E. Tatengkeng, "Akulah Si Telaga" (I am the Lake) by Sapardi Djoko Damono, "Apa Kata Bintang di Laut" (What the Star Tells the Sea) by Iwan Simatupang, "Kali Martapura" (Martapura River) by Hidjaz Yamani, and "Perempuan Pesisiran" (Women on the Coasts) by Iman Sembada all reflect the dynamic portrayals of water in Indonesian literature, as a charm of nature from each poet's perspective or a framework for criticizing the realities of the lives of the people who live alongside water. This research analyzed these authors' interconnectedness with nature, employing the qualitative descriptive method and using ecocriticism theory, which explores how nature is depicted in the respective poems and connects human relationships to nature. The results showed that the poets easily relate to the river, lake, or sea, and aside from describing the beauty of nature based on fond memories, their poems are used as critiques of the changing relationship between humans and nature, as well as between humans and humans. Their portrayals of nature further reveal the feelings of belonging engendered by water, which they use as criticism for the destruction of nature and societal changes stemming from the need for progress. [ABSTRACT FROM AUTHOR]

Mytilopsis sallei is a small bivalve that has invaded Asian waters, including southeast Asia. This shellfish has become a pest in coastal and estuary waters in Southeast Asia. This study is the first report on the presence and structure of the M. sallei population in Indonesia, precisely in the coastal lakes of Medan City, North Sumatra Province. This research was conducted in Lake Siombak, Medan City, North Sumatra, which is one of the tropical tidal lakes in Indonesia. Mytilopsis sallei shellfish samples were taken for a year from September 2018--August 2019. Mytilopsis sallei were obtained using a Petersen Grab with a mouth opening of 30 x 30 cm. The measurement of M. sallei consisted of the shell length, shell width, shell thickness, and body weight. The analysis of the population structure parameters with ELEFAN I was accommodated in the FiSAT II software. Spatially, M. sallei highest density in Siombak Lake is at station 5 with 24,100 and 23,948 ind.m-2 and the lowest at station 7 is only 967 ind.m-2. Monthly, M. sallei hase the highest density in the dry season (Feb--Jul) compared to the wet season (Aug--Jan). The density of M. sallei in the dry season reaches 1213--13,187 ind.m-2 and in wet seasons reaches 369-3,029 ind.m-2. The Mytilopsis sallei in Siombak Lake has a maximum length of 42.14 mm and the smallest size is 3.00 mm. The growth model of M. sallei in Lake Siombak is Lt = 42.14 (1-e-1.1(t-0.1598)). Mytilopsis sallei recruitment took place in January (fifth month). The instantaneous mortality rate (Z) of M. sallei mussels was 5.32 with an exploitation rate (E) of 0.66. [ABSTRACT FROM AUTHOR]

Large greenhouse gas emissions occur via the release of carbon dioxide (CO2) and methane (CH4) from the surface layer of lakes. Such emissions are modeled from the air-water gas concentration gradient and the gas transfer velocity (k). The links between k and the physical properties of the gas and water have led to the development of methods to convert k between gases through Schmidt number normalization. However, recent observations have found that such normalization of apparent k estimates from field measurements can yield different results for CH4 and CO2. We estimated k for CO2 and CH4 from measurements of concentration gradients and fluxes in four contrasting lakes and found consistently higher (on an average 1.7 times) normalized apparent k values for CO2 than CH4. From these results, we infer that several gas-specific factors, including chemical and biological processes within the water surface microlayer, can influence apparent k estimates. We highlight the importance of accurately measuring relevant air-water gas concentration gradients and considering gas-specific processes when estimating k.

The freshwater pearl mussel, Margaritifera margaritifera is widely considered to be confined to fast-flowing, near-pristine rivers, and is highly endangered throughout its Holartic range. Here we describe a large population of some 150–200,000 individuals of the freshwater pearl mussel living in an oligotrophic Irish lake.Employing underwater photographic techniques and snorkel diving, mussels were found in two separate locations in the lake. In the first location, 200 m from the shore, mussels were found at a maximum density of 43 m−2, in a largely random distribution in the sandy bed substrate of the lake, up to 9.5 m deep. In the second shoreline location, mussels were observed in dense aggregations up to 118 individuals m−2, in sandy pockets in between boulders and bedrock, in waters 1–2 m deep. In both locations, mussels were found associated with macrophytes – the charophyte Nitella sp. in the deeper location and the quillwort Isoetes lacustris in the shallower shoreline location. Juvenile mussels (>1.5 cm length) were observed lying exposed on the sediment surface in the shallow littoral location, indicating that recruitment occurs in this population, although no estimates of juvenile density were obtained.The discovery of a large population of lentic Margaritifera margaritifera has significant implications for the species’ conservation and indicates that there may be substantial lentic populations of the species elsewhere. The environmental envelope of the species is clearly much wider than thought and our discovery challenges assumptions about the fundamental feeding and reproductive biology of this endangered species.

