Limnological Review

17 pages, 2250 KB

Open AccessArticle

Surface Water Treatment with Carica papaya-Based Coagulants: A Natural and Sustainable Solution

by Guillermo Díaz-Martínez, Ricardo Navarro-Amador, José Luis Sánchez-Salas and Deborah Xanat Flores-Cervantes

Limnol. Rev. 2025, 25(4), 47; https://doi.org/10.3390/limnolrev25040047 - 4 Oct 2025

Abstract

Access to clean water remains a global challenge, particularly in areas where populations rely on surface water. These water sources must be treated. Coagulation with chemicals causes environmental problems and adverse effects on human health. Natural coagulants obtained from papaya (Carica papaya [...] Read more.

Access to clean water remains a global challenge, particularly in areas where populations rely on surface water. These water sources must be treated. Coagulation with chemicals causes environmental problems and adverse effects on human health. Natural coagulants obtained from papaya (Carica papaya) waste are presented as an alternative that is safe for human health, non-polluting, and biodegradable. The effectiveness of these natural coagulants is compared to that of aluminum sulfate using jar tests and synthetic and natural surface water, with statistical tools to model treatment processes. All coagulants have competitive results, reaching turbidity remotion levels above 90%. However, in equivalent tested ranges, natural coagulants require lower dosages and perform better with high initial water turbidity due to their polymeric bridging mechanisms and adsorption processes through the action of their functional groups, as detected by FTIR analysis. Additional testing with contaminated water from the Valsequillo dam confirms the use of these coagulants to treat water, with papaya seed coagulant yielding the best results and requiring lower doses, making it a competitive alternative. It can be concluded that papaya-based coagulants obtained from waste can be used as an eco-friendly alternative to aluminum sulfate in physicochemical treatments to purify surface water for human consumption. Full article

13 pages, 3029 KB

Open AccessArticle

Microplastics in Sediments of the Littoral Zone and Beach of Lake Baikal

by Anastasia Solodkova, Sofya Biritskaya, Artem Guliguev, Diana Rechile, Yana Ermolaeva, Arina Lavnikova, Dmitry Golubets, Alyona Slepchenko, Ivan Kodatenko, Alexander Bashkircev, Natalia Kulbachnaya, Darya Kondratieva, Anna Solomka, Dmitry Karnaukhov and Eugene Silow

Limnol. Rev. 2025, 25(4), 46; https://doi.org/10.3390/limnolrev25040046 - 24 Sep 2025

Abstract

Most studies on microplastic pollution in aquatic ecosystems have focused on the quantitative and qualitative assessment of particles in surface waters. However, the highest concentrations and accumulation of microplastic particles are observed in bottom sediments. The aim of this study was to determine [...] Read more.

Most studies on microplastic pollution in aquatic ecosystems have focused on the quantitative and qualitative assessment of particles in surface waters. However, the highest concentrations and accumulation of microplastic particles are observed in bottom sediments. The aim of this study was to determine the concentrations of microplastic particles of different morphology in sediments in the beach and littoral zones of Lake Baikal. This study is the first in relation to Lake Baikal to focus specifically on the analysis of microplastic particles in bottom sediments. The results of the study showed that the registered values of concentration of microplastic particles do not exceed the average values for lakes around the world. The predominant type of particles in both the littoral zone and the beach is microplastic fibers. An exception is observed only for one of the locations. This exception is related to the permanent mooring of vessels in this place. Analysis of the types of artificial polymers showed that the microplastic fibers were represented by polyester, and the fragments were represented by alkyd resin (66%), polyvinyl alcohol (32%) and polyvinyl chloride (2%). Shown for the first time in this study, the presence of large numbers of microplastic particles with rare types of artificial polymers suggests that these particles may be under-reported in other studies. The underestimation of particles may be due either to the selection of sampling locations located far from heavily contaminated areas, or to the fragility of these polymers. Although the harm of these types of polymers has not yet been confirmed, the large number of these particles in local areas of lakes should be taken into account. This is due to the large number of organisms, which is usually characteristic of littoral areas, including Lake Baikal, with its diversity of fauna and flora. Full article

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13 pages, 2353 KB

Open AccessArticle

Phytoplankton Sampling: When the Method Shapes the Message

by Diego Frau

Limnol. Rev. 2025, 25(3), 45; https://doi.org/10.3390/limnolrev25030045 - 18 Sep 2025

Abstract

Different sampling techniques were evaluated to assess potential differences in species richness and the abundances of phytoplankton across several lowland aquatic environments. Five sampling methods were used, including a bucket, narrow- and wide-mouth bottles, a 10 µm plankton net, and a vertical Van [...] Read more.

Different sampling techniques were evaluated to assess potential differences in species richness and the abundances of phytoplankton across several lowland aquatic environments. Five sampling methods were used, including a bucket, narrow- and wide-mouth bottles, a 10 µm plankton net, and a vertical Van Dorn bottle. These sampling methods were applied in subtropical streams, shallow lakes, and rivers. The results were compared using a two-way ANOVA to evaluate differences in total density by considering the morphological group and major phytoplankton phyla. Similarity analyses (SIMPER) and a permutational multivariate analysis of variance (PERMANOVA) were performed to compare the relative abundances of the species. The results showed, in general (except with Cyanophyta, Chrysophyta, and colonies—coenobia), significant differences in the effect of the sampling method but without interaction with the kind of environment. Particularly, the plankton net always reported lower density estimations, with the bucket having the highest values and the wide–narrow bottle methods having similar values. SIMPER and PERMANOVA indicated differences, especially with the plankton net and the other methods, particularly the bucket. These findings suggest that the sampling method can influence species counts and registration in subtropical water ecosystems, highlighting the need for standardized procedures across countries to obtain comparable and reliable results. Full article

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25 pages, 6705 KB

Open AccessArticle

Machine Learning-Enhanced Monitoring and Assessment of Urban Drinking Water Quality in North Bhubaneswar, Odisha, India

by Kshyana Prava Samal, Rakesh Ranjan Thakur, Alok Kumar Panda, Debabrata Nandi, Alok Kumar Pati, Kumarjeeb Pegu and Bojan Đurin

Limnol. Rev. 2025, 25(3), 44; https://doi.org/10.3390/limnolrev25030044 - 12 Sep 2025

Abstract

Access to clean drinking water is crucial for any region’s social and economic growth. However, rapid urbanization and industrialization have significantly deteriorated water quality, posing severe pollution threats from domestic, agricultural, and industrial sources. This study presents an innovative framework for assessing water [...] Read more.

Access to clean drinking water is crucial for any region’s social and economic growth. However, rapid urbanization and industrialization have significantly deteriorated water quality, posing severe pollution threats from domestic, agricultural, and industrial sources. This study presents an innovative framework for assessing water quality in North Bhubaneswar, integrating the Water Quality Index (WQI) with statistical analysis, geospatial technologies, and machine learning models. The WQI, calculated using the Weighted Arithmetic Index method, provides a single composite value representing overall water quality based on several key physicochemical parameters. To evaluate potable water quality across 21 wards in the northern zone, several key parameters were monitored, including pH, electrical conductivity (EC), dissolved oxygen (DO), hardness, chloride, total dissolved solids (TDSs), and biochemical oxygen demand (BOD). The Weighted Arithmetic WQI method was employed to determine overall water quality, which ranged from excellent to good. Furthermore, Principal Component Analysis (PCA) revealed a strong positive correlation (r > 0.6) between pH, conductivity, hardness, and alkalinity. To enhance the accuracy and reliability of water quality assessment, multiple machine learning models Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Naïve Bayes (NB) were applied to classify water quality based on these parameters. Among them, the Decision Tree (DT) and Random Forest (RF) models demonstrated the highest precision (91.8% and 92.7%, respectively) and overall accuracy (91.7%), making them the most effective in predicting water quality and integrating WQI, machine learning, and statistics to analyze water quality. The study emphasizes the importance of continuous water quality monitoring and offers data-driven recommendations to ensure sustainable access to clean drinking water in North Bhubaneswar. Full article

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20 pages, 1629 KB

Open AccessArticle

Estimating Lake–Groundwater Exchange Using Hourly Water Level Fluctuations in Central Florida

by Cortney Cameron

Limnol. Rev. 2025, 25(3), 43; https://doi.org/10.3390/limnolrev25030043 - 11 Sep 2025

Abstract

With mounting anthropogenic pressures on groundwater supplies, practical methods for quantifying lake–groundwater exchange are critical for water resources management. This is particularly important in karst environments where surface–groundwater connectivity is often high. The White method uses nighttime water level fluctuations to estimate groundwater [...] Read more.