ABSTRACT Background Fish is a possible source of foodborne infections with Salmonella and Escherichia coli. This study was conducted to identify Salmonella and E. coli along the fish value chain in Bahir Dar City, Ethiopia. Methods A cross‐sectional study was undertaken with purposive sampling. A total of 121 specimens comprising fresh fish, retailing fish, filleted and cooked fish, swabs, and water samples were collected. Both culture based and molecular methods were used for detection. Results E. coli isolated from 41 (33.88%) and Salmonella from 6 (4.96%) specimen. The highest E. coli isolation rate was from retailing fish 16 (80%), whereas the highest Salmonella isolation rate from filleted tissue 2 (20%). At restaurants, 12 (30%) samples were positive for E. coli and 3 (7.50%) for Salmonella. All 41 E. coli isolates were resistant to amoxicillin/clavulanate, whereas no resistance was shown for gentamicin and amikacin. Two thirds of Salmonella isolate and 95.12% of E. coli were detected as they develop multidrug resistance. The highest rate of resistance was recorded for ceftazidime against all (n = 6) isolates of Salmonella species. From a total of 10 E. coli isolates tested by PCR, 4 were positive for hemolysin A1 and/or eae virulence genes. Conclusions The study detects the potential biological hazards along the value chain. Hygiene of fish handlers and their working environment and proper fish cooking are highly valuable. One health campaign should be carried out on drug resistance, contamination of the lake, and fish safety.

Ephemeral waters (EW) are sensitive and vulnerable ecosystems that, although the numerous ecosystem services provided, are poorly investigated and properly managed. Diatoms represent an important biological model largely used in aquatic permanent habitats but underused in ephemeral waters. The aim of this review is to address the knowledge gap, examining the current state of knowledge regarding the health of EW, with a focus on diatoms as bioindicators, specially (i) presenting research trends on EW ecosystem types investigated (ii) analysing the methodological approach, (iii) providing the influence of abiotic factors on the diatom assemblages in EW. A bibliographic search yielded a total of 512 papers. After removing duplicate records, 118 were eliminated. The screening of abstracts resulted in the selection of 48 articles on diatoms and EW since 1982. To avoid discrepancy between terminology we decided to classify the EW found in 3 different categories: Intermittent Running Waters (IRW: rivers, streams, creek, springs), Temporary Large Wetlands (TLW: wetlands, lakes, lagoons) and Temporary Small Waters (TSW: ponds, pools, ventaroles, ditches, thermal waters, troughs, pans). Studies are reported in all continents including Antarctic. IRW are the most investigated ecosystem (n = 683), followed by TSW (239) and TLW (96). Furthermore, studies were mainly conducted on sites located below 1000 m a.s.l. of altitude (n = 27). Studies mainly focus on epilithic diatoms (52 %). Electrical conductivity (80 %), pH (77 %) and water temperature (75 %) are the principal physical–chemical parameters considered. Moreover, electrical conductivity, pH, temperature, nitrate and nitrite resulted the best diatom community drivers. Future research is encouraged (1) to achieve a standardised protocol for monitoring EW using diatoms, (2) to focus on conservation projects for high-altitude temporary waters, and (3) to investigate the main driving forces influencing diatom diversity on EW.

Abstract Lakes are hotspots for the biogeochemical processing of carbon, including dissolved organic matter (DOM). A less degradable fraction of DOM, preserved for a long time, can be categorized as recalcitrant DOM (RDOM). Lake RDOM is an important but neglected carbon sink, and its characteristics and transformation processes remain largely unknown.

This study compared two different methods, the satellite altimetry-based and DEM (digital elevation model)-based, for estimating lake water volume changes. We focused on 34 lakes in China as the testing sites to compare the two methods for lake water volume changes from 2005 to 2020. The satellite altimetry-based method used water levels provided by the DAHITI (Database for Hydrological Time Series of Inland Waters) data and surface areas derived from Landsat imagery. The DEM-based method used the SRTM DEM data in combination with Landsat-derived lake extents. Our results showed a high degree of consistency in lake water volume changes estimated between the two methods (R2 > 0.90), but each method has its limitations. In terms of temporal coverage, the satellite altimetry-based method with the DAHITI data is limited by missing water level data in certain periods. The performance of the DEM-based method in extracting lake shore boundaries in regions with flat terrains (slope

Study region: The endorheic Tibetan Plateau (TP). Study focus: Water salinity is sensitive indicator for variations of lake hydrologic and physicochemical characteristics. Due to the heterogeneous influences from geographical and climatic factors, lake water salinity is highly sensitive to environmental diversity and changes. The TP hosts a wide distribution of lakes, the majority of which belong to endorheic drainage type and are saline or salty lakes. However, the harsh environment on the TP poses great challenges for the in–site measurements at large scales, impeding the comprehension of the pattern and variations of lake water salinity across the TP. New hydrological insights for the region: Benefiting extensive field surveys and a meta–analysis, this study establishes machine learning models based on measurements from 100 terminal lakes (>1 km2) and related physical variables. The optimal model (R2 = 0.90, MAE = 8.11 g/L, MAPE = 36.40 %, RMSE = 12.51 g/L, RRMSE = 36.96 g/L) is then applied to predict the water salinity of the other 214 unmeasured terminal lakes. The modeling results reveal a spatial variation pattern of increasing water salinity of these terminal lakes from south to north across the endorheic basins. Further classification of water salinity levels indicated that more than half (213) of the terminal lakes are in an oligosaline state. This study contributes to a spatially–explicit understanding of the distribution variations in water salinity of terminal TP lakes and provides a feasible approach for estimating water salinity of unmeasured lakes at large scales.

In this study, we quantify the differences in gross primary production (GPP), respiration (R), and algal nutrient limitation (nitrogen and phosphorus) in the littoral and pelagic habitats of an oligotrophic Patagonian lake (southern South America). We used submerged high frequency sensors that measure light, temperature, and dissolved oxygen and wind data to calculate GPP and R in both lake habitats. In addition, we carry out nutrient enrichment bioassays with nitrate, ammonium, and phosphate to determine which nutrient(s) limit algal growth in each lake habitat. On average, the productivity rate was 7.2 times higher at the epi-littoral (32.0 to 5.3 mmol O2 m−2 d−1) relative to the epi-pelagic (4.1 to 1.3 mmol O2 m−2 d−1). Algal growth in the littoral habitat was limited by nitrate and ammonium, while the pelagic habitat was co-limited by nitrogen (nitrate or ammonium) and phosphorus. Our work demonstrates that the littoral habitat of a Patagonian oligotrophic lake is more productive than the pelagic habitat and that the nutrients limiting algal growth in both habitats are different. These results underscore habitat variations and their significance in shaping the lake's trophic dynamics for the first time in the southern hemisphere. [ABSTRACT FROM AUTHOR]

Lakes are hotspots for the biogeochemical processing of carbon, including dissolved organic matter (DOM). A less degradable fraction of DOM, preserved for a long time, can be categorized as recalcitrant DOM (RDOM). Lake RDOM is an important but neglected carbon sink, and its characteristics and transformation processes remain largely unknown. Highlights: • Recalcitrant dissolved organic matter (RDOM) is an important but neglected carbon sink in lakes. • The heterogeneity of lake environments determines the diversity and complexity of RDOM. • New techniques allow detailed studies of the mechanisms of RDOM formation and related processes. [ABSTRACT FROM AUTHOR]

Climate change has myriad impacts on ecosystems, but the mechanisms by which it affects individual species can be difficult to pinpoint. One strategy to discover such mechanisms is to identify a specific ecological factor related to survival or reproduction and determine how that factor is affected by climate. Here we used Landsat imagery to calculate water clarity for 127 lakes in northern Wisconsin from 1995 to 2021 and thus investigate the effect of clarity on the body condition of an aquatic visual predator, the common loon (Gavia immer). In addition, we examined rainfall and temperature as potential predictors of water clarity. Body mass tracked July water clarity strongly in loon chicks, which grow chiefly in that month, but weakly in adult males and females. Long‐term mean water clarity was negatively related to chick mass but positively related to adult male mass, suggesting that loons foraging in generally clear lakes enjoy good foraging conditions in the long run but might be sensitive to perturbations in clarity during chick‐rearing. Finally, chick mass was positively related to the density of docks, perhaps because angling removes large fishes and thus boosts the abundance of the small fishes on which chicks depend. Water clarity itself declined strongly from 1995 to 2021, was negatively related to July rainfall, and was positively related to July air temperature. Our findings identified both long‐term and short‐term water clarity as strong predictors of loon foraging efficiency, and suggest that climate change, through water clarity, impacts freshwater ecosystems profoundly. Moreover, our results identified the recent decrease in water clarity as a likely cause of population decline in common loons. [ABSTRACT FROM AUTHOR]