With mounting anthropogenic pressures on groundwater supplies, practical methods for quantifying lake–groundwater exchange are critical for water resources management. This is particularly important in karst environments where surface–groundwater connectivity is often high. The White method uses nighttime water level fluctuations to estimate groundwater flux. While the White method has been applied to flooded wetlands, published lake applications are rare. This study evaluated a modified White method for estimating leakage at 28 karst lakes in Florida. The method was modified to include evaporation correction, with both nighttime and all-day approaches evaluated. Using the nighttime correction approach, average annual groundwater flux (leakage) ranged from −2.4 to +1.9 m/y, with a mean of −0.5 m/y (negative indicates lake outflow). Without nighttime evaporation correction, leakage estimates would be erroneous by an average of −0.7 m/y. The results showed no significant difference from 138 leakage values compiled from previous studies that used diverse methods. The modified White method requires special attention to evaporation, filtering criteria, and hydrogeologic context. Overall, the method provides a useful complementary approach to other methods for estimating long-term annual lake–groundwater exchange with comparatively minimal data requirements. Full article

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27 pages, 1684 KB

Open AccessReview

Transforming Waste into Value: The Role of Physicochemical Treatments in Circular Water Management

by Jesús Barrera-Rojas, Carlos Vladimir Muro-Medina, Hasbleidy Palacios-Hinestroza, Valentín Flores-Payán, Daryl Rafael Osuna-Laveaga and Belkis Sulbarán-Rangel

Limnol. Rev. 2025, 25(3), 42; https://doi.org/10.3390/limnolrev25030042 - 11 Sep 2025

Cited by 1

Abstract

The growing global population and increasing water demand have intensified the urgency for efficient wastewater treatment strategies to address environmental pollution and water scarcity. Physicochemical treatment technologies remain among the most widely implemented solutions due to their high removal efficiency, operational simplicity, and [...] Read more.

The growing global population and increasing water demand have intensified the urgency for efficient wastewater treatment strategies to address environmental pollution and water scarcity. Physicochemical treatment technologies remain among the most widely implemented solutions due to their high removal efficiency, operational simplicity, and relatively low cost. These processes effectively target a broad spectrum of contaminants—including suspended solids, heavy metals, recalcitrant organic compounds, and high salinity—through unit operations such as coagulation, flocculation, adsorption, and filtration. Nevertheless, they often generate concentrated waste streams that present significant disposal and environmental challenges. Applying these technologies within a circular economy framework enables wastewater reuse, resource recovery, and a reduced environmental impact. Circular strategies enable the recovery and reuse of water, energy, and materials, converting waste into valuable resources. Treated water can be safely reused, while by-products such as biogas and nutrients (e.g., phosphorus, nitrogen, and organic carbon) can be recovered and reintegrated into agricultural and industrial processes. Furthermore, advanced methods such as membrane separation and electrochemical treatments allow for the selective recovery of high-value metals. This review analyzes key physicochemical technologies for wastewater treatment and evaluates their integration into circular economy models, with a focus on waste valorization, resource recovery, and environmental impact reduction. By adopting circular approaches, wastewater treatment systems can enhance sustainability, improve economic performance, and contribute to achieving the global water and sanitation target. Full article

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32 pages, 2297 KB

Open AccessReview

Status and Trends of Saline Lake Research in British Columbia, Canada

by Markus Heinrichs

Limnol. Rev. 2025, 25(3), 41; https://doi.org/10.3390/limnolrev25030041 - 30 Aug 2025

Abstract

Saline lakes are distinct, understudied aquatic ecosystems, particularly those that are hydrologically isolated from marine environments. In British Columbia (BC), Canada, the scope and trajectory of scientific research on these systems remain largely undocumented. To address this gap, a meta-analysis was conducted of [...] Read more.

Saline lakes are distinct, understudied aquatic ecosystems, particularly those that are hydrologically isolated from marine environments. In British Columbia (BC), Canada, the scope and trajectory of scientific research on these systems remain largely undocumented. To address this gap, a meta-analysis was conducted of peer-reviewed scholarly articles focusing on both coastal and inland saline lakes to identify the primary research themes and assess temporal trends in scientific inquiry. The coastal meromictic lakes Sakinaw and Powell were included because of their retention of relict marine waters. Thematic areas of research spanned a diverse array of disciplines, including paleolimnology, neolimnology, halophilic insect and plant ecology, microbial diversity, and functional genomics, as well as astrobiology as analog environments for extraterrestrial life. Temporal analysis revealed variable research intensity across disciplines: the number of paleolimnological training sets has declined, whereas microbial genomics and astrobiological analog investigations have increased. Among inland saline lakes, Mahoney Lake, Pavilion Lake, and various saline lakes within the Cariboo region emerged as key sites of ecological and geochemical interest. This synthesis highlights both the ecological significance and scientific potential of BC’s saline lakes while underscoring the need for more systematic and interdisciplinary research to better understand their roles in broader environmental and evolutionary contexts. Full article