The overall impact of a crude oil spill into a pristine freshwater environment in Canada is largely unknown. To evaluate the impact on the native microbial community, a large-scale in situ model experimental spill was conducted to assess the potential role of the natural community to attenuate hydrocarbons. A small volume of conventional heavy crude oil (CHV) was introduced within contained mesocosm enclosures deployed on the shoreline of a freshwater lake. The oil was left to interact with the shoreline for 72 h and then free-floating oil was recovered using common oil spill response methods (i.e. freshwater flushing and capture on oleophilic absorptive media). Residual polycyclic aromatic hydrocarbon (PAH) concentrations returned to near preoiling concentrations within 2 months, while the microbial community composition across the water, soil, and sediment matrices of the enclosed oligotrophic freshwater ecosystems did not shift significantly over this period. Metagenomic analysis revealed key polycyclic aromatic and alkane degradation mechanisms also did not change in their relative abundance over the monitoring period. These trends suggest that for small spills (<2 l of oil per 15 m2 of surface freshwater), physical oil recovery reduces polycyclic aromatic hydrocarbon concentrations to levels tolerated by the native microbial community. Additionally, the native microbial community present in the monitored pristine freshwater ecosystem possesses the appropriate hydrocarbon degradation mechanisms without prior challenge by hydrocarbon substrates. This study corroborated trends found previously (Kharey et al. 2024) toward freshwater hydrocarbon degradation in an environmentally relevant scale and conditions on the tolerance of residual hydrocarbons in situ. [ABSTRACT FROM AUTHOR]

With the increase in crude oil transport throughout Canada, the potential for spills into freshwater ecosystems has increased and additional research is needed in these sensitive environments. Large enclosures erected in a lake were used as mesocosms for this controlled experimental dilbit (diluted bitumen) spill under ambient environmental conditions. The microbial response to dilbit, the efficacy of standard remediation protocols on different shoreline types commonly found in Canadian freshwater lakes, including a testing of a shoreline washing agent were all evaluated. We found that the native microbial community did not undergo any significant shifts in composition after exposure to dilbit or the ensuing remediation treatments. Regardless of the treatment, sample type (soil, sediment, or water), or type of associated shoreline, the community remained relatively consistent over a 3-month monitoring period. Following this, metagenomic analysis of polycyclic aromatic and alkane hydrocarbon degradation mechanisms also showed that while many key genes identified in PAH and alkane biodegradation were present, their abundance did not change significantly over the course of the experiment. These results showed that the native microbial community present in a pristine freshwater lake has the prerequisite mechanisms for hydrocarbon degradation in place, and combined with standard remediation practices in use in Canada, has the genetic potential and resilience to potentially undertake bioremediation. [ABSTRACT FROM AUTHOR]

This study surveyed freshwater mussels (family Unionidae) in 116 lakes and reservoirs east of the Missouri River in South Dakota, USA, during 2017. Using two-person–hour/site timed searches, evidence of a total of 1789 mussels, including 1053 live mussels, was obtained from 50 waters. Nine species, from two different orders, were found in lakes and reservoirs throughout five of the six major river drainages east of the Missouri River. The native species observed included Giant Floater Pyganodon grandis, Fatmucket Lampsilis siliquoidea, Threeridge Amblema plicata, White Heelsplitter Lasmigona complanata, Wabash Pigtoe Fusconaia flava, Deertoe Truncilla truncata, and Pink Heelsplitter Potamilus alatus. Giant Floater was the most widespread and abundant species observed, representing 63.3% of the live mussels sampled. Two non-native species, Zebra Mussel Dreissena polymorpha and Chinese Basket Clam Corbicula fluminea, were also documented from three water bodies in the lower Missouri River drainage. Overall, mussel abundance was negatively correlated with lake water conductivity and positively correlated with turbidity. No significant correlations were observed between species abundance and water temperature, pH, dissolved oxygen, or substrate particle size. [ABSTRACT FROM AUTHOR]

Quantitative reconstructions of past continental climates are vital for understanding contemporary and past climate change. Branched glycerol dialkyl glycerol tetraethers (brGDGTs) are unique bacterial lipids that have been proposed as universal paleothermometers due to their correlation with temperature in modern settings. Thus, brGDGTs may serve as a crucial paleotemperature proxy for understanding past climate variations and improving regional climate projections, especially in critical but under constrained regions. That said, complications can arise in their application due to varying source contributions (e.g., soils vs. peats vs. lacustrine). As such, this study investigates brGDGT distributions in Chilean lake surface sediments and corresponding watershed soils to determine the source of brGDGTs to lake sediments. Global datasets of brGDGTs in lake sediments and soils were additionally compiled for comparison. Distinct brGDGT distributions in Chilean lakes and soils indicate minimal bias from soil inputs to the lacustrine sediments as well as in situ lacustrine production of brGDGTs, which supports the use of brGDGTs in lake sediments as reliable paleotemperature proxies in the region. The ΣIIIa/ΣIIa ratio, initially promising as a brGDGT source indicator in marine settings, shows global complexities in lacustrine settings, challenging the establishment of universal thresholds for source apportionment. That said, we show that the ratio can be successfully applied in Chilean lake surface sediments. Direct comparisons with watershed soils and further research are crucial for discerning brGDGT sources in lake sediments and improving paleotemperature reconstructions on regional and global scales moving forward. Overall, this study contributes valuable insights into brGDGT variability, essential for accurate paleoreconstructions. [ABSTRACT FROM AUTHOR]

Hydroxylated isoprenoid GDGTs (OH‐GDGTs) have emerged as a novel tool for reconstructing sea surface temperatures. However, when using marine OH‐GDGT calibration in lacustrine settings, it leads to a significant overestimation of temperatures, emphasizing the necessity for a thorough examination of OH‐GDGTs in lakes. Here, we investigated OH‐GDGT distributions in surface sediments from 65 lakes in West China and compiled published Asian lake and global marine OH‐GDGT data sets. Among all GDGT‐based indices, RI‐OH showed the strongest correlation with temperature across Asian lakes. The RI‐OH value was higher in lakes than in marine sediments, likely due to differences in the composition of Group 1.1a thaumarchaeotal species between the two settings. The first RI‐OH temperature calibration for lakes was developed and it addressed the issue of temperature overestimation when applied to both water column and sediment core, highlighting the potential of OH‐GDGTs as a new terrestrial paleothermometer. Plain Language Summary: Reconstruction of past terrestrial temperatures plays a crucial role in understanding modern global warming and projecting future climate patterns, yet reliable terrestrial temperature proxies remain limited. In this study, we present compelling evidence that the ring index of OH‐GDGTs, expressed as RI‐OH, is predominantly influenced by temperature in lacustrine settings, regardless of the wide range of physical and chemical characteristics of the lakes. We developed the first lacustrine RI‐OH‐temperature calibration and successfully applied it to a water column and a sediment core. These findings suggest that RI‐OH can be used as a novel paleothermometer in lacustrine settings. Key Points: OH‐GDGTs were first investigated in lacustrine settings along a wide temperature gradientTemperature was the most important factor affecting OH‐GDGT distributions in lacustrine settingsThe first calibration in lacustrine settings was established and successfully applied to a water column and a sediment core [ABSTRACT FROM AUTHOR]

Clarifying the driving mechanisms of spatial and temporal changes in the regulating ecosystem service value (RESV) is an important part of realizing the goal of sustainable development. Existing studies have focused on specific factors, ignoring the complex interactions between factors and their regional differences. In this regard, the spatial and temporal changes of RESV and its driving mechanisms in the different zones (core area, fringe area, and peripheral area) were explored in the Poyang Lake Area, China. The results showed that RESV spatially showed the distribution characteristics of fringe area > core area > peripheral area, while the lakes influenced the provision of regulating ecosystem services, showing that RESV per unit area was higher in the core area, and gradually declined with the increase of distance from the lakes, presenting the decreasing trend of fringe area > peripheral area. From 2000 to 2020, the study area lost 70.5988 billion CNY for RESV, in which the core area was the most affected. Further analysis of the driving mechanism of RESV in different areas found that there are regional differences in the paths of the driving factors: Population density mainly affects the core area, precipitation mainly affects the fringe area, and GDP per land mainly affects the peripheral area. [ABSTRACT FROM AUTHOR]

In this paper, attention is drawn to the deterioration of Romanian surface water ecosystems due to eutrophication, an important environmental issue both at national and international levels. An inventory of existing studies dealing with the issue of the eutrophication of lakes and reservoirs in Romania is made, aiming to identify the main problems Romania is facing in monitoring, classifying, and managing eutrophic ecosystems. On Web of Science, the keyword "Eutrophication", with "Romania" as country/region, leads to 50 publications, which are analyzed in this review. The number of articles found does not reflect the real environmental issue represented by eutrophic lakes and reservoirs in Romania. At a national level, only 126 lakes and reservoirs have been monitored and assessed between 2018 and 2020, in terms of ecological status/ecological potential. Thus, at a global evaluation, 77% of natural lakes and 33% of artificial ones do not reach the quality objectives. The results of this study showed that the frequency of measurements taken by water quality indicators is not the strongest point of measurement campaigns, as it is not sufficient for the diagnosis of eutrophic lakes, and supplementary measures must be undertaken to better understand and mitigate this phenomenon. [ABSTRACT FROM AUTHOR]