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1 pages, 132 KB

Open AccessCorrection

Correction: Kirvel et al. Evaluation of Efficiency of a Finned Corrugation Basin in Inclined Basin-Type Solar Stills in Regulating the Water Supply of the CaspiCement Plant. Limnol. Rev. 2024, 24, 150–163

by Ivan Kirvel, Ainur Zhidebayeva, Lyailim Taizhanova, Ainazhan Aitimova, Samal Syrlybekkyzy, Akmaral Serikbayeva, Kamshat Jumasheva and Symbat Koibakova

Limnol. Rev. 2025, 25(3), 40; https://doi.org/10.3390/limnolrev25030040 - 29 Aug 2025

Abstract

The following reference was retracted, and therefore its citation was removed from this manuscript [...] Full article

22 pages, 4857 KB

Open AccessArticle

Evaluating an Ensemble-Based Machine Learning Approach for Groundwater Dynamics by Downscaling GRACE Data

by Zahra Ghaffari, Abdel Rahman Awawdeh, Greg Easson, Lance D. Yarbrough and Lucas James Heintzman

Limnol. Rev. 2025, 25(3), 39; https://doi.org/10.3390/limnolrev25030039 - 21 Aug 2025

Abstract

Groundwater depletion poses a critical challenge to global water security, threatening ecosystems, agriculture, and sustainable development. The Mississippi Delta, a region heavily reliant on groundwater for agriculture, has experienced significant groundwater level declines due to intensive irrigation. Traditional in situ monitoring methods, while [...] Read more.

Groundwater depletion poses a critical challenge to global water security, threatening ecosystems, agriculture, and sustainable development. The Mississippi Delta, a region heavily reliant on groundwater for agriculture, has experienced significant groundwater level declines due to intensive irrigation. Traditional in situ monitoring methods, while valuable, lack the spatial coverage necessary to capture regional groundwater dynamics comprehensively. This study addresses these limitations by leveraging downscaled Gravity Recovery and Climate Experiment (GRACE) data to estimate groundwater levels using random forest modeling (RFM). We applied a machine-learning approach, utilizing the “Forest-based and Boosted Classification and Regression” tool in ArcGIS Pro, (ESRI, Redlands, CA) to predict groundwater levels for April and October over a 10-year period. The model was trained and validated with well-water level records from over 400 monitoring wells, incorporating input variables such as NDVI, temperature, precipitation, and NLDAS data. Cross-validation results demonstrate the model’s high accuracy, with R² values confirming its robustness and reliability. The outputs reveal significant groundwater depletion in the central Mississippi Delta, with the lowest water level observed in the eastern Sunflower and western Leflore Counties. Notably, April 2014 recorded a minimum water level of 18.6 m, while October 2018 showed the lowest post-irrigation water level at 54.9 m. By integrating satellite data with machine learning, this research provides a framework for addressing regional water management challenges and advancing sustainable practices in water-stressed agricultural regions. Full article

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20 pages, 1004 KB

Open AccessArticle

Macroinvertebrate Communities of Non-Glacial Alpine Streams in Western North America’s Coast Mountains

by Sabine Sherrin, Yulia Shcherbakova and John S. Richardson

Limnol. Rev. 2025, 25(3), 38; https://doi.org/10.3390/limnolrev25030038 - 18 Aug 2025

Abstract

Alpine streams are particularly vulnerable to climate change and in many parts of the world are poorly studied, which is true of western North America. We sampled the invertebrate communities and measured the physico-chemical parameters of nine small streams in a single alpine [...] Read more.