Many macrophyte species exhibit a high degree of plasticity, enabling them to thrive in various aquatic ecosystems. Identifying the growth conditions of individual aquatic plant species during research or specimen collection is not always possible. In many cases, the nature of the planned research does not necessitate recognizing environmental conditions. However, the scope of identifying the habitat parameters of the collections of submerged aquatic plant herbariums provides an opportunity for further research. This paper explores the possibilities of using isotopic signals of plants, supported by spectral analyses of powdered plant materials, to ascertain the environmental conditions from which the samples were collected. The results obtained from the stable carbon and nitrogen isotope compositions (δ13CORG and δ15NORG) and the analysis of spectral spectra via FTIR-ART (Fourier Transform Infrared Spectroscopy with Attenuated Total Reflectance) of plant material (Elodea canadensis Michx. species) collected from various habitat ecosystems, including rivers and both hard- and softwater lakes, exhibited significant distinctions between these habitats. Particularly high values of δ15NORG were recorded in the material from rivers. The stable carbon and nitrogen isotope compositions did not differentiate between the material collected from softwater and hardwater lakes. Nevertheless, when comparing the isotopic findings with the FTIR-ATR spectral analysis focused on identifying characteristic peaks associated with the presence of calcium carbonate, noticeable differences were observed in the presence and intensity of calcium carbonate peaks in the material. These differences were only evident when nondecarbonated plant material from hardwater lakes was used for the FTIR-ATR analysis. To the best of the author's knowledge, the combination of methods applied in this study to identify the origin of E. canadensis from various freshwater environments is the first application of its kind that could enable the rapid identification of plant material origin. Such identification could prove useful in environmental, ecological, and paleoenvironmental research. The increased knowledge of macrophytes' δ13CORG and δ15NORG values might also be essential in further tracking accelerated eutrophication based on aquatic vegetation's isotopic signals. This might be important due to the assumption that the increased rate of eutrophication influences organic matter sedimentation in aquatic ecosystems, especially lakes. [ABSTRACT FROM AUTHOR]

The balance of organic carbon (OC), nitrogen (N) and phosphorus (P) plays a crucial role in determining the processing, retention, and movement of these solutes across the aquatic continuum. Floods and droughts can significantly alter the quantity and ratios of OC:N:P export within inland waters, but how these ratios change, and are coupled within watersheds that integrate rivers and lakes, is not well known. We investigated the stoichiometry and export of dissolved organic carbon (DOC), total N (TN) and total P (TP) in two lake watersheds (10 inflows, 2 outflows) in the southern Boreal Shield over a 37‐year period. Although DOC, TN, and TP concentration behaved similarly, DOC:TN:TP ratios varied seasonally, strongly modulated by stream discharge. DOC:TN, DOC:TP and TN:TP export initially increased rapidly with increasing discharge, peaking at 10%–20% exceedance of the annual discharge for DOC:TP and TN:TP ratios, indicating a rapid depletion of catchment OC sources. Both flood and low flow events resulted in lower DOC:TN and lower DOC:TP export—thereby increasing the relative contributions of stream TN and TP. Consequently, elevated annual discharge coupled with infrequent but high floods and periods of low flow events increased the contributions of TN and TP relative to DOC. Overall, the lakes retained DOC, while increasing TN relative to TP. Nonetheless, the flow regime played a role in modulating nutrient retention in the lakes, likely due to changes in residence time, and the interplay of physical, photochemical, and biological degradation processes. Plain Language Summary: How floods and droughts affect the relationship between organic carbon (OC) and nitrogen and phosphorus in terms of their alteration, removal from, or storage within, river and lake environments is not well known. We investigated two lake watersheds with their 10 inflowing and 2 outflowing streams over 37 years. The ratios of the OC to nutrients changed seasonally and were affected by intra‐annual stream flow variability. Slightly higher than average flows (10%–20% higher) initially increased the amount of OC that was exported from the watershed compared to nitrogen and phosphorus, but this export was notably lower during low flows and floods. This highlights the effects of extremely high and low flows, resulting in increased nitrogen and phosphorus in the streams. Internal processing by lakes generally decreased OC, while adding nitrogen relative to phosphorus, however the lakes retained less OC and phosphorus when the number of annual floods increased. This is important as the frequency and intensity of floods and droughts are predicted to increase in the future which may change how nutrients are altered and removed along the inland‐marine aquatic continuum. These potential changes could impact aquatic ecosystems and the ecosystem services they provide. Key Points: Our long‐term data set provides a robust perspective on patterns in watershed‐scale stoichiometry and organic carbon and nutrient transportFlow regimes (floods and periods of low flow) are critical in shaping nutrient and organic carbon stoichiometry in aquatic ecosystemsLakes play an important role in nutrient and organic carbon removal within a stream network [ABSTRACT FROM AUTHOR]