Alpine streams are particularly vulnerable to climate change and in many parts of the world are poorly studied, which is true of western North America. We sampled the invertebrate communities and measured the physico-chemical parameters of nine small streams in a single alpine meadow. There was a wide variation in the physico-chemical variables in this single, small catchment. Three variables were selected based on their high loadings from principal component analysis, and these were slope, width and pH. There were relations between densities of some of the benthic organisms and the three main environmental gradients. We found large variation in densities (595 to 7340 individuals m⁻²) and diversity of benthic communities across a small gradient of physico-chemical variation in these nine streams in a single alpine meadow. High beta diversity (most > 0.8) between streams indicated substantial differences in community structure and diversity in a small area of about 1 km. These results suggest strong environmental filters on communities in these alpine stream systems and the potential for high regional biodiversity far beyond what individual streams support. Full article

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24 pages, 6460 KB

Open AccessArticle

Methodologies and Criteria for Defining Areas for Forest Restoration Aiming at Water Production and Security

by Terencio Rebello de Aguiar Junior, Lafayette Dantas da Luz, Reginaldo da Silva Rangel Neto, Diogo Caribé de Sousa and Eduardo Mariano-Neto

Limnol. Rev. 2025, 25(3), 37; https://doi.org/10.3390/limnolrev25030037 - 13 Aug 2025

Abstract

This study presents a methodological framework for prioritizing areas for forest restoration with the primary objective of enhancing water provision. A multi-scale approach was employed, starting with macro-scale criteria at the river basin level, followed by more localized landscape and hydro-ecological assessments. This [...] Read more.

This study presents a methodological framework for prioritizing areas for forest restoration with the primary objective of enhancing water provision. A multi-scale approach was employed, starting with macro-scale criteria at the river basin level, followed by more localized landscape and hydro-ecological assessments. This two-stage process facilitated strategic planning for interventions aimed at restoring forest cover in permanent preservation areas (PPAs) along watercourses and springs. The methodology was applied to the Joanes and Jacuípe Rivers Permanent Protection Areas Forest Rehabilitation Project in the Salvador Metropolitan Region, Bahia. The project’s primary goal is to improve water security by restoring native vegetation across 100 springs and 100 hectares of riparian zones, which are critical to the water supply system for the Salvador Metropolitan Region. The prioritization process integrated hydrological, ecological, and socio-environmental criteria, ensuring that restoration efforts not only enhance water production but also provide long-term ecological and social benefits. Full article

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20 pages, 27453 KB

Open AccessArticle

Natural and Anthropogenic Influence on the Physicochemical Characteristics of Spring Water: The Case Study of Medvednica Mountain (Central Croatia)

by Ivan Martinić and Ivan Čanjevac

Limnol. Rev. 2025, 25(3), 36; https://doi.org/10.3390/limnolrev25030036 - 1 Aug 2025

Abstract

During the period from 2020 to 2024, 900 springs were mapped on the southern slopes of Medvednica Mountain Nature Park. Physicochemical parameters (temperature, pH, and electrical conductivity) were measured at 701 of these springs using a portable multimeter, and results were analyzed in [...] Read more.

During the period from 2020 to 2024, 900 springs were mapped on the southern slopes of Medvednica Mountain Nature Park. Physicochemical parameters (temperature, pH, and electrical conductivity) were measured at 701 of these springs using a portable multimeter, and results were analyzed in relation to local lithology and human activities. This research provides the first results of this kind in this study area, aiming to expand the knowledge on local springs and to support the future protection and management of spring ecosystems. Springs on the Medvednica mountain showed substantial variation in measured parameters. The temperature ranged from 3.4 to 18.9 °C, reflecting local hydrological conditions, aquifer characteristics, and seasonal variability. Electrical conductivity (EC) ranged between 41 μS/cm and 2062 μS/cm, determined by both hydrogeological settings and anthropogenic impacts such as winter road salting. The pH values showed moderate variability, remaining mostly within neutral levels. These results emphasize the importance of continued monitoring and further research of Medvednica springs, in order to highlight their importance and to preserve their ecological and hydrological roles. Full article

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15 pages, 3267 KB

Open AccessArticle

Monitoring and Analyzing Aquatic Vegetation Using Sentinel-2 Imagery Time Series: A Case Study in Chimaditida Shallow Lake in Greece

by Maria Kofidou and Vasilios Ampas

Limnol. Rev. 2025, 25(3), 35; https://doi.org/10.3390/limnolrev25030035 - 1 Aug 2025

Abstract

Aquatic vegetation plays a crucial role in freshwater ecosystems by providing habitats, regulating water quality, and supporting biodiversity. This study aims to monitor and analyze the dynamics of aquatic vegetation in Chimaditida Shallow Lake, Greece, using Sentinel-2 satellite imagery, with validation from field [...] Read more.

Aquatic vegetation plays a crucial role in freshwater ecosystems by providing habitats, regulating water quality, and supporting biodiversity. This study aims to monitor and analyze the dynamics of aquatic vegetation in Chimaditida Shallow Lake, Greece, using Sentinel-2 satellite imagery, with validation from field measurements. Data processing was performed using Google Earth Engine and QGIS. The study focuses on discriminating and mapping two classes of aquatic surface conditions: areas covered with Floating and Emergent Aquatic Vegetation and open water, covering all seasons from 1 March 2024, to 28 February 2025. Spectral bands such as B04 (red), B08 (near infrared), B03 (green), and B11 (shortwave infrared) were used, along with indices like the Modified Normalized Difference Water Index and Normalized Difference Vegetation Index. The classification was enhanced using Otsu’s thresholding technique to distinguish accurately between Floating and Emergent Aquatic Vegetation and open water. Seasonal fluctuations were observed, with significant peaks in vegetation growth during the summer and autumn months, including a peak coverage of 2.08 km² on 9 September 2024 and a low of 0.00068 km² on 28 December 2024. These variations correspond to the seasonal growth patterns of Floating and Emergent Aquatic Vegetation, driven by temperature and nutrient availability. The study achieved a high overall classification accuracy of 89.31%, with producer accuracy for Floating and Emergent Aquatic Vegetation at 97.42% and user accuracy at 95.38%. Validation with Unmanned Aerial Vehicle-based aerial surveys showed a strong correlation (R² = 0.88) between satellite-derived and field data, underscoring the reliability of Sentinel-2 for aquatic vegetation monitoring. Findings highlight the potential of satellite-based remote sensing to monitor vegetation health and dynamics, offering valuable insights for the management and conservation of freshwater ecosystems. The results are particularly useful for governmental authorities and natural park administrations, enabling near-real-time monitoring to mitigate the impacts of overgrowth on water quality, biodiversity, and ecosystem services. This methodology provides a cost-effective alternative for long-term environmental monitoring, especially in regions where traditional methods are impractical or costly. Full article

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13 pages, 1482 KB

Open AccessArticle

Effect of Surrounding Detritus on Phragmites australis Litter Decomposition: Evidence from Laboratory Aquatic Microcosms

by Franca Sangiorgio, Daniela Santagata, Fabio Vignes, Maurizio Pinna and Alberto Basset

Limnol. Rev. 2025, 25(3), 34; https://doi.org/10.3390/limnolrev25030034 - 1 Aug 2025

Abstract

The availability of detritus is a key factor influencing aquatic biota and can significantly affect decomposition processes. In this study, we investigated how varying quantities of surrounding detritus impact leaf litter decay rates. It was tested in flowing and still-water microcosms to highlight [...] Read more.

The availability of detritus is a key factor influencing aquatic biota and can significantly affect decomposition processes. In this study, we investigated how varying quantities of surrounding detritus impact leaf litter decay rates. It was tested in flowing and still-water microcosms to highlight context-dependent effects of surrounding detritus on leaf litter decomposition. To isolate the effect of detritus amount, experiments were conducted in laboratory microcosms simulating lotic and lentic ecosystems, each containing leaf fragments for decomposition assessments. Four detritus quantities were tested, with invertebrates either allowed or restricted from moving among detritus patches. Leaf decomposition rates were influenced by the amount of surrounding detritus, with slower decay observed at higher detritus conditions, regardless of invertebrate mobility. Detritivore distribution responded to both detritus quantity and oxygen availability, showing a preference for high detritus conditions. Additionally, detritus quantity affected microbial activity with a quadratic response, as indicated by leaf respiration rates. Overall, our findings indicate that the amount of surrounding detritus modulates leaf litter decomposition independently of invertebrate density, by influencing oxygen dynamics and, consequently, the activity of biological decomposers. Full article

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22 pages, 5044 KB

Open AccessReview

Paleolimnological Approaches to Track Anthropogenic Eutrophication in Lacustrine Systems Across the American Continent: A Review

by Cinthya Soledad Manjarrez-Rangel, Silvana Raquel Halac, Luciana Del Valle Mengo, Eduardo Luis Piovano and Gabriela Ana Zanor

Limnol. Rev. 2025, 25(3), 33; https://doi.org/10.3390/limnolrev25030033 - 17 Jul 2025

Abstract

Eutrophication has intensified in lacustrine systems across the American continent, which has been primarily driven by human activities such as intensive agriculture, wastewater discharge, and land-use change. This phenomenon adversely affects water quality, biodiversity, and ecosystem functioning. However, studies addressing the historical evolution [...] Read more.