Invasive species threaten native biodiversity, potentially leading to a decline in endemic aquatic species. Thus, understanding their physiological responses and evaluating ecosystem impacts is crucial. The study investigates adaptive responses to oxidative stress in the invasive Sinanodonta woodiana in Lake Candia (northwest Italy). This approach represents a novel perspective in environmental monitoring, utilizing invasive species to gain insights into ecosystem health and potential ecological threats. The investigation delved into oxidative stress biomarkers, including superoxide dismutase, catalase, glutathione S-transferase, glyoxalase I, glyoxalase II, and lactate dehydrogenase, in mussel tissues (gills and digestive gland). Concurrently, environmental factors such as temperature, dissolved oxygen, pH, and conductivity were measured at four stations in Lake Candia during the summer. Environmental factors exhibited homogeneity across selected stations, with positive correlations observed only for temperature and conductivity with catalase and glyoxalase I. A distinct pattern of oxidative stress response was consistently observed in both mussel tissues throughout the sampling period across all monitoring stations, with more pronounced alterations observed in one specific station. This observation aligns with IBRv2 scores, indicating the station's highest impact. Gills exhibited a transient and severe oxidative stress response, while heightened antioxidant defenses in digestive glands suggested the adaptive ability of Chinese pond mussels to environmental disturbances. Proactive inclusion of invasive species in biomonitoring programs reduces reliance on native populations, enhancing strategies for controlling non-native mussels in protected areas like Lake Candia.

In this paper, attention is drawn to the deterioration of Romanian surface water ecosystems due to eutrophication, an important environmental issue both at national and international levels. An inventory of existing studies dealing with the issue of the eutrophication of lakes and reservoirs in Romania is made, aiming to identify the main problems Romania is facing in monitoring, classifying, and managing eutrophic ecosystems. On Web of Science, the keyword “Eutrophication”, with “Romania” as country/region, leads to 50 publications, which are analyzed in this review. The number of articles found does not reflect the real environmental issue represented by eutrophic lakes and reservoirs in Romania. At a national level, only 126 lakes and reservoirs have been monitored and assessed between 2018 and 2020, in terms of ecological status/ecological potential. Thus, at a global evaluation, 77% of natural lakes and 33% of artificial ones do not reach the quality objectives. The results of this study showed that the frequency of measurements taken by water quality indicators is not the strongest point of measurement campaigns, as it is not sufficient for the diagnosis of eutrophic lakes, and supplementary measures must be undertaken to better understand and mitigate this phenomenon.

The Odlezelské jezero National Nature Monument was established to protect Lake Odlezy, the youngest natural lake in the Czech Republic, situated near Odlezly in western Bohemia. This lake was created in 1872 by a landslide that blocked the stream. The aquatic molluscs of this unique site were studied in 2013 and 2023. Altogether, 16 species (8 gastropods and 8 bivalves) were found at 13 sites. Molluscan communities in the streams, springs and small wetlands surrounding the lake are very poor, consisting of 1–4 species. In contrast, 13 species were found in the lake. Particularly notable are the probably extensive populations of mussels Anodonta cygnea and Unio tumidus, which are rare in western Bohemia.

The PCLake model has not previously been used for tropical reservoirs. This study attempted to apply the PCLake model to predict the chlorophyll a concentrations (Chl-a) in a tropical reservoir in Thailand. Sensitivity analyses were performed for the constants affecting the prediction of Chl-a in the phytoplankton module. The model calibration was performed by using the adjusted value of the most sensitive constant with the observed data from July to December 2020. The effects of the initial trophic state of the reservoir on the simulated Chl-a were evaluated. The results showed that Chl-a were sensitive to six constants. Among these constants, the value of the specific extinction of detritus (cExtSpDet) was adjusted using the calculated values from the typical limnological parameters of the studied reservoir. Statistical analyses of the results of calibration and the subsequent validation with the observed data from February to September 2022 were listed as follows: NSE=0.55 and 0.37, RSR=0.67 and 0.79, and PBIAS=27% and 9%, respectively. The initial trophic state of the reservoir had no influence on the long-term prediction of Chl-a. This preliminary effort indicates that the PCLake model can be used to predict Chl-a, which is representative of algal biomass in tropical reservoirs and is essential to water quality models, without complex modifications.