Eutrophication has intensified in lacustrine systems across the American continent, which has been primarily driven by human activities such as intensive agriculture, wastewater discharge, and land-use change. This phenomenon adversely affects water quality, biodiversity, and ecosystem functioning. However, studies addressing the historical evolution of trophic states in lakes and reservoirs remain limited—particularly in tropical and subtropical regions. In this context, sedimentary records serve as invaluable archives for reconstructing the environmental history of water bodies. Paleolimnological approaches enable the development of robust chronologies to further analyze physical, geochemical, and biological proxies to infer long-term changes in primary productivity and trophic status. This review synthesizes the main methodologies used in paleolimnological research focused on trophic state reconstruction with particular attention to the utility of proxies such as fossil pigments, diatoms, chironomids, and elemental geochemistry. It further underscores the need to broaden spatial research coverage, fostering interdisciplinary integration and the use of emerging tools such as sedimentary DNA among others. High-resolution temporal records are critical for disentangling natural variability from anthropogenically induced changes, providing essential evidence to inform science-based lake management and restoration strategies under anthropogenic and climate pressures. Full article

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14 pages, 1209 KB

Open AccessArticle

Generation of Nitrous Oxide by Aerobic Denitrifiers Isolated from an Urban Wetland in Bogotá, Colombia

by Maribeb Castro-González and Verónica Molina

Limnol. Rev. 2025, 25(3), 32; https://doi.org/10.3390/limnolrev25030032 - 15 Jul 2025

Abstract

In this study, we evaluated the nitrous oxide production potential of denitrifying bacterial strains isolated from sediments of the urban wetland Santa María del Lago under anaerobic and aerobic conditions to determine their potential role in mitigating anthropogenic N₂O emissions, which [...] Read more.

In this study, we evaluated the nitrous oxide production potential of denitrifying bacterial strains isolated from sediments of the urban wetland Santa María del Lago under anaerobic and aerobic conditions to determine their potential role in mitigating anthropogenic N₂O emissions, which have increased by approximately 40% since 1980, and if these emissions could be related to the absence of the nitrous oxide reductase gene (nosZ). The results demonstrated that denitrifying bacteria belonging to the genus Bacillus were able to generate nitrous oxide in high concentrations under both aerobic (up to 83 nM/h) and anaerobic (up to 3865.5 nM/h) conditions in cultures with optimal concentrations of nitrate and carbon. The amplification of the nosZ gene as marker of denitrifying microorganisms showed that only 50% of strains possess this gene, and its presence did not correlate with nitrous oxide reduction under anoxic conditions. Interestingly, one strain was able to reduce nitrous oxide in the presence of air, which is promising for its potential use in aerobic bioremediation systems that require microorganisms with a high affinity for this greenhouse gas to reduce emissions into the atmosphere. Full article

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11 pages, 1969 KB

Open AccessArticle

Two New Strains of Microcystis Cyanobacteria from Lake Baikal, Russia: Ecology and Toxigenic Potential

by Ekaterina Sorokovikova, Irina Tikhonova, Galina Fedorova, Nadezhda Chebunina, Anton Kuzmin, Maria Suslova, Yanzhima Naidanova, Sergey Potapov, Andrey Krasnopeev, Anna Gladkikh and Olga Belykh

Limnol. Rev. 2025, 25(3), 31; https://doi.org/10.3390/limnolrev25030031 - 10 Jul 2025

Abstract

Microcystis, a potentially toxigenic cyanobacterium known to form extensive blooms in eutrophic lakes globally, was investigated in the cold oligotrophic Lake Baikal. We report the isolation of two Microcystis strains, Microcystis aeruginosa and M. novacekii, and document the presence of the [...] Read more.

Microcystis, a potentially toxigenic cyanobacterium known to form extensive blooms in eutrophic lakes globally, was investigated in the cold oligotrophic Lake Baikal. We report the isolation of two Microcystis strains, Microcystis aeruginosa and M. novacekii, and document the presence of the latter species in Lake Baikal for the first time. In M. aeruginosa strain BN23, we detected the microcystin synthetase gene mcyE. Liquid chromatography-mass spectrometry revealed the presence of two microcystin variants in BN23, with microcystin-LR, a highly potent toxin, being the dominant form. The concentration of MC-LR reached 540 µg/g dry weight. In contrast, M. novacekii strain BT23 lacked both microcystin synthesis genes and detectable toxins. The habitat waters were characterized as oligotrophic with minor elements of mesotrophy, exhibiting low phytoplankton biomass dominated by the chrysophyte Dinobryon cylindricum (76–77% of biomass), with cyanobacteria contributing 8–10%. The contribution of Microcystis spp. to the total phytoplankton biomass could not be quantified as they were exclusively found in net samples. The water temperature at both sampling stations was ~19 °C, which is considerably lower than optimal for Microcystis spp. and potentially conducive to enhanced microcystin production in toxigenic genotypes. Full article

(This article belongs to the Special Issue Trends in the Trophic State of Freshwater Ecosystems)

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15 pages, 528 KB

Open AccessReview

Water Monitoring Practices 2.0—Water Fleas as Key Species in Ecotoxicology and Risk Assessment

by Anne Leung, Emma Rowan, Flavia Melati Chiappara and Konstantinos Grintzalis

Limnol. Rev. 2025, 25(3), 30; https://doi.org/10.3390/limnolrev25030030 - 2 Jul 2025

Abstract

Humanity faces the great challenges arising from pollution and climate change which evidently lead to the irreversible effects observed on the planet. It is now more important than ever to monitor and safeguard the ecosystem as it has been highlighted by governments and [...] Read more.

Humanity faces the great challenges arising from pollution and climate change which evidently lead to the irreversible effects observed on the planet. It is now more important than ever to monitor and safeguard the ecosystem as it has been highlighted by governments and scientists. Conventional approaches for water pollution rely on the detection of chemicals in the environment. However, these descriptive observations when compared against water quality standards used as metrics for pollution are unable to predict pollution early or capture the extent of its impact. This weakness is reflected in the legislation and the thresholds for emerging pollutants such as pharmaceuticals and nanomaterials. To bridge the gap and to understand the underlying mechanisms for toxicity, research in the field of molecular ecotoxicology shifts more and more towards the integration of model systems, in silico approaches and molecular information as endpoints. Focusing on the freshwater ecosystem, daphnids are key species employed in risk assessment which are characterised as highly responsive to pollutants and physical stressors. The translation of molecular information describing the physiology of these organisms provides novel and sensitive metrics for pollution assessment. Full article

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23 pages, 7993 KB

Open AccessArticle

A New Machine Learning Algorithm to Simulate the Outlet Flow in a Reservoir, Based on a Water Balance Model

by Marco Antonio Cordero Mancilla, Wilmer Moncada and Vinie Lee Silva Alvarado

Limnol. Rev. 2025, 25(3), 29; https://doi.org/10.3390/limnolrev25030029 - 1 Jul 2025

Abstract

Predicting water losses and final storage in reservoirs has become increasingly relevant in the efficient control and optimization of water provided to agriculture, livestock, industry, and domestic consumption, aiming to mitigate the risks associated with flash floods and water crises. This research aims [...] Read more.

Predicting water losses and final storage in reservoirs has become increasingly relevant in the efficient control and optimization of water provided to agriculture, livestock, industry, and domestic consumption, aiming to mitigate the risks associated with flash floods and water crises. This research aims to develop a new Machine Learning (ML) algorithm based on a water balance model to simulate the outflow in the Cuchoquesera reservoir in the Ayacucho region. The method uses TensorFlow (TF), a powerful interface for graphing and time series forecasting, for data analysis of hydrometeorological parameters (HMP), inflow (QE_obs), and outflow (QS_obs) of the reservoir. The ML water balance model is fed, trained, and calibrated with daily HMP, QE_obs, and QS_obs data from the Sunilla station. The results provide monthly forecasts of the simulated outflow (QS_sim), which are validated with QS_obs values, with significant validation indicators: NSE (0.87), NSE-Ln (0.83), Pearson (0.94), R² (0.87), RMSE (0.24), Bias (0.99), RVB (0.01), NPE (0.01), and PBIAS (0.14), with QS_obs being slightly higher than QS_sim. Therefore, it is important to highlight that water losses due to evaporation and infiltration increased significantly between 2019 and 2023. Full article

(This article belongs to the Special Issue Hot Spots and Topics in Limnology)

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