Many macrophyte species exhibit a high degree of plasticity, enabling them to thrive in various aquatic ecosystems. Identifying the growth conditions of individual aquatic plant species during research or specimen collection is not always possible. In many cases, the nature of the planned research does not necessitate recognizing environmental conditions. However, the scope of identifying the habitat parameters of the collections of submerged aquatic plant herbariums provides an opportunity for further research. This paper explores the possibilities of using isotopic signals of plants, supported by spectral analyses of powdered plant materials, to ascertain the environmental conditions from which the samples were collected. The results obtained from the stable carbon and nitrogen isotope compositions (δ13CORG and δ15NORG) and the analysis of spectral spectra via FTIR-ART (Fourier Transform Infrared Spectroscopy with Attenuated Total Reflectance) of plant material (Elodea canadensis Michx. species) collected from various habitat ecosystems, including rivers and both hard- and softwater lakes, exhibited significant distinctions between these habitats. Particularly high values of δ15NORG were recorded in the material from rivers. The stable carbon and nitrogen isotope compositions did not differentiate between the material collected from softwater and hardwater lakes. Nevertheless, when comparing the isotopic findings with the FTIR-ATR spectral analysis focused on identifying characteristic peaks associated with the presence of calcium carbonate, noticeable differences were observed in the presence and intensity of calcium carbonate peaks in the material. These differences were only evident when nondecarbonated plant material from hardwater lakes was used for the FTIR-ATR analysis. To the best of the author’s knowledge, the combination of methods applied in this study to identify the origin of E. canadensis from various freshwater environments is the first application of its kind that could enable the rapid identification of plant material origin. Such identification could prove useful in environmental, ecological, and paleoenvironmental research. The increased knowledge of macrophytes’ δ13CORG and δ15NORG values might also be essential in further tracking accelerated eutrophication based on aquatic vegetation’s isotopic signals. This might be important due to the assumption that the increased rate of eutrophication influences organic matter sedimentation in aquatic ecosystems, especially lakes.

This study examines the dynamics of limnological parameters of a South American lake located in southern Chile with the objective of predicting chlorophyll-a levels, which are a key indicator of algal biomass and water quality, by integrating combined remote sensing and machine learning techniques. Employing four advanced machine learning models (recurrent neural network (RNNs), long short-term memory (LSTM), recurrent gate unit (GRU), and temporal convolutional network (TCNs)), the research focuses on the estimation of chlorophyll-a concentrations at three sampling stations within Lake Ranco. The data span from 1987 to 2020 and are used in three different cases: using only in situ data (Case 1), using in situ and meteorological data (Case 2), using in situ, and meteorological and satellite data from Landsat and Sentinel missions (Case 3). In all cases, each machine learning model shows robust performance, with promising results in predicting chlorophyll-a concentrations. Among these models, LSTM stands out as the most effective, with the best metrics in the estimation, the best performance was Case 1, with R2 = 0.89, an RSME of 0.32 µg/L, an MAE 1.25 µg/L and an MSE 0.25 (µg/L)2, consistently outperforming the others according to the static metrics used for validation. This finding underscores the effectiveness of LSTM in capturing the complex temporal relationships inherent in the dataset. However, increasing the dataset in Case 3 shows a better performance of TCNs (R2 = 0.96; MSE = 0.33 (µg/L)2; RMSE = 0.13 µg/L; and MAE = 0.06 µg/L). The successful application of machine learning algorithms emphasizes their potential to elucidate the dynamics of algal biomass in Lake Ranco, located in the southern region of Chile. These results not only contribute to a deeper understanding of the lake ecosystem but also highlight the utility of advanced computational techniques in environmental research and management.

In this study, we employ in situ, meteorological, and remote sensing data to estimate chlorophyll-a concentration at different depths in a South American freshwater ecosystem, focusing specifically on a lake in southern Chile known as Lake Maihue. For our analysis, we explored four different scenarios using three deep learning and traditional statistical models. These scenarios involved using field data (Scenario 1), meteorological variables (Scenario 2), and satellite data (Scenarios 3.1 and 3.2) to predict chlorophyll-a levels in Lake Maihue at three different depths (0, 15, and 30 m). Our choice of models included SARIMAX, DGLM, and LSTM, all of which showed promising statistical performance in predicting chlorophyll-a concentrations in this lake. Validation metrics for these models indicated their effectiveness in predicting chlorophyll levels, which serve as valuable indicators of the presence of algae in the water body. The coefficient of determination values ranged from 0.30 to 0.98, with the DGLM model showing the most favorable statistics in all scenarios tested. It is worth noting that the LSTM model yielded comparatively lower metrics, mainly due to the limitations of the available training data. The models employed, which use traditional statistical and machine learning models and meteorological and remote sensing data, have great potential for application in lakes in Chile and the rest of the world with similar characteristics. In addition, these results constitute a fundamental resource for decision-makers involved in the protection and conservation of water resource quality. [ABSTRACT FROM AUTHOR]